TY - JOUR
T1 - Heat-attributable deaths between 1992 and 2009 in Seoul, South Korea
AU - Kim, Clara T
AU - Lim, Youn-Hee
AU - Woodward, Alistair
AU - Kim, Ho
PY - 2015/2/18
Y1 - 2015/2/18
N2 - BACKGROUND: Climate change may significantly affect human health. The possible effects of high ambient temperature must be better understood, particularly in terms of certain diseases' sensitivity to heat (as reflected in relative risks [RR]) and the consequent disease burden (number or fraction of cases attributable to high temperatures), in order to manage the threat.PURPOSE: This study investigated the number of deaths attributable to abnormally high ambient temperatures in Seoul, South Korea, for a wide range of diseases.METHOD: The relationship between mortality and daily maximum temperature using a generalized linear model was analyzed. The threshold temperature was defined as the 90th percentile of maximum daily temperatures. Deaths were classified according to ICD-10 codes, and for each disease, the RR and attributable fractions were determined. Using these fractions, the total number of deaths attributable to daily maximum temperatures above the threshold value, from 1992 to 2009, was calculated. Data analyses were conducted in 2012-2013.RESULTS: Heat-attributable deaths accounted for 3,177 of the 271,633 deaths from all causes. Neurological (RR 1.07; 95% CI, 1.04-1.11) and mental and behavioral disorders (RR 1.04; 95% CI, 1.01-1.07) had relatively high increases in the RR of mortality. The most heat-sensitive diseases (those with the highest RRs) were not the diseases that caused the largest number of deaths attributable to high temperatures.CONCLUSION: This study estimated RRs and deaths attributable to high ambient temperature for a wide variety of diseases. Prevention-related policies must account for both particular vulnerabilities (heat-sensitive diseases with high RRs) and the major causes of the heat mortality burden (common conditions less sensitive to high temperatures).
AB - BACKGROUND: Climate change may significantly affect human health. The possible effects of high ambient temperature must be better understood, particularly in terms of certain diseases' sensitivity to heat (as reflected in relative risks [RR]) and the consequent disease burden (number or fraction of cases attributable to high temperatures), in order to manage the threat.PURPOSE: This study investigated the number of deaths attributable to abnormally high ambient temperatures in Seoul, South Korea, for a wide range of diseases.METHOD: The relationship between mortality and daily maximum temperature using a generalized linear model was analyzed. The threshold temperature was defined as the 90th percentile of maximum daily temperatures. Deaths were classified according to ICD-10 codes, and for each disease, the RR and attributable fractions were determined. Using these fractions, the total number of deaths attributable to daily maximum temperatures above the threshold value, from 1992 to 2009, was calculated. Data analyses were conducted in 2012-2013.RESULTS: Heat-attributable deaths accounted for 3,177 of the 271,633 deaths from all causes. Neurological (RR 1.07; 95% CI, 1.04-1.11) and mental and behavioral disorders (RR 1.04; 95% CI, 1.01-1.07) had relatively high increases in the RR of mortality. The most heat-sensitive diseases (those with the highest RRs) were not the diseases that caused the largest number of deaths attributable to high temperatures.CONCLUSION: This study estimated RRs and deaths attributable to high ambient temperature for a wide variety of diseases. Prevention-related policies must account for both particular vulnerabilities (heat-sensitive diseases with high RRs) and the major causes of the heat mortality burden (common conditions less sensitive to high temperatures).
KW - Cause of Death
KW - Heat Stress Disorders/mortality
KW - Hot Temperature/adverse effects
KW - Humans
KW - Linear Models
KW - Mental Disorders/etiology
KW - Nervous System Diseases/etiology
KW - Republic of Korea/epidemiology
KW - Urban Population/statistics & numerical data
U2 - 10.1371/journal.pone.0118577
DO - 10.1371/journal.pone.0118577
M3 - Journal article
C2 - 25692296
SN - 1932-6203
VL - 10
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 2
M1 - e0118577
ER -