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Analysis of the lag-effects of temperature on the five cities' mortality in China / 中华预防医学杂志
Chinese Journal of Preventive Medicine ; (12): 1015-1019, 2012.
Artigo em Chinês | WPRIM | ID: wpr-326190
ABSTRACT
<p><b>OBJECTIVE</b>To study the characteristics of the effect of different temperatures on mortality of different cities through analyzing the relationship between mortality and meteorology of five Chinese cities.</p><p><b>METHODS</b>We get the demography and climate data of Beijing, Tianjin, Shanghai, Nanjing and Changsha cities from National Center of Disease Control and Prevention and Climate net respectively. Then we applied the R software and Distributed Lag Non-linear Models (DLNM) package to analyze our data and find the nonlinear and lag effects on mortality using DLNM.</p><p><b>RESULTS</b>The city of Beijing and Tianjin are located in the temperate zone. And the climate of Shanghai, Nanjing, Changsha belong to subtropical monsoon climate. When the daily mean temperature arrived 30°C and on lag 0 day, the values of relative risk of effect of high mean temperature on mortality in Nanjing (1.31, 95%CI 1.21 - 1.41) and Changsha (1.25, 95%CI 1.13 - 1.39) are larger than that in Beijing (1.18, 95%CI 1.12 - 1.25), Tianjin (1.18, 95%CI 1.10 - 1.26) and Shanghai(1.15, 95%CI 1.06 - 1.24). While the relative risk of effect of low mean temperature on mortality is lower and lasts for a longer lag time. During the whole lag time, the relative risk of effect of the lowest daily mean temperature of each city on mortality in Tianjin, Changsha, Beijing, Nanjing, and Shanghai is 3.41, 95%CI 1.60 - 7.27, 2.15, 95%CI 1.11 - 4.15, 2.24, 95%CI 1.12 - 4.48, 2.80, 95%CI 1.75 - 4.48, 1.53, 95%CI 1.12 - 2.03, respectively. The cumulative effect of mean temperature on mortality appears like a U-shape. When on lag 0-1 day, the value of relative risk of effect of extremely high temperature and the highest mean temperature on mortality is larger than 1. While the effect of low temperature on mortality becomes obvious after lag 2 days.</p><p><b>CONCLUSION</b>Depending on this research, extremely low temperature and the lowest mean temperature has a more obvious impact on mortality in the northern area than in the south. Extremely high temperature and the highest daily mean temperature is on the contrary. Meanwhile, different temperatures have different impacts on mortality in the same city high temperature has an acute impact while there is a longer lag time in low temperature.</p>
Assuntos
Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Assunto principal: Temperatura / População Urbana / China / Mortalidade / Clima / Dinâmica não Linear Tipo de estudo: Estudo de etiologia / Estudo prognóstico Limite: Humanos País/Região como assunto: Ásia Idioma: Chinês Revista: Chinese Journal of Preventive Medicine Ano de publicação: 2012 Tipo de documento: Artigo

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Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Assunto principal: Temperatura / População Urbana / China / Mortalidade / Clima / Dinâmica não Linear Tipo de estudo: Estudo de etiologia / Estudo prognóstico Limite: Humanos País/Região como assunto: Ásia Idioma: Chinês Revista: Chinese Journal of Preventive Medicine Ano de publicação: 2012 Tipo de documento: Artigo