大气颗粒物与居民脑卒中发作 或死亡之间关系的Meta分析

目的 研究大气颗粒物污染(PM10、PM25)与居民脑卒中发作或死亡之间的关系.方法 检索文献数据库,应用Meta分析法对符合文献纳入标准的16个有关大气颗粒物与居民脑卒中每日发作或死亡关系的定量研究进行综合分析.根据异质性检验结果选用固定效应模型或随机效应模型,采用大气颗粒物每上升10 μg/m3,居民脑卒中死亡的危险度(OR)为效应值进行效应值合并,做敏感性分析.结果 PM10浓度每上升10 μg/m3,居民脑卒中发作的OR=1.011(95%CI:1.001～1.021),即发作增加1.09%(95%CI:0.10%～2.08%),死亡的OR=1.007(95%CI:1.006～1.008),即死亡增加0.70%(95%CI:0.60%～0.80%),说明PM10浓度上升与居民脑卒中发作或死亡均有统计学相关,敏感性分析结果均稳定;PM25浓度每上升10 μg/m3,居民脑卒中发作的OR=1.001(95%CI:0.992～1.010),死亡的OR=1.052(95%CI:0.958～1.154).结论 研究结果表明PM10的空气污染对居民脑卒中发作率和死亡率的增加有统计学相关,PM25浓度增高与脑卒中发作或死亡无统计学相关.     

镇江市大气颗粒物（PM10和PM2.5）对居民每日死亡率影响的时间序列分析

目的评价镇江市大气颗粒物(PM10和PM2.5)短期暴露对居民每日死亡率的影响。方法采用基于广义相加模型的时间序列分析方法评估大气颗粒物对镇江市居民死亡率的影响。结果 PM10和PM2.5对人群死亡影响存在滞后效应和累积滞后效应,对女性和≥65岁人群的影响更为显著。PM10和PM2.5分别在累积滞后1 d和2 d时效应最大,PM10和PM2.5每升高10μg/m3,居民死亡率分别增加0.52%(95%CI:0.10%～0.94%)和0.79%(95%CI:0.14%～1.43%)。结论镇江市大气颗粒物与居民的超额死亡风险显著相关。     

石家庄市大气颗粒物对居民循环系统疾病死亡的寿命损失年影响的研究

目的 探讨石家庄市大气颗粒物(PM₁₀、PM_2.5 )对居民每日循环系统疾病死亡和寿命损失年(YLL)的影响。方法收集石家庄市2018年1月1日—2021年12月31日的每日大气颗粒物、气象资料及循环系统死亡数据,计算每日YLL值,利用广义相加模型评估大气颗粒物对居民每日循环系统疾病死亡和YLL的影响。结果 研究期间,石家庄市PM₁₀、PM_2.5 浓度每升高10μg/m3对每日循环系统疾病死亡的效应最大值分别出现在lag02、lag0,分别为0.37%(95%CI:0.09%～0.64%)、0.61%(95%CI:0.18%～1.04%)。PM₁₀、PM_2.5 每升高10μg/m3,分别导致每日YLL增加1.07年(95%CI:0.06～2.09)、1.73年(95%CI:0.15～3.32)。双污染物模型中,PM10及PM_2.5 均具有独立的健康效应。性别分层结果显示,PM₁₀、PM_2.5...     

银川市大气颗粒物对人群循环系统疾病死亡影响的时间序列分析

目的探讨银川市大气颗粒物污染水平及其对居民循环系统疾病死亡的暴露-反应关系。方法通过收集银川市2013—2015年空气质量监测数据、气象监测数据和居民死亡监测资料,采用广义相加模型,分析银川市大气颗粒物物对与居民循环系统疾病死亡的暴露-反应关系。结果大气PM_(10)和PM_(2.5)年均浓度均超过GB 3095—2012《环境空气质量标准》二级标准。大气PM_(10)和PM_(2.5)浓度每升高10μg/m~3对人群循环系统疾病死亡的超额危险度分别为0.56%(95%CI:0.15%~0.97%),1.33%(95%CI:0.46%~2.21%);大气PM_(10)和PM_(2.5)浓度对小于65岁组的循环系统疾病死亡的影响无统计学意义(P0.05),对65岁以上年龄组人群循环系统疾病死亡的超额危险度分别在滞后7、5 d时达到最大效应,分别为1.24%(95%CI:0.21%~2.28%)和0.57%(95%CI:0.08%~1.06%);大气PM_(10)、PM_(2.5)浓度对女性循环系统疾病死亡的超额危险度高于男性。结论研究期间银川市大气颗粒物浓度较高,且对人群循环系统疾病死亡存在一定的暴露-反应关系。     

