Grace Mutati¹, Willard Mumbi^1,5, Chileshe Mboni², Chansa Kayula², Simon Chisi³, Felida Mwacalimba¹, Jessie Nyalazi¹, Patricia Mulenga², Elias Mashilipa⁴, Josias Ndhlovu³, Foster Maambo⁵, Timothy Kangwa¹, Moono Hampango⁶, Kangwa I. M. Muma^1,7 .

¹ University Teaching Hospitals Eye Hospital, Lusaka, Zambia

²Eye Department, Kitwe Teaching Hospital, Kitwe, Zambia

³Eye Department, Chipata Central Hospital, Chipata, Zambia

⁴ Eye Unit, Solwezi General Hospital, Solwezi, Zambia

⁵Eye Unit, Kabwe General Hospital, Kabwe, Zambia

⁶Eye Department, Levy Mwanawasa University Teaching Hospital, Lusaka, Zambia

⁷Ministry of Health, Ndeke House, Lusaka, Zambia

Download Pdf

Abstract

Aim: To determine the prevalence and causes of blindness and visual impairment in Muchinga Province of Zambia using the RAAB methodology.

Method: Ninety (90) clusters of 40 participants aged 50 years and older were randomly selected. Consenting subjects underwent enumeration to establish a demographic profile and thereafter a clinical eye examination. Visual acuity (VA) was measured with a Tumbling ‘E’ chart. Participants having a VA worse than 6/18 were retested with a pinhole. If no improvement in VA occurred, subjects underwent clinical examination, including a dilated fundus examination where necessary, to determine the cause of visual impairment.

Results: A total number of 3,600 persons aged 50 years and above were sampled; among these 3,502 (97.3%) were examined. The age and sex-adjusted prevalence of bilateral blindness (presenting VA < 3/60) was 4.1% (95% Confidence Interval [CI], 3.4-4.9%), and age and sex-adjusted prevalence of bilateral severe VI (VA of <6/60-3/60) was 3.1% (95% CI, 2.4-3.8%). Avoidable causes of blindness such as cataract, glaucoma and non-trachoma corneal scarring were responsible for 89.8% of bilateral blindness and 86.1% of bilateral severe VI. Cataract was the major cause of blindness (53.0%); similarly, it was a major cause of severe VI (63.5%). The cataract surgical coverage in blind people adjusted for age and sex was low at 36.8% with significant gender difference of 45.8% for males and 27.6% for females. The main barrier for cataract surgery was inaccessibility of the service (49.1%); this was followed by lack of awareness of the available service (32.7%).

Conclusion: The prevalence of blindness and VI in persons aged 50 years and above was higher than estimated by WHO for Zambia. The majority of the causes were avoidable, with cataract accounting for 53% of all cases of blindness. The data suggests that expansion of eye care programmes to address avoidable causes of blindness is necessary in this area of Zambia.

Key words: Rapid Assessment of Avoidable Blindness, Cataract, Blindness, Visual Impairment, Prevalence

Introduction

Globally, more than 82% of all blindness occurs in people ≥ 50 years old [1]. In Africa, the prevalence is 7.3 blind people per million population [1]. These estimates are based on the World Health Organization (WHO) definition of blindness as presenting visual acuity (VA) less than 3/60 in the better eye and visual impairment as VA less than 6/18 but at least 3/60 in the better eye [2]. The study area is in the Africa-E WHO sub-region [3]. Resnikoff et al. [4] posit an expected Africa-E sub-regional prevalence of bilateral blindness in individuals ≥ 50 years old of 9%. The implementation of the ‘VISION 2020: Right to Sight’ campaign has created global awareness of the causes of avoidable blindness and the need to provide evidence for eye health needs and the impact of interventions to guide future eye health strategies. This awareness has led to an expansion of epidemiological investigations as baseline data became more important. However, according to the International Centre for Eye Health, ‘Blindness surveys are usually lengthy, costly and complicated exercises, requiring expert assistance from epidemiologists or statisticians to produce reports [5]. It is for this reason that surveys have been undertaken in only a few countries and with only a few repeat surveys to determine the effect of the intervention programmes implemented. Comprehensive blindness surveys are therefore often not feasible for planning and monitoring VISION 2020 programmes. Affordable and faster methodologies are required.

The rapid assessment of avoidable blindness (RAAB) methodology has addressed this need. The RAAB study methodology elicits information on the magnitude and causes of blindness and vision impairment via reduced vision screening and ocular health screening of adults ≥ 50 years old. In addition, this methodology provides information on the output and quality ≥ 50 years old. In addition, this methodology provides information on the output and quality of eye care services, barriers to service, cataract surgical coverage and other indicators of eye care services in the study area. Numerous RAAB studies have been conducted in many countries around the world [6,7,8,9,10,11,12,13]. The RAAB survey provides a needs assessment in the region under investigation so that a focused district plan can be developed or adjusted accordingly.

Muchinga Province

Muchinga Province is located in the north-east of the country and borders with Tanzania in the north, Malawi in the east, and Eastern and Central Provinces in the south. The province is located on both sides of the Muchinga mountains (Muchinga Escarpment), which serve as a divide between the drainage basins of the Zambezi River (Indian Ocean) and the Congo River (Atlantic Ocean), making it geographically a hard-to-reach area. It is one of the most sparsely populated provinces in the country, with a population density of 8.1 persons per square kilometre and a population of 1,052,996 [14]. The main rivers of the province are the Luangwa River, a major left tributary of the Zambezi, the Chambeshi River, and a tributary of Lake Bangweulu in the drainage basin of the Congo. The northern part of the country receives the highest rainfall, with an annual average ranging from 1,100 mm to over 1,400 mm. The main economic activity for the province is agriculture, with livestock farming and the growing of cereals, cassava and beans at subsistence level [14].

Figure 1: Map of Zambia showing the RAAB districts

Methods

Sample selection

The RAAB study area Muchinga Province. The total population in the area was 1,052,996, with a mixture of urban, peri-urban and semi-rural areas [14]. The estimated total population of the region surveyed was 322,601, with the population for each district as follows: Chama 103,894, Chinsali 86,723, Isoka 72,189 and Shiwang’andu 59,795 [15]. As in the rest of Zambia, the delivery of eye care follows the district health model. Current eye health care infrastructure in the study area is found in a district hospital. Human resources for eye health in the area are ophthalmic nurses and clinical officers. Primary community health workers in the area refer to community health centres which also refer to the district hospitals. Sightsavers, a non-government organisation (NGO), supports eye health services in the province through the seeing is believing programme.  

A sample size adequate to demonstrate a prevalence of blindness of 4.0% ±0.8% with 95% confidence was calculated. This was increased for non-participation (10%) and design effect (1.5) resulting in a size of 3,563 or 90 clusters of 40 participants each (3,600 in total). The team decided on clusters of size 40 rather than 50 due to the long distances between homes in the villages and the difficulties envisaged in moving between the homes and enrolling enough participants each day.

Enumeration and recruitment of study participants

A list of all the villages and their populations in the respective wards was collected from the various districts and sent to the trainers who then used this to select the clusters. The sampling procedure embedded in the RAAB software uses probability proportional to the size of the population methodology to randomly select villages automatically. The households within clusters were selected through compact segment sampling which involved choosing a start point within the village and moving from house to house, enumerating all eligible residents (whether at home at the time of visit or absent) until 40 eligible participants are enrolled. If any eligible participants were away from home at the time of the visit, the survey team would return to the house at the end of the day to meet with them. If they were still absent, a neighbour or friend would be asked for details on the individual’s visual status.

In order to facilitate the survey team’s work, the selected village was visited a day or two beforehand by the cluster informer. They worked with village leaders to produce a sketch map of the ward showing major landmarks and the approximate distribution of households in the village. The cluster informer requested that local leaders inform the residents of the visit of the survey team and requested that residents of 50 years and above stay around their homes on the day of the survey. The village leader also appointed a guide to work with the survey team on the day of their visit to introduce them to residents.

Large villages were split into segments where each segment would include approximately 40 people aged 50 years and above. One of the segments was chosen at random in collaboration with the village leaders by drawing lots and all households within the segment were included in the sample sequentially, until 40 people aged 50 years and above were identified, examined, and their data entered on the data collection programme on the smartphone. If the segment had fewer than 40 people aged 50 years and above, then another segment was chosen at random and sampling continued. The sampling started at the edge of the village and all the households were sampled sequentially until 40 people aged 50 years and above had been examined.

If the village had fewer than 40 people aged 50 years and above, there was no need for segmentation and all the people of that age group were examined. In such cases, the cluster informer would inform the next village leader of the possibility of the RAAB team including his area in the survey.

Ethical approval

Ethical approval for this study was granted by the University of Zambia Research and Ethics Committee and cleared by the Ministry of Health. Permission to conduct the study was obtained from the Provincial Medical Office and the respective district medical offices.

When the team reached the area informed, (verbal) consent was obtained from the participants after providing information on the purpose, procedure and the possible benefits of the study.

Participants were informed that participation was voluntary, and that all discussions and data collected from the study would be kept confidential, and that findings will be anonymously reported. Appropriate counselling, treatment or referral for eye problems was provided to study participants. All subjects in the study were examined after informed consent and information documents were signed. All individuals requiring further investigation for refractive correction, treatment of ocular disease or further investigative procedures were referred to the most appropriate and accessible eye care facilities. Findings from the research were disseminated to the community in a feedback session to the community and its leaders at the end of the study.

Training

The study was preceded by a training session and pilot study involving the enumerators and clinical team to ensure the ability of all individuals in the study to carry out their respective roles. Kappa values were used as a measure of inter-observer agreement between the clinical research team and a ‘gold standard’ team, with 0.6 being an acceptable standard. All clinicians satisfied this criterion. There were five survey teams, each consisting of an ophthalmologist and an ophthalmic nurse or ophthalmic clinical officer, as well as a driver and a cluster informer who would work independently of the survey teams to prepare the clusters for their visit

Clinical examination

The standardised RAAB protocol was used in the clinical examination and involved the assessment of visual acuity using a tumbling E optotype of 6/60 and 6/18 sizes. Subjects who failed testing on the 6/60 optotype target were retested with a pinhole occluder. Blindness was classified as VA < 3/60 in the better eye with available correction; severe visual impairment as VA between ≥ 3/60 and 6/60 in the better eye with available correction; and moderate visual impairment as VA between ≥ 6/60 and 6/18 in the better eye with available correction. The VA examination was followed by an examination of the crystalline lens and the posterior segment with a direct ophthalmoscope. Subjects presenting with VA < 6/18 and with no improvement with pinhole were dilated using 0.5% tropicamide solution, and a dilated ophthalmoscopy was performed to determine any posterior segment cause for vision impairment. All measurements were taken in full daylight with available correction.

If the VA was <6/18 in either eye, then pinhole vision was also measured. If the vision improved to >6/18, then the condition was entered into the data as refractive error.

The participant was then moved to a dark location – this was usually in their homes, where the lens was assessed for cataract formation. If there was no cataract and the vision was still <6/18, the participants’ pupils were dilated with a short-acting mydriatic for direct fundoscopy. The fundus was then examined and the cause for vision loss recorded on the RAAB application.

A questionnaire on the barriers to cataract surgery and surgical success was administered to subjects presenting with cataracts or who had undergone cataract surgery respectively.

Statistical analysis

The specific RAAB software package developed for the survey (Version 4.02) was used for data entry and standardised data analysis.4 Data were captured by double entry (to ensure reliability of data entry) and reports were generated daily to ensure consistency within the data capture process. Automated analyses produced reports on the unadjusted prevalence of visual impairment, causes of visual impairment, age- and gender-adjusted prevalence, and cataract surgical coverage. Multiple logistic regression analysis was conducted to determine associations between gender, age and education levels and various degrees of vision loss.

The survey was carried out over 6 weeks from October to November 2009.

Results

Demographics of the sample

The total number of people examined was 3,600 giving a response rate of 97.3%, of which 80 individuals (2.2%) were unavailable, 11 (0.3%) refused and 7 (0.2%) were not capable of taking part in the survey.  Almost half of the people surveyed belonged to the 50-59 years age group.  The age and gender composition of examined participants in relation to the population in the survey area is summarised in Table 1.

Table 1: Age and gender composition of examined participants in relation to the

population in the survey area.

Age Distribution	Male	Female	Total
	Sample	Population	Sample	Population	Sample	Population
50-59 years	47.3%	44.9%	41.2%	43.3%	44.0%	44.1%
60-69 years	22.7%	28.6%	26.9%	33.1%	25.0%	30.9%
70-79 years	19.5%	18.8%	21.8%	17.3%	20.8%	18.0%
80-89 years	10.4%	7.7%	10.1%	6.3%	10.3%	7.0%

Females constituted 54.9% (1,921) of selected participants compared to 51.9% in the population.

Bilateral vision loss in the sample

Of 166 people in the sample, 4.7% (95%CI4.0-5.5%), were found to be bilaterally blind (defined as VA worse than 3/60 in the better eye with available correction – see Table 2). The prevalence was similar between males and females, 4.6% and 4.8% respectively.

The prevalence of bilateral blindness, SVI and VI is summarised in Table 2.

Table 2: Distribution by presenting visual acuity (with available correction) in the better eye (before pinhole examination).

VA with available correction	Male (n = 463)	Female (n = 1079)	Total (N = 1542)
n	Prevalence	95% CI	n	Prevalence	95% CI	n	Prevalence	95% CI
VA < 3/60, bilateral blindness	73	4.6	3.5-5.7	93	4.8	3.9-5.8	166	4.7	4.0-5.5
VA < 6/60 and ≥ 3/60, bilateral SVI	53	3.4	2.4-4.3	62	3.2	2.4-4.0	115	3.3	2.6-4.0
VA < 6/18 and ≥ 6/60, bilateral MVI	160	10.1	8.5-11.7	194	10.3	8.6-11.8	357	10.2	8.8-11.5

VA, visual acuity; SVI, severe visual impairment; MVI, moderate visual impairment.

Adjusting for differences in age and sex between the sample and survey area produced a prevalence of blindness of 4.1% (95%CI3.3-4.9% – see Table 3). Extrapolating this to the total population of the survey areas means that an estimated 2,315 people were blind, of whom 1,179 were females (50.1% female).

Table 3: Extrapolated prevalence of blindness, severe (SVI), and moderate (MVI) visual impairment – bilateral presenting VA

	Males	Females	Total
	N	% (95%CI)	N	% (95%CI)	N	% (95%CI)
Blindness	1,147	4.2 (3.1-5.4)	1,179	4.0 (3.1-5.0)	2,315	4.1 (3.4-4.9)
Severe VI	895	3.3 (2.4-4.2)	837	2.9 (2.0-3.7)	1,729	3.1 (2.4-3.8)
Moderate VI	2,678	9.9 (8.3-11.5)	2,733	9.4 (7.7-11.0)	5,414	9.6 (8.3-11.0)

Sample prevalence of severe VI (presenting VA<6/60-3/60 in better eye) was 3.3% (95% CI2.6-4.0%), and 3.1% (95%CI 2.4-3.8%) after adjustment for age and sex. Adjusted prevalence of SVI was 3.3% among males and 2.9% among females, which means an estimated 895 males and 837 females with bilateral severe VI in the survey area. Sample prevalence of moderate VI (presenting VA<6/18-6/60 in better eye) was 10.2% (95%CI 8.8-11.5%) and 9.6% (95%CI 8.3-11.0%) after adjustment for age and sex. Adjusted prevalence of MVI was 9.9% among males and 9.4% among females which means an estimated 2,678 males and 2,733 females in the survey area (50.5% female).

Causes of vision loss in the sample

Cataract was the primary cause of bilateral blindness (53.0%), and bilateral severe VI (63.5%), and a major contributor to moderate VI (36.4%). Of the remainder of blindness, glaucoma accounted for 14.5%, non-trachomatous cornea opacity was 10.2%, other posterior segment disease 7.2%, trachoma corneal opacity 6.0%, phthisis 3.0%, other globe/CNS abnormalities 3.0% and cataract surgical complications 3.0%. (Table 4).

Table 4: Causes of visual loss (with available correction) in the study sample.

Cause of vision loss	Bilateral blindness	Bilateral severe visual impairment	Bilateral moderate visual impairment
VA < 3/60 (%)	VA < 6/60 – ≥ 3/60 (%)	VA < 6/18 – ≥ 6/60 (%)
Refractive error		12	48
Cataract	53	63	36
Cataract surgical complications	3	1	1
Corneal scar	10	–	2
Glaucoma	15	3	2
Diabetic retinopathy	–	–	1
Other posterior segment disease	7	10	6
Age related macular degeneration (ARMD)	–	4	2
Trachoma cornea opacity	6	4	1
Phthisis	3	–	–
Other globe problems / CNS	3	–	1
Total	100	100	100

Note: Causes of visual loss (with available correction) in the study sample were determined by vision loss in the better eye. Total avoidable vision loss was a combination of total curable and total preventable vision loss.

VA, visual acuity.

Cataract blindness, surgical outcomes and cataract surgical coverage

After adjustment for age and sex, it was estimated that 3.6% (95%CI 2.9-4.3%) of eyes (approx. 4,059) were blind with a cataract (cataract may not be the major cause of blindness), table 5. Nine hundred and eighty-three (983) people (1.7%, 95%CI 1.2-2.3) in the survey area were estimated to be bilaterally blind with cataract and 2,092 (3.7%, 95%CI 3.0-4.4) were estimated to have one cataract blind eye, table 5. No major differences were observed between males and females.

Table 5: Age and sex-adjusted results for cataract and blindness, severe (SVI), and moderate (MVI) visual impairment – bilateral best corrected VA

Feature	Males	Females	Total
	N	% (95%CI)	N	% (95%CI)	N	% (95%CI)
Cataract and Blindness – VA<3/60 with best correction
Bilateral cataract	425	1.6 (0.8-2.3)	558	1.9 (1.2-2.6)	983	1.7 (1.2-2.3)
Unilateral cataract	1,069	3.9 (3.0-4.9)	1,023	3.5 (2.4-4.6)	2,092	3.7 (3.0-4.4)
Cataract eyes	1,919	3.5 (2.7 – 4.4)	2,140	3.7 (2.8-4.5)	4,059	3.6 (2.9-4.3)
Cataract and Severe VI – VA<6/60-3/60 with best correction
Bilateral cataract	289	1.1 (0.7-1.4)	341	1.2 (0.8-1.5)	630	1.1 (0.9-1.4)
Unilateral cataract	472	1.7 (1.0-2.5)	359	1.2 (0.5-2.0)	831	1.5 (0.9-2.0)
Cataract eyes	862	1.6 (1.1-2.1)	881	1.5 (1.0-2.1)	1,743	1.5 (1.1-2.0)
Cataract and Moderate VI – VA<6/18-6/60 with best correction
Bilateral cataract	612	2.3 (1.6-2.9)	963	3.3 (2.6-4.0)	1,575	2.8 (2.3-3.3)
Unilateral cataract	722	2.7 (1.4-3.9)	565	1.9 (1.0-2.9)	1,287	2.3 (1.5-3.1)
Cataract eyes	1,679	3.1 (2.2-4.0)	2,070	3.5 (2.7-4.4)	3,749	3.3 (2.6-4.0)

Cataract surgical coverage (CSC) was reflected in the number of aphakic/pseudophakic people divided by the number who had operable cataract (i.e. the number of aphakic/pseudophakic plus the number needing surgery). Ninety-two (92) eyes (1.3%, 95%CI 1.0-1.6) examined in the survey were found to be aphakic or pseudoaphakic. Age and sex adjustment imply this extrapolated to 1,360 eyes in the survey population (1.2%, 95%CI 0.9-1.5%). Following adjustment for age and sex, 37% of people with VA<3/60 who required surgery were found to have received it. Males were more likely to have received surgery than females (45.8% vs 27.6%).

Twenty eight percent (28%) of people with VA<6/60 who required surgery were found to have received it, with males more likely than female (36.7% vs 19.1%). 17.7% of people with VA<6/18 who required surgery were found to have received it with males more likely to have received it than female (24.3% vs 12.2%).

Table 6: Age and sex-adjusted results for cataract surgical coverage

	Males	Females	Total
Cataract surgical coverage (eyes) – percentage
VA<3/60	32.6	16.8	25.1
VA<6/60	25.0	12.5	19.0
VA<6/18	17.2	7.8	12.5
Cataract surgical coverage (persons) – percentage
VA<3/60	45.8	27.6	36.8
VA<6/60	36.7	19.1	28.0
VA<6/18	24.3	12.2	17.7

The CSC was 36.8% at visual acuity < 3/60 level; 28.8% at visual acuity < 6/60 level, and 17.7% at visual acuity < 6/18 level. Overall, CSC was greater amongst males than females.

Cataract surgical outcomes with available correction was relatively poor (Table 7). Exactly half of the eyes (50.0%) had a good outcome (can see 6/18), 17.0% had borderline outcome (can see 6/60) and 33.0% had poor outcome (cannot see 6/60). Among eyes operated on in the past three years, 58.1% of outcomes were good and 29.0% were poor. With best correction. the proportion of good outcomes could rise to 63.8%, borderline outcomes to 9.6% and poor outcomes would be 26.6%.  Over half (61.3%) of the poor outcomes were conducted in the government hospital. Of the 94 eyes that received cataract surgery, all except three had an intraocular lens (IOL) inserted.

Table 7: VA in operated eyes obtained after cataract surgery

	No IOL Eyes (n=3)	IOL Eyes (n=85)	All Eyes (n=94)
Available correction
Good: Can see 6/18	0 (0.0)	47 (51.6%)	47 (50.0%)
Borderline: Can see 6/60	1 (33.3%)	15 (16.5%)	16 (17.0%)
Poor: Cannot see 6/60	2 (66.7%)	29 (31.9%)	31 (33.0%)
Best correction
Good: Can see 6/18	1 (33.3%)	59 (64.8%)	60 (63.8%)
Borderline: Can see 6/60	0 (0.0)	9 (9.9%)	9 (9.6%)
Poor: Cannot see 6/60	2 (66.7%)	23 (25.3%)	25 (26.6%)

Discussion

This study was conducted to create baseline information on the prevalence and causes of blindness in Muchinga region.

These districts were selected because they were regions with inadequate eye health service before interventions were implemented. The response rate was 97.2% which can be considered very high. Although the cluster informers working with local leaders knew the village boundaries and residents well, the response rate could have probably been higher had the survey not been conducted during harvest time. Normally because of the mountainous terrain, villagers would camp at the farms away from the village until harvesting was complete. A proportion (0.3%) refused examination and the scope of the study did not provide an explanation for the reasons for refusal of the clinical examination.

The survey found a high prevalence of blindness (4.1%, 95%CI 3.4-4.9) compared to that obtained in Southern Zambia (2.3%) [16]. Results from other RAAB surveys done in Malawi [17], Rwanda [18] and Tanzania [19] ranged from 1.8-3.3% (unadjusted) which was lower than what was found in the study area. The prevalence of blindness in Muchinga was possibly higher than that of Southern Zambia due to a number of reasons: Southern Zambia’s demographic is an urban rural setting with the presence of active eye health services. The extrapolated number of blind people in the four districts of Muchinga was 2,315. The proportion of blind people was higher for females than males, a finding common to other RAAB studies in the region, except in a RAAB conducted in South Malawi where the prevalence of blindness was higher in males than females.

The main causes of blindness in Muchinga were cataract, glaucoma and non-trachomatous cornea opacities. Similar causes have been observed in other RAAB surveys in the southern province of Zambia and Malawi. This result is consistent with the current trend that cataract is the most common cause of blindness worldwide. Our study found that unoperated cataract is also the major cause of severe VI and that uncorrected refractive error is the primary cause of moderate VI. The finding of refractive error as the most common cause of VI could be due to the myopic shift induced by age-related nuclear sclerosis as reported by researchers for RAAB in Kwazulu Natal [20]. In this study, avoidable causes were responsible for 89.8% of blindness. The finding that most causes of blindness are avoidable justifies the initiative to address blindness in this area. The prevention of blindness initiative in this area should include the correction of refractive errors, which contributed to 48% of moderate VI.

The age and sex-adjusted cataract surgical coverage was low (37%) compared to studies from Malawi (44.6% unadjusted) [17], Kenya (78%) [21], Tanzania (68.9%) [19] and Rwanda (47%) [18]. Muchinga province has always depended on sporadic eye camps conducted by ophthalmologists from outside the province, with the support of cooperating partners. The low CSC could be due to the absence of a dedicated ophthalmic unit headed by an ophthalmologist. The finding of a low cataract surgical coverage for females (25.5%) has also been noted in other areas of Sub Saharan Africa [22].

WHO recommended that the grades of outcome for cataract surgery with an IOL are: good outcome VA >6/18 at 90%, borderline VA >6/60 at less than 5% and poor outcome of VA<6/60 at less than 5%. The high proportion of poor outcomes after cataract surgery in this survey could be due to a combination of factors, for instance there is no ophthalmologist to follow up patients and therefore manage any complications. In this study, the majority were attributed to poor patient selection and surgical complications. Most surgeries, although conducted in a hospital environment, have a setting like that of an eye camp where the screening of patients preoperatively is inadequate; for instance, conditions like glaucoma may be missed as most patients present with dense cataract that obscures fundus view, and may not have had any examination before the development of cataract. Secondly, biometry is not conducted pre-operatively and patients are offered a standard lens which may not be appropriate for the patient.

In our study, half of those that had not accessed surgery for cataract reported that they were not able to access the service. Studies have reported that major reasons for low cataract surgical rates include the following: low demand because of fear of surgery, low demand from poor people because of high cost of surgery, low demand because of poor visual results, lack of eye surgeons (particularly in Africa), old age, no available services close to the community, and lack of awareness of available surgical services [23]. In our study, subjects with blindness owing to bilateral cataracts (32.5%) did not seek intervention because they were ‘unaware of treatment’.

Conclusion

The prevalence of blindness in Muchinga province of 4.1%. Although lower than the WHO projected for Africa, it remains higher than that obtained in the region. Cataract is the commonest cause of blindness in Muchinga with refractive errors being the main cause of VI. Eye health services are severely inadequate and inaccessible.

Cataract surgical coverage is low and there is an obvious gender imbalance in the accessibility of cataract service. Information/sensitisation on the availability of services is also low. The quality of cataract surgeries performed in the area is below the WHO recommendation.

It is therefore evident that eye health services are not available in Muchinga province and the result of this survey justifies Sightsavers extending the services to Muchinga province.

Competing interests

The authors declare that they have no financial or personal relationships which may have inappropriately influenced them in writing this article.

The study was funded by Sightsavers Zambia and Ministry of Health, Zambia.

