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Article

Adherence to Annual Fundus Exams among Chinese Population with Diagnosed Diabetes

by
Yifan Zhou
1,†,
Xiaowen Li
2,3,4,†,
Qinglei Sun
5,
Jin Wei
6,7,8,
Haiyun Liu
6,7,8,
Keyan Wang
9,* and
Jianfeng Luo
2,3,4,*
1
Department of Ophthalmology, Putuo People’s Hospital, Tongji University, Shanghai 200060, China
2
Department of Biostatistics, School of Public Health, Fudan University, Shanghai 200032, China
3
NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
4
Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China
5
Department of Ophthalmology, Shanghai East Hospital, Shanghai 200120, China
6
Department of Ophthalmology, Shanghai General Hospital (Shanghai First People’s Hospital), School of Medicine, Shanghai JiaoTong University, Shanghai 200080, China
7
National Clinical Research Center for Eye Diseases, Shanghai 200080, China
8
Shanghai Key Laboratory of Fundus Diseases, Shanghai 200080, China
9
Department of Ophthalmology, Eye and ENT Hospital of Fudan University, Shanghai 200031, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
J. Clin. Med. 2022, 11(22), 6859; https://doi.org/10.3390/jcm11226859
Submission received: 8 October 2022 / Revised: 8 November 2022 / Accepted: 14 November 2022 / Published: 21 November 2022
(This article belongs to the Special Issue Advances in Vision Disorders: Causes and Epidemiology)
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Abstract

:
Adherence to annual fundus examinations in the Chinese population with diabetes and its correlates have not been investigated. The present study obtained data for the first nationally representative survey in China, China Health and Retirement Longitudinal Survey (CHARLS), which collected a wide range of data every 2 years, including demographic, socioeconomic, medical and lifestyle-related information. The adherence rates to annual fundus exams across four waves (2011–2018) were assessed. Univariate and multivariable logistic regressions were used to determine factors associated with adherence. The adherence rates to annual fundus examinations of ou study population were 23.6% in 2011, 15.3% in 2013, 17.5% in 2015 and 21.5% in 2018, respectively. Consistent results over four waves showed that non-adherent patients had a relatively lower educational level, insufficient diabetes medication use, fewer non-medication treatments and irregular physical examination compared to those who were adherent to the annual fundus exam (all p values < 0.05). These variables were further identified as factors associated with adherence according to univariate and multivariate logistic regression analyses (all p values < 0.05). The present study provides explicit evidence that the adherence rate to annual fundus examinations among Chinese population with diabetes is worryingly low. Insufficient educational attainment, especially specific diabetes education, has a negative impact on patients’ adherence to clinical guideline for eye health.

1. Introduction

Diabetes mellitus (DM) is a major public health problem worldwide [1]. Compared to other systemic diseases, DM more frequently leads to vision-threatening events, such as diabetic retinopathy (DR) [2]. The prevalence of both diabetes and DR is on the rise and it has already become the world’s leading causes of blindness among labor population and senior citizens [3]. Early detection and timely treatment are key strategies for DR interventions and the resulting vision impairment [4]. Proper adherence with screening guidelines for the early detection of DR and DR interventions could reduce the occurrence of severe vision losses by up to 90% [5]. Thus, joint guidelines set by authority organizations recommend annual screenings for patients with diabetes [6,7]. However, the conditions of the normative management of regular fundus examinations among patients with diabetes are not satisfactory in many countries [8,9,10,11,12,13,14,15].
Researchers have reported low adherence rates to annual fundus exams among the population with diagnosed diabetes to date [8,9,10,11,12,13,14,15]. Multiple factors have been considered to impacts on the poorer adherence to regular screenings in the population with diabetes, including racial disparities, coexistent diseases, educational level and insurance coverage [8,9,10,11,12,13,14,15,16]. Population-based data also indicate that a significant proportion of patients with diabetes receiving regular public medical services are suffering from undiagnosed ocular diseases [17,18], which reflects the insufficient acknowledgement and attention attached to the eye-care of patients with diabetes from the whole medical system.
Compared to the relatively higher adherence rate (over 50%) in some developed countries [19,20], according to some recent reports, the significantly lower adherence rates in developing countries are even more worrisome. To date, there are still very few nation-wide reports on adherence to regular fundus examinations among patients with diabetes from developing countries. China is the most populous developing country; it also has the largest number of patients with diabetes. The China Health and Retirement Longitudinal Study (CHARLS) surveyed personal information from a wide range, including demographic, socioeconomic, clinical, health conditions and lifestyle information, to facilitate research on the middle-aged and older Chinese population. Thus, here, for the first time, the present study aims to introduce the conditions of adherence to annual fundus examinations and its associated factors among the Chinese population with diagnosed diabetes.

2. Materials and Methods

2.1. Patients and Public Involvement

Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS) 2011 (wave 1, baseline), 2013 (wave 2), 2015 (wave 3) and 2018 (wave 4), which is the first nationally representative longitudinal survey sampling residents (middle-aged and older adults, ≥45 years old) from 150 counties across 28 provinces in China. With a response rate over 80%, CHARLS provides the most up-to-date longitudinal datasets for studying the health status and well-being of the middle-aged and elderly population in China.

2.2. CHARLS Datasets

Initiated in 2011, CHARLS was performed using a four-stage stratified cluster sampling method. First, 150 county-level units across 28 provinces in China were sampled to represent a mixture of urban and rural areas with a wide variation in terms of economic development. Next, primary sampling units (PSU), administrative villages in rural areas or residential neighborhoods in urban areas, were sampled within each county, resulting in a total number of 450 villages/neighborhoods. Then, the dwellings in each PSU were mapped and 24 of the mapped households in each PSU were sampled for further studies. At every stage, further sampling was performed through random selection. In each selected household, one individual aging 45 or above was invited to participate together with his or her spouse, if available.

2.3. Definition of Diabetes and Adherence to Annual Fundus Examinations

In CHARLS, diagnosed diabetes was defined as the situation in which the participants responded ‘yes’ to the questions: ‘Have you ever been diagnosed with diabetes or high blood sugar by a physician?’. According to the recommendations from several authority organizations including American Diabetes Association, American Academy of Ophthalmology, American Association of Clinical Endocrinologists and Chinese Medical Association, patients with diagnosed diabetes in CHARLS were considered adherent if they confirmed having fundus examinations within the past 12 months and non-adherent if they denied receiving such examinations.

2.4. Independent Variables

According to previous studies, multiple factors that could potentially affect patients’ adherence to regular fundus examinations were adapted into the statistical models in the present study, including age, gender, marital status [21], educational level [21], insurance [22], multi-morbidities [23], self-reported vision impairment [24,25], drinking status [21], smoking status [21], usage of medication for diabetes [26] and application of non-medication treatments (weight control, physical exercise, diet, smoking control and foot care). Criteria for these variables were described in previous CHARLS studies.

2.5. Statistical Methods

In the present study, demographic, socioeconomic, medical and lifestyle-related factors were compared between patients with diabetes who endorsed versus those who denied a fundus examination in the last year using analysis of variance, Wilcoxon test, Pearson χ2 or Fisher’s exact test, according to the types and distribution of data. Univariate logistic regressions were conducted to assess the associations between independent variables and adherence to annual fundus exams. Multivariable logistic regressions were then performed using filtered variables (with p values < 0.1) from univariate analysis to determine which variables were independently associated with improved adherence to annual fundus exams. Results were reported as odds ratio (OR) with 95% confidence intervals (95% CI), and p values < 0.05 were regarded as statistically significant in the present study. A statistical analysis was performed using SAS 9.4 statistical software (SAS Institute, Cary, NC, USA).

3. Results

The final analytic sample of the present study was 985 from CHARLS 2011, 1025 from CHARLS 2013, 1027 from CHARLS 2015, and 1050 from CHARLS 2018 (Figure 1). The adherence rates to annual fundus examinations of our study sample were 23.6% in 2011, 15.3% in 2013, 17.5% in 2015 and 21.5% in 2018, respectively (Figure 2). There were statistically significant differences of adherence rates between 2011 and 2018 (p value < 0.005, Supplementary Table S1).
Characteristic differences between patients with diabetes who were adherent or non-adherent to annual fundus exams are shown in Table 1. There were some consistent results over four waves: non-adherent patients had relatively lower educational level, reduced diabetes medication use and fewer regular physical examinations compared to those who were adherent to annual fundus exams (all p values < 0.005). From 2013 to 2018, among patients who denied annual fundus exams, there was a significantly lower proportion of patients having non-medication treatments, compared to those complied with annual fundus exams (all p values < 0.005). The descriptive characteristics of patients with diabetes who failed to comply with annual fundus exams from 2011 to 2018 are further exhibited in Supplementary Table S2.
The univariate logistic regression analysis revealed the potentially associated factors of adherence in our sample (Table 2). There were consistent results, showing that factors such as higher educational level, using diabetes medication, application of non-medication treatments and adherence to regular physical exams were significantly and positively correlated to patients’ adherence to annual fundus exams (all p values < 0.05). According to multivariate logistic regression analysis, certain variables, including higher educational level, using medication or non-medication treatments, and adherence to regular physical exams, were also shown to have explicit and profound correlations with adherence to annual fundus exams (Table 3, all p values < 0.05).

