Added effect of heat wave on mortality in Seoul, Korea

Abstract A heat wave could increase mortality owing to high temperature. However, little is known about the added (duration) effect of heat wave from the prolonged period of high temperature on mortality and different effect sizes depending on the definition of heat waves and models. A distributed lag non-linear model with a quasi-Poisson distribution was used to evaluate the added effect of heat wave on mortality after adjusting for long-term and intra-seasonal trends and apparent temperature. We evaluated the cumulative relative risk of the added wave effect on mortality on lag days 0–30. The models were constructed using nine definitions of heat wave and two relationships (cubic spline and linear threshold model) between temperature and mortality to leave out the high temperature effect. Further, we performed sensitivity analysis to evaluate the changes in the effect of heat wave on mortality according to the different degrees of freedom for time trend and cubic spline of temperature. We found that heat wave had the added effect from the prolonged period of high temperature on mortality and it was considerable in the aspect of cumulative risk because of the lagged influence. When heat wave was defined with a threshold of 98th percentile temperature and ≥2, 3, and 4 consecutive days, mortality increased by 14.8 % (7.5–22.6, 95 % confidence interval (CI)), 18.1 % (10.8–26.0, 95 % CI), 18.1 % (10.7–25.9, 95 % CI), respectively, in cubic spline model. When it came to the definitions of 90th and 95th percentile, the risk increase in mortality declined to 3.7–5.8 % and 8.6–11.3 %, respectively. This effect was robust to the flexibility of the model for temperature and time trend, while the definitions of a heat wave were critical in estimating its relationship with mortality. This finding could help deepen our understanding and quantifying of the relationship between heat wave and mortality and select an appropriate definition of heat wave and temperature model in the future studies. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Lee, Won Kyung [verfasserIn] Lee, Hye Ah [verfasserIn] Lim, Youn Hee [verfasserIn] Park, Hyesook [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Schlagwörter:	Heat wave Mortality Temperature Weather

Übergeordnetes Werk:	Enthalten in: International journal of biometeorology - Berlin : Springer, 1959, 60(2015), 5 vom: 01. Okt., Seite 719-726
Übergeordnetes Werk:	volume:60 ; year:2015 ; number:5 ; day:01 ; month:10 ; pages:719-726

Links:	Volltext

DOI / URN:	10.1007/s00484-015-1067-x

Katalog-ID:	SPR006448984

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author_variant	w k l wk wkl h a l ha hal y h l yh yhl h p hp
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allfields	10.1007/s00484-015-1067-x doi (DE-627)SPR006448984 (SPR)s00484-015-1067-x-e DE-627 ger DE-627 rakwb eng 570 ASE 38.84 bkl 44.08 bkl Lee, Won Kyung verfasserin aut Added effect of heat wave on mortality in Seoul, Korea 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A heat wave could increase mortality owing to high temperature. However, little is known about the added (duration) effect of heat wave from the prolonged period of high temperature on mortality and different effect sizes depending on the definition of heat waves and models. A distributed lag non-linear model with a quasi-Poisson distribution was used to evaluate the added effect of heat wave on mortality after adjusting for long-term and intra-seasonal trends and apparent temperature. We evaluated the cumulative relative risk of the added wave effect on mortality on lag days 0–30. The models were constructed using nine definitions of heat wave and two relationships (cubic spline and linear threshold model) between temperature and mortality to leave out the high temperature effect. Further, we performed sensitivity analysis to evaluate the changes in the effect of heat wave on mortality according to the different degrees of freedom for time trend and cubic spline of temperature. We found that heat wave had the added effect from the prolonged period of high temperature on mortality and it was considerable in the aspect of cumulative risk because of the lagged influence. When