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Open Access

Peer-reviewed

Research Article


VISUAL IMPAIRMENT AMONG DIABETES PATIENTS IN ETHIOPIA: A SYSTEMATIC REVIEW AND
META-ANALYSIS

 * Tigabu Munye Aytenew ,
   
   Roles Conceptualization, Data curation, Formal analysis, Methodology,
   Software, Validation, Writing – original draft, Writing – review & editing
   
   * E-mail: tigabumunye21@gmail.com
   
   Affiliation Department of Nursing, College of Health Sciences, Debre Tabor
   University, Debre Tabor, Ethiopia
   
   https://orcid.org/0000-0002-3933-5540
   
   ⨯
 * Demewoz Kefale,
   
   Roles Validation, Writing – review & editing
   
   Affiliation Department of Pediatrics and Child Health Nursing, College of
   Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia
   
   ⨯
 * Binyam Minuye Birhane,
   
   Roles Methodology, Visualization, Writing – review & editing
   
   Affiliations School of Public Health, University of Technology Sydney,
   Sydney, NSW, Australia, Department of Maternity and Neonatal Nursing, College
   of Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia
   
   ⨯
 * Solomon Demis Kebede,
   
   Roles Data curation, Methodology
   
   Affiliation Department of Maternity and Neonatal Nursing, College of Health
   Sciences, Debre Tabor University, Debre Tabor, Ethiopia
   
   ⨯
 * Worku Necho Asferie,
   
   Roles Methodology, Software, Writing – review & editing
   
   Affiliation Department of Maternity and Neonatal Nursing, College of Health
   Sciences, Debre Tabor University, Debre Tabor, Ethiopia
   
   ⨯
 * Habtamu Shimels Hailemeskel,
   
   Roles Conceptualization, Methodology
   
   Affiliation Department of Maternity and Neonatal Nursing, College of Health
   Sciences, Debre Tabor University, Debre Tabor, Ethiopia
   
   ⨯
 * Amare Kassaw,
   
   Roles Data curation, Methodology, Writing – review & editing
   
   Affiliation Department of Pediatrics and Child Health Nursing, College of
   Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia
   
   ⨯
 * Sintayehu Asnakew,
   
   Roles Methodology, Resources, Writing – review & editing
   
   Affiliation Department of Psychiatry, College of Health Sciences, Debre Tabor
   University, Debre Tabor, Ethiopia
   
   ⨯
 * Yohannes Tesfahun Kassie,
   
   Roles Conceptualization, Methodology
   
   Affiliation Department of Emergency and Critical Care Nursing, College of
   Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia
   
   ⨯
 * Gebrehiwot Berie Mekonnen,
   
   Roles Methodology, Writing – review & editing
   
   Affiliation Department of Pediatrics and Child Health Nursing, College of
   Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia
   
   https://orcid.org/0000-0001-9087-7794
   
   ⨯
 * Melese Kebede,
   
   Roles Methodology, Validation, Writing – review & editing
   
   Affiliation Department of Emergency and Critical Care Nursing, College of
   Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia
   
   ⨯
 * Yeshiambaw Eshetie,
   
   Roles Conceptualization, Methodology
   
   Affiliation Department of Nursing, College of Health Sciences, Debre Tabor
   University, Debre Tabor, Ethiopia
   
   ⨯
 * Netsanet Ejigu,
   
   Roles Data curation, Resources
   
   Affiliation Department of Midwifery, Dembya Primary Hospital, Koladiba,
   Gondar, Ethiopia
   
   ⨯
 * Shegaw Zeleke,
   
   Roles Conceptualization, Data curation, Methodology, Writing – review &
   editing
   
   Affiliation Department of Nursing, College of Health Sciences, Debre Tabor
   University, Debre Tabor, Ethiopia
   
   ⨯
 * Muluken Chanie Agimas,
   
   Roles Conceptualization, Formal analysis, Methodology
   
   Affiliation Department of Epidemiology and Biostatistics, Institute of Public
   Health, College of Medicine and Health Science, University of Gondar, Gondar,
   Ethiopia
   
   ⨯
 *  [ ... ],
 * Amare Simegn
   
   Roles Conceptualization, Methodology, Validation, Writing – review & editing
   
   Affiliation Department of Reproductive Health, College of Health Sciences,
   Debre Tabor University, Debre Tabor, Ethiopia
   
   ⨯
 * [ view all ]
 * [ view less ]


VISUAL IMPAIRMENT AMONG DIABETES PATIENTS IN ETHIOPIA: A SYSTEMATIC REVIEW AND
META-ANALYSIS

 * Tigabu Munye Aytenew, 
 * Demewoz Kefale, 
 * Binyam Minuye Birhane, 
 * Solomon Demis Kebede, 
 * Worku Necho Asferie,  …
 * Habtamu Shimels Hailemeskel, 
 * Amare Kassaw, 
 * Sintayehu Asnakew, 
 * Yohannes Tesfahun Kassie, 
 * Gebrehiwot Berie Mekonnen

x
 * Published: May 31, 2024
 * https://doi.org/10.1371/journal.pone.0303388
 * 


 * Article
 * Authors
 * Metrics
 * Comments
 * Media Coverage
 * Peer Review

 * Abstract
 * Introduction
 * Methods
 * Results
 * Meta-analysis
 * Discussion
 * Conclusions
 * Supporting information
 * Acknowledgments
 * References

 * Reader Comments
 * Figures





ABSTRACT


INTRODUCTION

The increased prevalence of visual impairment among diabetes patients has become
a major global public health problem. Although numerous primary studies have
been conducted to determine the prevalence of visual impairment and its
associated factors among diabetes patients in Ethiopia, these studies presented
inconsistent findings. Therefore, this review aimed to determine the pooled
prevalence of visual impairment and identify associated factors among diabetes
patients.


METHODS

An extensive search of literature was done on PubMed, Google Scholar, and Web of
Sciences databases. A manual search of the reference lists of included studies
was performed. A weighted inverse-variance random-effects model was used to
calculate the pooled prevalence of visual impairment.


RESULTS

A total of 34 eligible primary studies with a sample size of 11,884 participants
were included in the final meta-analysis. The pooled prevalence of visual
impairment was 21.73% (95% CI: 18.15, 25.30; I2 = 96.47%; P<0.001). Diabetes
mellitus with a duration of diagnosis ≥10 years [AOR = 3.18, 95% CI: 1.85,
5.49], presence of co-morbid hypertension [AOR = 3.26, 95% CI: 1.93, 5.50], poor
glycemic control [AOR = 4.30, 95% CI: 3.04, 6.06], age ≥56 years [AOR = 4.13,
95% CI: 2.27, 7.52], family history of diabetes mellitus [AOR = 4.18 (95% CI:
2.61, 6.69], obesity [AOR = 4.77, 95% CI: 3.00, 7.59], poor physical activity
[AOR = 2.46, 95% CI: 1.75, 3.46], presence of visual symptoms [AOR = 4.28, 95%
CI: 2.73, 6.69] and no history of eye exam [AOR = 2.30, 95% CI: 1.47, 3.57] were
significantly associated with visual impairment.


CONCLUSIONS

The pooled prevalence of visual impairment was high in Ethiopia. Diabetes
mellitus with a duration of diagnosis ≥10 years, presence of co-morbid
hypertension, poor glycemic control, age ≥56 years, and family history of
diabetes mellitus, obesity, poor physical activity, presence of visual symptoms,
and no history of eye exam were independent predictors. Therefore, diabetic
patients with these identified risks should be screened, and managed early to
reduce the occurrence of visual impairment related to diabetes. Moreover, public
health policy with educational programs and regular promotion of sight screening
for all diabetes patients are needed.


FIGURES

    

Citation: Aytenew TM, Kefale D, Birhane BM, Kebede SD, Asferie WN, Hailemeskel
HS, et al. (2024) Visual impairment among diabetes patients in Ethiopia: A
systematic review and meta-analysis. PLoS ONE 19(5): e0303388.
https://doi.org/10.1371/journal.pone.0303388

Editor: Mohammed Feyisso Shaka, Madda Walabu University, ETHIOPIA

Received: July 26, 2023; Accepted: April 24, 2024; Published: May 31, 2024

Copyright: © 2024 Aytenew et al. This is an open access article distributed
under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the
original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting
Information files.

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests
exist.

