Validation of a GIS facilities database: quantification and implications of error.

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: nonurban: 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 m in the nonurban and urban communities, respectively. However, 94% and 100% of nonurban 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.

Screen time and physical activity during adolescence: longitudinal effects on obesity in young adulthood.

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. METHODS: Nationally representative longitudinal data from Waves II (1995; mean age: 15.9) and III (2001; mean age: 21.4) of the National Longitudinal Study of Adolescent Health (n = 9,155) were collected. Sex-stratified multivariate logistic regression analysis assessed the odds of obesity associated with Wave II MVPA and screen time, controlling for sociodemographic characteristics and change in MVPA and screen time from Wave II to III. Obesity was defined using body mass index (BMI, kg/m2) International Obesity Task Force cut-points at Wave II and adult cut-points at Wave III (BMI >or= 30). RESULTS: In males, adjusted odds of prevalent obesity was strongly predicted by MVPA bouts [OR (95% CI): OR6 vs. 1 MVPA bouts = 0.50 (0.40, 0.62); OR4 vs. 40 hrs screen time = 0.83 (0.69, 1.00)]. In females, greater MVPA bouts and lower screen time correlated with lower prevalent obesity [OR (95% CI): OR6 vs. 1 MVPA bouts = 0.67 (0.49, 0.91); OR4 vs. 40 hrs screen time = 0.67 (0.53, 0.85)]. Longitudinally, adolescent screen time hours had a stronger influence on incident obesity in females [OR (95% CI): OR4 vs. 40 hrs = 0.58 (0.43, 0.80)] than males [OR (95% CI): OR4 vs. 40 hrs = 0.78 (0.61, 0.99)]. Longitudinal activity patterns were not predictive of incident obesity. CONCLUSION: Reducing screen time during adolescence and into adulthood may be a promising strategy for reducing obesity incidence, especially in females.

Medicaid programme changes and the chronically ill: early results from a prospective cohort study of the Oregon Health Plan.

OBJECTIVE: To describe the impacts of recent Oregon Health Plan (OHP) policy changes on individuals living with chronic illness in Oregon. METHODS: A mail survey was conducted of 1374 OHP beneficiaries who were directly affected by the new policies. The analyses reported in this article represent baseline findings from the first of three survey waves in an ongoing prospective cohort study. RESULTS: A significant association was found between Medicaid policy changes and high rates of disenrolment from the OHP. Compared to the non-chronically ill, the chronically ill were more likely to report inability to pay for medications, higher medical debt, more unmet health needs, and poorer health status. Among the chronically ill, those who lost insurance reported decreased access to and utilization of healthcare, more medical debt, and more restriction of medications. DISCUSSION: As policy-makers restructure public programmes to accommodate tight budgets and rising healthcare costs, people with chronic illness can easily be overlooked. Chronically ill individuals face disproportionate financial and health burdens. Small cost-saving policy changes can lead to widespread disenrolment that cascades into reduced access to healthcare services, altered utilization patterns, and financial strain.