Traffic particles and occurrence of acute myocardial infarction: a case–control analysis

OBJECTIVES: We modelled exposure to traffic particles using a latent variable approach and investigated whether long-term exposure to traffic particles is associated with an increase in the occurrence of acute myocardial infarction (AMI) using data from a population-based coronary disease registry. METHODS: Cases of individually validated AMI were identified between 1995 and 2003 as part of the Worcester Heart Attack Study. Population controls were selected from Massachusetts, USA, resident lists. NO(2) and PM(2.5) filter absorbance were measured at 36 locations throughout the study area. The air pollution data were used to estimate exposure to traffic particles using a semiparametric latent variable regression model. Conditional logistic models were used to estimate the association between exposure to traffic particles and occurrence of AMI. RESULTS: Modelled exposure to traffic particles was highest near the city of Worcester. Cases of AMI were more exposed to traffic and traffic particles compared to controls. An interquartile range increase in modelled traffic particles was associated with a 10% (95% CI 4% to 16%) increase in the odds of AMI. Accounting for spatial dependence at the census tract, but not block group, scale substantially attenuated this association. CONCLUSIONS: These results provide some support for an association between long-term exposure to traffic particles and risk of AMI. The results were sensitive to the scale selected for the analysis of spatial dependence, an issue that requires further investigation. The latent variable model captured variation in exposure, although on a relatively large spatial scale

Particulate Matter Air Pollution Exposure, Distance to Road, and Incident Lung Cancer in the Nurses’ Health Study Cohort

Background: A body of literature has suggested an elevated risk of lung cancer associated with particulate matter and traffic-related pollutants. Objective: We examined the relation of lung cancer incidence with long-term residential exposures to ambient particulate matter and residential distance to roadway, as a proxy for traffic-related exposures. Methods: For participants in the Nurses’ Health Study, a nationwide prospective cohort of women, we estimated 72-month average exposures to PM2.5, PM2.5–10, and PM10 and residential distance to road. Follow-up for incident cases of lung cancer occurred from 1994 through 2010. Cox proportional hazards models were adjusted for potential confounders. Effect modification by smoking status was examined. Results: During 1,510,027 person-years, 2,155 incident cases of lung cancer were observed among 103,650 participants. In fully adjusted models, a 10-μg/m3 increase in 72-month average PM10 [hazard ratio (HR) = 1.04; 95% CI: 0.95, 1.14], PM2.5 (HR = 1.06; 95% CI: 0.91, 1.25), or PM2.5–10 (HR = 1.05; 95% CI: 0.92, 1.20) was positively associated with lung cancer. When the cohort was restricted to never-smokers and to former smokers who had quit at least 10 years before, the associations appeared to increase and were strongest for PM2.5 (PM10: HR = 1.15; 95% CI: 1.00, 1.32; PM2.5: HR = 1.37; 95% CI: 1.06, 1.77; PM2.5–10: HR = 1.11; 95% CI: 0.90, 1.37). Results were most elevated when restricted to the most prevalent subtype, adenocarcinomas. Risks with roadway proximity were less consistent. Conclusions: Our findings support those from other studies indicating increased risk of incident lung cancer associated with ambient PM exposures, especially among never- and long-term former smokers. Citation: Puett RC, Hart JE, Yanosky JD, Spiegelman D, Wang M, Fisher JA, Hong B, Laden F. 2014. Particulate matter air pollution exposure, distance to road, and incident lung cancer in the Nurses’ Health Study Cohort. Environ Health Perspect 122:926–932; http://dx.doi.org/10.1289/ehp.130749

Exposure measurement error in PM2.5 health effects studies: A pooled analysis of eight personal exposure validation studies

Background: Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typically available surrogate exposures. Methods: Daily personal and ambient PM2.5, and when available sulfate, measurements were compiled from nine cities, over 2 to 12 days. True exposure was defined as personal exposure to PM2.5 of ambient origin. Since PM2.5 of ambient origin could only be determined for five cities, personal exposure to total PM2.5 was also considered. Surrogate exposures were estimated as ambient PM2.5 at the nearest monitor or predicted outside subjects’ homes. We estimated calibration coefficients by regressing true on surrogate exposures in random effects models. Results: When monthly-averaged personal PM2.5 of ambient origin was used as the true exposure, calibration coefficients equaled 0.31 (95% CI:0.14, 0.47) for nearest monitor and 0.54 (95% CI:0.42, 0.65) for outdoor home predictions. Between-city heterogeneity was not found for outdoor home PM2.5 for either true exposure. Heterogeneity was significant for nearest monitor PM2.5, for both true exposures, but not after adjusting for city-average motor vehicle number for total personal PM2.5. Conclusions: Calibration coefficients were <1, consistent with previously reported chronic health risks using nearest monitor exposures being under-estimated when ambient concentrations are the exposure of interest. Calibration coefficients were closer to 1 for outdoor home predictions, likely reflecting less spatial error. Further research is needed to determine how our findings can be incorporated in future health studies

The Association of Long-Term Exposure to Particulate Matter Air Pollution with Brain MRI Findings: The ARIC Study.