Abbreviations: DM, Diabetes mellitus; DR, Diabetic retinopathy; ICAM,
Inter-cellular adhesion molecule; IDF, International Diabetic Federation; LMICs,
Low and middle-income countries; NCDs, Non-communicable diseases; PRISMA,
Preferred Reporting Items for Systematic Reviews and Meta-Analyses; VI, Visual
impairment


INTRODUCTION

Diabetes mellitus (DM) is a major global public health problem [1]. It was one
of the four priority non-communicable diseases (NCDs) targeted for prevention
and control in 2011 [2]. According to the International Diabetic Federation’s
(IDF) 2019 report, it was estimated that around 500 million people are living
with diabetes worldwide [3], and predicted to be 693 million by 2045 [4]. The
majority occurred in low and middle-income countries (LMICs) [5], and 2.6
million diabetes cases were also reported in Ethiopia by 2017 [4].

DM is associated with chronic complications like diabetic neuropathy,
nephropathy, retinopathy, cardiovascular diseases, blindness, kidney failure,
and nerve damage [6, 7]. It causes visual impairment (VI) through early-onset
cataracts and diabetic retinopathy (DR), a progressive disease of the retinal
microvasculature [8]. Globally, around 2.2 billion people have a near or distant
visual impairment, of whom 3.9 million are visually impaired due to diabetic
retinopathy [9]. In Africa, the prevalence of visual impairment among diabetes
patients ranges from 17.1% to 78.25% [10–12]. The increased prevalence of
diabetes-related visual impairment has become a major global public health
problem requiring substantial attention [13–15]. It is more common among people
with diabetes than in people without diabetes [16, 17]. Visual impairment among
diabetes patients can be associated with older age, poor glycemic control, poor
physical exercise, long durations of diabetes, and type of treatment [18–20].

Visual impairment can increase the unemployment rate and medical expenses, and
reduce the performance of daily living activities, productivity, and social
participation, leading an individual with diabetes to have a reduced quality of
life [9, 21]. Therefore, controlling blood glucose levels, regular physical
activity, having regular eye exams, and undergoing early laser photocoagulation
have been used to reduce the burden of visual impairment among diabetes patients
[22–24].

Although numerous primary studies have been conducted to determine the
prevalence of visual impairment and its associated factors among diabetes
patients in Ethiopia, these studies presented inconsistent findings, ranging
from 7% [25] to 42% [26]. Therefore, this review aimed to determine the pooled
prevalence of visual impairment and identify associated factors.


METHODS


REPORTING AND REGISTRATION PROTOCOL

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)
statement guideline [27] was used to report the results of this systematic
review and meta-analysis (S1 Table). The review protocol was registered with
Prospero database: (PROSPERO, 2023: CRD42023438607).


DATABASES AND SEARCH STRATEGY

We have conducted a thorough search of databases on PubMed, Google Scholar, and
Web of Sciences for all relevant studies conducted in Ethiopia using the
following search terms and phrases: (ʺPrevalenceʺ OR ʺIncidenceʺ OR ʺMagnitudeʺ
OR ʺBurdenʺ) AND (ʺVisual impairmentʺ) OR ʺDiabetic retinopathyʺ OR
ʺRetinopathyʺ OR ʺCataractʺ AND (ʺAssociated factorsʺ OR ʺDeterminant factorsʺ
OR ʺRisk factorsʺ OR ʺDeterminantsʺ) AND ʺEthiopiaʺ. Besides, a manual search of
the reference lists of included studies was performed. The searched primary
studies were published in the English language between 2011 and 2023 in
Ethiopia.


ELIGIBILITY CRITERIA

All observational studies which were conducted among diabetes patients in
Ethiopia, and reported the prevalence of visual impairment, associated factors,
and written in English were included in the review. However, citations without
abstracts, full texts, anonymous reports, editorials, systematic reviews and
meta-analyses, and qualitative studies were excluded from the review.


STUDY SELECTION

All the retrieved studies were exported to the EndNote version 7 reference
manager to remove duplicate studies. Initially, two independent reviewers (TMA
and DK) screened the titles and abstracts, followed by the full-text reviews to
determine the eligibility of each study. The disagreement between the two
reviews was solved through dialogue.


DATA EXTRACTION

Two independent reviewers (TMA and AS) extracted the data using structured
Microsoft Excel. When variations were observed in the extracted data, the phase
was repeated. If discrepancies between the extracted data continued, the third
reviewer (SDK) was involved. The name of the first author, year of publication,
study area, study design, sample size, response rate, and effect size of the
eligible studies were collected.


PRIMARY OUTCOME MEASURE

The primary outcome of interest was the pooled prevalence of visual impairment
among diabetes patients in Ethiopia.


DATA ANALYSIS

The extracted data were exported to STATA version 17 for statistical analysis. A
weighted inverse-variance random-effects model [28] was used to calculate the
pooled prevalence of visual impairment and determine the impact of its
associated factors. The presence of publication bias was checked by observing
the symmetry of the funnel plot and Egger’s test with a p-value of <0.05 was
employed to determine significant publication bias [29]. The percentage of total
variation across studies due to heterogeneity was assessed using I2 statistical
test [30]. The I2 values of 0, 25, 50, and 75% represented no, low, moderate,
and high heterogeneity respectively [30].

A p-value of I2 statistic <0.05 was used to declare a significant heterogeneity
[31, 32]. To identify the influence of a single study on the overall
meta-analysis, sensitivity analysis was performed. A forest plot was used to
estimate the effect of independent factors on the outcome variable and a measure
of association at 95% CI was reported. The adjusted odds ratio (AOR) was the
most commonly reported measure of association in the eligible primary studies,
and a random-effects model was used to estimate the pooled OR effect.


RESULTS


SEARCH RESULTS

A total of 2476 studies were retrieved from PubMed (n = 1294), Google Scholar (n
= 1127), Web of Science (n = 39) databases, manual search (n = 7) and the
University’s research repository online library (n = 9). Upon removing the
duplicated studies (n = 129) and irrelevant studies based on their titles and
abstracts (n = 1852), a total of 495 studies were selected for full-text review.
During full-text review, 382 studies with no accessible full texts were removed.
Of the remaining 113 studies, 79 studies were excluded (full texts were not
written in English, different settings, and the outcomes were not well defined).
Finally, 34 studies were extracted to determine the pooled prevalence of visual
impairment and its associated factors among diabetes patients in Ethiopia. We
traced the PRISMA flow chart [33] to show the selection process from initially
identified records to finally included primary studies (Fig 1).

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Fig 1. PRISMA flow chart showing the studies selection process, 2023.



https://doi.org/10.1371/journal.pone.0303388.g001


CHARACTERISTICS OF THE INCLUDED STUDIES

The twenty-six studies [20, 25, 26, 34–56], six studies [57–62] and two studies
[63, 64] were conducted using cross-sectional, retrospective cohort and
case-control study designs respectively. Regarding geographical region,
seventeen studies [20, 25, 26, 35, 36, 38, 40, 43, 45, 49–51, 55, 56, 60–62]
were conducted in Amhara, eight studies [39, 41, 44, 48, 52, 58, 59, 63] were
conducted in Oromia, five studies [42, 46, 53, 57, 64] were conducted in Addis
Ababa, three studies [37, 47, 54] were conducted in Southern nations,
nationalities and peoples, and one study [34] was conducted in Sidama region.

The total sample size of the included studies was 11,884, where the smallest
sample size was 81 [54] in Southern nations, nationalities and Peoples, and the
largest sample size 739 [51] in Amhara region. The prevalence of visual
impairment among diabetes patients was obtained from thirty-two included primary
studies [20, 25, 26, 34–62], while the data regarding the associated factors of
visual impairment were obtained from the twenty-two studies [20, 34, 35, 37–40,
43–47, 49, 50, 55, 56, 58–60, 62–64], with a response rate ranges from 89.33 to
100% (Table 1).

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Table 1. General characteristics of the included primary studies, 2023.



https://doi.org/10.1371/journal.pone.0303388.t001


OPERATIONAL DEFINITION OF VARIABLES

Visual impairment is the loss of the functionality of the visual systems,
characterized by decreased visual acuity, visual field loss, visual distortion,
or perception problems [34, 36, 65, 66].


QUALITY APPRAISAL OF THE INCLUDED STUDIES

Two independent reviewers (TMA and DK) appraised the quality of the included
studies and scored for the validity of the results. The quality of each study
was evaluated using the Joanna Briggs Institute (JBI) quality appraisal criteria
[67]. Twenty-six studies [20, 25, 26, 34–56], six studies [57–62] and two
studies [63, 64] were appraised using JBI checklist for cross-sectional, cohort
and case-control studies, respectively.