天津市可吸人颗粒物与城区居民每日死亡关系的时间序列分析

目的 研究天津市大气可吸入颗粒物(PM10)与城区居民每日死亡间的相关性.方法 通过收集天津市城区2005-2007年空气污染数据、日平均气温和相对湿度及每日死亡人数,采用广义相加模型,控制长期和季节趋势、气温和相对湿度等气象因素及二氧化硫(SO2)和二氧化氮(NO2)等气态污染物的影响,分析天津市PM10与居民每日死亡之间的关系.结果 大气PM10与人群每日非意外死亡、循环系统疾病死亡和呼吸系统疾病死亡间显著相关.PM10浓度每升高10 μg/m3,人群每日非意外死亡、循环系统疾病死亡和呼吸系统疾病死亡分别增加0.45%(0.21～0.69)、0.60%(0.29～0.91)和0.82%(0.04～1.61).结论 天津市大气PM10污染与城区居民每日死亡显著相关,尤其是循环系统疾病和呼吸系统疾病死亡.     

大气颗粒物污染与脑卒中死亡的病例交叉研究

目的 评价大气颗粒物污染对人群脑卒中死亡的急性效应.方法 采用时间分层的病例交叉设计,分析杭州市2002-2004年间大气可吸入颗粒物(PM10)日平均浓度短期增加与人群每日脑卒中死亡的关系,同时分析其他气态污染物(NO2和SO2)的急性健康效应.结果共纳入9906例脑卒中死亡病例,粗死亡率约为83.54/10万.调整气象因素后,3 d内PM10、SO2和NO2日平均浓度每增加10μg/m3,人群脑卒中死亡则分别增加0.56%(95%CI:0.14%～0.99%)、1.62%(95%CI:0.26%～3.01%)和2.07%(95%CI:0.54%～3.62%).多污染物模型中未见有统计学意义的关联.敏感性分析结果显示进行缺失值填补后,单污染物模型中均有关联效应,多污染物模型中则无统计学意义的关联.结论大气颗粒物污染以及SO2和NO2污染物浓度短期升高均与脑卒中死亡增加存在一定关联.     

我国大气可吸入颗粒物污染对人群死亡率的影响

目的 综合相关文献并以暴露-反应关系的形式探讨中国可吸入颗粒物( PM10)污染对人群死亡率的影响.方法 收集符合纳入标准的中国大气颗粒物污染与居民总死亡率、心脑血管疾病死亡率、呼吸系统疾病死亡率关系的文献,共纳入21篇文献.采用Stata9.0软件进行统计分析,提取PM10与人群死亡率的暴露-反应系数,利用固定或随机效应模型合并效应值,并对结果进行敏感性分析、发表偏倚检验与校正.结果 我国大气PM10每上升10 μg/m3,人群每日总死亡率、心脑血管疾病和呼吸系统疾病死亡率的相对危险度(RR)分别为1.0033(95％ CI:1.0022～1.0044)、1.0045(95％ CI:1.0029 ～1.0062)和1.0056(95％CI:1.0033～1.0079);校正发表偏倚后,人群每日总死亡率、心脑血管疾病和呼吸系统疾病死亡率的RR值降为1.0012(95％CI:1.0002～1.0022)、1.0011(95％ CI:0.9996～1.0026)和1.0023(95％ CI:1.0001～1.0045).结论 大气中PM10浓度的上升会导致我国人群每日总死亡率、心脑血管疾病死亡率和呼吸系统疾病死亡率的增加.     