4. Discussion

The latest global research on causes of blindness and its trends over 30 years indicated that DR is the only vision-threatening disease with increased prevalence between 1990 and 2020 [27]. To reduce vision impairment and consequent disability associated with DR, it is crucial to investigate the situation of adherence to regular fundus examinations, which is a secondary level of prevention, and to identify modifiable risk factors of patients’ adherence. To the best of our knowledge, the present study is the first nation-wide report on this issue from the Chinese population with diabetes.
Overall, the adherence rates of annual fundus examinations according to CHARLS were 23.6% in 2011, 15.4% in 2013, 17.2% in 2015 and 21.5% in 2018, respectively (Figure 2). Such adherence rates were relatively lower than those reported in certain studies performed in some developed countries, such as the United States of America [15,20], Korea [28] and Germany [19], which indicates the worrying condition of this issue in our country. There was a recent report of an adherence rate of 33.3% among Chinese patients with diabetes [29]. However, that research was a clinic-based study, which focused only on a small sample of patients from Guangdong province.
Above all, we proposed that the low adherence rate might be due to the low self-awareness rate of diabetes among the Chinese population. The stubbornly high prevalence of undiagnosed diabetes is a major problem in diabetes prevention and control in both developed and developing countries [30]. According to IDF diabetes Atlas, the self-awareness rate of diabetes in China was probably less than 50% in the last decade [31]. Such a condition was echoed in CHARLS. There are two main definitions of diabetes in CHARLS: self-reported diabetes and reference-defined diabetes, which have been described in the CHARLS protocol [32,33]. Blood tests could contribute to a more accurate estimation of the self-awareness rate. The self-awareness rate regarding diabetes among our study sample in 2011 baseline was 46% (Supplementary Table S3). This self-awareness rate is consistent with other CHRALS studies [33]. We further analyzed the adherence rate among people who were not aware of their diabetes (diabetes identified by blood test upon survey, but the patient responded ‘no diabetes’ in the questionnaire). Not surprisingly, but appallingly, none of these patients had attended any fundus screening in the last 12 months (Supplementary Table S3). Thus, the realistic adherence rate among our population might be greatly lower than that assessed in the present study. Hence, we propose that one important intervention to promote adherence to regular fundus examinations among the population with diabetes is to reduce the rate of undiagnosed diabetes in our population as a precondition in China.
Non-adherent patients had a significantly lower educational level, reduced diabetes medication use or less application of non-medication treatments for blood glucose control, and fewer regular physical examinations compared to those who were adherent with annual fundus exams in the present study (Table 1). Consistently, according to further logistic regression analyses, these variables were also identified as factors that could possibly affect the adherence to annual fundus exams among our study sample (Table 2 and Table 3). We propose that all these significantly associated factors could be correlated with each other in some way or another. We hypothesized that the attainment of education could play a central role.
Education level has been reported to have close a relationship with patients’ self-consciousness and knowledge of diabetes [34,35]. As mentioned above, improvements in self-consciousness of diabetes should come prior to the promotion of adherence to regular fundus examinations among our population with diabetes. From a specifically ophthalmic level, lower educational attainment may limit patients’ knowledge of vision-threatening ocular diseases [36,37,38]. Less educated people are less likely to be exposed to educational materials and may find it harder to acquire essential information from educational materials [38]. They may, therefore, lack knowledge of the rationale behind the multiple complications caused by diabetes [39], and consequently, could not understand the importance of normative management of diabetes, including periodic fundus exams [38,39]. Thus, insufficient knowledge about diabetes has been raised as the most significant barrier to eye-care among the population with diabetes [11,38,40], and lack of specific diabetes education has been considered the main reason for non-adherence to annual fundus exams among patients with diabetes [8,9,10,13], which may have detrimental impacts on their the self-management of diabetes, including taking diabetes medication or non-medication treatments and receiving regular physical examinations [34,35,38,41,42,43].
Some other factors, such as insurance coverage, vision impairment, and multi-morbidities, have been reported to have certain associations with adherence to the annual fundus exam among patients with diabetes in previous research. However, we did not notice consistent and profound evidence in the current study.
The present study is the first to introduce a nation-wide condition of adherence to regular fundus examinations among the population with diabetes in China, which included a large sample size from a nationally representative population. A wide range of factors, including demographic, socioeconomic, medical and lifestyle-related information, were adapted in statistical models. Meanwhile, we acknowledge several limitations to our study. First, most data from CHARLS were self-reported and might be subjected to recall bias or inaccurate identifications of medical conditions. Some factors, such as physician visits and glycosylated hemoglobin, were not included in our statistical models, due to the inaccessibility of CHARLS datasets. We also lacked PSU data in CHARLS 2015 and 2018; therefore, the adherence rate of our study sample cannot be seen as the adherence rate of the whole country.

5. Conclusions

The adherence rate to annual fundus exams among patients with diabetes in China is worryingly low. This situation should receive immediate attention. Insufficient educational attainment is found to be the main reason for non-adherence to periodic eye exams among the Chinese population with diabetes in the last decade. Especially, specific diabetes education and the consequent normative managements of diabetic condition could be addressed as efficient interventions that are supposed to have great impacts on patients’ adherence to clinical guidelines for eye health and the prognosis of diabetes-related complications.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jcm11226859/s1, Table S1: Adherence rate of patients with diabetes complying with annual fundus exam; Table S2: Changes in descriptive characteristics of non-adherent sample from 2011 to 2018; Table S3: Different Sample size of diabetic participants in CHARLS 2011 and adherence rate to annual fundus exam based on four definitions of diabetes.

Author Contributions

Conceptualization: K.W. and J.L.; methodology, formal analysis, data curation: Q.S. and Y.Z.; software, investigation: X.L. and J.L.; draft preparation, drafted the manuscript: Y.Z.; writing—review and editing: J.W. and H.L. All authors have read and agreed to the published version of the manuscript.

Funding

Shanghai Leading Academic Discipline Project of Public Health (Award Number: GWV-10.1-XK14). Science and Technology Commission of Shanghai Municipality (Award Number: 17411961900). Project of Shanghai Putuo District People’s Hospital (Award Number: 2021rmlcky01). The above sponsors or funding organizations had no role in the design or conduct of this research.

Institutional Review Board Statement

The CHARLS study data are publicly available and are open to researchers all over the world. Our study is a secondary analysis by using the de-identified CHARLS public data. Ethical approval for CHARLS was granted from the Institutional Review Board at Peking University. The IRB approval number for the main household survey, including anthropometrics, is IRB00001052-11015; the IRB approval number for biomarker collection, was IRB00001052-11014.

Informed Consent Statement

All participants signed informed consent at the time of participation, and they were informed and consented for secondary analysis of the survey results. The Medical Ethics Committee of Fudan University granted an exempt research determination to the current study.

Data Availability Statement

The original dataset of CHARLS is available on http://charls.pku.edu.cn/ (accessed on 3 December 2013).