heat wave was defined with a threshold of 98th percentile temperature and ≥2, 3, and 4 consecutive days, mortality increased by 14.8 % (7.5–22.6, 95 % confidence interval (CI)), 18.1 % (10.8–26.0, 95 % CI), 18.1 % (10.7–25.9, 95 % CI), respectively, in cubic spline model. When it came to the definitions of 90th and 95th percentile, the risk increase in mortality declined to 3.7–5.8 % and 8.6–11.3 %, respectively. This effect was robust to the flexibility of the model for temperature and time trend, while the definitions of a heat wave were critical in estimating its relationship with mortality. This finding could help deepen our understanding and quantifying of the relationship between heat wave and mortality and select an appropriate definition of heat wave and temperature model in the future studies. Heat wave (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Temperature (dpeaa)DE-He213 Weather (dpeaa)DE-He213 Lee, Hye Ah verfasserin aut Lim, Youn Hee verfasserin aut Park, Hyesook verfasserin aut Enthalten in International journal of biometeorology Berlin : Springer, 1959 60(2015), 5 vom: 01. Okt., Seite 719-726 (DE-627)253724341 (DE-600)1459227-7 1432-1254 nnns volume:60 year:2015 number:5 day:01 month:10 pages:719-726 https://dx.doi.org/10.1007/s00484-015-1067-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.84 ASE 44.08 ASE AR 60 2015 5 01 10 719-726
spelling	10.1007/s00484-015-1067-x doi (DE-627)SPR006448984 (SPR)s00484-015-1067-x-e DE-627 ger DE-627 rakwb eng 570 ASE 38.84 bkl 44.08 bkl Lee, Won Kyung verfasserin aut Added effect of heat wave on mortality in Seoul, Korea 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A heat wave could increase mortality owing to high temperature. However, little is known about the added (duration) effect of heat wave from the prolonged period of high temperature on mortality and different effect sizes depending on the definition of heat waves and models. A distributed lag non-linear model with a quasi-Poisson distribution was used to evaluate the added effect of heat wave on mortality after adjusting for long-term and intra-seasonal trends and apparent temperature. We evaluated the cumulative relative risk of the added wave effect on mortality on lag days 0–30. The models were constructed using nine definitions of heat wave and two relationships (cubic spline and linear threshold model) between temperature and mortality to leave out the high temperature effect. Further, we performed sensitivity analysis to evaluate the changes in the effect of heat wave on mortality according to the different degrees of freedom for time trend and cubic spline of temperature. We found that heat wave had the added effect from the prolonged period of high temperature on mortality and it was considerable in the aspect of cumulative risk because of the lagged influence. When heat wave was defined with a threshold of 98th percentile temperature and ≥2, 3, and 4 consecutive days, mortality increased by 14.8 % (7.5–22.6, 95 % confidence interval (CI)), 18.1 % (10.8–26.0, 95 % CI), 18.1 % (10.7–25.9, 95 % CI), respectively, in cubic spline model. When it came to the definitions of 90th and 95th percentile, the risk increase in mortality declined to 3.7–5.8 % and 8.6–11.3 %, respectively. This effect was robust to the flexibility of the model for temperature and time trend, while the definitions of a heat wave were critical in estimating its relationship with mortality. This finding could help deepen our understanding and quantifying of the relationship between heat wave and mortality and select an appropriate definition of heat wave and temperature model in the future studies. Heat wave (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Temperature (dpeaa)DE-He213 Weather (dpeaa)DE-He213 Lee, Hye Ah verfasserin aut Lim, Youn Hee verfasserin aut Park, Hyesook verfasserin aut Enthalten in International journal of biometeorology Berlin : Springer, 1959 60(2015), 5 vom: 01. Okt., Seite 719-726 (DE-627)253724341 (DE-600)1459227-7 1432-1254 nnns volume:60 year:2015 number:5 day:01 month:10 pages:719-726 https://dx.doi.org/10.1007/s00484-015-1067-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.84 ASE 44.08 ASE AR 60 2015 5 01 10 719-726
