The Predictive Performance of Objective Measures of #physical Activity Derived From Accelerometry Data for 5-Year All-Cause Mortality in #Older Adults: National Health and Nutritional Examination Survey 2003–2006

Declining physical activity (PA) is a hallmark of aging. Wearable technology provides reliable measures of the frequency, duration, intensity, and timing of PA..

In univariate logistic regression, the total activity count was the best predictor of 5-year mortality (Area under the Curve (AUC) = 0.771) followed by age (AUC = 0.758). Overall, 9 of the top 10 predictors were objective PA measures (AUC from 0.771 to 0.692). In multivariate regression, the 10-fold cross-validated AUC was 0.798 for the model without objective PA variables (9 predictors) and 0.838 for the forward selection model with objective PA variables (13 predictors). The Net Reclassification Index was substantially improved by adding objective PA variables (p < .001).

Conclusions
Objective accelerometry-derived PA measures outperform traditional predictors of 5-year mortality, including age. This highlights the importance of wearable technology for providing reproducible, unbiased, and prognostic biomarkers of health.

https://bit.ly/36RgDFC