Thus, among the twenty-six cross-sectional studies, twenty-one studies scored
seven of the eight questions, 87.5% (low risk), three studies scored six of the
eight questions, 75% (low risk), and the remaining two studies also scored five
of the eight questions, 62.5% (low risk). But the two cross-sectional studies
[68, 69] were appraised, and each scored three of the eight questions, 37.5%
(high risk). As a result, these two studies have been excluded from the study
due to their low quality. Likewise, among the six cohort studies, four studies
scored eight of the ten questions, 80% (low risk), and two studies also scored
seven of the ten questions, 70% (low risk). Moreover, the two case-control
studies were appraised, and each study scored eight of the ten questions (S2
Table in S1 File).

Studies were of low risk when they scored 50% or higher on the quality
assessment indicators. After conducting a thorough quality appraisal, we
determined that the primary studies included in the analysis displayed a high
level of reliability in their methodological quality scores. The cross-sectional
studies scored between 5 and 7 out of a total of 8 points, while the cohort and
case-control studies scored between 7 and 8 out of a total of 10 points. Hence,
all the included primary studies [20, 25, 26, 34–64] had high quality.

RISK OF BIAS ASSESSMENT.

The adopted assessment tool [70] was used to assess the risk of bias. The tool
consists of ten items that assess four areas of bias: internal validity and
external validity. Items 1–4 evaluate selection bias, non-response bias and
external validity. Items 5–10 assess measure bias, analysis-related bias, and
internal validity. Accordingly, of the total of the thirty-four included
studies, twenty-nine studies scored eight of the ten questions and five studies
also scored seven of the ten questions. Studies were classified as ʺlow riskʺ if
eight and above of the ten questions received ʺYesʺ, as ʺmoderate riskʺ if six
to seven of the ten questions received ʺYesʺ and as ʺhigh riskʺ if five or lower
of the ten questions received ʺYesʺ. Therefore, all the included primary studies
[20, 25, 26, 34–64] had a low risk of bias (high quality) (S3 Table in S1 File).


META-ANALYSIS


POOLED PREVALENCE OF VISUAL IMPAIRMENT

A total of 34 eligible primary studies [20, 25, 26, 34–64] were included in the
final meta-analysis, and the pooled prevalence of visual impairment among
diabetes patients in Ethiopia was 21.73% (95% CI:18.15, 25.30; I2 = 96.47%;
P<0.001) (Fig 2).

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Fig 2. Forest plot showing the pooled prevalence of visual impairment with 95%
CIs in Ethiopia, 2023.



https://doi.org/10.1371/journal.pone.0303388.g002


PUBLICATION BIAS

The asymmetric distribution of the included primary studies on the funnel plot
suggests the presence of publication bias (Fig 3A), and the p-value of Egger’s
regression test (P<0.001) also indicated the presence of publication bias.
Hence, trim and fill analyses were done to manage the publication bias (Fig 3B).

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Fig 3.



Funnel plot before adjustment (3a) and after adjustment (3b) using trim and fill
analysis for publication bias of visual impairment among diabetes patients in
Ethiopia, 2023.



https://doi.org/10.1371/journal.pone.0303388.g003


INVESTIGATION OF HETEROGENEITY

The percentage of I2 statistics of the forest plot indicates a marked
heterogeneity among the included primary studies (I2 = 96.47%, P<0.001) (Fig 2).
Hence, sensitivity and subgroup analyses were performed to minimize the
heterogeneity.


SENSITIVITY ANALYSIS

To determine the influence of a particular primary study on the overall
meta-analysis, sensitivity analysis was conducted. The forest plot showed that
the estimate from a single primary study is closer to the combined estimate,
which implied the absence of a single study effect on the overall pooled
estimate. Thus, it has been demonstrated that a single study has no significant
impact on the overall outcome of the meta-analysis (Fig 4).

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Fig 4. Sensitivity analysis of visual impairment among diabetes patients in
Ethiopia, 2023.



https://doi.org/10.1371/journal.pone.0303388.g004


SUBGROUP ANALYSIS

The subgroup analysis was performed based on the study area and study period.
Thus, the highest pooled prevalence of visual impairment was found among studies
conducted in Addis Ababa [25.35, 95% CI: 11.18, 39.52, I2 = 97.30%, P<0.001],
followed by studies conducted in Oromia region [24.42, 95% CI: 17.38, 31.47, I2
= 94.02%, P<0.001] (Fig 5). Similarly, the higher pooled prevalence of visual
impairment was among studies conducted in the year 2021 and later [23.25, 95%
CI: 17.58, 28.91; I2 = 96.39%, P<0.001], followed by studies conducted before
the year 2021 [20.19, 95% CI: 15.66, 24.73, I2 = 95.05%, P<0.001] (Fig 6). Based
on the subgroup analyses, the heterogeneity of this study might be attributed to
differences in study area and period across the included primary studies.

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Fig 5. Forest plot of the prevalence of visual impairment with 95% CIs of the
sub-group analysis by study areas.



https://doi.org/10.1371/journal.pone.0303388.g005

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Fig 6. Forest plot of the prevalence of visual impairment with 95% CIs of the
sub-group analysis by study period.



https://doi.org/10.1371/journal.pone.0303388.g006


FACTORS ASSOCIATED WITH VISUAL IMPAIRMENT

In the review, fourteen studies [20, 34, 35, 37, 40, 43–47, 49, 50, 59, 60]
reported that DM with a duration of diagnosis ≥10 years was significantly
associated with visual impairment. The pooled AOR of visual impairment for
diabetes patients with a duration of diagnosis ≥10 years was 3.18 (95% CI: 1.85,
5.49; I2 = 91.05%; P<0.001) (Fig 7).

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Fig 7. Forest plot of the AORs with 95% CIs of studies on the association of DM
with duration of diagnosis ≥10 years and visual impairment among diabetes
patients in Ethiopia, 2023.



https://doi.org/10.1371/journal.pone.0303388.g007

Thirteen studies [35, 37, 45, 46, 49, 50, 55, 58–60, 62–64] showed that the
presence of co-morbid hypertension was significantly associated with visual
impairment. The pooled AOR of visual impairment for diabetes patients with
co-morbid hypertension was 3.26 (95% CI: 1.93, 5.50; I2 = 82.18%; P<0.001) (Fig
8).

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Fig 8. Forest plot of the adjusted odds ratios with 95% CIs of studies on the
association of comorbid hypertension and visual impairment among diabetes
patients in Ethiopia, 2023.



https://doi.org/10.1371/journal.pone.0303388.g008

Nine studies [20, 34, 35, 39, 46, 49, 50, 63, 64] also reported a significant
association between poor glycemic control and visual impairment. The pooled AOR
of visual impairment for diabetes patients with poor glycemic control was 4.30
(95% CI: 3.04, 6.06; I2 = 25.51%; P<0.22) (Fig 9).

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Fig 9. Forest plot of the adjusted odds ratios with 95% CIs of studies on the
association of poor glycemic control and visual impairment among diabetes
patients in Ethiopia, 2023.



https://doi.org/10.1371/journal.pone.0303388.g009

Thirteen studies [20, 34, 37–40, 43, 45, 47, 55, 56, 59, 63] reported that age
≥56 years was significantly associated with visual impairment. The pooled AOR of
visual impairment for diabetes patients with the age of ≥56 years was 4.13 (95%
CI: 2.27, 7.52; I2 = 88.82%; P<0.001).

Three studies [37, 59, 63] reported a significant association between family
history of DM and visual impairment. The pooled AOR of visual impairment for
diabetes patients with family history of DM was 4.18 (95% CI: 2.61, 6.69; I2 =
0%; P<0.98).

Five studies [35, 38, 44, 49, 56] showed that obesity was significantly
associated with visual impairment. The pooled AOR of visual impairment for
diabetes patients having obesity was 4.77 (95% CI: 3.00, 7.59; I2 = 0%; P<0.93).

Four studies [20, 38, 56, 64] reported a significant association between poor
physical activity and visual impairment. The pooled AOR of visual impairment for
diabetes patients with poor physical activity was 2.46 (95% CI: 1.75, 3.46; I2 =
0%; P<0.48).

Two studies [38, 56] reported a significant association between the presence of
visual symptoms and visual impairment. The pooled AOR of visual impairment for
diabetes patients having visual symptoms was 4.28 (95% CI: 2.73, 6.69; I2 = 0%;
P<0.85).

Two studies [34, 56] showed that no history of eye exam was significantly
associated with visual impairment. The pooled AOR of visual impairment for
diabetes patients with no history of eye exam was 2.30 (95% CI: 1.47, 3.57; I2 =
0%; P<0.34).


