pp 1–8 | Cite as

Do sedentary behavior and physical activity spatially cluster? Analysis of a population-based sample of Boston adolescents

  • Kosuke Tamura
  • Dustin T. Duncan
  • Jessica Athens
  • Marc Scott
  • Michael RientiJr.
  • Jared Aldstadt
  • Laurie M. Brotman
  • Brian Elbel


Sedentary behavior and lack of physical activity are key modifiable behavioral risk factors for chronic health problems, such as obesity and diabetes. Little is known about how sedentary behavior and physical activity among adolescents spatially cluster. The objective was to detect spatial clustering of sedentary behavior and physical activity among Boston adolescents. Data were used from the 2008 Boston Youth Survey Geospatial Dataset, a sample of public high school students who responded to a sedentary behavior and physical activity questionnaire. Four binary variables were created: (1) TV watching (>2 h/day), (2) video games (>2 h/day), (3) total screen time (>2 h/day); and (4) 20 min/day of physical activity (≥5 days/week). A spatial scan statistic was utilized to detect clustering of sedentary behavior and physical activity. One statistically significant cluster of TV watching emerged among Boston adolescents in the unadjusted model. Students inside the cluster were more than twice as likely to report >2 h/day of TV watching compared to respondents outside the cluster. No significant clusters of sedentary behavior and physical activity emerged. Findings suggest that TV watching is spatially clustered among Boston adolescents. Such findings may serve to inform public health policy-makers by identifying specific locations in Boston that could provide opportunities for policy intervention. Future research should examine what is linked to the clusters, such as neighborhood environments and network effects.


TV viewing Exercise Youth Spatial scan statistics Urban city Geographical patterns 


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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Department of Population HealthNew York University School of MedicineNew YorkUSA
  2. 2.College of Global Public HealthNew York UniversityNew YorkUSA
  3. 3.PRIISM Applied Statistics CenterNew York UniversityNew YorkUSA
  4. 4.Department of Geography, University at BuffaloState University of New YorkBuffaloUSA
  5. 5.Wagner Graduate School of Public ServiceNew York UniversityNew YorkUSA

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