|Year : 2022 | Volume
| Issue : 1 | Page : 19-25
Visual impairment among adult diabetic patients and associated factors at debre brihan referral hospital, Central Ethiopia, 2017
Ketemaw Z Demilew, Nebiyat F Adimassu, Destaye S Alemu
Department of Optometry, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia
|Date of Submission||16-Oct-2020|
|Date of Acceptance||06-Jun-2022|
|Date of Web Publication||23-Nov-2022|
Mr. Ketemaw Z Demilew
Department of Optometry, College of Medicine and Health Sciences, University of Gondar, Gondar
Source of Support: None, Conflict of Interest: None
| Abstract|| |
PURPOSE: The study aimed to assess the proportion of visual impairment and associated factors among diabetic patients at Debre Berhan Referral Hospital (DBRH).
METHODS: A hospital-based cross-sectional study was carried out from April 27 to May 19, 2017. All adult diabetic patients attending DBRH during the study period were included in the study. A pretested, structured questionnaire and clinical examinations were used for data collection. The collected data were entered into Epi Info 7 and exported to the Statistical Package for Social Sciences version 20 for analysis. The descriptive analysis was summarized by frequency, percent, and summary statistics. Association between visual impairment and independent variables was determined via bivariable and multivariable binary logistic regressions. P < 0.05 was considered statistically significant. Adjusted odds ratio (AOR) and 95% confidence interval (CI) were used to determine the strength of association. Hosmer and Lemeshow goodness of fit was used to check for model fitness.
RESULTS: A total of 388 study subjects with a 92% response rate took part in the study. The prevalence of visual impairment was 29.38% (95% CI: 24.83%–33.93%). Age >56 years (AOR = 5.24, 95% CI: 1.37–20.04), physical inactivity (AOR = 2.34, 95% CI: 1.33–4.14), presence of visual symptoms (AOR = 4.48, 95% CI: 2.35–8.57), lower body mass index (AOR = 6.23, 95% CI: 1.87–20.68), and diabetic retinopathy (AOR = 5.12, 95% CI: 1.91–13.70) had a statistically significant association with visual impairment.
CONCLUSION: A high proportion of diabetic patients had visual impairment. Independent variables older age, physical inactivity, presence of visual symptoms, lower body mass index, and diabetic retinopathy had a positive statistically significant association with visual impairment.
Keywords: Diabetes mellitus, Ethiopia, proportion, visual impairment
|How to cite this article:|
Demilew KZ, Adimassu NF, Alemu DS. Visual impairment among adult diabetic patients and associated factors at debre brihan referral hospital, Central Ethiopia, 2017. Middle East Afr J Ophthalmol 2022;29:19-25
|How to cite this URL:|
Demilew KZ, Adimassu NF, Alemu DS. Visual impairment among adult diabetic patients and associated factors at debre brihan referral hospital, Central Ethiopia, 2017. Middle East Afr J Ophthalmol [serial online] 2022 [cited 2023 Feb 7];29:19-25. Available from: http://www.meajo.org/text.asp?2022/29/1/19/361878
| Introduction|| |
In this study, visual impairment is defined as presenting visual acuity (PVA) of <6/18 in the worse eye.
Visual impairment is a significant public health issue in diabetic patients, particularly in developing countries. Visual impairment is highly prevalent in diabetic patients. Over 10% of diabetic patients develop visual impairment within 15 years of diagnosis. Diabetes mellitus (DM) is one of the top and most preventable causes of new cases of blindness in adults aged 20–74 years in the United States., Several studies in the world and Africa reported that the prevalence of visual impairment among diabetic patients was between 16.7% and 55%. They also determined some factors associated with visual impairment.,,,,,,
Visual impairment can cause loss of productivity and dependency. The frequent health service use by diabetic patients makes DM a more expensive disease that can pose large economic challenges on individuals and the country at large. Many countries spend between 5% and 20% of their total health expenditure on diabetes.