可吸入大气颗粒物污染与居民每日死亡关系的Meta分析

目的综合分析国内外可吸入大气颗粒物（PM10）短期暴露与人群死亡关系的流行病学资料,以获取大气PM10污染与居民死亡的暴露-反应关系。方法在计算机联机检索文献和手工检索的基础上,对近十年来发表的相关研究文献采用meta分析的方法进行综合评价,并检验、校正可能存在的发表偏倚,从而准确、定量地确定PM10污染与居民死亡的暴露-反应关系。结果建立了居民短期接触大气PM10污染的暴露一反应关系,即在未考虑发表偏倚的情况下,大气中PM10每增加1130μg／m3,居民死亡的相对危险度增加3．87％（95％CI：2．84％～5．02％）,在校正了发表偏倚后大气中PM10每增加100μg／m3,死亡的相对危险度增加下降为1．41％（95％CI：0．30％-2．43％）,与考虑偏倚前相比下降了63．6％。结论本研究建立的暴露-反应关系较早注意到发表偏倚的影响,具有一定的代表性与科学性,可用于大气颗粒物暴露健康危险度评价工作参考,为制定相关环境决策提供科学依据。     

石家庄市PM2.5浓度对居民死亡的急性影响分析

目的 了解石家庄市PM2.5污染特征及其对居民死亡率的影响。方法 收集2013 - 2015年该市逐日大气PM2.5浓度、平均气温、平均相对湿度和居民的死亡数据,利用广义相加模型分析PM2.5日均浓度和居民死亡的关系。结果 研究期间石家庄市日均非意外死亡32人,其中循环系统疾病死亡17人,呼吸系统疾病死亡5人;PM2.5浓度范围为6.3～771.3 μg/m3,平均浓度为118.8 μg/m3。时间序列分析结果表明,该市大气PM2.5浓度每升高10 μg/m3,居民非意外总死亡（lag05）、循环系统疾病死亡（lag05）和呼吸系统疾病死亡（lag1）的风险分别增加0.73%（95%CI:0.42%～1.04%）、1.04%（95%CI:0.64%～1.46%）和0.63%（95%CI:0.07%～1.19%）。结论 石家庄市大气PM2.5浓度的升高可能导致居民非意外总死亡,尤其是循环系统疾病和呼吸系统疾病死亡的增加。     

空气污染物与绿化环境暴露水平对心肌梗塞死亡交互作用的病例交叉研究

目的 探索空气污染物与绿化暴露水平对心梗死亡的发生所产生的交互作用。方法 主要收集天津市2017—2019年因心梗死亡的个案病例,估计每名病例环境因素的暴露水平,采用条件logistic回归模型,分析空气污染物与绿化暴露水平对心梗死亡的发生所产生的交互作用。结果 在不同的季节,空气污染物浓度、气象因素和绿化环境暴露水平存在着差异（P＜0.001）。在单污染物模型中,每升高10 μg/m3的NO2（lag2期）,可使心梗死亡发生的风险升高0.4%（OR = 1.004,95%CI:1.000～1.008）。在多污染物模型中,每升高10 μg/m3的NO2（lag2期）、PM2.5（lag2期）和PM10（lag6期）,可使心梗死亡发生的风险升高1.1%（OR = 1.011,95%CI:1.005～1.018）、0.4%（OR = 1.004,95%CI:1～1.008）和0.3%（OR = 1.003,95%CI: 1.000～1.006）。对于滞后期lag1、lag2、lag6和lag7的暴露水平来说,颗粒污染物［可入肺颗粒物（PM1）、PM2.5 和PM10］与绿化环境暴露水平对心梗死亡的发生具有拮抗作用。结论 绿化环境可以起到降低颗粒污染物升高心梗死亡风险的作用,为指导人们有效的防护空气污染的危害,减轻颗粒污染物对心梗以及其他心血管疾病的发生和死亡提供依据。     

Association between ambient particulate matter and daily cause-specific mortality in Tanggu,Tianjin Binhai New Area,China

The aim of the study was to determine whether the area of Tanggu, Tianjin Binhai New Economic Developing Area, China, is subject to similar effects of ambient particulate matter less than 10 micrometres in aerodynamic diameter (PM10) similar to other areas of China. This study was designed to investigate cause-specific mortality risks associated with air pollution in this geographical region. The present study used a time-series analysis to explore the relationship between PM10 and the cause-specific mortalities for non-accidental, cardiovascular, and cardiopulmonary mortality from 1 January 2006 to 31 December 2010. A 10 μg/m³ increment of PM10 was associated with a 1.02% (95% confidence interval (CI): 0.48, 1.56) increase in cardiovascular mortality, and a 0.88% (95% CI: 0.36, 1.39) increase in cardiopulmonary mortality. In addition, the effects from PM10 appear to be consistent with multi-pollutant models. The results show that there are strong associations between daily cardiovascular and cardiopulmonary mortality and ambient PM10 exposure.     

