Beyond Lifelong Marriage and Spousal Coresidence: A Research Note on Racial and Ethnic Differences in Late-Life Family and Living Arrangements

We employ an innovative Bayesian multistate life table approach to examine how race, ethnicity, and sex shape marital status and living arrangements in later life. Using the Health and Retirement Study (1992-2018), we estimate expected years spent in various marital and living arrangements after age 50. Our findings reveal stark disparities: White adults largely follow traditional patterns, spending most of their later years married and living with a spouse. In contrast, Black adults experience the shortest durations of marriage and spousal coresidence, spending much of later life alone or with nonspouse family members. Hispanic adults occupy an intermediate position, maintaining substantial years in marriage while also spending extended time in multigenerational households. These patterns are further stratified by sex, with minority females experiencing significantly fewer years married and living with a spouse than males, amplifying their reliance on alternative family support structures. These findings highlight how the intersection of race, ethnicity, and sex shapes later life social and economic security, emphasizing the need for policies that account for diverse family structures in aging populations.

Authors

Institutions

Publication Details

Journal
Demography
Published
2026-02-01
DOI
https://doi.org/10.1215/00703370-12458349
Primary Topic
Intergenerational Family Dynamics and Caregiving
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Beyond Lifelong Marriage and Spousal Coresidence: A Research Note on Racial and Ethnic Differences in Late-Life Family and Living Arrangements

Emma Zang, Xuezhixing Zhang, Xueqing Wang
Demography
Intergenerational Family Dynamics and Caregiving
article

Beyond Lifelong Marriage and Spousal Coresidence: A Research Note on Racial and Ethnic Differences in Late-Life Family and Living Arrangements

Emma Zang, Xuezhixing Zhang, Xueqing Wang
article en

Abstract

We employ an innovative Bayesian multistate life table approach to examine how race, ethnicity, and sex shape marital status and living arrangements in later life. Using the Health and Retirement Study (1992-2018), we estimate expected years spent in various marital and living arrangements after age 50. Our findings reveal stark disparities: White adults largely follow traditional patterns, spending most of their later years married and living with a spouse. In contrast, Black adults experience the shortest durations of marriage and spousal coresidence, spending much of later life alone or with nonspouse family members. Hispanic adults occupy an intermediate position, maintaining substantial years in marriage while also spending extended time in multigenerational households. These patterns are further stratified by sex, with minority females experiencing significantly fewer years married and living with a spouse than males, amplifying their reliance on alternative family support structures. These findings highlight how the intersection of race, ethnicity, and sex shapes later life social and economic security, emphasizing the need for policies that account for diverse family structures in aging populations.

DemographyVol. 63(1)
University of Michigan (US), Yale University (US), Michigan Medicine (US), Duke-NUS Medical School (SG), Institute for Social Research (NO)
Princeton University
Gender equality
Openalex Percentile: Top 65%
Intergenerational Family Dynamics and Caregiving
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.