Acknowledgments

We thank all participants enrolled in CHARLS. We also give our gratitude to Ying Jiang from Fudan University for data collection and Ziyang Chen for document processing in the current study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ning, C.; Mitchell, P.; Wong, T.Y. Diabetic retinopathy. Lancet 2010, 376, 124–136. [Google Scholar]
  2. Sayin, N.; Kara, N.; Pekel, G. Ocular complications of diabetes mellitus. World J. Diabetes 2015, 6, 92–108. [Google Scholar] [CrossRef] [PubMed]
  3. Leasher, J.L.; Bourne, R.R.; Flaxman, S.R.; Jonas, J.B.; Keeffe, J.; Naidoo, K.; Vision Loss Expert Group of the Global Burden of Disease Study. Erratum. Global Estimates on the Number of People Blind or Visually Impaired by Diabetic Retinopathy: A Meta-analysis from 1990 to 2010. Diabetes Care 2016, 39, 1643–1649, 2096. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Schaneman, J.; Kagey, A.; Soltesz, S.; Stone, J. The Role of Comprehensive Eye Exams in the Early Detection of Diabetes and Other Chronic Diseases in an Employed Population. Popul. Health Manag. 2010, 13, 195–199. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Schoenfeld, E.R.; Greene, J.M.; Wu, S.Y.; Leske, M. Patterns of adherence to diabetes vision care guidelines: Baseline findings from the Diabetic Retinopathy Awareness Program. Ophthalmology 2001, 108, 563–571. [Google Scholar] [CrossRef]
  6. Listed, N. Screening guidelines for diabetic retinopathy. American College of Physicians, American Diabetes Association, and American Academy of Ophthalmology. Ann. Intern. Med. 1992, 116, 683–685. [Google Scholar]
  7. Solomon, S.D.; Chew, E.; Duh, E.J.; Sobrin, L.; Sun, J.K.; VanderBeek, B.L.; Gardner, T.W. Diabetic Retinopathy: A Position Statement by the American Diabetes Association. Diabetes Care 2017, 40, 412–418. [Google Scholar] [CrossRef] [Green Version]
  8. Dadaci, Z.; Acir, N.O.; Borazan, M. Self-Declaration of Diabetes and Factors Associated with Having Regular Eye Examinations among Patients with Type 2 Diabetes in Turkey. Eur. J. Ophthalmol. 2015, 25, 333–337. [Google Scholar] [CrossRef]
  9. Piyasena, M.M.P.N.; Murthy, G.V.S.; Yip, J.L.Y.; Gilbert, C.; Peto, T.; Premarathna, M.; Zuurmond, M. A qualitative study on barriers and enablers to uptake of diabetic retinopathy screening by people with diabetes in the Western Province of Sri Lanka. Trop. Med. Health 2019, 47, 34. [Google Scholar] [CrossRef]
  10. Zou, Y.-H.; Li, Q.; Cui, S.-S.; Jia, W.; Zhang, N.; Ma, K.; Snellingen, T.; Liu, X.-P. Predictors for attending annual eye screening for diabetic retinopathy amongst patients with diabetes in an urban community of Beijing. Int. J. Ophthalmol. 2017, 10, 1144–1149. [Google Scholar]
  11. Lian, J.; McGhee, S.M.; A Gangwani, R.; Lam, C.L.K.; Yap, M.; Wong, D.S.H. Awareness of diabetic retinopathy and its association with attendance for systematic screening at the public primary care setting: A cross-sectional study in Hong Kong. BMJ Open 2018, 8, e019989. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Akuffo, K.O.; Asare, A.K.; Sewpaul, R.; Dukhi, N.; Ben Kumah, D.; Agyei-Manu, E.; Addo, E.K.; Reddy, P. Eye care utilization among diabetics in the South African National Health and Nutrition Examination Survey (SANHANES-1): A cross-sectional study. BMC Res. Notes 2020, 13, 407. [Google Scholar] [CrossRef] [PubMed]
  13. Mwangi, N.; MacLeod, D.; Gichuhi, S.; Muthami, L.; Moorman, C.; Bascarán, C.; Foster, A. Predictors of uptake of eye examination in people living with diabetes mellitus in three counties of Kenya. Trop. Med. Health 2017, 45, 41. [Google Scholar] [CrossRef] [PubMed]
  14. Ahmed, T.M.; Demilew, K.Z.; Tegegn, M.T.; Hussen, M.S. Use of Eye Care Service and Associated Factors among Adult Diabetic Patients Attending at Diabetic Clinics in Two Referral Hospitals, Northeast Ethiopia. Diabetes Metab. Syndr. Obesity Targets Ther. 2021, ume14, 2325–2333. [Google Scholar] [CrossRef]
