Where can they play? Outdoor spaces and physical activity among adolescents in U.S. urbanized areas

Objective—To estimate behavior-specific effects of several objectively-measured outdoor spaces on different types of moderate to vigorous physical activity (MVPA) in a large, diverse sample of U.S. adolescents. Methods—Using data from Wave I (1994–95) of the National Longitudinal Study of Adolescent Health (U.S., n=10,359) and a linked geographic information system, we calculated percent greenspace coverage and distance to the nearest neighborhood and major parks. Using sex-stratified multivariable logistic regression, we modeled reported participation in wheel-based activities, active sports, exercise, and ≥5 MVPA bouts/week as a function of each outdoor space variable, controlling for individual- and neighborhood-level sociodemographics. Results—Availability of major or neighborhood parks was associated with higher participation in active sports and, in females, wheel-based activity and reporting ≥5 MVPA bouts/week [OR (95% CI): up to 1.71 (1.29. 2.27)]. Greater greenspace coverage was associated with reporting ≥5 MVPA bouts/week in males and females [OR (95% CI): up to 1.62 (1.10, 2.39) for 10.1 to 20% versus ≤10% greenspace] and exercise participation in females [OR (95% CI): up to 1.73 (1.21, 2.49)]. Conclusions—Provision of outdoor spaces may promote different types of physical activities, with potentially greater benefits in female adolescents, who have particularly low physical activity levels

Are neighbourhood food resources distributed inequitably by income and race in the USA? Epidemiological findings across the urban spectrum

ObjectiveMany recent policies focus on socioeconomic inequities in availability of healthy food stores and restaurants. Yet understanding of how socioeconomic inequities vary across neighbourhood racial composition and across the range from rural to urban settings is limited, largely due to lack of large, geographically and socio-demographically diverse study populations. Using a national sample, the authors examined differences in neighbourhood food resource availability according to neighbourhood-level poverty and racial/ethnic population in non-urban, low-density urban and high-density urban areas.DesignCross-sectional data from an observational cohort study representative of the US middle and high school-aged population in 1994 followed into young adulthood.ParticipantsUsing neighbourhood characteristics of participants in the National Longitudinal Study of Adolescent Health (Wave III, 2001–2002; n=13 995 young adults aged 18–28 years representing 7588 US block groups), the authors examined associations between neighbourhood poverty and race/ethnicity with neighbourhood food resource availability in urbanicity-stratified multivariable linear regression.Primary and secondary outcome measuresNeighbourhood availability of grocery/supermarkets, convenience stores and fast-food restaurants (measured as number of outlets per 100 km roadway).ResultsNeighbourhood race and income disparities were most pronounced in low-density urban areas, where high-poverty/high-minority areas had lower availability of grocery/supermarkets (β coefficient (β)=–1.91, 95% CI –2.73 to –1.09) and convenience stores (β=–2.38, 95% CI –3.62 to –1.14) and greater availability of fast-food restaurants (β=4.87, 95% CI 2.26 to 7.48) than low-poverty/low-minority areas. However, in high-density urban areas, high-poverty/low-minority neighbourhoods had comparatively greater availability of grocery/supermarkets (β=8.05, 95% CI 2.52 to 13.57), convenience stores (β=2.89, 95% CI 0.64 to 5.14) and fast-food restaurants (β=4.03, 95% CI 1.97 to 6.09), relative to low-poverty/low-minority areas.ConclusionsIn addition to targeting disproportionate fast-food availability in disadvantaged dense urban areas, our findings suggest that policies should also target disparities in grocery/supermarket and fast-food restaurant availability in low-density areas.Article summaryArticle focusUsing national data, we examined whether neighbourhood food resource availability exhibits joint race and socioeconomic inequities across levels of urbanicity.Key messagesSocio-demographic inequities in neighbourhood food resource availability were most pronounced in low-density urban (largely suburban) areas.In high-density urban areas, higher neighbourhood poverty was associated with greater availability of all food resources.Whereas policy has focused on dense urban settings, less urban areas might also benefit from policies addressing food access.Strengths and limitations of this studyWhile business records provide comparable data across the USA, these data may contain error and do not indicate availability of specific foods.National coverage enabled examination of the joint role of neighbourhood race and socioeconomic status across urban strata within a single study