Despite these economic challenges, the prevalence of DM is progressively increasing from time to time, which eventually increases the magnitude of visual impairment among diabetic patients., Evidence-based actions are required to prevent and avoid visual impairment in diabetic patients.
However, the evidence is limited on the prevalence and associated factors of visual impairment among diabetic patients in Ethiopia.
Diabetic eye disease is among the priorities of vision 2020 “the right to sight,” to eliminate avoidable blindness from the world by the year 2020, in which Ethiopia is a member state.
Because of lacking evidence, it is difficult to speak about the progress of visual impairment. Providing information on the magnitude and factors associated with visual impairment in diabetic patients may be helpful to advocate for greater political and financial commitment and proper allocation of resources so that effective delivery of eye care services is possible for diabetic patients in avoiding avoidable visual impairment., It also helps as a baseline for monitoring, follow-up, and evaluation of programs.
Therefore, this study aimed to estimate the proportion of visual impairment and associated factors among diabetic patients.
| Methods|| |
A hospital-based cross-sectional study was conducted. The study was conducted at Debre Berhan Referral Hospital (DBRH) from April 27, 2017, to May 19, 2017. DBRH is found in the North Shoa Zone of Amhara National Regional State which is located 130 km north of Addis Ababa, the capital city of Ethiopia. It is the only referral hospital and the only eye center in the North Shoa Zone and has a catchment of approximately 2.8 million people according to the data obtained from the DBRH Health Information Department. It mainly receives patients from the North Shoa Zone of the Amhara region and partly from the Oromia and Afar regions. The clinical service at the diabetic clinic was given by general practitioners, internists, and nurses.
The sample size was calculated with a single population proportion formula:
where n = Sample size, Z = The value of z statistic at 95% confidence level = 1.96, P – Proportion of visual impairment = 50% = 0.5 (Since hospital-based study on the PVA was not conducted in the study area or other similar areas which had related population characteristics and methodology, 50% proportion was used), and d – Maximum tolerable error (marginal error) 5% = 0.05, n = 384). Considering a 10% nonresponse rate, the final sample size was estimated to be 422. A consecutive sampling method was employed to attain 422 study subjects.
Visual impairment was defined as PVA worse than 6/18 (<6/18–NLP). Visual impairment was further categorized into moderate visual impairment (PVA <6/18–6/60), severe visual impairment (PVA <6/60–3/60), blindness (PVA <3/60–NLP), monocular moderate visual impairment (presenting distance visual acuity of <6/18–6/60 in one eye and 6/6–6/18 in the other eye), monocular severe visual impairment (PVA <6/60–3/60 in one eye and 6/6–6/60 in the other eye), and monocular blindness (PVA <3/60–NLP in one eye and PVA of 6/6–3/60 in the other eye).
Body mass index (BMI) (kg/m2) was calculated as weight (kg) divided by height in square meters (m2) and was graded according to the WHO classification. A BMI of <18.5 was underweight, a BMI of 18.5–24.9 kg/m2 was normal, a BMI of 25–29.9 kg/m2 was overweight, and a BMI of ≥30 kg/m2 was obese.
People who performed at least 75 min of aerobic physical activity throughout the week, such as running, bicycling, rope jumping, and swimming, were considered engaged in physical activity.
People who had been examined their eyes after the diagnosis of DM and before the data collection time were considered as they have a history of ocular examination.
People who had symptoms such as blurring of vision, flashing of light, floaters, halos, or visual field loss at the time of data collection were considered symptomatic. Those who had not visual symptoms were considered asymptomatic.
Fasting blood sugar (FBS) level of >126 mg/dl was considered hyperglycemia and <126 mg/dl was normal.
Participants who came from the place with infrastructures such as paved streets, electric lighting, sewerage, or where there is surplus employment were classified as urban residents. On the other hand, participants who were not classified as urban constitute rural.
Data were collected using an interviewer-administered pretested questionnaire and ocular examinations. Snellen's E chart, slit-lamp biomicroscope, direct ophthalmoscope, and 90D Volk were used for ocular examination to get the clinical data. A digital balance was used for weight measurement and meter tape was used for height measurement.
