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Association between metabolic syndrome (MetS) and depression among community-dwelling super-old adults: results from the China Health and Retirement Longitudinal Study

Published:05 April 2024Publication History

ABSTRACT

Background and purpose: Depression can give rise to a wide variety of negative health results, including abdominal obesity, elevated blood glucose, elevated blood pressure, or dyslipidemia. Nevertheless, evidence supporting the relationship between depression and metabolic syndrome (MetS), a series of cardiometabolic risk factors, remains insufficient. The present research in order to inspect the associations between MetS and depression out of community-dwelling Chinese super-old adults.

Methods: This study used the data from 1,172 super-old (aged ≥ 80 years) Chinese adults from the China Health and Retirement Longitudinal Study (CHARLS) in 2011. The MetS refers to the presence of at least three of the five selected indications: hypertension, central obesity, raised triglyceride, reduced HDL-cholesterol, and raised fasting plasma glucose. We measured metabolic syndrome, depressive symptoms, and covariates. Odds ratio (OR) and 95% confidence interval (95% CI) were performed using Logistic regression analyses, after adjusting all potential confounders.

Results: MetS had a significant association with depression (OR = 0.682, 95% CI = 0.529-0.880). After fully adjusted for gender, education level, married, current drinkers, current smokers, and social isolation, the logistic regression analyses showed that super-old adults with MetS had also an increased risk of depression (OR = 0.674, 95% CI = 0.521-0.872), compared with those without MetS.

Conclusions: MetS was prevalent among older Chinese super-old adults and was an independent risk factor of depression. To study cause and effect and investigate possible action mechanisms, longitudinal studies with a bigger number of people are required in the future.

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      ISAIMS '23: Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine Science
      October 2023
      1394 pages
      ISBN:9798400708138
      DOI:10.1145/3644116

      Copyright © 2023 ACM

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      Publication History

      • Published: 5 April 2024

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