DISCUSSION

This review aimed to determine the overall pooled prevalence of visual
impairment and its associated factors among diabetes patients in Ethiopia. In
this study, the pooled prevalence of visual impairment was 21.73% (95% CI:18.15,
25.30; I2 = 96.47%; P<0.001), which was higher than the study findings conducted
in Spain (8.07%) [71], rural India (10.30%) [72], Northwestern Tanzania (10.30%)
[73], Malaysia (13.50%) [74], Pakistan (17.60%) [75], Dares Salaam-Tanzania
(18.60%) [76] and India (21.70%) [77]. But this finding was lower than the study
findings conducted in Tunisia (22.20%) [78], China (23.0%) [79], Tanzania
(23.30%) [80], Ghana (24.0%) [81], India (24.90%) [82], Asia (28.0%) [83],
Zimbabwe (28.40%) [84], Bangladesh (29.40%) [85], Cameroon (29.70%) [11], Libya
(30.60%) [86], China (34.08%) [87], Zambia (36.0%) [12], Nepal (38.26%) [88],
Sudan (39.90%) [89], Iran (41.90%) [90] and Yemen (76.50%) [91]. This variation
might be due to differences in healthcare systems, methodologies, study
settings, study periods, sample sizes and differences in health-seeking behavior
of the study participants [26, 55, 57].

Besides, the finding of this study reported that diabetes patients with a
duration of diagnosis ≥10 years were 3.18 times more likely to develop visual
impairment compared to diabetes patients with a duration of diagnosis <10 years.
This finding was congruent with studies conducted in China [13] and India [82].
The likely reason for this association is prolonged diabetes can decrease
insulin hormone production by the pancreas or result in target cell resistance.
This, in turn, increases the risk of developing diabetic retinopathy, cataract,
and ocular edema that cause visual impairment [34, 47, 75, 88].

The finding of this study also showed that diabetes patients with co-morbid
hypertension were 3.26 times more likely to develop visual impairment than
diabetes patients without co-morbid hypertension. This finding was similar to a
study conducted in India [82]. High blood pressure accelerates the progress and
development of micro vascular complications due to increased intracellular
hyperglycemia. So, increased plasma glucose level leads to damage to retinal
blood vessels and glomeruli, and impairing the regulation of retinal perfusion.
Finally, it ends up with visual impairment [20, 82, 88].

Additionally, this study reported that diabetes patients with poor glycemic
control were 4.30 times more likely to encounter visual impairment compared to
diabetes patients with good glycemic control. This finding was in line with a
study conducted in India [82]. It could be explained that an increment in the
level of hyperglycemia or having poor glycemic control can increase the onset
and rate of progression of diabetic retinopathy, leading to visual impairment
[34].

Similarly, the study finding showed that diabetes patients with the age ≥56
years were 4.13 times more likely to develop visual impairment compared to
diabetes patients with the age of <56 years. This finding was consistent with a
study conducted in Bangladesh [85]. This might be explained as age advances,
there might be decrease in physical activity, loss of muscle mass, gain weight
and the fatty cells become more resistant to insulin action leading to
hyperglycemia. Besides, as age increases, blood vessels become hard, losing
their elasticity and more stiffened and leads to cardiac insufficient which
end-up with micro vascular complications [20, 39, 63].

Likewise, the study finding indicated that diabetes patients with a family
history of DM were 4.18 times more likely to experience visual impairment than
diabetes patients who had no family history. This finding was in line with a
study conducted in Iran [92]. A family history of diabetes suggests familial
genetic and epigenetic contributions to the disease complications. Therefore,
patients with a family history of DM are more likely to develop micro vascular
complications, such as diabetic retinopathy, cataract and macular edema, leading
to visual impairment [59].

In this study, diabetes patients having obesity were also 4.77 times more likely
to develop visual impairment compared to patients without having obesity. This
finding was similar to a study conducted in Bangladesh [85] and Iran [93]. It
could be explained that obesity causes increasing blood viscosity, oxidative
stress, vascular growth factors, leptin, cytokines, and intercellular adhesion
molecule 1 (ICAM 1), which leads to micro vascular complications and visual
impairment [94].

Similarly, the finding of this reported that diabetes patients with poor
physical activity were 2.46 times more likely to encounter visual impairment
compared to patients with good physical activity. This might be because exercise
can promote an increase in the bioavailability of nitric oxide which decreases
blood pressure, post-exercise can increase glycolipid uptake and utilization,
which improves glucose homeostasis, insulin sensitivity, maintaining glycemic
level and optimized body mass index [95].

Additionally, this study indicated that diabetes patients having visual symptoms
were 4.28 times more likely to develop visual impairment than patients without
visual symptoms. Visual symptoms, such as eye pain, low vision and blurring of
vision among diabetes patients can be worsened as the DM advances, leading to
visual impairment [38, 56].

Furthermore, the finding of this study reported that diabetes patients having no
history of eye exam were 2.30 times more likely to encounter visual impairment
compared to their counterparts. This might be due to the fact that the
utilization of eye care services for diabetic patients is vital for managing
sight-threatening diabetes-related eye complications early. On the contrary,
those diabetes patients who didn’t have a history of eye examinations are highly
susceptible to undiagnosed diabetes-related eye complications [34, 56].


STRENGTHS AND LIMITATIONS OF THE STUDY

To the best of our knowledge, this is the first study to combine the results of
multiple studies conducted in Ethiopia, providing stronger evidence on visual
impairment and the factors predicting it. While all the studies are of good
quality, it should be noted that the majority of the studies analyzed were
cross-sectional. Moreover, the study couldn’t perform a subgroup analysis using
the study designs.


CONCLUSIONS

The overall pooled prevalence of visual impairment was considerably high in
Ethiopia. DM with a duration of diagnosis ≥10 years, presence of co-morbid
hypertension, poor glycemic control, age ≥56 years, family history of DM,
obesity, poor physical activity, presence of visual symptoms and no history of
eye exam were independent predictors of visual impairment. Therefore, diabetic
patients with these identified risks should be screened, and managed early to
reduce the occurrence of visual impairment related to diabetes. Moreover, public
health policy with educational programs and regular promotion of sight screening
for all diabetes patients is needed.


SUPPORTING INFORMATION

PRISMA statement guideline.

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Supplemental Table 1
:
PRISMA checklist
Section/Topic
#
Checklist item
Reported on
page #
TITLE
Title
1
Identify the report as a systematic review, meta-analysis, or both.
1
ABSTRACT
Abstract
2
Provide a structured summary including, as applicable: background; objectives;
data
sources; study eligibility criteria, participants, and interventions; study
appraisal and
synthesis methods; results; limitations; conclusions and implications of key
findings;
systematic review registration number.
2-3
INTRODUCTION
Rationale
3
Describe the rationale for the review in the context of existing knowledge.
4-5
Objectives
4
Provide an explicit statement of questions being addressed with reference to
participants,
interventions, comparisons, outcomes, and study design (PICOS).
5
METHODS
Protocol and
registration
5
Indicate if a review protocol exists, if and where it can be accessed (e.g., Web
address),
and, if available, provide registration information including registration
number.
5
Eligibility criteria
6
Specify study characteristics (e.g., PICOS, length of follow-up) and report
characteristics
(e.g., years considered, language, publication status) used as criteria for
eligibility, giving
rationale.
5
Information sources
7
Specify all databases, registers, websites, organisations, reference lists and
other sources
searched or consulted to identify studies. Specify the date when each source was
last
searched or consulted.
5
Search strategy
8
Present the full search strategies for all databases, registers and websites,
including any
filters and limits used.
5
Study selection
9
State the process for selecting studies (i.e., screening, eligibility, included
in systematic
review, and, if applicable, included in the meta-analysis).
6
Data collection
process
10
Describe method of data extraction from reports (e.g., piloted forms,
independently, in
duplicate) and any processes for obtaining and confirming data from
investigators.
6
Data items
11
List and define all variables for which data were sought (e.g., PICOS, funding
sources) and
any assumptions and simplifications made.
7
Risk of bias in
individual studies
12
Describe methods used for assessing risk of bias of individual studies
(including
specification of whether this was done at the study or outcome level), and how
this
information is to be used in any data synthesis.
11
Summary measures
13
State the principal summary measure(s) (e.g., risk ratio, mean difference) used
in the
synthesis.
10
Synthesis of results
14
Describe the methods of handling data and combining results of studies, if done,
including
measures of consistency (e.g., I2) for each meta-analysis.
7-9
Risk of bias across
studies
15
Specify any assessment of risk of bias that may affect the cumulative evidence
(e.g.,
publication bias, selective reporting within studies)
11
Additional analyses
16
Describe methods of additional analyses (e.g., sensitivity or subgroup
analyses, meta-regression), if done, indicating which were pre-specified.
14-17
RESULTS
Study selection
17
Give numbers of studies screened, assessed for eligibility, and included in the
review, with
reasons for exclusions at each stage, ideally with a flow diagram.
7 & Fig1
Study characteristics
18
For each study, present characteristics for which data were extracted (e.g.,
study size,
PICOS, follow-up period) and provide the citations.
10 & Table1
Risk of bias within
studies
19
Present data on risk of bias of each included study and, if available, any
outcome level
assessment.
12&
S/Table2
1
Results of individual
studies
20
For all outcomes considered (benefits or harms), present, for each study: (a)
simple
summary data for each intervention group (b) effect estimates and confidence
intervals,
ideally with a forest plot.
11 & Fig2
Synthesis of results
21
Present results of each meta-analysis done, including confidence intervals and
measures of
consistency.
7-15
Reporting biases
22
Present results of any assessment of risk of bias across studies.
14& Table5
Additional analysis
23
Give results of additional analyses, if done (e.g., sensitivity or subgroup
analyses, meta-
regression.
14&15
DISCUSSION
Summary of evidence
24
Summarize the main findings including the strength of evidence for each main
outcome;
consider their relevance to key groups (e.g., healthcare providers, users, and
policy
makers).
18-25
Limitations
25
Discuss limitations at study and outcome level (e.g., risk of bias), and at
review-level (e.g.,
incomplete retrieval of identified research, reporting bias).
26
Conclusions
26
Provide a general interpretation of the results in the context of other
evidence, and
implications for future research.
26
OTHERS INFORMATION
Funding
27
Describe sources of funding for the systematic review and other support (e.g.,
supply of
data); role of funders for the systematic review.
27
Competing interests
28
Declare any competing interests of review authors.
28
Availability of data,
code and other
materials
29
Report which of the data are publicly available and where they can be found:
template data
collection forms; data extracted from included studies; data used for all
analyses; analytic
code; any other materials used in the review.
27
Note: From: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD,
et al. The
PRISMA 2020 statement: an updated guideline for reporting systematic reviews and
Meta analyses. BMJ
2021;372: n71. doi: 10.1136/bmj. n71. For more information, visit:
http://www.prisma-statement.org/
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ACKNOWLEDGMENTS

