Cross-level regional and socioeconomic inequalities in step counts: a descriptive epidemiological investigation of...

Although regional inequalities in physical activity are recognised as a global concern, nationwide evidence from device-based measurements is limited. Given the multilevel nature of inequality, we quantified step count disparities across municipalities and examined cross-level interactions between individual-level socioeconomic status (SES) and walkability.

We conducted municipality- and individual-level analyses using step count data from 1,542,536 smartphone users aged 20-64 years. We calculated municipality-level mean daily steps and Gini coefficients, and examined associations between mean daily steps, municipal walkability, and Gini coefficients. Linear mixed-effects models quantified cross-level interactions between individual SES (education, employment, and equivalised household income) and walkability (modelled as a continuous variable) on individual-level mean daily steps. Cross-level patterns were visualised across quintile-based walkability strata.

Municipality-level mean daily steps varied substantially across the 951 municipalities, with a maximum difference of 3724 steps/day (ranging from 4026 to 7750 steps/day, nearly a 2-fold disparity). Municipalities with higher mean daily steps had greater walkability (r = 0.76) and more equal step-count distributions (Gini coefficient; r = -0.79, stronger than simulated mathematical correlations). Significant cross-level interactions on individual-level mean daily steps were evident, with patterns differing across SES domains: step-count differences across walkability strata were prominent for education and income (623-762 steps/day), whereas employment status showed substantial differences between employed and non-employed individuals, reaching 826-1514 steps/day in highly walkable areas.

Substantial inequalities exist across and within municipalities, and individual-level disparities vary based on SES and walkability. Nationwide surveillance and cross-sectoral collaborations are needed to identify populations vulnerable to inactivity and implement targeted strategies.

Japan Society for the Promotion of Science and Japan Science and Technology Agency.