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Comparison of Five Expressions of Handgrip Strength for Predicting Cardiovascular Disease Risk Factors in Chinese Middle-Aged Community Residents

Authors :
Yanan Gao
Huiming Huang
Chunxia Ni
Yong Feng
Junwu Yu
Yutong Huang
Lijun Luo
Yongbao Jiang
Aiwen Wang
Source :
Frontiers in Public Health, Vol 10 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

ObjectiveTo compare the predictive performance of five handgrip strengths for cardiovascular disease (CVD) risk factors.MethodsA 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.ResultsHGS 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 p < 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.ConclusionsAlmost 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.

Details

Language :
English
ISSN :
22962565
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Frontiers in Public Health
Publication Type :
Academic Journal
Accession number :
edsdoj.174eed534fdf43e980b986de37a04032
Document Type :
article
Full Text :
https://doi.org/10.3389/fpubh.2022.903036