We would like to extend our deepest gratitude to Mr. Henok Andualem for his
unreserved statistical and methodological support throughout the review.


REFERENCES

 1.  1. Akrofi B, Tetteh J, Amissah-Arthur KN, Buxton EN, Yawson A. Utilization
     of eye health services and diabetic retinopathy: a cross-sectional study
     among persons living with diabetes visiting a tertiary eye care facility in
     Ghana. BMC Health Services Research. 2021 Dec;21(1):1–1.
     * View Article
     * Google Scholar
 2.  2. World Health Organization. Noncommunicable diseases country profiles
     2018.
 3.  3. Kaiser AB, Zhang N, Der Pluijm WV. Global prevalence of type 2 diabetes
     over the next ten years (2018–2028). Diabetes. 2018 Jul 1;67(Supplement-1).
     * View Article
     * Google Scholar
 4.  4. Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge
     AW, et al. IDF Diabetes Atlas: Global estimates of diabetes prevalence for
     2017 and projections for 2045. Diabetes research and clinical practice.
     2018 Apr 1;138:271–81. pmid:29496507
     * View Article
     * PubMed/NCBI
     * Google Scholar
 5.  5. Achigbu EO, Agweye CT, Achigbu KI, Mbatuegwu AI. Diabetic retinopathy in
     sub-Saharan Africa: a review of magnitude and risk factors. Nigerian
     Journal of Ophthalmology. 2021 Jan 1;29(1):3.
     * View Article
     * Google Scholar
 6.  6. Feleke Y, Enquselassie F. An assessment of the health care system for
     diabetes in Addis Ababa, Ethiopia. Ethiopian journal of health development.
     2005;19(3):203–10.
     * View Article
     * Google Scholar
 7.  7. Hoda SA, Hoda RS. Rubin’s pathology: clinicopathologic foundations of
     medicine. JAMA. 2007 Nov 7;298(17):2070–5.
     * View Article
     * Google Scholar
 8.  8. Pascolini D, Mariotti SP. Global estimates of visual impairment: 2010.
     British Journal of Ophthalmology. 2012 May 1;96(5):614–8. pmid:22133988
     * View Article
     * PubMed/NCBI
     * Google Scholar
 9.  9. World Health Organization.Blindness and vision impairment, 2022.
 10. 10. Burgess PI, Allain TJ, García‐Fiñana M, Beare NA, 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.
     pmid:24823871
     * View Article
     * PubMed/NCBI
     * Google Scholar
 11. 11. Jingi AM, Nansseu JR, Noubiap JJ, Bilong Y, Ellong A, Mvogo CE.
     Diabetes and visual impairment in sub-Saharan Africa: evidence from
     Cameroon. Journal of Diabetes & Metabolic Disorders. 2015 Dec;14:1–8.
     pmid:25866740
     * View Article
     * PubMed/NCBI
     * Google Scholar
 12. 12. Lewis A.D., Hogg R.E., Chandran M., Musonda L., North L., Chakravarthy
     U., et al., 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, 32(7), pp.1201–1208. pmid:29503450
     * View Article
     * PubMed/NCBI
     * Google Scholar
 13. 13. Cui Y, Zhang L, Zhang M, Yang X, Zhang L, Kuang J, et al. Prevalence
     and causes of low vision and blindness in a Chinese population with type 2
     diabetes: the Dongguan Eye Study. Scientific Reports. 2017 Sep
     11;7(1):11195. pmid:28894238
     * View Article
     * PubMed/NCBI
     * Google Scholar
 14. 14. Eckert KA, Carter MJ, Lansingh VC, Wilson DA, Furtado JM, Frick KD, et
     al. A simple method for estimating the economic cost of productivity loss
     due to blindness and moderate to severe visual impairment. Ophthalmic
     epidemiology. 2015 Sep 3;22(5):349–55. pmid:26395661
     * View Article
     * PubMed/NCBI
     * Google Scholar
 15. 15. Flaxman SR, Bourne RR, Resnikoff S, Ackland P, Braithwaite T, Cicinelli
     MV, et al. Global causes of blindness and distance vision impairment
     1990–2020: a systematic review and meta-analysis. The Lancet Global Health.
     2017 Dec 1;5(12):e1221–34. pmid:29032195
     * View Article
     * PubMed/NCBI
     * Google Scholar
 16. 16. Khan A, Petropoulos IN, Ponirakis G, Malik RA. Visual complications in
     diabetes mellitus: beyond retinopathy. Diabetic medicine. 2017
     Apr;34(4):478–84. pmid:27917530
     * View Article
     * PubMed/NCBI
     * Google Scholar
 17. 17. Zhang X, Gregg EW, Cheng YJ, Thompson TJ, Geiss LS, Duenas MR, et al.
     Diabetes mellitus and visual impairment: national health and nutrition
     examination survey, 1999–2004. Archives of Ophthalmology. 2008 Oct
     13;126(10):1421–7. pmid:18852421
     * View Article
     * PubMed/NCBI
     * Google Scholar
 18. 18. Agarwal S, Raman R, Paul PG, Rani PK, Uthra S, Gayathree R, et al.
     Sankara Nethralaya-Diabetic retinopathy epidemiology and molecular genetic
     study (SN-DREAMS 1): Study design and research methodology. Ophthalmic
     epidemiology. 2005 Jan 1;12(2):143–53. pmid:16019696
     * View Article
     * PubMed/NCBI
     * Google Scholar
 19. 19. Idil A, Caliskan D, Ocaktan E. The prevalence of blindness and low
     vision in older onset diabetes mellitus and associated factors: a
     community-based study. European journal of ophthalmology. 2004
     Jul;14(4):298–305. pmid:15309974
     * View Article
     * PubMed/NCBI
     * Google Scholar
 20. 20. Seid MA, Ambelu A, Diress M, Yeshaw Y, Akalu Y, Dagnew B. Visual
     impairment and its predictors among people living with type 2 diabetes
     mellitus at Dessie town hospitals, Northeast Ethiopia: institution-based
     cross-sectional study. BMC ophthalmology. 2022 Feb 3;22(1):52.
     pmid:35114950
     * View Article
     * PubMed/NCBI
     * Google Scholar
 21. 21. Steinmetz JD, Bourne RR, Briant PS, Flaxman SR, Taylor HR, Jonas JB, et
     al. Causes of blindness and vision impairment in 2020 and trends over 30
     years, and prevalence of avoidable blindness in relation to VISION 2020:
     the Right to Sight: an analysis for the Global Burden of Disease Study. The
     Lancet Global Health. 2021 Feb 1;9(2):e144–60. pmid:33275949
     * View Article
     * PubMed/NCBI
     * Google Scholar
 22. 22. Lachin J.M. and Nathan D.M., 2021. Understanding metabolic memory: the
     prolonged influence of glycemia during the Diabetes Control and
     Complications Trial (DCCT) on future risks of complications during the
     study of the Epidemiology of Diabetes Interventions and Complications
     (EDIC). Diabetes Care, 44(10), pp.2216–2224. pmid:34548284
     * View Article
     * PubMed/NCBI
     * Google Scholar
 23. 23. Nathan DM, DCCT/Edic Research Group. The diabetes control and
     complications trial/epidemiology of diabetes interventions and
     complications study at 30 years: overview. Diabetes care. 2014 Jan
     1;37(1):9–16. pmid:24356592
     * View Article
     * PubMed/NCBI
     * Google Scholar
 24. 24. Relhan N, Flynn HW. The Early Treatment Diabetic Retinopathy Study
     historical review and relevance to today’s management of diabetic macular
     edema. Current opinion in ophthalmology. 2017 May 1;28(3):205–12.
     pmid:28151747
     * View Article
     * PubMed/NCBI
     * Google Scholar
 25. 25. Alemu S, Dessie A, Tsegaw A, Patterson CC, Parry EH, Phillips DI, et