allfields_unstemmed	10.1007/s00484-015-1067-x doi (DE-627)SPR006448984 (SPR)s00484-015-1067-x-e DE-627 ger DE-627 rakwb eng 570 ASE 38.84 bkl 44.08 bkl Lee, Won Kyung verfasserin aut Added effect of heat wave on mortality in Seoul, Korea 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A heat wave could increase mortality owing to high temperature. However, little is known about the added (duration) effect of heat wave from the prolonged period of high temperature on mortality and different effect sizes depending on the definition of heat waves and models. A distributed lag non-linear model with a quasi-Poisson distribution was used to evaluate the added effect of heat wave on mortality after adjusting for long-term and intra-seasonal trends and apparent temperature. We evaluated the cumulative relative risk of the added wave effect on mortality on lag days 0–30. The models were constructed using nine definitions of heat wave and two relationships (cubic spline and linear threshold model) between temperature and mortality to leave out the high temperature effect. Further, we performed sensitivity analysis to evaluate the changes in the effect of heat wave on mortality according to the different degrees of freedom for time trend and cubic spline of temperature. We found that heat wave had the added effect from the prolonged period of high temperature on mortality and it was considerable in the aspect of cumulative risk because of the lagged influence. When heat wave was defined with a threshold of 98th percentile temperature and ≥2, 3, and 4 consecutive days, mortality increased by 14.8 % (7.5–22.6, 95 % confidence interval (CI)), 18.1 % (10.8–26.0, 95 % CI), 18.1 % (10.7–25.9, 95 % CI), respectively, in cubic spline model. When it came to the definitions of 90th and 95th percentile, the risk increase in mortality declined to 3.7–5.8 % and 8.6–11.3 %, respectively. This effect was robust to the flexibility of the model for temperature and time trend, while the definitions of a heat wave were critical in estimating its relationship with mortality. This finding could help deepen our understanding and quantifying of the relationship between heat wave and mortality and select an appropriate definition of heat wave and temperature model in the future studies. Heat wave (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Temperature (dpeaa)DE-He213 Weather (dpeaa)DE-He213 Lee, Hye Ah verfasserin aut Lim, Youn Hee verfasserin aut Park, Hyesook verfasserin aut Enthalten in International journal of biometeorology Berlin : Springer, 1959 60(2015), 5 vom: 01. Okt., Seite 719-726 (DE-627)253724341 (DE-600)1459227-7 1432-1254 nnns volume:60 year:2015 number:5 day:01 month:10 pages:719-726 https://dx.doi.org/10.1007/s00484-015-1067-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.84 ASE 44.08 ASE AR 60 2015 5 01 10 719-726
allfieldsGer	10.1007/s00484-015-1067-x doi (DE-627)SPR006448984 (SPR)s00484-015-1067-x-e DE-627 ger DE-627 rakwb eng 570 ASE 38.84 bkl 44.08 bkl Lee, Won Kyung verfasserin aut Added effect of heat wave on mortality in Seoul, Korea 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A heat wave could increase mortality owing to high temperature. However, little is known about the added (duration) effect of heat wave from the prolonged period of high temperature on mortality and different effect sizes depending on the definition of heat waves and models. A distributed lag non-linear model with a quasi-Poisson distribution was used to evaluate the added effect of heat wave on mortality after adjusting for long-term and intra-seasonal trends and apparent temperature. We evaluated the cumulative relative risk of the added wave effect on mortality on lag days 0–30. The models were constructed using nine definitions of heat wave and two relationships (cubic spline and linear threshold model) between temperature and mortality to leave out the high temperature effect. Further, we performed sensitivity analysis to evaluate the changes in the effect of heat wave on mortality according to the different degrees of freedom for time trend and cubic spline of temperature. We found that heat wave had the added effect from the prolonged period of high temperature on mortality and it was considerable in the aspect of cumulative risk because