BACKGROUND Type 1 diabetes originates from gene-environment interactions,with increasing incidence over time.AIM To identify correlates of childhood type 1 diabetes in European countries using an ecological approach.S...BACKGROUND Type 1 diabetes originates from gene-environment interactions,with increasing incidence over time.AIM To identify correlates of childhood type 1 diabetes in European countries using an ecological approach.Several environmental variables potentially influencing the onset of type 1 diabetes have been previously evaluated.However,the relationships between epidemiologic data and exposure to toxic airborne molecules are scarcely studied.METHODS We employed an ecological model to explore,in a wide time period(1990-2018),associations between type 1 diabetes incidence in 19 European countries(systematic literature review)and the nationwide production of five widely diffused air pollutants:particulate matter<10μm(PM10),nitrogen oxides(NO),non-methane volatile organic compounds(VOCs),sulphur oxide(SO2),and ammonia.RESULTS Data confirm a raising incidence of type 1 diabetes in 18 out of 19 explored countries.The average difference(last vs first report,all countries)was+6.9×100000/year,with values ranging from-1.4(Germany)to+16.6(Sweden)per 100000/year.Although the overall production of pollutants decreased progressively from 1990 to 2018,type 1 diabetes incidence was positively associated with the nationwide emissions of PM10,VOCs,and NO but not with those of SO2 and ammonia.Type 1 diabetes incidence was significantly higher in countries with high emissions than in those with low emissions of PM10(27.5±2.4 vs 14.6±2.4×100000 residents,respectively),VOCs(24.5±4.4 vs 13.2±1.7×100000 residents,respectively),and NO(26.6±3 vs 13.4±2.4×100000 residents,respectively),but not of SO2 or ammonia.CONCLUSION Evidence justify further studies to explore better links between long-term air quality and type 1 diabetes onset at the individual level,which should include exposures during pregnancy.In this respect,type 1 diabetes could be,at least in part,a preventable condition.Thus,primary prevention policies acting through a marked abatement of pollutant emissions might attenuate future type 1 diabetes incidence throughout Europe.展开更多
NIKE AIR FORCE 1是NIKE各种鞋类中拥有最大专营模式的系列。从纽约到北京，AIR FORCE 1都是在街头巷尾最热门的鞋款。AIR FORCE 1是以篮球鞋来体现街头HIP HOP精神的典范。在这25年中，有超过1700双不同版本的AIR FORCE 1被制造出来．...NIKE AIR FORCE 1是NIKE各种鞋类中拥有最大专营模式的系列。从纽约到北京，AIR FORCE 1都是在街头巷尾最热门的鞋款。AIR FORCE 1是以篮球鞋来体现街头HIP HOP精神的典范。在这25年中，有超过1700双不同版本的AIR FORCE 1被制造出来．而AF1的大型庆祝活动将贯穿2007年的春夏秋冬。就在2007年逐步走到年底的时候．NIKE再次重拳出击。推出了SERATO AIR FORCE 1PACK。展开更多
In the present study, the air quality is assessed for the year 2010 regarding to the Total Suspended Particles (TSP) for six cities of Sonora, Mexico, representing the first regional study in Sonora in air quality. Th...In the present study, the air quality is assessed for the year 2010 regarding to the Total Suspended Particles (TSP) for six cities of Sonora, Mexico, representing the first regional study in Sonora in air quality. The assessment used performance indicators and indicators of compliance with the regulations. It is established that in all the cities the maximum limit value of daily concentration of 210 μg/m3 is exceeded, being the percentage of days above the rule of 30%, 78%, 76%, 6%, 3% and 62% for Agua Prieta, Nogales, Puerto Penasco, Hermosillo, Guaymas and Obregón respectively, classifying these days with poor air quality. According to the annualized index used, the air quality was not satisfactory for the period of study in the six cities. Nogales and Puerto Penasco presented the most adverse conditions of air quality with annual average values of TSP of 363 and 345 μg/m3 and maximum daily of 1047 and 1239 μg/m3 (498% and 590% above the norm) respectively. The requirements of coverage that establishes the Mexican Official Standard NOM-025-SSA1-1993 (SSA, 2005) are questioned for its compliance, proposing in this paper a criterion of non-compliance by prioritizing the protection of health and the precautionary principle. It is recommended to implement air quality management programs (PROAIRE) in these cities.展开更多
