Research Square · Dec 15, 2020

Longitudinal Health Behaviour Patterns Among Chinese Adults Aged ≥ 50 Years and Their Associations With Trajectories of Depressive Symptoms Over Time: A Latent Class Analysis

By Feng Z, van den Broek T, Cramm JM et al.

Abstract Background Whether different longitudinal patterns of multiple health behaviours are associated with different trajectories of depressive symptoms is not well understood.Purpose To identify distinct longitudinal patterns of multiple health behaviours and their associations with trajectories of depressive symptoms among people aged ≥ 50 years in China.Methods We used longitudinal data from the Harmonized China Health and Retirement Longitudinal Study (three waves, 2010–2015; n = 8439). We performed latent class analyses to identify distinct patterns of multiple health behaviours at three timepoints. We estimated longitudinal random-effects models to predict differences in depressive symptoms trajectories by health behaviour class.Results The best-fitting model had five latent classes, all of which showed strong behavioural stability over time: 1) socially active, moderately physically active non-smokers (29.4%); 2) socially inactive, physically active non-smokers (22.3%); 3) socially and physically inactive non-smokers (17.9%); 4) socially inactive, moderately physically active smokers (14.6%); and (5) socially active, moderately physically active smokers (14.2%). All classes characterized by low social participation (classes 2–4) were associated with significantly higher predicted depressive symptom scores compared with the other classes (1 and 5). Conclusions Longitudinal behavioural patterns involving low probabilities of social participation were associated with more depressive symptoms. This overshadowing effect suggests that the damage caused by socially inactivity may render the effects of co-existing (un)healthy behaviours meaningless. The stability of the patterns of multiple health behaviours across survey waves suggests that interventions are needed earlier in life.

doi.org/10.21203/rs.3.rs-124395/v1Open accessPopulations

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