Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 143
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 143
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 209
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 994
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3134
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 574
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 488
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Objectives: To evaluate the association between percent body fat (%BF) and body mass index (BMI) among BMI-defined non-obese individuals between 40 and 69 years of age using a population-based Canadian sample.
Data And Methods: Cross-sectional data from the Canadian Health Measures Survey (2007 and 2009) was used to select all middle-aged individuals with BMI < 30 kg/m2 (n = 2,656). %BF was determined from anthropometric skinfolds and categorized according to sex-specific equations. Association of other anthropometry measures and metabolic markers were evaluated across different %BF categories. Significance of proportions was evaluated using chi-squared and Bonferroni-adjusted Wald test. Diagnostic performance measures of BMI-defined overweight categories compared to those defined by %BF were reported.
Results: The majority (69%) of the sample was %BF-defined overweight/obese, while 55% were BMI-defined overweight. BMI category was not concordant with %BF classification for 30% of the population. The greatest discordance between %BF and BMI was observed among %BF-defined overweight/obese women (32%). Sensitivity and specificity of BMI-defined overweight compared to %BF-defined overweight/obese were (58%, 94%) among females and (82%, 59%) among males respectively. According to the estimated negative predictive value, if an individual is categorized as BMI-defined non-obese, he/she has a 52% chance of being in the %BF-defined overweight/obese category.
Conclusion: Middle-aged individuals classified as normal by BMI may be overweight/obese based on measures of %BF. These individuals may be at risk for chronic diseases, but would not be identified as such based on their BMI classification. Quantifying %BF in this group could inform targeted strategies for disease prevention.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6972441 | PMC |
http://dx.doi.org/10.17269/cjph.107.5652 | DOI Listing |
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