  15. An, J.; Niu, F.; Turpcu, A.; Rajput, Y.; Cheetham, T.C. Adherence to the American Diabetes Association retinal screening guidelines for population with diabetes in the United States. Ophthalmic Epidemiol. 2018, 25, 257–265. [Google Scholar] [CrossRef]
  16. Shi, Q.; Zhao, Y.; Fonseca, V.; Krousel-Wood, M.; Shi, L. Racial disparity of eye examinations among the U.S. working-age population with diabetes: 2002–2009. Diabetes Care 2014, 37, 1321–1328. [Google Scholar] [CrossRef] [Green Version]
  17. Witkin, S.R.; Klein, R. Ophthalmologic care for persons with diabetes. J. Am. Med. Assoc. 1984, 251, 2534–2537. [Google Scholar] [CrossRef]
  18. Wang, F.; Ford, D.; Tielsch, J.M.; Quigley, H.A.; Whelton, P.K. Undetected Eye Disease in a Primary Care Clinic Population. Arch. Intern. Med. 1994, 154, 1821. [Google Scholar] [CrossRef]
  19. Baumeister, S.E.; Schomerus, G.; Andersen, R.M.; Tost, F.; Markus, M.R.; Volzke, H.; Jürgens, C. Trends of barriers to eye care among adults with diagnosed diabetes in Germany, 1997–2012. Nutr. Metab. Cardiovasc. Dis. 2015, 25, 906–915. [Google Scholar] [CrossRef]
  20. Eppley, S.E.; Mansberger, S.L.; Ramanathan, S.; Lowry, E.A. Characteristics Associated with Adherence to Annual Dilated Eye Examinations among US Patients with Diagnosed Diabetes. Ophthalmology 2019, 126, 1492–1499. [Google Scholar] [CrossRef]
  21. Zhou, Y.; Hu, Y.; Luo, J.; Li, Y.; Liu, H.; Sun, X.; Zhou, M. Association between Sensory Loss and Falls among Middle-Aged and Older Chinese Population: Cross-Sectional and Longitudinal Analyses. Front. Med. 2022, 8, 810159. [Google Scholar] [CrossRef] [PubMed]
  22. Sun, J.; Lyu, S.; Li, C.; Coyte, P.C. The contribution of Urban and Rural Resident Basic Medical Insurance to income-related inequality in depression among middle-aged and older adults: Evidence from China. J. Affect. Disord. 2021, 293, 168–175. [Google Scholar] [CrossRef] [PubMed]
  23. Hu, W.-H.; Liu, Y.-Y.; Yang, C.-H.; Zhou, T.; Yang, C.; Lai, Y.-S.; Liao, J.; Hao, Y.-T. Developing and validating a Chinese multimorbidity-weighted index for middle-aged and older community-dwelling individuals. Age Ageing 2022, 51, afab274. [Google Scholar] [CrossRef]
  24. Shang, X.; Zhu, Z.; Wang, W.; He, M. Associations of vision impairment and eye diseases with memory decline over four years in China and the United States. Am. J. Ophthalmol. 2021, 228 (Suppl. S1), 16–26. [Google Scholar] [CrossRef]
  25. Xie, T.; Liu, D.; Guo, J.; Zhang, B. The longitudinal effect of sensory loss on depression among Chinese older adults. J. Affect. Disord. 2021, 283, 216–222. [Google Scholar] [CrossRef] [PubMed]
  26. Liu, H.; Xu, X.; Hall, J.J.; Wu, X.; Zhang, M. Differences in depression between unknown diabetes and known diabetes: Results from China health and retirement longitudinal study. Int. Psychogeriatr. 2016, 28, 1191–1199. [Google Scholar] [CrossRef] [PubMed]
  27. Blindness, G.B.D. Vision Impairment C, Vision Loss Expert Group of the Global Burden of Disease S. 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. Lancet Glob. Health 2021, 9, e144–e160. [Google Scholar]
  28. Song, S.J.; Han, K.; Choi, K.S.; Ko, S.-H.; Rhee, E.-J.; Park, C.-Y.; Park, J.-Y.; Lee, K.-U.; Ko, K.-S.; the Task Force Team for Diabetes Fact Sheet of the Korean Diabetes Association. Trends in diabetic retinopathy and related medical practices among type 2 diabetes patients: Results from the National Insurance Service Survey 2006–2013. J. Diabetes Investig. 2018, 9, 173–178. [Google Scholar] [CrossRef]
  29. Wang, D.; Ding, X.; He, M.; Yan, L.; Kuang, J.; Geng, Q.; Congdon, N. Use of Eye Care Services among Diabetic Patients in Urban and Rural China. Ophthalmology 2010, 117, 1755–1762. [Google Scholar] [CrossRef]
  30. Harris, M.I.; Flegal, K.M.; Cowie, C.C.; Eberhardt, M.S.; Goldstein, D.E.; Little, R.R.; Byrd-Holt, D.D. Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults. The Third National Health and Nutrition Examination Survey, 1988–1994. Diabetes Care 1998, 21, 518–524. [Google Scholar] [CrossRef]
