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American Journal of Preventive Medicine, April 2012
Brian E. Saelens, PhD brian.saelens at seattlechildrens.org , James F. Sallis, PhD, Lawrence D. Frank, PhD, Sarah C. Couch, PhD, RD, Chuan Zhou, PhD, Trina Colburn, PhD, Kelli L. Cain, MA, James Chapman, MSCE, Karen Glanz, PhD, MPH
From the Seattle Children's Research Institute (Saelens, Zhou, Colburn), the Department of Pediatrics (Saelens, Zhou), University of Washington, Urban Design 4 Health, Inc. (Chapman), Seattle, Washington; the Department of Family and Preventive Medicine, University of California San Diego (Sallis), the SDSU Research Foundation (Cain), San Diego State University, San Diego, California; the Department of Nutritional Sciences (Couch), University ofCincinnati, Cincinnati, Ohio; Department ofEpide-miology and Biostatistics (Glanz), Perelman School of Medicine, Department of Biobehavioral Health Sciences (Glanz), School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania; and the Schools of Environmental Health and Community and Regional Planning College for Interdisciplinary Studies (Frank), University of British Columbia, Vancouver, British Columbia, Canada
James Sallis was employed at San Diego State University when this research was completed.
Background: Identifying neighborhood environment attributes related to childhood obesity can inform environmental changes for obesity prevention.
Purpose: To evaluate child and parent weight status across neighborhoods in King County (Seattle metropolitan area) and San Diego County differing in GIS-defined physical activity environment (PAE) and nutrition environment (NE) characteristics.
Methods: Neighborhoods were selected to represent high (favorable) versus low (unfavorable) on the two measures, forming four neighborhood types (low on both measures, low PAE/high NE, high PAE/low NE, and high on both measures). Weight and height of children aged 6-11 years and one parent (n=730) from selected neighborhoods were assessed in 2007-2009. Differences in child and parent overweight and obesity by neighborhood type were examined, adjusting for neighborhood-, family-, and individual-level demographics.
Results: Children from neighborhoods high on both environment measures were
- less likely to be obese (7.7% vs 15.9%, OR=0.44,p=0.02) and
- marginally less likely to be overweight (23.7% vs 31.7%, OR=0.67, p=0.08)
than children from neighborhoods low on both measures. In models adjusted for parent weight status and demographic factors, neighborhood environment type remained related to child obesity (high vs low on both measures, OR=0.41, p<0.03). Parents in neighborhoods high on both measures (versus low on both) were marginally less likely to be obese (20.1% vs 27.7%, OR=0.66, p=0.08), although parent overweight did not differ by neighborhood environment. The lower odds of parent obesity in neighborhoods with environments supportive of physical activity and healthy eating remained in models adjusted for demographics (high vs low on the environment measures, OR=0.57, p=0.053).
- built environments that were more conducive to walking,
with a higher than median summed z-score value on
retail floor area ratio,
land-use mix, and
street connectivity for their respective county, and
- at least one high-quality park as assessed by the Environmental Assessment of Public Recreation Spaces tool
- below-region median summed z-score walkability and
- no park within the block group or a 0.25-mile buffer around it.
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Melanie M. Wall, PhD, Nicole I. Larson, PhD, MPH, RD, Ann Forsyth, PhD, David C. Van Riper, MA, Dan J. Graham, PhD, Mary T. Story, PhD, RD, Dianne Neumark-Sztainer, PhD, MPH, RD
(Am J Prev Med 2012;xx(x):xxx) © 2012 American Journal of Preventive Medicine
From the Department of Biostatistics (Wall), the Department of Psychiatry (Wall), Columbia University, New York, the Department of City and Regional Planning (Forsyth), Cornell University, Ithaca, New York; the Division of Epidemiology and Community Health (Larson, Graham, Story, Neumark-Sztainer), School of Public Health, Minnesota Population Center (Van Riper), University of Minnesota, Minneapolis, Minnesota
Address correspondence to: Melanie M. Wall, PhD, Division ofBiosta-tistics in the Department of Psychiatry and Department of Biostatistics in the Mailman School of Public Health, Columbia University, 1051 Riverside Dr., Unit 48, New York NY 10032. E-mail: mmw2177 at columbia.edu.
Background: Few studies have addressed the potential influence of neighborhood characteristics on adolescent obesity risk, and findings have been inconsistent.
Purpose: Identify patterns among neighborhood food, physical activity, street/transportation, and socioeconomic characteristics and examine their associations with adolescent weight status using three statistical approaches.
Methods: Anthropometric measures were taken on 2682 adolescents (53% female, mean age= 14.5 years) from 20 Minneapolis/St. Paul MN schools in 2009-2010. Neighborhood environmental variables were measured using GIS data and by survey. Gender-stratified regressions related to BMI z-scores and obesity to (1) separate neighborhood variables; (2) composites formed using factor analysis; and (3) clusters identified using spatial latent class analysis in 2012.
Results: Regressions on separate neighborhood variables found a low percentage of parks/recreation, and low perceived safety were associated with higher BMI z-scores in boys and girls. Factor analysis found five factors: away-from-home food and recreation accessibility, community disadvantage, green space, retail/transit density, and supermarket accessibility. The first two factors were associated with BMI z-score in girls but not in boys. Spatial latent class analysis identified six clusters with complex combinations of both positive and negative environmental influences. In boys, the cluster with highest obesity (29.8%) included low SES, parks/recreation, and safety; high restaurant and convenience store density; and nearby access to gyms, supermarkets, and many transit stops.
Conclusions: The mix of neighborhood-level barriers and facilitators of weight-related health behaviors leads to difficulties disentangling their associations with adolescent obesity; however, statistical approaches including factor and latent class analysis may provide useful means for addressing this complexity.
Extracted from PDF attached at bottom of this page
Probability of neighborhood characteristics and adolescent BMI for Park/recreation space (% of area)
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- Overview Obesity and Vitamin D
- All items in Obesity and vitamin D
- Obesity and diabetes reduced when move to better neighborhood – or better UV – Oct 2011
- Urban residents had 2X less vitamin D – 2008
- 4X more suburban UV than urban UV – Nov 2010
- All items in category Noontime sun and D 115 items April 2012
- An overview analysis of the time people spend outdoors – Dec 2010
- No – 10 minutes per day of sun-UVB is NOT enough
UNLESS white, young, thin, near the equator, and wear minimal clothes
- Obesity pandemic since 1975 - is it due to Vitamin D, Magnesium, Iodine, adenovirus, or what which has the following graph