Marianthi-Anna Kioumourtzoglou

Long-term PM2.5 Exposure and Neurological Hospital Admissions in the Northeastern United States

Background Long-term exposure to fine particles (particulate matter ≤ 2.5 μm; PM2.5) has been consistently linked to heart and lung disease. Recently, there has been increased interest in examining the effects of air pollution on the nervous system, with evidence showing potentially harmful effects on neurodegeneration. Objective Our objective was to assess the potential impact of long-term PM2.5 exposure on event time, defined as time to first admission for dementia, Alzheimer’s (AD), or Parkinson’s (PD) diseases in an elderly population across the northeastern United States. Methods We estimated the effects of PM2.5 on first hospital admission for dementia, AD, and PD among all Medicare enrollees ≥ 65 years in 50 northeastern U.S. cities (1999–2010). For each outcome, we first ran a Cox proportional hazards model for each city, adjusting for prior cardiopulmonary-related hospitalizations and year, and stratified by follow-up time, age, sex, and race. We then pooled the city-specific estimates by employing a random effects meta-regression. Results We followed approximately 9.8 million subjects and observed significant associations of long-term PM2.5 city-wide exposure with all three outcomes. Specifically, we estimated a hazard ratio (HR) of 1.08 (95% CI: 1.05, 1.11) for dementia, an HR of 1.15 (95% CI: 1.11, 1.19) for AD, and an HR of 1.08 (95% CI: 1.04, 1.12) for PD admissions per 1-μg/m3 increase in annual PM2.5 concentrations. Conclusions To our knowledge, this is the first study to examine the relationship between long-term exposure to PM2.5 and time to first hospitalization for common neurodegenerative diseases. We found strong evidence of association for all three outcomes. Our findings provide the basis for further studies, as the implications of such exposures could be crucial to public health. Citation Kioumourtzoglou MA, Schwartz JD, Weisskopf MG, Melly SJ, Wang Y, Dominici F, Zanobetti A. 2016. Long-term PM2.5 exposure and neurological hospital admissions in the northeastern United States. Environ Health Perspect 124:23–29; http://dx.doi.org/10.1289/ehp.1408973

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

BackgroundExposure 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.MethodsDaily 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.ResultsWhen 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.ConclusionsCalibration 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 relation between past exposure to fine particulate air pollution and prevalent anxiety: observational cohort study

Objective To determine whether higher past exposure to particulate air pollution is associated with prevalent high symptoms of anxiety. Design Observational cohort study. Setting Nurses’ Health Study. Participants 71 271 women enrolled in the Nurses’ Health Study residing throughout the contiguous United States who had valid estimates on exposure to particulate matter for at least one exposure period of interest and data on anxiety symptoms. Main outcome measures Meaningfully high symptoms of anxiety, defined as a score of 6 points or greater on the phobic anxiety subscale of the Crown-Crisp index, administered in 2004. Results The 71 271 eligible women were aged between 57 and 85 years (mean 70 years) at the time of assessment of anxiety symptoms, with a prevalence of high anxiety symptoms of 15%. Exposure to particulate matter was characterized using estimated average exposure to particulate matter <2.5 μm in diameter (PM2.5) and 2.5 to 10 μm in diameter (PM2.5-10) in the one month, three months, six months, one year, and 15 years prior to assessment of anxiety symptoms, and residential distance to the nearest major road two years prior to assessment. Significantly increased odds of high anxiety symptoms were observed with higher exposure to PM2.5 for multiple averaging periods (for example, odds ratio per 10 µg/m3 increase in prior one month average PM2.5: 1.12, 95% confidence interval 1.06 to 1.19; in prior 12 month average PM2.5: 1.15, 1.06 to 1.26). Models including multiple exposure windows suggested short term averaging periods were more relevant than long term averaging periods. There was no association between anxiety and exposure to PM2.5-10. Residential proximity to major roads was not related to anxiety symptoms in a dose dependent manner. Conclusions Exposure to fine particulate matter (PM2.5) was associated with high symptoms of anxiety, with more recent exposures potentially more relevant than more distant exposures. Research evaluating whether reductions in exposure to ambient PM2.5 would reduce the population level burden of clinically relevant symptoms of anxiety is warranted.