Three nurses and two optometrists were involved in the data collection process. After getting the informed consent from study subjects, two nurses interviewed the study participants on the interview part of the questionnaire including demography, behavioral factors, and systemic comorbidities. Regarding the clinical data, the nurses also interviewed the study participants about the duration of DM, mode of treatment, and presence of visual symptoms; took measurements on weight and height; and referred patients' folder to note on the type of DM and FBS level. The patients' folder was marked after relevant data collected to avoid the repeated collection of data on the same patient. The patient was then sent to the Ophthalmology Department to undergo ocular examinations. The vision was measured by the third nurse. The PVA was measured using Snellen's E chart at 6 m. The PVA was recorded as fraction notation.
Anterior and posterior segment examinations were done by two optometrists in the Ophthalmology Department. Anterior segment examination was done with a slit-lamp biomicroscope. The posterior segment examination was done using 90D Volk after dilating with 1% tropicamide eye drop. At the end of the ocular examination, each patient was told about his/her vision status and eye conditions. All the data collectors were trained for 1 day on how to collect the data. One clinical optometry master's degree holder supervised the data collection process. Cronbach's alpha was used to check the reliability of the questionnaire.
Each day during the data collection, 5% of the data were cross-checked for completeness by the principal investigator. After the data were checked for completeness and consistency, it was coded and entered into Epi Info 7 (CDC, Atlanta, Georgia, USA) and exported to SPSS version 20 for analysis (IBM corp., Armonk (N.Y., USA).
Ethical clearance was obtained from the University of Gondar, College of Medicine and Health Sciences, School of Medicine Ethical Review Committee. Permission was obtained from DBRH. Informed consent was obtained from each study participant after explaining the purpose of the study. Participants had full right to take part, refuse, or withdraw from the study when they want. Confidentiality was assured by coding and locking the data.
Diabetic patients with visual impairment and other ocular problems were linked to the Ophthalmology Department for treatment, follow-up, and/or referral. All study participants were advised about the importance of regular ocular screening, even in the absence of any visual symptoms or problems.
Statistical analysis for descriptive and binary logistic regression was done with SPSS version. The descriptive statistics were summarized using summary statistics, such as frequency tables, percentages, means, medians, and standard deviations. Bivariable and multivariable binary logistic regressions were used to identify factors associated with visual impairment. P < 0.05 was set to declare statistical significance. Adjusted odds ratio (AOR) and 95% confidence interval (CI) were used to determine the strength of association. Hosmer and Lemeshow goodness of fit was used to check for model fitness.
| Results|| |
Sociodemographic characteristics of study participants
A total of 388 participants with a response rate of 92% were included in this study. The response rate was 92%. The median age of study participants was 45 years (interquartile range [IQR]: 30, 56). Males were 208 (53.6%) and 359 (92.5%) were Orthodox Christians. Most of the study participants were urban residents 253 (65.2%) and Amhara 326 (84%) in ethnicity. The median monthly income was ETB 700 (IQR of 1600 ETB) [Table 1].
|Table 1: Sociodemographic characteristics of diabetic patients at Debre Berhan Referral Hospital, Ethiopia, 2017 (n=388)|
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Clinical and behavioral characteristics of study participants
Type 2 diabetic patients were 228 (58.8%). The median for the duration of diabetes was 3.5 years (IQR: 4.75). The minimum duration of diabetes after diagnosis was 1 day, and the maximum was 28 years. The median for FBS was 147.5 mg/dl (IQR: 113, 188.75). About 225 (58%) were engaged in physical activities and 200 (51.5%) had a history of an eye examination [Table 2].
|Table 2: Clinical and behavioral characteristics of adults diabetic patients at Debre Berhan Referral Hospital, Ethiopia, 2017 (n=388)|
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Prevalence of visual impairment in diabetic patients
The prevalence of visual impairment among diabetic adults was found to be 29.38% (95% CI: 24.7%–34.3%).
