Spatiotemporal analysis of heat and heat wave effects on elderly mortality in Texas, 2006-2011

Lung Chang Chien, Yuming Guo, Kai Zhang

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)

Abstract

Background: Heat and heat waves have been linked to the increased risk of deaths, hospital admissions, and emergency visits. Objectives: This study presents a spatiotemporal analysis of heat and heat wave effects on elderly mortality (≥65 years) in Texas. Methods: We compiled a six-year daily weather and mortality counts dataset from 254 counties in Texas during 2006-2011. Heat index (HI), a combination of temperature and relative humidity, was used as the exposure metric in this study. Associations between daily all-cause elderly mortality and daily maximum HI and heat waves (≥2 days of county-specific daily maximum HI > 95th percentiles) were examined using a quasi-Poisson regression. A Markov random field smoother was included in the model to account for spatial autocorrelations and spatial heterogeneity. The model also controlled for long-term trend and seasonality in mortality, and the effects of day of the week. Discussion: On average, the lag effect of heat on elderly mortality risk lasted up to 10 days, and the cumulative heat effects started to increase rapidly when daily maximum HI exceeded the 90th percentile in Texas. Elderly living in Northwest Texas and parts of West Texas were at greater risk of elderly mortality attributable to heat waves, and the highest relative risk for elderly mortality occurred in El Paso County (4.70, 95% Confidence Interval = 4.33, 5.10). Conclusions: Our study indicates strong geographical variations of heat wave effects on elderly mortality risk in Texas.

Original languageEnglish
Pages (from-to)845-851
Number of pages7
JournalScience of the Total Environment
Volume562
DOIs
Publication statusPublished - 15 Aug 2016
Externally publishedYes

Keywords

  • Distributed lagged nonlinear model
  • Heat index
  • Mortality
  • Spatial heterogeneity

Cite this

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title = "Spatiotemporal analysis of heat and heat wave effects on elderly mortality in Texas, 2006-2011",
abstract = "Background: Heat and heat waves have been linked to the increased risk of deaths, hospital admissions, and emergency visits. Objectives: This study presents a spatiotemporal analysis of heat and heat wave effects on elderly mortality (≥65 years) in Texas. Methods: We compiled a six-year daily weather and mortality counts dataset from 254 counties in Texas during 2006-2011. Heat index (HI), a combination of temperature and relative humidity, was used as the exposure metric in this study. Associations between daily all-cause elderly mortality and daily maximum HI and heat waves (≥2 days of county-specific daily maximum HI > 95th percentiles) were examined using a quasi-Poisson regression. A Markov random field smoother was included in the model to account for spatial autocorrelations and spatial heterogeneity. The model also controlled for long-term trend and seasonality in mortality, and the effects of day of the week. Discussion: On average, the lag effect of heat on elderly mortality risk lasted up to 10 days, and the cumulative heat effects started to increase rapidly when daily maximum HI exceeded the 90th percentile in Texas. Elderly living in Northwest Texas and parts of West Texas were at greater risk of elderly mortality attributable to heat waves, and the highest relative risk for elderly mortality occurred in El Paso County (4.70, 95{\%} Confidence Interval = 4.33, 5.10). Conclusions: Our study indicates strong geographical variations of heat wave effects on elderly mortality risk in Texas.",
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Spatiotemporal analysis of heat and heat wave effects on elderly mortality in Texas, 2006-2011. / Chien, Lung Chang; Guo, Yuming; Zhang, Kai.

In: Science of the Total Environment, Vol. 562, 15.08.2016, p. 845-851.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

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N2 - Background: Heat and heat waves have been linked to the increased risk of deaths, hospital admissions, and emergency visits. Objectives: This study presents a spatiotemporal analysis of heat and heat wave effects on elderly mortality (≥65 years) in Texas. Methods: We compiled a six-year daily weather and mortality counts dataset from 254 counties in Texas during 2006-2011. Heat index (HI), a combination of temperature and relative humidity, was used as the exposure metric in this study. Associations between daily all-cause elderly mortality and daily maximum HI and heat waves (≥2 days of county-specific daily maximum HI > 95th percentiles) were examined using a quasi-Poisson regression. A Markov random field smoother was included in the model to account for spatial autocorrelations and spatial heterogeneity. The model also controlled for long-term trend and seasonality in mortality, and the effects of day of the week. Discussion: On average, the lag effect of heat on elderly mortality risk lasted up to 10 days, and the cumulative heat effects started to increase rapidly when daily maximum HI exceeded the 90th percentile in Texas. Elderly living in Northwest Texas and parts of West Texas were at greater risk of elderly mortality attributable to heat waves, and the highest relative risk for elderly mortality occurred in El Paso County (4.70, 95% Confidence Interval = 4.33, 5.10). Conclusions: Our study indicates strong geographical variations of heat wave effects on elderly mortality risk in Texas.

AB - Background: Heat and heat waves have been linked to the increased risk of deaths, hospital admissions, and emergency visits. Objectives: This study presents a spatiotemporal analysis of heat and heat wave effects on elderly mortality (≥65 years) in Texas. Methods: We compiled a six-year daily weather and mortality counts dataset from 254 counties in Texas during 2006-2011. Heat index (HI), a combination of temperature and relative humidity, was used as the exposure metric in this study. Associations between daily all-cause elderly mortality and daily maximum HI and heat waves (≥2 days of county-specific daily maximum HI > 95th percentiles) were examined using a quasi-Poisson regression. A Markov random field smoother was included in the model to account for spatial autocorrelations and spatial heterogeneity. The model also controlled for long-term trend and seasonality in mortality, and the effects of day of the week. Discussion: On average, the lag effect of heat on elderly mortality risk lasted up to 10 days, and the cumulative heat effects started to increase rapidly when daily maximum HI exceeded the 90th percentile in Texas. Elderly living in Northwest Texas and parts of West Texas were at greater risk of elderly mortality attributable to heat waves, and the highest relative risk for elderly mortality occurred in El Paso County (4.70, 95% Confidence Interval = 4.33, 5.10). Conclusions: Our study indicates strong geographical variations of heat wave effects on elderly mortality risk in Texas.

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