County-level associations between passively collected walking and bicycling and self-reported nonoccupational physical activity data.

Passively collected location-based services data on walking and bicycling trips could potentially complement traditional public health surveillance systems as related but distinct sources for physical activity data. Starting with a sample of 298 counties, we explored county-level associations between 2019 StreetLight location-based services measures and 2017 and 2019 Behavioral Risk Factor Surveillance System self-reported nonoccupational physical activity measures using Spearman's rank correlation coefficients (rho), following Cohen's interpretation (low: < 0.3; moderate: 0.3 to <0.5; strong: ≥ 0.5). Then, we explored stratified associations for the two strongest correlated StreetLight-Behavioral Risk Factor Surveillance System pairs of measures to understand how these associations differed by county characteristics. Of 72 StreetLight-Behavioral Risk Factor Surveillance System measure combinations, 4 pairs were moderately correlated (rho 0.3 to <0.5). The remaining pairs had low correlations (rho < 0.3). Select stratified measure pairs had strong correlations (rho ≥ 0.5) for medium and small metro counties and counties in the middle tertile of social vulnerability. Location-based services measures and Behavioral Risk Factor Surveillance System physical activity measures mostly showed limited convergent validity. The usefulness of location-based services data for representing nonoccupational physical activity may be context-sensitive to certain types of counties, where the constructs may have more in common.