Nearly half (49.1%) of the patients with visual impairment were in the moderate visual impairment category [Table 3].
|Table 3: Frequencies of visual impairment categories among adults with diabetes mellitus at Debre Berhan Referral Hospital, Ethiopia, 2017|
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Factors associated with visual impairment in diabetic patients
In multivariable analysis, variables that had a statistically significant association with visual impairment were age, physical inactivity, history of an eye examination, lower BMI, and presence of visual symptoms.
The study participants whose age >56 years had nearly five times (AOR = 5.24, 95% CI: 1.37–20.04) more likely to have visual impairment than age 18–30 years. Those who did not engage in physical exercise had 2.34 times more likely (AOR = 2.34, 95% CI: 1.33–4.14) to develop visual impairment as compared to those who performed physical activities. Having visual symptoms prior to the data collection time was 4.48 times more likely (AOR=4.48, 95% CI: 2.35-8.57) to have visual impairment than those who had no visual symptoms. Underweight (lower BMI) diabetics were about six times (AOR = 6.23, 95% CI: 1.87–20.68) likely to have visual impairment than normal weighted diabetic individuals. Visual impairment in those who had diabetic retinopathy was 5.12 times (AOR = 5.12, 95% CI: 1.91–13.7) than those who had no diabetic retinopathy [Table 4].
|Table 4: Bivariable and multivariable analysis of factors associated with visual impairment among diabetic patients at Debre Berhan Referral Hospital, Ethiopia, 2017|
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| Discussion|| |
The prevalence of visual impairment among diabetic patients attending DBRH, Central Ethiopia, was found to be 29.38% (95% CI: 24.83%–33.93%). This proportion of visual impairment was higher than those studies done in China (12.2%), Tunisia (22.2%), Nigeria (16.7%), and Cameroon (22.6%). The difference between this study from the Chinese and Tunisian studies may be because of differences in the definition of visual impairment. The Chinese study used the best-corrected visual acuity (VA) to define visual impairment, unlike this study which used PVA. Best-corrected VA underestimates the real burden of visual impairment. The Tunisian study used better eye vision to say visual impairment. If a person's one eye is normal and the other is impaired, this person will not be considered visually impaired when a better eye definition is used. However, in this study, monocular visual impairment was incorporated according to the International Classification of Diseases update and revision platform. The Nigerian and the Cameroonian study used a very small sample size, 84 and 96, respectively, which may be the reason for their small prevalence of visual impairment as compared to this study. However, the prevalence of visual impairment in this study was lower than studies done in South Africa (44.9%) and Yemen (55%). This visual impairment definition may be the reason for the higher prevalence of visual impairment in the South African study. In the South African study, visual impairment was defined as VA of <6/9.5, unlike this study, which was VA of <6/18. It may also be due to differences in VA measurement charts and visual impairment definitions. Because of the crowding effect in the logMAR chart as compared to Snellen's E chart, more people may be grouped into visual impairment. LogMAR was used in the South African study and Snellen's E chart was used in this study. The study participants were diabetic patients aged 40 years and older in the South African study and aged 18 years and above in this study. The relatively older study participants in the South Africa study may be the reason for the higher prevalence of visual impairment. Sociocultural variations may be responsible for the wide difference between the Yemeni and this study. Because of familial clustering and the high rate of consanguinity in the Yemeni population, which are genetic risk factors for early onset of DM, higher DM complications are expected that may result in visual impairment.,, The Yemenis diabetic patients had a longer duration of diabetes than this study subjects. In the Yemeni study, 52% of the study population had DM for over 10 years whereas only <15% of the study population had DM for over 10 years in this study.
The proportion of visual impairment in this study was in line with studies done in Uganda (28.6%). This may be because of similarities in the age of study participants (≥18 years), the use of PVA, and the cut-off point for visual impairment (VA <6/18).
