The study, published in the Journal of Activity, Sedentary and Sleep Behaviors, was conducted by a team of researchers based largely at the National Institute on Minority Health and Health Disparities and the National Cancer Institute, both parts of the National Institutes of Health. Led by Mohammad Moniruzzaman and Kosuke Tamura of the Socio-Spatial Determinants of Health Laboratory, the team set out to determine whether adults living in more segregated counties spend more of their waking hours in sedentary behavior than those living in more integrated places. The hypothesis was grounded in a well-established socio-ecological framework: segregation is considered a fundamental cause of health disparities, and it plausibly shapes the environments, routines, and stressors that govern daily movement.

To test the idea, the researchers drew on the AmeriSpeak panel, a probability-based survey designed to represent the US adult population aged 20 to 75. From 15,153 panelists invited, 2,877 completed a short survey and at least one valid recall of their previous day’s activities, and after exclusions for incomplete or inconsistent data, the final analytical sample comprised 2,637 adults with a mean age of 45.1 years, just over half of them female. Data were collected by NORC at the University of Chicago in October and November 2019, a period deliberately chosen to avoid the seasonal extremes of summer and winter that can distort physical activity estimates. Participants were invited on randomly selected days to complete a recall covering the full previous day from midnight to midnight, and those who completed a first recall were invited to complete a second one one to two weeks later, giving the team a total of 4,161 valid daily observations.

The measurement tool at the heart of the study was the Activities Completed over Time in 24-hours instrument, or ACT24, a previous-day recall developed to capture behavior at the population level with unusual granularity. Participants reported their activities from a list of more than 170 individual activities organized into 14 major categories and six life domains: work, transport, leisure, personal care, household activities, and other pursuits. Each reported activity was linked to the Compendium of Physical Activities and assigned a metabolic equivalent value, allowing the researchers to define sedentary behavior precisely as waking activity involving sitting or reclining at energy expenditure of roughly 1.5 METs or less, excluding time spent asleep in the primary sleep period. Validation studies have shown that ACT24 estimates population-level sedentary time within about one percent of the activPAL monitor, a thigh-worn device considered a gold standard for posture-based measurement, which gives the self-reported figures considerable credibility.

The exposure of interest was quantified using the isolation index, a classic demographic measure calculated at the county level separately for non-Hispanic Black and Hispanic residents. The index ranges from 0 to 1 and captures the probability that a member of a given minority group will encounter only members of their own group in their residential area, with higher values indicating deeper segregation. For the non-Hispanic Black index, all other racial and ethnic groups served as the reference, and the same logic applied to the Hispanic index. The researchers also adjusted their models for a battery of individual covariates, including age, sex, marital status, education, occupation, and body mass index, as well as two area-level factors: county poverty, derived from American Community Survey five-year estimates, and census region. Survey-weighted linear regression was used to model the relationship, with both the segregation index and sedentary time treated as continuous variables.

The headline finding was a null result, and a robust one. US adults in the sample reported an average of 9.5 hours of sedentary time per day, with non-Hispanic Black adults at 9.8 hours and Hispanic adults at 8.9 hours. Yet living in a more segregated county was not associated with total daily sedentary time for either group. The regression coefficient for non-Hispanic Black segregation was -0.30 hours per day, with a 95 percent confidence interval spanning -2.53 to 1.94 and a p-value of 0.790, while Hispanic segregation yielded a coefficient of 0.32 with a confidence interval of -1.64 to 2.28 and a p-value of 0.743. In plain terms, the data are consistent with effects ranging from a substantial reduction to a substantial increase in sitting time, which is another way of saying the study detected no signal at all. Sensitivity analyses using non-Hispanic White adults as the reference group in the isolation index produced the same pattern.

