Social determinants of health and depressive symptoms states transitions among middle-aged and older adults: A markov-based longitudinal study

Title : Social determinants of health and depressive symptoms states transitions among middle-aged and older adults: A markov-based longitudinal study

Abstract:

Background: Social determinants of health (SDoH) are associated with an increased risk of depressive symptoms (DS). However, it remains unclear whether SDoH affect state-to-state transitions of DS. Therefore, this study aimed to examine the impact of SDoH on transitions between different DS states.
Methods: We used data from five waves of the China Family Panel Studies (2012, 2016, 2018, 2020, and 2022) to categorize DS into three states: non-DS, mild-DS, and severe-DS. Multi-state Markov modeling was applied to estimate transition probabilities and examine associations with SDoH.
Results: The study included 4034 participants aged 45 years or older. Transitions in DS states were found to occur between both adjacent and non-adjacent states, with adjacent transitions exhibiting relatively higher intensities. Greater cumulative unfavorable SDoH were significantly associated with increased risks of DS progression from non-DS to mild-DS (HR=1.20; 95% CI: 1.16, 1.25) and from mild-DS to severe-DS states (HR=1.14; 95% CI: 1.04, 1.25), as well as a decreased likelihood of remission from severe-DS to non-DS states (HR=0.35; 95% CI: 0.15, 0.82).
Conclusions: This study provides empirical evidence for the longitudinal impact of unfavorable SDoH on DS transitions. Integrating SDoH into mental health risk stratification and intervention frameworks may improve outcomes in aging populations.
Keywords: Social Determinants of Health; Depressive Symptoms; Middle-Aged and Older Adults; Markov Model; Longitudinal Study.

Biography:

Xue Wang is a PhD candidate at the School of Nursing, Peking University. Xue Wang’s research focuses on aging, frailty, and mental health among community-dwelling older adults, with an emphasis on risk prediction and intervention strategies. Xue Wang has expertise in big data analytics, system dynamics modeling, and network analysis of depressive and anxiety symptoms. To date, Xue Wang has published 23 peer-reviewed articles in SCI/SSCI journals as first or co-first author, and actively contributes to interdisciplinary behavioral health research aimed at promoting healthy aging. Xue Wang is a PhD candidate at the School of Nursing, Peking University. Xue Wang’s research focuses on aging, frailty, and mental health among community-dwelling older adults, with an emphasis on risk prediction and intervention strategies. Xue Wang has expertise in big data analytics, system dynamics modeling, and network analysis of depressive and anxiety symptoms. To date, Xue Wang has published 23 peer-reviewed articles in SCI/SSCI journals as first or co-first author, and actively contributes to interdisciplinary behavioral health research aimed at promoting healthy aging.