The Study Of Temperature-related Respiratory Mortality Disease Burden Under Climate Change

Background and ObjectiveUnder the background of climate change,the global mean temperature(TM)has increased dramatically,along with the frequent extreme climate events,which may increase the temperature variability(TV)at the same time.Temperature(TM and TV)is associated with human health.Respiratory disease is one of the top contributors of disease burden throughout the world.However,few studies have focused on the temperature(TM and TV)related respiratory disease burden,most of which were conducted in a single city and barely taking climate change into consideration.In addition,another limitation of previous studies is that mortality number was the most widely used outcome,which did not consider the different years of life lost(YLL)of different age.Therefore,in this study firstly we would like to estimate the trend of temperature change in China in 1951?2019,then conduct a large-scale study in multi-cities to evaluate the temperature(TM and TV)-related respiratory disease burden during 2006?2017 in China,after that we would like to predict the temperature-related respiratory disease burden under climate change in the future(2030s,2060s and 2090s).Methods(1)In this study,we first analyzed the overall trend,regional and seasonal differences of temperature(TM and TV)in China during 1951?2019 based on data of 599 meteorological stations published by China national meteorological data center.(2)Then we conducted a large-scale muti-cities time-series study to evaluate the temperature(TM and TV)-related respiratory disease burden during 2006?2017 in 364 counties of China,using temperature(TM and TV)as exposure,respiratory-related YLL rate as outcome.In this section,we also conducted subgroup analyses based on demographic characteristics,regions,development levels and disease types.In addition,we provided a new TV index named total temperature variability(TTV)to better reflect the direction and magnitude of TV.(3)After that,we applied Distributed Lag Non-linear Model to predict the temperature-related respiratory disease burden under different scenarios in the future(2030s,2060s and 2090s)based on the historical exposure-effect relationship and global climate models.Results(1)During 1951?2019,the annual TM increased by 0.18?/10 years,while TV did not show significant change in China.(2)During 2006?2017,12.39%(95%CI:10.09%?14.61%)of respiratory YLL rate could be attributed to TM,most of which resulted from moderate TM[attributable fraction(AF),7.12%(95%CI:6.23%?7.98%)].TTV could be an appropriate index to evaluate TV,with an AF of 7.22%(95%CI:2.63%?11.80%),among which high TTV was the major contributor(AF:6.85%,95%CI:2.51%?11.18%).The disease burden differed in subgroups.AFs among males and people suffered from chronic lower respiratory infections were higher than other subgroups.In addition,respiratory YLL rates attributed to TTV among people lived in low developed areas are higher than those who lived in high developed areas.In different climate scenarios,the net effect of temperature on respiratory YLL rate would decrease in the future,while the attributable respiratory YLL rate to the heat and high TV will still increase in 2030s,2060s and 2090s.ConclusionTM but not TV increased significantly in the past 70 years in China.TM could increase the respiratory YLL rate,among which cold effect was much larger than heat effect.TV could also increase the respiratory YLL rate.The respiratory YLL rates in males and chronic lower respiratory infections YLL rates were more significantly affected by temperature(TM and TV)than other subgroups.People lived in low developed areas suffered more than those who lived in high developed areas.The respiratory YLL rates attributed to the heat and high TTV will still increase in the future,which could offer some information for the policy makers to formulate appropriate climate change adaptation strategies.