{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:54:07Z","timestamp":1790816047848,"version":"4.1.0"},"reference-count":47,"publisher":"American Chemical Society (ACS)","issue":"2","license":[{"start":{"date-parts":[[2017,12,29]],"date-time":"2017-12-29T00:00:00Z","timestamp":1514505600000},"content-version":"vor","delay-in-days":885,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,2,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Extreme heat is a public health challenge. The scarcity of directly comparable studies on the association of heat with morbidity and mortality and the inconsistent identification of threshold temperatures for severe impacts hampers the development of comprehensive strategies aimed at reducing adverse heat-health events.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>This quantitative study was designed to link temperature with mortality and morbidity events in Maricopa County, Arizona, USA, with a focus on the summer season.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using Poisson regression models that controlled for temporal confounders, we assessed daily temperature\u2013health associations for a suite of mortality and morbidity events, diagnoses, and temperature metrics. Minimum risk temperatures, increasing risk temperatures, and excess risk temperatures were statistically identified to represent different \u201ctrigger points\u201d at which heat-health intervention measures might be activated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We found significant and consistent associations of high environmental temperature with all-cause mortality, cardiovascular mortality, heat-related mortality, and mortality resulting from conditions that are consequences of heat and dehydration. Hospitalizations and emergency department visits due to heat-related conditions and conditions associated with consequences of heat and dehydration were also strongly associated with high temperatures, and there were several times more of those events than there were deaths. For each temperature metric, we observed large contrasts in trigger points (up to 22\u00b0C) across multiple health events and diagnoses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Consideration of multiple health events and diagnoses together with a comprehensive approach to identifying threshold temperatures revealed large differences in trigger points for possible interventions related to heat. Providing an array of heat trigger points applicable for different end-users may improve the public health response to a problem that is projected to worsen in the coming decades.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Citation<\/jats:title>\n                    <jats:p>Petitti DB, Hondula DM, Yang S, Harlan SL, Chowell G. 2016. Multiple trigger points for quantifying heat-health impacts: new evidence from a hot climate. Environ Health Perspect 124:176\u2013183;\u2002http:\/\/dx.doi.org\/10.1289\/ehp.1409119<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1289\/ehp.1409119","type":"journal-article","created":{"date-parts":[[2015,7,28]],"date-time":"2015-07-28T12:25:54Z","timestamp":1438086354000},"page":"176-183","source":"Crossref","is-referenced-by-count":99,"title":["Multiple Trigger Points for Quantifying Heat-Health Impacts: New Evidence from a Hot Climate"],"prefix":"10.1021","volume":"124","author":[{"given":"Diana B.","family":"Petitti","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, and"},{"name":"Department of Family, Community and Preventive Medicine, College of Medicine-Phoenix, University of Arizona, Phoenix, Arizona, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David M.","family":"Hondula","sequence":"additional","affiliation":[{"name":"Center for Policy Informatics, Arizona State University, Phoenix, Arizona, USA"},{"name":"School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, Arizona, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuo","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Human Evolution & Social Change, Arizona State University, Tempe, Arizona, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sharon L.","family":"Harlan","sequence":"additional","affiliation":[{"name":"School of Human Evolution & Social Change, Arizona State University, Tempe, Arizona, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gerardo","family":"Chowell","sequence":"additional","affiliation":[{"name":"School of Human Evolution & Social Change, Arizona State University, Tempe, Arizona, USA"},{"name":"School of Public Health, Georgia State University, Atlanta, Georgia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2015,7,28]]},"reference":[{"key":"2026080607050645800_micit1","unstructured":"Agency for Healthcare Research and Quality (AHRQ)\n          \n          Healthcare Cost and Utilization Project (HCUP). 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