  31. Ogurtsova, K.; Guariguata, L.; Barengo, N.C.; Ruiz, P.L.-D.; Sacre, J.W.; Karuranga, S.; Sun, H.; Boyko, E.J.; Magliano, D.J. IDF diabetes Atlas: Global estimates of undiagnosed diabetes in adults for 2021. Diabetes Res. Clin. Pract. 2021, 183, 109118. [Google Scholar] [CrossRef] [PubMed]
  32. Quan, J.; Ng, C.S.; Kwok, H.H.Y.; Zhang, A.; Yuen, Y.H.; Choi, C.-H.; Siu, S.-C.; Tang, S.Y.; Wat, N.M.; Woo, J.; et al. Development and validation of the CHIME simulation model to assess lifetime health outcomes of prediabetes and type 2 diabetes in Chinese populations: A modeling study. PLoS Med. 2021, 18, e1003692. [Google Scholar] [CrossRef] [PubMed]
  33. Yuan, X.; Liu, T.; Wu, L.; Zou, Z.-Y.; Li, C. Validity of self-reported diabetes among middle-aged and older Chinese adults: The China Health and Retirement Longitudinal Study. BMJ Open 2015, 5, e006633. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Li, J.; Ni, J.; Wu, Y.; Zhang, H.; Liu, J.; Tu, J.; Wang, J. Sex Differences in the Prevalence, Awareness, Treatment, and Control of Diabetes Mellitus among Adults Aged 45 Years and Older in Rural Areas of Northern China: A Cross-Sectional, Population-Based Study. Front. Endocrinol. 2019, 10, 147. [Google Scholar] [CrossRef]
  35. Wu, H.; Jackson, C.A.; Wild, S.H.; Jian, W.; Dong, J.; Gasevic, D. Socioeconomic status and self-reported, screen-detected and total diabetes prevalence in Chinese men and women in 2011–2012: A nationwide cross-sectional study. J. Glob. Health 2018, 8, 020501. [Google Scholar] [CrossRef]
  36. Li, L.-S.; Ge, Z.-Y.; Lohfeld, L.; Zhou, K.; Zhou, W.-H.; Cui, L.-L.; Qu, J.; Liang, Y.-B. Knowledge, attitudes and practices related to seeking medical eyecare services by adults with moderate-to-severe visual impairment in rural Yueqing, Wenzhou, China: A cross-sectional survey. Int. J. Ophthalmol. 2020, 13, 1115–1123. [Google Scholar] [CrossRef]
  37. Desalegn, A.; Tsegaw, A.; Shiferaw, D.; Woretaw, H. Knowledge, attitude, practice and associated factors towards spectacles use among adults in Gondar town, northwest Ethiopia. BMC Ophthalmol. 2016, 16, 184. [Google Scholar] [CrossRef] [Green Version]
  38. Hartnett, M.E.; Key, I.J.; Loyacano, N.M.; Horswell, R.L.; Desalvo, K.B. Perceived barriers to diabetic eye care: Qualitative study of patients and physicians. Arch. Ophthalmol. 2005, 123, 387–391. [Google Scholar] [CrossRef] [Green Version]
  39. Ellish, N.J.; Royak-Schaler, R.; Passmore, S.R.; Higginbotham, E.J. Knowledge, attitudes, and beliefs about dilated eye examinations among African-Americans. Investig. Ophthalmol. Vis Sci. 2007, 48, 1989–1994. [Google Scholar] [CrossRef] [Green Version]
  40. Peng, P.H.; Laditka, S.B.; Lin, H.S.; Lin, H.C.; Probst, J.C. Factors associated with retinal screening among patients with diabetes in Taiwan. Taiwan J. Ophthalmol. 2019, 9, 185–193. [Google Scholar] [CrossRef]
  41. Brechner, R.J.; Cowie, C.C.; Howie, L.J.; Herman, W.H.; Will, J.C.; Harris, M.I. Ophthalmic Examination among Adults with Diagnosed Diabetes Mellitus. JAMA 1993, 270, 1714–1718. [Google Scholar] [CrossRef] [PubMed]
  42. Paz, S.H.; Varma, R.; Klein, R.; Wu, J.; Azen, S.P. Noncompliance with Vision Care Guidelines in Latinos with Type 2 Diabetes Mellitus. The Los Angeles Latino Eye Study. Ophthalmology 2006, 113, 1372–1377. [Google Scholar] [CrossRef] [PubMed]
  43. Paksin-Hall, A.; Dent, M.L.; Dong, F.; Ablah, E. Factors contributing to diabetes patients not receiving annual dilated eye examinations. Ophthalmic Epidemiol. 2013, 20, 281–287. [Google Scholar] [CrossRef] [PubMed]
Jcm 11 06859 g001 550
Figure 1. Sample screening of diabetic participants in CHARLS 2011, 2013, 2015 and 2018 for the present study.
Figure 1. Sample screening of diabetic participants in CHARLS 2011, 2013, 2015 and 2018 for the present study.
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Figure 2. Adherence rates of participants with diabetes in CHARLS from 2011 to 2018.
Figure 2. Adherence rates of participants with diabetes in CHARLS from 2011 to 2018.