References

1. Pascolini D, Mariotti SP. Global estimates of visual impairment: 2010. Br J Ophthalmol. 2012;96:614–618. http://dx.doi.org/10.1136/bjophthalmol-2011-300539
2. World Health Organization. Cumulative official updates to ICD-10 [homepage on the Internet]. [cited 07 February 2011]. Available from: http://www.who. int/classifications/icd/updates/Official_WHO_updates_combined_1996_2012_ Volume_1.pdf
3. World Health Organization. Regional Health Observatory – Sub Regional Codelist. [homepage on the Internet]. [cited 25 November 2014]. Available from: http:// apps.who.int/gho/athena/data/download.xsl?format=xml&target=SUBREGION& profile=excel&filter=
4. Resnikoff S, Pascolini D, Etya’ale D, et al. Global data on visual impairment in the year 2002. Bull World Health Organ. 2004;82:844–851.
5. International Centre for Eye Health. RAAB Instruction Manual. London: London School of Hygiene and Tropical Medicine; 2007.
6. Müller A, Zerom M, Limburg H, et al. Results of a rapid assessment of avoidable blindness (RAAB) in Eritrea. Ophthalmic Epidemiol. 2011;18:103–108. http:// dx.doi.org/10.3109/09286586.2010.545932
7. Oye J, Kuper H. Prevalence and causes of blindness and visual impairment in Limbe urban area, South West Province, Cameroon. Br J Ophthalmol. 2007;91:1435– 1439. http://dx.doi.org/10.1136/bjo.2007.115840
8. Kalua K, Lindfield R, Mtupanyama M, Mtumodzi D, Msiska V. Findings from a rapid assessment of avoidable blindness (RAAB) in Southern Malawi. PloS One. 2011;6:e19226. http://dx.doi.org/10.1371/journal.pone.0019226
9. Oye J, Kuper H, Dineen B, Befidi-Mengue R, Foster A. Prevalence and causes of blindness and visual impairment in Muyuka: A rural health district in South West Province, Cameroon. Br J Ophthalmol. 2006;90(5):538–542. http://dx.doi. org/10.1136/bjo.2005.082271
10. Wadud Z, Kuper H, Polack S, et al. Rapid assessment of avoidable blindness and needs assessment of cataract surgical services in Satkhira District, Bangladesh. Br J Ophthalmol. 2006;90:1225–1229. http://dx.doi.org/10.1136/bjo.2006.101287
11. Chiang F, Kuper H, Lindfield R, et al. Rapid assessment of avoidable blindness in the Occupied Palestinian Territories. PloS One. 2010;5:e11854. http://dx.doi. org/10.1371/journal.pone.0011854
12. Neena J, Rachel J, Praveen V, Murthy GV. Rapid assessment of avoidable blindness in India. PloS One. 2008;3:e2867. http://dx.doi.org/10.1371/journal. pone.0002867
13. Wu M. Rapid assessment of avoidable blindness in Kunming, China. Comm Eye Health/Int Cent Eye Health. 2007;20:10.
14. Central Statistical Office of Zambia. Agriculture Analytical Report for the 2000 Census of Population and Housing. . 2003
15. Central Statistical Office of Zambia. 2010 CENSUS OF POPULATION AND HOUSING Population and Demographic Projections 2011 – 2035.; 2013.
16. Lindfield R, Griffiths U, Bozzani F, Mumba M, Munsanje J. A Rapid Assessment of Avoidable Blindness in Southern Zambia. PLOS ONE. 2012;7(6):e38483.
17. Kalua K, Lindfield R, Mtupanyama M, Mtumodzi D, Msiska V. Findings from a rapid assessment of avoidable blindness (RAAB) in Southern Malawi. PLoS One. 2011;6(4):e19226.
18. Mathenge W, Nkurikiye J, Limburg H, Kuper H. Rapid assessment of avoidable blindness in Western Rwanda: blindness in a postconflict setting. PLoS medicine. 2007;4(7):e217.
19. Habiyakire C, Kabona G, Courtright P, Lewallen S. Rapid assessment of avoidable blindness and cataract surgical services in Kilimanjaro region, Tanzania. Ophthalmic epidemiology. 2010;17(2):90-4.
20. Govender P, Ramson P, Visser L, Naidoo KS. Rapid assessment of avoidable blindness in the northern eThekwini district of KwaZulu-Natal Province, South Africa. African Vision and Eye Health. 2015;74(1):7 pages.
21. Mathenge W, Kuper H, Limburg H, Polack S, Onyango O, Nyaga G, et al. Rapid assessment of avoidable blindness in Nakuru district, Kenya. Ophthalmology. 2007;114(3):599-605.
22. Lewallen S, Mousa A, Bassett K, Courtright P. Cataract surgical coverage remains lower in women. British Journal of Ophthalmology. 2009;93(3):295-8.
23. Foster A. Vision 2020: the cataract challenge. Community eye health. 2000;13(34):17-9.

Vrundaben Patel¹, Elijah M. Munachonga¹, Grace Mutati^1,2, Jessie Nyalazi², Kangwa I. M. Muma^1,2

¹University of Zambia, School of Medicine, Lusaka

²University Teaching Hospitals – Eye hospital, Lusaka Zambia

Download Pdf

Abstract

Purpose:

Diabetic retinopathy (DR) is a blinding complication of diabetes mellitus and a leading cause of visual impairment in people aged 20–64 years. Retinopathy develops overtime in all diabetics and controlling the modifiable risk factors delays its onset and reduces progression. This study was carried out to assess DR; its prevalence and associated clinical and demographic characteristics among patients attending the UTHs-Adult Hospital medical clinic in Lusaka, Zambia

Methods:

This was a hospital-based cross-sectional study carried out from 18^th December, 2018 to 16^th April, 2019 at the adult medical diabetic clinic. Snellen visual acuity (VA), blood pressure, weight and height were measured as well as relevant demographic and medical information collected. Retinal images were captured after pupil dilatation and used for grading retinopathy using the International classification of DR scale. The worse eye was used to grade for DR.

Results:

A total of 213 participants were studied with a female to male ratio of 2.3:1. The median age was 53 years and majority (183=85.2%) had type 2 diabetes. Median duration of diabetes was five years. Median glycated haemoglobin level was high at 8.1%. One hundred sixty-three participants (76.5%) had normal VA and six (2.8%) were blind.

The prevalence of DR in this study was 47.4%; 95% CI 40.8%-54.2% (101 participants), with 8.9% (19 participants) having proliferative diabetic retinopathy.  Diabetic macula oedema was present in 24 (11.3%; 95% CI 7.5%-16.1%). Duration of diabetes was the most significant (p<0.0001) association found with retinopathy.

Even though 104 participants (51.1%) had the knowledge that diabetes affects the eyes, only 55 (25.8%) had had a dilated eye examination in the preceding twelve months.

Conclusion:

A high prevalence of DR among patients attending the adult medical diabetic clinic was found in this study, with only about a quarter of them having had dilated eye examination in the preceding twelve months. The study findings suggest that better advocacy for retinopathy screening and diabetes control needs to be implemented at the UTHs-Adult Hospital in Lusaka.

Introduction

Diabetic retinopathy is a common microvascular complication of diabetes mellitus (DM) [1] and also a leading cause of visual impairment in people aged 20–64 years affecting 1 in 3 persons with diabetes ([2]. The International Agency for Prevention of Blindness (IAPB) reports that 75% of diabetes burden is in low to middle income countries and that DR is emerging among the top causes of vision loss globally [3]. Risk factors for visual impairment that have been identified from studies such as the Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR) include poor glycaemic control, hypertension, smoking and severity of baseline retinopathy [4]. Controlling blood sugar levels reduces the annual incidence of DR but not the lifetime risk of developing DR as it usually develops over time in all diabetes patients [2]. In most cases of DR, an actual decrease in visual acuity is not noticed until progression to very advanced disease occurs [2]. This delays the presentation to any eye health care personnel [5].

A study from the Copperbelt province of Zambia based on a screening programme found a prevalence rate of DR of 52%, which was higher than average from other studies [6]. In a Malawian cohort of patients from diabetic clinics, DR was the most common primary cause of vision loss (38.6%), followed by cataract (16.5%), and both DR and cataract (3.9%) [7]. Cleland et al. looked at a DR screening programme in Tanzania and of the 3463 people analysed, DR was found in 27.9% of people, maculopathy in 16.1%, Proliferative diabetic retinopathy (PDR) in 2.8%, non-proliferative diabetic retinopathy (NPDR) in 25.1% [8]. In the capital city of Zambia – Lusaka, there was a lack of data on the level of retinopathy in diabetic patients and whether the patients are having regular dilated eye examination done by a health worker trained to perform fundoscopy. This study aimed at ascertaining what the prevalent severity of DR was in patients at UTHs adult hospital medical clinic to determine if there was as high a prevalence of DR at UTHs as seen in the Copperbelt. It also assessed risk factors that were associated with DR and whether diabetes patients were having dilated fundoscopy regularly.

Methodology

This was a hospital-based cross sectional study carried from 18th December, 2018 to 16th April, 2019 at the University Teaching Hospitals (UTHs) in Lusaka. The UTHs include the Adult and Emergency Hospital, Eye hospital, Cancer Diseases Hospital, Children’s Hospital, and Women and New Born Hospital. Participants were DM patients recruited weekly into the study from the Adult Hospital medical diabetes clinic. Eye examination equipment was set up in a designated room during the clinic and information collected by ophthalmic personnel from the Eye Hospital and the principle investigator. The sample size was 213 participants; calculated using the prevalence formula for a finite population. Inclusion criteria were known DM patients who consented to take part in the study. Exclusion criteria included patients with ocular media not clear for classifying fundus photos in both eyes and patients found to have retinal co-morbidities, during fundus imaging, affecting the grading of DR. Every consecutive diabetic patient meeting inclusion criteria was included in the study.

A researcher-administered questionnaire for information regarding the demographic characteristics of the patients, the relevant diabetes medical and ocular history and a section for the findings of blood pressure (BP), Body Mass Index (BMI), pin hole visual acuity (VA) and retinopathy grading was used for data collection. Other tools used included Snellen chart, pin hole, Digital Retinography System (DRS) fundus camera by Centervue, Italy, Sphygmomanometer, weighing scale and height scale, and blood collection consumables. Patients were identified as they were waiting for the physician’s review and informed consent was obtained. Those found to have ocular media not clear enough to get gradable retinal images in both eyes were excluded from the study and referred to a consultant ophthalmologist at the eye hospital for further assessment and management. After measurement of VA, BP and BMI, the participants’ pupils were dilated with one drop of a mydriatic eye drop that had a combination of tropicamide 0.8% and phenylephrine 5%. DRS fundus camera was used once the pupils were dilated to capture retinal images. Both colour and red-free retinal images were captured from both eyes and graded to assess the severity of retinopathy. The worse eye or the only eye with a gradable image was used in the analysis. The principle investigator read all retinal images and graded using the international classification of DR. One consultant ophthalmologist randomly reviewed selected images to ensure quality and adherence to the international standard and protocol for the study.

Figure 1: Procedure flow chart

Data was collected and entered in a Microsoft Excel spread sheet. Analysis was done using STATA version 13.1. Continuous variables were tested for normality using Shapiro-Wilk test. The chi square and Mann-Whitney tests were used to compare no DR to DR depending on the type of variable. To determine the correlation between two normally distributed independent variables Pearson coefficient was used; while Spearman coefficient was used for non-normally distributed variables. In the final analysis to rule out confounders, a multiple logistic regression model was constructed using a cut off of 20% for the variables. Age, HbA1c and use of Anti-HTN medication were included in the final analysis due to significant associations found in several other studies. The model helped identify factors that were associated with DR after adjusting for baseline characteristics. A p-value <0.05 was regarded as significant.

Results

The socio-demographic characteristics of participants in the study are shown in table 1 below:

Table 1: Socio-demographic characteristics of participants

Variable	Category	Proportion (%)
Age	Median IQR (25%-75%)	53 years44-63 years
Sex	FemaleMale	150 (70.4)63 (29.6)
Occupation	Not employedInformal employmentFormal employment	47 (22.07)109 (51.17)57 (26.76)
Education	None PrimarySecondaryTertiary	35 (16.43)50 (23.47)45 (21.13)83 (38.97)
Smoking	YesNo	7 (3.29)206 (96.71)
Alcohol intake	YesNo	33 (15.49)180 (84.51)

Of the 213 study participants, 30 (14.8%) had type 1 DM and 183 (85.2%) had type 2 DM. The median duration of DM was 5 years (IQR = 2-10 years). The median duration of attendance at UTHs adult hospital medical clinic was 3 years (IQR = 6 months to 7 years).

One hundred fifteen (54.5%) participants were taking insulin for DM control while 80 (37.6%) were taking oral hypoglycaemic medication. Twelve (5.6%) participants were taking both insulin and oral hypoglycaemics with 87 (40.8%) participants also taking anti-hypertensive medication.

One hundred twenty four (58.2%) participants did not report any complications arising from diabetes. However, 13 (6.1%) gave a history of diabetic foot, 67 (31.5%) had peripheral neuropathy and 3 (1.4%) had kidney-related complications.

Systolic BP measurements were normal in 117 (54.9%) participants, with 61 (28.6%) having stage 1 hypertension and 35 (16.4%) having stage 2 hypertension levels. Diastolic blood pressure measurements were normal in 142 (66.7%) participants, with 41 (19.2%) having stage 1 hypertension and 30 (14.1%) stage 2 hypertension. The BMI was normal for 78 (37.7%) participants, 69 (33.3%) participants were overweight and 60 (29.0%) of the participants were obese.

When asked if they had had a dilated eye examination in the preceding 12 months, 55 (25.8%) responded positively. The median age of participants who had the examination (58 years) was significantly higher than those who did not (52 years). Univariate logistic regression analysis revealed that those with tertiary level of education (p=0.038), longer duration of medical diabetes clinic attendance (p=0.009), and those with knowledge that diabetes has eye complications (p=0.034) were more likely to have had a dilated eye examination in the preceding 12 months.

Regarding knowledge about the ocular complications of DM, 104 (51.2%) participants had some idea with poor vision and blindness being the most common responses. There was no statistically significant difference in terms of gender (p=0.203) nor education level (p=0.114) in relation to knowledge about the ocular complications of DM.

Diabetic retinopathy and maculopathy were classified using the ICO international classification of

DR. DR was present in 101 (47.4%; 95% CI 40.7% – 54.2%) participants while 112 (52.6%; 95% CI 45.8% – 59.3%) participants had no DR. Eighty two (38.5%; 95% CI 32.1% – 45.3%) had NPDR and 19 (8.9%; 95% CI 5.7% – 13.6%) had PDR. 24 (11.3% with 95% CI 7.6% – 16.3%) participants had DME. No participant had had previous laser treatment for DR.

In the univariate analysis (table 2) the factors significantly associated with DR included duration of DM (p=0.001), duration of clinic 5 attendance (p=0.040), type of DM medication used (p=0.010), DM related illnesses (p=0.001), BMI class (p=0.030) and alcohol intake (p=0.002).

In the multiple logistic regression analysis (table 3), duration of DM (p<0.0001), having diabetic foot (p=0.006) and alcohol intake (p=0.005) were maintained as factors found to be statistically significant associations of DR.

For maculopathy, only duration of DM was found to be a statistically significant association (Odds ratio=1.10 with 95% CI 1.03-1.18).

Figure 2: Distribution of DR among participants

 Table 2: Univariate analysis of associations of Diabetic retinopathy and maculopathy

Variable	No DR	NPDR	PDR	p-value	No DME	DME	p-value
Age (median years)	51.5	54	52	0.712	53	57.5	0.027
Sex (n)FemaleMale	4072	1864	514	0.110	5613	717	0.963
Occupation (n)NoneInformal Formal	265728	174322	397	0.847	409652	6135	0.762
Education level (n)None PrimarySecondaryTertiary	18332239	15111937	2647	0.241	30424176	5847	0.501
Smoking (n)No Yes	1102	774	181	0.424	1836	231	0.766
Alcohol (n)NoYes	10012	6813	118	0.002	16128	195	0.387
Type of DM (n)Type 1Type 2	1894	1072	217	0.670	30159	024	0.035
Duration of DM (years)	3	7	10	<0.0001	5	10.5	<0.0001
DM medication (n):NoneInsulinOral hypoglycaemicBothAnti-HTN medication (n)YesNo Other DM-related illnesses (n):Renal diseaseDiabetic footPeripheral neuropathyNoneDuration of medical diabetes clinic attendance (years)BMI class (n)NormalOverweightObese HbA1c (%)SBP (n)NormalStage 1 HTNStage 2 HTNDBP (n)NormalStage 1 HTNStage 2 HTN	562441 4567 0338652  3931397.5 662818 732415	143317 3646 2524514  3226218.17 412912 551413	01054 613 15583  71209.3 10415 1432	0.010    0.603  0.001    0.040 0.030   0.2580.378   0.889	5105727 76113 18621122  6460608.0 1075527 1273725	11085 1113 255123.5  14909.2 1068 1545	0.007    0.598  <0.0001    0.071 0.003   0.2500.058   0.595

Table 3: Multiple logistic regression analysis of risk factors associated with diabetic retinopathy

Variable	Odds ratio	95% Confidence interval	p-value
Age	1.00	0.97 1.02	0.836
Alcohol	3.48	1.46            8.26	0.005
Duration of DM	1.12	1.05            1.19	< 0.0001
DM medication:InsulinOral hypoglycaemicBoth	15.77 23.72127.48	0.47        524.550.71        791.373.16      5147.44	0.1230.080     0.010
Anti HTN medication	1.33	0.66           2.66	0.420
Other DM-related illnesses:Renal diseaseDiabetic footPeripheral neuropathy	23.026.283.00	1.57        337.681.68          23.540.430          1.63	0.0220.0060.601
Duration of medical diabetes clinic attendance HbA1c	0.98   1.05	0.91 1.06   0.90            1.22	0.591   0.558

Glycated haemoglobin (HbA1c) findings showed a median value of 8.1%, with the lowest being 4.6% and highest 13%. The median HbA1c level increased with the severity of DR as shown in figure 2 below.

Figure 3: HbA1c levels in different grades of DR

Using the International Classification of Diseases 11 (ICD 11) VA was graded, upon which classification of visual impairment and blindness was determined. One hundred sixty three (76.5%) participants had normal visual acuity, 44 (20.7%) had visual impairment and 6 (2.8%) were blind.

Table 4: ICD 11 class of visual acuity of participants

ICD 11 Class	Visual acuity	Proportion (%)
Normal vision	≥ 6/12	163 (76.53)
Visual impairmentMild ModerateSevere	< 6/12<6/18<6/60	24 (11.27)17 (7.98)3 (1.41)
Blindness	<3/60	6 (2.82)

DISCUSSION

This was a cross sectional study looking at the prevalence of DR and its associated risk factors. Duration of DM, microvascular complications and alcohol intake were found to be associated with DR. The prevalence of DR was found to be 47.42% (95% CI 40.75% – 54.18%) in this study. This result reaffirms the findings of the Copperbelt province study where prevalence of DR was found to be 52% [6].

The median age of participants in this study was 53 years (IQR=44 to 63 years) which was consistent with many studies looking at patients with both type 1 and type 2 diabetes [6,9]. This study had a high ratio of female to male participants (2.3:1). Generally, females are more than males in study populations of type 2 DM or type 1 and 2 combined [10,11]. The number of smokers was very small in this study and no association was found with DR. Smoking is not an established known risk factor for DR, particularly type 2 DM, though it has  been associated with DR in type 1 DM [12].

In studies involving the adult population, type 2 DM is more prevalent than type 1 DM [13,14] and this was the case in this study too. The type of DM had no impact on DR in this study. Type 1 DM participants had a median duration of DM of 5 years while for type 2 DM participants it was 5.5 years.  

Among the participants, 40.85% were taking anti- hypertensive medication. Among those found to have stage 2 hypertension level systolic and diastolic BP, less than 70% were taking anti-hypertensive medication. However, no significant association was found with any of these three BP parameters and DR in this study. This is comparable to findings from studies by Akpalu (2011) and by Rotimi et al., (2003) from Africa [15,16].  However, major epidemiological studies such as the UKPDS have shown that strict control of BP is associated with reduced risk of DR and it’s progression though the effect wears off with cessation of such control [17]. Other studies also show an association with stage 1 or 2 hypertension level of blood pressure and DR [8,18]. Findings from a review done by Do et el in 2015 showed that strict hypertension control had a modest effect in reducing the incidence of DR by 4 to 5 years but lack of effect on progression of DR over the same time period [19]. Thus, hypertension control in DM patients is advised to reduce the overall morbidity associated cardiovascular disease rather than to reduce progression of DR [20].

Retinopathy, nephropathy and neuropathy are all microvascular complications of DM and have been shown to be present simultaneously in an individual. Three patients had nephropathy in this study and 2 of these had NPDR while 1 had PDR. Having a DM-related complication was also found to be significantly associated with DR in this study (p<0.0001).

The University Teaching Hospitals are tertiary level referral hospitals for the whole of Zambia. As such most of the DM patients seen are those that were poorly controlled from local health centres or have severe comorbidities. Type 1 DM patients require insulin for adequate glycaemic control while for type 2 DM patients oral hypoglycaemic medication may be enough but about one third need insulin [21]. These two factors can explain the high number of participants using insulin in this study. Unadjusted p-value suggested an association between medication used and DR though this was not significant in the multiple analysis. Some studies report majority of participants taking oral hypoglycaemics [6] while others report higher rate of insulin use, particularly in hospital patients [14,22].

Strict glycaemic control has been shown to reduce the occurrence of DR as presented in the UKPDS study where mean HbA1c was 7.0% in the strict glycaemic control group and 7.9% in the conventional group [23]. A systematic review looking at HbA1c and DM showed significant association with DR at HbA1c levels of 5.8% to 7.3% and suggest a threshold of 6.5% for diabetes-specific retinopathy [24]. In this study, there was no statistically significant association between the overall median HbA1c level and DR. However, the box and whisker plot shown in figure 3 indicates the median HbA1c was progressively higher from the ‘no DR’ to ‘PDR’ groups. The median for the ‘no DR group’ (7.5%) was higher than that of the ‘no DR groups’ in other studies showing generally poor glycaemic control in this study sample [18]. Other studies with similar samples of mostly type 2 DM patients also did not find association between HbA1c and DR [25,26]. Generally, when looking at glycaemic control and DR,  evidence is available to show intensive glycaemic control lowers risk of incidence and, to a lesser extent, risk of progression of DR in patients with younger-onset or type 1 disease [27]. For older or type 2 patients, this is not so apparent [28].

A little more than half of the participants (51.1%) in this study had some knowledge about diabetes affecting the eyes though the knowledge was not specific to retinopathy. Sadly, this knowledge gap was seen even among the participants who had a positive medical background. The most common responses were visual impairment and blindness. Other studies have shown a much higher percentage of diabetic patients with knowledge that diabetes affects the eye; 75.62% from a Saudi Arabian study and 89.0% from a Tanzanian study [29,30]. This highlights gaps in sensitisation and dissemination of information at the primary health care level as well as during specialized medical diabetic clinic visits in this setting.

Despite about half of participants knowing that diabetes affects vision, only 28.8% had had a dilated fundal eye examination in the preceding twelve months. This low rate is consistent with other studies- 28.8% in the study by Mumba et al. in Tanzania [29]. Yearly eye screening for DR is the current recommended practice for all diabetics, particularly those with no DR on initial screening [2]. This could be a proxy indicator of physicians eventually referring diabetic patients for fundoscopy overtime though this could also be attributed to patients developing visual complaints.  

As seen with other hospital-based studies, the prevalence of DR (47.42%) in this study was higher than findings from population-based studies. This value was closer to the 49% prevalence of DR found in the study by Akpalu et al in Ghana [15] and the 52.0% in the Copperbelt province of Zambia [6]. In contrast, DR was found in only 27.9% in a population-based Tanzanian study on enrolment into a screening programme [8]. The systematic review by Burgess et al had a range of DR from 9.55% to 62.4%, with maculopathy ranging from 1.2% to 31.1% across East and Southern Africa [7]. Grading of DR by means of retinal photographs (used in this study) as opposed to ophthalmoscopy has been found to produce higher frequency of DR detected [31].

Final risk factor analysis revealed duration of DM as the most important risk factor for DR in this study. This is consistent with all studies done analysing risk factors and it is known that all diabetics develop DR overtime [32]. Alcohol intake and diabetic foot were also found to be associated with DR in our study; though the 95% confidence intervals were not even and slightly wide suggesting less significance than indicated by the p-value. A UK primary-care based study did find an association of alcohol intake with DR [33]. According to a meta-analysis study in 2016 by Zhu et al., alcohol intake was not associated with increased risk of DR, even in subgroup analysis of type of alcohol [34]. No African study was part of the meta-analysis though. In our study, no quantification of type and frequency of alcohol intake was done and this would need to be further studied to explore any real association with DR.

CONCLUSION

From this study, a high prevalence rate of DR at 47.42% (95% CI 40.75% – 54.18%) was seen among patients attending the UTHs-Adult Hospital medical diabetic clinic in Lusaka. NPDR was present in 38.5% and PDR in 8.92% while 11.27% (95% CI 7.46%-16.13%) had diabetic macula oedema. Duration of diabetes was the most significant association found with retinopathy. Median HbA1c was 8% which showed poor average glycaemic control among participants. Even though 51.1% had the knowledge that diabetes affects the eyes, only 25.82% had had a dilated eye examination in the preceding twelve months.

RECOMMENDATIONS

From these findings, it is recommended that more sensitisation programmes in the primary health care facilities on need for regular retinal examinations in diabetic patients are needed. Also, regular HbA1c testing needs to be used as a means to assess glycaemic control in patients attending the medical diabetic clinic. This includes advocating for supportive laboratory services. Another recommendation is to scale up country wide DR screening using retinal photography across Zambia. This includes use of telemedicine for interpretation of images from areas with trained photographers but not trained image graders or ophthalmologists. Further studies are also needed with larger sample sizes for a definite risk factor analysis in both hospital-and community-based settings in Lusaka.

REFERENCES

1. Khurana AK. Comprehensive Ophthalmology. 4th ed. New Delhi: New Age International (P) Limited; 2007. 259–263 p.

2. Taylor H, Binder S, Das T, Farah M, Ferris F, Massin P, et al. ICO Guidelines for Diabetic Eye Care. International Council of Ophthalmology.; 2017.

3. IAPB. Diabetic Retinopathy [Internet]. iapb.org. 2018 [cited 2018 May 23]. Available from: https://www.iapb.org/knowledge/what-is-avoidable-blindness/diabetic-retinopathy/

4. Klein R, Lee KE, Gangnon RE, Klein BEK. The 25-Year Incidence of Visual Impairment in Type 1 Diabetes Mellitus. Ophthalmology. 2010 Jan;117(1):63–70.

5. Ammary-Risch NJ, Huang SS. Preventing blindness from diabetes.pdf. JOURNAL OF THE NATIONAL MEDICAL ASSOCIATION. 2011 Mar;103(3):281–3.

6. Lewis AD, Hogg RE, Chandran M, Musonda L, North L, Chakravarthy U, et al. Prevalence of diabetic retinopathy and visual impairment in patients with diabetes mellitus in Zambia through the implementation of a mobile diabetic retinopathy screening project in the Copperbelt province: a cross-sectional study. Eye. 2018 Mar 5;32:1201–8.

7. Burgess PI, MacCormick IJC, Harding SP, Bastawrous A, Beare NAV, Garner P. Epidemiology of diabetic retinopathy and maculopathy in Africa: a systematic review: Diabetic retinopathy in Africa. Diabetic Medicine. 2013 Apr;30(4):399–412.

8. Cleland C R., Burton Matthew J., Hall Claudette, Hall Anthony, Courtright Paul, Makupa William U., et al. Diabetic retinopathy in Tanzania: prevalence and risk factors at entry into a regional screening programme. Tropical Medicine & International Health. 2015 Dec 8;21(3):417–26.

9. Mashige K, Notshweleka A, Moodley S, Rahmtoola F, Sayed S, Singh S, et al. An assessment of the level of diabetic patients’ knowledge of diabetes mellitus, its complications and management in Durban, South Africa. South African Optometrist. 2008 Sep 30;67:95–105.