BACKGROUND: Increasing evidence links higher particulate matter (PM) air pollution exposure to late-life cognitive impairment. However, few studies have considered associations between direct estimates of long-term past exposures and brain MRI findings indicative of neurodegeneration or cerebrovascular disease. OBJECTIVE: Our objective was to quantify the association between brain MRI findings and PM exposures approximately 5 to 20 y prior to MRI in the Atherosclerosis Risk in Communities (ARIC) study. METHODS: ARIC is based in four U.S. sites: Washington County, Maryland; Minneapolis suburbs, Minnesota; Forsyth County, North Carolina; and Jackson, Mississippi. A subset of ARIC participants underwent 3T brain MRI in 2011-2013 (n=1,753). We estimated mean exposures to PM with an aerodynamic diameter less than 10 or 2.5μm (PM RESULTS: In pooled analyses, higher mean PM CONCLUSIONS: Long-term past PM exposure in was not associated with markers of cerebrovascular disease. Higher long-term past PM exposures were associated with smaller deep-gray volumes overall, and higher P

Protected area targets post-2020

The ten-year Strategic Plan for Biodiversity, made up of 20 Aichi Biodiversity Targets, is coming to an end and it is therefore timely to assess their appropriateness so as to provide scientific support on the development of an improved post-2020 framework. Here we focus on Aichi Target 11, concerned with conserving protected areas and other effective area-based conservation measures by 2020. We identify four broad problems with Aichi Target 11 that have led to perverse outcomes and an inability for nations to account for true conservation progress. We propose a formulation for a target for site-based conservation beyond 2020 aimed at overcoming them: ‘The value of all key biodiversity areas and other sites of global significance for biodiversity is documented and retained through protected areas and other effective area-based conservation measures’

Particulate matter and albuminuria, glomerular filtration rate, and incident ckd

Background and objectives Exposure to particulate matter (PM),2.5 mm in aerodynamic diameter (PM2.5) has been linked to detrimental health effects. This study aimed to describe the relationship between long-term PM2.5 exposure and kidney disease, including eGFR, level of albuminuria, and incident CKD. Design, setting, participants, &amp; measurements The study included 10,997 participants from the Atherosclerosis Risk in Communities cohort who were followed from 1996–1998 through 2016. Monthly mean PM2.5 concentrations (mg/m3 ) were estimated at geocoded participant addresses using geographic information system–based, spatiotemporal generalized additive mixed models—including geospatial covariates such as land use—and then averaged over the 12-month period preceding participant examination. Covariate-adjusted, cross-sectional associations of PM2.5, baseline eGFR, and urinary albumin-creatinine ratio (UACR) were estimated using linear regression. PM2.5 and incident CKD (defined as follow-up eGFR,60 ml/min per 1.73 m2 with $25% eGFR decline relative to baseline, CKD-related hospitalization or death based on International Classification of Diseases 9/10 codes, or development of ESKD) associations were estimated using Cox proportional hazards regression. Modeling was stratified by study site, and stratum-specific estimates were combined using random-effects meta-analyses. Results Baseline mean participant age was 63 (66) years and eGFR was 86 (616) ml/min per 1.73 m2. There was no significant PM2.5-eGFR association at baseline. Each 1-mg/m3 higher annual average PM2.5 was associated with higher UACR after adjusting for demographics, socioeconomic status, and clinical covariates (percentage difference, 6.6%; 95% confidence interval [95% CI], 2.6% to 10.7%). Each 1-mg/m3 higher annual average PM2.5 was associated with a significantly higher risk of incident CKD (hazard ratio, 1.05; 95% CI, 1.01 to 1.10). Conclusions Exposure to higher annual average PM2.5 concentrations was associated with a higher level of albuminuria and higher risk for incident CKD in a community-based cohort

Inflammation and acute traffic-related air pollution exposures among a cohort of youth with type 1 diabetes