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Table
Table 1. Descriptive characteristics of study sample from 2011 to 2018.
Table 1. Descriptive characteristics of study sample from 2011 to 2018.
2011 (n = 985)2013 (n = 1025)2015 (n = 1027)2018 (n = 1050)
VariablesAdherent
(n = 231)		Non-Adherent
(n = 754)		p ValueAdherent
(n = 157)		Non-Adherent
(n = 868)		p ValueAdherent
(n = 180)		Non-Adherent
(n = 847)		p ValueAdherent
(n = 226)		Non-Adherent
(n = 824)		p Value
Gender 0.1285 0.1364 0.3880 0.2867
  Male113 (48.9%)326 (43.2%) 79 (50.3%)381 (43.9%) 74 (41.1%)378 (44.6%) 108 (47.8%)361 (43.8%)
  Female118 (51.1%)428 (56.8%) 78 (49.7%)487 (56.1%) 106 (58.9%)469 (55.4%) 118 (52.2%)463 (56.2%)
Age61.60 ± 9.5261.07 ± 9.240.447762.31 ± 8.7961.98 ± 9.270.684563.72 ± 8.6763.68 ± 9.100.955563.67 ± 9.5262.61 ± 9.390.1351
Education <0.005 <0.005 <0.005 0.0047
  Illiterate35 (15.2%)197 (26.1%) 24 (15.3%)207 (23.8%) 32 (17.8%)208 (24.6%) 46 (20.4%)219 (26.6%)
  Less than elementary school85 (36.8%)304 (40.3%) 43 (27.4%)371 (42.7%) 56 (31.1%)356 (42.0%) 87 (38.5%)348 (42.2%)
  Middle school53 (22.9%)146 (19.4%) 40 (25.5%)168 (19.4%) 43 (23.9%)166 (19.6%) 52 (23.0%)150 (18.2%)
  High school or vocational school39 (16.9%)84 (11.1%) 36 (22.9%)96 (11.1%) 33 (18.3%)87 (10.3%) 27 (11.9%)89 (10.8%)
  college and above19 (8.2%)23 (3.1%) 14 (8.9%)26 (3.0%) 16 (8.9%)30 (3.5%) 14 (6.2%)18 (2.2%)
Marital status 0.4756 0.1327 0.3252 0.3794
  Yes192 (83.1%)611 (81.0%) 123 (78.3%)723 (83.3%) 154 (85.6%)699 (82.5%) 175 (77.4%)660 (80.1%)
  No39 (16.9%)143 (19.0%) 34 (21.7%)145 (16.7%) 26 (14.4%)148 (17.5%) 51 (22.6%)164 (19.9%)
Smoke 0.9344 0.2357 0.3199 0.6137
  Yes80 (34.6%)263 (34.9%) 67 (42.7%)327 (37.7%) 68 (37.8%)354 (41.8%) 76 (33.6%)292 (35.4%)
  No151 (65.4%)490 (65.1%) 90 (57.3%)541 (62.3%) 112 (62.2%)493 (58.2%) 150 (66.4%)532 (64.6%)
Drinking status 0.432 0.2568 0.6172 0.4758
  Drink more than once a month42 (18.2%)130 (17.3%) 38 (24.2%)162 (18.7%) 33 (18.3%)162 (19.1%) 52 (23.0%)171 (20.8%)
  Drink but less than once a month10 (4.3%)50 (6.6%) 12 (7.6%)64 (7.4%) 9 (5.0%)58 (6.8%) 20 (8.8%)59 (7.2%)
  None of these179 (77.5%)573 (76.1%) 107 (68.2%)642 (74.0%) 138 (76.7%)627 (74.0%) 154 (68.1%)594 (72.1%)
Using diabetes medication <0.005 <0.005 <0.005 <0.005
  Yes190 (82.3%)512 (67.9%) 145 (92.4%)534 (61.5%) 156 (86.7%)512 (60.4%) 167 (73.9%)469 (56.9%)
  No41 (17.7%)242 (32.1%) 12 (7.6%)334 (38.5%) 24 (13.3%)335 (39.6%) 59 (26.1%)355 (43.1%)
Non-medication treatments 0.1086 <0.005 <0.005 <0.005
  Yes105 (45.5%)298 (39.5%) 83 (52.9%)335 (38.6%) 90 (50.0%)298 (35.2%) 122 (54.0%)340 (41.3%)
  No126 (54.5%)456 (60.5%) 74 (47.1%)533 (61.4%) 90 (50.0%)549 (64.8%) 104 (46.0%)484 (58.7%)
Multi-morbidities 0.9407 0.1144 0.5164 0.2161
  Yes199 (86.1%)651 (86.3%) 141 (89.8%)738 (85.0%) 163 (90.6%)753 (88.9%) 188 (83.2%)655 (79.5%)
  No32 (13.9%)103 (13.7%) 16 (10.2%)130 (15.0%) 17 (9.4%)94 (11.1%) 38 (16.8%)169 (20.5%)
Vision impairment 0.3551 0.2759 0.3432 0.4458
  Yes109 (47.2%)382 (50.7%) 70 (44.6%)428 (49.3%) 80 (44.4%)344 (40.6%) 75 (33.2%)296 (35.9%)
  No122 (52.8%)372 (49.3%) 87 (55.4%)440 (50.7%) 100 (55.6%)503 (59.4%) 151 (66.8%)528 (64.1%)
Regular physical exam <0.005 <0.005 <0.005 <0.005
  Yes179 (77.5%)496 (65.8%) 127 (80.9%)479 (55.2%) 137 (76.1%)449 (53.0%) 172 (76.1%)458 (55.6%)
  No52 (22.5%)258 (34.2%) 30 (19.1%)389 (44.8%) 43 (23.9%)398 (47.0%) 54 (23.9%)366 (44.4%)
Insurance coverage 0.4885 0.3779 0.0142 0.6999
  Yes220 (95.2%)709 (94.0%) 151 (96.2%)820 (94.5%) 166 (92.2%)816 (96.3%) 222 (98.2%)806 (97.8%)
  No11 (4.8%)45 (6.0%) 6 (3.8%)48 (5.5%) 14 (7.8%)31 (3.7%) 4 (1.8%)18 (2.2%)
Table
Table 2. Univariate logistic regression of factors associated with adherence to annual fundus exam.
Table 2. Univariate logistic regression of factors associated with adherence to annual fundus exam.
Variables2011 (n = 985)2013 (n = 1025)2015 (n = 1027)2018 (n = 1050)
Odd ratio (95% Confidence Interval)
Gender
   FemaleReference
   Male1.254 (0.933, 1.686)1.295 (0.921, 1.820)0.866 (0.625, 1.200)1.174 (0.874, 1.577)
