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A new approach to estimate aerobic fitness using the NHANES dataset.
- Author(s): Lu, Kim D;
- Bar-Yoseph, Ronen;
- Radom-Aizik, Shlomit;
- Cooper, Dan M
- et al.
Published Web Locationhttps://doi.org/10.1111/sms.13461
IntroductionPhysical activity and fitness are essential for healthy growth in children. The National Health and Nutrition Examination Survey (NHANES) evaluated fitness by estimating V̇O2 max from submaximal measurements of heart rate (HR) during graded treadmill exercise. Our aims were (a) to examine how well NHANES methodology used to estimate V̇O2 max correlated with actual VO2 max and (b) to evaluate a novel fitness metric using actual data collected during exercise and its relationship to physical activity and sedentary time, lipid profiles, and body composition.
MethodsFifty-three adolescents completed NHANES submaximal exercise protocol and maximal graded cardiopulmonary exercise testing. We used a novel approach to quantifying fitness (Δvelocity × incline × body mass (VIM)/ΔHR slopes) and evaluated its relationship to physical activity and sedentary time using NHANES data (n = 4498). In a subset (n = 740), we compared ΔVIM/ΔHR slopes to NHANES estimated V̇O2 max and examined their relationship to cardiovascular risk factors (BMI percentiles and lipid levels).
ResultsMeasured V̇O2 peak was moderately correlated with NHANES estimated V̇O2 max (r = 0.53, P < 0.01). Significantly higher ΔVIM/ΔHR slopes were associated with increased physical activity and decreased sedentary time. ΔVIM/ΔHR slopes were negatively associated with LDL, triglycerides, and BMI percentiles (P < 0.01). In general, the two fitness models were similar; however, ΔVIM/ΔHR was more discriminating than NHANES in quantifying the relationship between fitness and LDL levels.
ConclusionWe found that the NHANES estimated V̇O2 max accounted for approximately 28% of the variability in the measured V̇O2 peak. Our approach to estimating fitness (ΔVIM/ΔHR slopes) using actual data provided similar relationships to lipid levels. We suggest that fitness measurements based on actually measured data may produce more accurate assessments of fitness and, ultimately, better approaches linking exercise to health in children.
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