{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:06:41Z","timestamp":1782846401149,"version":"3.54.5"},"reference-count":49,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Mhealth Uhealth"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Being overweight and obese are major health concerns worldwide, contributing to lifestyle-related diseases such as hypertension, dyslipidemia, type 2 diabetes, and cardiovascular disease. Increasing physical activity is an effective strategy for weight management. However, earlier step count studies have remained limited to small populations, short-term measurements of 1\u20102 weeks, and mainly cross-sectional comparisons of average step counts. The effects of long-term step count changes on weight loss remain unclear.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study was conducted to assess the effects of long-term patterns of step counts on weight loss using data from the \u201cAsmile\u201d mobile health app in Japan. We hypothesized that participants with continuously increasing step counts over time would have a higher likelihood of significant weight reduction than participants who show steady or fluctuating patterns, even if their average step counts were similar.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n We analyzed data of 2778 Asmile users aged 40\u201074 years with BMI \u226525 kg\/m\u00b2 who underwent a specific health checkup during fiscal years 2019\u20102023 and who had valid step count records for 10\u201014 months. Step count trajectories, reflecting long-term trends in physical activity, were classified using a latent class mixed model into four patterns:\n UP<\/jats:italic>\n (increasing),\n FLAT<\/jats:italic>\n (steady),\n DOWN<\/jats:italic>\n (decreasing), and\n UP\/DOWN<\/jats:italic>\n (increasing then decreasing). Logistic regression was applied to estimate odds ratios for achieving \u22653% weight loss, with step trajectory as the explanatory variable and weight loss as the outcome.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Among participants, 1601 (57.6%) were men and 1177 (42.4%) were women, with respective mean ages of 65.8 (SD 7.9) and 64 (SD 8.2) years. Step count trajectories were distributed as 28.5%\n UP<\/jats:italic>\n , 36.2%\n FLAT<\/jats:italic>\n , 20.1%\n DOWN<\/jats:italic>\n , and 15.2%\n UP\/DOWN<\/jats:italic>\n . Compared with the\n FLAT<\/jats:italic>\n group, participants in the\n UP<\/jats:italic>\n group had a significantly higher likelihood of achieving \u22653% weight loss (adjusted odds ratio 2.45, 95% CI 1.78\u20103.38).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Long-term tracking of step counts using the Asmile app revealed distinct activity patterns. Continuous increases in step counts were associated with the greatest likelihood of weight loss, emphasizing the importance of sustained physical activity. These findings support the use of long-term step monitoring to guide interventions for obesity and lifestyle-related disease prevention.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/80339","type":"journal-article","created":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T00:40:07Z","timestamp":1774572007000},"page":"e80339-e80339","source":"Crossref","is-referenced-by-count":0,"title":["One-Year Trajectory of Step Counts and Weight Loss in Adults With Overweight\/Obesity: Retrospective Cohort Study"],"prefix":"10.2196","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-0558-4500","authenticated-orcid":false,"given":"Kenshiro","family":"Taguchi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6584-5958","authenticated-orcid":false,"given":"Asuka","family":"Oyama","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5233-6003","authenticated-orcid":false,"given":"Jun'ichi","family":"Kotoku","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1332-8286","authenticated-orcid":false,"given":"Hiroshi","family":"Toki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2610-9824","authenticated-orcid":false,"given":"Ryohei","family":"Yamamoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,5,4]]},"reference":[{"issue":"1","key":"R1","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1093\/epirev\/mxm001","article-title":"Socioeconomic status and obesity","volume":"29","author":"McLaren","journal-title":"Epidemiol Rev"},{"issue":"1","key":"R2","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1038\/nrendo.2012.199","article-title":"Global obesity: trends, risk factors and policy implications","volume":"9","author":"Malik","journal-title":"Nat Rev Endocrinol"},{"issue":"6778","key":"R3","doi-asserted-by":"publisher","first-page":"635","DOI":"10.1038\/35007508","article-title":"Obesity as a medical problem","volume":"404","author":"Kopelman","journal-title":"Nature New Biol"},{"key":"R4","unstructured":"Obesity and overweight. 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