of the lagged influence. When heat wave was defined with a threshold of 98th percentile temperature and ≥2, 3, and 4 consecutive days, mortality increased by 14.8 % (7.5–22.6, 95 % confidence interval (CI)), 18.1 % (10.8–26.0, 95 % CI), 18.1 % (10.7–25.9, 95 % CI), respectively, in cubic spline model. When it came to the definitions of 90th and 95th percentile, the risk increase in mortality declined to 3.7–5.8 % and 8.6–11.3 %, respectively. This effect was robust to the flexibility of the model for temperature and time trend, while the definitions of a heat wave were critical in estimating its relationship with mortality. This finding could help deepen our understanding and quantifying of the relationship between heat wave and mortality and select an appropriate definition of heat wave and temperature model in the future studies. Heat wave (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Temperature (dpeaa)DE-He213 Weather (dpeaa)DE-He213 Lee, Hye Ah verfasserin aut Lim, Youn Hee verfasserin aut Park, Hyesook verfasserin aut Enthalten in International journal of biometeorology Berlin : Springer, 1959 60(2015), 5 vom: 01. Okt., Seite 719-726 (DE-627)253724341 (DE-600)1459227-7 1432-1254 nnns volume:60 year:2015 number:5 day:01 month:10 pages:719-726 https://dx.doi.org/10.1007/s00484-015-1067-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.84 ASE 44.08 ASE AR 60 2015 5 01 10 719-726
allfieldsSound	10.1007/s00484-015-1067-x doi (DE-627)SPR006448984 (SPR)s00484-015-1067-x-e DE-627 ger DE-627 rakwb eng 570 ASE 38.84 bkl 44.08 bkl Lee, Won Kyung verfasserin aut Added effect of heat wave on mortality in Seoul, Korea 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract A heat wave could increase mortality owing to high temperature. However, little is known about the added (duration) effect of heat wave from the prolonged period of high temperature on mortality and different effect sizes depending on the definition of heat waves and models. A distributed lag non-linear model with a quasi-Poisson distribution was used to evaluate the added effect of heat wave on mortality after adjusting for long-term and intra-seasonal trends and apparent temperature. We evaluated the cumulative relative risk of the added wave effect on mortality on lag days 0–30. The models were constructed using nine definitions of heat wave and two relationships (cubic spline and linear threshold model) between temperature and mortality to leave out the high temperature effect. Further, we performed sensitivity analysis to evaluate the changes in the effect of heat wave on mortality according to the different degrees of freedom for time trend and cubic spline of temperature. We found that heat wave had the added effect from the prolonged period of high temperature on mortality and it was considerable in the aspect of cumulative risk because of the lagged influence. When heat wave was defined with a threshold of 98th percentile temperature and ≥2, 3, and 4 consecutive days, mortality increased by 14.8 % (7.5–22.6, 95 % confidence interval (CI)), 18.1 % (10.8–26.0, 95 % CI), 18.1 % (10.7–25.9, 95 % CI), respectively, in cubic spline model. When it came to the definitions of 90th and 95th percentile, the risk increase in mortality declined to 3.7–5.8 % and 8.6–11.3 %, respectively. This effect was robust to the flexibility of the model for temperature and time trend, while the definitions of a heat wave were critical in estimating its relationship with mortality. This finding could help deepen our understanding and quantifying of the relationship between heat wave and mortality and select an appropriate definition of heat wave and temperature model in the future studies. Heat wave (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Temperature (dpeaa)DE-He213 Weather (dpeaa)DE-He213 Lee, Hye Ah verfasserin aut Lim, Youn Hee verfasserin aut Park, Hyesook verfasserin aut Enthalten in International journal of biometeorology Berlin : Springer, 1959 60(2015), 5 vom: 01. Okt., Seite 719-726 (DE-627)253724341 (DE-600)1459227-7 1432-1254 nnns volume:60 year:2015 number:5 day:01 month:10 pages:719-726 https://dx.doi.org/10.1007/s00484-015-1067-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA SSG-OPC-GGO SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.84 ASE 44.08 ASE AR 60 2015 5 01 10 719-726
