Built-in Healthcare Applications Reveal Step Changes Associated with Temperature, Transportation, and Marital Status Among Urban Cities in Japan
This study investigated associations between daily step counts and temperature, transportation patterns, and marital status among 622 Japanese adults aged 40–79 from five urban cities, using retrospective time-series step data collected via built-in smartphone healthcare applications over a mean period of 2,344 days. Using seasonal-trend decomposition with LOESS, the authors report a high explanatory fit (R2 = 0.798) and fitted an absolute value relationship between temperature and the mean daily steps of the seasonal component. Train usage differed by area, with Saitama, Kawasaki, and Fukuoka showing higher ordinary train use than Kobe and Kyoto, and males with married/divorced-or-bereaved statuses had higher mean daily step counts than females, while unmarried differences were small. The paper’s main limitation is that it is observational, relies on de-identified smartphone step data without mechanistic explanation for causality, and focuses on specific Japanese cities and time periods. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.
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