Built and Social Environments

Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota 55455-1015, USA.
American Journal of Preventive Medicine (Impact Factor: 4.53). 09/2006; 31(2):109-17. DOI: 10.1016/j.amepre.2006.03.026
Source: PubMed


Little is known about the patterning of neighborhood characteristics, beyond the basic urban, rural, suburban trichotomy, and its impact on physical activity (PA) and overweight.
Nationally representative data (National Longitudinal Study of Adolescent Health, 1994-1995, n = 20,745) were collected. Weight, height, PA, and sedentary behavior were self-reported. Using diverse measures of the participants' residential neighborhoods (e.g., socioeconomic status, crime, road type, street connectivity, PA recreation facilities), cluster analyses identified homogeneous groups of adolescents sharing neighborhood characteristics. Poisson regression predicted relative risk (RR) of being physically active (five or more bouts/week of moderate to vigorous PA) and overweight (body mass index equal or greater than the 95th percentile, Centers for Disease Control and Prevention/National Center for Health Statistics growth curves).
Six robust neighborhood patterns were identified: (1) rural working class; (2) exurban; (3) newer suburban; (4) upper-middle class, older suburban; (5) mixed-race urban; and (6) low-socioeconomic-status (SES) inner-city areas. Compared to adolescents living in newer suburbs, those in rural working-class (adjusted RR[ARR] = 1.38, 95% confidence interval [CI] = 1.13-1.69), exurban (ARR = 1.30, CI = 1.04-1.64), and mixed-race urban (ARR = 1.31, CI = 1.05-1.64) neighborhoods were more likely to be overweight, independent of individual SES, age, and race/ethnicity. Adolescents living in older suburban areas were more likely to be physically active than residents of newer suburbs (ARR = 1.11, CI = 1.04-1.18). Those living in low-SES inner-city neighborhoods were more likely to be active, though not significantly so, compared to mixed-race urban residents (ARR = 1.09, CI = 1.00-1.18).
These findings demonstrate disadvantageous associations between specific rural and urban environments and behavior, illustrating important effects of the neighborhood on health and the inherent complexity of assessing residential landscapes across the United States. Simple classical urban-suburban-rural measures mask these important complexities.

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    • "Most of these studies have been of adults and few studies have focused on children or adolescents specifically. Further, most studies of children and adolescents have been cross-sectional (e.g., Chen & Paterson, 2006; Janssen et al., 2006; Nelson et al., 2006), with only a few having a longitudinal design (Burdette & Needham, 2012; Nicholson & Browning, 2012). "
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    ABSTRACT: Although many studies have examined the relationship of adiposity with neighborhood socioeconomic context in adults, few studies have investigated this relationship during adolescence. Using 10-year annual measurements of body mass index, expressed as z-scores (BMIz), obtained from 775 black and white participants of the National Heart, Lung, and Blood Institute Growth and Health Study, a prospective cohort study of girls from pre- to postadolescence, we used multilevel modeling to investigate whether family socioeconomic status (SES) and neighborhood socioeconomic characteristics (measured by census-tract median family income) explain variation in BMIz trajectory parameters. Analyses controlled for pubertal maturation. We found that lower SES was associated with higher overall levels of BMIz for both white and black girls. Additionally, lower-SES black girls had a more sustained increase in BMIz during early adolescence and reached a higher peak compared to higher-SES black girls and to white girls. Neighborhood income was associated with BMIz trajectory for black girls only. Unexpectedly, among black girls, living in higher-income neighborhoods was associated with higher overall levels of BMIz, controlling for SES. Our findings suggest that neighborhood socioeconomic characteristics may affect adolescent BMIz trajectories differently in different racial/ethnic groups.
    Full-text · Article · Apr 2015
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    • "There are two dominant approaches to creating these measures of the built environment (Fig. 1). Radial, or Euclidean, buffers are created by drawing a straight line out a given distance from a home address creating a circle that is used to define the built environment (Berke et al., 2007, Rutt and Coleman, 2005, Nelson et al., 2006). While radial buffers may theoretically be more representative of the built environment that may influence behavior compared to administrative boundaries due to the issues outlined above, radial buffers may be less likely to represent the " true " relevant spatial context in areas with natural features such as bodies of water or built features such as railways or poorly connected roads. "
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    ABSTRACT: Uncertainty in the relevant spatial context may drive heterogeneity in findings on the built environment and energy balance. To estimate the effect of this uncertainty, we conducted a sensitivity analysis defining intersection and business densities and counts within different buffer sizes and shapes on associations with self-reported walking and body mass index. Linear regression results indicated that the scale and shape of buffers influenced study results and may partly explain the inconsistent findings in the built environment and energy balance literature.
    Full-text · Article · Mar 2014 · Health & Place
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    • "Researchers of child and adolescent obesity have mainly focused on individual factors such as gender, socio-economic position, physical activity, sedentary habits, nutrition and sleep duration [12,13,19]. Evidence also suggests that environmental and family factors influence adopted habits, particularly in children [14-16,20,21]. The neighborhood environment can include both physical aspects, which create opportunities or barriers for obesogenic behaviors, and social aspects of perceived safety or facility availability [22,23]. "
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    ABSTRACT: There is a growing worldwide trend of obesity in children. Identifying the causes and modifiable factors associated with child obesity is important in order to design effective public health strategies.Our objective was to provide empirical evidence of the association that some individual and environmental factors may have with child excess weight. A cross-sectional study was performed using multi-stage probability sampling of 978 Spanish children aged between 8 and 17 years, with objectively measured height and weight, along with other individual, family and neighborhood variables. Crude and adjusted odds ratios were calculated. In 2012, 4 in 10 children were either overweight or obese with a higher prevalence amongst males and in the 8-12 year age group. Child obesity was associated negatively with the socio-economic status of the adult responsible for the child's diet, OR 0.78 (CI95% 0.59-1.00), girls OR 0.75 (CI95% 0.57-0.99), older age of the child (0.41; CI95% 0.31-0.55), daily breakfast (OR 0.59; p = 0.028) and half an hour or more of physical activity every day. No association was found for neighborhood variables relating to perceived neighborhood quality and safety. This study identifies potential modifiable factors such as physical activity, daily breakfast and caregiver education as areas for public health policies. To be successful, an intervention should take into account both individual and family factors when designing prevention strategies to combat the worldwide epidemic of child excess weight.
    Full-text · Article · Jan 2014 · BMC Pediatrics
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