language	English
source	Enthalten in International journal of biometeorology 60(2015), 5 vom: 01. Okt., Seite 719-726 volume:60 year:2015 number:5 day:01 month:10 pages:719-726
sourceStr	Enthalten in International journal of biometeorology 60(2015), 5 vom: 01. Okt., Seite 719-726 volume:60 year:2015 number:5 day:01 month:10 pages:719-726
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Heat wave Mortality Temperature Weather
dewey-raw	570
isfreeaccess_bool	false
container_title	International journal of biometeorology
authorswithroles_txt_mv	Lee, Won Kyung @@aut@@ Lee, Hye Ah @@aut@@ Lim, Youn Hee @@aut@@ Park, Hyesook @@aut@@
publishDateDaySort_date	2015-10-01T00:00:00Z
hierarchy_top_id	253724341
dewey-sort	3570
id	SPR006448984
language_de	englisch
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author	Lee, Won Kyung
spellingShingle	Lee, Won Kyung ddc 570 bkl 38.84 bkl 44.08 misc Heat wave misc Mortality misc Temperature misc Weather Added effect of heat wave on mortality in Seoul, Korea
authorStr	Lee, Won Kyung
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topic_title	570 ASE 38.84 bkl 44.08 bkl Added effect of heat wave on mortality in Seoul, Korea Heat wave (dpeaa)DE-He213 Mortality (dpeaa)DE-He213 Temperature (dpeaa)DE-He213 Weather (dpeaa)DE-He213
topic	ddc 570 bkl 38.84 bkl 44.08 misc Heat wave misc Mortality misc Temperature misc Weather
topic_unstemmed	ddc 570 bkl 38.84 bkl 44.08 misc Heat wave misc Mortality misc Temperature misc Weather
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title	Added effect of heat wave on mortality in Seoul, Korea
ctrlnum	(DE-627)SPR006448984 (SPR)s00484-015-1067-x-e
title_full	Added effect of heat wave on mortality in Seoul, Korea
author_sort	Lee, Won Kyung
journal	International journal of biometeorology
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author_browse	Lee, Won Kyung Lee, Hye Ah Lim, Youn Hee Park, Hyesook
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author-letter	Lee, Won Kyung
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title_sort	added effect of heat wave on mortality in seoul, korea
title_auth	Added effect of heat wave on mortality in Seoul, Korea
abstract	Abstract A heat wave could increase mortality owing to high temperature. However, little is known about the added (duration) effect of heat wave from the prolonged period of high temperature on mortality and different effect sizes depending on the definition of heat waves and models. A distributed lag non-linear model with a quasi-Poisson distribution was used to evaluate the added effect of heat wave on mortality after adjusting for long-term and intra-seasonal trends and apparent temperature. We evaluated the cumulative relative risk of the added wave effect on mortality on lag days 0–30. The models were constructed using nine definitions of heat wave and two relationships (cubic spline and linear threshold model) between temperature and mortality to leave out the high temperature effect. Further, we performed sensitivity analysis to evaluate the changes in the effect of heat wave on mortality according to the different degrees of freedom for time trend and cubic spline of temperature. We found that heat wave had the added effect from the prolonged period of high temperature on mortality and it was considerable in the aspect of cumulative risk because of the lagged influence. When heat wave was defined with a threshold of 98th percentile temperature and ≥2, 3, and 4 consecutive days, mortality increased by 14.8 % (7.5–22.6, 95 % confidence interval (CI)), 18.1 % (10.8–26.0, 95 % CI), 18.1 % (10.7–25.9, 95 % CI), respectively, in cubic spline model. When it came to the definitions of 90th and 95th percentile, the risk increase in mortality declined to 3.7–5.8 % and 8.6–11.3 %, respectively. This effect was robust to the flexibility of the model for temperature and time trend, while the definitions of a heat wave were critical in estimating its relationship with mortality. This finding could help deepen our understanding and quantifying of the relationship between heat wave and mortality and select an appropriate definition of heat wave and temperature model in the future studies.
