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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.

Background: To better understand physical activity behavior and its health benefits in people living with health conditions, we studied people with and without 20 different self-reported health conditions with regard to (1) their physical activity levels, (2) factors correlated with these physical activity levels, and (3) the association between physical activity and all-cause mortality. Methods: We used a subsample (n = 88,659) of the Lifelines cohort study from the Netherlands. For people living with and without 20 different self-reported health conditions, we studied the aforementioned factors in relation to physical activity. Physical activity was assessed with the Short Questionnaire to Assess Health-Enhancing Physical Activity Questionnaire, and mortality data were obtained from the Dutch death register. Results: People with a reported health condition were less likely to meet physical activity guidelines than people without a reported health condition (odds ratios ranging from 0.55 to 0.89). Higher body mass index and sitting time, and lower self-rated health, physical functioning, and education levels were associated with lower odds of meeting physical activity guidelines across most health conditions. Finally, we found a protective association between physical activity and all-cause mortality in both people living with and without different health conditions. Conclusion: People living with different health conditions are generally less physically active compared with people living without a health condition. Both people living with and without self-reported health conditions share a number of key factors associated with physical activity levels. We also observed the expected protective association between physical activity and all-cause mortality.

Background: This study examined the after-school activities of Japanese elementary school children in which little information is available for understanding the process by which participation in organized activities leads to the decrease in children’s independent mobility. Methods: One thousand eight hundred and twenty-four mothers of elementary school children participated in an online survey. The mothers responded to the questions on the number of lessons (or cram schools) their children attended weekdays, as well as their children’s behavior after classes, and parents providing transportation when their children go out to play. Results: The proportion of children attending lessons and/or cram schools increased as their grades progressed. A significant interaction existed between the degree of parental transportation and grade in terms of whether or not the children attended lessons and/or cram schools. Parental involvement included pick up or drop-off for a large percentage of younger children without lessons, whereas the degree of parental involvement was greater for older children attending lessons. In other words, parents of children without attending lessons or cram schools tended to allow children to engage in independent activities when they reached the higher grades, whereas parents of children who frequently attended lessons and cram schools tended to remain involved in transporting their children, even when they reached the higher grades. Conclusions: The results suggested that the participation of children in organized activities leads to a routine of parental pickup and/or drop-off, which renders difficult the facilitation of opportunities for children to independently participate in play activities.

Background: National physical activity (PA) policy processes are only beginning to be studied in Latin America, and little attention has focused at the subnational level. This study examined national–subnational relations in the policy process (agenda setting, policy formulation, adoption, implementation, and evaluation) in selected Latin American countries. Methods: The Global Observatory for Physical Activity’s (GoPA!) INTEGRATE-PA-Pol tool was applied in Colombia, Costa Rica, Ecuador, and Mexico. Data were collected in matched pairs of the capital plus one noncapital city among national and subnational policymakers (n = 27), previously identified by the GoPA! Country Contacts. PA policy development and implementation were assessed using descriptive statistics. Results: Twenty-three (response rate = 85.2%) informants provided data, mainly from the health sector (52.2%), followed by the sport (26.1%), transport (13.0%), and education (8.7%) sectors. Most informants reported that their countries had a current PA policy embedded within noncommunicable diseases prevention plans (46.2%), other plans (46.2%), or obesity prevention/management/control plans (7.7%). Respondents at the subnational level rated PA promotion as central (64.3%), while the national-level role was important but not central (75.0%). National and subnational policymakers indicated low-to-little involvement in the other level’s PA policy processes across the 5 policy stages. Conclusions: This study demonstrated that collecting national and subnational PA policy data across countries with the active collaboration of the GoPA! network was feasible. We also successfully identified governmental interactions throughout the PA policy process, suggesting suboptimal engagement between national and subnational levels.