Seasonal variation of chemical species associated with short-term mortality effects of PM(2.5) in Xi'an, a Central City in China

The authors conducted a time-series analysis to examine seasonal variation of mortality risk in association with particulate matter less than 2.5 μm in aerodynamic diameter (PM(2.5)) and chemical species in Xi'an, China, using daily air pollution and all-cause and cause-specific mortality data (2004-2008). Poisson regression incorporating natural splines was used to estimate mortality risks of PM(2.5) and its chemical components, adjusting for day of the week, time trend, and meteorologic effects. Increases of 2.29% (95% confidence interval: 0.83, 3.76) for all-cause mortality and 3.08% (95% confidence interval: 0.94, 5.26) for cardiovascular mortality were associated with an interquartile range increase of 103.0 μg/m(3) in lagged 1-2 day PM(2.5) exposure. Stronger effects were observed for the elderly (≥65 years), males, and cardiovascular diseases groups. Secondary components (sulfate and ammonium), combustion species (elemental carbon, sulfur, chlorine), and transition metals (chromium, lead, nickel, and zinc) appeared most responsible for increased risk, particularly in the cold months. The authors concluded that differential association patterns observed across species and seasons indicated that PM(2.5)-related effects might not be sufficiently explained by PM(2.5) mass alone. Future research is needed to examine spatial and temporal varying factors that might play important roles in modifying the PM(2.5)-mortality association.     

Association of daily cause-specific mortality with ambient particle air pollution in Wuhan, China

In Asia, limited literature has been published on the association between daily mortality and ambient air pollution. We examined the associations of daily cause-specific mortality with daily mean concentrations of particulate matter (PM) with a mass median aerodynamic diameter less than 10 microm (PM(10)) in Wuhan, China using 4 years of data (2001-2004). There are approximately 4.5 million residents in Wuhan who live in the city core area of 201 km(2) where air pollution levels are higher and pollution ranges are wider than the majority of cities in the published literature. We use quasi-likelihood estimation within the context of the generalized additive models (GAMs) (natural spline (NS) models in R) to model the natural logarithm of the expected daily death counts as a function of the predictor variables. We found consistent PM(10) effects on mortality with the strongest effects on lag 0 day. Every 10 microg/m(3) increase in PM(10) daily concentration at lag 0 day was significantly associated with an increase in non-accidental (0.36%; 95% CI 0.19-0.53%), cardiovascular (0.51%; 95% CI 0.28-0.75%), stroke (0.44%; 95% CI 0.16-0.72%), cardiac (0.49%; 95% CI 0.08-0.89%), respiratory (0.71%; 95% CI 0.20-1.23%), and cardiopulmonary (0.46%; 95% CI 0.23-0.69%). In general, these effects were stronger among the elderly (65 years > or = 45 years) than among the young. The exploration of exposure-response relationships between PM(10) and cause-specific mortality suggests the appropriateness of assuming linear relationships, where the PM(10) concentration in Wuhan ranged from 24.8 to 477.8 microg/m(3). We conclude that there is consistent evidence of acute effects of PM(10) on cardiopulmonary mortality. A linear no threshold exposure-response relationship is suggested between PM(10) and the studied cause-specific mortality.     

Associations between mortality and air pollution in central Europe

Increased mortality has been observed in association with elevated concentrations of air pollutants in European cities and in the United States. We reassessed the effects of particulate matter in Central Europe. Mortality and air pollution data were obtained for a highly polluted region of the Czech Republic and a rural region in Germany. Poisson regression analyses were conducted considering trend, season, meteorology, and influenza epidemics as confounders in both a parametric and a nonparametric approach. The Czech Republic had a 3.8% increase in mortality [95% confidence interval (CI), 0.8-6.9%] in association with 100 microg/m(3) total suspended particles (TSP) (lagged 2 days) for the time period 1982-1994. During the last 2 years of study, 68% of the TSP consisted of particulate matter [less than/equal to] 10 microm in aerodynamic diameter (PM(10)). An increase of 100 microg/m(3) TSP (lagged 1 day) was associated with a 9.5% increase in mortality (CI, 1.2-18.5%) and 100 microg/m(3) PM(10 )(lagged 1 day) showed a 9.8% increase in mortality (CI, 0.7-19.7%). We found no evidence for an association between mortality and particulate matter in the rural area in Germany at the Czech border. Data from the coal basin in the Czech Republic suggested an increase in mortality associated with the concentration of particulate matter in a highly polluted setting in Central Europe that is consistent with the associations observed in other western European cities and in the United States.     

