This study aimed to assess the prevalence of depression in middle-aged and elderly patients with diabetes in China, determine the risk factors of depression in these patients, and explore the internal relationship between influencing factors and depression by constructing a pathway model. Methods: Data were collected from the 2018 China Health and Retirement Longitudinal Study (CHRLS). We included 1743 patients with diabetes who were assessed using the CES-D10, which is used to measure depressive symptoms in Chinese older adults. Based on the theory of psychological stress, data were analyzed using SPSS software version 22.0 and MPLUS 8.0. A correlation analysis was used to explore the relationship between the variables and depression scores. A path model was constructed to explore the interrelationships between variables and verify the relationships between variables and depression in patients with diabetes. Results: The prevalence of depression among patients with diabetes was 42.5%. The path analysis results showed that income, diabetes duration, sleep duration, pain distress, self-rated health, and glycemic control directly affected depression, and self-rated health had the largest effect value. With self-rated health and glycemic control as mediator variables, income, diabetes duration, sleep duration, pain distress, glycemic control, and insulin use had indirect effects on depression by influencing self-rated health. Age, frequency of blood glucose monitoring, and exercise glycemic control awareness indirectly affected depression by affecting glycemic control, self-rated health status, and depression. Conclusion:We found that the path analysis model could construct the interaction between the influencing factors and explore the potential interrelationship between the influencing factors and diabetes-related depression. Patients with diabetes must adhere to regular medication, maintain a healthy lifestyle, and have effective glycemic control. Diabetes depression can be effectively prevented by making psychological knowledge publicly available, providing health education, and establishing corresponding for diabetes.
Background Depressive symptoms has become an increasingly important public health issue, contributing to disability and disease burden around the world. Studies have found that social support is strongly associated with depression in rural older people, so it is important to explore the factors influencing depression in rural older people in a comprehensive manner and to analyze the association between social support and depression. Methods On the basis of a theoretical model of health ecological, data were obtained from The China Health and Retirement Longitudinal Study in the 2018, with a sample consisting of 5,660 rural individuals aged ≥ 60 years. Then, Chi-square test and logistic regression analyses were used for statistical description and inference. Results Results indicate that the prevalence of depressive symptoms amongst rural older adults in China is 41.18%. The logistic regression analysis reveals that being female (OR = 1.406, 95% CI: 1.170–1.689), having ≥ 3 non-communicable diseases (OR = 1.736, 95% CI: 1.447–2.082), being not satisfied with spouse (OR = 2.978, 95% CI: 2.304–3.849), and being not at all satisfied with children (OR = 3.640, 95% CI: 1.736–7.635) are significantly correlated with depression. Conclusions The prevalence of depression amongst rural Chinese older adults is obviously high. Women and the elderly with chronic diseases need to be focused on. Hence, this study suggests that promoting interactivity amongst family members, increasing their relationship satisfaction, and encouraging active participation in social activities are necessary to further reduce the risk of depression amongst rural Chinese older adults. The government should not only improve the social security system, but also provide financial support and assistance to the elderly in rural China.
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