Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: No prior studies in children have evaluated how age may modify relationships of the built and social environments with BMI, nor evaluated the range of scales and contexts over which places may influence health.
Purpose: To systematically evaluate associations of 33 environmental measures in three domains (land use, physical activity, and social environments) with BMI in children and adolescents in five geographies.
Methods: A cross-sectional, multilevel analysis was completed in 2009-2010 of electronic health record data (2001-2008) from 47,769 children aged 5-18 years residing in a 31-county region of Pennsylvania. Associations of environmental measures with BMI were evaluated using 0.5-mile network buffers; census tracts; minor civil divisions (i.e., townships, boroughs, cities); a mixed definition of place (townships, boroughs, and census tracts in cities); and counties, overall and by age strata.
Results: Among all children, lower levels of community socioeconomic deprivation and greater diversity of physical activity establishments were associated with lower BMI. Associations of environmental measures differed by age, depending on scale and context. For example, higher population density was associated with lower BMI in older children; this effect was strongest in the larger geographies. Similarly, a lower level of county sprawl was associated with lower BMI in older children.
Conclusions: Associations differed by age and definition of place, suggesting that the benefits of environmental intervention may not be uniform across the childhood age range. The study demonstrated the utility of using electronic patient information for large-scale, population-based epidemiologic research, a research area of growing interest and investment in the U.S.
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http://dx.doi.org/10.1016/j.amepre.2011.06.038 | DOI Listing |
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