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Role of the physical fitness test in risk prediction of diabetes among municipal in-service personnel in Guangxi

机译:体质测试在广西市在职人员糖尿病风险预测中的作用

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摘要

To explore the relationship between risk prediction of diabetes mellitus (DM) and different physical fitness parameters in municipal in-service personnel in Guangxi.This was a cross-sectional study conducted in China from July 2015 to December 2016. We enrolled in-service adults (20–65 year of age) from public institutions. All subjects underwent National Physical Fitness Test (NPFT) and EZSCAN screening.The 5668 subjects were 42.9±12.3 years; 2984 (52.6%) were male; 3998 (70.5%), 1579 (27.9%) and 85 (1.6%) were Han, Zhuang, and other ethnicities, respectively. The multivariable analysis showed that systolic blood pressure (odds ratio [OR] = 1.013, 95% confidence interval [CI]: 1.003–1.022, P = .01), Harvard step test index (OR = 0.958, 95% CI: 0.941–0.976, P <.001), bend-ahead in sitting (OR = 0.945, 95% CI: 0.926–0.963, P <.001), hand grip strength (OR = 0.981, 95% CI: 0.966–0.997, P = .02), vertical jump height (OR = 0.969, 95% CI: 0.944–0.996, P = .02), time of single-leg standing with eyes closed (OR = 0.981, 95% CI: 0.968–0.995, P = .007), choice reaction time (OR = 2.103, 95% CI: 1.261–3.507, P = .004), and body composition minerals (OR = 1.649, 95% CI: 1.261–1.813, P < .001) were independently associated with DM. The resulting equation for the prediction of DM had an area under the receiver operating characteristic curve of 0.808, indicating good predictive ability.NPFT and EZSCAN could help predict the risk of diabetes and give early warnings to undertake preventive actions such as changing diet and performing physical activity.
机译:为了研究广西市在职人员的糖尿病风险预测与不同体质参数之间的关系。这是2015年7月至2016年12月在中国进行的一项横断面研究。我们纳入了在职成年人(20-65岁)来自公共机构。所有受试者均接受了美国国家体质测试(NPFT)和EZSCAN筛查。5668名受试者的年龄为42.9±12.3岁。男性2984(52.6%);汉族,壮族和其他族裔分别为3998(70.5%),1579(27.9%)和85(1.6%)。多变量分析显示,收缩压(比值[OR] = 1.013,95%置信区间[CI]:1.003-1.022,P = .01),哈佛大学步测指数(OR = 0.958,95%CI:0.941– 0.976,P <.001),坐姿向前弯曲(OR = 0.945,95%CI:0.926-0.963,P <.001),握力(OR = 0.981,95%CI:0.966-0.997,P = .02),垂直跳高(OR = 0.969,95%CI:0.944-0.996,P = .02),单腿站立时闭眼的时间(OR = 0.981,95%CI:0.968-0.995,P = .007),选择反应时间(OR = 2.103,95%CI:1.261–3.507,P = .004)和身体成分矿物质(OR = 1.649,95%CI:1.261–1.813,P <.001)独立与DM相关联。 DM的预测方程在接收器工作特性曲线下的面积为0.808,表明具有良好的预测能力.NPFT和EZSCAN可以帮助预测糖尿病的风险并给出预警,以采取预防措施,例如改变饮食和进行身体锻炼活动。

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