In this study, older age was positively associated with visual impairment which was consistent with other studies done in China, Singapore, South Africa, Tunisia, Yemen, and Uganda. The reason for increased visual impairment in old age may be due to increased age-related eye diseases with old age and because of the long duration of DM with older age that may cause diabetic complications in the eyes. Physical inactivity was positively associated with visual impairment, which was in line with the South African study. The reason for this may be because of the poor control of diabetes in people who were not engaged in physical activities. The presence of visual symptoms was also positively associated with visual impairment in this study, which was in line with the Ugandan study. Visual impairment is most likely to have symptoms such as blurring of vision. Hence, the positive association of visual impairment and visual symptoms is likely. Patients with lower BMI in this study were positively associated with visual impairment, which was in agreement with a multi-ethnic Asian study. In this study, the majority of patients underweight (72%) were hyperglycemic, which may be the reason for the positive association with visual impairment.
Patients with diabetic retinopathy had a significant association with visual impairment, which agreed with the Tunisian study. Diabetic retinopathy is among the leading causes of visual impairment in the world.
Visual impairment among adult diabetic patients at Debre Berhan hospital was high which needs stakeholders' attention. Older age, physical inactivity, presence of visual symptoms, lower BMI, and diabetic retinopathy had a positive statistically significant association with visual impairment.
The study has the following limitations. This study was a single-site study which made the sample size relatively small and eventually generalization for the large number of population difficult. History of any prior treatment for diabetic eye disease such as laser, anti-vascular endothelial growth factor injection, or vitrectomy which might have an effect on the proportion of visual impairment was not asked.
We thank the University of Gondar and Debre Berhan for permitting and supporting this study. We thank the study participants for their cooperation during the data collection.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| Questionnaire|| |
Part 1. Socio-demographic data
1. ID __________
2. Age (year) ___________
3. Sex 1) Male 2) Female
4. Relegion 1) Orthodox 2)Muslim 3)Protestant 4) Catholic
5) Other Specify______
5. Ethinicity 1) Amhara 2) Oromo 3)Afar 4)Tigrie
5) Other specify_______
6. Marital status 1) Single 2) Married 3) Widowed 4) Divorced
7. Educational status 1) cannot read and write 2) Can read and write only 3) primary school
4) Secondary school 5) College/University
8. Occupation 1) daily laborer 2) merchant 3) employed 4) farmer
5) house wife 6) retired 7) not employed 8) Other specify__
9. Residence 1) Urban 2) Rural
10. Monthly income __________
Part 2. questions about knowledge on the effect of DM in the eye
11. Can DM affect the eyes? 1) Yes 2) No 3) I don't know
12. Can DM cause visual impairment? 1) Yes 2) No 3) I don't know
13. Can DM cause diabetic retinopathy? 1) Yes 2) No 3) I don't know
14. Can DM cause Glaucoma? 1) Yes 2) No 3) I don't know
15. Can DM cause Cataract? 1) Yes 2) No 3) I don't know
16. Can DM cause refractive error? 1) Yes 2) No 3) I don't know
17. Can ocular problems caused by DM be prevented? 1) Yes 2) No 3) I don't know
18. Are regular follow ups helpful for eye health? 1) Yes 2) No 3) I don't know
Part 3. Questions on clinical and behavioral factors
19. Do you do physical exercises ? if no go to question 25. 1) Yes 2) No
20. How frequent?___________ How long?_________
21. Have you history of eye examination before? if no go to question 27. 1) Yes 2) No
22. When? 1) within 1 week 2) 1week -1 month 3) 1 month - 6 months
4) 6 months- one year 5) before one year 6) I don't remember
23. BMI __________height(m) __________weight(kg)__________
24. Type of DM 1) Type 1 2) Type 2
25. Duration of DM since diagnosis? __________
26. level of recent fasting blood sugar? __________
27. Are there any visual symptomts you know? 1) Yes 2) No
28. HPN? 1) Yes 2) No
29. Distance presenting visual acuity: right eye--------------------left eye-----------------
30. Diabetic retinopathy: 1) Yes 2) No
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[Table 1], [Table 2], [Table 3], [Table 4]