Incidence and risk factors of depression in patients with metabolic syndrome.

World J Psychiatry

Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi Province, China.

Published: February 2024

Background: Many studies have explored the relationship between depression and metabolic syndrome (MetS), especially in older people. China has entered an aging society. However, there are still few studies on the elderly in Chinese communities.

Aim: To investigate the incidence and risk factors of depression in MetS patients in mainland China and to construct a predictive model.

Methods: Data from four waves of the China Health and Retirement Longitudinal Study were selected, and middle-aged and elderly patients with MetS ( = 2533) were included based on the first wave. According to the center for epidemiological survey-depression scale (CESD), participants with MetS were divided into depression ( = 938) and non-depression groups ( = 1595), and factors related to depression were screened out. Subsequently, the 2-, 4-, and 7-year follow-up data were analyzed, and a prediction model for depression in MetS patients was constructed.

Results: The prevalence of depression in middle-aged and elderly patients with MetS was 37.02%. The prevalence of depression at the 2-, 4-, and 7-year follow-up was 29.55%, 34.53%, and 38.15%, respectively. The prediction model, constructed using baseline CESD and Physical Self-Maintenance Scale scores, average sleep duration, number of chronic diseases, age, and weight had a good predictive effect on the risk of depression in MetS patients at the 2-year follow-up (area under the curve = 0.775, 95% confidence interval: 0.750-0.800, < 0.001), with a sensitivity of 68% and a specificity of 74%.

Conclusion: The prevalence of depression in middle-aged and elderly patients with MetS has increased over time. The early identification of and intervention for depressive symptoms requires greater attention in MetS patients.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10921290PMC
http://dx.doi.org/10.5498/wjp.v14.i2.245DOI Listing

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