Accuracy of Non-Exercise Estimated Cardiorespiratory Fitness in Japanese Adults.
Accuracy of Non-Exercise Estimated Cardiorespiratory Fitness in Japanese Adults.
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DOI：
10.3390/ijerph182312288
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发表时间：
2021-11-23
影响因子：
--
通讯作者：
Sawada SS
中科院分区：
文献类型：
--
作者：
Sloan RA;Scarzanella MV;Gando Y;Sawada SS
心肺适能（CRF）是发病率和死亡率的独立预测因子。在日本，每年在工作场所进行体检是强制性的，大多数医疗机构都有电子医疗记录（emr）。然而，在这两种情况下，通常无法确定CRF，从而限制了利用电子病历数据进行流行病学调查的潜力。目的：利用电子病历中常用的记录变量估计CRF （mL/kg/min）。方法：2004年，5293名日本成年人（11.7%为女性）在日本东京的一家大型燃气公司完成了年度体检。平均年龄48.3±8.0岁。估计的CRF （eCRF）基于年龄、测量的体重指数、静息心率、收缩压和舒张压以及吸烟。测量的CRF由次最大循环计力器分级运动试验确定。结果：采用回归模型计算男性和女性的Pearson相关系数和回归系数。采用最低的五分位数、四分位数和五分位数作为不适合的类别，对测量的CRF和eCRF进行交叉分类。男性eCRF的R值为0.61 (MD 4.41)，女性为0.64 （MD 4.22）。各模型的整体精度水平合理且一致，但考虑到正预测值和敏感性，不适合的下五分位数模型提供了最佳的整体模型。结论：eCRF可能提供了一种有用的方法，可以使用来自电子病历的数据或没有CRF或身体活动测量的数据集进行调查。
Cardiorespiratory fitness (CRF) is an independent predictor of morbidity and mortality. In Japan, annual physical exams are mandatory in workplace settings, and most healthcare settings have electronic medical records (EMRs). However, in both settings, CRF is not usually determined, thereby limiting the potential for epidemiological investigations using EMR data. PURPOSE: To estimate CRF (mL/kg/min) using variables commonly recorded in EMRs. METHODS: Participants were 5293 Japanese adults (11.7% women) who completed an annual physical exam at a large gas company in Tokyo, Japan, in 2004. The mean age was 48.3 ± 8.0 years. Estimated CRF (eCRF) was based on age, measured body mass index, resting heart rate, systolic and diastolic blood pressure, and smoking. Measured CRF was determined by a submaximal cycle ergometer graded exercise test. RESULTS: Regression models were used for males and females to calculate Pearson’s correlation and regression coefficients. Cross-classification of measured CRF and eCRF was conducted using the lowest quintile, quartile, and tertile as the unfit categories. R’s for eCRF were 0.61 (MD 4.41) for men and 0.64 (MD 4.22) for women. The overall accuracy level was reasonable and consistent across models, yet the unfit lower tertile model provided the best overall model when considering the positive predictive value and sensitivity. CONCLUSION: eCRF may provide a useful method for conducting investigations using data derived from EMRs or datasets devoid of CRF or physical activity measures.
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影响因子：
7.1
作者：
Shikany, James M.;Jacobs, David R., Jr.;Richman, Joshua S.
通讯作者：
Richman, Joshua S.
影响因子：
4.9
作者：
Hsieh, SD;Yoshinaga, H;Muto, T
通讯作者：
Muto, T
影响因子：
4.5
作者：
Matsuo, Tomoaki;So, Rina;Takahashi, Masaya
通讯作者：
Takahashi, Masaya
影响因子：
4.6
作者：
Sloan, Robert A.;Sawada, Susumu S.;Miyachi, Motohiko
通讯作者：
Miyachi, Motohiko
影响因子：
24
作者：
Artero, Enrique G.;Jackson, Andrew S.;Blair, Steven N.
通讯作者：
Blair, Steven N.