Socioeconomic differentiation in sport engagement: frequent exercise, live sport attendance, and their overlap in the 2023 Chinese General Social Survey.
- 1School of Physical Education and Sport Science, Fujian Normal University, Fuzhou, Fujian, China.
- 2Fujian Provincial Heavy Athletic Sports Management Center, Fuzhou, Fujian, China.
Abstract
Objective
To examine how education, personal income, subjective social status, and urban-rural residence were associated with joint categories of frequent exercise and live sport attendance among adult respondents in CGSS2023.Methods
This cross-sectional study included 5,585 adults from the 2023 Chinese General Social Survey. Frequent leisure-time exercise and any past-year live attendance were cross-classified into low, active-only, spectator-only, and dual engagement. Weighted percentages described the category distribution, and covariate-adjusted associations were estimated using an unweighted multinomial logistic model with robust standard errors. Sensitivity analyses varied weighting, sample composition and outcome definitions. Exploratory interaction tests were adjusted for multiple comparisons.Results
Education showed the most consistent associations, with the largest relative risk ratio for dual engagement in the primary unweighted model (1.185, 95% CI 1.148-1.224). Urban residence was also positively associated with dual engagement in the primary unweighted model (relative risk ratio 2.287, 95% CI 1.753-2.985). The corresponding estimates were 1.412 and 1.458 in the combined-weight and selection-adjusted models, respectively; none of the three urban-rural contrasts was statistically significant in either model. Income associations varied with income coding, work-status adjustment, weighting and the attendance threshold. Associations with subjective social status were modest. The education-by-residence interaction was statistically significant after multiplicity adjustment in the unweighted linear-score model. The categorical interaction was not statistically significant under combined weighting.Conclusion
In the CGSS2023 analytical sample, socioeconomic patterning differed across combinations of frequent leisure-time exercise and live sport attendance. Education was positively associated with active-only and dual engagement across the weighting specifications examined, while income associations varied with model specification and evidence for urban-rural differences depended on weighting. Monitoring sport engagement should distinguish exercise from live attendance and examine their overlap to identify the forms of engagement in which socioeconomic differences are concentrated.
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BibTeX
@article{lu2026socioeconomic,
title = {{Socioeconomic differentiation in sport engagement: frequent exercise, live sport attendance, and their overlap in the 2023 Chinese General Social Survey.}},
author = {Congfei Lu and Huili Dai and Jianhua Xu},
journal = {Frontiers in public health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1965653},
url = {https://europepmc.org/article/MED/42908536},
note = {CC BY},
}
RIS
TY - JOUR
TI - Socioeconomic differentiation in sport engagement: frequent exercise, live sport attendance, and their overlap in the 2023 Chinese General Social Survey.
AU - Congfei Lu
AU - Huili Dai
AU - Jianhua Xu
PY - 2026
DA - 2026/10/07
JO - Frontiers in public health
DO - 10.3389/fpubh.2026.1965653
UR - https://europepmc.org/article/MED/42908536
AB - Objective To examine how education, personal income, subjective social status, and urban-rural residence were associated with joint categories of frequent exercise and live sport attendance among adult respondents in CGSS2023.Methods This cross-sectional study included 5,585 adults from the 2023 Chinese General Social Survey. Frequent leisure-time exercise and any past-year live attendance were cross-classified into low, active-only, spectator-only, and dual engagement. Weighted percentages described the category distribution, and covariate-adjusted associations were estimated using an unweighted multinomial logistic model with robust standard errors. Sensitivity analyses varied weighting, sample composition and outcome definitions. Exploratory interaction tests were adjusted for multiple comparisons.Results Education showed the most consistent associations, with the largest relative risk ratio for dual engagement in the primary unweighted model (1.185, 95% CI 1.148-1.224). Urban residence was also positively associated with dual engagement in the primary unweighted model (relative risk ratio 2.287, 95% CI 1.753-2.985). The corresponding estimates were 1.412 and 1.458 in the combined-weight and selection-adjusted models, respectively; none of the three urban-rural contrasts was statistically significant in either model. Income associations varied with income coding, work-status adjustment, weighting and the attendance threshold. Associations with subjective social status were modest. The education-by-residence interaction was statistically significant after multiplicity adjustment in the unweighted linear-score model. The categorical interaction was not statistically significant under combined weighting.Conclusion In the CGSS2023 analytical sample, socioeconomic patterning differed across combinations of frequent leisure-time exercise and live sport attendance. Education was positively associated with active-only and dual engagement across the weighting specifications examined, while income associations varied with model specification and evidence for urban-rural differences depended on weighting. Monitoring sport engagement should distinguish exercise from live attendance and examine their overlap to identify the forms of engagement in which socioeconomic differences are concentrated.
SN - 2296-2565
ER -