0927 Associations Between Daily GPS-Based Neighborhood Physical Disorder and Crime Exposure and Actigraphy-Estimated Sleep Patterns in Adolescents

Abstract Introduction While growing evidence suggests that neighborhood safety and disorder may impact adolescent sleep, prior research has not accounted for travel outside the home neighborhood, which may misclassify environmental exposures. This study examined associations of neighborhood physical disorder and crime in adolescents’ daily activity spaces with sleep patterns. Methods In a micro-longitudinal study, 142 adolescents aged 15-18 were followed for 14 days using smartphone GPS tracking and actigraphy. GPS locations recorded during adolescents’ waking hours were linked to neighborhood physical disorder (number of vacant lots) and crime (annual count of part 1 crimes, e.g., homicide, assault) to derive daily average exposures in adolescents’ activity spaces. Multivariable linear mixed effects regression estimated associations of daily neighborhood exposures with nightly actigraphy-assessed adolescent sleep duration and timing, and mixed effects modified Poisson regression estimated associations with risk of insufficient sleep (< 8 hours) and very short sleep (< 6 hours). Exposures were decomposed to assess between-person differences (sleep differences based on adolescents’ average exposures) and within-person differences (whether sleep differed on days where exposure was higher than their individual average). Models adjusted for school night status, month (for seasonality), adolescent age, sex, race/ethnicity, household income, parent education, parent marital status, distance from home to school, percent of GPS points >250 meters from home, and daily activity space neighborhood economic deprivation, social fragmentation, and tree canopy cover. Results Among participants, the average sleep duration was 6.5 hours. On days when adolescents’ exposure to vacant lots was higher than their own average, they had shorter sleep duration, later sleep onset, earlier sleep offset, and higher risk of insufficient sleep (RR per IQR difference: 1.09, 95% CI: 1.02, 1.17) and very short sleep (RR: 1.23, 95% CI: 1.06, 1.44). Adolescents with higher average crime exposure had shorter sleep duration, earlier sleep offset, and higher risk of insufficient and very short sleep, but there were no within-person associations between crime and sleep outcomes. Conclusion Higher exposure to vacant lots and crime in adolescents’ activity spaces was associated with more adverse sleep patterns. While associations do not necessarily indicate causal relationships, the findings may suggest intervention targets to improve adolescent sleep. Support (if any) K01HL155860(NHLBI)

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Journal
SLEEP
Published
2026-05-01
DOI
https://doi.org/10.1093/sleep/zsag091.0926
Primary Topic
Urban Transport and Accessibility
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article
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article

0927 Associations Between Daily GPS-Based Neighborhood Physical Disorder and Crime Exposure and Actigraphy-Estimated Sleep Patterns in Adolescents

Gabrielle DiFiore, Mathias Basner, Alexander Fiks, Jonathan Mitchell et al.
SLEEP
Urban Transport and Accessibility
article

0927 Associations Between Daily GPS-Based Neighborhood Physical Disorder and Crime Exposure and Actigraphy-Estimated Sleep Patterns in Adolescents

Gabrielle DiFiore, Mathias Basner, Alexander Fiks, Jonathan Mitchell, Douglas Wiebe, Hannah Martin, Ian Barnett, Vicky Tam, Karen Glanz, Stephanie Mayne
article en

Abstract

Abstract Introduction While growing evidence suggests that neighborhood safety and disorder may impact adolescent sleep, prior research has not accounted for travel outside the home neighborhood, which may misclassify environmental exposures. This study examined associations of neighborhood physical disorder and crime in adolescents’ daily activity spaces with sleep patterns. Methods In a micro-longitudinal study, 142 adolescents aged 15-18 were followed for 14 days using smartphone GPS tracking and actigraphy. GPS locations recorded during adolescents’ waking hours were linked to neighborhood physical disorder (number of vacant lots) and crime (annual count of part 1 crimes, e.g., homicide, assault) to derive daily average exposures in adolescents’ activity spaces. Multivariable linear mixed effects regression estimated associations of daily neighborhood exposures with nightly actigraphy-assessed adolescent sleep duration and timing, and mixed effects modified Poisson regression estimated associations with risk of insufficient sleep (< 8 hours) and very short sleep (< 6 hours). Exposures were decomposed to assess between-person differences (sleep differences based on adolescents’ average exposures) and within-person differences (whether sleep differed on days where exposure was higher than their individual average). Models adjusted for school night status, month (for seasonality), adolescent age, sex, race/ethnicity, household income, parent education, parent marital status, distance from home to school, percent of GPS points >250 meters from home, and daily activity space neighborhood economic deprivation, social fragmentation, and tree canopy cover. Results Among participants, the average sleep duration was 6.5 hours. On days when adolescents’ exposure to vacant lots was higher than their own average, they had shorter sleep duration, later sleep onset, earlier sleep offset, and higher risk of insufficient sleep (RR per IQR difference: 1.09, 95% CI: 1.02, 1.17) and very short sleep (RR: 1.23, 95% CI: 1.06, 1.44). Adolescents with higher average crime exposure had shorter sleep duration, earlier sleep offset, and higher risk of insufficient and very short sleep, but there were no within-person associations between crime and sleep outcomes. Conclusion Higher exposure to vacant lots and crime in adolescents’ activity spaces was associated with more adverse sleep patterns. While associations do not necessarily indicate causal relationships, the findings may suggest intervention targets to improve adolescent sleep. Support (if any) K01HL155860(NHLBI)

SLEEPVol. 49(Supplement_1)
Children's Hospital of Philadelphia (US), University of Michigan (US), California University of Pennsylvania (US)
No poverty
Openalex Percentile: Top 5%
Urban Transport and Accessibility
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