目的探索隔日温差(temperature changes between neighboring days,TCN)对人群死亡的影响。方法收集我国21个地区2014-2018年的每日气象因素数据、空气污染物数据和死因统计数据。运用分布滞后非线性模型(distributed lag non-linear mo...目的探索隔日温差(temperature changes between neighboring days,TCN)对人群死亡的影响。方法收集我国21个地区2014-2018年的每日气象因素数据、空气污染物数据和死因统计数据。运用分布滞后非线性模型(distributed lag non-linear model,DLNM)和多元Meta分析,估计不同季节的TCN对每日总死亡人数的影响。结果研究显示,不同季节的TCN对每日总死亡人数均有显著影响,且阈值不同。冷季时,P_(95)TCN(升温)的14天累积相对危险度(CRR)为0.868(_(95)%CI:0.794,0.948),而P_(5)(降温)对每日总死亡人数的影响没有统计学意义。暖季时,P_(95)TCN(升温)的7天CRR为1.078(_(95)%CI:1.009,1.152),而P_(5)(降温)的7天CRR为0.929(_(95)%CI:0.889,0.971)。冷季时,患有呼吸系统疾病人群更容易受到温度变化的不利影响。暖季时,循环系统疾病人群、女性和≥65岁人群对温度变化更为敏感。南北区域的分析显示,北方城市的人群对P_(95)TCN的影响更加敏感。结论不同季节的极端TCN与人群死亡的风险存在关联,冷季时升温可降低人群死亡风险,而暖季时升温可增加人群死亡风险,降温可降低人群死亡风险。健康促进策略应该考虑相邻两天之间的温度变化对人群死亡影响。展开更多
Background:Light at night(LAN)has become a concern in interdisciplinary research in recent years.This global interdisciplinary study aimed to explore the exposure-lag-response association between LAN exposure and lung...Background:Light at night(LAN)has become a concern in interdisciplinary research in recent years.This global interdisciplinary study aimed to explore the exposure-lag-response association between LAN exposure and lung cancer incidence.Methods:LAN data were obtained from the Defense Meteorological Satellite Program’s Operational Linescan System.Data of lung cancer incidence,socio-demographic index,and smoking prevalence of populations in 201 countries/territories from 1992 to 2018 were collected from the Global Burden of Disease Study.Spearman correlation tests and population-weighted linear regression analysis were used to evaluate the correlation between LAN exposure and lung cancer incidence.A distributed lag nonlinear model(DLNM)was used to assess the exposure-lag effects of LAN exposure on lung cancer incidence.Results:The Spearman correlation coefficients were 0.286-0.355 and the population-weighted linear regression correlation coefficients were 0.361-0.527.After adjustment for socio-demographic index and smoking preva-lence,the Spearman correlation coefficients were 0.264-0.357 and the population-weighted linear regression correlation coefficients were 0.346-0.497.In the DLNM,the maximum relative risk was 1.04(1.02-1.06)at LAN exposure of 8.6 with a 2.6-year lag time.After adjustment for socio-demographic index and smoking prevalence,the maximum relative risk was 1.05(1.02-1.07)at LAN exposure of 8.6 with a 2.4-year lag time.Conclusion:High LAN exposure was associated with increased lung cancer incidence,and this effect had a specific lag period.Compared with traditional individual-level studies,this group-level study provides a novel paradigm of effective,efficient,and scalable screening for risk factors.展开更多
Background:Evidence is inefficient about how meteorological factors influence the trends of influenza transmission in different regions of China.Methods:We estimated the time-varying reproduction number(Rt)of influenz...Background:Evidence is inefficient about how meteorological factors influence the trends of influenza transmission in different regions of China.Methods:We estimated the time-varying reproduction number(Rt)of influenza and explored the impact of temperature and relative humidity on Rt using generalized additive quasi-Poisson regression models combined with the distribution lag non-linear model(DLNM).The effect of temperature and humidity interaction on Rt of influenza was explored.The multiple random-meta analysis was used to evaluate region-specific association.The excess risk(ER)index was defined to investigate the correlation between Rt and each meteorological factor with the modification of seasonal and regional characteristics.Results:Low temperature and low relative humidity contributed to influenza epidemics on the national level,while shapes of merged cumulative effect plots were different across regions.Compared to that of median temperature,the merged RR(95%CI)of low tem-perature in northern and southern regions were 1.40(1.24,1.45)and 1.20(1.14,1.27),respectively,while those of high temperature were 1.10(1.03,1.17)and 1.00(0.95,1.04),respectively.There were negative interactions between temperature and relative humidity on national(SI=0.59,95%CI:0.57e0.61),southern(SI=0.49,95%CI:0.17e0.80),and northern regions(SI=0.59,95%CI:0.56,0.62).In general,with the increase of the change of the two meteorological factors,the ER of Rt also gradually increased.Conclusions:Temperature and relative humidity have an effect on the influenza epidemics in China,and there is an interaction between the two meteorological factors,but the effect of each factor is heterogeneous among regions.Meteorological factors may be considered to predict the trend of influenza epidemic.展开更多
