Objectives: Against the background of the growing recognition of the need for a holistic perspective on health behaviour, we aim to identify longitudinal patterns of multiple health behaviours, and to assess associations of such patterns with depressive symptoms among older people in China.
Methods: Using three waves of China Health and Retirement Longitudinal Study data (n = 8439), we performed latent class growth analyses (LCGAs) to identify longitudinal patterns of multiple health behaviours. Random-effects models were estimated to assess associations between health behaviour patterns and depressive symptoms.
Results: The best fitting LCGA model had seven classes: (1) connected active non-smokers (average posterior probability: 21.8%), (2) isolated active non-smokers (24.7%), (3) isolated inactive non-smokers (17.0%), (4) isolated active smokers (14.5%), (5) connected active smokers (12.2%), (6) increasingly connected and active non-smokers (5.4%), and (7) moderately connected inactive smokers (4.4%). Depressive symptoms were highest in the four classes with lower probabilities of social participation across waves. No evidence was found of change over time in depressive symptomatology gaps between people with different health behaviour trajectories.
Conclusion: Health behaviour patterns characterized by consistently low social participation were associated with raised depressive symptomatology, suggesting that focusing on social participation may benefit later-life mental health promotion strategies.
Keywords: ageing; health behaviour; latent class growth analysis; longitudinal analysis; mental health.