OBJECTIVES: We evaluated the association between the county sprawl index, a measure of residential density and street accessibility, and physical activity and body mass index (BMI). METHODS: We conducted a multilevel cross-sectional analysis in a sample of Nurses' Health Study participants living throughout the United States in 2000 to 2001 (n = 136 592). RESULTS: In analyses adjusted for age, smoking status, race, and husband's education, a 1-SD (25.7) increase in the county sprawl index (indicating a denser, more compact county) was associated with a 0.13 kilograms per meters squared (95% confidence interval [CI] = -0.18, -0.07) lower BMI and 0.41 (95% CI = 0.17, 0.65) more metabolic equivalent (MET) hours per week of total physical activity, 0.26 (95% CI = 0.19, 0.33) more MET hours per week of walking, and 0.47 (95% CI = 0.34, 0.59) more MET hours per week of walking, bicycling, jogging, and running. We detected potential effect modification for age, previous disease status, husband's education level (a proxy for socioeconomic status), and race. CONCLUSIONS: Our results suggest that living in a dense, compact county may be conducive to higher levels of physical activity and lower BMI in women.
OBJECTIVES: We evaluated the association between the county sprawl index, a measure of residential density and street accessibility, and physical activity and body mass index (BMI). METHODS: We conducted a multilevel cross-sectional analysis in a sample of Nurses' Health Study participants living throughout the United States in 2000 to 2001 (n = 136 592). RESULTS: In analyses adjusted for age, smoking status, race, and husband's education, a 1-SD (25.7) increase in the county sprawl index (indicating a denser, more compact county) was associated with a 0.13 kilograms per meters squared (95% confidence interval [CI] = -0.18, -0.07) lower BMI and 0.41 (95% CI = 0.17, 0.65) more metabolic equivalent (MET) hours per week of total physical activity, 0.26 (95% CI = 0.19, 0.33) more MET hours per week of walking, and 0.47 (95% CI = 0.34, 0.59) more MET hours per week of walking, bicycling, jogging, and running. We detected potential effect modification for age, previous disease status, husband's education level (a proxy for socioeconomic status), and race. CONCLUSIONS: Our results suggest that living in a dense, compact county may be conducive to higher levels of physical activity and lower BMI in women.
Authors: B E Ainsworth; W L Haskell; A S Leon; D R Jacobs; H J Montoye; J F Sallis; R S Paffenbarger Journal: Med Sci Sports Exerc Date: 1993-01 Impact factor: 5.411
Authors: W Willett; M J Stampfer; C Bain; R Lipnick; F E Speizer; B Rosner; D Cramer; C H Hennekens Journal: Am J Epidemiol Date: 1983-06 Impact factor: 4.897
Authors: A M Wolf; D J Hunter; G A Colditz; J E Manson; M J Stampfer; K A Corsano; B Rosner; A Kriska; W C Willett Journal: Int J Epidemiol Date: 1994-10 Impact factor: 7.196
Authors: Peter James; David Berrigan; Jaime E Hart; J Aaron Hipp; Christine M Hoehner; Jacqueline Kerr; Jacqueline M Major; Masayoshi Oka; Francine Laden Journal: Health Place Date: 2014-03-07 Impact factor: 4.078
Authors: Ruby Fore; Jaime E Hart; Christine Choirat; Jennifer W Thompson; Kathleen Lynch; Francine Laden; Jorge E Chavarro; Peter James Journal: Cancer Epidemiol Biomarkers Prev Date: 2020-02-25 Impact factor: 4.254
Authors: Adela Hruby; JoAnn E Manson; Lu Qi; Vasanti S Malik; Eric B Rimm; Qi Sun; Walter C Willett; Frank B Hu Journal: Am J Public Health Date: 2016-07-26 Impact factor: 9.308