10. Banda L. A suvey of common complications associated with diabetes mellitus in the diabetic clinic at the University teaching hospital,Lusaka,Zambia [Internet] [Thesis]. [Lusaka]: University of Zambia; 2012 [cited 2019 May 3]. Available from: http://dspace.unza.zm:8080/xmlui/handle/123456789/1298

11. Burn H, Pons J. Diabetic retinopathy in Swaziland [Internet]. Community Eye Health Journal. 2016 [cited 2018 Jun 15]. Available from: https://www.cehjournal.org/article/diabetic-retinopathy-in-swaziland/

12. Cai X, Chen Y, Yang W, Gao X, Han X, Ji L. The association of smoking and risk of diabetic retinopathy in patients with type 1 and type 2 diabetes: a meta-analysis. Endocrine. 2018;62(2):299–306.

13. Burgess PI, Allain TJ, García-Fiñana M, Beare NAV, Msukwa G, Harding SP. High prevalence in Malawi of sight-threatening retinopathy and visual impairment caused by diabetes: identification of population-specific targets for intervention. Diabetic Medicine. 2014 Dec;31(12):1643–50.

14. Gill G, Gebrekidan A, English P, Wile D, Tesfaye S. Diabetic complications and glycaemic control in remote North Africa. Quarterly ournal of Medicine. 2008 Oct 1;101(10):793–8.

15. Akpalu J. Magnitude, pattern and level of awareness of diabetic retinopathy at korle-bu teaching Hospital accra-ghana. University of Nairobi; 2011.

16. Rotimi C HD, et al. Prevalence and determinants of diabetic retinopathy and cataracts in West African type 2 diabetes patients. Ethnicity and Disease. 2003;13(Spring):S2-110±S2-117.

17. King P, Peacock I, Donelly R. The UK Prospective Diabetes Study (UKPDS): clinical and therapeutic implications for type 2 diabetes. British Journal of Clinical Pharmacology. 1999;48:643–648.

18. Njikam EJ, Kariuki MM, Kollmann MKH, Wilhelm F, Nentwich MM. The magnitude and pattern of diabetic retinopathy in Yaoundé, Cameroon – a cross-sectional hospital-based study. Acta Ophthalmologica. 2016 Mar;94(2):e156–7.

19. Do DV, Wang X, Vedula SS, Marrone M, Sleilati G, Hawkins BS, et al. Blood pressure control for diabetic retinopathy. Cochrane Database Syst Rev. 2015 Jan 31;1:CD006127.

20. Lee R, Wong TY, Sabanayagam C. Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss. Eye and Vision [Internet]. 2015 Dec [cited 2018 Nov 12];2(1). Available from: http://www.eandv.org/content/2/1/17

21. WHO. WHO | Diabetes mellitus [Internet]. WHO. 2018 [cited 2018 Dec 8]. Available from: https://www.who.int/mediacentre/factsheets/fs138/en/

22. Axer-Siegel R. The Relationship between Diabetic Retinopathy, Glycemic Control, Risk Factor Indicators and Patient Education. IMAJ. 2006 Aug;8:523–526.

23. Gupta A, Aggarwal VK, Goel N. Handbook of Clinical Trials in Ophthalmology. First. Jaypee Brothers Medical Publishers; 2014.

24. WHO. HbA1c in the diagnosis of type 2 diabetes: a systematic review [Internet]. WHO; 2011. Available from: www.who.int/diabetes/publications/diagnosis_diabetes2011/en/

25. Glover SJ, Burgess PI, Cohen DB, Harding SP, Hofland HWC, Zijlstra EE, et al. Prevalence of diabetic retinopathy, cataract and visual impairment in patients with diabetes in sub-Saharan Africa. British Journal of Ophthalmology. 2012 Feb 1;96(2):156–61.

26. Ponto KA, Koenig J, Peto T, Lamparter J, Raum P, Wild PS, et al. Prevalence of diabetic retinopathy in screening-detected diabetes mellitus: results from the Gutenberg Health Study (GHS). Diabetologia. 2016 Sep 1;59(9):1913–9.

27. Lachin J, Nathan DM, Cleary P, Crofford O, Davis M, Rand L, et al. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993 30;329(14):977–86.

28. Fullerton B, Jeitler K, Seitz M, Horvath K, Berghold A, Siebenhofer A. Intensive glucose control versus conventional glucose control for type 1 diabetes mellitus. Cochrane Database Syst Rev. 2014 Feb 14;(2):CD009122.

29. Mumba M, Susan Lewallen, Anthony Hall,. Compliance with Eye Screening Examinations among Diabetic Patients at a Tanzanian Referral Hospital. Ophthalmic Epidemiology. 2007 Oct;(14):306–310.

30. Al Zarea BK. Knowledge, Attitude and Practice of Diabetic Retinopathy amongst the Diabetic Patients of AlJouf and Hail Province of Saudi Arabia. Journal of Clinical and Diagnostic Research : JCDR. 2016 May;10(5):NC05–8.

31. Schachat AP, Hyman L, Leske MC, Connell AMS, Hiner C, Javornik N, et al. Comparison of Diabetic Retinopathy Detection by Clinical Examinations and Photograph Gradings. Arch Ophthalmol. 1993 Aug 1;111(8):1064–70.

32. Bowling B. Kanski’s Clinical ophthalmology, A Systematic Approach. 8th ed. Elsevier limited; 2016. 618–622 p.

33. Martín-Merino E, Fortuny J, Rivero-Ferrer E, Lind M, Garcia-Rodriguez LA. Risk factors for diabetic retinopathy in people with Type 2 diabetes: A case–control study in a UK primary care setting. Primary Care Diabetes. 2016 Aug 1;10(4):300–8.

34. Zhu W, Meng Y-F, Wu Y, Xu M, Lu J. Association of alcohol intake with risk of diabetic retinopathy: a meta-analysis of observational studies. Scientific Reports [Internet]. 2017 Dec [cited 2019 May 7];7(1). Available from: http://www.nature.com/articles/s41598-017-00034-w

Kangwa I. M. Muma^1,2,3, Jessie I. M. Nyalazi², Chisomo Mbewe², Timothy Kangwa², George Zulu², Grace Chipalo – Mutati^2,3 and Gardner Syakantu⁴

¹National Eye Health Coordination, Directorate of Clinical Care and Diagnostic Services, Ministry of Health, Lusaka, Zambia

²University Teaching Hospitals – Eye Hospital, Lusaka, Zambia

³Department of Ophthalmology, School of Medicine and Clinical Sciences, Levy Mwanawasa Medical University, Lusaka, Zambia

⁴School of Medicine and Clinical Sciences, Levy Mwanawasa Medical University, Lusaka, Zambia

Download Pdf

Abstract

Objective: To develop a diabetic retinopathy strategy for early detection of sight-threatening diabetic retinopathy in Zambia.

Background: The Ministry of Health (MoH), Zambia, embarked on a programme to scale up the initiative for Universal Health Coverage of services across the continuum of health care throughout the country. The University Teaching Hospitals (UTHs) was tasked to play a pivotal role in this noble cause in line with MoH’s vision of bringing health as close to the family as possible. A National Diabetic Retinopathy Screening (DRS) programme was commenced in 2012 in collaboration with the Frimley Park Hospital of the United Kingdom (UK).

Methods: The DRS programme is based on fundus camera screening using the UK protocol. This is both community and hospital based. The idea was to develop strategies that would ensure the capture of all diabetic patients in the country and have them screened for diabetic retinopathy (DR). A national Diabetes Mellitus (DM) register was also to be created where all the DM patients would be registered and accounted for. The UTHs – Eye Hospital (UTHs – EH) was to implement the programme at the University Teaching Hospitals (UTHs), in Lusaka Province and oversee the roll out the national DRS programme through the National Eye Health Coordination (NEHC) office. In this endeavour, in 2018, the UTHs – EH introduced a weekly DRS screening clinic at the medical clinic of the UTHs – Adult Hospital (UTHs – AH) to increase the uptake of DRS by all the DM patients attending the diabetic clinic.

Results: A total of 1517 DM patients had both their eyes screened for DR at the UTHs from January 2016 to June 2019 of which nine hundred and ninety-three (993) were screened at the UTHs – EH compared to 524 (34.5%) screened at the UTHs – AH. Screening at UTHs – AH started in 2018. For the years 2016 and 2017, 36.9% (560/1517) participants were screened compare to 43.2% (656/1517) in 2018 of which 50.6% (332/656) were screened at the UTHs – AH and 49.4% (324/656) at the UTHs – EH. Quarters one and two of 2019 saw 63.8% (192/301) participants screened at UTHs – AH compared to 36.2% (109/301) at the UTHs – EH. Overall, 57.2% (524/957) participants were screened at the UTHs – AH in 2018 and 2019 implying that the setting up of this service significantly increased the uptake of DRS by 57.2%, p < 0.0001. There was an increase of the patients attended to by 63.7% from 102 in quarters one and two in 2016 to 167 in the same quarters in 2019. The hosting of the DRS clinic by the medical clinic also enhanced collaboration in the management of DR between ophthalmologists and physicians at the UTHs. Nine hundred and twenty-two (922) participants screened had DR making the prevalence of DR 60.8%.

Conclusion: The 57% more DM patients screened at the UTHs – AH demonstrated a huge need of following the DM patients to the medical clinic in order to increase the uptake and compliance to have DR screening. Thinking without the box strategies including collaboration of all disciplines involved in the DM management is vital in scaling up the DRS and preventing blindness due to DR. The study demonstrated the importance of creating convenience for the patients and making the service not only relevant but readily available to the public.

Keywords: Diabetes Mellitus, Diabetic Retinopathy, Diabetic Retinopathy Screening, Prevalence

INTRODUCTION

Background

Diabetes mellitus (DM), commonly known as diabetes, is a group of metabolic disorders characterized by high blood sugar due to either the pancreas not producing enough insulin (TYPE 1), or the cells of the body not responding properly to the insulin produced (TYPE 2) [1]. With the rise of a more sedentary lifestyle in both developed and developing countries, the global prevalence of DM is increasing rapidly. Diabetes prevalence in Zambia was reported at 6.2% in the population aged 20 to 79 years [3].

In the United States of America (USA) and UK, diabetic retinopathy is an important cause of visual impairment and blindness among adults aged 20–74 years [4]. About 50–73% of those with visual impairment or blindness because of DR can be prevented by early detection and treatment of risk factors, and by photocoagulation [5,6]. With timely laser treatment and intravitreal anti-vascular endothelial growth factor (VEGF) therapy, severe vision loss from DR can be reduced by 90% [7,8,9]. Diabetic retinopathy is not only a blinding condition but also affects visual functions that affect performance of daily activities like contrast sensitivity [10].

In the Copperbelt province of Zambia, a population-based study on 2153 diabetic participants identified at various health centres and recruited in the DRS programme found some form of DR in 52% of participants and 36% had sight-threatening DR [11]. The reported prevalence rate was higher than most estimates from other studies; be it hospital-based or population-based. Several classification systems exist for grading severity of DR. In Zambia the United Kingdom Diabetic Retinopathy Grading System (UKDRGS) using fundus photos is used (Table 1). In this study, the UKDRGS was used [11].

Table 1: Grading of DR based on retinal images

R	Retinopathy
R0	None	No abnormalities / No DR
R1	Background	Microaneurysm(s) Retinal haemorrhage(s) Venous loop Any exudate in the presence of other features of DR Any number of cotton wool spots (CWS) in presence of other features of DR
R2	Pre-proliferative	Venous beading Venous reduplication Multiple blot haemorrhages Intraretinal microvascular abnormality (IRMA)
R3	Proliferative
	R3a	New vessels on disc (NVD)New vessels elsewhere (NVE)New pre-retinal or vitreous haemorrhageNew pre-retinal fibrosisNew tractional retinal detachment
	R3s	Stable pre-retinal fibrosis + peripheral retinal scatter laserStable fibrous proliferation + peripheral retinal scatter laserStable R2 features + peripheral retinal scatter laserR1 features + peripheral retinal scatter laser
M	Maculopathy
	M0	No maculopathyAny microaneurysm or haemorrhage within 1DD of the centre of the fovea if associated with a best VA of ≤ 6/12 where the cause of the reduced vision is known and is not diabetic macular oedema.
	M1	Exudate within 1-disc diameter (DD) of the centre of the foveaGroup of exudates within the maculaRetinal thickening within 1DD of the centre of the fovea (if stereo available)Any microaneurysm or haemorrhage within 1DD of the centre of the fovea only if associated with a best VA of ≤ 6/12 (if no stereo)CSMO – Retinal thickening at or within 500 microns of the centre of the maculaCSMO – Hard exudates at or within 500 microns of the centre of the macula, if associated with thickening of the adjacent retina (not residual hard exudates remaining after disappearance of retinal thickening) hard exudates remainingCSMO – A zone or zones of retinal thickening one-disc area or larger, any part of which is within one-disc diameter of the centre of the macula.
P	Photocoagulation
	P0	No evidence of previous photocoagulation (default)
	P1	Focal/grid to macula or peripheral scatter
U	Ungradable
	U	An image set that cannot be graded

(Core NDESP team, 2012)

African studies have shown low numbers of diabetic participants having routine eye examinations. A study done in Tanzania looking at participants not being part of any screening programme for DR found that only 29% of participants had had an eye examination in the previous year [12]. Similarly, in a South African study, 48.3% of participants had their last eye examination more than a year and a half period [13]. However, in a Saudi Arabian study, about 95% of participants had regular eye examinations, much higher than in the African set up [14].

A multiple case study by Poore et al. (2014) evaluating DR screening programmes in 2014 in Botswana, Ghana, Tanzania and Zambia noted a lack of local data in Africa on the scale of DR problem and that even in participants that were screened, uptake of referrals to the eye department was the main challenge [15].

Mild and moderate non-proliferative DR can be managed by good systemic glycaemic control and regular ophthalmoscopy examinations. Severe Non-proliferative DR, proliferative DR and centre-involving macular oedema require urgent treatment to prevent vision loss. With the advent of retinal laser photocoagulation therapy and anti- Vascular Endothelial Growth Factor (VEGF) agents, DR and maculopathy can be treated to prevent blindness if detected early enough [16]. Studies such as the Early Treatment of Diabetic Retinopathy Study (ETDRS) have shown that treatment with retinal laser photocoagulation can reduce the incidence of severe vision loss in participants with sight-threatening DR [17].

Diabetic Retinopathy Screening

Timely screening and treatment for DR can prevent morbidity. As early DR is asymptomatic, the International Diabetic Foundation (IDF) guidelines recommend early detection of DR by means of DR screening which is very effective in the proper management of DR [19]. It is only through screening that diagnosis and treatment can be made at an early stage and prevent sight threatening DR [20]. The importance of eye screening programme is to reduce the risk of sight loss amongst people with diabetes by the prompt identification and effective treatment if necessary, of sight-threatening DR, at the appropriate stage during the disease process [21].

Feasible and efficacious methods for increasing screening follow-up rates include patient education, a streamlined referral and scheduling process, and collaboration with local ophthalmologists and primary care providers [18]. Diabetic patients should be educated on the importance of regular eye examinations to detect early retinopathy [18, 20]. Even with the control of retinopathy risk factors such as high blood pressure, high serum cholesterol, poor diabetic control, smoking, obesity, and renal disease, regular ocular examination is highly recommended [20]. This is because long duration of the disease is probably the most significant risk factor for retinopathy [21]. Since diabetes is by nature a chronic ailment, most patients ultimately develop retinopathy in the course of the disease.

Prevention of visual loss in DR has improved considerably during the last decade, especially in northern Europe due to robust screening programmes in place [22]. Patient compliance with DR screening is not optimal, as shown by attendance rates ranging from 32 to 85% [24,25,26,27,28]. To increase DR screening attendance, insight into incentives and barriers to retinopathy screening is necessary. However, longer diabetes duration, older age and diabetes-related visual problems are associated with screening compliance [28,29]. In the USA, financial barriers are also often reported [27,28,29,30]. Nevertheless, the main barrier for compliance was the patient’s belief that they do not have DR [31]. Other factors were embarrassment about poor glycaemic control and fear of ophthalmological examination and treatment [32]. Many conclude that patients’ lack of awareness (due to lack of education/ information) is the main obstacle to attend a screening programme [26,32,33,34,35]. In view of the major investments in screening and treatment programmes, developing interventions to reduce non-compliance should be a priority [23]. another barrier is the making of appointments for eye screening at the eye facilities which be situated far from the medical clinic and could have a programme that is not aligned to favour immediate attention of the DM patients. There is also the barrier of travelling long distances to go for eye check-up. These barriers result in low uptake and follow-up rates of DM patients for DR [22].

Several types of screening programmes have been designed throughout the world to meet the DR problem. We report on our active screening programme for diabetic eye disease and describe the sight and eye condition of the diabetic patients who have been involved in this programme.

METHODS

Study design

This was a retrospective study.

Study duration

January 2016 to June, 2019

Study site

The study was carried out at the University Teaching Hospitals (UTHs) in Lusaka. The DM patients in this study were recruited weekly from the medical clinic (clinic 5) of the Adult Hospital and the outpatient clinic at the Eye Hospital.

Study population

All diabetes mellitus patients seen at the medical and eye clinics at the UTHs

Inclusion criteria

All patients with a diagnosis of diabetes mellitus attending the medical clinic at the UTHs – AH and UTHs – EH were eligible for DR screening programme and could participate. Fundus photographs taken were graded in accordance with the DR grading system used in the UK National Health service (NHS). Visual impairment data were collected from visual acuity measurements recorded using Snellen chart.

Exclusion criteria

None was excluded

Study sample

All diabetes mellitus patients seen at the medical clinic and the eye clinic who have not had it done and those due for their annual DRS. For the study, no patient was recruited more than once.

Sampling technique

Every consecutive diabetic patient meeting inclusion criteria was included in the study.

Data collection instruments

A researcher-administered questionnaire adapted from the current form used in screening programme at UTHs – Eye Hospital and Adult Hospital. The questionnaire contained information regarding the demographic characteristics of the patients, the relevant diabetic medical and ocular history. A section for the findings of blood pressure, visual acuity and retinopathy grading was included. Other tools included a Snellen chart with pinhole, Digital Retinography System (DRS, Centervue, Italy) fundus camera and manual Sphygmomanometer

Data collection procedure 

PROCEDURE:

Diabetic patients’ records were recruited to be included in the study at the adult hospital weekly medical clinic for diabetes and other endocrinology conditions.

Measurement of blood pressure, VA with pinhole to get the Best Corrected Visual Acuity (BCVA) was done. Ophthalmic nurses from the Eye hospital trained in fundus imaging and DR grading were used as research assistants. Then the patients’ pupils were dilated with a mydriatic that had a combination of tropicamide 0.8% and phenylephrine 5%. 1 eye drop was instilled in each eye and repeated as needed to achieve adequate pupillary dilatation.

DRS fundus camera was used to capture retinal images on patients dilated with mydriatically dilated pupils. Both colour and red-free retinal images were captured from both eyes and graded to assess the severity of retinopathy. The worse eye or the eye with a gradable image was used in the analysis. The principle investigator read all retinal images and graded using the international classification of DR. One ophthalmologist reviewed randomly selected images to ensure quality and adherence to the international standard and protocol for the study.

Sight-threatening DR was defined as any of the following: moderate pre-proliferative retinopathy or worse (level 40–71 +); macular exudates in a circinate pattern or within one disc diameter of the foveal centre or clinically significant macular oedema (level 3–4: sight-threatening maculopathy); or other diabetes-related retinal vascular disease: central or branch retinal artery occlusion, central or branch retinal vein occlusion.

Data analysis

Data was collected and entered in Excel spread sheet. Analysis was then done using SPSS version 24. Continuous variables were tested for normality using Shapiro-Wilk test. The chi square and Mann-Whitney tests were used to compare no DR to DR depending on the type of variable. To determine the correlation between two normally distributed independent variables Pearson coefficient was used; while Spearman coefficient was used for non-normally distributed variables. In the final analysis to rule out confounders, a multiple logistic regression model was constructed using a cut off of 20% for the variables. Age, HbA1c (in some patients) and use of Anti-HTN medication were included in the final analysis due to significant associations found in several other studies. The model helped identify factors that were associated with DR after adjusting for baseline characteristics. A p-value <0.05 was regarded as significant.

Ethical considerations

The University of Zambia Biomedical Research Ethics Committee (UNZABREC) approved the study (reference number 169-2019) and was carried out in compliance with the Helsinki Declaration (2006). Further approval was obtained from Ministry of Health of Zambia through the UTHs to use the data capture records.

Limitations of the study

This study was a retrospective one and some data could not be found.

RESULTS

Demographic details

A total of 1517 diabetic patients were screened from January 2016 to June 2019. Of the 1517 patients 93.8% had at least one eye of gradable quality for statistical analysis. The male patients represented 36.3% (550/1517) and the female counterparts 63.7% (967/1517). Mean age was 55. (SD 14.1), median age was 58 (SD14.1) and range was 66 years. Mean reported duration of diagnosed diabetes was 4 years (SD 3.1), median was 5 years and range was 45 years.

Table 2: Gender versus Screening Centre, N = 1,517

Sex	Screening Centre	Total
Eye Hospital	Adult Hospital
Number	%	Number	%	Number	%
Male	380	25.1	170	11.2	550	36.3
Female	613	40.4	354	23.3	967	63.7
Total	993	65.5	524	34.5	1,517	100

Table 3: Year Seen versus Screening Centre, N = 1,517

Year Screened	Screening Centre	Total
Eye Hospital	Adult Hospital
Number	%	Number	%	Number	%
2016	242	16.0	0	0	242	16.0
2017	318	21.0	0	0	318	21.0
2018	324	21.3	332	21.9	656	43.2
2019	109	7.2	192	12.6	301	19.8
Total	993	65.5	524	34.5	1,517	100

Figure 1: Year seen versus Screening Centre

Table 4: Age Group versus Screening Centre, N = 1,517

Age Group	Screening Centre	Total
Eye Hospital	Adult Hospital
Number	%	Number	%	Number	%
10 – 19	22	1.5	12	0.8	34	2.3
20 – 29	21	1.4	25	1.6	46	3.0
30 – 39	61	4.0	51	3.4	112	7.4
40 – 49	157	10.4	113	7.5	270	17.9
50 – 59	260	17.1	125	8.2	385	25.3
60 – 69	306	20.2	124	8.1	430	28.3
≥ 70	166	10.9	74	4.9	240	15.8
Total	993	65.5	524	34.5	1,517	100

Figure 2: Participants attended to according to age group

The clinical characteristics of the patients included in statistical analysis were: type 1 diabetes 10.5% (160/1517), type 2 diabetes 80.6% (1223/1517) and unspecified diabetes 8.9% (134/1517). The females had more type 2 diabetes at 63.8% (780/1223) than their male counterparts, 36.2% (443/1223). However, there was no statistical difference between the females and the males, p = 0.665; table 5. The type 2 diabetes patients had suffered more from hypertension 43.7% (534/1223) than the type 1 patients 25.0% (40/160) and this was statistically significant, p < 0.001; table 5.

Table 5: Type of DM versus other parameters

	DM Type	p
Type I	Type II	Not Known
n	%	n	%	n	%
Sex							0.665
Male	62	38.8%	443	36.2%	45	33.6%
Female	98	61.3%	780	63.8%	89	66.4%
Age group							<0.001
10 – 19	31	19.4%	3	0.2%	0	0.0%
20 – 29	20	12.5%	21	1.7%	5	3.7%
30 – 39	18	11.3%	81	6.6%	13	9.7%
40 – 49	29	18.1%	222	18.2%	19	14.2%
50 – 59	23	14.4%	330	27.0%	32	23.9%
60 – 69	23	14.4%	368	30.1%	39	29.1%
≥70	16	10.0%	198	16.2%	26	19.4%
Duration							0.493
≤ 5	76	47.5%	579	47.3%	74	55.2%
> 5 – 10	41	25.6%	289	23.6%	33	24.6%
> 10 – 15	24	15.0%	170	13.9%	14	10.4%
> 20	10	6.3%	118	9.6%	7	5.2%
Not known	9	5.6%	67	5.5%	6	4.5%
Hypertension							<0.001
Yes	40	25.0%	534	43.7%	56	41.8%
No	92	57.5%	475	38.8%	30	22.4%
Unknown	28	17.5%	214	17.5%	48	35.8%
Family history							0.011
Yes	64	40.5%	649	53.2%	68	51.9%
No	94	59.5%	572	46.8%	63	48.1%

Family history of diabetes was positive in 51.5% (781/1517) and 48.5% (736/1517) reported no family history of diabetes. Family history was statistically significantly different between the types 1 and 2 diabetic patients with 53.2% (649/1223) of type 2 diabetes having a positive family history compared to 40.5% (64/160) of the type 1 cohort; table 5.  Of the 160 type 1 diabetes patients, 89.4% (143/160) were on insulin compared to 32.3% (395/1223) of the type 2 diabetes patients. The majority 61.0% (746/1223) of the type 2 diabetes patients while 2.6% (32/1223) were on both oral hypoglycaemics and insulin.

Diabetic retinopathy

The prevalence of DR was graded based on the worst affected eye and the results are shown in Table 6. Sixty point eight per cent (60.8% (922/1517)) of all DM patients (type 1, type 2 and type unspecified) showed evidence of DR. Forty one per cent of patients graded (41.0% (623/1517)) had sight threatening DR. Five point seven per cent (5.7% (86/1517)) of all patients were graded as having proliferative DR which was distributed as 3.8% in type 1 diabetics (6/160) compared to 5.8% (71/1223) of type 2 diabetics (p = <0.001).

Prevalence of sight threatening DR was 31.3% (50/160) in type 1 diabetics compared to 43.1% (526/1517) of type 2 (p = <0.001).

Table 6: Prevalence of DR

	No DR	DR
n	Prevalence %	n	Prevalence %
Age Group
10 – 19	26	4.4	8	0.9
20 – 29	28	4.7	18	2.0
30 – 39	57	9.6	55	6.0
40 – 49	138	23.2	132	14.3
50 – 59	149	25.0	236	25.6
60 – 69	128	21.5	302	32.8
≥70	69	11.6	171	18.5
BCVA
Normal	547	91.9	721	78.2
Abnormal	48	8.1	201	21.8
Family History
Yes	322	54.1	459	49.8
No	270	45.4	459	49.8
Hypertension
Yes	210	35.3	420	45.6
No	282	47.4	315	34.2
Unknown	103	17.3	187	20.3
Duration
≤ 5	388	65.2	341	37.0
> 5 – 10	131	22.0	232	25.2
> 10 – 15	46	7.7	162	17.6
> 20	18	3.0	117	12.7
Not known	12	2.0	70	7.6
DM Type
Type I	79	13.3	81	8.8
Type II	463	77.8	760	82.4
Not Known	53	8.9	81	8.8

DISCUSSION

The DR screening programme at the UTHs meets the World Health Organization criteria for screening programmes, which stipulates that early DR must be recognized, acceptable treatment options available and recognize DR as an important public health concern [36]. Efforts to increase patient screening   for   DR   should   accompany efforts to increase patient education regarding the disease. This is the practice currently at the UTHs. Despite efforts to educate people about DR in USA in 2012, the national survey showed that 73% of adults aged 40 and over with DR were unaware of their condition [37]. At the UTHs only 25.7% of the participants were not aware of the DR challenge. This was particularly so in patients with less severe DR, shorter diabetes duration, and lack of a recent eye examination just as was reported in other studies [37]. This shows that eye health education and promotion must be an ongoing programme. Some studies have shown that follow-up rates increase most with education. A randomized, controlled study in 1999 showed that intensive education to an intervention group increased follow-up appointment rates to about 54%, from about 27% [38]. This should include the sensitisation and education of physicians and nurses dealing with DM patients in the medical departments. This proved to be very crucial in improving uptake at the UTHs by setting up a DR screening facility at the medical clinic. Health promotion was also critical in this exercise which further improved the uptake of the DR screening services.

