Accuracy of Non-Exercise Estimated Cardiorespiratory Fitness in Japanese Adults

Robert A. Sloan, Marco V. Scarzanella, Yuko Gando and Susumu S. Sawada
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Robert A. Sloan: Department of Social and Behavioral Medicine, Kagoshima University, Kagoshima 890-8520, Japan
Marco V. Scarzanella: Department of Science and Engineering, Kagoshima University, Kagoshima 890-0065, Japan
Yuko Gando: Department of Sport Science, Surugadai University, Hannō 357-8555, Japan
Susumu S. Sawada: Department of Sport Sciences, Waseda University, Tokorozawa-shi 359-1192, Japan

IJERPH, 2021, vol. 18, issue 23, 1-7

Abstract: 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.

Keywords: estimated cardiorespiratory fitness; electronic medical records; epidemiology; public health (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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