| BackgroundGlobally,a wide range of climate system changes may be affecting the population health.The potential risks and adverse effects of the climate changes are increasing.Changes in the atmospheric environment can eventually lead to a variety of diseases,which are sensitive to the climate,such as cardiovascular diseases,respiratory diseases,nutritional disorders,and infectious diseases.The range of warm areas increases as the temperature increases,and vector insects originating from the tropics may migrate to temperate regions as result,which may lead to changes in the epidemiological characteristics of infectious diseases worldwide.Impacts of meteorological factors on the population health have been widespread concerned,and a large number of related studies emerged,most of which were aimed to reveal the impacts of meteorological factors on mortality,hospitalization rates,fatality of respiratory and cardiovascular diseases,vector and water-borne diseases in the population.In developing countries,the infectious diseases seriously affect the population health and national economy.In China,the development of infectious disease surveillance systems provides a good data source for the studies about the relationship of meteorological factors and the infectious diseases.However,current domestic research is still inadequate.Especially for the lag effects of meteorological factors,the related study is far from in-depth.Guangzhou city is a coastal city in southern China.Its climate and development characteristics make the infectious disease prevention and control in this region faced with great challenges.Hand,foot and mouth disease(HFMD),other infectious diarrhea(OID)and chickenpox are the diseases with relatively high incidence in Guangzhou city.These three diseases communicate through different routes.HFMD is usually infected through multiple routes including digestive tract,respiratory tract,and direct contact.OID is usually infected through gastrointestinal tract,while chickenpox is usually infected through respiratory tract.The aim of this study is to analyze the effects of air temperature on these three diseases,so as to provide a scientific basis for more targeted disease prevention and control measures.Objectives1.To analyze the time distribution,spatial distribution and population distribution of HFMD,OID,and chickenpox in Guangzhou,and to determine the high-risk population of these infectious diseases.2.To determine the relationships between the meteorological factors and the HFMD,OID,and chickenpox and specify the distribution of the lag effects;to estimate the effects of temperature on infectious diseases in different subgroups.MethodsThe meteorological data of Guangzhou city were obtained from the China Meteorological Data Network,and the data of infectious diseases were obtained from the infectious disease surveillance system of China Center for Disease Control and Prevention(CDC).A time series data set containing meteorological factor variables and the number of cases of infectious diseases were organized.The time series and the seasonal distribution of disease cases were plotted to describe the time distribution of the diseases;Histograms were drawn to describe the age distribution of the diseases;pie charts were plotted to describe the sex and occupational distribution of diseases.We also plotted maps showing spatial distribution of diseases with the ArcGIS10.O software.In this study,ecology study was adopted,and distributed lag nonlinear models(DLNMs)were constructed based on the time series data sets.The cross basis function of temperature was included in the models,so as to estimate the impacts of temperature on infectious diseases in exposure and lag dimensions simultaneously.The potential confounders including relative humidity,air temperature,wind speed,and sunshine duration were modeled as natural splines.The natural spline of time variable was included in the models to control the long term trend and seasonal trend.Day of week was also included as an indicator in the models,to adjust any confounding by weekly pattern.The median value of temperature(23.45?)was defined as the reference for the estimation of relative risks(RRs).All the data analysis was conducted using R3.1.1 software.Through changing the parameters in the model and referring to the evaluation of the model goodness by Akaike Information Criterion(QAIC),we selected the optimal model to determine the relationships between the temperature and the infectious disease and also specified the distribution of the lag effects.Single and cumulative RRs of infectious diseases at different lag time after the specific temperature were estimated respectively,so as to reflect both the degree and persistent of effects.Two-side statistical test were conducted,and the significance level was defined as 0.05.Results1.A total of 20,4919 new cases of HFMD were reported in Guangzhou in 2009-2013.Annually,there were two peaks of HFMD,between May and September.44,549 cases were reported in Baiyun district,accounting for 21.7%of the total cases and ranking