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Reduced metabolic insulin sensitivity following sub-acute exposures to low levels of ambient fine particulate matter air pollution.

ABSTRACT: Epidemiological studies suggest that fine particulate matter (PM2.5) may increase the risk for developing diabetes mellitus (DM). To evaluate possible mechanisms explaining these associations, we investigated if sub-acute ambient-level exposures can impair insulin sensitivity. Twenty-five healthy adults living in rural Michigan were transported to an urban location for 5 consecutive days (exposure-block) of daily 4- to 5-hour-long ambient air pollution exposures. Health outcomes, including the homeostasis model assessment of insulin resistance (HOMA-IR) the primary outcome of insulin sensitivity, were measured at 3 time points in relation to exposure-blocks: 7days prior to start; on the last exposure-day; and 7days after completion. PM2.5 was monitored at the urban exposure site and at community monitors near subjects' residences. We calculated 3 "sub-acute" exposure periods (approximately 5-days-long) starting retrospective from the time of health outcome measurements (PM2.5 ranges: 9.7±3.9 to 11.2±3.9?g·m(-3)). A 10?g·m(-3) increase in sub-acute PM2.5 exposures was associated with increased HOMA-IR (+0.7, 95% confidence interval (CI) 0.1 to 1.3; p=0.023) and reduced heart rate variability (standard deviation of normal-to-normal intervals [-13.1ms, 95%CI -25.3 to -0.9; p=0.035]). No alterations in other outcomes (inflammatory markers, vascular function) occurred in relation to PM2.5 exposures. Our findings suggest that ambient PM2.5, even at low levels, may reduce metabolic insulin sensitivity supporting the plausibility that air pollution could potentiate the development of DM.

SUBMITTER: Brook RD

PROVIDER: S-EPMC4391076 | biostudies-literature | 2013 Mar

REPOSITORIES: biostudies-literature

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Reduced metabolic insulin sensitivity following sub-acute exposures to low levels of ambient fine particulate matter air pollution.

Brook Robert D RD Xu Xiaohua X Bard Robert L RL Dvonch J Timothy JT Morishita Masako M Kaciroti Niko N Sun Qinghua Q Harkema Jack J Rajagopalan Sanjay S

The Science of the total environment 20120815

Epidemiological studies suggest that fine particulate matter (PM2.5) may increase the risk for developing diabetes mellitus (DM). To evaluate possible mechanisms explaining these associations, we investigated if sub-acute ambient-level exposures can impair insulin sensitivity. Twenty-five healthy adults living in rural Michigan were transported to an urban location for 5 consecutive days (exposure-block) of daily 4- to 5-hour-long ambient air pollution exposures. Health outcomes, including the h ...[more]

PMID: 22901427

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Project description:ObjectiveTo quantitate the 2016 global and national burden of chronic kidney disease (CKD) attributable to ambient fine particulate matter air pollution ≤ 2.5 μm in aerodynamic diameter (PM2.5).DesignWe used the Global Burden of Disease (GBD) study data and methodologies to estimate the 2016 burden of CKD attributable to PM2.5 in 194 countries and territories. Population-weighted PM2.5 levels and incident rates of CKD for each country were curated from the GBD study publicly available data sources.SettingGBD global and national data on PM2.5 and CKD.Participants194 countries and territories.Main outcome measuresWe estimated the attributable burden of disease (ABD), years living with disability (YLD), years of life lost (YLL) and disability-adjusted life-years (DALYs).ResultsThe 2016 global burden of incident CKD attributable to PM2.5 was 6 950 514 (95% uncertainty interval: 5 061 533-8 914 745). Global YLD, YLL and DALYs of CKD attributable to PM2.5 were 2 849 311 (1 875 219-3 983 941), 8 587 735 (6 355 784-10 772 239) and 11 445 397 (8 380 246-14 554 091), respectively. Age-standardised ABD, YLL, YLD and DALY rates varied substantially among geographies. Populations in Mesoamerica, Northern Africa, several countries in the Eastern Mediterranean region, Afghanistan, Pakistan, India and several countries in Southeast Asia were among those with highest age-standardised DALY rates. For example, age-standardised DALYs per 100 000 were 543.35 (391.16-707.96) in El Salvador, 455.29 (332.51-577.97) in Mexico, 408.41 (283.82-551.84) in Guatemala, 238.25 (173.90-303.98) in India and 178.26 (125.31-238.47) in Sri Lanka, compared with 5.52 (0.82-11.48) in Sweden, 6.46 (0.00-14.49) in Australia and 12.13 (4.95-21.82) in Canada. Frontier analyses showed that Mesoamerican countries had significantly higher CKD DALY rates relative to other countries with comparable sociodemographic development.ConclusionsOur results demonstrate that the global toll of CKD attributable to ambient air pollution is significant and identify several endemic geographies where air pollution may be a significant driver of CKD burden. Air pollution may need to be considered in the discussion of the global epidemiology of CKD.

Project description:Using daily fine particulate matter (PM2.5) composition data from the 2000-2005 U.S. EPA Chemical Speciation Network (CSN) for over 200 sites, we applied multivariate methods to identify and quantify the major fine particulate matter (PM2.5) source components in the U.S. Novel aspects of this work were: (1) the application of factor analysis (FA) to multi-city daily data, drawing upon both spatial and temporal variations of chemical species; and, (2) the exclusion of secondary components (sulfates, nitrates and organic carbon) from the source identification FA to more clearly discern and apportion the PM2.5 mass to primary emission source categories. For the quantification of source-related mass, we considered two approaches based upon the FA results: 1) using single key tracers for sources identified by FA in a mass regression; and, 2) applying Absolute Principal Component Analysis (APCA). In each case, we followed a two-stage mass regression approach, in which secondary components were first apportioned among the identified sources, and then mass was apportioned to the sources and to other secondary mass not explained by the individual sources. The major U.S. PM2.5 source categories identified via FA (and their key elements) were: Metals Industry (Pb, Zn); Crustal/Soil Particles (Ca, Si); Motor Vehicle Traffic (EC, NO2); Steel Industry (Fe, Mn); Coal Combustion (As, Se); Oil Combustion (V, Ni); Salt Particles (Na, Cl) and Biomass Burning (K). Nationwide spatial plots of the source-related PM2.5 impacts were confirmatory of the factor interpretations: ubiquitous sources, such as Traffic and Soil, were found to be spread across the nation, more unique sources (such as Steel and Metals Processing) being highest in select industrialized cities, Biomass Burning was highest in the U.S. Northwest, while Residual Oil combustion was highest in cities in the Northeastern U.S. and in cities with major seaports. The sum of these source contributions and the secondary PM2.5 components agreed well with the U.S. PM2.5 observed during the study period (mean=14.3 ug/m3; R2= 0.91). Apportionment regression analyses using single-element tracers for each source category gave results consistent with the APCA estimates. Comparisons of nearby sites indicated that the PM2.5 mass and the secondary aerosols were most homogenous spatially, while traffic PM2.5 and its tracer, EC, were among the most spatially representative of the source-related components. Comparison of apportionment results to a previous analysis of the 1979-1982 IP Network revealed similar and correlated major U.S. source category factors, albeit at lower levels than in the earlier period, suggesting a consistency in the U.S. spatial patterns of these source-related exposures over time, as well. These results indicate that applying source apportionment methods to the nationwide CSN can be an informative avenue for identifying and quantifying source components for the subsequent estimation of source-specific health effects, potentially contributing to more efficient regulation of PM2.5.

Project description:BackgroundEcologic analyses suggest that living in areas with higher levels of ambient fine particulate matter air pollution (PM2.5) is associated with higher risk of adverse COVID-19 outcomes. Studies accounting for individual-level health characteristics are lacking.MethodsWe leveraged the breadth and depth of the US Department of Veterans Affairs national healthcare databases and built a national cohort of 169,102 COVID-19 positive United States Veterans, enrolled between March 2, 2020 and January 31, 2021, and followed them through February 15, 2021. Annual average 2018 PM2.5 exposure, at an approximately 1 km2 resolution, was linked with residential street address at the year prior to COVID-19 positive test. COVID-19 hospitalization was defined as first hospital admission between 7 days prior to, and 15 days after, the first COVID-19 positive date. Adjusted Poisson regression assessed the association of PM2.5 with risk of hospitalization.ResultsThere were 25,422 (15.0%) hospitalizations; 5,448 (11.9%), 5,056 (13.0%), 7,159 (16.1%), and 7,759 (19.4%) were in the lowest to highest PM2.5 quartile, respectively. In models adjusted for State, demographic and behavioral factors, contextual characteristics, and characteristics of the pandemic a one interquartile range increase in PM2.5 (1.9 µg/m3) was associated with a 10% (95% CI: 8%-12%) increase in risk of hospitalization. The association of PM2.5 and risk of hospitalization among COVID-19 individuals was present in each wave of the pandemic. Models of non-linear exposure-response suggested increased risk at PM2.5 concentrations below the national standard 12 µg/m3. Formal effect modification analyses suggested higher risk of hospitalization associated with PM2.5 in Black people compared to White people (p = 0.045), and in those living in socioeconomically disadvantaged neighborhoods (p < 0.001).ConclusionsExposure to higher levels of PM2.5 was associated with increased risk of hospitalization among COVID-19 infected individuals. The risk was evident at PM2.5 levels below the regulatory standards. The analysis identified those of Black race and those living in disadvantaged neighborhoods as population groups that may be more susceptible to the untoward effect of PM2.5 on risk of hospitalization in the setting of COVID-19.

Project description:Few epidemiologic studies have evaluated the effects of air pollution on the risk of Parkinson disease (PD).We investigated the associations of long-term residential concentrations of ambient particulate matter (PM) < 10 ?m in diameter (PM10) and < 2.5 ?m in diameter (PM2.5) and nitrogen dioxide (NO2) in relation to PD risk.Our nested case-control analysis included 1,556 self-reported physician-diagnosed PD cases identified between 1995 and 2006 and 3,313 controls frequency-matched on age, sex, and race. We geocoded home addresses reported in 1995-1996 and estimated the average ambient concentrations of PM10, PM2.5, and NO2 using a national fine-scale geostatistical model incorporating roadway information and other geographic covariates. Air pollutant exposures were analyzed as both quintiles and continuous variables, adjusting for matching variables and potential confounders.We observed no statistically significant overall association between PM or NO2 exposures and PD risk. However, in preplanned subgroup analyses, a higher risk of PD was associated with higher exposure to PM10 (ORQ5 vs. Q1 = 1.65; 95% CI: 1.11, 2.45; p-trend = 0.02) among women, and with higher exposure to PM2.5 (ORQ5 vs. Q1 = 1.29; 95% CI: 0.94, 1.76; p-trend = 0.04) among never smokers. In post hoc analyses among female never smokers, both PM2.5 (ORQ5 vs. Q1 = 1.79; 95% CI: 1.01, 3.17; p-trend = 0.05) and PM10 (ORQ5 vs. Q1 = 2.34; 95% CI: 1.29, 4.26; p-trend = 0.01) showed positive associations with PD risk. Analyses based on continuous exposure variables generally showed similar but nonsignificant associations.Overall, we found limited evidence for an association between exposures to ambient PM10, PM2.5, or NO2 and PD risk. The suggestive evidence that exposures to PM2.5 and PM10 may increase PD risk among female never smokers warrants further investigation. Citation: Liu R, Young MT, Chen JC, Kaufman JD, Chen H. 2016. Ambient air pollution exposures and risk of Parkinson disease. Environ Health Perspect 124:1759-1765;?http://dx.doi.org/10.1289/EHP135.

Project description:BackgroundEpidemiological studies report fairly consistent associations between various air pollution metrics and autism spectrum disorder (ASD), with some elevated risks reported for different prenatal and postnatal periods.ObjectivesTo examine associations between ASD and ambient fine particulate matter (PM2.5) and ozone concentrations during the prenatal period through the second year of life in a case-control study.MethodsASD cases (n = 428) diagnosed at Cincinnati Children's Hospital Medical Center were frequency matched (15:1) to 6420 controls from Ohio birth records. We assigned daily PM2.5 and ozone estimates for 2005-2012 from US EPA's Fused Air Quality Surface Using Downscaling model to each participant for each day based on the mother's census tract of residence at birth. We calculated adjusted odds ratios (aORs) using logistic regression across continuous and categorical exposure window averages (trimesters, first and second postnatal years, and cumulative measure), adjusting for maternal- and birth-related confounders, both air pollutants, and multiple temporal exposure windows.ResultsWe detected elevated aORs for PM2.5 during the 2nd trimester, 1st year of life, and a cumulative period from pregnancy through the 2nd year (aOR ranges across categories: 1.41-1.44, 1.54-1.84, and 1.41-1.52 respectively), and for ozone in the 2nd year of life (aOR range across categories: 1.29-1.42). Per each change in IQR, we observed elevated aORs for ozone in the 3rd trimester, 1st and 2nd years of life, and the cumulative period (aOR range: 1.19-1.27) and for PM2.5 in the 2nd trimester, 1st year of life, and the cumulative period (aOR range: 1.11-1.17).DiscussionWe saw limited evidence of linear exposure-response relationships for ASD with increasing air pollution, but the elevated aORs detected for PM2.5 in upper exposure categories and per IQR unit increases were similar in magnitude to those reported in previous studies, especially for postnatal exposures.

Project description:BackgroundExperimental evidence and studies of children and adolescents suggest that ambient fine particulate matter [particulate matter ≤2.5μm in aerodynamic diameter (PM2.5)] air pollution may be obesogenic, but the relationship between PM2.5 and the risk of body weight gain and obesity in adults is uncertain.ObjectivesOur goal was to characterize the association between PM2.5 and the risks of weight gain and obesity.MethodsWe followed 3,902,440 U.S. Veterans from 2010 to 2018 (median 8.1 y, interquartile range: 7.3-8.4) and assigned time-updated PM2.5 exposures by linking geocoded residential street addresses with satellite-based estimates of surface-level PM2.5 mass (at ∼1-km2 resolution). Associations with PM2.5 were estimated using Cox proportional hazards models for incident obesity [body mass index (BMI)≥30 kg/m2] and a 10-lb increase in weight relative to baseline and linear mixed models for associations with intra-individual changes in BMI and weight.ResultsA 10-μg/m3 higher average annual PM2.5 concentration was associated with risk of incident obesity [n=2,325,769; hazard ratio (HR)=1.08 (95% CI: 1.06, 1.11)] and the risk of a 10-lb (4.54 kg) increase in weight [HR=1.07 (95% CI: 1.06, 1.08)] and with higher intra-individual changes in BMI [0.140 kg/m2 per year (95% CI: 0.139, 0.142)] and weight [0.968 lb/y (95% CI: 0.955, 0.981)]. Nonlinear exposure-response models indicated associations at PM2.5 concentrations below the national standard of 12 μg/m3. As expected, a negative exposure control (ambient air sodium) was not associated with obesity or weight gain. Associations were consistent in direction and magnitude across sensitivity analyses that included alternative outcomes and exposures assigned at different spatial resolutions.DiscussionPM2.5 air pollution was associated with the risk of obesity and weight gain in a large predominantly male cohort of U.S. Veterans. Discussions about health effects of PM2.5 should include its association with obesity, and deliberations about the epidemiology of obesity should consider its association with PM2.5. Investigation in other cohorts will deepen our understanding of the relationship between PM2.5 and weight gain and obesity. https://doi.org/10.1289/EHP7944.

Dataset Information

Reduced metabolic insulin sensitivity following sub-acute exposures to low levels of ambient fine particulate matter air pollution.

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Reduced metabolic insulin sensitivity following sub-acute exposures to low levels of ambient fine particulate matter air pollution.

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