文摘目的探索隔日温差(temperature changes between neighboring days,TCN)对人群死亡的影响。方法收集我国21个地区2014-2018年的每日气象因素数据、空气污染物数据和死因统计数据。运用分布滞后非线性模型(distributed lag non-linear model,DLNM)和多元Meta分析,估计不同季节的TCN对每日总死亡人数的影响。结果研究显示,不同季节的TCN对每日总死亡人数均有显著影响,且阈值不同。冷季时,P_(95)TCN(升温)的14天累积相对危险度(CRR)为0.868(_(95)%CI:0.794,0.948),而P_(5)(降温)对每日总死亡人数的影响没有统计学意义。暖季时,P_(95)TCN(升温)的7天CRR为1.078(_(95)%CI:1.009,1.152),而P_(5)(降温)的7天CRR为0.929(_(95)%CI:0.889,0.971)。冷季时,患有呼吸系统疾病人群更容易受到温度变化的不利影响。暖季时,循环系统疾病人群、女性和≥65岁人群对温度变化更为敏感。南北区域的分析显示,北方城市的人群对P_(95)TCN的影响更加敏感。结论不同季节的极端TCN与人群死亡的风险存在关联,冷季时升温可降低人群死亡风险,而暖季时升温可增加人群死亡风险,降温可降低人群死亡风险。健康促进策略应该考虑相邻两天之间的温度变化对人群死亡影响。
文摘Background:Light at night(LAN)has become a concern in interdisciplinary research in recent years.This global interdisciplinary study aimed to explore the exposure-lag-response association between LAN exposure and lung cancer incidence.Methods:LAN data were obtained from the Defense Meteorological Satellite Program’s Operational Linescan System.Data of lung cancer incidence,socio-demographic index,and smoking prevalence of populations in 201 countries/territories from 1992 to 2018 were collected from the Global Burden of Disease Study.Spearman correlation tests and population-weighted linear regression analysis were used to evaluate the correlation between LAN exposure and lung cancer incidence.A distributed lag nonlinear model(DLNM)was used to assess the exposure-lag effects of LAN exposure on lung cancer incidence.Results:The Spearman correlation coefficients were 0.286-0.355 and the population-weighted linear regression correlation coefficients were 0.361-0.527.After adjustment for socio-demographic index and smoking preva-lence,the Spearman correlation coefficients were 0.264-0.357 and the population-weighted linear regression correlation coefficients were 0.346-0.497.In the DLNM,the maximum relative risk was 1.04(1.02-1.06)at LAN exposure of 8.6 with a 2.6-year lag time.After adjustment for socio-demographic index and smoking prevalence,the maximum relative risk was 1.05(1.02-1.07)at LAN exposure of 8.6 with a 2.4-year lag time.Conclusion:High LAN exposure was associated with increased lung cancer incidence,and this effect had a specific lag period.Compared with traditional individual-level studies,this group-level study provides a novel paradigm of effective,efficient,and scalable screening for risk factors.
基金supported by the National Natural Science Foundation of China(82073673)National Key R&D Program of China(2022YFC2304000).
文摘Background:Evidence is inefficient about how meteorological factors influence the trends of influenza transmission in different regions of China.Methods:We estimated the time-varying reproduction number(Rt)of influenza and explored the impact of temperature and relative humidity on Rt using generalized additive quasi-Poisson regression models combined with the distribution lag non-linear model(DLNM).The effect of temperature and humidity interaction on Rt of influenza was explored.The multiple random-meta analysis was used to evaluate region-specific association.The excess risk(ER)index was defined to investigate the correlation between Rt and each meteorological factor with the modification of seasonal and regional characteristics.Results:Low temperature and low relative humidity contributed to influenza epidemics on the national level,while shapes of merged cumulative effect plots were different across regions.Compared to that of median temperature,the merged RR(95%CI)of low tem-perature in northern and southern regions were 1.40(1.24,1.45)and 1.20(1.14,1.27),respectively,while those of high temperature were 1.10(1.03,1.17)and 1.00(0.95,1.04),respectively.There were negative interactions between temperature and relative humidity on national(SI=0.59,95%CI:0.57e0.61),southern(SI=0.49,95%CI:0.17e0.80),and northern regions(SI=0.59,95%CI:0.56,0.62).In general,with the increase of the change of the two meteorological factors,the ER of Rt also gradually increased.Conclusions:Temperature and relative humidity have an effect on the influenza epidemics in China,and there is an interaction between the two meteorological factors,but the effect of each factor is heterogeneous among regions.Meteorological factors may be considered to predict the trend of influenza epidemic.
