Age-Dependent Heterogeneity in the Association Between Physical Activity and Mental Distress: A Causal Machine Learning Analysis of 3.2 Million U.S. Adults
Yuan Shan (Department of Statistical Science, Duke University)

TL;DR
This study reveals that the mental health benefits of physical activity vary significantly with age, with older adults experiencing stronger protective effects, and highlights a concerning decline in benefits among young adults over recent years.
Contribution
It employs causal machine learning on a large national dataset to uncover age as the key factor in heterogeneity of physical activity's mental health benefits.
Findings
Protective effect of physical activity increases with age.
The mental health benefit for young adults has diminished over the past decade.
Age is identified as the primary driver of heterogeneity in the association.
Abstract
Physical activity (PA) is widely recognized as protective against mental distress, yet whether this benefit varies systematically across population subgroups remains poorly understood. Using pooled data from ten consecutive annual waves of the U.S. Behavioral Risk Factor Surveillance System (2015-2024; n = 3,242,218), we investigate heterogeneity in the association between leisure-time PA and frequent mental distress (FMD, >=14 days/month) across age groups. Survey-weighted logistic regression reveals a striking age gradient: the adjusted odds ratio for PA ranges from 0.89 among young adults (18-24) to 0.50 among adults aged 55-64, with the protective association strengthening monotonically with age. Temporal analysis across all ten years shows that the young-adult PA effect has been eroding over the past decade, with the 18-24 OR reaching 1.01 (null) in both 2018 and 2024 --…
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