Current DR screening guidelines recommend a retinal examination of at least once per year in type 1 diabetics 5 years after diagnosis whereas Type 2 diabetes patients should be examined immediately at the time of diagnosis and at least annually thereafter. More frequent examinations are advised for patients with progressing retinopathy [10]. The retinal examination should be conducted by an ophthalmologist, optometrist or a medical licentiate in ophthalmology (known as ophthalmic medical practitioner (OMP)) who should look through a dilated pupil using the indirect or direct ophthalmoscope or slit lamp biomicroscopy [10]. This is the practice at the UTHs.

Disparities   in   screening   rates   exist   between   ethnic, socioeconomic, and geographical groups nationally and in North Carolina [39]. A North Carolina survey of people with diabetes showed that approximately 70% of non-Hispanic whites and African Americans received eye examinations in the year before the survey, compared to 61% of Native Americans and 52% of Hispanics [39]. The study did not investigate the details of possible disparities among the people seeking DR services.

Screening rates also vary by geographic location, with rural populations having lower rates of screening, likely due to issues with access to care [40]. In this study 81.5% were from the urban setting and 18.5% from the rural setting/high density areas. Diabetes patients with retinopathy who have access to retinopathy screening at or near the office of their primary care provider may more likely be screened out of convenience compared with those who are referred to an eye health care specialist [41]. This tends to be the case in the hospital settings as well were we saw that uptake improved by 57% when the screening was introduced at the medical clinic. Other potential barriers to screening include financial difficulties and language differences [42]. This was not a barrier in our case.

Improving screening rates for DR can improve focus for research and inform policy. This can also help in enhancing interventions utilized in different communities to increase patient and provider awareness, collaboration with community-based programmes and disciplines, using electronic medical records and automatic reminders, utilizing mobile diabetes clinics, and providing services in multiple languages [42]. The University of North Carolina’s management of diabetes patients is a current example of a health care system utilizing electronic medical records, automatic reminders, and interdisciplinary collaboration [18]. The UTHs have to introduce electronic data capture and records for easy access and to prevent loss of records and to promote interdisciplinary collaboration. This should be escalated to the whole country in order to capture all DM patients and screen them for DR and later store data for planning and research purposes.

In   many   locations   around   North   Carolina, diabetes patients were seen for initial eye examinations; retaining these patients for their follow-up has been a bigger challenge [18]. This difficulty in following up with patients is not just a USA phenomenon; a study by Keenum et al. based largely on an African American population in an urban setting, less than 30% of the study participants adhered to their recommended follow-up ophthalmic examinations [43]. These patients had access to a health care centre housing both ophthalmology and primary care physicians in the same building that welcomed patients, including those without insurance [43]. Poor compliance was more so in younger patients [43]. This is what was implemented at the UTHs where a one stop DR screening clinic was created were patients were attended by the physicians and soon after that the ophthalmic team took over and conducted a thorough DR screening. This collaboration strategy led to uptake increase of 57%.

The strategy also created convenience for the patients to be attended to and patients were not required to make appointments of being attended at a later date at the UTHs EH.

The fact that this study minimized the access barriers to immediate screening and aided with scheduling follow-up, suggests that additional barriers to DR screening can be overcome through more collaboration with all the stakeholders dealing with DM. More research is needed to elucidate factors involved in low uptake and follow-up rates. Anecdotal data at the UTHs EH showed that only 25.0% of the DM patients adhered to the recommended follow up plans.

Conclusion

A one stop DR screening clinic is fundamental in improving the uptake of DR services. Cascading screening for DR requires effective strategies such collaboration between the physicians and the ophthalmologists within the hospital setting. This strategy increased uptake and follow up of DR patients at the UTHs by 57%. This led to early detection of DR and early intervention in case of sight threatening DR. Fundus photography improves DR screening and retention because screening will be done by other medical personnel and ophthalmologists will grade the photos later and come up with management plans.

Recommendations

Fundus photography telemedicine provides an alternative strategy for obtaining the retinal examination. This method involves a trained photographer taking retinal images and sending them to a remote trained reader (typically an ophthalmologist or DR graders) for interpretation. Fundus photography telemedicine has been shown to have acceptable sensitivity and specificity for screening of diabetic retinopathy compared to in-person screens. It is also cost-effective and generally well-liked by patients. System alerts can also be used in letting primary care providers know when eye examinations are due and when they have been completed, giving them the opportunity to remind and counsel patients. Putting up fundus photography across the country and training people to capture the images for transmission to the DR grading centre will prevent patients from travelling long distances to be screened.

One way of implementing tele-medicine and tele-screening is by utilisation of the training hubs for the Levy Mwanawasa Medical University (LMMU). This will enhance both training and screening of DM patients for DR and the images will be analysed and interpreted from the DR centre at LMMU.

Acknowledgments

Potential conflicts of interest. All authors have no relevant conflicts of interest.

REFERENCES

1. Shoback DG, Gardner D, eds. (2011). “Chapter 17”. Greenspan’s basic & clinical endocrinology (9th ed.). New York: McGraw-Hill Medical. ISBN 978-0-07-162243-1
2. Whiting, D.R., Guariguata, L., Weil, C., Shaw, J., 2011. IDF Diabetes Atlas: Global estimates of the prevalence of diabetes for 2011 and 2030. Diabetes Research and Clinical Practice 94, 311–321. https://doi.org/10.1016/j.diabres.2011.10.029
3. Zambia STEPS survey, 2018. https://www.who.int/ncds/surveillance/steps/Zambia-NCD-STEPS-Survey-Report-2017.pdf?ua=1
4. Bruce et al. 2007; Lecture Notes in Ophthalmology Blackwell Publishing, Massachusetts.
5. Mohamed Q, Gillies MC, Wong TY. Management of diabetic retinopathy: a systematic review. JAMA 2007;298:902–16.
6. Rohan TE, Frost CD, Wald NJ. Prevention of blindness by screening for diabetic retinopathy: a quantitative assessment. BMJ 1989;299:1198–201.
7. Writing Committee for the Diabetic Retinopathy Clinical Research Network, Gross JG, Glassman AR, et al. Panretinal photocoagulation vs intravitreous ranibizumab for proliferative diabetic retinopathy: a randomized clinical trial. JAMA. 2015;314(20):2137-2146.
8. Early photocoagulation for diabetic retinopathy. ETDRS report number 9. Early Treatment Diabetic Retinopathy Study Research Group. Ophthalmology. 1991;98(5 Suppl):766-785.
9. Wells JA, Glassman AR, Ayala AR, et al. Aflibercept, bevacizumab, or ranibizumab for diabetic macular edema: two-year results from a comparative effectiveness randomized clinical trial. Ophthalmology. 2016;123(6):1351-1359.
10. American Academy of Opthalmology. Diabetic Retinopathy PPP – Updated 2016. American Academy of Ophthalmology website. http://www.aao.org/preferred-practice-pattern/diabetic-retinop athy-ppp-updated-2016. Published February 24, 2016. Accessed October 16, 2016.
11. Lewis, A.D., Hogg, R.E., Chandran, M., Musonda, L., North, L., Chakravarthy, U., Sivaprasad, S., Menon, G., 2018. Prevalence of diabetic retinopathy and visual impairment in patients with diabetes mellitus in Zambia through the implementation of a mobile diabetic retinopathy screening project in the Copperbelt province: a cross-sectional study. Eye. https://doi.org/10.1038/s41433-018-0055-x
12. Mumba, M., Susan Lewallen, Anthony Hall, 2007. Compliance with Eye Screening Examinations among Diabetic Patients at a Tanzanian Referral Hospital. Ophthalmic Epidemiology. https://doi.org/10.1080/09286580701272079
13. Mashige, K., Notshweleka, A., Moodley, S., Rahmtoola, F., Sayed, S., Singh, S., Sardiwalla, Z., 2008. An assessment of the level of diabetic patients’ knowledge of diabetes mellitus, its complications and management in Durban, South Africa. South African Optometrist 67, 95–105. https://doi.org/10.4102/aveh.v67i3.190 
14. Al Zarea, B.K., 2016. Knowledge, Attitude and Practice of Diabetic Retinopathy amongst the Diabetic Patients of AlJouf and Hail Province of Saudi Arabia. J Clin Diagn Res 10, NC05–NC08. https://doi.org/10.7860/JCDR/2016/19568.7862 
15. Poore, S., Foster, A., Zondervan, M., Blanchet, K., 2014. Planning and developing services for diabetic retinopathy in Sub-Saharan Africa. International Journal of Health Policy and Management 4, 19–28. https://doi.org/10.15171/ijhpm.2015.04
16. Ammary-Risch, N.J., Huang, S.S., 2011. Preventing blindness from diabetes.pdf. Journal of The National Medical Association 103, 281–283.
17. Gupta, A., Aggarwal VK, Goel N, 2014. Handbook of Clinical Trials in Ophthalmology, First. ed. Jaypee Brothers Medical Publishers.
18. Skaggs J B, Zhang X, Olson D.J, Garg S, Davis R. M, Screening for Diabetic Retinopathy: Strategies for Improving Patient Follow-up, N C Med J. 2017;78(2):121-123. ©2017 by the North Carolina Institute of Medicine and The Duke Endowment. All rights reserved. 0029-2559/2017/78212
19. IDF Clinical Guidelines Task Force. Global guideline for type 2 diabetes: recommendations for standard, comprehensive, and minimal care. Diabetes Med 2006;23(June (6)):579–93.
20. UK Prospective Diabetes Study Group. Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38. BMJ 1998;317:703– 13.
21. Klein R., Klein B. E., Moss S. E., Criuckshanks K. J. 1994; The Wisconsin epidemiological study of diabetic retinopathy 14. Ten year incidence and progression of diabetic retinopathy. Arch Ophthalmol ; 112: 1217-28.
22. Scanlon Peter H, Acta Diabetol The English National Screening Programme for diabetic retinopathy 2003–2016, 2017 54:515–525 DOI 10.1007/s00592-017-0974-1
23. Ockrim Z and Yorston D. Managing diabetic retinopathy. BMJ 2010;341:c5400.
24. Schoenfeld ER, Greene JM, Wu SY, Leske MC. Patterns of adherence to diabetes vision care guidelines: baseline findings from the Diabetic Retinopathy Awareness Program. Ophthalmology 2001;108:563–71.
25. Younis N, Broadbent DM, James M, Harding SP, Vora JP. Current status of screening for diabetic retinopathy in the UK. Diabetes Med 2002;19(Suppl. 4):44–9.
26. Funatsu H, Hori S, Shimizu E, Nakamura S. Questionnaire survey on periodic ocular examination in Japanese diabetic patients. Am J Ophthalmol 2003;136:955–7.
27. Saadine JB, Fong DS, Yao J. Factors associated with followup eye examinations among persons with diabetes. Retina 2008;28:195–200.
28. Sundling V, Gulbrandsen P, Jervell J, Straand J. Care of vision and ocular health in diabetic members of a national diabetes organization: a cross-sectional study. BMC Health Serv Res 2008;8:159.
29. Puent BD, Nichols KK. Patients’ perspectives on noncompliance with diabetic retinopathy standard of care guidelines. Optometry 2004;75:709–16.
30. Ellish NJ, Royak-Schaler R, Passmore SR, Higginbotham EJ. Knowledge, attitudes, and beliefs about dilated eye examinations among African-Americans. Invest Ophthalmol Vis Sci 2007;48:1989–94. [19] Maberley DA, Koushik A, Cruess AF. Factors associated with missed eye examinations in a cohort with diabetes. Can J Public Health 2002;93:229–32.
31. Putzer GJ, Ramirez AM, Sneed K, Brownlee HJ, Roetzheim RG, Campbell RJ. Prevalence of patients with type 2 diabetes mellitus reaching the American Diabetes Association’s target guidelines in a university primary care setting. South Med J 2004;97:145–8.
32. Lewis K, Patel D, Yorston D, Charteris D. A qualitative study in the United Kingdom of factors influencing attendance by patients with diabetes at ophthalmic outpatient clinics. Ophthalmic Epidemiol 2007;14:375–80.
33. Moss SE, Klein R, Klein BE. Factors associated with having eye examinations in persons with diabetes. Arch Fam Med 1995;4:529–34.
34. Hartnett ME, Key IJ, Loyacano NM, Horswell RL, Desalvo KB. Perceived barriers to diabetic eye care: qualitative study of patients and physicians. Arch Ophthalmol 2005;123:387–91.
35. Paz SH, Varma R, Klein R, Wu J, Azen SP. Noncompliance with vision care guidelines in Latinos with type 2 diabetes mellitus: the Los Angeles Latino eye study. Ophthalmology 2006;113:1372–7.
36. Scanlon PH. The English national screening programme for sight-threatening diabetic retinopathy. J Med Screen. 2008;15(1):1-4.
37. Gibson DM. Diabetic retinopathy and age-related macular degeneration in the U.S. Am J Prev Med. 2012;43(1):48-54.
38. Basch CE, Walker EA, Howard CJ, Shamoon H, Zybert P. The effect of health education on the rate of ophthalmic examinations among African Americans with diabetes mellitus.  Am J Public Health. 1999;89(12):1878-1882.
39. Meyer RE, Herrick H. Prevalence of diabetes-related eye disease in North Carolina: findings from the North Carolina Behavioral Risk Factor Surveillance System. N C Med J. 2011;72(5):413-416.
40. Gibson DM. Eye care availability and access among individuals with diabetes, diabetic retinopathy, or age-related macular degeneration. JAMA Ophthalmol. 2014;132(4):471-477.
41. Taylor CR, Merin LM, Salunga AM, et al. Improving diabetic retinopathy screening ratios using telemedicine-based digital retinal imaging technology:  The Vine Hill study.  Diabetes Care.  2007;30(3):574-578.
42. Zhang X, Norris SL, Saadine J, et al. Effectiveness of interventions to promote screening for diabetic retinopathy.  Am J Prev Med. 2007;33(4):318-335.
43. Keenum Z, McGwin G Jr., Witherspoon CD, Haller JA, Clark ME, Owsley C. Patients’ adherence to recommended follow-up eye care after diabetic retinopathy screening in a publicly funded county clinic and factors associated with follow-up eye care use. JAMA Ophthalmol. 2016;134(11):1221-1228.

Kangwa I. M. Muma^1,3, George Zulu¹, Tyness Mumba – Malisawa¹, Jessie I. M. Nyalazi¹, Lillian Chinama – Musonda², Gardner Syakantu³

¹ University Teaching Hospitals Eye Hospital, Lusaka, Zambia

²Eye Department, Levy Mwanawasa University Teaching Hospital, Lusaka, Zambia

³School of Medicine and Health Sciences, Levy Mwanawasa Medical University, Lusaka, Zambia

Download Pdf

Abstract

Aim: To assess the awareness and knowledge levels of glaucoma among eye patients attending the University Teaching Hospitals Eye Hospital.

Background: Awareness and knowledge on glaucoma can be vital in the fight against blindness due to glaucoma. Spread of knowledge regarding some well-recognized risk factors for glaucoma may encourage more awareness. For instance, a risk factor such as a positive family history of glaucoma, raises awareness because it encourages a search for more information regarding the disease and its assessment.

Methods: This was a cross section study to assess the awareness and knowledge levels of glaucoma. A total of 1714 participants aged 18 to 98 years were recruited for the study. Respondents “having heard of glaucoma” even before they were contacted/recruited for the study were defined as “aware” and respondents having some understanding of the glaucoma disease were defined as “knowledgeable”.

Results: 1625 (94.8%) subjects completed a questionnaire that assessed their awareness and knowledge level of glaucoma. Overall 1,162 (71.5%; 95% CI: 70.7 – 73.9) participants were aware of glaucoma and 899 (55.3%; 95% CI: 51.3 – 72.1) had some knowledge about glaucoma. Awareness of glaucoma was not statistically significant in terms of age (P =0.43) and gender (P =0.87). Literate participants were four times more likely to be aware and seven times more likely to be knowledgeable than illiterate participants (P value < 0.001). The level of education had a significant association with both awareness and knowledge (p=0.001). In addition, participants who were related or known to glaucoma patients were more likely to be aware and knowledgeable than other participants (Odds ratio: 4.11; 95% CI: 2.12 – 5.45). Determinants of glaucoma awareness and knowledge were higher levels of education and family history of glaucoma.

Conclusion: Awareness and knowledge about glaucoma was fairly good among the eye patients attending the clinic at the University Teaching Hospitals Eye Hospital. Participants with lower levels of education were less aware and knew less about glaucoma than their counterparts with higher education levels. The study findings stress the need for health education and eye health promotion for effective prevention of blindness due to glaucoma.

Keywords: Awareness, glaucoma, knowledge

INTRODUCTION

Owing to the asymptomatic nature of glaucomatous progression, glaucoma may remain undetectable in most of the cases until it reaches an advanced stage [1]. This finding highlights the high burden of disease despite the existence of many effective treatments [1,2]. It is estimated that approximately 90% of glaucoma-related blindness is preventable with proper early treatment [3]. One of the most important and effective actions for early detection of glaucoma and its management may be raising public awareness and knowledge levels regarding the disease. Different levels of glaucoma awareness have been reported in different populations [4-9]. Published studies from developing countries indicate low levels of awareness, [4-6] while those from developed countries suggests higher levels of awareness [7-9]. Spread of knowledge regarding some well-recognized risk factors for glaucoma may encourage more awareness. These include a positive family history of glaucoma, which is associated with higher glaucoma awareness [5,7,10]. This is because the presence of this risk factor encourages a search for more information regarding the disease and its assessment. The relatives have been reported as an important source of information regarding glaucoma [11]. However, a high awareness level does not indicate that the individual has complete knowledge regarding glaucoma or enough understanding of the disease. For example, several studies indicate that most individuals do not have an accurate understanding of this disease despite being aware of this disease [6-9]. Almost 40% of the study participants had inadequate knowledge of glaucoma [11].

In describing the changing dynamics regarding HIV infection patterns in Zambia, Michelo et al. (2006) argues that “lifestyles, cultural practices and communication patterns may significantly differ by educational attainment. However, whenever change happens, it does most probably begin with the higher educated groups [12]. This could therefore explain the lower risk levels of glaucoma seen among higher educated groups. On the other hand, we are aware that there is no other study that has made this observation on the association of education and prevalence of POAG, thereby this study endeavouring to do that.

MATERIALS AND METHODS

Study area and population

A cross sectional survey of 1,714 participants aged 18 to 98 years old was conducted on POAG at the UTHs Eye Hospital in Lusaka, Zambia. The UTHs Eye Hospital is the national referral eye hospital which provides ophthalmological surgical and clinical services. The UTHs’ Eye Hospital is estimated to cater for more than 21,000 clients annually for both routine and morbidity driven health care. The clients that attend this clinic come from across the country and include both self- and system-referrals, representing all age groups and all ethnic groups.

A systematic random sampling using 50% – time sampling was employed which meant that of the 220 (on average) eye patients seen in the outpatient eye clinic every month, 110 were to be picked to participate in the study. This translated to a minimum 1320 participants to be recruited into the study for a period of twelve months. To cater for attrition and assuming a response rate of 80%, the sample size of the study pegged at 1,714 participants. Only 1625 (94.8%) eye patients consented to study participation of which 309 had glaucoma.

General awareness regarding glaucoma among patients was assessed using the following broad questions:

1. If they had previously heard of glaucoma
2. If they were aware of glaucoma running in families
3. If they knew about the role of intra ocular pressure in causing glaucoma
4. If the visual loss due to glaucoma is irreversible or not and that it causes blindness
5. If they were aware of any treatment modalities available for glaucoma.

We defined “awareness” as having heard about the disease. Awareness was accordingly classified. Having glaucoma knowledge was classified based on the other responses provided for the questions above.

Ethical statement

The University of Zambia Biomedical Research Ethics Committee approved the study (reference number 013-08-12). Further approval was obtained from Ministry of Health of Zambia through the UTH.

RESULTS

Of the 1,714 patients, 89 (5.2%) did not accept to be in the study due to various reasons. Therefore, a total of 1,625 people were screened giving a 94.8% response rate.

Factor	Description	Proportion (%)	Odds Ratio (95% CI)
Sex	Male	46.4	1
Female	53.6	4.2 (2.1, 7.2)

Table 1: Gender distribution of participants; N = 1625

Most of the participants were females 871 (53.6%) versus 754 (46.4%) male participants (p=0.789), [Table 1]. The age range of participants was 20 to 98 years with a mean age being 51 years.

Table 2: Awareness of glaucoma; glaucoma patients vs non-glaucoma patients N=1625

Glaucoma awareness	Yes (%)	Total Yes Average (%)	P – value
Glaucoma patients (n=309)	275 (89.0)	1,162 (71.5)	0.033
No glaucoma patients (n=1,316)	887 (67.4)

Awareness was statistically different (p=0.033) between the glaucoma patient and the non-glaucoma one, Table 2.

Table 3: Knowledge of glaucoma; glaucoma patients vs non-glaucoma patients n=1625

Knowledge on glaucoma	Yes (%)	Total Yes Average (%)	P – value
Glaucoma patients (n=309)	244 (79.1)	899 (55.3)	0.039
No glaucoma patients (n=1,316)	655 (49.8)

A total of 1,162 (71.5%; 95% CI: 70.7 – 73.9) participants were aware of glaucoma and 899 (55.3%; 95% CI: 51.3 – 72.1) had some knowledge about glaucoma (Tables 2 and 3).

Awareness of glaucoma was not statistically significant in terms of age (P =0.43) and gender (P =0.87). Literate participants were four times more likely to be aware and seven times more likely to be knowledgeable than illiterate participants (P value < 0.001). The level of education had a significant association with both awareness and knowledge (p=0.001). In addition, participants who were related or known to glaucoma patients were more likely to be aware and knowledgeable than other participants (Odds ratio: 4.11; 95% CI: 2.12 – 5.45).

A total of 199 (12.2%; 95% CI: 10.4 – 17.5) participants understood the risk of familial predisposition to glaucoma. Awareness about the irreversible nature of vision loss in glaucoma was noted in 331 (20.4%; 95% CI: 17.9 – 25.8) of the respondents. Five hundred and fifty-one (33.9%; 95% CI: 28.1 – 38.3) responded that glaucoma could be treated and 625 (38.5%; 95% CI: 37.2 – 40.4) new that glaucomatous eyes could become blind. Interestingly, 826 (50.8%; 95% CI: 44.7 – 56.7) of the respondents believed that glaucoma was the same as trachoma.

One hundred and fifteen respondents (7.1%; 95% CI: 3.9 – 10.4) considered that screening could prevent glaucoma, but only 517 (31.8%; 95% CI: 27.9 – 36.1%) had undergone screening/consulted an ophthalmologist in the previous year. Source of information for 343 (21.1%; 95% CI: 17.4 – 24.7) participants was ‘word of mouth’ from family or friends. Another 1,031 (63.4%; 95% CI: 59.1 – 68.3) participants had received information from visiting hospitals, medical personnel, eye camps or other healthcare recourses. Mass media was source of information for 251 (15.4%; 95% CI: 11.9 – 20.2) of the participants.

No associations were found between gender and awareness or knowledge of glaucoma (p = 0.765) or age (p = 0.875). 258 (76.3%; 95% CI: 72.1 – 79.3) participants were aware of glaucoma and the same number (258) of participants had some knowledge about glaucoma (Tables 1 and 2). There was a positive association between glaucoma awareness and education level (p<0.0001).

DISCUSSION

The study looked at awareness and knowledge of glaucoma in patients with glaucoma and those without glaucoma. The process of behavior changes, which culminates in action and maintenance, requires awareness and knowledge as its starting point [13]. Glaucoma is a highly prevalent ocular disease with a natural course that ultimately leads to blindness as compliance with treatment may improve with excellent patient knowledge and awareness. It may also lead to awareness among the patients’ relatives and encourage them to participate in screening programmes. Low levels of awareness of glaucoma highlight the need for public education regarding this disease. It was discovered that knowledge regarding this condition was insufficient in both the glaucoma patients and those without glaucoma. Early diagnosis and institution of treatment can result in reduction of visual impairment and blindness, as the main predictor of eventual blindness is a late presentation of the disease.

Awareness was defined as having heard about the disease. Our results indicate that 89.0% of patients with glaucoma and 67.4% of those without glaucoma were aware of glaucoma. The most striking result from our study is that only 89.0% of the cases (patients with) of glaucoma were aware of the disease. The glaucoma knowledge was high (64.5%) in our study compared to studies from Australia and India who respectively reported that 29% and 40.6% of the participants had knowledge regarding glaucoma [14,15]. This difference with our study may be attributed to the slightly high literacy rate in the country which stands at 63.4% [16].

There are some differences in awareness of glaucoma in different areas and nations. For instance, a study from Melbourne, Australia, reported awareness of glaucoma in 76% of the general population, while a population-based study from Nepal reported a very low (2.4%) level of glaucoma awareness [4,17]. In a study in Barbados, 51% of participants with glaucoma were unaware of their diagnosis compared to our study where 53.6% were aware of their diagnosis [18]. The 71.5% observed level of glaucoma awareness in this study is consistent with the data in published reports from the United States, which indicate that 70–93% of participants attending eye clinics have heard about glaucoma [7,19,20]. In another survey from Australia, 93% of 3,654 adult study participants had awareness regarding glaucoma [14].

Costa et al. (2006) and associates assessed and compared awareness regarding glaucoma in two groups of study participants. One group consisted of high level of educated American patients with glaucoma, while the other comprised low level of educated Brazilian patients with glaucoma. The authors found significant differences between these two groups and concluded that differences in educational level lead to this disparity [21]. In this study, the high number of participants with secondary and tertiary education may have led to the high rate of glaucoma awareness. This correlates well with national literacy levels which stands at over 60%.¹⁶ The findings of a study conducted by Gogate and colleagues from India are consistent with this idea. In that study, which found lower levels of glaucoma awareness, most study participants were less educated [22]. Our results indicate that level of education is the strongest explanatory variable for glaucoma awareness.

In describing the changing dynamics regarding HIV infection patterns in Zambia, Michelo et al. (2006) argues that “lifestyles, cultural practices and communication patterns may significantly differ by educational attainment. However, whenever change happens, it does most probably begin with the higher educated groups [12]. Therefore, the lower risk levels of glaucoma seen among higher educated groups may be a stage of progression. On the other hand, we are aware that there is no other study that has made this observation on the association of education and prevalence of POAG, thereby calling for additional observational studies on this factor. In addition, the glaucoma patients should also be encouraged to persuade their relatives to seek glaucoma-screening examinations. Certainly, this would lead to early diagnosis of the glaucoma in the relatives.

Patients who were unaware of their diagnosis were most probably unaware of the possibility of glaucoma being a heritable disease. In this study, only 199 of 1,625 (12.2%) participants believed that a positive family history was a risk factor for glaucoma. This may indicate the necessity of urgent action regarding patient knowledge of glaucoma and the need to provide patients with useful information regarding inheritance of glaucoma. Lack of awareness regarding heritability of glaucoma has been reported to vary from 21% to 68% [11,23]. Deokule and associates found that 41% of patients with glaucoma were aware of a risk for glaucoma in their family members, even though 45% of their family members were not screened for glaucoma [24]. Therefore, providing information to patients with glaucoma regarding the heritability of glaucoma and necessity of screening of their family members is crucial. This would encourage patients to inform their family members regarding the prognosis of glaucoma and their higher chance of being affected by this blinding disease compared to the general population. To achieve this, clinicians should periodically ask their patients about the awareness of their relatives regarding their diagnosis and whether their family members have participated in glaucoma screening examinations. The slightly low level of knowledge among the patients and non-patients highlights the importance of education for enhancing overall knowledge of glaucoma. This knowledge may encourage these individuals to seek glaucoma-screening examinations and help reduce the number of severe cases of this blinding condition.

