Income, aging, and the gendered patterns of wellness: Physical health and subjective well-being in China

Abstract

This article investigates the impact of demographic and socioeconomic inequalities on wellness, composed of both physical health and subjective well-being. We examine how gender inequality moderates the joint effects of aging and income on wellness in China. Utilizing generalized linear mixed model (GLMM), we analyze data from the Chinese General Social Survey (CGSS) spanning from 2003 to 2021. Our results reveal that income inequality disproportionately affects physical health among older, underweight, lower-class females; males are more susceptible to negative impacts on subjective well-being, particularly among lower-class, middle-aged males. These gendered patterns are situated in the contemporary Chinese society and are explained in relation to intra-household distributional inequality and the gender role expectations in the Confucian culture. We also discussed the policy implications of how to reduce the gaps in wellness across social classes, age cohorts, and genders.

Keywords:

• China
• gender
• income
• physical health
• subjective well-being

Acknowledgments

The authors would like to thank Zixuan Shan and Qixuan Sun for their valuable research assistance.

Contribution and credit of authors

The authors share equal authorship and the names are displayed in alphabetical order. The specific responsibilities are as follows: Jinjin Liu (literature review and the first draft write-up), Yue Liu (literature review; data collection, and analysis), Yingzhu Pu (data collection and analysis), and Tony Huiquan Zhang (research idea and design, theorization, final draft write-up).

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of this study are available at http://cgss.ruc.edu.cn/. All the data used in this study are available to the public and, hence, no ethical or governmental permissions were required for this study.

Notes

1 The 12 waves that have been made publicly available include the CGSS 2003, 2005, 2006, 2008, 2010, 2011, 2012, 2013, 2015, 2017, 2018, and 2021.

2 The CGSS project does not include Taiwan, Macau SAR, and Hong Kong SAR in its sampling frame.

Additional information

Funding

The present study is supported by the Post-Doctoral Fellowship Program of CPSF [Grant Number: GZC20230820] and the Multi-Year Research Grant by the Faculty of Social Sciences, University of Macau [Grant Number: MYRG2022-00085-FSS].