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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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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
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Objective: To compare the predictive performance of five handgrip strengths for cardiovascular disease (CVD) risk factors.
Methods: A total of 804 Chinese middle-aged community residents' health medical examinations were collected. The absolute handgrip strength was denoted as HGS. HGS/body weight (HGS/BW), HGS/body mass index (HGS/BMI), HGS/lean body mass (HGS/LBM), and HGS/muscle mass (HGS/MM) represented relative handgrip strength (RHGS). To assess predictive performance, receiver operating characteristic (ROC) curves and the area under the curve (AUC) were constructed.
Results: HGS was not associated with most CVD risk biomarkers; however, RHGS showed a negative correlation trend after controlling for covariates (sex, age, smoking, and exercise). HGS/BMI and HGS/BW had better AUCs for predicting CVD risk factors than HGS/LBM or HGS/MM. HGS/BMI and HGS/BW can successfully predict all CVD risk factors in men with AUCs 0.55-0.65; similarly, women may effectively predict arteriosclerosis, hyperglycemia, hyperuricemia, and metabolic syndrome with AUCs 0.59-0.64, all < 0.05. The optimal HGS/BW cut-off points for identifying different CVD risk factors were 0.59-0.61 in men and 0.41-0.45 in women, while the HGS/BMI were 1.75-1.79 in men and 1.11-1.15 in women.
Conclusions: Almost all CVD risk biomarkers and CVD risk factors were unrelated to HGS. There is, however, a significant inverse relationship between RHGS and CVD risk factors. HGS/BMI or HGS/BW should be recommended to be the best choice for predicting the risk of CVD risk factors in five expressions of handgrip strength. We also acquired the recommended optimal cut-off points of HGS/BMI and HGS/BW for predicting CVD risk factors.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9234447 | PMC |
http://dx.doi.org/10.3389/fpubh.2022.903036 | DOI Listing |
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