In a study from Germany, participants’ relatives were the main sources of information regarding glaucoma [25], while mass media was found to be the main source of information in a study from India [1]. In the current study, study participants declared that close acquaintances were their main source of information. Our observations may be due to selection bias, as all of our study participants were hospital recruited. This should be considered when interpreting the results of our study.

There are inconsistent findings regarding the relationship between gender and awareness of glaucoma. In a few studies from various countries, lack of glaucoma awareness was associated with male gender [13,26], while the opposite has been reported in other studies [4,27]. Other studies found no gender differences associated with knowledge or awareness of glaucoma [14,25,28]. This study equally found the same.

Conclusions

The awareness and knowledge levels of glaucoma were fairly low. These findings suggest that there is a need for health education in this Zambia population to increase their level of awareness and knowledge of glaucoma. Education level was found to be a predictor of knowledge and awareness of glaucoma. Inadequate knowledge in the general population may be an important cause for failure to detect glaucoma early and may result in blindness from the disease.

Recommendations

Community sensitization and education would be an effective and feasible public health strategy to enhance knowledge and awareness of glaucoma, especially among individuals with a family history of the disease. This approach may ultimately reduce loss of vision due to glaucoma.

As awareness about glaucoma can lead to early detection, a very important step in preventing glaucoma-related blindness; [29] similarly educating masses will cardinal in improving awareness. Furthermore, there is a need to identify interventions that reinforce people’s attitude above the perceived level of awareness about glaucoma and to devise strategies that can influence behavior to the risk of blindness from glaucoma.

References

1. Dandona R, Dandona L, John RK, McCarty CA, Rao GN. Awareness of eye diseases in an urban population in southern India. Bull World Health Organ. 2001;79(2):96–102. Epub 2003 Sep 18. PubMed PMID: 11242828. [PMC free article] [PubMed] [Google Scholar]
2. Quigley HA, Buhrmann RR, West SK, Isseme I, Scudder M, Oliva MS. Long term results of glaucoma surgery among participants in an east African population survey. Br J Ophthalmol. 2000 ;84(8):860–4. PubMed PMID: 10906092. [PMC free article][PubMed] [Google Scholar]
3. Quigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol. 2006;90:262–267. doi: 10.1136/bjo.2005.081224. [PMC free article] [PubMed] [Cross Ref]
4. Thapa SS, Berg RV, Khanal S, Paudyal I, Pandey P, Maharjan N, Twyana SN, Paudyal G, Gurung R, Ruit S, Rens GH. Prevalence of visual impairment, cataract surgery and awareness of cataract and glaucoma in Bhaktapur district of Nepal: the Bhaktapur Glaucoma Study. BMC Ophthalmol. 2011;11:2. PubMed PMID: 21255382. [PMC free article] [PubMed] [Google Scholar]
5. Sathyamangalam RV, Paul PG, George R, Baskaran M, Hemamalini A, Madan RV, Augustian J, Prema R, Lingam V. Determinants of glaucoma awareness and knowledge in urban Chennai. Indian J Ophthalmol. 2009 ;57(5):355–60. PubMed PMID: 19700873. [PMC free article] [PubMed] [Google Scholar]
6. Tenkir A, Solomon B, Deribew A. Glaucoma awareness among people attending ophthalmic outreach services in Southwestern Ethiopia. BMC Ophthalmol. 2010 ;10:17. PubMed PMID: 20509877. [PMC free article] [PubMed] [Google Scholar]
7. Gasch AT, Wang P, Pasquale LR. Determinants of glaucoma awareness in a general eye clinic. Ophthalmology. 2000 ;107(2):303–8. PubMed PMID: 10690830. [PubMed] [Google Scholar]
8. Mitchell P, Smith W, Attebo K, Healey PR. Prevalence of open-angle glaucoma in Australia The Blue Mountains Eye Study. Ophthalmology. 1996 ;103(10):1661–9. PubMed PMID: 8874440. [PubMed] [Google Scholar]
9. Altangerel U, Nallamshetty HS, Uhler T, Fontanarosa J, Steinmann WC, Almodin JM, Chen BH, Henderer JD. Knowledge about glaucoma and barriers to follow-up care in a community glaucoma screening program. Can J Ophthalmol. 2009 ;44(1):66–9.PubMed PMID: 19169316. [PubMed] [Google Scholar]
10. Saw SM, Gazzard G, Friedman D, Foster PJ, Devereux JG, Wong ML, Seah S. Awareness of glaucoma, and health beliefs of patients suffering primary acute angle closure. Br J Ophthalmol. 2003 ;87(4):446–9. PubMed PMID: 12642308. [PMC free article][PubMed] [Google Scholar]
11. Onyekwe LO, Nwosu SN. Medical students perception of undergraduate ophthalmology training in Nnamdi Azikiwe University Nnewi Campus. Niger Postgrad Med J. 2006 ;13(4):305–8. PubMed PMID: 17203120. [PubMed] [Google Scholar] Ophthalmology 26: 907–909.
12. 12. Michelo, C., Sandøy, I. F. and Fylkesnes, K. 2006. Marked HIV prevalence declines in higher educated young people: evidence from population-based surveys (1995–2003) in Zambia. Aids, 20, 1031-1038.
13. Landers JA, Goldberg I, Graham SL. Factors affecting awareness and knowledge of glaucoma among patients presenting to an urban emergency department. ClinExpOphthalmol. 2002;30(2):104–9. PubMed PMID: 11886413. [PubMed] [Google Scholar]
14. Attebo K, Mitchell P, Cumming R, Smith W. Knowledge and beliefs about common eye diseases. Aust N Z J Ophthalmol. 1997 ;25(4):283–7. PubMed PMID: 9395831. [PubMed] [Google Scholar]
15. Celebi Ali Riza Cenk Knowledge and Awareness of Glaucoma in Participants with Glaucoma and their Normal First-Degree Relatives; Med Hypothesis Discov Innov Ophthalmol. 2018 Spring; 7(1): 40–47
16. United Nations Data, UNESCO Institute for Statistics, 2019, Zambia population clock, https://countrymeters.info/en/Zambia
17. Livingston PM, McCarty CA, Taylor HR. Knowledge, attitudes, and self-care practices associated with age related eye disease in Australia. Br J Ophthalmol. 1998 ;82(7):780–5. PubMed PMID: 9924371. [PMC free article] [PubMed] [Google Scholar]
18. Leske M. C., Connell A. M., Schachat A. P., and Hyman L., 1994, The Barbados Eye Study. Prevalence of open angle glaucoma. Arch Ophthalmol 112(6): 821-829.
19. Pöhls U G, Renner SP, Fasching PA, Lux MP, Kreis H, Ackermann S, Bender HG, Beckmann MW. Awareness of breast cancer incidence and risk factors among healthy women. Eur J Cancer Prev. 2004;13(4):249–56. PubMed PMID: 15554551. [PubMed] [Google Scholar]
20. Michielutte R, Diseker RA, Stafford CL, Carr P. Knowledge of diabetes and glaucoma in a rural North Carolina community. J Community Health. 1984 ;9(4):269–84. PubMed PMID: 6480891. [PubMed] [Google Scholar]
21. Costa VP, Spaeth GL, Smith M, Uddoh C, Vasconcellos JP, Kara-José N. Patient education in glaucoma: what do patients know about glaucoma? Arq Bras Oftalmol. 2006 ;69(6):923–7. PubMed PMID: 17273690. [PubMed] [Google Scholar]
22. Gogate P, Deshpande R, Chelerkar V, Deshpande S, Deshpande M. Is glaucoma blindness a disease of deprivation and ignorance? A case-control study for late presentation of glaucoma in India.Indian J Ophthalmol. 2011 ;59(1):29–35. PubMed PMID: 21157069. [PMC free article] [PubMed] [Google Scholar]
23. Okeke CN, Friedman DS, Jampel HD, Congdon NG, Levin L, Lai H, et al. Targeting relatives of patients with primary open angle glaucoma: The help the family glaucoma project. J Glaucoma. 2007;16:549–55. [PubMed] [Google Scholar]
24. Deokule S, Sadiq S, Shah S. Chronic open angle glaucoma: patient awareness of the nature of the disease, topical medication, compliance and the prevalence of systemic symptoms. Ophthalmic Physiol Opt. 2004 ;24(1):9–15. PubMed PMID: 14687196. [PubMed] [Google Scholar]
25. Pfeiffer N, Krieglstein GK, Wellek S. Knowledge about glaucoma in the unselected population: a German survey. J Glaucoma. 2002 ;11(5):458–63. PubMed PMID: 12362089. [PubMed] [Google Scholar]
26. Noertjojo K, Maberley D, Bassett K, Courtright P. Awareness of eye diseases and risk factors: identifying needs for health education and promotion in Canada. Can J Ophthalmol. 2006 ;41(5):617–23. PubMed PMID: 17016537. [PubMed] [Google Scholar]
27. Krishnaiah S, Kovai V, Srinivas M, Shamanna BR, Rao GN, Thomas R. Awareness of glaucoma in the rural population of Southern India. Indian J Ophthalmol. 2005 ;53(3):205–8. PubMed PMID: 16137971. [PubMed] [Google Scholar]
28. Mansouri K, Orgül S, Meier-Gibbons F, Mermoud A. Awareness about glaucoma and related eye health attitudes in Switzerland: a survey of the general public. Ophthalmologica. 2006;220(2):101–8. PubMed PMID: 16491032. [PubMed] [Google Scholar]
29. Rosenstock IM. Why people use health services. Milbank Mem Fund Q. 1966;44(Suppl):94–127. [PubMed] [Google Scholar]

Research Article
By: K I M Muma1,3, G Zulu1, T Mumba – Malisawa1, J I M. Nyalazi1, L Chinama – Musonda2, G Syakantu3
1 University Teaching Hospitals Eye Hospital, Lusaka, Zambia
2 Eye Department, Levy Mwanawasa University Teaching Hospital, Lusaka, Zambia
3 School of Medicine and Health Sciences, Levy Mwanawasa Medical University, Lusaka, Zambia
E-mail Addresses: Kangwa M. I. Muma: mkmuma@yahoo.com and drichengelo@gmail.com

Download PDF

Abstract

Aim: To assess the awareness and knowledge levels of glaucoma among eye patients attending the University Teaching Hospitals Eye Hospital.

Background: Awareness and knowledge on glaucoma can be vital in the fight against blindness due to glaucoma. Spread of knowledge regarding some well-recognized risk factors for glaucoma may encourage more awareness. For instance, a risk factor such as a positive family history of glaucoma, raises awareness because it encourages a search for more information regarding the disease and its assessment.

Methods: This was a cross section study to assess the awareness and knowledge levels of glaucoma. A total of 1714 participants aged 18 to 98 years were recruited for the study. Respondents “having heard of glaucoma” even before they were contacted/recruited for the study were defined as “aware” and respondents having some understanding of the glaucoma disease were defined as “knowledgeable”.

Results: 1625 (94.8%) subjects completed a questionnaire that assessed their awareness and knowledge level of glaucoma. Overall 1,162 (71.5%; 95% CI: 70.7 – 73.9) participants were aware of glaucoma and 899 (55.3%; 95% CI: 51.3 – 72.1) had some knowledge about glaucoma. Awareness of glaucoma was not statistically significant in terms of age (P =0.43) and gender (P =0.87). Literate participants were four times more likely to be aware and seven times more likely to be knowledgeable than illiterate participants (P value < 0.001). The level of education had a significant association with both awareness and knowledge (p=0.001). In addition, participants who were related or known to glaucoma patients were more likely to be aware and knowledgeable than other participants (Odds ratio: 4.11; 95% CI: 2.12 – 5.45). Determinants of glaucoma awareness and knowledge were higher levels of education and family history of glaucoma.

Conclusion: Awareness and knowledge about glaucoma was fairly good among the eye patients attending the clinic at the University Teaching Hospitals Eye Hospital. Participants with lower levels of education were less aware and knew less about glaucoma than their counterparts with higher education levels. The study findings stress the need for health education and eye health promotion for effective prevention of blindness due to glaucoma.

Keywords: Awareness, glaucoma, knowledge

INTRODUCTION

Owing to the asymptomatic nature of glaucomatous progression, glaucoma may remain undetectable in most of the cases until it reaches an advanced stage [1]. This finding highlights the high burden of disease despite the existence of many effective treatments [1,2]. It is estimated that approximately 90% of glaucoma-related blindness is preventable with proper early treatment [3]. One of the most important and effective actions for early detection of glaucoma and its management may be raising public awareness and knowledge levels regarding the disease. Different levels of glaucoma awareness have been reported in different populations [4-9]. Published studies from developing countries indicate low levels of awareness, [4-6] while those from developed countries suggests higher levels of awareness [7-9]. Spread of knowledge regarding some well-recognized risk factors for glaucoma may encourage more awareness. These include a positive family history of glaucoma, which is associated with higher glaucoma awareness [5,7,10]. This is because the presence of this risk factor encourages a search for more information regarding the disease and its assessment. The relatives have been reported as an important source of information regarding glaucoma [11]. However, a high awareness level does not indicate that the individual has complete knowledge regarding glaucoma or enough understanding of the disease. For example, several studies indicate that most individuals do not have an accurate understanding of this disease despite being aware of this disease [6-9]. Almost 40% of the study participants had inadequate knowledge of glaucoma [11].

In describing the changing dynamics regarding HIV infection patterns in Zambia, Michelo et al. (2006) argues that “lifestyles, cultural practices and communication patterns may significantly differ by educational attainment. However, whenever change happens, it does most probably begin with the higher educated groups [12]. This could therefore explain the lower risk levels of glaucoma seen among higher educated groups. On the other hand, we are aware that there is no other study that has made this observation on the association of education and prevalence of POAG, thereby this study endeavouring to do that.

MATERIALS AND METHODS

Study area and population

A cross sectional survey of 1,714 participants aged 18 to 98 years old was conducted on POAG at the UTHs Eye Hospital in Lusaka, Zambia. The UTHs Eye Hospital is the national referral eye hospital which provides ophthalmological surgical and clinical services. The UTHs’ Eye Hospital is estimated to cater for more than 21,000 clients annually for both routine and morbidity driven health care. The clients that attend this clinic come from across the country and include both self- and system-referrals, representing all age groups and all ethnic groups.

A systematic random sampling using 50% – time sampling was employed which meant that of the 220 (on average) eye patients seen in the outpatient eye clinic every month, 110 were to be picked to participate in the study. This translated to a minimum 1320 participants to be recruited into the study for a period of twelve months. To cater for attrition and assuming a response rate of 80%, the sample size of the study pegged at 1,714 participants. Only 1625 (94.8%) eye patients consented to study participation of which 309 had glaucoma.

General awareness regarding glaucoma among patients was assessed using the following broad questions:

1. If they had previously heard of glaucoma
2. If they were aware of glaucoma running in families
3. If they knew about the role of intra ocular pressure in causing glaucoma
4. If the visual loss due to glaucoma is irreversible or not and that it causes blindness
5. If they were aware of any treatment modalities available for glaucoma.

We defined “awareness” as having heard about the disease. Awareness was accordingly classified. Having glaucoma knowledge was classified based on the other responses provided for the questions above.

Ethical statement

The University of Zambia Biomedical Research Ethics Committee approved the study (reference number 013-08-12). Further approval was obtained from Ministry of Health of Zambia through the UTH.

RESULTS

Of the 1,714 patients, 89 (5.2%) did not accept to be in the study due to various reasons. Therefore, a total of 1,625 people were screened giving a 94.8% response rate.

Factor	Description	Proportion (%)	Odds Ratio (95% CI)
Sex	Male	46.4	1
Female	53.6	4.2 (2.1, 7.2)

Table 1: Gender distribution of participants; N = 1625

Most of the participants were females 871 (53.6%) versus 754 (46.4%) male participants (p=0.789), [Table 1]. The age range of participants was 20 to 98 years with a mean age being 51 years.

Table 2: Awareness of glaucoma; glaucoma patients vs non-glaucoma patients N=1625

Glaucoma awareness	Yes (%)	Total Yes Average (%)	P – value
Glaucoma patients (n=309)	275 (89.0)	1,162 (71.5)	0.033
No glaucoma patients (n=1,316)	887 (67.4)

Awareness was statistically different (p=0.033) between the glaucoma patient and the non-glaucoma one, Table 2.

Table 3: Knowledge of glaucoma; glaucoma patients vs non-glaucoma patients n=1625

Knowledge on glaucoma	Yes (%)	Total Yes Average (%)	P – value
Glaucoma patients (n=309)	244 (79.1)	899 (55.3)	0.039
No glaucoma patients (n=1,316)	655 (49.8)

A total of 1,162 (71.5%; 95% CI: 70.7 – 73.9) participants were aware of glaucoma and 899 (55.3%; 95% CI: 51.3 – 72.1) had some knowledge about glaucoma (Tables 2 and 3).

Awareness of glaucoma was not statistically significant in terms of age (P =0.43) and gender (P =0.87). Literate participants were four times more likely to be aware and seven times more likely to be knowledgeable than illiterate participants (P value < 0.001). The level of education had a significant association with both awareness and knowledge (p=0.001). In addition, participants who were related or known to glaucoma patients were more likely to be aware and knowledgeable than other participants (Odds ratio: 4.11; 95% CI: 2.12 – 5.45).

A total of 199 (12.2%; 95% CI: 10.4 – 17.5) participants understood the risk of familial predisposition to glaucoma. Awareness about the irreversible nature of vision loss in glaucoma was noted in 331 (20.4%; 95% CI: 17.9 – 25.8) of the respondents. Five hundred and fifty-one (33.9%; 95% CI: 28.1 – 38.3) responded that glaucoma could be treated and 625 (38.5%; 95% CI: 37.2 – 40.4) new that glaucomatous eyes could become blind. Interestingly, 826 (50.8%; 95% CI: 44.7 – 56.7) of the respondents believed that glaucoma was the same as trachoma.

One hundred and fifteen respondents (7.1%; 95% CI: 3.9 – 10.4) considered that screening could prevent glaucoma, but only 517 (31.8%; 95% CI: 27.9 – 36.1%) had undergone screening/consulted an ophthalmologist in the previous year. Source of information for 343 (21.1%; 95% CI: 17.4 – 24.7) participants was ‘word of mouth’ from family or friends. Another 1,031 (63.4%; 95% CI: 59.1 – 68.3) participants had received information from visiting hospitals, medical personnel, eye camps or other healthcare recourses. Mass media was source of information for 251 (15.4%; 95% CI: 11.9 – 20.2) of the participants.

No associations were found between gender and awareness or knowledge of glaucoma (p = 0.765) or age (p = 0.875). 258 (76.3%; 95% CI: 72.1 – 79.3) participants were aware of glaucoma and the same number (258) of participants had some knowledge about glaucoma (Tables 1 and 2). There was a positive association between glaucoma awareness and education level (p<0.0001).

DISCUSSION

The study looked at awareness and knowledge of glaucoma in patients with glaucoma and those without glaucoma. The process of behavior changes, which culminates in action and maintenance, requires awareness and knowledge as its starting point [13]. Glaucoma is a highly prevalent ocular disease with a natural course that ultimately leads to blindness as compliance with treatment may improve with excellent patient knowledge and awareness. It may also lead to awareness among the patients’ relatives and encourage them to participate in screening programmes. Low levels of awareness of glaucoma highlight the need for public education regarding this disease. It was discovered that knowledge regarding this condition was insufficient in both the glaucoma patients and those without glaucoma. Early diagnosis and institution of treatment can result in reduction of visual impairment and blindness, as the main predictor of eventual blindness is a late presentation of the disease.

Awareness was defined as having heard about the disease. Our results indicate that 89.0% of patients with glaucoma and 67.4% of those without glaucoma were aware of glaucoma. The most striking result from our study is that only 89.0% of the cases (patients with) of glaucoma were aware of the disease. The glaucoma knowledge was high (64.5%) in our study compared to studies from Australia and India who respectively reported that 29% and 40.6% of the participants had knowledge regarding glaucoma [14,15]. This difference with our study may be attributed to the slightly high literacy rate in the country which stands at 63.4% [16].

There are some differences in awareness of glaucoma in different areas and nations. For instance, a study from Melbourne, Australia, reported awareness of glaucoma in 76% of the general population, while a population-based study from Nepal reported a very low (2.4%) level of glaucoma awareness [4,17]. In a study in Barbados, 51% of participants with glaucoma were unaware of their diagnosis compared to our study where 53.6% were aware of their diagnosis [18]. The 71.5% observed level of glaucoma awareness in this study is consistent with the data in published reports from the United States, which indicate that 70–93% of participants attending eye clinics have heard about glaucoma [7,19,20]. In another survey from Australia, 93% of 3,654 adult study participants had awareness regarding glaucoma [14].

Costa et al. (2006) and associates assessed and compared awareness regarding glaucoma in two groups of study participants. One group consisted of high level of educated American patients with glaucoma, while the other comprised low level of educated Brazilian patients with glaucoma. The authors found significant differences between these two groups and concluded that differences in educational level lead to this disparity [21]. In this study, the high number of participants with secondary and tertiary education may have led to the high rate of glaucoma awareness. This correlates well with national literacy levels which stands at over 60%.¹⁶ The findings of a study conducted by Gogate and colleagues from India are consistent with this idea. In that study, which found lower levels of glaucoma awareness, most study participants were less educated [22]. Our results indicate that level of education is the strongest explanatory variable for glaucoma awareness.

In describing the changing dynamics regarding HIV infection patterns in Zambia, Michelo et al. (2006) argues that “lifestyles, cultural practices and communication patterns may significantly differ by educational attainment. However, whenever change happens, it does most probably begin with the higher educated groups [12]. Therefore, the lower risk levels of glaucoma seen among higher educated groups may be a stage of progression. On the other hand, we are aware that there is no other study that has made this observation on the association of education and prevalence of POAG, thereby calling for additional observational studies on this factor. In addition, the glaucoma patients should also be encouraged to persuade their relatives to seek glaucoma-screening examinations. Certainly, this would lead to early diagnosis of the glaucoma in the relatives.

Patients who were unaware of their diagnosis were most probably unaware of the possibility of glaucoma being a heritable disease. In this study, only 199 of 1,625 (12.2%) participants believed that a positive family history was a risk factor for glaucoma. This may indicate the necessity of urgent action regarding patient knowledge of glaucoma and the need to provide patients with useful information regarding inheritance of glaucoma. Lack of awareness regarding heritability of glaucoma has been reported to vary from 21% to 68% [11,23]. Deokule and associates found that 41% of patients with glaucoma were aware of a risk for glaucoma in their family members, even though 45% of their family members were not screened for glaucoma [24]. Therefore, providing information to patients with glaucoma regarding the heritability of glaucoma and necessity of screening of their family members is crucial. This would encourage patients to inform their family members regarding the prognosis of glaucoma and their higher chance of being affected by this blinding disease compared to the general population. To achieve this, clinicians should periodically ask their patients about the awareness of their relatives regarding their diagnosis and whether their family members have participated in glaucoma screening examinations. The slightly low level of knowledge among the patients and non-patients highlights the importance of education for enhancing overall knowledge of glaucoma. This knowledge may encourage these individuals to seek glaucoma-screening examinations and help reduce the number of severe cases of this blinding condition.

In a study from Germany, participants’ relatives were the main sources of information regarding glaucoma [25], while mass media was found to be the main source of information in a study from India [1]. In the current study, study participants declared that close acquaintances were their main source of information. Our observations may be due to selection bias, as all of our study participants were hospital recruited. This should be considered when interpreting the results of our study.

There are inconsistent findings regarding the relationship between gender and awareness of glaucoma. In a few studies from various countries, lack of glaucoma awareness was associated with male gender [13,26], while the opposite has been reported in other studies [4,27]. Other studies found no gender differences associated with knowledge or awareness of glaucoma [14,25,28].This study equally found the same.

Conclusions

The awareness and knowledge levels of glaucoma were fairly low. These findings suggest that there is a need for health education in this Zambia population to increase their level of awareness and knowledge of glaucoma. Education level was found to be a predictor of knowledge and awareness of glaucoma. Inadequate knowledge in the general population may be an important cause for failure to detect glaucoma early and may result in blindness from the disease.

Recommendations

Community sensitization and education would be an effective and feasible public health strategy to enhance knowledge and awareness of glaucoma, especially among individuals with a family history of the disease. This approach may ultimately reduce loss of vision due to glaucoma.

As awareness about glaucoma can lead to early detection, a very important step in preventing glaucoma-related blindness; [29] similarly educating masses will cardinal in improving awareness. Furthermore, there is a need to identify interventions that reinforce people’s attitude above the perceived level of awareness about glaucoma and to devise strategies that can influence behavior to the risk of blindness from glaucoma.