     al. Retinopathy in type 1 diabetes mellitus: Major differences between
     rural and urban dwellers in northwest Ethiopia. Diabetes research and
     clinical practice. 2015 Jul 1;109(1):191–8. pmid:25944537
     * View Article
     * PubMed/NCBI
     * Google Scholar
 26. 26. Kabtu E, Tsegaw A. Prevalence of diabetic macular edema and risk
     factors among diabetic patients at the University of Gondar Tertiary Eye
     Care and Training Center, North West Ethiopia. medRxiv. 2022 Apr
     17:2022–04.
     * View Article
     * Google Scholar
 27. 27. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et
     al. The PRISMA 2020 statement: an updated guideline for reporting
     systematic reviews. International journal of surgery. 2021 Apr 1;88:105906.
     pmid:33789826
     * View Article
     * PubMed/NCBI
     * Google Scholar
 28. 28. DerSimonian R, Kacker R. Random-effects model for meta-analysis of
     clinical trials: an update. Contemporary clinical trials. 2007 Feb
     1;28(2):105–14. pmid:16807131
     * View Article
     * PubMed/NCBI
     * Google Scholar
 29. 29. Peters JL, Sutton AJ, Jones DR, Abrams KR, Rushton L. Comparison of two
     methods to detect publication bias in meta-analysis. Jama. 2006 Feb
     8;295(6):676–80. pmid:16467236
     * View Article
     * PubMed/NCBI
     * Google Scholar
 30. 30. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency
     in meta-analyses. Bmj. 2003 Sep 4;327(7414):557–60. pmid:12958120
     * View Article
     * PubMed/NCBI
     * Google Scholar
 31. 31. Borenstein M, Hedges LV, Higgins JP, Rothstein HR. A basic introduction
     to fixed‐effect and random‐effects models for meta‐analysis. Research
     synthesis methods. 2010 Apr;1(2):97–111. pmid:26061376
     * View Article
     * PubMed/NCBI
     * Google Scholar
 32. 32. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta‐analysis.
     Statistics in medicine. 2002 Jun 15;21(11):1539–58. pmid:12111919
     * View Article
     * PubMed/NCBI
     * Google Scholar
 33. 33. Stovold E, Beecher D, Foxlee R, Noel-Storr A. Study flow diagrams in
     Cochrane systematic review updates: an adapted PRISMA flow diagram.
     Systematic reviews. 2014 Dec;3:1–5.
     * View Article
     * Google Scholar
 34. 34. Alemayehu HB, Tegegn MT, Tilahun MM. Prevalence and associated factors
     of visual impairment among adult diabetic patients visiting Adare General
     Hospital, Hawassa, South Ethiopia, 2022. Plos one. 2022 Oct
     13;17(10):e0276194. pmid:36227943
     * View Article
     * PubMed/NCBI
     * Google Scholar
 35. 35. Alemu Mersha G, Alimaw YA, Woredekal AT. Prevalence of diabetic
     retinopathy among diabetic patients in Northwest Ethiopia: A cross
     sectional hospital based study. Plos one. 2022 Jan 21;17(1):e0262664.
     pmid:35061820
     * View Article
     * PubMed/NCBI
     * Google Scholar
 36. 36. Asemu MT, Ahunie MA. The impact of diabetes on visual acuity in
     Ethiopia, 2021. PloS one. 2021 Aug 13;16(8):e0256145. pmid:34388219
     * View Article
     * PubMed/NCBI
     * Google Scholar
 37. 37. Chisha Y, Terefe W, Assefa H, Lakew S. Prevalence and factors
     associated with diabetic retinopathy among diabetic patients at Arbaminch
     General Hospital, Ethiopia: Cross sectional study. PloS one. 2017 Mar
     2;12(3):e0171987. pmid:28253261
     * View Article
     * PubMed/NCBI
     * Google Scholar
 38. 38. 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 African Journal of Ophthalmology. 2022
     Jan;29(1):19. pmid:36685341
     * View Article
     * PubMed/NCBI
     * Google Scholar
 39. 39. Ejeta A, Abdosh T, Hawulte B, Lamessa A, Belete Fite M, Fekadu G.
     Diabetes concordant comorbidities and associated factors among adult
     diabetic out-patients at Hiwot Fana specialized university hospital, Harar,
     Eastern Ethiopia: a cross-sectional study. Diabetes, Metabolic Syndrome and
     Obesity. 2021 May 21:2281–9. pmid:34045877
     * View Article
     * PubMed/NCBI
     * Google Scholar
 40. 40. Ejigu T, Tsegaw A. Prevalence of diabetic retinopathy and risk factors
     among diabetic patients at university of Gondar tertiary eye care and
     training center, North-West Ethiopia. Middle East African Journal of
     Ophthalmology. 2021 Apr;28(2):71. pmid:34759663
     * View Article
     * PubMed/NCBI
     * Google Scholar
 41. 41. Gudina EK, Amade ST, Tesfamichael FA, Ram R. Assessment of quality of
     care given to diabetic patients at Jimma University Specialized Hospital
     diabetes follow-up clinic, Jimma, Ethiopia. BMC Endocrine disorders. 2011
     Dec;11(1):1–9. pmid:22185229
     * View Article
     * PubMed/NCBI
     * Google Scholar
 42. 42. Gizaw M, Harries AD, Ade S, Tayler-Smith K, Ali E, Firdu N, et al.
     Diabetes mellitus in Addis Ababa, Ethiopia: admissions, complications and
     outcomes in a large referral hospital. Public Health Action. 2015 Mar
     21;5(1):74–8. pmid:26400605
     * View Article
     * PubMed/NCBI
     * Google Scholar
 43. 43. Lebeta R, Argaw Z, Walle B. Prevalence of diabetic complications and
     its associated factors among diabetes mellitus patients attending diabetes
     mellitus clinics; institution based cross sectional study. Am J Health Res.
     2017 Mar 9;5(2):38.
     * View Article
     * Google Scholar
 44. 44. Sahiledengle B, Assefa T, Negash W, Tahir A, Regasa T, Tekalegn Y, et
     al. Prevalence and Factors Associated with Diabetic Retinopathy among Adult
     Diabetes Patients in Southeast Ethiopia: A Hospital-Based Cross-Sectional
     Study. Clinical Ophthalmology. 2022 Jan 1:3527–45. pmid:36274673
     * View Article
     * PubMed/NCBI
     * Google Scholar
 45. 45. Seid MA, Akalu Y, Gela YY, Belsti Y, Diress M, Fekadu SA, et al.
     Microvascular complications and its predictors among type 2 diabetes
     mellitus patients at Dessie town hospitals, Ethiopia. Diabetology &
     Metabolic Syndrome. 2021 Dec;13(1):1–8. pmid:34404465
     * View Article
     * PubMed/NCBI
     * Google Scholar
 46. 46. Shibru T, Aga F, Boka A. Prevalence of Diabetic Retinopathy and
     Associated Factors among Type 2 Diabetes Patients at Tikur Anbessa
     Hospital, Ethiopia. Journal of Diabetes & Metabolism, 2019. 10(02).
     * View Article
     * Google Scholar
 47. 47. Tesfaye DJ. Coexistence of chronic complications among diabetic
     patients at nigist eleni mohammed memorial hospital, hossana, south
     Ethiopia. Open Access Library Journal. 2015;2(01):1.
     * View Article
     * Google Scholar
 48. 48. Tilahun AN, Waqtola C, Tewodros GM, Amare DW, Yohannis M. Major micro
     vascular complications and associated risk factors among diabetic
     outpatients in Southwest Ethiopia. Endocrinol Metab Syndr. 2017;6(4):272.
     * View Article
     * Google Scholar
 49. 49. Tilahun M, Gobena T, Dereje D, Welde M, Yideg G. Prevalence of Diabetic
     retinopathy and its associated factors among diabetic patients at Debre