天津市大气气态污染物与居民每日死亡关系的时间序列分析

目的 研究天津市大气气态污染物二氧化硫(SO2)和二氧化氮(NO2)与城区居民每日死亡间的相关性.方法 收集天津市城区2005-2007年大气主要污染物[SO2、NO2和可吸入颗粒物(PM10)]日平均浓度、日平均气温和相对湿度以及每日死因别死亡人数,采用广义相加模型,控制长期和季节趋势、气温和相对湿度等气象因素的影响,探讨SO2和NO2日平均浓度与每日死因别死亡间的相关性,分析PM10及模型参数对其相对危险度估计的影响.结果 大气SO2和NO2与人群每日非意外死亡和循环系统疾病死亡间显著相关,与呼吸系统疾病间无显著关联.SO2浓度每升高10μg/m3,人群非意外死亡和循环系统疾病死亡分别增加0.56%(0.23%～0.89%)和0.49%(0.06%～0.93%);NO2浓度每升高10 μg/m3,人群非意外死亡和循环系统疾病死亡分别增加0.94%(0.17%～1.70%)和1.29%(0.29%～2.30%).结论 天津市大气SO2和NO2污染与城区居民每日非意外死亡和循环系统疾病死亡显著相关.     

Is the association of airborne particles with daily deaths confounded by gaseous air pollutants? An approach to control by matching.

Although particulate air pollution has been associated with increased numbers of daily deaths in dozens of cities around the world, issues still remain about the association. Some have questioned the complex modeling used to control for season in Poisson regression or the role of gaseous air pollutants as potential confounders of the association. I examined the association between deaths and particulate matter with an aerodynamic diameter less than or equal to 10 microm (PM10) using a case-crossover design. In this approach, the pollution on the day of each death is contrasted with the pollution level on control days when the subject did not die. Season and gaseous air pollutants were controlled by matching. Control days were chosen within the same month of the same year to control for season, and matched on either sulfur dioxide (SO2; within 1 ppb), nitrogen dioxide (within 1 ppb), maximum ozone (within 2 ppb), or carbon monoxide (within 0.03 ppm). The analysis was conducted in 14 U.S. cities that have daily PM10 monitoring. After matching, there were about 400,000 deaths in each analysis. Results were combined across cities using a maximum likelihood method. PM10 was a significant predictor of mortality when controlling for gaseous air pollutants, with effect sizes ranging from a 0.45% increase per 10 microg/m3 increment of PM10 [95% confidence interval (CI), 0.12-0.79%] when matched on maximum hourly ozone levels, to a 0.81% increase per 10 microg/m3 increment of PM10 (95% CI, 0.47-1.16%) when matched on 24-hr average SO2.     

Time series analysis of personal exposure to ambient air pollution and mortality using an exposure simulator

This paper describes a modeling framework for estimating the acute effects of personal exposure to ambient air pollution in a time series design. First, a spatial hierarchical model is used to relate Census tract-level daily ambient concentrations and simulated exposures for a subset of the study period. The complete exposure time series is then imputed for risk estimation. Modeling exposure via a statistical model reduces the computational burden associated with simulating personal exposures considerably. This allows us to consider personal exposures at a finer spatial resolution to improve exposure assessment and for a longer study period. The proposed approach is applied to an analysis of fine particulate matter of <2.5?μm in aerodynamic diameter (PM(2.5)) and daily mortality in the New York City metropolitan area during the period 2001-2005. Personal PM(2.5) exposures were simulated from the Stochastic Human Exposure and Dose Simulation. Accounting for exposure uncertainty, the authors estimated a 2.32% (95% posterior interval: 0.68, 3.94) increase in mortality per a 10?μg/m(3) increase in personal exposure to PM(2.5) from outdoor sources on the previous day. The corresponding estimates per a 10?μg/m(3) increase in PM(2.5) ambient concentration was 1.13% (95% confidence interval: 0.27, 2.00). The risks of mortality associated with PM(2.5) were also higher during the summer months.     

