{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:19:40Z","timestamp":1760059180385,"version":"build-2065373602"},"reference-count":63,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,5,26]],"date-time":"2025-05-26T00:00:00Z","timestamp":1748217600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Institute on Minority Health and Health Disparities of the National Institutes of Health","award":["R01MD018025"],"award-info":[{"award-number":["R01MD018025"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>High ambient temperature poses a significant public health challenge, particularly for low-income older adults (LOAs) with preexisting health and social issues and disproportionate living conditions, placing them at a vulnerable condition of heat-related illnesses and associated public health risks. This study aims to utilize advanced statistical regression and machine learning methods to analyze complex relationships between elevated temperature, physical activity (PA), sociodemographic factors and fall incidents among LOAs. We collected data from a cohort of 304 LOAs aged 60 and above, living in free-living conditions in low-income communities in Central Florida, USA. Zero-inflated Poisson regression was employed to examine the linear relationships, which reflect the zero-abundant nature of fall incidents. Then, an advanced machine learning approach\u2014the mixed undirected graphical model (MUGM)\u2014was employed to further explore the intricate, nonlinear relationships among daily PA, daily temperature, and fall incidents. The findings suggest that more moderate-to-vigorous PA is significantly associated with fewer fall incidents (RR = 0.90, 95% CI: (0.816, 0.993), p=0.037), after adjusting for other variables. In contrast, elevated temperature is strongly linked to a greater risk of falls (RR = 1.733, 95% CI: (1.581, 1.901), p &lt; 0.0001), potentially reflecting seasonal influences. Although higher temperature increases fall events, this effect is mitigated among LOAs with increased sedentary behavior (p&lt;0.0001). Additionally, findings from the MUGM reinforce the intricate nature of falls. Fall counts were highly correlated with race and positively associated with temperature, highlighting the importance of tailoring fall prevention strategies to account for seasonal variations and health disparities, and promoting PA.<\/jats:p>","DOI":"10.3390\/info16060442","type":"journal-article","created":{"date-parts":[[2025,5,27]],"date-time":"2025-05-27T11:12:57Z","timestamp":1748344377000},"page":"442","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Effect of Elevated Temperature on Physical Activity and Falls in Low-Income Older Adults Using Zero-Inflated Poisson and Graphical Models"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-3414-2922","authenticated-orcid":false,"given":"Tho","family":"Nguyen","sequence":"first","affiliation":[{"name":"Department of Statistics and Data Science, University of Central Florida, Orlando, FL 32816, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4376-9536","authenticated-orcid":false,"given":"Dahee","family":"Kim","sequence":"additional","affiliation":[{"name":"College of Nursing, University of Central Florida, Orlando, FL 32826, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6434-1387","authenticated-orcid":false,"given":"Yingru","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Sociology, University of Central Florida, Orlando, FL 32816, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6773-7387","authenticated-orcid":false,"given":"Christopher T.","family":"Emrich","sequence":"additional","affiliation":[{"name":"National Center for Integrated Coastal Research, School of Public Administration, University of Central Florida, Orlando, FL 32816, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7255-6425","authenticated-orcid":false,"given":"Jennifer","family":"Crook","sequence":"additional","affiliation":[{"name":"College of Nursing, University of Central Florida, Orlando, FL 32826, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8506-5812","authenticated-orcid":false,"given":"Ladda","family":"Thiamwong","sequence":"additional","affiliation":[{"name":"College of Nursing, University of Central Florida, Orlando, FL 32826, USA"},{"name":"Disability, Aging and Technology Cluster, University of Central Florida, Orlando, FL 32816, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9769-8131","authenticated-orcid":false,"given":"Rui","family":"Xie","sequence":"additional","affiliation":[{"name":"Department of Statistics and Data Science, University of Central Florida, Orlando, FL 32816, USA"},{"name":"College of Nursing, University of Central Florida, Orlando, FL 32826, USA"},{"name":"Disability, Aging and Technology Cluster, University of Central Florida, Orlando, FL 32816, USA"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,26]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Gamble, J.L., Balbus, J., Berger, M., Bouye, K., Campbell, V., Chief, K., Conlon, K., Crimmins, A., Flanagan, B., and Gonzalez-Maddux, C. 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