Typologies of intergenerational relations in urban and rural China: a latent class analysis
Typologies of intergenerational relations in urban and rural China: a latent class analysis
Understanding intergenerational relations in China has become increasingly important against a backdrop of rapid social and demographic transitions and an ongoing urban-rural divide. From the parental perspective, this research investigates patterns and determinants of intergenerational relations between middle-aged and older parents and their non-coresident children in urban and rural China using data from the China Health and Retirement Longitudinal Study (2018) (N = 14,616). Latent class analysis revealed three typologies of intergenerational relations found across both urban and rural China – Tight-knit, Support-at-distance and Material-oriented-detached, and one typology particularly for urban China – Staying-in-touch-but-independent. The observed patterns suggest intergenerational bonds remain solid alongside the emergence of new trends, reflecting the modernization process. Multivariate multinomial regression analysis identified determinants for membership of each relationship typology. The findings will inform policy-makers and care professionals, supporting the identification of the vulnerable groups and the design of targeted policies for older parents with different family resources.
Advance Care Planning, China, Intergenerational Relations, Latent Class Analysis, Quantitative Methods, Urban-rural Differences
Wang, Ning
734a4393-d4fe-49b6-aaea-93b35eb3bc7b
Evandrou, Maria
cd2210ea-9625-44d7-b0f4-fc0721a25d28
Falkingham, Jane
8df36615-1547-4a6d-ad55-aa9496e85519
Xu, Maodi
00fa5814-cd92-4e45-8908-03e990da4f81
25 October 2022
Wang, Ning
734a4393-d4fe-49b6-aaea-93b35eb3bc7b
Evandrou, Maria
cd2210ea-9625-44d7-b0f4-fc0721a25d28
Falkingham, Jane
8df36615-1547-4a6d-ad55-aa9496e85519
Xu, Maodi
00fa5814-cd92-4e45-8908-03e990da4f81
Wang, Ning, Evandrou, Maria, Falkingham, Jane and Xu, Maodi
(2022)
Typologies of intergenerational relations in urban and rural China: a latent class analysis.
Journal of Applied Gerontology.
(doi:10.1177/07334648221133811).
Abstract
Understanding intergenerational relations in China has become increasingly important against a backdrop of rapid social and demographic transitions and an ongoing urban-rural divide. From the parental perspective, this research investigates patterns and determinants of intergenerational relations between middle-aged and older parents and their non-coresident children in urban and rural China using data from the China Health and Retirement Longitudinal Study (2018) (N = 14,616). Latent class analysis revealed three typologies of intergenerational relations found across both urban and rural China – Tight-knit, Support-at-distance and Material-oriented-detached, and one typology particularly for urban China – Staying-in-touch-but-independent. The observed patterns suggest intergenerational bonds remain solid alongside the emergence of new trends, reflecting the modernization process. Multivariate multinomial regression analysis identified determinants for membership of each relationship typology. The findings will inform policy-makers and care professionals, supporting the identification of the vulnerable groups and the design of targeted policies for older parents with different family resources.
Text
Falkingham Manuscript0930_De-anonymised_JAG-22-0360
- Accepted Manuscript
More information
Accepted/In Press date: 25 October 2022
e-pub ahead of print date: 25 October 2022
Published date: 25 October 2022
Additional Information:
Funding Information:
This work was supported by Chinese Social Science Foundation Youth Project [20CSH014] and Shanghai Pujiang Program [2020PJC023].
Publisher Copyright:
© The Author(s) 2022.
Keywords:
Advance Care Planning, China, Intergenerational Relations, Latent Class Analysis, Quantitative Methods, Urban-rural Differences
Identifiers
Local EPrints ID: 471829
URI: http://eprints.soton.ac.uk/id/eprint/471829
ISSN: 0733-4648
PURE UUID: 0c53e736-fc49-4688-b268-3b4f9daf514e
Catalogue record
Date deposited: 21 Nov 2022 17:50
Last modified: 17 Mar 2024 03:03
Export record
Altmetrics
Contributors
Author:
Ning Wang
Author:
Maodi Xu
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics