The effects of particulate matter sources on daily mortality: a case-crossover study of Barcelona, Spain.
Ontology highlight
ABSTRACT: Background
Dozens of studies link acute exposure to particulate matter (PM) air pollution with premature mortality and morbidity, but questions remain about which species and sources in the vast PM mixture are responsible for the observed health effects. Although a few studies exist on the effects of species and sources in U.S. cities, European cities-which have a higher proportion of diesel engines and denser urban populations-have not been well characterized. Information on the effects of specific sources could aid in targeting pollution control and in articulating the biological mechanisms of PM.Objectives
Our study examined the effects of various PM sources on daily mortality for 2003 through 2007 in Barcelona, a densely populated city in the northeast corner of Spain.Methods
Source apportionment for PM ≤ 2.5 μm and ≤ 10 µm in aerodynamic diameter (PM2.5 and PM10) using positive matrix factorization identified eight different factors. Case-crossover regression analysis was used to estimate the effects of each factor.Results
Several sources of PM2.5, including vehicle exhaust, fuel oil combustion, secondary nitrate/organics, minerals, secondary sulfate/organics, and road dust, had statistically significant associations (p < 0.05) with all-cause and cardiovascular mortality. Also, in some cases relative risks for a respective interquartile range increase in concentration were higher for specific sources than for total PM2.5 mass.Conclusions
These results along with those from our multisource models suggest that traffic, sulfate from shipping and long-range transport, and construction dust are important contributors to the adverse health effects linked to PM.
SUBMITTER: Ostro B
PROVIDER: S-EPMC3261985 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Background: Exposure to fine particulate matter (PM2.5) during wildfire seasons has been associated with adverse health outcomes. Previous studies have focused on daily exposure, but PM2.5 levels in smoke events can vary considerably within 1 d.Objectives: We aimed to assess the immediate and lagged relationship between sub-daily exposure to PM2.5 and acute health outcomes during wildfire seasons in British Columbia.Methods: We used a time-stratified case-crossover study design to evaluate the association between modeled hourly PM2.5 and ambulance dispatches during wildfire seasons from 2010 to 2015. Distributed lag nonlinear models were used to estimate the lag-specific and cumulative odds ratios (ORs) at lags from 1 to 48 h. We examined the relationship for all dispatches and dispatches related to respiratory, circulatory, and diabetic conditions, identified by codes for ambulance dispatch (AD), paramedic assessment (PA) or hospital diagnosis (HD).Results: Increased respiratory health outcomes were observed within 1 h of exposure to a 10-?g/m3 increase in PM2.5. The 48-h cumulative OR [95% confidence interval (CI)] was 1.038 (1.009, 1.067) for the AD code Breathing Problems and 1.098 (1.013, 1.189) for PA code Asthma/COPD. The point estimates were elevated within 1 h for the PA code for Myocardial Infarction and HD codes for Ischemic Heart Disease, which had 24-h cumulative ORs of 1.104 (0.915, 1.331) and 1.069 (0.983, 1.162), respectively. The odds of Diabetic AD and PA codes increased over time to a cumulative 24-h OR of 1.075 (1.001, 1.153) and 1.104 (1.015, 1.202) respectively.Conclusions: We found increased PM2.5 during wildfire seasons was associated with some respiratory and cardiovascular outcomes within 1 h following exposure, and its association with diabetic outcomes increased over time. Cumulative effects were consistent with those reported elsewhere in the literature. These results warrant further investigation and may have implications for the appropriate time scale of public health actions. https://doi.org/10.1289/EHP5792.
| S-EPMC7313403 | biostudies-literature
Project description:BackgroundSeasonal variation and regional heterogeneity have been observed in the estimated effect of fine particulate matter (PM2.5) mass on mortality. Differences in the chemical compositions of PM2.5 may cause this variation. We investigated the association of the daily concentration of PM2.5 components with mortality in Nagoya, Japan.MethodsWe combined daily mortality counts for all residents aged 65 years and older with concentration data for PM2.5 mass and components in Nagoya from April 2003 to December 2007. A time-stratified case-crossover design was used to examine the association of daily mortality with PM2.5 mass and each component (chloride, nitrate, sulfate, sodium, potassium, calcium, magnesium, ammonium, elemental carbon [EC], and organic carbon [OC]).ResultsWe found a stronger association between mortality and PM2.5 mass in transitional seasons. In analysis for each PM2.5 component, sulfate, nitrate, chloride, ammonium, potassium, EC, and OC were significantly associated with mortality in a single-pollutant model. In a multi-pollutant model, an interquartile range increase in the concentration of sulfate was marginally associated with an increase in all-cause mortality of 2.1% (95% confidence interval, -0.1 to 4.4).ConclusionsThese findings suggest that some specific PM components have a more hazardous effect than others and contribute to seasonal variation in the health effects of PM2.5.
| S-EPMC4848323 | biostudies-literature
Project description:BackgroundOutbreaks of Saharan-Sahel dust over Euro-Mediterranean areas frequently induce exceedances of the Europen Union's 24-hr standard of 50 ?g/m3 for particulate matter (PM) with aerodynamic diameter ? than 10 ?m (PM10).ObjectivesWe evaluated the effect of Saharan dust on the association between different PM fractions and daily mortality in Rome, Italy.MethodsIn a study of 80,423 adult residents who died in Rome between 2001 and 2004, we performed a time-series analysis to explore the effects of PM2.5, PM2.5-10, and PM10 on natural, cardiac, cerebrovascular, and respiratory mortality. We defined Saharan dust days by combining light detection and ranging (LIDAR) observations and analyses from operational models. We tested a Saharan dust-PM interaction term to evaluate the hypothesis that the effects of PM, especially coarse PM (PM2.5-10), on mortality would be enhanced on dust days.ResultsInterquartile range increases in PM2.5-10 (10.8 ?g/m3) and PM10 (19.8 ?g/m3) were associated with increased mortality due to natural, cardiac, cerebrovascular, and respiratory causes, with estimated effects ranging from 2.64% to 12.65% [95% confidence interval (CI), 1.18-25.42%] for the association between PM2.5-10 and respiratory mortality (0- to 5-day lag). Associations of PM2.5-10 with cardiac mortality were stronger on Saharan dust days (9.73%; 95% CI, 4.25-15.49%) than on dust-free days (0.86%; 95% CI, -2.47% to 4.31%; p = 0.005). Saharan dust days also modified associations between PM10 and cardiac mortality (9.55% increase; 95% CI, 3.81-15.61%; vs. dust-free days: 2.09%; 95% CI, -0.76% to 5.02%; p = 0.02).ConclusionsWe found evidence of effects of PM2.5-10 and PM10 on natural and cause-specific mortality, with stronger estimated effects on cardiac mortality during Saharan dust outbreaks. Toxicological and biological effects of particles from desert sources need to be further investigated and taken into account in air quality standards.
| S-EPMC3230430 | biostudies-literature
Project description:BACKGROUND:Acute exposure to ambient particulate matter <2.5μm in aerodynamic diameter (PM2.5) has been associated with adult psychiatric exacerbations but has not been studied in children. OBJECTIVES:Our objectives were to estimate the association between acute exposures to ambient PM2.5 and psychiatric emergency department (ED) utilization and to determine if it is modified by community deprivation. METHODS:We used a time-stratified case-crossover design to analyze all pediatric, psychiatric ED encounters at Cincinnati Children's Hospital Medical Center in Cincinnati, Ohio, from 2011 to 2015 (n=13,176). Conditional logistic regression models adjusted for temperature, humidity, and holiday effects were used to estimate the odds ratio (OR) for a psychiatric ED visit 0-3 d after ambient PM2.5 exposures, estimated at residential addresses using a spatiotemporal model. RESULTS:A 10-μg/m3 increase in PM2.5 was associated with a significant increase in any psychiatric ED utilization 1 [OR=1.07 (95% CI: 1.02, 1.12)] and 2 [OR=1.05 (95% CI: 1.00, 1.10)] d later. When stratified by visit reason, associations were significant for ED visits related to adjustment disorder {e.g., 1-d lag [OR=1.24 (95% CI: 1.02, 1.52)] and suicidality 1-d lag [OR=1.44 (95% CI: 1.03, 2.02)]}. There were significant differences according to community deprivation, with some lags showing stronger associations among children in high versus low deprivation areas for ED visits for anxiety {1-d lag [OR=1.39 (95% CI: 0.96, 2.01) vs. 0.85 (95% CI: 0.62, 1.17)] and suicidality same day [OR=1.98 (95% CI: 1.22, 3.23) vs. 0.93 (95% CI: 0.60, 1.45)]}. In contrast, for some lags, associations with ED visits for adjustment disorder were weaker for children in high-deprivation areas {1-d lag [OR=1.00 (95% CI: 0.76, 1.33) vs. 1.50 (95% CI: 1.16, 1.93)]}. DISCUSSION:These findings warrant additional research to confirm the associations in other populations. https://doi.org/10.1289/EHP4815.
| S-EPMC6792357 | biostudies-literature
Project description:BackgroundEstimating the causal effect of pollution on human health is integral for evaluating returns to pollution regulation, yet separating out confounding factors remains a perennial challenge.MethodsWe use a quasi-experimental design to investigate the causal relationship between regulation of particulate matter smaller than 2.5 micrograms per cubic meter (PM2.5) and mortality among those 65 years of age and older. We exploit regulatory changes in the Clean Air Act Amendments (CAAA). Regulation in 2005 impacted areas of the United States differentially based on pre-regulation air quality levels for PM2.5. We use county-level mortality data, extracted from claims data managed by the Centers for Medicare & Medicaid Services, merged to county-level average PM2.5 readings and attainment status as classified by the Environmental Protection Agency.ResultsBased on estimates from log-linear difference-in-differences models, our results indicate after the CAAA designation for PM2.5 in 2005, PM2.5 levels decreased 1.59 micrograms per cubic meter (95% CI = 1.39, 1.80) and mortality rates among those 65 and older decreased by 0.93% (95% CI = 0.10%, 1.77%) in nonattainment counties, relative to attainment ones. Results are robust to a series of alternate models, including nearest-neighbor matching based on propensity score estimates.ConclusionThis analysis suggests large health returns to the 2005 PM2.5 designations, and provides evidence of a causal association between pollution and mortality among the Medicare population.
| S-EPMC7880579 | biostudies-literature
Project description:Numerous studies have demonstrated the relationship between summer temperatures and increased heat-related deaths. Epidemiological analyses of the health effects of climate exposures usually rely on observations from the nearest weather station to assess exposure-response associations for geographically diverse populations. Urban climate models provide high-resolution spatial data that may potentially improve exposure estimates, but to date, they have not been extensively applied in epidemiological research. We investigated temperature-mortality relationships in the city of Barcelona, and whether estimates vary among districts. We considered georeferenced individual (natural) mortality data during the summer months (June-September) for the period 1992-2015. We extracted daily summer mean temperatures from a 100-m resolution simulation of the urban climate model (UrbClim). Summer hot days (above percentile 70) and reference (below percentile 30) temperatures were compared by using a conditional logistic regression model in a case crossover study design applied to all districts of Barcelona. Relative Risks (RR), and 95% Confidence Intervals (CI), of all-cause (natural) mortality and summer temperature were calculated for several population subgroups (age, sex and education level by districts). Hot days were associated with an increased risk of death (RR = 1.13; 95% CI = 1.10-1.16) and were significant in all population subgroups compared to the non-hot days. The risk ratio was higher among women (RR = 1.16; 95% CI= 1.12-1.21) and the elderly (RR = 1.18; 95% CI = 1.13-1.22). Individuals with primary education had similar risk (RR = 1.13; 95% CI = 1.08-1.18) than those without education (RR = 1.10; 95% CI= 1.05-1.15). Moreover, 6 out of 10 districts showed statistically significant associations, varying the risk ratio between 1.12 (95% CI = 1.03-1.21) in Sants-Montjuïc and 1.25 (95% CI = 1.14-1.38) in Sant Andreu. Findings identified vulnerable districts and suggested new insights to public health policy makers on how to develop district-specific strategies to reduce risks.
| S-EPMC7177772 | biostudies-literature
Project description:Most studies of short-term particulate matter (PM) exposure use 24-hour averages. However, other pollutants have stronger effects at shorter timeframes, which has influenced policy (e.g., ozone 8-hour maximum). Selecting appropriate exposure timeframes is important for effective regulation. The U.S. EPA identified health effects for sub-daily PM exposures as a critical research need. Unlike most areas, Seoul, Korea has hourly measurements of PM10, although not PM2.5. We investigated PM10 and mortality (total, cardiovascular, respiratory) in Seoul (1999-2009) considering sub-daily exposures: 24-hour, daytime (7am-8pm), morning (7-10am), nighttime (8pm-7am), and 1-hour daily maximum. We applied Poisson generalized linear modeling adjusting for temporal trends and meteorology. All PM10 metrics were significantly associated with total mortality. Compared to other exposure timeframes, morning exposure had the most certain effect with total mortality (based on statistical significance). A 10µg/m3 increase in 24-hour, daytime, morning, nighttime, and 1-hour maximum PM10 was associated with a 0.15% (95% confidence interval 0.02-0.28%), 0.14% (0.01-0.27%), 0.10% (0.03-0.18%), 0.12% (0.03-0.22%), and 0.10% (0.00-0.21%) increase in total mortality, respectively. PM10 was significantly associated with cardiovascular mortality for 24-hour, morning, and nighttime exposures. We did not identify significant associations with respiratory mortality. Results support use of a 24-hour averaging time as an appropriate metric for health studies and regulation, particularly for PM10 and mortality.
