Fig. 6: PpgAge gap associates with behavior.

PpgAge gap (adjusted) stratified by self-reported smoking status and chronological age for A male and B female participants. Results in both subpopulations are consistent with a dose-response effect—never smokers (n = 58,025) appear younger than former smokers (n = 25,644), who appear younger than occasional smokers (n = 2453), who appear younger than daily smokers (n = 4190). In both populations, results are also consistent with an exposure effect—i.e., the gap between daily smokers and never smokers is small in the youngest population, but grows to be about 3–4 years in the [55,65) year old groups. PpgAge gap stratified by C male (n = 98,986) and D female (n = 54,256) participants, stratified by exercise minutes. Among men, the age gap is largest for the lowest exercise minutes quintile, i.e., the least active individuals, and the difference between the lowest and the remaining quintiles grows with age, consistent with an exposure effect. The ranking of the average age gap is consistent with increasing amounts of exercise minutes. Among women, a similar effect can be observed, although the uncertainty is slightly larger due to a smaller sample size. (See quintile cutoffs in Table S1.) E, F PpgAge gap by REM latency quintile for male (n = 56,802) and female (n = 32,769) participants, respectively. An increased REM latency is associated with an elevated PpgAge gap across all age categories. See Fig. S10 for analysis of total sleep duration, deep sleep duration, and sleep efficiency. All intervals are 95% confidence intervals about the mean from 1000 bootstrap replicates.