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This study leverages 19.1 million photoplethysmography readings from the Welltory app to investigate the relationship between resting heart rate and state-level material hardship across the U.S. The findings reveal a strong correlation (Spearman $\rho = +0.74$) between higher resting heart rates and greater socioeconomic hardship, even after controlling for various health and demographic factors. Notably, the gradient persists across multiple robustness checks, indicating that passive wearable technology can effectively capture socioeconomic disparities in health without direct user surveys.
Resting heart rate from wearable devices reveals a striking socioeconomic gradient, with users in high-hardship states averaging 1.33 bpm higher than those in low-hardship states.
Resting heart rate is an established marker of cardiovascular risk, but population-scale measurement has depended on clinical or survey instruments. We ask whether passively sensed consumer-wearable physiology recovers the socioeconomic gradient established in clinical cohorts. Using 19.1 million quality-filtered photoplethysmography readings from 18,734 opt-in users of the Welltory app, we computed cohort-adjusted mean daytime resting heart rate per US state and related it to a four-component state-level material-hardship composite (uninsurance, food insecurity, utility shutoff, housing insecurity; 41 states with module coverage, 12,497 contributing users). Adjusting for six state health and behaviour indicators, latitude, median age, and density, state resting heart rate tracked hardship at partial Spearman $\rho = +0.74$ (bootstrap 95\% CI $[+0.31, +0.87]$; $[+0.06, +0.79]$ under a conservative two-stage bootstrap that also resamples users within states). The gradient stayed positive under every check: leave-one-state-out ($+0.67$ to $+0.79$), demographic re-weighting, composition and census-region fixed effects ($+0.75$, $+0.78$), split-sample resampling (held-out median $+0.51$ to $+0.56$), and reduced variants such as a heavy-wear subsample ($+0.48$); residuals carry no detectable spatial autocorrelation. It was absent in two other metrics from the same panel and not matched by income or inequality under the same adjustment. Users in the five highest-hardship states averaged $+1.33$ bpm over those in the five lowest. Passive consumer-wearable physiology tracks, at the area level, a gradient previously established primarily in clinical and cohort studies, without surveying the users themselves. The composite was selected in exploratory analysis, after a pre-specified broader precarity index gave a weaker association ($+0.29$); the association is cross-sectional and ecological.
