Factors Related to Fundus Examination in Diabetes Mellitus Patients

Choi, Joo-Hyuck; Na, Baeg-Ju; Chun, Sung-A

doi:10.4332/kjhpa.2010.20.1.125

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…This may explain differences in the use of healthcare services and glycaemic control capacity, which may be influenced by the characteristics of the individual (eg, education and income level). Several studies have found low SEPs to be associated with a greater likelihood of having higher HbA1c levels62 and a smaller likelihood of receiving eye examinations for diabetes than high SEPs 6 63 64. Also, there was an inverse association between diabetes knowledge and glycaemic control among low-income patients with diabetes 65…”

Section: Discussionmentioning

confidence: 99%

Area-based inequalities and distribution of healthcare resources for managing diabetes in South Korea: a cross-sectional multilevel analysis

Jung-Choi²

2022

BMJ Open

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ObjectivesWe aimed to identify area-based socioeconomic inequalities in diabetes management and to examine whether the distribution of healthcare resources could explain area-based inequalities in diabetes management.DesignCross-sectional multilevel analysis from national survey data.Setting and participantsData were derived from the 2018 Korean Community Health Survey. Study subjects included 23 760 participants aged 30 years or older with diabetes diagnosed by a doctor.Main outcome measuresThe dependent variables were self-reported good glycaemic control, haemoglobin A1c (HbA1c) testing, recognition of the term HbA1c, and diabetic complications testing. Area Deprivation Index was used as an area-based measure of socioeconomic position. Factors related to regional healthcare resources—the coefficient of variation (CV) value of clinics and the number of physicians per 1000—were considered as potential mediating variables in explaining the association between diabetes management and area deprivation. A multilevel logistic regression analysis was used.ResultsCompared with the least deprived quintile, the likelihoods of not taking HbA1c tests, not recognising the term HbA1c, and not taking diabetic complication tests in the most deprived quintile were approximately 1.5 times (95% CI 1.25 to 1.80), 2.6 times (95% CI 1.97 to 3.45) and two times (95% CI 1.67 to 2.48) higher, respectively. In the most deprived quintile, CV value of clinics was the highest and the number of doctors was the lowest. Regional healthcare resource factors explained inequalities in managing diabetes by 14%–18%, especially in the most deprived quintile.ConclusionsThe results in this study suggest that socioeconomic inequalities in diabetes management may be explained by regional healthcare resource disparities. Policy interventions for a more even distribution of healthcare resources would likely reduce the magnitude of regional socioeconomic inequalities in diabetes management.

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Section: Discussionmentioning

confidence: 99%

Area-based inequalities and distribution of healthcare resources for managing diabetes in South Korea: a cross-sectional multilevel analysis

Jung-Choi²

2022

BMJ Open

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“…Many previous studies (10)(11)(12)(13) indicated the disease duration of diabetes, age, education level, residential area, income level, diabetes education, and subjective health status were factors associated with the fundus examination of diabetic patients. Moreover, other studies reported that sex, age, hospitalization experience, and comorbidities were related to receiving using the glycated hemoglobin test (14,15).…”

Section: Introductionmentioning

confidence: 98%

Factors Influencing the Utilization of Diabetes Complication Tests Under the COVID-19 Pandemic: Machine Learning Approach

Byeon

2022

Front. Endocrinol.

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ObjectiveThere are still not enough studies on the prediction of non-utilization of a complication test or a glycated hemoglobin test for preventing diabetes complications by using large-scale community-based big data. This study identified the ratio of not taking a diabetes complication test (fundus examination and microprotein urination test) among adult diabetic patients over 19 years using a national survey conducted in South Korea and developed a model for predicting the probability of not taking a diabetes complication test based on it.MethodsThis study analyzed 25,811 subjects who responded that they had been diagnosed with diabetes by a doctor in the 2020 Community Health Survey. Outcome variables were defined as the utilization of the microprotein urination test and the fundus examination during the past year. This study developed a model for predicting the utilization of a diabetes complication test using logistic regression analysis and nomogram to understand the relationship of predictive factors on the utilization of a diabetes complication test.ResultsThe results of this study confirmed that age, education level, the recognition of own blood glucose level, current diabetes treatment, diabetes management education, not conducting the glycated hemoglobin test in the past year, smoking, single-person household, subjectively good health, and living in the rural area were independently related to the non-utilization of diabetes complication test after the COVID-19 pandemic.ConclusionAdditional longitudinal studies are required to confirm the causality of the non-utilization of diabetes complication screening tests.

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Regional disparity of medical resources and its effect on age-standardized mortality rates in Korea

Chang

Kim

2019

Ann Reg Sci

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Factors Related to Fundus Examination in Diabetes Mellitus Patients

Cited by 4 publications

References 9 publications

Area-based inequalities and distribution of healthcare resources for managing diabetes in South Korea: a cross-sectional multilevel analysis

Area-based inequalities and distribution of healthcare resources for managing diabetes in South Korea: a cross-sectional multilevel analysis

Factors Influencing the Utilization of Diabetes Complication Tests Under the COVID-19 Pandemic: Machine Learning Approach

Regional disparity of medical resources and its effect on age-standardized mortality rates in Korea

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