References

1. Dandona R, Dandona L, John RK, McCarty CA, Rao GN. Awareness of eye diseases in an urban population in southern India. Bull World Health Organ. 2001;79(2):96–102. Epub 2003 Sep 18. PubMed PMID: 11242828. [PMC free article] [PubMed] [Google Scholar]
2. Quigley HA, Buhrmann RR, West SK, Isseme I, Scudder M, Oliva MS. Long term results of glaucoma surgery among participants in an east African population survey. Br J Ophthalmol. 2000 ;84(8):860–4. PubMed PMID: 10906092. [PMC free article][PubMed] [Google Scholar]
3. Quigley HA, Broman AT. The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol. 2006;90:262–267. doi: 10.1136/bjo.2005.081224. [PMC free article] [PubMed] [Cross Ref]
4. Thapa SS, Berg RV, Khanal S, Paudyal I, Pandey P, Maharjan N, Twyana SN, Paudyal G, Gurung R, Ruit S, Rens GH. Prevalence of visual impairment, cataract surgery and awareness of cataract and glaucoma in Bhaktapur district of Nepal: the Bhaktapur Glaucoma Study. BMC Ophthalmol. 2011;11:2. PubMed PMID: 21255382. [PMC free article] [PubMed] [Google Scholar]
5. Sathyamangalam RV, Paul PG, George R, Baskaran M, Hemamalini A, Madan RV, Augustian J, Prema R, Lingam V. Determinants of glaucoma awareness and knowledge in urban Chennai. Indian J Ophthalmol. 2009 ;57(5):355–60. PubMed PMID: 19700873. [PMC free article] [PubMed] [Google Scholar]
6. Tenkir A, Solomon B, Deribew A. Glaucoma awareness among people attending ophthalmic outreach services in Southwestern Ethiopia. BMC Ophthalmol. 2010 ;10:17. PubMed PMID: 20509877. [PMC free article] [PubMed] [Google Scholar]
7. Gasch AT, Wang P, Pasquale LR. Determinants of glaucoma awareness in a general eye clinic. Ophthalmology. 2000 ;107(2):303–8. PubMed PMID: 10690830. [PubMed] [Google Scholar]
8. Mitchell P, Smith W, Attebo K, Healey PR. Prevalence of open-angle glaucoma in Australia The Blue Mountains Eye Study. Ophthalmology. 1996 ;103(10):1661–9. PubMed PMID: 8874440. [PubMed] [Google Scholar]
9. Altangerel U, Nallamshetty HS, Uhler T, Fontanarosa J, Steinmann WC, Almodin JM, Chen BH, Henderer JD. Knowledge about glaucoma and barriers to follow-up care in a community glaucoma screening program. Can J Ophthalmol. 2009 ;44(1):66–9.PubMed PMID: 19169316. [PubMed] [Google Scholar]
10. Saw SM, Gazzard G, Friedman D, Foster PJ, Devereux JG, Wong ML, Seah S. Awareness of glaucoma, and health beliefs of patients suffering primary acute angle closure. Br J Ophthalmol. 2003 ;87(4):446–9. PubMed PMID: 12642308. [PMC free article][PubMed] [Google Scholar]
11. Onyekwe LO, Nwosu SN. Medical students perception of undergraduate ophthalmology training in Nnamdi Azikiwe University Nnewi Campus. Niger Postgrad Med J. 2006 ;13(4):305–8. PubMed PMID: 17203120. [PubMed] [Google Scholar] Ophthalmology 26: 907–909.
13. Landers JA, Goldberg I, Graham SL. Factors affecting awareness and knowledge of glaucoma among patients presenting to an urban emergency department. ClinExpOphthalmol. 2002;30(2):104–9. PubMed PMID: 11886413. [PubMed] [Google Scholar]
14. Attebo K, Mitchell P, Cumming R, Smith W. Knowledge and beliefs about common eye diseases. Aust N Z J Ophthalmol. 1997 ;25(4):283–7. PubMed PMID: 9395831. [PubMed] [Google Scholar]
15. Celebi Ali Riza Cenk Knowledge and Awareness of Glaucoma in Participants with Glaucoma and their Normal First-Degree Relatives; Med Hypothesis Discov Innov Ophthalmol. 2018 Spring; 7(1): 40–47
16. United Nations Data, UNESCO Institute for Statistics, 2019, Zambia population clock, https://countrymeters.info/en/Zambia
17. Livingston PM, McCarty CA, Taylor HR. Knowledge, attitudes, and self-care practices associated with age related eye disease in Australia. Br J Ophthalmol. 1998 ;82(7):780–5. PubMed PMID: 9924371. [PMC free article] [PubMed] [Google Scholar]
18. Leske M. C., Connell A. M., Schachat A. P., and Hyman L., 1994, The Barbados Eye Study. Prevalence of open angle glaucoma. Arch Ophthalmol 112(6): 821-829.
19. Pöhls U G, Renner SP, Fasching PA, Lux MP, Kreis H, Ackermann S, Bender HG, Beckmann MW. Awareness of breast cancer incidence and risk factors among healthy women. Eur J Cancer Prev. 2004;13(4):249–56. PubMed PMID: 15554551. [PubMed] [Google Scholar]
20. Michielutte R, Diseker RA, Stafford CL, Carr P. Knowledge of diabetes and glaucoma in a rural North Carolina community. J Community Health. 1984 ;9(4):269–84. PubMed PMID: 6480891. [PubMed] [Google Scholar]
21. Costa VP, Spaeth GL, Smith M, Uddoh C, Vasconcellos JP, Kara-José N. Patient education in glaucoma: what do patients know about glaucoma? Arq Bras Oftalmol. 2006 ;69(6):923–7. PubMed PMID: 17273690. [PubMed] [Google Scholar]
22. Gogate P, Deshpande R, Chelerkar V, Deshpande S, Deshpande M. Is glaucoma blindness a disease of deprivation and ignorance? A case-control study for late presentation of glaucoma in India.Indian J Ophthalmol. 2011 ;59(1):29–35. PubMed PMID: 21157069. [PMC free article] [PubMed] [Google Scholar]
23. Okeke CN, Friedman DS, Jampel HD, Congdon NG, Levin L, Lai H, et al. Targeting relatives of patients with primary open angle glaucoma: The help the family glaucoma project. J Glaucoma. 2007;16:549–55. [PubMed] [Google Scholar]
24. Deokule S, Sadiq S, Shah S. Chronic open angle glaucoma: patient awareness of the nature of the disease, topical medication, compliance and the prevalence of systemic symptoms. Ophthalmic Physiol Opt. 2004 ;24(1):9–15. PubMed PMID: 14687196. [PubMed] [Google Scholar]
25. Pfeiffer N, Krieglstein GK, Wellek S. Knowledge about glaucoma in the unselected population: a German survey. J Glaucoma. 2002 ;11(5):458–63. PubMed PMID: 12362089. [PubMed] [Google Scholar]
26. Noertjojo K, Maberley D, Bassett K, Courtright P. Awareness of eye diseases and risk factors: identifying needs for health education and promotion in Canada. Can J Ophthalmol. 2006 ;41(5):617–23. PubMed PMID: 17016537. [PubMed] [Google Scholar]
27. Krishnaiah S, Kovai V, Srinivas M, Shamanna BR, Rao GN, Thomas R. Awareness of glaucoma in the rural population of Southern India. Indian J Ophthalmol. 2005 ;53(3):205–8. PubMed PMID: 16137971. [PubMed] [Google Scholar]
28. Mansouri K, Orgül S, Meier-Gibbons F, Mermoud A. Awareness about glaucoma and related eye health attitudes in Switzerland: a survey of the general public. Ophthalmologica. 2006;220(2):101–8. PubMed PMID: 16491032. [PubMed] [Google Scholar]
29. Rosenstock IM. Why people use health services. Milbank Mem Fund Q. 1966;44(Suppl):94–127. [PubMed] [Google Scholar]

National Influenza Center – Zambia
Pathology and Microbiology Department, University Teaching Hospital, Virology Laboratory

Download PDF

Methodology for Establishment of Epidemic Thresholds
Thresholds are calculated using Moving Epidemic Methods (MEM), a sequential analysis using R language available from: http//CRAN.R-project.org/web/package =mem) designed to calculate the duration, start and end of the annual influenza epidemic. MEM uses the 40th, 90th and 97.5th percentile established from available years of historical data to calculate threshold activities. Threshold activity for influenza is categorized as: below epidemic threshold, low, moderate, high or very high. Transmissibility of influenza can be inferred from ILI data while SARI data gives an indication of severity.

Summary

There was increased influenza activity in the third quarter of 2019 between epi-weeks 27 and 39. Rates of Influenza-Like Illness (ILI) and Severe Acute Respiratory Infection (SARI) attributable to influenza virus infection were within the moderate threshold and remained within the low seasonal threshold in week 39. This second cycle of activity was of a moderate transmissibility and severity.

ILI Surveillance:
Specimens from 895 outpatients were received from two ILI surveillance sites. 794 (89%) were adequately sampled and tested. Influenza virus was detected in 155 (20%) of these samples. 75 (48%) were identified as Influenza B, 14 (9%) Influenza A H3N2, 26 (17%) Influenza A H1N1 (pandemic), 32 (21%) influenza A Untyped and 8(5%) as Influenza A unsubtypeable.

SARI Surveillance:
During this same period, specimens were received from 1551 patients admitted to four SARI surveillance sites. 986 (64%) were adequately sampled and tested. Influenza was detected in 157 (16%) specimens; 104 (66%) of which were identified as Influenza B, 6(4%) as Influenza A H3N2, 9 (6%) as Influenza A H1N1 (pandemic), 28(18%) influenza A Untyped and 10(6%) as Influenza A unsubtypeable.

Influenza Transmissibility
Fig 1: Percentage of Influenza Positive ILI Cases1 (Out-Patient Visit Surveillance) per Epi-Week against Epidemic Thresholds Set Using 2013 – 2018 Data

Fig 2: Percentage of Influenza Positive SARI Cases1 (Hospital Admission Surveillance) per Epi-Week against Epidemic
Thresholds Set Using 2013 – 2018 Data

Fig 3: Positives samples* by influenza type and detection rate** by epi-week in 2019.

Influenza viruses circulating are predominantly influenza B and there was also random detection of influenza A. Among the influenza A viruses subtyped, H1N1 (Pandemic) and H3N2 were seen in weeks 26 -32. Most viruses were detected between weeks 8 and 37.

The virus circulation was greater at the beginning of the age spectrum but the most affected age groups were the under-fives, aged 3 years.

Fig: 5: Cumulative number of influenza types and subtypes and total number of samples tested by sentinel sites.

The total number of samples collected as at 30th October 2019, is 2446. 88% (2159/2446) of the received samples were tested and 14.5% (312/2159) were positive for influenza virus while 86% (1847/2159) were negative. The highest numbers of patients investigated were aged 10 years.

Fig: 7: Reported Influenza Cases among SARI patients’ admissions from sentinel sites in 2019.

By B. Moraes1, A. Ngomah-Moraes2, E. Munsaka3

1. Ministry of Education – Ngona Secondary School, Kawambwa, Luapula, Zambia
2. Zambia National Public Health Institute, Lusaka, Zambia
3. University of Zambia, Ringgold standard institution, Department of educational psychology and
   special education, Lusaka, Zambia

Download PDF

Sickle cell disease (SCD) is an inherited chronic disease characterised by low red blood count and infection. SCD taxes the cardiovascular system and results in reduced exercise tolerance, delayed growth and sexual development. Adolescence is a developmental stage with numerous challenges, more so for adolescents with SCD. Adolescents who suffer from chronic pain due to the SCD are usually alienated from their peers and may also be victimised by them. As a result, adolescents with SCD commonly do not disclose their condition, which may lead to further alienation and stigmatisation by their teachers as well as their peers. There is a dearth of literature on the experiences of adolescent learners with SCD. The current study therefore sought to explore the experiences of adolescent learners with SCD as they pursue their education. A phenomenological qualitative research design was used. The target population comprised adolescents with SCD, their caregivers and their teachers. The adolescents were randomly selected from among those who attend the Sickle Cell clinic every Friday at the University Teaching Hospital. Purposive sampling was used to identify caregivers and teachers. In line with the phenomenological requirement of using small samples, 5 adolescents, 5 parents and 5 teachers were used in order to more comprehensively capture their experiences. Semi-structured interviews were used to collect the data. The data from the interviews was analysed, coded and grouped according to emerging themes. The Interpretative Phenomenological Analysis (IPA) technique was used to interpret the experiences of adolescent learners with the SCD, as well as the experiences of parents and teachers. Among the adolescent learners the themes that emerged were: Being sick often; Repeating grades; need for extra lessons; and Teachers not understanding the SCD condition. Among the parents the themes that included: Children with SCD missing school often; Children with SCD needing more attention in class; Need for Extra lessons, and Teachers not understanding sickle cell disease. Among the teachers, the following were the themes: Parents and learners not wanting the SCD condition to be known; Lack of knowledge by teachers about the SCD; Need for learners with Children with SCD missing school often; Children with SCD needing more attention in class; Need for Extra lessons, and Teachers not understanding sickle cell disease. Among the teachers, the following were the themes: Parents and learners not wanting the SCD condition to be known; Lack of knowledge by teachers about the SCD; Need for learners with SCD to have individualised attention during lessons; and Inadequate support given to learners with SCD in schools. The physical and psychological burden that SCD has on school attendance by adolescents, may have a bearing on their future employment prospects, ability to form healthy relationships, and may further lead to poor mental health and to the increase in health care needs. Based on these findings, the current study recommends that the Ministry of education pays particular attention to the plight of adolescent learners with SCD in schools so that they too can be given optimal chances to succeed.

Introduction
Sickle Cell Disease (SCD) is a chronic disease that is inherited. It is categorized as a disease accompanied by frequent pain, low red blood cell count, and infection [1]. People who have SCD produce abnormal type of haemoglobin, this is sickle haemoglobin and is shaped like a sickle or others would say, like a banana. Normal cells are shaped like a ring doughnut, and can move freely through blood vessels carrying much needed oxygen to all parts of the body. In addition to all this, sickle cells clog the flow of blood and can break apart as they move through the blood vessels. Implying that, they do not deliver oxygen throughout the body as well as normal cells do. This means that a person living with Sickle Cell Disease (SCD) suffers with chronic, debilitating pain, also known as pain crisis, anaemia or even stroke. They also suffer from leg ulcers, avascular necrosis of the hip or shoulder; acute chest syndrome, organ failure and also vision loss [2].

From a global point, SCD occurs in approximately 300,000 births annually; it is mostly prevalent in malaria endemic parts of the world, primarily Africa, the Middle East and South Asia. In many African countries, 10% to 40% of the population carries the Sickle Cell gene, resulting in estimated SCD prevalence of at least 20% [3].

The statistics on the exact number of people living with SCD in the whole of Zambia are not very clear. However, the University Teaching Hospital (UTH) claims to have close to 4,000 people of all ages, with SCD who attend their Friday outpatients’ clinic. Changufu [4] wrote that in Zambia, 17or more of every 100 indigenous Zambians carries the sickle cell trait and about 200 or even more out of every 10, 000 births per year are infants who have SCD. According to his research findings [4], SCD is among the top diseases that leads to morbidity among children in countries where SCD is prevalent, most commonly in Africa and India. This genetic disorder is one of the causes of high morbidity and mortality. The recurrent pain and complications caused by the disease can interfere with many aspects of the patients’ lives including their education, employment and psychological development.

SCD can have a great impact on the patients’ psychological development. Psychological complications in patients with SCD stem from the pain and symptoms that they suffer throughout the day and night, also in retrospect, society’s attitude towards the sufferer. There is a great deal more recognition of the psychological difficulties that take place because of the biological challenges that come with the disease. Due to the many stressful experiences that commonly occur, children with SCD who have not suffered stroke may inadvertently be potentially prone to excessive anxiety, depression, moods, poor self-concept and difficulties with being accepted socially [5].
There are issues that affect their self-esteem and poor body images. The disease can also affect the physical appearance of adolescents. Small stature and delayed menarche and physical development, complications of SCD, can affect self-esteem and peer relationships. It can also limit the learners’ ability to take part in sport. This may lead to a feeling of not belonging which can affect their self–esteem [6]. Studies have identified a relationship between chronic disease and the adolescents’ physical development. The combination of psychological problems such as learning disabilities, small stature and chronic fatigue places children with SCD at a high risk of having problematic relationships [7,8]

Sickle Cell Disease taxes the cardiovascular system, or the circulatory system; which results in reduced exercise tolerance, delayed growth and sexual development. Also, a majority of males with sickle cell anaemia are likely to experience ‘priapism’ which is the painful or undesired erection that lasts from four to twelve hours. It occurs between the ages of 5 to 40 [9].
Adolescents who suffer from chronic pain are usually alienated from their peers and may also be victimised by them. It is common for SCD adolescents not to disclose their condition, and this may lead to alienation and stigmatisation by their teachers as well as their peers. There is a psychological and physical burden that SCD has on school attendance which may unknowingly prevent the patient from getting any future employment and relationships; and may further lead to poor mental health and to the requirement of higher healthcare needs. Studies have shown that the most frequent psychological problems encountered by learners with SCD include an increase in anxiety, depression, as well as social withdrawal, aggression and poor relationships [10].
In addition to this, lower educational achievement, limitations in occupation, frequent truancy and psychiatric disorders

have been noted. Symptoms of anxiety, including feeling tense, worry and fearfulness are prevalent in the adolescents with chronic illness [11]. These adolescents also face problems with parental and peer relationships are also a source of psychological distress for them. The severity of the disease also has a role to play in the academic performance of these children. Eaton, Haye, Armstrong, Pegelow and Thomas [12] came to the conclusion that adolescents who were hospitalised more frequently for pain missed a significant number of days from school as compared to the other adolescents.
Another issue that is said to influence the academic outcomes of adolescents with SCD is how the family functions. It is quite possible that this factor directly affects the academic outcome of adolescents with SCD. However, it is another factor that still needs to be researched. When we speak of family functioning, we are talking about the relationship between and among family members [13]. A family that functions well is characterised as adaptive, cohesive, and low in conflict, organised and using good communication styles [14].
Children with chronic diseases that constantly need management tend to remain dependent on their families for care and emotional support. A negative outcome of this is the overprotectiveness of the parents over their children. Parents’ anxiety and overprotectiveness can lead to restrictions of activities for the adolescent with SCD; which in turn leads to the restriction of autonomy that the adolescent desires. The manner in which parents respond to a child can lead to anxiety and distress but can also lead to much needed support that the patient requires in order to gain confidence in their ability to cope with their disease.

A third aspect that should be taken into consideration when dealing with the psychological impact of sickle cell disease on children is the attitude of teachers towards them. There has been evidence that the teachers do not take the symptoms that the child has seriously because they think it is just an attention seeking tactic or merely being disruptive [15]. It has been noted that children and adolescents with SCD often have a different set of feelings from their peers and most of the time wish to hide their disease in order to avoid constant scrutiny, judgement and isolation by peers. At times the SCD sufferer is

called lazy when in fact they are just suffering from fatigue due to anaemia.
The school environment is an important aspect of the child’s life. It is one that can help the child make sense of their illness and may even help them cope better. It is evident too that interaction with peers and teachers is beneficial to the adolescent with SCD. It is possible that the positive attitude from their teachers will help the child handle their pain better and may even help them get through crisis better. Though there is little literature in Zambia that has been published on this aspect, it is true to say that the coping with chronic pain, can be handled better when other people are involved than when one is alone [16]. Teachers are an integral part of any child’s life and their positive outlook can help the child with their psychological issues.
A lack of understanding on the part of the school can create many difficulties for the child with SCD which in turn means that, the child may not achieve or attain their potential. Teachers mostly are not able to deal with crises in school. Parents feel that teachers are ignorant and more often than not, misjudge their children in the sense that, they feel that these children exaggerate or even just pretend to be sick. About 10% of parents do not tell the school the child has SCD [17, 18]

Method
The Phenomenological design was used in this study. This is because it focuses on how people perceive the world around them, and their experiences as they go through a phenomenon. The Phenomenological Research Design is concerned with what phenomenon would present itself as we interact with the world [19]. The target population comprised adolescents with Sickle Cell Disease, one or both their caregivers (parents or guardians) and their teachers. These were drawn from the children who attend the Sickle Cell clinic every Friday at UTH. The parents were those of the adolescents and the teachers were those who have experience teaching adolescents with SCD. The sample size consisted of 5 adolescents, 5 parents and 5 teachers. These were taken from UTH in Lusaka as the starting point. In line with the interpretive phenomenological analysis which seeks to capture participants’ lived experiences, the number of participants used had to be small [19].

The adolescents who suffer from SCD were selected using purposive sampling. This is because there are close to a thousand adolescents who attend the Sickle Cell clinic at UTH. However, the research design only required a small population. Purposive sampling was carried out to target the adolescents, care givers as well as the teachers of adolescents who suffer from SCD; one of whom was a guidance teacher (as this is the teacher to whom learners are most likely to report bullying and other challenges faced) [20]. This is because purposive sampling allowed the researchers to identify the respondents who fit the required criteria. The researcher used semi structured interviews to capture participants’ experiences [21]. There were interview guides for the three groups of participants namely, the adolescent learners with SCD, their parents/ caregivers and their teachers. By using this type of interview, the researchers’ were able to steer the participants towards the discussion that were deemed important for this project.

The data from the interviews were analysed, coded and grouped according to emerging themes. Interpretative Phenomenological Analysis (IPA) was used in this study. Through phenomenological analysis a researcher produces and in many ways interprets the experiences that participants go through [19].

Findings
From the study conducted, a number of themes were generated that bring out the experiences that learners go through as they attend school. They reflect the experiences that the adolescent learners have as well as those of their parents and their teachers.
From the interviews that were carried out with the learners who suffer from SCD, a number of themes emerged that bring out the experiences that they have had. The themes are as follows: Being sick often; Grades are repeated; studies and extra lessons; Exemption from strenuous activities
and Teachers do not understand the condition.
From the interviews that were carried out with mothers, a number of aspects were brought out. These highlighted the experiences that their children had as learners who suffer from sickle cell disease. The themes that were generated are as follows; Children with SCD miss school often; Children with SCD need more attention in class; Extra lessons and classes are repeated and Teachers do not understand sickle cell disease.
The themes that were generated from the interviews carried out with teachers bring out the perspective that teachers have about learners with sickle cell disease. The themes are as follows: Parents and learners not wanting the SCD condition to be known; Lack of knowledge by teachers about the SCD; Need for individualised attention for children with SCD; Inadequate support given to learners with SCD in the schools

Discussion
The study’s purpose was to find out the experiences of adolescent learners with sickle cell disease as they pursue their education. From the themes that have been generated from the interviews, a number of issues can be outlined, that were similar in all three respondent groups. The first is the theme of parents and learners not wanting the SCD condition to be known. Under this theme, it was revealed that teachers felt frustrated by parents and learners hiding the SCD condition from them. This did not help the teachers as it led to the child being treated in the same manner as other learners. A study by Afolayan and Jolayemi [22] brought out frustration by parents, while others never come to terms with their child’s condition. Hence, they are never ready to reveal their condition to teachers or society.
I also feel that there are other teachers who do not know about this condition and so you find that because of government policy, if a child misses school for two weeks, this teacher won’t bother to find out why the child has been absent, instead, they will just cross the child out of the register. So I think parents should also be talked to so that they inform the class teachers of their child’s illness and also help this teacher to understand exactly the disease the child suffers from (Teacher 3).
Another theme is the need for individualised attention and extra lessons. These learners miss classes more often than their healthy counterparts. This absenteeism affects their studies and their performance.
… It’s not easy to study alone. I ask for help from friends. I even asked my mother to pay for extra lessons so that I can be at the same level as my friends… (Child 1)
I would…love that when he misses classes, teachers take it upon themselves to help him catch up. But this doesn’t happen. I have to go and ask the teacher to help him with school work. Usually, the teacher will first say that I should take him for extra lessons, but I cannot afford it (Mother 2).
One study [23] noted that the complications of SCD further set a student with this disease apart from the others and with this reduced quality of life,
which may in the end lead to a great deal of lost time from academic and vocational training.
Another pertinent theme is that of grades being repeated. This again stems from the fact that these learners miss school more often than their classmates. Ogunfowora, Olanrewaju and Akenzu [24] state that it is not possible for a learner to achieve academic prowess if they are constantly absent from school. These learners are often in and out of hospital and so are not able to be part of the learning process as their peers would be. One mother narrated her experience:
She, (her daughter), suffered a stroke in 2017 so I had to make her repeat. She stayed at home for a whole year, she should have written her grade 12 exams last year (Mother 5).
The repetition of grades also affects the learners in that they are forced to make new friends in the new grade and so have to explain their condition again to these new friends. Because of this, it is not farfetched to conclude that, these children end up being isolated from their fellow learners.
The findings that have been presented in this paper bring out a number of issues that need to be considered. Adolescent learners with SCD need a great deal of support. From the analysis of the data collected, it shows that parents do not want to expose their child’s condition, fearing that this same society would stigmatise them. There is also an aspect of the learners themselves not wanting to let society know that they have the SCD for fear of being stigmatised and side lined in various aspects of their educational journey as well as in various school activities.
Another factor is that not all the teachers who handle these learners understand what it entails to have this disease. It is one drawback for these learners. When a learner does not have adequate support while they are in school, their educational journey becomes difficult. The teachers hold the biggest key to the success of any learner, but more so for one who has a chronic illness such as sickle cell anaemia. Therefore, the teachers’ understanding of the disease and what a learner with this disease goes through, is important so that they can help these learners progress successfully. As stated in the report by Schartz [25], teachers who do not understand SCD tend to be harsh
or treat learners with SCD with suspicion especially when the concerned learner is constantly tired, or unable to perform tasks given to him or her with the same dexterity as their counterparts.
From the interviews conducted with parents, teachers and the adolescent learners, it became apparent that the learner who suffers from SCD require more attention than the average student. They needed to be given more time to study and extra lessons outside of normal class time. These learners, require more attention from their teachers since most of the time during the term, they miss classes and have to find a way to catch up to their classmates.
The manner in which this adolescent learner with SCD is treated can affect their psychological demeanour and may then affect their self-esteem and self -concept. From the interviews the researcher discovered that the aspect of missing school more often than not meant that the learner could not build meaningful relationships with their peers because a bigger part of their lives is spent in bed at home or in hospital. This is an issue that affects their lives a great deal.

Conclusion
It would be prudent for teachers to be sensitised on how to help these learners have a better learning experience. This will require the involvement of both the parents and adolescent learners, as well as disclosure of the condition to the teachers so as to enable them better understand the unique needs and challenges of the learners. Additionally, relevant authorities, including the Ministry of Education, must look into the plight of these adolescent learners with SCD and find ways to help both the learners and teachers such as support for the much needed extra lessons and sensitisation of the parents on the need to partner with school authorities to help their children

Declarations
Ethical Consideration: Clearance was sought from the University of Zambia Humanities and Social Sciences Research Ethics Committee. The study was conducted with the informed consent of all participants. Anonymity and confidentiality of participant data was maintained by ensuring that no names appeared in the research findings; the information collected from the participants was
recorded anonymously and used purely for research purposes.
Only the researchers had access to the information.
Availability of data and materials: The data that support the findings of this study are available from the authors upon reasonable request.
Competing Interests: The authors have declared that they have no competing interests.
Funding: All costs for data collection and preparation of the manuscript were covered by the corresponding author.
Author contributions: BM conceptualised the study and drafted the manuscript. EM and ANM contributed substantially to the literature review and manuscript writing. All named authors read and approved the final manuscript

LIST OF REFERENCES

1. National Library of Medicine [NLM]. Genetics Home Reference-Sickle Cell Disease 2012. Available at https://ghr.nlm.nih. gov/condition/sickle-cell-disease. Last accessed January 2018
2. Serjeant, GR and Serjeant BE. Sickle Cell Disease. 1992. Sickle cell disease (Vol. 3). New York: Oxford university press.
3. WHO Regional Office for Africa. Sickle cell disease prevention and control.2015. http://www.afro.who.int/en/nigeria/nige ria-publications/1775. Last accessed May, 2017
4. Changufu, K. C. Foundation of people living with sickle cell anaemia. 2005. Available at http://www.sicklecelldisease.net/ cbo/docum. Last accessed February 2018
5. Brown, R. T., Buchanan, I., Doepke, K., & Eckman, J. R. Cognitive and academic functioning in children with sickle-cell disease. Journal of Clinical Child Psychology, 1993; 22(2), 207-218
6. Thompson, R. J., Gil, K. M., Burbach, D. J., Keith, B. R., & Kinney, T. R. Role of child and maternal processes in the psycho logical adjustment of children with sickle cell disease. Journal of Consulting and Clinical Psychology, 1993; 61(3), 468-474.
7. Noll RB, Vannatta K, Koontz K, Kalinyak K, Bukowski WM, Davies WH. Peer relationships and emotional well‐being of youngsters with sickle cell disease. Child development. 1996 Apr;67(2):423-36.
8. Lennon JM, Psihogios AM, Murray CB, Holbein CE, Holmbeck GN. Promoting Resilience During the Transition to Adoles cence in Chronically Ill Children and Their Families. InChild and Adolescent Resilience Within Medical Contexts 2016 (pp. 51-75). Springer, Cham.
9. Barakat, L., Patterson, C., Weinberger, B., Simon, K., Gonzalez, E. & Dampier, C. A prospective study of the role of coping and family functioning in health Outcomes for adolescents with sickle cell disease. Journal of Paediatric Haema tology Oncology, 2007; 9, 752-760.
10. Anie, K. Psychological complications in sickle cell disease. British Journal of Haematology. 2005; 129, 723-729.
11. Pao, M., & Bosk, A. Anxiety in medically ill children/ adolescents. Depression and Anxiety, 2011; Vol 28, 40-49
12. Eaton, M. L., Haye, J. S., Armstrong, F. D., Pegelow, C. H., & Thomas, M. Hospitalizations for painful episodes: Association with school absenteeism and academic performance in children and adolescents with sickle cell anaemia. Issues in Comprehensive Paediatric Nursing, 1995; 18(1), 1-9.
13. Lewandowski AS, Palermo TM, Stinson J, Handley S, Chambers CT. Systematic review of family functioning in families of children and adolescents with chronic pain. The Journal of Pain. 2010 Nov 1;11(11):1027-38.
14. Alderfer MA, Fiese BH, Gold JI, Cutuli JJ, Holmbeck GN, Goldbeck L, Chambers CT, Abad M, Spetter D, Patterson J. Evi dence-based assessment in pediatric psychology: Family measures. Journal of Pediatric Psychology. 2007 Sep 28;33(9):1046-61.
15. Atkin K, Ahmad WI. Living with sickle cell disorder: how young people negotiate their care and treatment. In W. I. U. Ah mad (Ed.), Ethnicity, disability and chronic illness (pp. 45-66). Buckingham: Open University Press
16. Gil KM, Carson JW, Sedway JA, Porter LS, Schaeffer JJ, Orringer E. Follow-up of coping skills training in adults with sickle cell disease: analysis of daily pain and coping practice diaries. Health Psychology. 2000 Jan;19(1):85.
17. Atkin K, Ahmad WI, Anionwu EN. Screening and counselling for sickle cell disorders and thalassaemia: the experience of parents and health professionals. Social science & medicine. 1998 Dec 1;47(11):1639-51.
18. Atkin K, Ahmad W, Anionwu E. Service support to families caring for a child with a sickle cell disorder or thalassaemia: the experience of health professionals, service managers and health commissioners. Health:. 1998 Jul;2(3):305-27.
19. Willig C, Stainton-Rogers W. Qualitative research in psychology. Maidenhead: Open University Press. Google Scholar. 2008.
20. Creswell JW. Mapping the field of mixed methods research.
21. Spencer R, Pryce JM, Walsh J. Philosophical approaches to qualitative research. The Oxford handbook of qualitative research. 2014 Apr 7:81-98
22. Afolayan JA, Jolayemi FT. Parental attitude to children with sickle cell disease in selected health facilities in Irepodun Local Government, Kwara State, Nigeria. Studies on Ethno-Medicine. 2011 Apr 1;5(1):33-40.
23. Adams-Graves P, Bronte-Jordan L. Recent treatment guidelines for managing adult patients with sickle cell disease: challenges in access to care, social issues, and adherence. Expert review of hematology. 2016 Jun 2;9(6):541-52.
24. Ogunfowora OB, Olanrewaju DM, Akenzua GI. A comparative study of academic achievement of children with sickle cell anemia and their healthy siblings. Journal of the National Medical Association. 2005 Mar;97(3):405.
25. Schatz J. Brief report: Academic attainment in children with sickle cell disease. Journal of Pediatric Psychology. 2004 Dec 1;29(8):627-33.

