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
Purpose: To develop profiles of obesity risk behaviors for children and adolescents.
Design And Methods: Risk assessments were obtained from patients (n = 971) at a school-based health center. Latent class analysis was used to create subgroups based on seven indicators measuring diet, activity, and screen time.
Results: Four classes emerged, with 44% classified as the "Healthiest," 8% as the "Least Healthy," 37% as "Mixed Diet/Low Activity/Low Screen Time," and 11% as "Mixed Diet/High Activity/High Screen Time." Several demographic predictors distinguished the classes.
Practice Implications: Obesity risk factor profiles may help providers identify strengths and risks, tailor counseling, and plan interventions with families.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1111/jspn.12131 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!