Diabetes Mellitus, Obesity, and Diagnosis of Amyotrophic Lateral Sclerosis: A Population-Based Study

IMPORTANCE Although prior studies have suggested a role of cardiometabolic health on pathogenesis of amyotrophic lateral sclerosis (ALS), the association with diabetes mellitus has not been widely examined. Amyotrophic lateral sclerosis is the most common motor neuron disorder. Several vascular risk factors have been associated with decreased risk for ALS. Although diabetes is also a risk factor for vascular disease, the few studies of diabetes and ALS have been inconsistent. OBJECTIVE To examine the association between diabetes and obesity, each identified through International Statistical Classification of Diseases, Eighth or Tenth Revision codes in a hospital registry, and ALS using data from the Danish National Registers. DESIGN, SETTING, AND PARTICIPANTS Population-based nested case-control study of 3650 Danish residents diagnosed as having ALS between January 1, 1982, and December 31, 2009, and 365,000 controls (100 for each ALS case) matched on age and sex. The analysis was conducted in September and October 2014. MAIN OUTCOMES AND MEASURES Adjusted odds ratio for ALS associated with diabetes or obesity diagnoses at least 3 years prior to the ALS diagnosis date. RESULTS When considering diabetes and our obesity indicator together, the estimated odds ratio for ALS was 0.61 (95% CI, 0.46-0.80) for diabetes and 0.81 (95% CI, 0.57-1.16) for obesity. We observed no effect modification on the association with diabetes by sex. We did find a significant modification by age at ALS diagnosis and age at first mention of diabetes in the hospital registers. The protective association was stronger with increasing age at ALS diagnosis (P = .01), and the odds ratio for first mention of diabetes was 1.66 (95% CI, 0.85-3.21) before age 40 years but 0.52 (95% CI, 0.39-0.70) for older ages. These results are consistent with different associations for type 1 vs type 2 diabetes. CONCLUSIONS AND RELEVANCE In this Danish nationwide study to investigate the association between diabetes and ALS diagnosis, our findings are in agreement with previous reports of a protective association between vascular risk factors and ALS and suggest that type 2 diabetes, but not type 1, is protective for ALS.

Air Pollution and Autism Spectrum Disorders: Causal or Confounded?

In the last decade, several studies have examined the association between perinatal exposure to ambient air pollution and risk of autism spectrum disorder (ASD). These studies have largely been consistent, with associations seen with different aspects of air pollution, including hazardous air toxics, ozone, particulate, and traffic-related pollution. Confounding by socioeconomic status (SES) and place of residence are of particular concern, as these can be related to ASD case ascertainment and other potential causal risk factors for ASD. While all studies take steps to address this concern, residual confounding is difficult to rule out. Two recent studies of air pollution and ASD, however, present findings that strongly argue against residual confounding, especially for factors that do not vary over relatively short time intervals. These two studies, conducted in communities around the USA, found a specific association with air pollution exposure during the 3rd, but not the 1st, trimester, when both trimesters were modeled simultaneously. In this review, we discuss confounding possibilities and then explain—with the aid of directed acyclic graphs (DAGs)—why an association that is specific to a particular time window, when multiple exposure windows are simultaneously assessed, argues against residual confounding by (even unmeasured) non-time-varying factors. In addition, we discuss why examining ambient air pollution concentration as a proxy for personal exposure helps avoid confounding by personal behavior differences, and the implications of measurement error in using ambient concentrations as a proxy for personal exposures. Given the general consistency of findings across studies and the exposure-window-specific associations recently reported, the overall evidence for a causal association between air pollution and ASD is increasingly compelling.

PM2.5 and Mortality in 207 US Cities: Modification by Temperature and City Characteristics.