Age1.006 (0.991, 1.022)1.004 (0.985, 1.023)1.001 (0.983, 1.019)1.012 (0.996, 1.028)
Education
   IlliterateReference
   Less than elementary school1.566 (1.016, 2.413) *1.000 (0.590, 1.694)1.022 (0.641, 1.631)1.190 (0.802, 1.767)
   Middle school2.033 (1.261, 3.278) **2.054 (1.190, 3.543) *1.684 (1.020, 2.779) *1.650 (1.055, 2.583) *
   High school or vocational school2.600 (1.541, 4.387) ***3.234 (1.828, 5.722) ***2.466 (1.427, 4.260) **1.444 (0.846, 2.467)
   college and above4.626 (2.283, 9.373) ***4.644 (2.140, 10.08) ***3.467 (1.701, 7.064) **3.703 (1.719, 7.976) **
Marital status
   NoReference
   Yes1.144 (0.775, 1.689)0.725 (0.477, 1.104)1.254 (0.798, 1.970)0.853 (0.597, 1.217)
Smoke
   NoReference
   Yes0.987 (0.724, 1.345)1.232 (0.872, 1.739)0.846 (0.607, 1.177)0.923 (0.677, 1.259)
Drinking status
   None of theseReference
   Drink but less than once a month0.641 (0.318, 1.289)1.125 (0.588, 2.154)0.705 (0.341, 1.457)1.308 (0.764, 2.238)
   Drink more than once a month1.034 (0.703, 1.522)1.408 (0.936, 2.117)0.926 (0.610, 1.405)1.173 (0.820, 1.677)
Using diabetes medication
   NoReference
   Yes2.195 (1.515, 3.179) ***7.557 (4.129, 13.83) ***4.253 (2.708, 6.678) ***2.142 (1.544, 2.972) ***
Non-medication treatments
   NoReference
   Yes1.279 (0.950, 1.723)1.785 (1.268, 2.512) **1.842 (1.332, 2.548) ***1.670 (1.242, 2.245) **
Multi-morbidities
   NoReference
   Yes0.985 (0.643, 1.511)1.552 (0.896, 2.690)1.197 (0.695, 2.061)1.276 (0.866, 1.880)
Vision impairment
   NoReference
   Yes0.872 (0.649, 1.172)0.827 (0.588, 1.164)1.170 (0.846, 1.618)0.886 (0.649, 1.210)
Regular physical exam
   NoReference
   Yes1.784 (1.265, 2.515) **3.437 (2.259, 5.230) ***2.824 (1.954, 4.081) ***2.545 (1.820, 3.559) ***
Insurance coverage
   NoReference
   Yes1.271 (0.646, 2.500)1.472 (0.619, 3.500)0.450 (0.234, 0.865)1.239 (0.415, 3.699)
p < 0.05 *; p < 0.005 **; p < 0.0005 ***.
Table
Table 3. Multivariate logistic regression of factors associated with adherence to annual fundus exams.
Table 3. Multivariate logistic regression of factors associated with adherence to annual fundus exams.
Variables2011 (n = 985)2013 (n = 1025)2015 (n = 1027)2018 (n = 1050)
Odd ratio (95% Confidence Interval)
Education
   IlliterateReference
   Less than elementary school1.490 (0.961, 2.309)0.911 (0.527, 1.577)0.885 (0.545, 1.435)1.184 (0.789, 1.777)
   Middle school1.862 (1.147, 3.021) *1.571 (0.888, 2.780)1.397 (0.829, 2.354)1.446 (0.910, 2.298)
   High school or vocational school2.488 (1.464, 4.227) **2.605 (1.422, 4.771) **1.792 (1.011, 3.175) *1.303 (0.752, 2.259)
   College and above4.067 (1.977, 8.369) ***3.208 (1.399, 7.359) *2.380 (1.116, 5.075) *1.303 (0.752, 2.259) *
Using diabetes medication
   NoReference
   Yes2.113 (1.448, 3.084) ***7.124 (3.856, 13.16) ***3.772 (2.379, 5.979) ***2.083 (1.487, 2.919) ***
Non-medication treatments
   NoReference
   Yes1.310 (0.906, 1.893)1.310 (0.906, 1.893)1.515 (1.076, 2.132) *1.521 (1.118, 2.070) *
Regular physical exam
   NoReference
   Yes1.665 (1.171, 2.366) **2.917 (1.881, 4.524) ***2.408 (1.645, 3.525) ***2.410 (1.704, 3.407) ***
p < 0.05 *; p < 0.005 **; p < 0.0005 ***.
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Zhou, Y.; Li, X.; Sun, Q.; Wei, J.; Liu, H.; Wang, K.; Luo, J. Adherence to Annual Fundus Exams among Chinese Population with Diagnosed Diabetes. J. Clin. Med. 2022, 11, 6859. https://doi.org/10.3390/jcm11226859

AMA Style

Zhou Y, Li X, Sun Q, Wei J, Liu H, Wang K, Luo J. Adherence to Annual Fundus Exams among Chinese Population with Diagnosed Diabetes. Journal of Clinical Medicine. 2022; 11(22):6859. https://doi.org/10.3390/jcm11226859

Chicago/Turabian Style

Zhou, Yifan, Xiaowen Li, Qinglei Sun, Jin Wei, Haiyun Liu, Keyan Wang, and Jianfeng Luo. 2022. "Adherence to Annual Fundus Exams among Chinese Population with Diagnosed Diabetes" Journal of Clinical Medicine 11, no. 22: 6859. https://doi.org/10.3390/jcm11226859

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