The urban built environment and obesity in New York City: a multilevel analysis

Am J Health Promot. Mar-Apr 2007;21(4 Suppl):326-34. doi: 10.4278/0890-1171-21.4s.326.


Purpose: To examine whether urban form is associated with body size within a densely-settled city.

Design: Cross-sectional analysis using multilevel modeling to relate body mass index (BMI) to built environment resources.

Setting: Census tracts (n = 1989) within the five boroughs of New York City.

Subjects: Adult volunteers (n = 13,102) from the five boroughs of New York City recruited between January 2000 and December 2002.

Measures: The dependent variable was objectively-measured BMI. Independent variables included land use mix; bus and subway stop density; population density; and intersection density. Covariates included age, gender, race, education, and census tract-level poverty and race/ethnicity.

Analysis: Cross-sectional multilevel analyses.

Results: Mixed land use (Beta = -.55, p < .01), density of bus stops (Beta = -.01, p < .01) and subway stops (Beta = -.06, p < .01), and population density (Beta = -.25, p < .001), but not intersection density (Beta = -. 002) were significantly inversely associated with BMI after adjustmentfor individual- and neighborhood-level sociodemographic characteristics. Comparing the 90th to the 10th percentile of each built environment variable, the predicted adjusted difference in BMI with increased mixed land use was -. 41 units, with bus stop density was -.33 units, with subway stop density was -.34 units, and with population density was -.86 units.

Conclusion: BMI is associated with built environment characteristics in New York City.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Body Mass Index
  • Cross-Sectional Studies
  • Environment Design*
  • Female
  • Health Status Indicators*
  • Humans
  • Life Style
  • Male
  • Middle Aged
  • New York City / epidemiology
  • Obesity / epidemiology*
  • Population Density
  • Prevalence
  • Residence Characteristics
  • Socioeconomic Factors
  • Urban Health / statistics & numerical data*