first in all the city.Among all the cases,12,9013 individuals were male,accounting for 63.0%;7,5906 individuals were female,accounting for 37.0%;.19,5416 individuals were 5 years old and below,accounting for 95.4%;15,4283 individuals were scattered children,accounting for 75.3%;4,4233 individuals were children in kindergarten,accounting for 21.6%.2.In terms of the single effect,when temperature of 12.55? appeared,the RR of the HFMD in the whole population on the current day was the highest(RR=1.17,95%CI:1.06?1.30).The lag effect of this temperature level on HFMD was basically U-shape distributed;in terms of cumulative effect,after the temperature of the P10 level appeared,the cumulative effect on the 21th lag day was larger than that on the 7th and 14th lag day.On the current day under the temperature of the P10 level,the RR of HFMD in the scattered children was the highest(RR=1.21,95%CI:1.09-1.34).However,on the 21th lag day,the cumulative RR of HFMD in males was the highest(RR=2.38,95%CI:1.51?3.74).3.A total of 7,0582 new cases of OID were reported in Guangzhou in 2009?2013.Annually,there was one peak of OID at the end of each year.1,4179 cases were reported in Baiyun district.accounting for 20.1%of the total cases and ranking first in all the city.Among all the cases,4,3259 individuals were male,accounting for 61.3%;2,7323 individuals were female.accounting for 38.7%;5,6988 individuals were 5 years old and below,accounting for 95.4%;15,4283 individuals were scattered children,accounting for 80.7%;5,6007 individuals were children in kindergarten,accounting for 74.9%.4.In terms of the single effect,when the minimum average temperature(5.30?)appeared,the RR of the OID in the whole population on the 10th day was the highest(RR=1.22,95%CI:1.18?1.26),and then kept stable as the lag time extend.When the temperature decreased below 10.19?,the RR of OID increased rapidly.In terms of cumulative effect,after the 5.30? appeared,the cumulative RR on the 2th lag day was larger than that on the 7th and 14th lag day.On the 10th day after the 5.30?,the RR of OID in children who were 5 years old and below was the highest(RR=1.24,95%CI:1.19?1.29).However,on the 21th lag day,the cumulative RR of OID in females was the highest(RR=29.40,95%CI:14.11?61.27).5.A total of 7,6530 new cases of chickenpox were reported in Guangzhou in 2009?2013.Annually,there was one peak between May and July,and another peak between December and the next January.1,3815 cases were reported in Baiyun district,accounting for 18.1%of the total cases and ranking first in all the city.Among all the cases,4,3968 individuals were male,accounting for 57.5%;3,2562 individuals were female,accounting for 42.5%;2,5683 individuals were 5 years old and below,accounting for 33.6%;5,0776 individuals were 6?55 years old,accounting for 66.3%;1.5213 individuals were scattered children,accounting for 19.9%;1,3270 individuals were children in kindergarten,accounting for 17.3%;3.3063 individuals were students,accounting for 43.2%.6.In terms of the single effect,when the maximum average temperature(31.70?)appeared,the RR of the chickenpox in the whole population on the 3th day was the highest(RR=1.07,95%CI:1.03?1.10).The lag effect of this temperature level on HFMD was U-shaped distributed.On the 3th lag day,the risks of chickenpox increased as the temperature increased.In terms of the cumulative effect,the cumulative effect on the 7th day was larger than that on the 14th day and 21th day.On the 3th day after the 31.70?,the RR of chickenpox in the population of 6?15 years old was the highest(RR=1.12,95%CI:1.07?1.17).On the 7th day,the cumulative RR of the chickenpox in the same population was also the highest(RR=1.47,95%CI:1.16?1.86).Conclusions1.Temperature has an obvious nonlinear effect on HFMD.The risk of HFMD under 12.55? is the highest.The HFMD incidence of scattered children is most sensitive to the temperature,while the cumulative effect in males are the largest.2.The OID is in negatively correlated with the temperature,the risk of OID under the minimum average temperature(5.30?)is the highest.The OID incidence is particularly sensitive to the temperature below 10.19?.Children who were 5 years old or below were most sensitive to the temperature,while the cumulative effect in females are the largest.3.The chickenpox is positively correlated with the temperature,the risk of chickenpox under the maximum daily average temperature(31.70?)is the highest.The chickenpox incidence is particularly sensitive to the temperature beyond 23.45?.Population of 6?15 years old is most sensitive to the temperature,while the cumulative effect in the same population is also the largest.4.The effects of temperature on HFMD,OID,and chickenpox are different.The temperature impacts on the OID is the highest,the most persistent,and with the largest cumulative effects.The degree of temperature effect on the chickenpox is the slightest,the shortest,and with the smallest cumulative effects.The patterns of influence on HFMD are between that of other infectious diarrhea and chickenpox. |
PDF Full Text Request