| S-EPMC4288032 | biostudies-literature
Project description:BackgroundCharacterizing and comparing the determinant of cotinine concentrations in different populations should facilitate a better understanding of smoking patterns and addiction. This study describes and characterizes determinants of salivary cotinine concentration in a sample of Spanish adult daily smoker men and women.MethodsA cross-sectional study was carried out between March 2004 and December 2005 in a representative sample of 1245 people from the general population of Barcelona, Spain. A standard questionnaire was used to gather information on active tobacco smoking and passive exposure, and a saliva specimen was obtained to determine salivary cotinine concentration. Two hundred and eleven adult smokers (>16 years old) with complete data were included in the analysis. Determinants of cotinine concentrations were assessed using linear regression models.ResultsSalivary cotinine concentration was associated with the reported number of cigarettes smoked in the previous 24 hours (R2 = 0.339; p < 0.05). The inclusion of a quadratic component for number of cigarettes smoked in the regression analyses resulted in an improvement of the fit (R2 = 0.386; p < 0.05). Cotinine concentration differed significantly by sex, with men having higher levels.ConclusionThis study shows that salivary cotinine concentration is significantly associated with the number of cigarettes smoked and sex, but not with other smoking-related variables.
| S-EPMC2749042 | biostudies-literature
Project description:Exposure to particulate matter (PM) air pollution has been associated with a range of adverse health outcomes, including cardiovascular disease hospitalizations and other clinical parameters. Determining which sources of PM, such as traffic or industry, are most associated with adverse health outcomes could help guide future recommendations aimed at reducing harmful pollution exposure for susceptible individuals. Information obtained from multisite studies, which is generally more precise than information from a single location, is critical to understanding how PM impacts health and to informing local strategies for reducing individual-level PM exposure. However, few methods exist to perform multisite studies of PM sources, which are not generally directly observed, and adverse health outcomes. We developed SHared Across a REgion (SHARE), a hierarchical modeling approach that facilitates reproducible, multisite epidemiologic studies of PM sources. SHARE is a two-stage approach that first summarizes information about PM sources across multiple sites. Then, this information is used to determine how community-level (i.e., county-level or city-level) health effects of PM sources should be pooled to estimate regional-level health effects. SHARE is a type of population value decomposition that aims to separate out regional-level features from site-level data. Unlike previous approaches for multisite epidemiologic studies of PM sources, the SHARE approach allows the specific PM sources identified to vary by site. Using data from 2000 to 2010 for 63 northeastern US counties, we estimated regional-level health effects associated with short-term exposure to major types of PM sources. We found that PM from secondary sulfate, traffic, and metals sources was most associated with cardiovascular disease hospitalizations. Copyright © 2017 John Wiley & Sons, Ltd.
| S-EPMC5378603 | biostudies-literature
Project description:There are concerns that the reported association of ambient fine particulate matter (PM2.5) with mortality might be a mixture of PM2.5 and weather conditions. We evaluated the effects of extreme weather conditions and weather types on mortality as well as their interactions with PM2.5 concentrations in a time series study. Daily non-accidental deaths, individual demographic information, daily average PM2.5 concentrations and meteorological data between 2012 and 2014 were obtained from Shanghai, China. Days with extreme weather conditions were identified. Six synoptic weather types (SWTs) were generated. The generalized additive model was set up to link the mortality with PM2.5 and weather conditions. Parameter estimation was based on Bayesian methods using both the Jeffreys' prior and an informative normal prior in a sensitivity analysis. We estimate the percent increase in non-accidental mortality per 10 ?g/m3 increase in PM2.5 concentration and constructed corresponding 95% credible interval (CrI). In total, 336,379 non-accidental deaths occurred during the study period. Average daily deaths were 307. The results indicated that per 10 ?g/m3 increase in daily average PM2.5 concentration alone corresponded to 0.26-0.35% increase in daily non-accidental mortality in Shanghai. Statistically significant positive associations between PM2.5 and mortality were found for favorable SWTs when considering the interaction between PM2.5 and SWTs. The greatest effect was found in hot dry SWT (percent increase = 1.28, 95% CrI: 0.72, 1.83), followed by warm humid SWT (percent increase = 0.64, 95% CrI: 0.15, 1.13). The effect of PM2.5 on non-accidental mortality differed under specific extreme weather conditions and SWTs. Environmental policies and actions should take into account the interrelationship between the two hazardous exposures.
| S-EPMC5679525 | biostudies-literature