Air pollution is a problem that directly affects human health,the global environment and the climate.The air quality index(AQI)indicates the degree of air pollution and effect on human health;however,when assessing ai...Air pollution is a problem that directly affects human health,the global environment and the climate.The air quality index(AQI)indicates the degree of air pollution and effect on human health;however,when assessing air pollution only based on AQI monitoring data the fact that the same degree of air pollution is more harmful in more densely populated areas is ignored.In the present study,multi-source data were combined to map the distribution of the AQI and population data,and the analyze their pollution population exposure of Beijing in 2018 was analyzed.Machine learning based on the random forest algorithm was adopted to calculate the monthly average AQI of Beijing in 2018.Using Luojia-1 nighttime light remote sensing data,population statistics data,the population of Beijing in 2018 and point of interest data,the distribution of the permanent population in Beijing was estimated with a high precision of 200 m×200 m.Based on the spatialization results of the AQI and population of Beijing,the air pollution exposure levels in various parts of Beijing were calculated using the population-weighted pollution exposure level(PWEL)formula.The results show that the southern region of Beijing had a more serious level of air pollution,while the northern region was less polluted.At the same time,the population was found to agglomerate mainly in the central city and the peripheric areas thereof.In the present study,the exposure of different districts and towns in Beijing to pollution was analyzed,based on high resolution population spatialization data,it could take the pollution exposure issue down to each individual town.And we found that towns with higher exposure such as Yongshun Town,Shahe Town and Liyuan Town were all found to have a population of over 200000 which was much higher than the median population of townships of51741 in Beijing.Additionally,the change trend of air pollution exposure levels in various regions of Beijing in 2018 was almost the same,with the peak value being in winter and the lowest value being in summer.The exposure intensity in population clusters was relatively high.To reduce the level and intensity of pollution exposure,relevant departments should strengthen the governance of areas with high AQI,and pay particular attention to population clusters.展开更多
文摘BACKGROUND Type 1 diabetes originates from gene-environment interactions,with increasing incidence over time.AIM To identify correlates of childhood type 1 diabetes in European countries using an ecological approach.Several environmental variables potentially influencing the onset of type 1 diabetes have been previously evaluated.However,the relationships between epidemiologic data and exposure to toxic airborne molecules are scarcely studied.METHODS We employed an ecological model to explore,in a wide time period(1990-2018),associations between type 1 diabetes incidence in 19 European countries(systematic literature review)and the nationwide production of five widely diffused air pollutants:particulate matter<10μm(PM10),nitrogen oxides(NO),non-methane volatile organic compounds(VOCs),sulphur oxide(SO2),and ammonia.RESULTS Data confirm a raising incidence of type 1 diabetes in 18 out of 19 explored countries.The average difference(last vs first report,all countries)was+6.9×100000/year,with values ranging from-1.4(Germany)to+16.6(Sweden)per 100000/year.Although the overall production of pollutants decreased progressively from 1990 to 2018,type 1 diabetes incidence was positively associated with the nationwide emissions of PM10,VOCs,and NO but not with those of SO2 and ammonia.Type 1 diabetes incidence was significantly higher in countries with high emissions than in those with low emissions of PM10(27.5±2.4 vs 14.6±2.4×100000 residents,respectively),VOCs(24.5±4.4 vs 13.2±1.7×100000 residents,respectively),and NO(26.6±3 vs 13.4±2.4×100000 residents,respectively),but not of SO2 or ammonia.CONCLUSION Evidence justify further studies to explore better links between long-term air quality and type 1 diabetes onset at the individual level,which should include exposures during pregnancy.In this respect,type 1 diabetes could be,at least in part,a preventable condition.Thus,primary prevention policies acting through a marked abatement of pollutant emissions might attenuate future type 1 diabetes incidence throughout Europe.
