Background: The joint impact of sedentary behavior and physical activity on obesity has not been assessed in a large cohort followed from adolescence to adulthood.
Purpose-To validate a commercial database of community-level physical activity facilities that can be used in future research examining associations between access to physical activity facilities and individual-level physical activity and obesity.Methods-Physical activity facility characteristics and locations obtained from a commercial database were compared to a field census conducted in 80 Census block groups within two U.S. communities. Agreement statistics, agreement of administratively-defined neighborhoods, and distance between locations were used to quantify count, attribute, and positional error.Results-There was moderate agreement (concordance: non-urban: 0.39; urban: 0.46) of presence of any physical activity facility and poor to moderate agreement (kappa range: 0.14 to 0.76) of physical activity facility type. The mean Euclidean distance between commercial database versus field census locations was 757 and 35 meters in the non-urban and urban communities, respectively. However, 94 and 100% of non-urban and urban physical activity facilities, respectively, fell into the same 5-digit ZIP code, dropping to 92 and 98% in the same block group and 71% along the same street.Conclusions-Our findings suggest that the commercial database of physical activity facilities may contain appreciable error, but patterns of error suggest that built environment-health associations are likely biased downward.
Obesity is related to diet and activity patterns, yet pattern analyses are rare and findings population‐specific. We compared cluster analysis (individuals with shared behaviors), factor analysis (underlying correlated behavior patterns), and an index (scoring of behavior items) to describe obesity‐related behavior patterns. Data from the National Longitudinal Study of Adolescent Health (Wave I age 11–21; N=9,251) included 36 self‐reported diet, activity, and behavior variables, and measured anthropometry [Waves I: 1995; II: 1996, III: 2000]. Sex‐stratified, longitudinal logistic regression, controlling for sociodemographics, assessed odds of incident obesity (BMI ≥30 kg/m2 or BMI ≥95th percentile CDC/NCHS) across clusters, factor level, and index score. Cluster analysis findings linked several behavior patterns to elevated incident obesity in females (relative to school involvement) [e.g., OR (95% CI): 2.8 (1.9, 4.3)]. Factor findings linked nutrient dense diet, sports & exercise, and junk food & sedentary time to incident obesity in females [e.g., OR (95% CI): 2.2 (1.1, 4.3)]. High index scores were associated with incident obesity [OR (95% CI): male: 1.8 (1.3, 2.5); female: 2.6 (2.0, 3.3)]. Cluster and factor analyses revealed similar patterning of diverse behaviors, and an index measure applicable to other populations yielded comparable obesity associations.
Funding: RO1‐041375
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