Background: The reported estimated effects between long-term PM2.5 exposures and mortality vary spatially. We assessed whether community-level variables, including socioeconomic status indicators and temperature, modify this association. Methods: We used data from >35 million Medicare enrollees from 207 US cities (2000–2010). For each city, we calculated annual PM2.5 averages, measured at ambient central monitoring sites. We used a variation of a causal modeling approach and fitted city-specific Cox models, which we then pooled using a random effects meta-regression. In this second stage, we assessed whether temperature and city-level variables, including smoking and obesity rates, poverty, education and greenness, modify the long-term PM2.5–mortality association. Results: We found an association between long-term PM2.5 and survival (hazard ratio = 1.2; 95% confidence interval [CI]: 1.1, 1.3 per 10 &mgr;g/m3 increase in the annual PM2.5 average concentrations). We observed elevated estimates in the Southeastern, South and Northwestern US (hazard ratio = 1.9; 95% CI: 1.7, 2.2, and 1.4; 95% CI: 1.2, 1.7, and 1.4; 95% CI: 1.1, 1.9, respectively). We observed a higher association between long-term PM2.5 exposure and mortality in warmer cities. Furthermore, we observed increasing estimates with increasing obesity rates, %residents and families in poverty, %black residents and %population without a high school degree, and lower effects with increasing median household income and %white residents. Conclusions: To the best of our knowledge, this is the first study to assess modification by temperature and community-level characteristics on the long-term PM2.5–survival association. Our findings suggest that living in cities with high temperatures and low socio economic status (SES) is associated with higher effect estimates.

Comparison of diagnoses of amyotrophic lateral sclerosis by use of death certificates and hospital discharge data in the Danish population.

Abstract Because ALS is rare, large-scale studies are difficult. Hospital and death certificate data are valuable tools, but understanding of how well they capture cases is needed. We identified 3650 incident cases in the Danish National Patient Register (NPR) between 1982 and 2009, using ICD-8 (before 1994) or ICD-10 codes. Death certificates were obtained from the Danish Register of Causes of Death. We obtained medical records for 173 of the cases identified in the NPR and classified these according to the El Escorial criteria. We compared ALS identification from death certificates to hospital discharges, and both to medical records. Results showed that the sensitivity for use of death certificates was 84.2% (95% CI 82.9–85.5%) and was significantly higher for females, subjects younger than 77 years, and when coded with ICD-8. Using only the underlying cause of death resulted in significantly lower sensitivity. The estimated overall positive predictive value (PPV) was 82.0% (95% CI 80.0–83.8%). Sensitivity and PPV were similar compared with medical records. In conclusion, we found that use of hospital discharges and death certificates is highly reliable and, therefore, a valuable tool for ALS epidemiologic studies. The possible effects on findings of slight differences by age, gender, and ICD coding should be considered.

The impact of source contribution uncertainty on the effects of source-specific PM2.5 on hospital admissions: A case study in Boston, MA

Epidemiologic studies of particulate sources and adverse health do not account for the uncertainty in the source contribution estimates. Our goal was to assess the impact of uncertainty on the effect estimates of particulate sources on emergency cardiovascular (CVD) admissions. We examined the effects of PM2.5 sources, identified by positive matrix factorization (PMF) and absolute principle component analysis (APCA), on emergency CVD hospital admissions among Medicare enrollees in Boston, MA, during 2003–2010, given stronger associations for this period. We propagated uncertainty in source contributions using a block bootstrap procedure. We further estimated average across-methods source-specific effect estimates using bootstrap samples. We estimated contributions for regional, mobile, crustal, residual oil combustion, road dust, and sea salt sources. Accounting for uncertainty, same-day exposures to regional pollution were associated with an across-methods average effect of 2.00% (0.18, 3.78%) increase in the rate of CVD admissions. Weekly residual oil exposures resulted in an average 2.12% (0.19, 4.22%) increase. Same-day and 2-day exposures to mobile-related PM2.5 were also associated with increased admissions. Confidence intervals when accounting for the uncertainty were wider than otherwise. Agreement in PMF and APCA results was stronger when uncertainty was considered in health models. Accounting for uncertainty in source contributions leads to more stable effect estimates across methods and potentially to fewer spurious significant associations.

