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Longitudinal patterns and sociodemographic profiles of health-related behaviour clustering among middle-aged and older adults in China and Japan

Published online by Cambridge University Press:  14 February 2023

Min Wu ,
Conghui Yang ,
Yu'an Zhang ,
Maki Umeda ,
Jing Liao Open the ORCID record for Jing Liao [Opens in a new window]  and
Claire Mawditt
Min Wu
Affiliation:
Department of Medical Statistics and Epidemiology, Sun Yat-sen University, Guangzhou, China Global Health Institute, School of Public Health, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
Conghui Yang
Affiliation:
Department of Medical Statistics and Epidemiology, Sun Yat-sen University, Guangzhou, China Global Health Institute, School of Public Health, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
Yu'an Zhang
Affiliation:
Department of Medical Statistics and Epidemiology, Sun Yat-sen University, Guangzhou, China
Maki Umeda
Affiliation:
Research Institute of Nursing Care for People and Community, University of Hyogo, Kobe, Japan
Jing Liao*
Affiliation:
Department of Medical Statistics and Epidemiology, Sun Yat-sen University, Guangzhou, China Global Health Institute, School of Public Health, Institute of State Governance, Sun Yat-sen University, Guangzhou, China
Claire Mawditt
Affiliation:
NHS England, Leeds, UK
*
*Corresponding author. Email: liaojing5@mail.sysu.edu.cn
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Abstract

Given inevitable age-related decreases in physical or mental capacity, studies on health-related behaviour (HRB) clustering in older people provide an opportunity to reduce health-care costs and promote healthy ageing. This study explores the clustering of HRBs and transition probabilities of cluster memberships over time, and compares sociodemographic characteristics of these clusters among Chinese and Japanese middle-aged and older adults. Using the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2015 (N = 19614) and the Japanese Study of Ageing and Retirement (JSTAR) from 2007 to 2011 (N = 7,080), Latent Transition Analysis was applied to investigate the clustering and change in clustering memberships of smoking, alcohol consumption, physical activity and body mass index. Multivariate logistic regression was used to explore the sociodemographic characteristics of these longitudinal HRB cluster members. We identified four common clusters in CHARLS and JSTAR: ‘smoking’, ‘overweight or obese’, ‘healthy lifestyle’ and ‘current smoking with drinking’, and an additional cluster named ‘ex-smoking with drinking’ in JSTAR. Although HRB cluster members were largely stable in both cohorts, participants in China tended to move towards an unhealthy lifestyle, while participants in Japan did the opposite. We also found that participants who smoked and drank were more likely to be male, younger, less educated and unmarried in both cohorts, but the overweight or obese participants were female, urban and higher income in CHARLS but not JSTAR. Our study not only contributes to the knowledge of longitudinal changes in health-related behavioural clustering patterns in an Asian elderly population, but may also facilitate the design of targeted multi-behavioural interventions to promote healthy lifestyles among older people in both countries.

Keywords

health-related behaviourslongitudinal methodssocioeconomic statustransition models
Type
Article
Information
Ageing & Society , First View , pp. 1 - 20
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

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