Evidence map›Paper›PMID 42865444›Full record

ArticleFrontiers in public health2026

Physical activity, entertainment screen time, and dietary fat profiles and concurrent weight status among school-attending Chinese children and adolescents: CHNS 2004-2011.

Boao Qin, Changyang Wang, Yuchen Zhang, Linwei Sheng, Xiaobo Jiang, Chen Cheng, Yukuo Wang

Abstract read
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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Boao QinSchool of Physical Education, Yanshan University, Qinhuangdao, China.
Changyang WangSchool of Physical Education, Yanshan University, Qinhuangdao, China.
Yuchen ZhangSchool of Physical Education, Yanshan University, Qinhuangdao, China.
Linwei ShengSchool of Physical Education, Yanshan University, Qinhuangdao, China.
Xiaobo JiangSchool of Physical Education, Yanshan University, Qinhuangdao, China.
Chen ChengSchool of Physical Education, Yanshan University, Qinhuangdao, China.
Yukuo WangSchool of Physical Education, Yanshan University, Qinhuangdao, China.

Funding

MONITORING SOCIAL CHANGE: HEALTH, REPRODUCTION, AGINGR01HD030880 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ADAIR, LINDA S, POPKIN, BARRY M · 1994 to 2024
$27.0M
Monitoring Social Change: Dynamics Of Aging And Cognitive FunctionR01AG065357 · NIA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ADAIR, LINDA S, POPKIN, BARRY M · 2020 to 2024
$3.6M
Emergence of Cardiometabolic Risk Across the Lifecycle in ChinaR01HL108427 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GORDON-LARSEN, PENNY · 2012 to 2015
$2.7M
Transition to a Western diet and cardiometabolic risk: biomarkers derived from the microbiomeR01DK104371 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GORDON-LARSEN, PENNY · 2015 to 2018
$2.5M
Nutrition-Related NCD Prevention Training in ChinaD43TW009077 · FIC · UNIV OF NORTH CAROLINA CHAPEL HILL · PI POPKIN, BARRY M · 2011 to 2015
$1.1M
FIC NIH HHS D43 TW009077NHLBI NIH HHS R01 HL108427NIA NIH HHS R01 AG065357NICHD NIH HHS R01 HD030880NIDDK NIH HHS R01 DK104371
6 · The paper itself

Abstract

Background: Physical activity, screen-based leisure, and diet co-occur, but profiles estimated from a small set of indicators may be sensitive to historical period and model assumptions. We identified profiles defined by total physical activity, reported entertainment screen time, and dietary fat contribution to energy intake in the 2004-2011 China Health and Nutrition Survey (CHNS), and examined their concurrent associations with weight status. Methods: This pooled cross-sectional analysis included 4,112 person-wave observations from school-attending participants aged 6-17 years. A prespecified Gaussian mixture analysis compared one through six profiles. Associations with measured overweight/obesity were estimated in 4,068 observations from 2,757 participants using posterior-probability pseudo-class draws and participant-clustered robust standard errors. Wave-, age-, model-specification-, missing-data-, and alternative-outcome analyses assessed robustness. Results: The prespecified model retained five profiles: very low activity (6.9%), low-to-moderate activity/lower fat (37.8%), no reported entertainment screen time (5.4%), higher fat (27.8%), and highly active (22.2%). The exact BIC-preferred number of profiles varied across survey waves, age groups, and model specifications, and 48.4% of observations had a maximum posterior probability below 0.70. The estimated prevalence of overweight/obesity, accounting for profile-membership uncertainty, was highest in the very-low-activity profile (24.4%) and was 16.4% in the reference profile. This descriptive difference attenuated after adjustment (odds ratio, 1.18; 95% confidence interval, 0.81-1.69), and the fully adjusted global profile test was non-significant ( Conclusion: In the 2004-2011 CHNS analytic sample, the measured behaviors formed heterogeneous combinations, but the selected profiles did not independently distinguish concurrent weight status after adjustment. The findings are historical and sample-specific; they should not be interpreted as current national profile distributions or as validation of profile-based interventions.

Indexed as

Body WeightDietary FatsExerciseScreen TimeAdolescentChildChinaCross-Sectional StudiesEast Asian PeopleFemaleHumansMaleNutrition SurveysOverweightDietary Fatsbehavioral profileschildren and adolescentsChina Health and Nutrition Surveydietary fatentertainment screen timelatent profile analysisphysical activityweight status

Identifiers

PMID42865444
PMCPMC13654989

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.