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: 3122
Function: getPubMedXML
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
Locational data, logged on portable GPS units and matched with accelerometer data, was used to examine associations of the built environment with physical activity and sedentary behaviors of adolescent females. In a sample of 293 adolescent females aged 15 to 18 years old in Minneapolis and San Diego, the built environment around each GPS point and its corresponding sedentary, light, and moderate-to-vigorous intensity physical activity was examined using random intercept multinomial logistic regression models. The odds of higher physical activity intensity (3-level outcome: sedentary, light, MVPA) were higher in places with parks, schools, and high population density, during weekdays, and lower in places with more roads and food outlets. Understanding the places where physical activity and sedentary behaviors occur appears to be a promising strategy to clarify relationships and inform policy aimed at increasing physical activity and reducing sedentary behaviors.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3259163 | PMC |
http://dx.doi.org/10.1016/j.healthplace.2011.08.020 | DOI Listing |
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