文摘NIKE AIR FORCE 1是NIKE各种鞋类中拥有最大专营模式的系列。从纽约到北京，AIR FORCE 1都是在街头巷尾最热门的鞋款。AIR FORCE 1是以篮球鞋来体现街头HIP HOP精神的典范。在这25年中，有超过1700双不同版本的AIR FORCE 1被制造出来．而AF1的大型庆祝活动将贯穿2007年的春夏秋冬。就在2007年逐步走到年底的时候．NIKE再次重拳出击。推出了SERATO AIR FORCE 1PACK。
基金supported by the Institute of Engineering of the Autonomous University of Baja California,also by to the Industrial Environmental Engineering Program of the Sonora State University,and the Division of Engineering,Department of Chemical Engineering and Metallurgy of the University of Sonora.
文摘In the present study, the air quality is assessed for the year 2010 regarding to the Total Suspended Particles (TSP) for six cities of Sonora, Mexico, representing the first regional study in Sonora in air quality. The assessment used performance indicators and indicators of compliance with the regulations. It is established that in all the cities the maximum limit value of daily concentration of 210 μg/m3 is exceeded, being the percentage of days above the rule of 30%, 78%, 76%, 6%, 3% and 62% for Agua Prieta, Nogales, Puerto Penasco, Hermosillo, Guaymas and Obregón respectively, classifying these days with poor air quality. According to the annualized index used, the air quality was not satisfactory for the period of study in the six cities. Nogales and Puerto Penasco presented the most adverse conditions of air quality with annual average values of TSP of 363 and 345 μg/m3 and maximum daily of 1047 and 1239 μg/m3 (498% and 590% above the norm) respectively. The requirements of coverage that establishes the Mexican Official Standard NOM-025-SSA1-1993 (SSA, 2005) are questioned for its compliance, proposing in this paper a criterion of non-compliance by prioritizing the protection of health and the precautionary principle. It is recommended to implement air quality management programs (PROAIRE) in these cities.
基金Under the auspices of National Natural Science Foundation of China (No.42071342,31870713,42171329)Natural Science Foundation of Beijing,China (No.8222069,8222052)。
文摘Air pollution is a problem that directly affects human health,the global environment and the climate.The air quality index(AQI)indicates the degree of air pollution and effect on human health;however,when assessing air pollution only based on AQI monitoring data the fact that the same degree of air pollution is more harmful in more densely populated areas is ignored.In the present study,multi-source data were combined to map the distribution of the AQI and population data,and the analyze their pollution population exposure of Beijing in 2018 was analyzed.Machine learning based on the random forest algorithm was adopted to calculate the monthly average AQI of Beijing in 2018.Using Luojia-1 nighttime light remote sensing data,population statistics data,the population of Beijing in 2018 and point of interest data,the distribution of the permanent population in Beijing was estimated with a high precision of 200 m×200 m.Based on the spatialization results of the AQI and population of Beijing,the air pollution exposure levels in various parts of Beijing were calculated using the population-weighted pollution exposure level(PWEL)formula.The results show that the southern region of Beijing had a more serious level of air pollution,while the northern region was less polluted.At the same time,the population was found to agglomerate mainly in the central city and the peripheric areas thereof.In the present study,the exposure of different districts and towns in Beijing to pollution was analyzed,based on high resolution population spatialization data,it could take the pollution exposure issue down to each individual town.And we found that towns with higher exposure such as Yongshun Town,Shahe Town and Liyuan Town were all found to have a population of over 200000 which was much higher than the median population of townships of51741 in Beijing.Additionally,the change trend of air pollution exposure levels in various regions of Beijing in 2018 was almost the same,with the peak value being in winter and the lowest value being in summer.The exposure intensity in population clusters was relatively high.To reduce the level and intensity of pollution exposure,relevant departments should strengthen the governance of areas with high AQI,and pay particular attention to population clusters.