     Markos referral hospital, Northwest Ethiopia, 2019: hospital-based
     cross-sectional study. Diabetes, Metabolic Syndrome and Obesity. 2020 Jun
     24:2179–87. pmid:32636659
     * View Article
     * PubMed/NCBI
     * Google Scholar
 50. 50. Tilahun M, Yitbarek GY, Taderegew MM, Alem DT, Gedfew M, Akalu TY, et
     al. The Magnitude of Diabetic Macular Edema and Its Associated Factors
     among Diabetic Patients at Debre Markos Referral Hospital, North-West
     Ethiopia, 2021." A Hospital Cross-Sectional Study.
     * View Article
     * Google Scholar
 51. 51. Tsegaw A, Alemu S, Dessie A, Patterson CC, Parry EH, Phillips DI, et
     al. Diabetic retinopathy in type 2 diabetes mellitus patients attending the
     diabetic clinic of the University of Gondar Hospital, Northwest Ethiopia.
     Journal of Ophthalmology. 2021 Mar 31;2021. pmid:33859836
     * View Article
     * PubMed/NCBI
     * Google Scholar
 52. 52. Worku D, Hamza L, Woldemichael K. Patterns of diabetic complications at
     jimma university specialized hospital, southwest ethiopia. Ethiopian
     journal of health sciences. 2010;20(1). pmid:22434958
     * View Article
     * PubMed/NCBI
     * Google Scholar
 53. 53. Woyessa DN. Magnitude of Diabetic Retinopathy in newly diagnosed type 2
     diabetes patients in Menelik II Hospital, Addis Ababa. Ethiopian Medical
     Journal. 2020 Jun 25;58(03).
     * View Article
     * Google Scholar
 54. 54. YimamAhmed M, Hambisa Ejigu S, Zewudie Zeleke A, Yimam Hassen M.
     Glycemic control, diabetes complications and their determinants among
     ambulatory diabetes mellitus patients in southwest ethiopia: A prospective
     cross-sectional study. Diabetes, Metabolic Syndrome and Obesity. 2020 Apr
     9:1089–95. pmid:32308458
     * View Article
     * PubMed/NCBI
     * Google Scholar
 55. 55. Zegeye AF, Temachu YZ, Mekonnen CK. Prevalence and factors associated
     with Diabetes retinopathy among type 2 diabetic patients at Northwest
     Amhara Comprehensive Specialized Hospitals, Northwest Ethiopia 2021. BMC
     ophthalmology. 2023 Jan 5;23(1):9. pmid:36604682
     * View Article
     * PubMed/NCBI
     * Google Scholar
 56. 56. Zewdu K. Prevalence and associated factors of visual impairment among
     diabetic patients at Debre Berhan Referral Hospital, North Shoa, Ethiopia,
     2017 (Doctoral dissertation).
 57. 57. Azeze TK, Sisay MM, Zeleke EG. Incidence of diabetes retinopathy and
     determinants of time to diabetes retinopathy among diabetes patients at
     Tikur Anbessa Hospital, Ethiopia: a retrospective follow up study. BMC
     research notes. 2018 Dec;11(1):1–6.
     * View Article
     * Google Scholar
 58. 58. Debele GR, Kanfe SG, Weldesenbet AB, Ayana GM, Jifar WW, Raru TB.
     Incidence of diabetic retinopathy and its predictors among newly diagnosed
     type 1 and type 2 diabetic patients: a retrospective follow-up study at
     tertiary health-care setting of Ethiopia. Diabetes, Metabolic Syndrome and
     Obesity. 2021 Mar 22:1305–13. pmid:33790598
     * View Article
     * PubMed/NCBI
     * Google Scholar
 59. 59. Gelcho GN, Gari FS. Time to Diabetic Retinopathy and Its Risk Factors
     among Diabetes Mellitus Patients in Jimma University Medical Center, Jimma,
     Southwest Ethiopia. Ethiopian Journal of Health Sciences. 2022 Sep
     20;32(5):937–46. pmid:36262700
     * View Article
     * PubMed/NCBI
     * Google Scholar
 60. 60. Kebede SA, Tessema ZT, Balcha SA, Ayele TA. Joint modeling of time to
     diabetic retinopathy and change in fasting blood sugar among type 2
     diabetic patients, Northwest Ethiopia. Scientific Reports. 2022 Feb
     9;12(1):2236. pmid:35140323
     * View Article
     * PubMed/NCBI
     * Google Scholar
 61. 61. Takele MB, Boneya DJ, Alemu HA, Tsegaye TB, Birhanu MY, Alemu S, et al.
     Retinopathy among Adult Diabetics and Its Predictors in Northwest Ethiopia.
     Journal of Diabetes Research. 2022 Feb 15;2022. pmid:35211627
     * View Article
     * PubMed/NCBI
     * Google Scholar
 62. 62. Wolde HF, Atsedeweyen A, Jember A, Awoke T, Mequanent M, Tsegaye AT, et
     al. Predictors of vascular complications among type 2 diabetes mellitus
     patients at University of Gondar Referral Hospital: a retrospective
     follow-up study. BMC endocrine disorders. 2018 Dec;18(1):1–8.
     * View Article
     * Google Scholar
 63. 63. Garoma D, Merga H, Hiko D. Determinants of diabetic retinopathy in
     Southwest Ethiopia: a facility-based case-control study. BMC Public Health.
     2020 Dec;20(1):1–9.
     * View Article
     * Google Scholar
 64. 64. Seid K, Tesfaye T, Belay A, Mohammed H. Determinants of diabetic
     retinopathy in Tikur Anbessa Hospital, Ethiopia: a case–control study.
     Clinical Diabetes and Endocrinology. 2021 Dec;7:1–9.
     * View Article
     * Google Scholar
 65. 65. Diress M, Belsti Y, Getnet M, Fekadu SA, Dagnew B, Akalu Y, et al.
     Visual impairment and associated factors among pregnant women attending
     antenatal care units at health institutions in Gondar City Administration,
     Northwest Ethiopia. BMC Pregnancy and Childbirth. 2021 Dec 13;21(1):824.
     pmid:34903217
     * View Article
     * PubMed/NCBI
     * Google Scholar
 66. 66. Habtewold TD, Tsega WD, Wale BY. Diabetes mellitus in outpatients in
     Debre Berhan referral hospital, Ethiopia. Journal of diabetes research.
     2016 Jan 6;2016. pmid:26881245
     * View Article
     * PubMed/NCBI
     * Google Scholar
 67. 67. Peters MD, Godfrey CM, McInerney P, Soares CB, Khalil H, Parker D. The
     Joanna Briggs Institute reviewers’ manual 2015: methodology for JBI scoping
     reviews.
 68. 68. Abera E. Patterns of chronic complications of diabetic patients in
     Menelik II Hospital, Ethiopia. Ethiopian Journal of Health Development.
     2000;14(1):113–6.
     * View Article
     * Google Scholar
 69. 69. Shibeshi MS, Fantahun B, Kebede T, Tilahun B. Pediatric diabetic
     retinopathy: experience of a tertiary hospital in Ethiopia. BMC research
     notes. 2016 Dec;9(1):1–6. pmid:26899627
     * View Article
     * PubMed/NCBI
     * Google Scholar
 70. 70. Hoy D, Brooks P, Woolf A, Blyth F, March L, Bain C, et al. Assessing
     risk of bias in prevalence studies: modification of an existing tool and
     evidence of interrater agreement. Journal of clinical epidemiology. 2012
     Sep 1;65(9):934–9. pmid:22742910
     * View Article
     * PubMed/NCBI
     * Google Scholar
 71. 71. Salinero-Fort MA, San Andres-Rebollo FJ, de Burgos-Lunar C,
     Arrieta-Blanco FJ, Gomez-Campelo P, MADIABETES Group. Four-year incidence
     of diabetic retinopathy in a Spanish cohort: the MADIABETES study. PLoS
     One. 2013 Oct 17;8(10):e76417. pmid:24146865
     * View Article
     * PubMed/NCBI
     * Google Scholar
 72. 72. Raman R., Ganesan S., Pal S.S., Kulothungan V. and Sharma T., 2014.
     Prevalence and risk factors for diabetic retinopathy in rural India.