abstractGer	Abstract A heat wave could increase mortality owing to high temperature. However, little is known about the added (duration) effect of heat wave from the prolonged period of high temperature on mortality and different effect sizes depending on the definition of heat waves and models. A distributed lag non-linear model with a quasi-Poisson distribution was used to evaluate the added effect of heat wave on mortality after adjusting for long-term and intra-seasonal trends and apparent temperature. We evaluated the cumulative relative risk of the added wave effect on mortality on lag days 0–30. The models were constructed using nine definitions of heat wave and two relationships (cubic spline and linear threshold model) between temperature and mortality to leave out the high temperature effect. Further, we performed sensitivity analysis to evaluate the changes in the effect of heat wave on mortality according to the different degrees of freedom for time trend and cubic spline of temperature. We found that heat wave had the added effect from the prolonged period of high temperature on mortality and it was considerable in the aspect of cumulative risk because of the lagged influence. When heat wave was defined with a threshold of 98th percentile temperature and ≥2, 3, and 4 consecutive days, mortality increased by 14.8 % (7.5–22.6, 95 % confidence interval (CI)), 18.1 % (10.8–26.0, 95 % CI), 18.1 % (10.7–25.9, 95 % CI), respectively, in cubic spline model. When it came to the definitions of 90th and 95th percentile, the risk increase in mortality declined to 3.7–5.8 % and 8.6–11.3 %, respectively. This effect was robust to the flexibility of the model for temperature and time trend, while the definitions of a heat wave were critical in estimating its relationship with mortality. This finding could help deepen our understanding and quantifying of the relationship between heat wave and mortality and select an appropriate definition of heat wave and temperature model in the future studies.
abstract_unstemmed	Abstract A heat wave could increase mortality owing to high temperature. However, little is known about the added (duration) effect of heat wave from the prolonged period of high temperature on mortality and different effect sizes depending on the definition of heat waves and models. A distributed lag non-linear model with a quasi-Poisson distribution was used to evaluate the added effect of heat wave on mortality after adjusting for long-term and intra-seasonal trends and apparent temperature. We evaluated the cumulative relative risk of the added wave effect on mortality on lag days 0–30. The models were constructed using nine definitions of heat wave and two relationships (cubic spline and linear threshold model) between temperature and mortality to leave out the high temperature effect. Further, we performed sensitivity analysis to evaluate the changes in the effect of heat wave on mortality according to the different degrees of freedom for time trend and cubic spline of temperature. We found that heat wave had the added effect from the prolonged period of high temperature on mortality and it was considerable in the aspect of cumulative risk because of the lagged influence. When heat wave was defined with a threshold of 98th percentile temperature and ≥2, 3, and 4 consecutive days, mortality increased by 14.8 % (7.5–22.6, 95 % confidence interval (CI)), 18.1 % (10.8–26.0, 95 % CI), 18.1 % (10.7–25.9, 95 % CI), respectively, in cubic spline model. When it came to the definitions of 90th and 95th percentile, the risk increase in mortality declined to 3.7–5.8 % and 8.6–11.3 %, respectively. This effect was robust to the flexibility of the model for temperature and time trend, while the definitions of a heat wave were critical in estimating its relationship with mortality. This finding could help deepen our understanding and quantifying of the relationship between heat wave and mortality and select an appropriate definition of heat wave and temperature model in the future studies.
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container_issue	5
title_short	Added effect of heat wave on mortality in Seoul, Korea
url	https://dx.doi.org/10.1007/s00484-015-1067-x
remote_bool	true
author2	Lee, Hye Ah Lim, Youn Hee Park, Hyesook
author2Str	Lee, Hye Ah Lim, Youn Hee Park, Hyesook
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doi_str	10.1007/s00484-015-1067-x
up_date	2024-07-03T23:05:16.964Z
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Added effect of heat wave on mortality in Seoul, Korea

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