Physical activity phenotypes from volume-based versus intensity-based wearable metrics: discordant classification and divergent metabolomic, body composition, and cardiac magnetic resonance associations

Background Consumer wearables report direct volume-based metrics (steps, distance, floors climbed) alongside device-derived metrics generated by manufacturer algorithms (activity-intensity minutes, energy expenditure). Both are widely used to characterize individuals into activity phenotypes, yet whether these representations yield concordant activity phenotypes and biological associations is unclear. Objective To compare activity phenotypes derived from direct accelerometry with those derived from device-derived intensity metrics, and to evaluate each against metabolomic, body composition, and cardiac magnetic resonance (CMR) phenotypes. Methods Using the SingHEART cohort, two hierarchical cluster analyses using Ward linkage yielded five phenotypes each for volume-based and intensity-based metrics. Agreement was quantified by the adjusted Rand index. For analyses, the two high-variability phenotypes were combined, giving four groups: sedentary, average movers, regular exercisers, and high-variability movers. Serum ¹H-NMR metabolomics was analyzed by PERMANOVA with Holm adjustment across pairwise contrasts. Body and CMR associations were assessed using linear regression with false discovery rate correction. Results In total, 984 adults (mean age 45.6 years, 48.3% male) wore accelerometers for a mean of 7.1 valid days. The two classifications agreed poorly: adjusted Rand index was 0.18, with only 46.2% assigned identically. Volume-based phenotypes differed in metabolomic profiles ( P < .001). Active participants (high-variability movers plus regular exercisers) differed from sedentary participants across 106 of 250 biomarkers (FDR q < 0.05), including higher HDL, lower VLDL, LDL and lower GlycA. Conversely, although intensity-based phenotypes showed a nominally significant omnibus metabolomic association ( P = .003), no metabolomic difference was observed between active and sedentary groups defined by intensity-based phenotyping ( P = .29). Across 16 body composition and CMR outcomes, volume-based phenotypes were associated with 11 and intensity-based phenotypes with 6, in divergent directions: volume-based high-variability movers showed lower body fat, higher skeletal muscle, and larger ventricular volumes and mass, whereas intensity-based high-variability movers showed higher body mass index and waist circumference. Conclusions Volume-based metrics and intensity-based metrics assign the same individuals to discordant activity phenotypes. Volume-based phenotypes showed more consistent associations across metabolomic, body composition, and cardiac imaging measures. These findings suggest that the choice of wearable-derived metrics substantially influences digital activity phenotyping and its biological interpretation.