PM2.5 and survival among older adults: effect modification by particulate composition.

Background: Fine particulate (PM2.5) air pollution has been consistently linked to survival, but reported effect estimates are geographically heterogeneous. Exposure to different types of particle mixtures may explain some of this variation. Methods: We used k-means cluster analyses to identify cities with similar pollution profiles, (ie, PM2.5 composition) across the United States. We examined the impact of PM2.5 on survival, and its variation across clusters of cities with similar PM2.5 composition, among Medicare enrollees in 81 US cities (2000–2010). We used time-varying annual PM2.5 averages, measured at ambient central monitoring sites, as the exposure of interest. We ran by-city Cox models, adjusting for individual data on previous cardiopulmonary-related hospitalizations and stratifying by follow-up time, age, gender, and race. This eliminates confounding by factors varying across cities and long-term trends, focusing on year-to-year variations of air pollution around its city-specific mean and trend. We then pooled the city-specific effects using a random effects meta-regression. In this second stage, we also assessed effect modification by cluster membership and estimated cluster-specific PM2.5 effects. Results: We followed more than 19 million subjects and observed more than 6 million deaths. We found a harmful impact of annual PM2.5 concentrations on survival (hazard ratio = 1.11 [95% confidence interval = 1.01, 1.23] per 10 &mgr;g/m3). This effect was modified by particulate composition, with higher effects observed in clusters containing high concentrations of nickel, vanadium, and sulfate. For instance, our highest effect estimate was observed in cities with harbors in the Northwest, characterized by high nickel, vanadium, and elemental carbon concentrations (1.9 [1.1, 3.3]). We observed null or negative associations in clusters with high oceanic and crustal particles. Conclusions: To the best of our knowledge, this is the first study to examine the association between PM2.5 composition and survival. Our findings indicate that long-term exposure to fuel oil combustion and power plant emissions have the highest impact on survival.

The effect of primary organic particles on emergency hospital admissions among the elderly in 3 US cities.

BackgroundFine particle (PM2.5) pollution related to combustion sources has been linked to a variety of adverse health outcomes. Although poorly understood, it is possible that organic carbon (OC) species, particularly those from combustion-related sources, may be partially responsible for the observed toxicity of PM2.5. The toxicity of the OC species may be related to their chemical structures; however, few studies have examined the association of OC species with health impacts.MethodsWe categorized 58 primary organic compounds by their chemical properties into 5 groups: n-alkanes, hopanes, cyclohexanes, PAHs and isoalkanes. We examined their impacts on the rate of daily emergency hospital admissions among Medicare recipients in Atlanta, GA and Birmingham, AL (2006–2009), and Dallas, TX (2006–2007). We analyzed data in two stages; we applied a case-crossover analysis to simultaneously estimate effects of individual OC species on cause-specific hospital admissions. In the second stage we estimated the OC chemical group-specific effects, using a multivariate weighted regression.ResultsExposures to cyclohexanes of six days and longer were significantly and consistently associated with increased rate of hospital admissions for CVD (3.40%, 95%CI = (0.64, 6.24%) for 7-d exposure). Similar increases were found for hospitalizations for ischemic heart disease and myocardial infarction. For respiratory related hospital admissions, associations with OC groups were less consistent, although exposure to iso-/anteiso-alkanes was associated with increased respiratory-related hospitalizations.ConclusionsResults suggest that week-long exposures to traffic-related, primary organic species are associated with increased rate of total and cause-specific CVD emergency hospital admissions. Associations were significant for cyclohexanes, but not hopanes, suggesting that chemical properties likely play an important role in primary OC toxicity.