The null findings held up when the team stratified the analysis by sex, with no significant associations emerging for non-Hispanic Black or Hispanic men or women considered separately. The domain-specific analyses, which broke sedentary time into its component life domains, produced one marginal exception: among Hispanic adults, segregation was weakly and positively associated with sedentary time in the personal domain, with a coefficient of 0.65 hours per day and a confidence interval of 0.00 to 1.29 that just grazed the threshold of significance. No other domain—leisure, work, transport, household, or other—showed a significant relationship for either group. Given that most sedentary time in the sample was accumulated during leisure activities, followed by work and transportation, the absence of associations in those larger domains carries particular weight.

Why might segregation fail to shape sitting time when it demonstrably shapes so much else? The authors point to several possibilities. One is statistical power: the subgroup samples were relatively small, with 283 non-Hispanic Black adults and 336 Hispanic adults, which limits the ability to detect modest effects. But that explanation cannot account for similar null results in much larger studies, including an analysis of the CARDIA cohort of 2,120 participants that used accelerometer-measured sedentary time and also found no cross-sectional or longitudinal association between neighborhood segregation and sitting. Another possibility is that county-level indices are simply too coarse to capture the neighborhood experiences that matter. Segregation is a socially constructed phenomenon, and people’s perceptions of safety, social cohesion, familiarity with neighbors, and access to activity-promoting facilities may influence behavior in ways that a county-wide statistic cannot register. Factors such as how long residents have lived in a neighborhood and how neighborhood conditions have changed over time also remain unmeasured in this kind of analysis.

The broader literature on segregation and movement behavior is, as the authors note, mixed and inconclusive. Studies using the Behavioral Risk Factor Surveillance System found no association between segregation and physical inactivity among Black adults, and a metropolitan-level analysis found no link between the isolation index and any exercise in the past month. A North Carolina study, by contrast, reported that Black adults living in more segregated neighborhoods actually engaged in more walking and moderate-to-vigorous activity than those in predominantly European American neighborhoods, and a national study of Hispanic adults found that living in segregated metropolitan areas was associated with an 18 percent lower likelihood of exercising. The new study’s use of the county-level isolation index and the comprehensive ACT24 tool, rather than the dissimilarity index and a single yes-or-no exercise question, makes direct comparison difficult—and, as the authors caution, exercising less does not necessarily mean sitting more.

The study’s strengths are considerable: a nationally representative sample, a validated recall instrument benchmarked against device-based measurement, coverage of all major life domains, and careful survey weighting adjusted to population totals for age, sex, education, race and ethnicity, housing tenure, telephone status, and census division. Its limitations are equally clear: the cross-sectional design cannot establish causation, self-reported behavior may carry social desirability bias although prior validation work found no evidence of it, and the modest minority subsamples constrain statistical power. The authors conclude that residential segregation alone may not exert a significant effect on sedentary behavior, and they call for replication with larger samples of underrepresented minority populations, deeper exploration of sex-specific and domain-specific variation, and closer investigation of how built and social environments relate to sitting. For now, the message is that the geography of who lives next to whom does not, by itself, determine how long Americans spend in their chairs—a finding that redirects attention toward the finer-grained neighborhood conditions that might.

Subject of Research: The association between county-level racial and ethnic residential segregation and sedentary behavior among US adults

Article Title: County-level residential segregation and sedentary behavior in US adults

Article References: Moniruzzaman, M., Deng, Y., Rogers, B., Islam, S. M. S., Jones, K. K., Saint-Maurice, P. F., Patel, S., Berrigan, D., Matthews, C. E., & Tamura, K. (2025). County-level residential segregation and sedentary behavior in US adults. Journal of Activity, Sedentary and Sleep Behaviors, 4(1), Article 15. https://doi.org/10.1186/s44167-025-00084-w

Image Credits: AI Generated

DOI: 10.1186/s44167-025-00084-w

Keywords: sedentary behavior, residential segregation, isolation index, public health, health disparities, ACT24, physical activity, county-level analysis, non-Hispanic Black adults, Hispanic adults, AmeriSpeak panel, built environment