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

<p>Abstract</p> <p>Background</p> <p>The joint impact of sedentary behavior and physical activity on obesity has not been assessed in a large cohort followed from adolescence to adulthood.</p> <p>Methods</p> <p>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 ≥ 30).</p> <p>Results</p> <p>In males, adjusted odds of prevalent obesity was strongly predicted by MVPA bouts [OR (95% CI): OR_{6 vs. 1 MVPA bouts}= 0.50 (0.40, 0.62); OR_{4 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): OR_{6 vs. 1 MVPA bouts}= 0.67 (0.49, 0.91); OR_{4 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): OR_{4 vs. 40 hrs}= 0.58 (0.43, 0.80)] than males [OR (95% CI): OR_{4 vs. 40 hrs}= 0.78 (0.61, 0.99)]. Longitudinal activity patterns were not predictive of incident obesity.</p> <p>Conclusion</p> <p>Reducing screen time during adolescence and into adulthood may be a promising strategy for reducing obesity incidence, especially in females.</p

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

<p>Abstract</p> <p>Background</p> <p>The joint impact of sedentary behavior and physical activity on obesity has not been assessed in a large cohort followed from adolescence to adulthood.</p> <p>Methods</p> <p>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 ≥ 30).</p> <p>Results</p> <p>In males, adjusted odds of prevalent obesity was strongly predicted by MVPA bouts [OR (95% CI): OR_{6 vs. 1 MVPA bouts}= 0.50 (0.40, 0.62); OR_{4 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): OR_{6 vs. 1 MVPA bouts}= 0.67 (0.49, 0.91); OR_{4 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): OR_{4 vs. 40 hrs}= 0.58 (0.43, 0.80)] than males [OR (95% CI): OR_{4 vs. 40 hrs}= 0.78 (0.61, 0.99)]. Longitudinal activity patterns were not predictive of incident obesity.</p> <p>Conclusion</p> <p>Reducing screen time during adolescence and into adulthood may be a promising strategy for reducing obesity incidence, especially in females.</p

Residential self-selection bias in the estimation of built environment effects on physical activity between adolescence and young adulthood

Abstract Background Built environment research is dominated by cross-sectional designs, which are particularly vulnerable to residential self-selection bias resulting from health-related attitudes, neighborhood preferences, or other unmeasured characteristics related to both neighborhood choice and health-related outcomes. Methods We used cohort data from the National Longitudinal Study of Adolescent Health (United States; Wave I, 1994-95; Wave III, 2001-02; n = 12,701) and a time-varying geographic information system. Longitudinal relationships between moderate to vigorous physical activity (MVPA) bouts and built and socioeconomic environment measures (landcover diversity, pay and public physical activity facilities per 10,000 population, street connectivity, median household income, and crime rate) from adolescence to young adulthood were estimated using random effects models (biased by unmeasured confounders) and fixed effects models (within-person estimator, which adjusts for unmeasured confounders that are stable over time). Results Random effects models yielded null associations except for negative crime-MVPA associations [coefficient (95% CI): -0.056 (-0.083, -0.029) in males, -0.061 (-0.090, -0.033) in females]. After controlling for measured and time invariant unmeasured characteristics using within-person estimators, MVPA was higher with greater physical activity pay facilities in males [coefficient (95% CI): 0.024 (0.006, 0.042)], and lower with higher crime rates in males [coefficient (95% CI): -0.107 (-0.140, -0.075)] and females [coefficient (95% CI): -0.046 (-0.083, -0.009)]. Other associations were null or in the counter-intuitive direction. Conclusions Comparison of within-person estimates to estimates unadjusted for unmeasured characteristics suggest that residential self-selection can bias associations toward the null, as opposed to its typical characterization as a positive confounder. Differential environment-MVPA associations by residential relocation suggest that studies examining changes following residential relocation may be vulnerable to selection bias. The authors discuss complexities of adjusting for residential self-selection and residential relocation, particularly during the adolescent to young adult transition