Background: Evidence remains equivocal regarding the association of inflammation, a precursor to cardiovascular disease, and acute exposures to ambient air pollution from traffic-related particulate matter. Though youth with type 1 diabetes are at higher risk for cardiovascular disease, the relationship of inflammation and ambient air pollution exposures in this population has received little attention. Objectives: Using five geographically diverse US sites from the racially- and ethnically-diverse SEARCH for Diabetes in Youth Cohort, we examined the relationship of acute exposures to PM2.5 mass, Atmospheric Dispersion Modeling System (ADMS)-Roads traffic-related PM concentrations near roadways, and elemental carbon (EC) with biomarkers of inflammation including interleukin-6 (IL-6), c-reactive protein (hs-CRP) and fibrinogen. Methods: Baseline questionnaires and blood were obtained at a study visit. Using a spatio-temporal modeling approach, pollutant exposures for 7 days prior to blood draw were assigned to residential addresses. Linear mixed models for each outcome and exposure were adjusted for demographic and lifestyle factors identified a priori. Results: Among the 2566 participants with complete data, fully-adjusted models showed positive associations of EC average week exposures with IL-6 and hs-CRP, and PM2.5 mass exposures on lag day 3 with IL-6 levels. Comparing the 25th and 75th percentiles of average week EC exposures resulted in 8.3% higher IL-6 (95%CI: 2.7%,14.3%) and 9.8% higher hs-CRP (95%CI: 2.4%,17.7%). We observed some evidence of effect modification for the relationships of PM2.5 mass exposures with hs-CRP by gender and with IL-6 by race/ethnicity. Conclusions: Indicators of inflammation were associated with estimated traffic-related air pollutant exposures in this study population of youth with type 1 diabetes. Thus youth with type 1 diabetes may be at increased risk of air pollution-related inflammation. These findings and the racial/ethnic and gender differences observed deserve further exploration

Long-Term Exposure to Ambient Air Pollution and Type 2 Diabetes in Adults

PURPOSE OF REVIEW We identified 24 publications from January 2010 until September 2018 in the peer-reviewed literature addressing the relationship of long-term air pollution exposures and type 2 diabetes-related morbidity and mortality among adults. We examine key methodological issues, synthesize findings, and address study strengths and limitations. We also discuss biological mechanisms, policy implications, and future research needed to address existing knowledge gaps. RECENT FINDINGS In general, the studies included in this review employed rigorous methodology with large sample sizes, appropriate study designs to maximize available cohort study or administrative data sources, and exposure modeling that accounted for spatial patterns in air pollution levels. Overall, studies suggested increased risks of type 2 diabetes-related morbidity and mortality among adults associated with increased exposures; however, findings were not uniformly positive nor statistically significant. SUMMARY Current research is particularly limited regarding the biological mechanisms involved and the relationship between ozone and diabetes. Additionally, more research is needed to distinguish clearly the effects of nitrogen oxides from those of other pollutants and to identify potential subpopulations with greater susceptibility for certain pollutant exposures. A better understanding of the potential link between long-term ambient air pollution exposures and type 2 diabetes may provide opportunities for the reduction of health risks and inform future interventions for environmental protection and diabetes management

Air pollution and decreased bone mineral density among Women's Health Initiative participants

Background: Osteoporosis heavily affects postmenopausal women and is influenced by environmental exposures. Determining the impact of criteria air pollutants and their mixtures on bone mineral density (BMD) in postmenopausal women is an urgent priority. Methods: We conducted a prospective observational study using data from the ethnically diverse Women's Health Initiative Study (WHI) (enrollment, September 1994–December 1998; data analysis, January 2020 to August 2022). We used log-normal, ordinary kriging to estimate daily mean concentrations of PM10, NO, NO2, and SO2 at participants' geocoded addresses (1-, 3-, and 5-year averages before BMD assessments). We measured whole-body, total hip, femoral neck, and lumbar spine BMD at enrollment and follow-up (Y1, Y3, Y6) via dual-energy X-ray absorptiometry. We estimated associations using multivariable linear and linear mixed-effects models and mixture effects using Bayesian kernel machine regression (BKMR) models. Findings: In cross-sectional and longitudinal analyses, mean PM10, NO, NO2, and SO2 averaged over 1, 3, and 5 years before the visit were negatively associated with whole-body, total hip, femoral neck, and lumbar spine BMD. For example, lumbar spine BMD decreased 0.026 (95% CI: 0.016, 0.036) g/cm2/year per a 10% increase in 3-year mean NO2 concentration. BKMR suggested that nitrogen oxides exposure was inversely associated with whole-body and lumbar spine BMD. Interpretation: In this cohort study, higher levels of air pollutants were associated with bone damage, particularly on lumbar spine, among postmenopausal women. These findings highlight nitrogen oxides exposure as a leading contributor to bone loss in postmenopausal women, expanding previous findings of air pollution-related bone damage. Funding: US National Institutes of Health