     Sankara Nethralaya Diabetic Retinopathy Epidemiology and Molecular Genetic
     Study III (SN-DREAMS III), report no 2. BMJ Open Diabetes Research and
     Care, 2(1), p.e000005. pmid:25452856
     * View Article
     * PubMed/NCBI
     * Google Scholar
 73. 73. Msanga D, Reis K, Kayange N, Bakalemwa R, Kidenya B, Hau D, et al.
     Diabetic microvascular complications among children and adolescents in
     northwestern Tanzania: A cross-sectional study. Annals of Global Health.
     2020;86(1). pmid:32346524
     * View Article
     * PubMed/NCBI
     * Google Scholar
 74. 74. Naserrudin NA, Jeffree MS, Kaur N, Syed Abdul Rahim SS, Ibrahim MY.
     Diabetic retinopathy among type 2 diabetes mellitus patients in Sabah
     primary health clinics–Addressing the underlying factors. Plos one. 2022
     Jan 28;17(1):e0261249. pmid:35089931
     * View Article
     * PubMed/NCBI
     * Google Scholar
 75. 75. Sultan S, Fawwad A, Siyal NA, Butt A, Khokar AR, Basit A. Frequency and
     risk factors of diabetic retinopathy in patients with type 2 diabetes
     presenting at a tertiary care hospital. International Journal of Diabetes
     in Developing Countries. 2020 Mar;40:87–92.
     * View Article
     * Google Scholar
 76. 76. Lutale JK, Thordarson H, Sanyiwa A, Mafwiri M, Vetvik K, Krohn J.
     Diabetic retinopathy prevalence and its association with microalbuminuria
     and other risk factors in patients with Type 1 and Type 2 diabetes in Dar
     es Salaam, Tanzania. JOECSA. 2013 Jun 10;15(1).
     * View Article
     * Google Scholar
 77. 77. Gadkari SS, Maskati QB, Nayak BK. Prevalence of diabetic retinopathy in
     India: The all India ophthalmological society diabetic retinopathy eye
     screening study 2014. Indian journal of ophthalmology. 2016 Jan;64(1):38.
     pmid:26953022
     * View Article
     * PubMed/NCBI
     * Google Scholar
 78. 78. Kahloun R, Jelliti B, Zaouali S, Attia S, Ben Yahia S, Resnikoff S, et
     al. Prevalence and causes of visual impairment in diabetic patients in
     Tunisia, North Africa. Eye. 2014 Aug;28(8):986–91. pmid:24924439
     * View Article
     * PubMed/NCBI
     * Google Scholar
 79. 79. Liu L, Wu X, Liu L, Geng J, Yuan Z, Shan Z, et al. Prevalence of
     diabetic retinopathy in mainland China: a meta-analysis. PLoS One, 2012.
     7(9): p. e45264. pmid:23028893
     * View Article
     * PubMed/NCBI
     * Google Scholar
 80. 80. Chibuga EB. Prevalence, severity, risk indicators and impact of visual
     impairment among diabetic patients in Mkuranga district, Tanzania (Doctoral
     dissertation).
 81. 81. Lartey SY, Aikins AK. Visual impairment amongst adult diabetics
     attending a tertiary outpatient clinic. Ghana Medical Journal.
     2018;52(2):84–7. pmid:30662080
     * View Article
     * PubMed/NCBI
     * Google Scholar
 82. 82. Khan S, Rani T, Falak S, Charan LS. A Cross-Sectional Study on
     Prevalence of Diabetic Retinopathy and Its Associated Factor among Diabetic
     Patients. population.;13:16.
     * View Article
     * Google Scholar
 83. 83. Yang QH, Zhang Y, Zhang XM, Li XR. Prevalence of diabetic retinopathy,
     proliferative diabetic retinopathy and non-proliferative diabetic
     retinopathy in Asian T2DM patients: a systematic review and meta-analysis.
     International journal of ophthalmology. 2019;12(2):302. pmid:30809489
     * View Article
     * PubMed/NCBI
     * Google Scholar
 84. 84. Machingura PI, Macheka B, Mukona M, Mateveke K, Okwanga PN, Gomo E.
     Prevalence and risk factors associated with retinopathy in diabetic
     patients at Parirenyatwa Hospital outpatients’ clinic in Harare, Zimbabwe.
     Archives of medical and biomedical research. 2017 Mar 30;3(2):104–11.
     * View Article
     * Google Scholar
 85. 85. Hasan MA, Islam SM, Azad MA. A hospital-based cohort study on risk
     factors for diabetic retinopathy among patients with type 2 diabetes
     mellitus. Informatics in Medicine Unlocked. 2023 Jan 1;38:101219.
     * View Article
     * Google Scholar
 86. 86. Roaeid RB, Kadiki OA. Prevalence of long-term complications among Type
     2 diabetic patients in Benghazi, Libya. Journal of Diabetology. 2011 Sep
     1;2(3):3.
     * View Article
     * Google Scholar
 87. 87. Liu Y, Song Y, Tao L, Qiu W, Lv H, Jiang X, et al. Prevalence of
     diabetic retinopathy among 13473 patients with diabetes mellitus in China:
     a cross-sectional epidemiological survey in six provinces. BMJ open. 2017
     Jan 1;7(1):e013199. pmid:28069622
     * View Article
     * PubMed/NCBI
     * Google Scholar
 88. 88. Thapa R, Joshi DM, Rizyal A, Maharjan N, Joshi RD. Prevalence, risk
     factors and awareness of diabetic retinopathy among admitted diabetic
     patients at a tertiary level hospital in Kathmandu. Nepal J Ophthalmol.
     2014; 6. Br J Ophthalmol. 2015;99(12):1614–21.
     * View Article
     * Google Scholar
 89. 89. Elwali ES, Almobarak AO, Hassan MA, Mahmooud AA, Awadalla H, Ahmed MH.
     Frequency of diabetic retinopathy and associated risk factors in Khartoum,
     Sudan: population based study. International journal of ophthalmology.
     2017;10(6):948. pmid:28730087
     * View Article
     * PubMed/NCBI
     * Google Scholar
 90. 90. Maroufizadeh S, Almasi-Hashiani A, Hosseini M, Sepidarkish M, Samani
     RO. Prevalence of diabetic retinopathy in Iran: a systematic review and
     Meta-analysis. International journal of ophthalmology. 2017;10(5):782.
     pmid:28546938
     * View Article
     * PubMed/NCBI
     * Google Scholar
 91. 91. Bamashmus MA, Gunaid AA, Khandekar RB. Diabetic retinopathy, visual
     impairment and ocular status among patients with diabetes mellitus in
     Yemen: a hospital-based study. Indian journal of ophthalmology. 2009
     Jul;57(4):293. pmid:19574698
     * View Article
     * PubMed/NCBI
     * Google Scholar
 92. 92. Maghbooli Z, Pasalar P, Keshtkar A, Farzadfar F, Larijani B. Predictive
     factors of diabetic complications: a possible link between family history
     of diabetes and diabetic retinopathy. Journal of diabetes & metabolic
     disorders. 2014 Dec;13:1–5. pmid:24860795
     * View Article
     * PubMed/NCBI
     * Google Scholar
 93. 93. Ghaem H, Daneshi N, Riahi S, Dianatinasab M. The prevalence and risk
     factors for diabetic retinopathy in Shiraz, Southern Iran. Diabetes &
     Metabolism Journal. 2018 Dec;42(6):538–43. pmid:30113147
     * View Article
     * PubMed/NCBI
     * Google Scholar
 94. 94. Hinkle JL, Cheever KH. Brunner and Suddarth’s textbook of
     medical-surgical nursing. Wolters kluwer india Pvt Ltd; 2018 Aug 30.
 95. 95. Onakpoya OH, Kolawole BA, Adeoye AO, Adegbehingbe BO, Laoye O. Visual
     impairment and blindness in type 2 diabetics: Ife-Ijesa diabetic
     retinopathy study. International ophthalmology. 2016 Aug;36:477–85.
     pmid:26537878
     * View Article
     * PubMed/NCBI
     * Google Scholar


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