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
Objective: To evaluate the relationship between waist to stature ratio (WSR) and hypertension, diabetes, dyslipidemia in Qingdao.
Methods: Data were collected from a 2001 - 2007 Qingdao area diabetes survey, population-based cross-sectional study, and 30 712 Chinese adults aged>18 years old were enrolled. Correlation analysis of BMI, WSR, hip circumference, waist circumference, waist to hip ratio (WHR) with blood glucose, blood pressure, blood lipid were conducted. ROC curve analysis in diabetes, hypertension, dyslipidemia and multivariate logistic regression analysis were also conducted.
Results: Anthropometric indicators were related with hypertension, diabetes and dyslipidemia in both men and women. Comparing with other anthropometric indicators, WSR was found to have the largest area under the ROC curve and the best cut-off point of WSR was 0.52. Multivariate logistic regression analysis showed that, after controlling age, disease history, physical activity, sex, the diabetes hypertension and dyslipidemia risk OR of WSR ≥ 0.52 were largest.
Conclusions: Anthropometric indicators intimately related with cardiovascular risk factors in Qingdao region, and may predict and evaluate the risk of cardiovascular disease. WSR may be the best index for predicting cardiovascular risk factors in Qingdao area. The optimal WSR cut off point for identifying cardiovascular risk factors clustering is 0.52.
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