By : B Gianetti, KE Musakanya, A Ngomah Moraes, C Chizuni, C Groeneveld, M Kapina, R Hamoonga, ML Mazaba, V Mukonka
Zambia National Public Health Institute

Download PDF

Globally, about 830 women die each day due to complications during pregnancy and childbirth [1]. In 2017 maternal associated causes were the fourth leading cause of death in Zambian women of childbearing age [2]. Zambia routinely reports maternal death occurrences and conducts investigations to determine causality. To understand trends in maternal deaths in Zambia, we performed a review of routinely reported maternal deaths using the 2018 Maternal Perinatal Death Surveillance Review. In 2018 Zambia reported 674 maternal deaths (MMR: 183 deaths per 100,000 live births). The primary causes of maternal deaths were obstetric hemorrhage and indirect causes. Obstetric hemorrhage was the most common cause of death among women ages 30-49 and women who had experienced more than one pregnancy, while indirect causes attributed to the most deaths among pregnant women ages 10-29 and first-time pregnant women. Despite committing to improve maternal health by endorsing the United Nations Sustainable Development Goals (SDG), Zambia is behind in achieving the third SDG of a maternal mortality ratio of less than 70 maternal deaths per 100,000 live births [3]. To actualize this goal, Zambia must continue comprehensive surveillance of maternal deaths as well as increase access to family planning services, quality antenatal care services, skilled birth attendants, and emergency obstetric care.

Introduction
In 2015 an estimated 303,000 maternal deaths occurred worldwide, the majority of which happened in low and middle income countries [1]. The World Health Organisation (WHO) defines a maternal death as: the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and the site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management, but not from accidental or incidental causes [4]. Maternal deaths are subdivided into two groups: direct obstetric deaths and indirect obstetric deaths. Direct obstetric deaths are defined as those resulting from obstetric complications during pregnancy, labour and the puerperium, or from interventions, omissions, and incorrect treatment. The cause of direct obstetric deaths is further classified as: pregnancies with an abortive outcome, hypertensive disorders, obstetric haemorrhage, pregnancy-related infection, obstructive labour, and unanticipated complications [4]. Indirect obstetric deaths are those caused by the aggravation of preexisting disease or disease that developed during pregnancy by the physiologic effects of pregnancy. Indirect obstetric deaths may result from cardiac disease, skeletal disease, neoplasms, endocrine conditions, autoimmune disorders, and infections, such as HIV, tuberculosis, and malaria [4]. A systematic review of global maternal deaths found that about three quarters of maternal deaths were due to direct causes and a quarter to indirect causes. Of the direct causes of maternal death, the leading causes were obstetric hemorrhage followed by hypertensive disorders and pregnancy related infections [5].
With an average total fertility rate of 4.98 births per woman among Zambian women ages 15-49 years, the population of Zambia is growing steadily [6]. However maternal mortality is a major cause of death among women. In 2017 maternal associated causes were the fourth leading cause of death in Zambian women of childbearing age [2]. According to the Saving Mothers, Giving Life Maternal Mortality Endline Census in Zambia (SMGL), maternal deaths accounted for 17.2% of all deaths in women ages 15-49 years in surveyed districts [7].
Improving maternal health is included in the third goal of the United Nations Sustainable Development Goals (SDG) framework, to which Zambia
subscribes [3]. Furthermore, maternal health is also highlighted as a primary focus in the UN Global Strategy for Women’s, Children’s and Adolescents’ Health [8]. Between 1990 and 2013, Zambia’s annualized rate of decline in maternal deaths was 0.56%. At its current rate, Zambia is not on track to reach the third SDG’s goal of a maternal mortality ratio of less than 70 maternal deaths per 100,000 live births by 2030 [3]. Understanding the underlying causes of maternal deaths through routine surveillance is crucial for reducing mortality. In this report we present a review of routinely reported maternal deaths from the 2018 Maternal Perinatal Death Surveillance Review reports in an attempt to further comprehend the nature of maternal deaths and help target policy to mitigate the burden.

Methods
Informed by an increase in maternal deaths reported by the Integrated Disease Surveillance and Response reports, we conducted a comprehensive retrospective analysis of maternal mortality data collected using the Maternal Perinatal Death Surveillance Review (MPDSR) reports from public facilities between January 2018 and January 2019. The MPDSR database is compiled by and housed in the Ministry of Health. The epidemiological week, age, location, place of death, parity, gravidity, and cause of death for each maternal death were extracted from the weekly 2018 MPDSR reports and analyzed using Microsoft Excel, Tableau, and qGIS.
Results
Six hundred and seventy four maternal deaths were reported in the 2018 MPDSR reports collated from public facilities. Of those, 38.7% of all deaths were caused

by obstetric hemorrhage, 28.3% by indirect causes, 13.1% by hypertensive disorders, 6.8% by pregnancy related infection, 5.9% by abortive outcomes, 5.3% by unknown or undocumented causes, 1.3% by unanticipated complications, and 0.4% by obstructed labour (Table 1). Maternal deaths occurred at a consistent rate throughout the year (Figure 1). Maternal deaths were reported from public facilities in all ten provinces and 101 of 117 districts throughout Zambia (Figure 2a and 2b). Lusaka province reported the highest number of maternal deaths (115 deaths) followed by Eastern (87 deaths)
and Southern (82 deaths) provinces (Table 1 and Figure 2a). Over three fourths of all maternal deaths were reported from hospitals: 37.5% from district level hospitals, 25.3% from central hospitals, and 15.3% from general hospitals (Table 2). The remaining deaths were reported from health centres (10.7%), health posts (1.8%), and the community (8.8%) (Table 2).
Seventeen percent of the maternal deaths reported among first-time pregnant women (primegravidas) were due to obstetric hemorrhage. However, hemorrhages accounted for 34% of maternal
deaths among women classified as multiparas (1-3 previous births) and nearly half (51%) of maternal deaths reported among women classified as gradmultiparas (four or more previous births) (Table 1). The most common cause of death among first-time pregnancies was indirect causes (39.0%). Indirect causes were also the most common cause of death among pregnant women ages 10-19 and 20-29 years of age (Table 1). Obstetric hemorrhage was the most common form of death among pregnant women

Table 1: Overview of maternal deaths in Zambia (2018)

Table 2: Maternal deaths by delivery site (2018)

Discussion
Over six hundred maternal deaths were reported in 2018, of which the primary causes were obstetric hemorrhage and indirect causes. Obstetric hemorrhage was most common among older women and women who had experienced multiple pregnancies; whereas indirect causes were the leading cause of maternal deaths in younger women and first-time pregnant women
Most maternal deaths are preventable. Obstetric hemorrhages are often observed in regions with poor access to health services and can be exacerbated by comorbidities such as anemia, malnutrition, and malaria. Risk factors for obstetric hemorrhage include multiple pregnancies, being over 30 years of age, anemia, abnormal placental attachment, and prior caesarean section [9]. The indirect causes of maternal death consisted of anemia, malaria, HIV related complications, cancers, and cardiac disease. Previous reports have shown that malaria contributes significantly to maternal mortality in Zambia [10]. Most maternal deaths can be avoided by addressing inadequacies in antenatal care (ANC), delays in treatment, and lack of emergency obstetric care during the delivery.
In 2016, an estimated 92% of pregnant women in Zambia received antenatal care (ANC) from a skilled provider, such as a doctor or midwife, while 6% received care from a person with no formal training. Only 2% of pregnant women reported not having sought any form of ANC [7]. Data from the MPDSR for 2018 revealed that 25% of pregnant women attended their first ANC visit during the first trimester, 27% in the second trimester, and 29% in the third trimester. Suggesting that while pregnant women are receiving ANC, many are beginning care at a late stage in their pregnancies. Furthermore, an assessment of ANC care indicated that nearly 70% of women who sought ANC in Zambia received suboptimal services [11].
In 2016, an estimated 92% of pregnant women in Zambia received antenatal care (ANC) from a skilled provider, such as a doctor or midwife, while 6% received care from a person with no formal training. Only 2% of pregnant women reported not having sought any form of ANC [7]. Data from the MPDSR for 2018 revealed that 25% of pregnant women attended their first ANC visit during the first trimester, 27% in the second trimester, and 29% in the third trimester. Suggesting that while pregnant women are receiving ANC, many are beginning care at a late stage in their pregnancies. Furthermore, an assessment of ANC care indicated that nearly 70% of women who sought ANC in Zambia received suboptimal services [11].
A case study of maternal deaths in Lundazi district in Eastern province, Zambia found that delays in access to care were the primary factors associated with maternal deaths and complications [12]. The 2015-2016 Zambia Sample Vital Registration with Verbal Autopsy Report (SAVVY) examined which delays involving access to care were associated with the greatest risk of maternal mortality. Delays associated with the decision to seek medical care were sited by 68.4% of maternal deaths reported. Delays associated with accessing or reaching a health facility were reported by 31.5% of maternal deaths, and delays associated with access to treatment upon reaching a health facility were sited by 28.4% of reported maternal deaths [13]. In Lundazi, the majority of maternal deaths lived more than five kilometres from a health facility and had low levels of literacy, indicating that long distances, and lack of maternal education may have resulted in delays to care [12]. Additional reports also found that long distances from health facilities with emergency obstetric care capability was a major risk for maternal death in Zambia [14]. Delays in decisions to seek care in Zambia were also influenced by ingrained cultural birth practice beliefs [15,16].
Poor case management and lack of skilled personnel was identified as a leading cause of maternal deaths in an assessment of maternal deaths in Copperbelt province [17]. In our review, over 90% of the maternal deaths reported occurred within a health facility. However, MPDSR data indicated that skilled birth attendants only conducted 59% of institutional deliveries in 2018. Better staffing of health facilities, training of personnel, and infrastructure to provide emergency obstetric care are required to decrease maternal mortality.
Continued surveillance of maternal deaths is required to identify gaps in antenatal and maternal care accessibility and quality. Upon reporting of a maternal death in Zambia, an investigation is launched within 24 hours to determine the cause of death. Currently, the Ministry of Health coordinates the MPDSR database. Maternal deaths are also electronically documented using the District Health Information System 2 (DHIS2) and the national Health Management Information System (HMIS) as well as captured on a weekly basis in the Integrated Disease Surveillance and Response (IDSR) reports. In addition to the electronic reporting systems, maternal deaths are reported in a paper-based format and sent to the Ministry of Health on a weekly basis. Discrepancies in the multiple surveillance databases make it difficult to ascertain the true number of maternal deaths, and require a platform on which data from all surveillance systems can be collected and collated. Zambia has already begun enhancing its surveillance efforts. The introduction of Event Based Surveillance is leading to higher reporting of community based maternal deaths. However, electronic integration of national maternal death data is required to provide a comprehensive view of maternal mortality in Zambia.
Conclusions and Recommendations
The review of the 2018 MPDSR indicates a total of over six hundred maternal deaths translating to a MMR of 183 deaths per 100,000 live births. According to the Zambia National Health Strategic Plan, the nation aims to reduce the maternal mortality ratio to less than 100 deaths per 100,000 live births by 2021. In order to decrease the MMR to reach the target established by the ZNHSP, Zambia must continue comprehensive surveillance as well as increase access to family planning services, antenatal care services, skilled birth attendants, and emergency obstetric and neonatal care.

LIST OF REFERENCES

1. Maternal mortality [Internet]. [cited 2019 May 23];Available from: https://www.who.int/news-room/fact-sheets/detail/ maternal-mortality
2. GBD Compare | IHME Viz Hub [Internet]. [cited 2019 May 23];Available from: http://vizhub.healthdata.org/gbd-compare
3. Rosa W, editor. Transforming Our World: The 2030 Agenda for Sustainable Development [Internet]. In: A New Era in Global Health. New York, NY: Springer Publishing Company; 2017 [cited 2019 May 23]. Available from: http:// connect.springerpub.com/lookup/doi/10.1891/9780826190123.ap02
4. World Health Organization, editor. The WHO application of ICD-10 to deaths during pregnancy, childbirth and the puer perium, IDC MM. Geneva: World Health Organization; 2012.
5. Say L, Chou D, Gemmill A, Tunçalp Ö, Moller A-B, Daniels J, et al. Global causes of maternal death: a WHO systematic analysis. The Lancet Global Health 2014;2:e323–33.
6. Fertility rate, total (births per woman) | Data [Internet]. [cited 2019 May 23];Available from: https://data.worldbank.org/ indicator/SP.DYN.TFRT.IN?locations=ZM
7. Central Statistical Office Zambia, University of Zambia Department of Population Studies, ICF. 2017 Zambia Maternal Mortality Endline Census in Selected Districts. Rockville, Maryland, USA: 2017.
8. Every Woman Every Child. The Global Strategy for Women’s, Children’s, and Adolescents’ Health (2016-2030). 2015.
9. Durmaz A, Komurcu N. Relationship Between Maternal Characteristics and Postpartum Hemorrhage: A Meta-Analysis Study. J Nurs Res 2018;26:362–72.
10. Zambia National Malaria Elimination Centre. Zambia’s 2018 Malaria Indicator Survey. Health Press Zambia Bull 2019;3:3–5.
11. Kyei NNA, Chansa C, Gabrysch S. Quality of antenatal care in Zambia: a national assessment. BMC Pregnancy and Child birth 2012;12:151.
12. Moyo N, Makasa M, Chola M, Musonda P. Access factors linked to maternal deaths in Lundazi district, Eastern Province of Zambia: a case control study analysing maternal death reviews. BMC Pregnancy Childbirth 2018;18:101.
13. Ministry of Home Affairs, Central Statistical Office, Ministry of Health. Zambia Sample Vital Registration with Verbal Autopsy Report (SAVVY) 2015-2016. 2018.

Akatama B. Inambao^{1, 4}, R. Kumar², B. Hamainza³, M. Makasa⁴, C.F. Nielsen⁵

1. Zambia Field Epidemiology Training Program, Ministry of Health, Lusaka, Zambia;
2. ASPPH/CDC Allan Rosenfield Global Health Fellow;
3. National Malaria Elimination Center, Lusaka, Zambia;
4. University of Zambia, Lusaka, Zambia;
5. United States Centers for Disease Control and Prevention, President’s Malaria Initiative, Zambia.

Download pdf

Citation Style For This Article: Inambao AB, Kumar R, Hamainza B, Makasa M, Nielsen CF. The Additional Effect of Focal Indoor
Residual Spraying on Incidence of Malaria in a Setting With High Insecticide Treated Bed Nets Coverage in Mansa District, Luapula
Province. Health Press Zambia Bull. 2019; 3(4); pp 12-20.

Malaria is a leading cause of morbidity and mortality especially in children under 5 years and pregnant women in Zambia [1, 2]. Environmental factors and behavioral patterns of vectors and human populations combine to provide favorable conditions for malaria transmission. Focal-Indoor Residual Spraying (IRS) was first conducted in Zambia’s Luapula Province in 2014 in areas with high burden of malaria. A quasi experimental study design comparing incidence of malaria pre and post-IRS intervention was used. Malaria is diagnosed by use of rapid diagnostic test or microscopically. Malaria incidence was calculated based on extrapolated census data for health centres. We extracted malaria morbidity data from the Health Management Information System from 2013 to 2015. There was no physical contact with participants as only secondary data were used. Epi-Info version 7 was used to analyze the data. Associations between variables were tested using a Chi-square with the level of statistical significance set at desired accuracy of 5% and 95% confidence interval.A total of 11 of 25 (44%) health facility catchment areas conducted focal-IRS in 2014 in addition to Insecticide Treated bed Nets (ITNs) use. Six of 11 (55%) IRS health facility catchment areas recorded spray coverage of above 85%.  Of the 11 IRS health facility catchment areas, 5 (45%) recorded decrease in incidence of total malaria (clinical and confirmed) in 2015 compared to 2013 whilst 6 (55%) recorded increased incidence post spraying. About 5 of 14 (36%) ITN only health facility catchment areas recorded decrease in incidence of total malaria in 2015 compared to 2013. Only 1 of 11(9%) IRS-health facility catchment areas (Muwanguni RHC) recorded decrease in incidence of lab-confirmed malaria while 91% recorded increase in 2015 compared to 2013. Use of focal IRS strategy in addition to ITNs in Mansa district did not yield additional effect compared to use of ITNs only. This strategy needs to be redesigned to ensure that questions of its efficacy and operationalization are well understood before scale-up of the concept is enhanced.

INTRODUCTION

Malaria is a major public health problem. It is transmitted to humans by an infected female anopheles mosquito bite [3] with about 3.4 billion people at risk of the disease globally, with 1.2 billion people at high risk [4].  Environmental factors and behavioral patterns of vectors and human populations combine to provide favorable conditions for malaria transmission. Geographic distribution of malaria around the world where malaria is found depends mainly on climatic factors such as temperature, humidity, and rainfalls, where malaria is transmitted in tropical and subtropical areas [4].

In Africa, an estimated 74% of the population lives in areas that are highly endemic and 19% lives in epidemic prone areas [1]. About 30% of outpatient consultations, 20-50% of hospital admissions, and 20% of under five mortality are due to malaria [5]. In 2013, there were about 198 million malaria cases and an estimated 584 000 malaria deaths [1]. Increased prevention and control measures have led to a reduction in malaria mortality rates by 47% globally since 2000 and by 54% in the WHO African Region [1].

Malaria is also endemic in Zambia and a leading cause of morbidity and mortality, especially in children under five years and pregnant women [2]. Fighting the disease is a national priority that requires a focused, comprehensive, and consistent approach in order to achieve the vision of “a malaria-free Zambia by 2030” [2]. As part of Zambia’s National Malaria Control and Elimination Strategy, a number of interventions has been launched to reduce malaria, including universal insecticide treated mosquito net coverage and indoor residual spraying (IRS) in targeted areas. The plan also includes strategies to improve malaria case management, improve diagnostic testing capacity and quality; increase coverage of three doses of sulfadoxine – pyrimethamine (SP) for intermittent preventive treatment in pregnancy (IPTp), strengthen behavior change and communication or malaria prevention and treatment and establish a robust surveillance, and monitoring and evaluation framework [2].

IRS, while typically used for low malaria risk or epidemic prone regions [6], has been further advocated for use in high and medium malaria transmission settings [7], [8]. In 2011, 30 (of 44) countries in Africa with ongoing malaria transmission used both IRS and ITN in at least some areas to further reduce the malaria burden [9]. The proportion of at risk populations protected by IRS in Africa has increased from less than 5% in 2005 to 11% in 2011 [9].

Beyond mathematical modeling of ITNs and IRS on health outcomes [10], [11], [12], few studies have empirically measured the combined effectiveness of the two interventions. In rural Gambia, a community-based trial is currently exploring the effectiveness of having ITNs and IRS against clinical malaria [13]. In Kenya, Hamel and colleagues showed that household members who were exposed to both ITNs and IRS had significantly greater protection against malaria infection than those who only used ITNs [14]; however, the study did not include a comparison group of IRS – only users. In southern Benin, on the other hand, no significant protective benefits against malaria parasite density were provided by ITNs and IRS combined, as compared to ITNs only [15].

Implementing IRS in addition to ITNs was beneficial for individuals from villages with a wide range of transmission intensities and net utilization levels [16]. Net users received additional protection from IRS. These results demonstrated that there is a supplementary benefit of IRS even when ITNs are effective. Mamta et al. (2009) proved that in spite of the constraints associated with IRS, it still has a major role in the control of malaria if implemented with proper supervision, better coverage and community participation [17].

Zambia firstly introduced focal IRS in 2014. This was conducted in seven out of the eleven districts of Luapula province in targeted health facility catchment areas with high prevalence of malaria. These include Chienge, Kawambwa, Mansa, Milenge, Mwansabombwe, Mwense and Nchelenge districts [18]. Based on this activity, this study therefore focuses on effects of focal IRS in a setting with high utilization of ITN in Mansa district of Luapula province pre and post 2014 spraying season.

METHOD

A quasi experimental study design comparing incidence of malaria pre and post IRS intervention was used. The study was conducted in Mansa District in Luapula Province of Zambia. The district had a population of 251,505 in 2014 and has a total of 30 Health facilities which include 1 level II hospital, 26 HCs and 3 health posts. Mansa serves administrative and commercial functions, being situated on a relatively featureless plateau between the Luapula River to the west and Lake Bangweulu to the east. Fishing and subsistence farming are some of the major economic activities.

The study population consisted of health centre catchment areas for 25 health facilities. The study included all the 25 health facility catchment areas in Mansa district (excluding the hospital). All the 25 health centre catchments were selected to determine effect of focal IRS on incidence of malaria because data was available for these catchment areas and were estimated to be used as study sample.

 

Over three weeks period, Data on ITN coverage (sleeping bed spaces with ITNs), focal IRS coverage (structures sprayed over targeted, population protected) and type of insecticide used   were extracted from ITNs and IRS record sheets respectively, from Mansa District Medical Office (DMO) for Health facility catchment areas. We accessed and verified available malaria data on ITNs and IRS for Mansa for the period under review (2013 to 2015). IRS was conducted in 2014 spraying season and never in 2013.

The DHIS2 database (web based) contains various data sets, but this study extracted data elements such as total malaria (clinical and confirmed), total tested cases and confirmed malaria. from HMIS dataset pertaining to malaria morbidity from 2013 (baseline data) to 2015.

Malaria data were processed to establish the malaria incidence based on census data for health facility catchment area for a particular year. The age category included all age groups (both under five and over five years old).

This study used secondary data and therefore, no standardized questionnaires were designed to collect the data. However, a data extraction form was used to capture from both focal spray data sheets obtained at the District Medical Office for 2014 spraying season, and the web-based DHIS2 database. Extracted data were edited and cleaned up to check on completeness of data. All information extracted was confidentially stored and data backup kept in an external hard drive at the end of the study for future reference.

The analysis was conducted to establish IRS coverage for the single spraying season (2014). We obtained total malaria and laboratory confirmed malaria morbidity data retrieved from HMIS on the web based DHIS2 database to calculate malaria incidence rates using pivot tables of Microsoft Excel sheet, based on Central Statistical Office (CSO) population data for health facilities in Mansa District. We determined the change in incidence of malaria pre and post focal spraying, 2013 data being the baseline when only ITNs were used.

Data were then transferred and entered into Microsoft excel sheet and Epi-Info statistical package to analyze and compare descriptive statistics and incidence rates for the two groups. Group 1 included the health facility catchment areas that received ITNS only during the study period and group 2 included health facility catchment areas that received both ITNS and focal IRS for malaria intervention.

The spraying related variables that include malaria incidence rate, proportion of structures sprayed, population covered by the spray and timing of spraying, and type of insecticide used were analyzed. Associations between variables were tested using a Chi-square with the level of statistical significance set at desired accuracy of 5% and 95% confidence interval to measure the public health impact of focal IRS. Risk ratio statistical methods of analysis were used to compare the measure of association between IRS and non-IRS health facility catchment areas in Mansa district in relation to malaria incidence.

In order to determine the additional effect of IRS, the monthly morbidity data for this study were aggregated to 12 months post IRS to analyze and evaluate the 12-month effect of focal spraying on malaria incidence for the 25 health facility catchment areas.

The non-combined effect was measured by taking into account pre-IRS malaria morbidity data where only ITNs were used to determine malaria incidence before focal IRS was implemented in 2013.The combined effect was measured by determining outcome of interest (malaria incidence) in 2014 when both focal IRS and ITNs where used as interventions to counter the transmission of malaria. The combined effect henceforth, were measured 12 months post focal IRS (by Dec 2015).

Ethical considerations

There was no physical contact with participants as only secondary data were used. Ethics approval was received from ERES Converge, whilst permission to conduct the study was obtained from the Ministry of Health and via Mansa District Medical Office. All information extracted was confidentially stored at the end of the study. The information generated from this study helped improve individual participation in future IRS services and offered better health service provision that would contribute to the reduction of malaria disease burden in the community as a whole.

RESULTS

Data for the 25 Health facility catchment areas were abstracted to calculate and analyze malaria incidence rates pre and post focal indoor residual spraying period for 2013 to 2015.

Mansa district had a total population of 257, 517 by 2015 with a CSO 2010 projected annual growth rate of 2.1%. Of the total number of malaria cases (189,407) recorded in 2015, at least 163,135 cases (86%) were laboratory confirmed. Overall, the incidence of total malaria decreased by 0.4% from 739/1000 persons per year in 2013 to 736/1000 persons per year in 2015. With regard to lab-confirmed malaria, an increase of 74% occurred between 2013 and 2015. Total malaria was fluctuating somewhat while lab-confirmed malaria increasing substantially, largely due to increased confirmatory testing.

