Literature DB >> 31981937

Social transition and health inequality in China: an age-period-cohort analysis.

J Jiang1, X Zhang2.   

Abstract

OBJECTIVES: To examine self-rated health (SRH) trajectories by age, period and cohort in the dynamic environment of China and to focus on sex, educational, family economic status (FES) and regional disparities in these temporal trajectories. STUDY
DESIGN: Repeated cross-sectional data from the World Value Survey from 1990 to 2012 (n = 7731) were used.
METHODS: An age-period-cohort (APC) model with an intrinsic estimator method was applied, using SRH as a continuous variable to analyse SRH trajectories by age, period and cohort in different groups in China. Robust analyses were conducted using SRH as a binary variable and a hierarchical APC cross-classified random effects model.
RESULTS: SRH was adversely associated with age, and a global trend of declining SRH was observed between 1990 and 2012; however, SRH generally increased across successive cohorts in China. SRH was better in males, individuals from the eastern region, and in those with higher levels of education and higher FES. Regional and FES disparities in SRH increased with age and across successive cohorts; however, educational disparities in SRH first decreased and then increased with age and across successive cohorts, and sex disparities in SRH decreased across successive cohorts, in general.
CONCLUSIONS: A well-performing social environment is related to better population health. The cumulative disadvantage in health among individuals from underprivileged regions/families with less education should be the focus of social transition in China.
Copyright © 2019 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Keywords:  Age-period-cohort model; China; Health inequality; Self-rated health; Social transition

Mesh:

Year:  2020        PMID: 31981937     DOI: 10.1016/j.puhe.2019.08.025

Source DB:  PubMed          Journal:  Public Health        ISSN: 0033-3506            Impact factor:   2.427


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