Accelerometer Metrics: Healthy Adult Reference Values, Associations with Cardiorespiratory Fitness, and Clinical Implications
Accelerometer-assessed physical activity (PA) can be summarised using cut-point-free or population-specific cut-point-based outcomes. We aimed to: 1) examine the interrelationship between cut-point-free (intensity gradient [IG] and average acceleration [AvAcc]) and cut-point-based accelerometer metrics, 2) compare the association between cardiorespiratory fitness (CRF) and cut-point-free metrics to that with cut-point-based metrics in healthy adults aged 20 to 89 years and patients with heart failure, and 3) provide age-, sex-, and CRF-related reference values for healthy adults.
In the COmPLETE study, 463 healthy adults and 67 patients with heart failure wore GENEActiv accelerometers on their non-dominant wrist and underwent cardiopulmonary exercise testing. Cut-point-free (IG: distribution of intensity of activity across the day; AvAcc: proxy of volume of activity) and traditional (moderate-to-vigorous and vigorous activity) metrics were generated. The ‘interpretablePA’ R-package was developed to translate findings into clinical practice.
IG and AvAcc yield complementary information on PA with both IG (p = 0.009) and AvAcc (p < 0.001) independently associated with CRF in healthy individuals (adjusted R2 = 73.9%). Only IG was independently associated with CRF in patients with heart failure (p = 0.043, adjusted R2 = 38.4%). The best cut-point-free and cut-point-based model had similar predictive value for CRF in both cohorts. We produced age- and sex-specific reference values and percentile curves for IG, AvAcc, moderate-to-vigorous PA, and vigorous PA for healthy adults.
IG and AvAcc are strongly associated with CRF and, thus, indirectly with the risk of non-communicable diseases and mortality, in healthy adults and patients with heart failure. However, unlike cut-point-based metrics, IG and AvAcc are comparable across populations. Our reference values provide a healthy age- and sex-specific comparison that may enhance the translation and utility of cut-point-free metrics in clinical practice.
Author affiliationDiabetes Research Centre, University of Leicester
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