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Physical activity can be performed across several domains, including leisure, occupation, household, and transportation, but physical activity research, measurement, and surveillance have historically been focused on leisure-time physical activity. Emerging evidence suggests differential health effects across these domains. In particular, occupational physical activity may be associated with adverse health outcomes. We argue that to adequately consider and evaluate such impacts, physical activity researchers and public health practitioners engaging in measurement, surveillance, and guideline creation should measure and consider all relevant physical activity domains where possible. We describe why physical activity science is often limited to the leisure-time domain and provide a rationale for expanding research and public health efforts to include all physical activity domains.

Background: Physical activity for any purpose counts toward meeting Physical Activity Guidelines (PAG). However, national surveillance systems traditionally focus on leisure-time physical activity. There is an incomplete understanding of the association between meeting PAG in leisure time and occupation activity level among US workers. Methods: We used cross-sectional 2020 National Health Interview Survey data to examine US adults aged 18–64 years who worked the week before the survey (n = 14,814). We estimated the proportion meeting aerobic and muscle-strengthening PAG in leisure time by occupation activity level (low, intermediate, and high). Using logistic regression, we examined the association between meeting PAG in leisure time and occupation activity level, adjusted for sociodemographic characteristics and stratified by hours worked. We compared the sociodemographic characteristics of adults working ≥40 hours (the previous week) in high-activity occupations to those in low- or intermediate-activity occupations. Results: Adults working in high-activity occupations were less likely to meet PAG in leisure time (26.1% [24.3–28.1]) versus those in low-activity (30.6% [29.1–32.2], P < .01) or intermediate-activity (32.4% [30.8–34.2]) occupations. In stratified, adjusted models, adults working ≥40 hours in low- and intermediate-activity occupations were 13% and 20%, respectively, more likely to meet PAG in leisure time versus those in high-activity occupations. Among those working ≥40 hours, adults in high-activity occupations were more likely to be Hispanic or Latino, male, younger, and have a high school education or lower compared with those in less active occupations. Conclusion: Traditional surveillance may underestimate meeting PAG among people working in high-activity occupations, potentially disproportionately affecting certain groups.