上海市A城区大气PM_(10)、PM_(2.5)污染与居民日死亡数的相关分析

目的　探讨大气颗粒物污染对人群健康的影响。方法　采用Poisson广义相加模型对上海市A城区大气PM1 0 、PM2 5的日平均污染浓度与居民日死亡数进行相关回归分析 ,并控制了时间长期趋势、气象、季节、一周日效应混杂因素的影响。结果　当大气PM1 0 、PM2 5浓度上升 10 μg m3时 ,总死亡数分别上升 0 5 3%(0 2 2 %～ 0 85 % )、0 85 % (0 32 %～ 1 39% )。结论　大气粗细颗粒物污染具有潜在的急性人群健康危害。     

佳木斯市大气PM10对呼吸系统疾病日人院人数的影响

目的 探讨2010-2014年佳木斯市大气PM10对城区居民呼吸系统疾病日入院人数的影响.方法 采用1∶3配比的时间分层病例交叉研究,控制气象等因素的影响,以条件logistic回归分析佳木斯市2010年1月1日-2014年12月31日大气PM10浓度与呼吸系统疾病日入院人数的关系,并按性别(男、女)、年龄(＜15岁、15～65岁、＞65岁)和疾病类型[肺炎、慢性阻塞性肺疾病(COPD)和支气管肺炎],对大气污染物的健康效应进行分层分析.结果 研究期间佳木斯市大气PM10的日均浓度及年均浓度均低于国家二级标准.大气PM10日均浓度与SO2、NO2、日均气压呈正相关,与日均温度呈负相关,差异均有统计学意义(P＜O.01).单污染物模型显示,研究期间大气PM10浓度每升高10μg/m3,与肺炎、COPD日入院人数的OR值分别在滞后4、3d达到最高,相应的OR值(95％CI)分别为1.021(1.002～1.041),1.022(1.004～1.040),均有统计学意义(P＜0.05);在控制气温、相对湿度、气压的影响后,多污染物模型显示,大气PM10浓度每升高10 μg/m3,仍会增加肺炎、COPD日入院人数,均有统计学意义(P＜0.05).性别分层结果显示,大气PM10浓度每升高10 μg/m3,可引起男性肺炎患者及男、女性COPD患者日入院人数增加,差异均有统计学意义(P＜0.05);年龄分层结果显示,大气PM10浓度每升高10μg/m3,可引起＜15岁、15～65岁、＞65岁肺炎、COPD、支气管肺炎患者日入院人数增加,差异均有统计学意义(P＜0.05).结论 佳木斯市呼吸系统常见疾病的日入院人数增加可能与该市大气PM10短期低浓度暴露有关联.     

Confounding and effect modification in the short-term effects of ambient particles on total mortality: results from 29 European cities within the APHEA2 project

We present the results of the Air Pollution and Health: A European Approach 2 (APHEA2) project on short-term effects of ambient particles on mortality with emphasis on effect modification. We used daily measurements for particulate matter less than 10 microm in aerodynamic diameter (PM10) and/or black smoke from 29 European cities. We considered confounding from other pollutants as well as meteorologic and chronologic variables. We investigated several variables describing the cities' pollution, climate, population, and geography as potential effect modifiers. For the individual city analysis, generalized additive models extending Poisson regression, using a smoother to control for seasonal patterns, were applied. To provide quantitative summaries of the results and explain remaining heterogeneity, we applied second-stage regression models. The estimated increase in the daily number of deaths for all ages for a 10 microg/m3 increase in daily PM10 or black smoke concentrations was 0.6% [95% confidence interval (CI) = 0.4-0.8%], whereas for the elderly it was slightly higher. We found important effect modification for several of the variables studied. Thus, in a city with low average NO2, the estimated increase in daily mortality for an increase of 10 microg/m3 in PM10 was 0.19 (95% CI = 0.00-0.41), whereas in a city with high average NO2 it was 0.80% (95% CI = 0.67-0.93%); in a relatively cold climate the corresponding effect was 0.29% (95% CI = 0.16-0.42), whereas in a warm climate it was 0.82% (95% CI = 0.69-0.96); in a city with low standardized mortality rate it was 0.80% (95% CI = 0.65-0.95%), and in one with a high rate it was 0.43% (95% CI = 0.24-0.62). Our results confirm those previously reported on the effects of ambient particles on mortality. Furthermore, they show that the heterogeneity found in the effect parameters among cities reflects real effect modification, which is explained by specific city characteristics.