The Mansa district recorded ITN coverage of 100% during 2013 to 2015. All the 25 health facilities received and distributed ITNs into the community according to the available sleeping bed spaces. This provided 100% protection to the population of Mansa district.

A total 11 of 25 (44%) health facilities conducted focal IRS in their targeted catchment areas in 2014 in addition to use of ITNs. At least 7 out of 11 (64%) IRS health facilities recorded spray coverage of above 85% in their catchment areas. Mibenge RHC (96%) had the highest IRS coverage followed by Mabumba RHC (94%) and Buntungwa UHC (93%). The lowest coverage was recorded in Senama UHC (65%) followed by Mutiti RHCs with 74%. All the targeted IRS health facility catchment areas used an insecticide commonly known as Actellic 300CS during the 2014 spraying season. Mansa district recorded average spray coverage of 84% during October to December 2014 spray season.

A total of 5 of 11 (45%) IRS health facilities recorded decrease in incidence of total malaria in their catchment areas in 2015 compared to 2013 whilst 6 of 11 (55%) IRS health facilities recorded increase in incidence of total malaria post spraying.

Central Urban HC (-46%) recorded the highest percent decrease in incidence of malaria after IRS followed, Mabumba RHC (-28%) and Buntungwa RHCs (-23%) by the end of 2015. Highest percent increase in incidence of malaria after spraying was observed in Matanda RHC (80%) followed by Mibenge (34%) and Mantumbusa RHC (28%) among others. On average, total malaria incidence among IRS-health facility catchment areas slightly decreased by 0.69% by end 2015 compared to 2013.

total of 14 of 25 (56%) health facilities did not conduct IRS in their catchment areas but used ITNs only as a strategy to prevent malaria. At least 5 of 14 (36%) ITN only health facilities recorded decrease in incidence of total malaria in 2015 compared to 2013, whilst 9 of 14 (64%) recorded increase in incidence. Lubende RHC (-36%) had the highest percent decrease in incidence of total malaria followed by Mano (-31%) and Moloshi RHCs (-21%). Highest percent increase in incidence of malaria after spraying was observed in Kansenga RHC (147%) followed by Musaila RHC (83%) and Nsonga HP (73%) by the end of 2015.

On average, total malaria incidence for ITN only health facilities increased by 155/1000 persons (20%) by end of 2015 compared to 2013. Based on the exposure – outcome analysis, the risk ratio of 0.85 (0.43 – 1.65) with p-value of 0.69 indicated non-statistically significant difference in incidence of total malaria between IRS and ITN only health facilities.

At least 1 of 11(9%) IRS-health facilities (Muwanguni RHC) recorded decrease in incidence of lab-confirmed malaria by 238 (40%) while 10 of 11 IRS-health facilities recorded increase in 2015 compared to 2013. Highest percent increase in incidence was observed in Mabumba (136%), Buntungwa UHC (116%), Chisembe and Senama UHC catchment areas with 107% increase respectively. On average, confirmed malaria incidence in IRS health facilities increased from 547 to 890 per thousand (63%) by end of 2015 compared 2013.

At least 1 of 14 (7%) of  non-IRS health facilities (Mano RHC) recorded a decrease (-2%) in incidence of confirmed malaria from 517 per 1000 persons in 2013 to 506 per 1000 persons in 2015  while a total of 13 out of 14 (93%) ITN only health facilities recorded increased incidence in  2015 compared to 2013. Highest percent increase in incidence of confirmed malaria was observed in Musaila followed by Kalaba and Kansenga RHC catchment areas by the end of 2015. On average, total malaria incidence for ITN only health facilities increased from 359 to 789/1000 persons (120%) by end of 2015 compared to 2013.

Based on the exposure – outcome analysis, the risk ratio of 0.98 (0.77 – 1.24) with p-value of 1.0 indicated non-statistically significant difference in incidence of lab-confirmed malaria between IRS and non-IRS health facilities.

Table 2:  Demographic and Malaria disease characteristics, Mansa District, 2013 to 2015

Year	Population (CSO)	Projected annual pop growth rate	Total malaria cases	Lab-confirmed malaria cases	Total malaria  incidence / 1000 persons	Lab-conf malaria incidence / 1000 persons
2013	245,510	2.1	181,384	89,472	739	364
2014	251,505	2.1	193,781	146,111	770	581
2015	257,517	2.1	189,407	163,135	736	633

Table 3: Coverage of Sprayed Unit Structures by Health Facility Catchment Area, October to December, 2014, Mansa District

Health facility catchment area	Total structures targeted (n)	Total structures sprayed (n)	Spray coverage (%)
Mibenge RHC	532	512	96%
Mabumba RHC	1,680	1,581	94%
Buntungwa UHC	2,566	2,386	93%
Mantumbusa RHC	757	688	91%
Matanda RHC	502	450	90%
Muwanguni RHC	427	366	86%
Chisembe RHC	516	436	84%
Central UHC	7,477	6,147	82%
Kabunda RHC	689	613	89%
Mutiti RHC	297	221	74%
Senama UHC	2,658	1,738	65%
Average	18,101	15,138	84%

Table 4: Comparison of Total Malaria Incidence for IRS-Health Facility Catchment Areas Pre and Post Spraying Period, Mansa, 2013 and 2015

IRS Health facility	Total malaria incidence, 2013 (Pre-IRS)	Total malaria incidence, 2015 (Post-IRS)	Change in incidence	Percent difference	Comment on change in incidence
Mabumba RHC	1,824	1,315	-509	-28	Decreased
Kabunda RHC	1,795	1,700	-95	-5	Decreased
Chisembe RHC	1,032	1,158	126	12	Increased
Mutiti RHC	1,004	1,027	23	2	Increased
Central UHC	922	501	-421	-46	Decreased
Senama UHC	854	957	103	12	Increased
Mantumbusa RHC	817	1,046	229	28	Increased
Mibenge RHC	805	1,082	277	34	Increased
Buntungwa UHC	797	614	-183	-23	Decreased
Muwanguni RHC	785	767	-183	-2	Decreased
Matanda RHC	486	875	389	80	Increased
	Average	1,011	1,004	-7	-0.69	Decreased

Table 5: Comparison of Total Malaria Incidence for ITN only Health Facilities Catchment Areas Pre and Post Spraying Period, Mansa, 2013 and 2015

Non-IRS Health facility	Total malaria incidence 2013 (Pre-IRS)	Total malaria incidence 2015 (Post IRS)	Change in incidence	Percent difference	Comment on change in  incidence
Lubende	1,696	1081	-615	-36	Decreased
Kalyongo RHC	1,154	1640	486	42	Increased
Fimpulu RHC	876	1253	377	43	Increased
Paul Mambilima RHC	848	685	-163	-19	Decreased
Kalaba RHC	847	1179	332	39	Increased
Luamfumu RHC	808	643	-165	-20	Decreased
Mano RHC	754	519	-235	-31	Decreased
Ndoba RHC	746	1091	345	46	Increased
Kansenga RHC	725	1788	1063	147	Increased
Musaila RHC	656	1202	546	83	Increased
Katangwe RHC	469	528	59	13	Increased
Moloshi RHC	398	314	-84	-21	Decreased
Chisunka RHC	388	431	43	11	Increased
Nsonga HP	236	408	172	73	Increased
Average	757	912	155	20	Increased

Table 6: Laboratory Confirmed Malaria Incidence, IRS-Health Facility Catchment Areas, Mansa District, 2013 – 2015

IRS Health facility	Conf. malaria incidence 2013 ( Pre IRS)	Conf. malaria incidence 2015 (Post IRS)	Change in incidence	Percent difference	Comment on change in incidence
Buntungwa UHC	208	450	242	116	Increased
Central UHC	377	395	18	5	Increased
Chisembe RHC	462	958	496	107	Increased
Kabunda RHC	1,221	1647	426	35	Increased
Matanda RHC	456	875	419	92	Increased
Mabumba RHC	552	1305	753	136	Increased
Mantumbusa RHC	642	1046	404	63	Increased
Mibenge RHC	497	964	467	94	Increased
Mutiti RHC	560	861	301	54	Increased
Senama UHC	446	925	479	107	Increased
Muwanguni RHC	599	361	– 238	-40	Decreased
Average	547	890	343	63	Increased

Table 7: Laboratory Confirmed Malaria Incidence per 1000 person, ITN only Health Facility Catchment Areas, Mansa District, 2013 – 2015

ITN only Health Facility	Conf. malaria Incidence 2013 (Pre IRS)	Conf. malaria incidence 2015 (Post IRS)	Change in incidence /1000 persons	Percent difference	Comment on change in incidence
Luamfumu RHC	296	448	152	51	Increased
Kalyongo RHC	543	1632	1089	201	Increased
Lubende	868	1078	210	24	Increased
Kansenga RHC	510	1695	1185	232	Increased
Mano RHC	517	506	-11	-2	Decreased
Kalaba RHC	259	1165	906	350	Increased
Moloshi RHC	193	294	101	52	Increased
Paul Mambilima RHC	477	685	208	44	Increased
Ndoba RHC	514	862	348	68	Increased
Nsonga HP	210	401	191	91	Increased
Musaila RHC	86	966	880	1,023	Increased
Chisunka RHC	217	424	207	95	Increased
Fimpulu RHC	463	1183	720	156	Increased
Katangwe RHC	227	500	273	120	Increased
Average	359	789	430	120	Increased

DISCUSSION

This study was set out to determine whether there is an additional benefit of using focal IRS in a setting with high ITN use compared to the practice of use of ITNs alone. The main outcome variable was change in incidence of malaria disease assessed using abstracted malaria morbidity data for health facility catchment areas in Mansa district between 2013 (pre-IRS) and 2015 (post-IRS).

Overall, Mansa district recorded a slight decrease in total malaria incidence of less than 1% in 2015 (post IRS) compared to 2013 (pre-IRS). A proportion of more than 80% of recorded cases in 2015 were laboratory confirmed by either use of Rapid Diagnostic Test or microscopically (Table 1). This signified an improvement in adherence to testing recommendations compared to 2013. The district recorded average spray coverage of more than 80% during 2014 spraying season using Actellic 300CS, a new long-lasting micro-encapsulated formulation of the organophosphate insecticide pirimiphos-methyl. This insecticide has been specifically designed for use in indoor residual spraying (IRS) programs to provide up to one year’s residual control of mosquitoes and other public health pests. Actellic 300CS is effective against pyrethroid resistant Anopheles, Aedes and Culex species [19].

Mansa district, conducted focal indoor residual spraying strategy in combination with ITN usage, targeting health facility catchment areas with high incidence of malaria and also considering cost effectiveness compared to carrying out generalized spraying.  Spraying was conducted in a total of 11 out of 25 health facilities from October to December of 2014 in addition to use of ITNs with over half (63%) having achieved spray coverage of above 85% (table 3). We however, observed that conducting IRS during this time frame may have a negative impact on the coverage due to high refusals and or poor community acceptability of the programme presumably due to heightened rainfall and busy farming schedules by some of the community members. Commencing IRS slightly earlier would improve spray coverage.

The results further showed that almost half of the IRS health facility catchment areas had recorded relatively reduced incidence of malaria after spraying compared to the incidence they had before spraying signifying probable effect of spraying in addition to use of ITNs. Conversely, half of the health facilities that achieved spray coverage above 85% recorded increase in incidence of malaria, with Matanda RHC almost doubling the incidence in 2015 compared to 2013. This seemed unusual and prompted us to further ask ourselves questions concerning some operational dynamics, such as whether the insecticide solution wasn’t well formulated, maybe rightful residue was not applied on the walls, whether all the rooms were sprayed or not or emerging insecticide resistance among others. The average effects of spraying showed insignificant decrease (0.69%) in incidence among sprayed health facilities comparing the 12-month malaria incidence rates for unsprayed health facility catchment areas (20% increase) in 2015 with the similar period in the preceding 2 years, 2013.

The findings on incidence of total malaria in ITN only health facilities demonstrated that 5 out of 14 (less than half) of the facilities recorded a decrease in incidence of malaria while about  64% of health facilities recorded increased incidence in 2015 compared to 2013. Comparatively, we observed that incidence of total malaria either increased or decreased in both sprayed and non-sprayed health facility catchment areas regardless of spray status. There was an insignificant difference in change of incidence of malaria between IRS and ITN only health facilities. The exposure – outcome analysis indicated the risk ratio of 0.89 (0.43 – 1.65) demonstrating a non-statistically significant difference in incidence of total malaria between IRS and ITN only health facilities suggesting that provision of focal IRS and ITNs was relatively not protective compared to use of ITNs only.

We further analyzed incidence of laboratory confirmed malaria for both IRS and ITN only health facilities. Among the IRS health facilities, Muwanguni RHC was the only health facility that recorded   decrease in incidence of lab-confirmed malaria in 2015 while only Mano RHC recorded decreased incidence among ITN only health facilities.  In view of the analysis above, these results demonstrates that there was no difference in effect of both interventions on incidence of lab-confirmed malaria post IRS period entailing that there were no advantages of combining IRS with ITNs relative to using ITNs alone in Mansa district. We are however, mindful that this outcome may be different in certain situations, since there are numerous confounding factors that can affect the results.

LIMITATIONS OF THE STUDY

This study focused on the additional effect of focal indoor residual spraying on incidence of malaria in a setting with high insecticide treated bed nets coverage in Mansa district, Luapula province. This being the case, the findings may not be generalized to other parts of Zambia since only health facility catchment areas in Mansa provided information for this study.

CONCLUSION AND RECOMMENDATIONS

Based on the findings of the study, it became clear that even though combining IRS and ITNs is increasingly being practiced and are already known to confer significant benefits against malaria [21], [15] the results for Mansa district could not give us sufficient evidence as to whether it is indeed better than ITNs on their own. This is especially evident when we analyzed incidence of laboratory confirmed malaria that showed no difference in outcome between IRS and ITN only health facilities. We therefore concluded that, use of focal IRS strategy in addition to ITNs in Luapula province and Mansa district in particular did not yield additional effect compared to use of ITNs only.

This strategy needs to be redesigned to ensure raised questions of its efficacy and operationalization are well understood by stakeholders before scale-up of the concept is enhanced. Therefore, to maximize any possible additional benefits from IRS/ITN co-applications, rigorous field evidence, supported by mathematical modeling where necessary should be pursued to support the entire process of decision making, including the selection of which insecticides to be used for IRS and what type of ITNs to use. This will require different kinds of studies on combined ITN-IRS use to include: 1) experimental hut investigations where efficacies of the combinations are directly assessed against wild free-flying malaria vectors in malaria endemic areas, 2) mathematical simulation incorporating characteristics of candidate insecticidal applications to estimate likely benefits of the combinations in different scenarios, 3) long-term community-wide studies to determine effectiveness of the combinations and 4) cost benefit analysis of the combinations compared to individual methods on their own and also to other existing interventions.

As correlations between these two methods and accrued health benefits become better understood, their acquisition and utilization will require that the implementation is monitored closely to ensure proper use and optimal efficacy, maximum cost effectiveness and also to prevent problems such as insecticide resistance. On the other hand, health authorities in Mansa district need to ensure that important gains so far achieved from existing interventions are not lost especially as malaria control enters the phase of intensive and sustained vector control.

Acknowledgements

This work was funded by the United States Centers for Disease Control and Prevention and the US President’s Malaria Initiative. The author acknowledges them with gratitude for supporting and funding the manuscript writing workshop on behalf of the Zambian Field Epidemiology Training Program (FETP). We also acknowledge the role the Ministry of Health is undertaking in coordinating, supporting and ensuring that FETP becomes a success in Zambia.

We would like to thank the following: Dorothy Southern, for providing mentorship and technical skills during training; Nicole Bellows, for providing guidance and mentorship towards the production of this document and Dr. Henry K. Baggett, for reviewing and providing technical advice towards the production of this document. This publication was supported by Cooperative Agreement Number U36OE000002 from the Centers for Disease Control and Prevention and the Association of Schools and Programs of Public Health. The findings and conclusions of this publication do not necessarily represent the official views of CDC or ASPPH.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

Extracted the data: AI, Analyzed the data: AI, RK. Wrote the paper: AI, RK, BH, MM, CFN. All authors read and approved the final manuscript.

 

REFERENCES

1. World Health Organization (2014). “Ten Facts on Malaria,” WHO, last modified December.
2. MOH (2011). National malaria strategic plan 2011–2015: consolidating malaria gains for impact. Lusaka Zambia: Ministry of Health; 2011.
3. Cook and Zumla (2009). Mansons Tropical Disease 21st ed. Saunders. London.
4. World Health Organization (2014). World Malaria Report 2014. Geneva: World Health Organization.
5. World Health Organization (2003), African malaria report 2003. Harare: World Health Organization, Regional Office for Africa; 2004.
6. World Health Organization (2007). Insecticide-treated mosquito nets: a WHO position statement. Geneva: WHO.
7. Kolaczinski, K., Kolaczinski, J., Kilian, A., & Meek, S. (2007). Extension of indoor residual spraying for malaria control into high transmission settings in Africa. Transactions of the Royal Society of Tropical Medicine and Hygiene, 101(9), 852-853
8. Kim D, Fedak K, Kramer R (2012). Reduction of malaria prevalence by indoor residual spraying: a meta-regression analysis. AmJTrop Med Hyg
9. World Health Organization (2012). World Malaria Report 2012. Geneva: World Health Organization.
10. Chitnis N, Schapira A, Smith T, Steketee R: Comparing the effectiveness of malaria vector-control interventions through a mathematical model. AmJTrop Med Hyg 2010, 83:230–240.
11. Griffin JT, Hollingsworth TD, Okell LC, Churcher TS, White M, et al. (2010). Reducing Plasmodium falciparum malaria transmission in Africa: a model-based evaluation of intervention strategies. PLoS Med 7.
12. Yakob L, Dunning R, Yan G: Indoor residual spray and insecticide-treated bednets for malaria control: theoretical synergisms and antagonisms. J R Soc 2010, doi:10.1098/rsif.2010.0537.
13. Pinder M, Jawara M, Jarju LBS, et al. (2014). To assess whether indoor residual spraying can provide additional protection against clinical malaria over current best practice of long-lasting insecticidal mosquito nets in The Gambia: study protocol for a two-armed cluster-randomized study.
14. Hamel MJ, Otieno P, Bayoh N, Kariuki S, Were V, et al. (2011). The combination of indoor residual spraying and insecticide-treated nets provides added protection against malaria compared with insecticide-treated nets alone. Am J Trop Med Hyg. 2011; 85: 1080–86.
15. Corbel V, Akogbeto M, Damien GB, Djenontin A, Chandre F, et al. (2012). Combination of malaria vector control interventions in pyrethroid resistance area in Benin: a cluster randomized controlled trial. Lancet Infect Dis 12: 617–26.
16. West PA, Protopopoff N, Wright A, Kivaju Z, Tigererwa R, Mosha FW, et al. (2015) Enhanced Protection against Malaria by Indoor Residual Spraying in Addition to Insecticide Treated Nets: Is It Dependent on Transmission Intensity or Net Usage? Muleba, Tanzania. PLoS Med 2014
17. Mamta, D., Prajapat, P. B., and Dinkar R., (2009). Impact of Indoor Residual Spray with Synthetic Pyrethroid in Gandhinagar District, Gujarat. Indian Journal of Community Med.
18. NMCC (2015).  ITN report for 2014 (draft), Lusaka, Zambia
19. Syngenta (2013).  Long-lasting control of pyrethroids resistance. Basel, Switzerland
20. Chanda E, Chanda J, Kandyata A, Phiri FN, Muzia L, Haque U, Baboo KS (2013). Efficacy of ACTELLIC 300 CS, pirimiphos methyl, for indoor residual spraying in areas of high vector resistance to pyrethroids and carbamates in Zambia.
21. Okumu FO, Moore SJ (2011). Combining indoor residual spraying and insecticide-treated nets for malaria control in Africa: a review of possible outcomes and an outline of suggestions for the future. Malar. J 10: 208.

By BM Katemba¹, B Gianetti¹, C Groeneveld¹, KE Musakanya¹

1. Zambia National Public Health Institute

Download pdf

---

Citation Style For This Article: Katemba BM, Gianett B, Groeneveld C, Musakanya KE. Typhoid in Zambia: An analysis of cases
reported between 2016 and 2018. Health Press Zambia Bull. 2019; 3(4); pp 6-11.

---

Introduction

Typhoid fever is an acute, life-threatening, febrile illness [1]. In humans, Salmonella is categorized in two types; Salmonella enterica (S. enterica) low virulence serotypes that result in food poisoning and the high virulence serotypes known as Salmonella typhi (S. typhi) that cause typhoid. S. enterica also includes a group of serovars called S. paratyphi A, B and C that cause paratyphoid [2]. Typhoid has a case fatality rate of 1–4% in patients with appropriate therapy and can rise to 10–30% in untreated cases [3].

Globally, it is difficult to estimate the exact number of typhoid cases. According to the World Health Organization (WHO), the global typhoid fever burden ranges from 11 and 21 million cases and 128 000 to 161 000 typhoid-related deaths annually, and the burden of the diseases is skewed towards the middle and low-income countries [4].

In developing countries typhoid is estimated to affect about 400,000 people annually with an incidence of 50 per 100,000 persons per year [5]. A number of typhoid outbreaks have been recorded in different African countries such as the Democratic Republic of Congo, Uganda, Malawi, Zambia, South Africa, Mozambique and the Ivory Coast [6].

Between January 2010 to September 2012, Zambia recorded a total of 2,040 typhoid cases with a case fatality rate of 0.5%. The disease mostly affected children less than 15 years with an even distribution of males and females. During this outbreak, most (83%) of the S. typhi isolates exhibited resistance to five core antimicrobials: ampicillin, chloramphenicol, streptomycin, sulfamethoxazole, and trimethoprim [7].

In 2017, a typhoid outbreak was reported in Mpika district of Zambia with a total of 127 cases and one recorded death, translating to a case fatality rate of 0.8% (by May 2017)  [8]. On 10 March 2017, the country recoded 28 cases with two typhoid related deaths in Luamala area of Solwezi district [9].

Previous reports have shown differing results in the number of typhoid cases reported from different parts of the country between 2016 and 2018. As such, this paper provides a consolidated trend analysis of typhoid cases between 2016 and 2018 in Zambia.

Methodology

Typhoid data was collected from the Integrated Disease Surveillance and Response (IDSR) system. Weekly IDSR data from 2016 to 2019 was entered and analyzed using Microsoft Excel and STATA 13. Trends of typhoid cases by province and year were presented using graphs generated in Microsoft Excel. The study used Tableau to show the spatial distribution of typhoid cases from 2016 to 2018. The study further utilized case reports generated during the outbreaks to supplement IDSR data and make recommendations.

Results

According to the IDSR, a suspected case definition of typhoid is; any person with gradual onset of steadily increasing and persistently high fever, chills, malaise, headache, sore throat, cough, and, sometimes adnominal pain and constipation. Based on the IDSR definition, Zambia recorded 414 suspected typhoid cases in 2016 (Figure 1). In 2017, there was more than 50% increase in suspected cases compared to the previous year. 730 suspected cases were recorded in 2018 showing a 40% reduction from 2017 (not accounting for population change) (Figure 1).

The majority of suspected cases occurred in 2017 between epidemiological week 15 and 18. There was a sudden upswing of typhoid cases in week 34 in all the years under review (Figure 2).

Lusaka province had the highest number of typhoid suspected cases in 2017 and 2018 (Figure 3). In 2016, Northern Province had more suspected cases than Lusaka province. Central province reported zero suspected cases of typhoid in 2016 and 2018. Overall, Central province had the lowest suspected cases in the time series of 2016 to 2018 (Figure 3 & 4).

Trend analysis of typhoid cases by province (2016-2018)
8

Discussion

This paper retrospectively investigated typhoid fever trends in Zambia using IDSR data. According to the findings, Zambia recorded more suspected cases of typhoid in 2017 compared to 2016 and 2018.  There is no clear pattern of typhoid in Zambia suggesting the disease to be endemic. A sudden peak of suspected cases occurred between week 34 and week 35 each reported year. A study done in Delhi suggest that although the disease is endemic, the peak occurs in the hot days of summer [10]. Unlike Zambia’s observed situation, a seasonal pattern of the disease has become apparent in Malawi, A study done in 2015 showed that typhoid fever cases usually peak during the wet and dry season [11].

Despite all provinces recording suspected cases of typhoid fever, the study showed that Lusaka province, with 1,190 suspected cases, had the highest number of suspected cases. There is limited information on the actual risk factors for typhoid in Zambia; however, different studies have shown that typhoid fever is elevated in areas of low socio-economic status and high density populations. A study done in Malawi found that consuming water from a river and not washing hands after using the toilet were the main risk factors for typhoid. In Zimbabwe, water from shallow wells, boreholes and dams were contaminated with E.coli, indicating the possibility of further contamination with S. typhi [12].

Data providing a clear and representative picture of the samples sent for laboratory confirmation is yet to be obtained and validated. However, a typhoid outbreak investigation in Solwezi (Northern Zambia) in 2017 established that there was a critical need for laboratory investigation as patients presenting with malaria-like symptoms could also have typhoid fever [13]. Another study in Delhi established that correct diagnosis for typhoid fever is likely to be missed as patients often present with multiple clinical problems, requiring laboratory confirmation [14]. Therefore, typhoid fever suspected case reporting is prone to conflation by both over-counting and undercounting due to typhoid patients being falsely diagnosed with malaria and malaria patients being falsely diagnosed with typhoid.

Conclusion

According to data collected from the IDSR, typhoid fever is endemic in Zambia. Suspected cases did not follow any clear pattern in the last three years. There is need to further investigate the exact number of suspected cases that are laboratory confirmed and determine why certain suspected cases are not sent for laboratory investigation. It was clear in this study that Lusaka province suffered the highest number of typhoid suspected cases of all the provinces in Zambia. Finally, of the three years reviewed, the most suspected cases were reported in 2017 and lowest in 2016.

References

1. WER9313.Pdf. Typhoid vaccines: WHO position paper – March 2018
2. Kanungo, Dutta, and Sur, Epidemiology of Typhoid and Paratyphoid Fever in India.
3. WER9313.Pdf. Typhoid vaccines: WHO position paper – March 2018
4. WHO_SurveillanceVaccinePreventable_21_Typhoid_R2.Pdf.
5. Kariuki, Typhoid Fever in Sub-Saharan Africa.
6. Slayton, Date, and Mintz, Vaccination for Typhoid Fever in Sub-Saharan Africa.
7. Hendriksen et al., Genomic Signature of Multidrug-Resistant Salmonella Enterica Serovar Typhi Isolates Related to a Massive Outbreak in Zambia between 2010 and 2012.
8. OEW22-270262017.Pdf. Weekly bulletin on outbreaks and other emergencies
9. Mwansa et al., Typhoid Fever Outbreak Investigation in a Malaria Endemic Community, Solwezi, North-Western Province, Zambia, 2017.
10. Gulati et al., Changing Pattern of Typhoid Fever.
11. Feasey et al., Rapid Emergence of Multidrug Resistant, H58-Lineage Salmonella Typhi in Blantyre, Malawi.
12. Lantagne et al., Household Water Treatment Uptake during a Public Health Response to a Large Typhoid Fever Outbreak in Harare, Zimbabwe.
13.   Mwansa et al., “Typhoid Fever Outbreak Investigation in a Malaria Endemic Community, Solwezi, North-Western Province, Zambia, 2017.”
14.   Gulati et al., “Changing Pattern of Typhoid Fever.”