Person:

Fitzgerald, Kathryn C.

Background: Exposure to metals has been implicated in the pathogenesis of Parkinson disease (PD). Objectives: We sought to examine in a large prospective study of female nurses whether exposure to airborne metals was associated with risk of PD. Methods: We linked the U.S. Environmental Protection Agency (EPA)’s Air Toxics tract-level data with the Nurses’ Health Study, a prospective cohort of female nurses. Over the course of 18 years of follow-up from 1990 through 2008, we identified 425 incident cases of PD. We examined the association of risk of PD with the following metals that were part of the first U.S. EPA collections in 1990, 1996, and 1999: arsenic, antimony, cadmium, chromium, lead, manganese, mercury, and nickel. To estimate hazard ratios (HRs) and 95% CIs, we used the Cox proportional hazards model, adjusting for age, smoking, and population density. Results: In adjusted models, the HR for the highest compared with the lowest quartile of each metal ranged from 0.78 (95% CI: 0.59, 1.04) for chromium to 1.33 (95% CI: 0.98, 1.79) for mercury. Conclusions: Overall, we found limited evidence for the association between adulthood ambient exposure to metals and risk of PD. The results for mercury need to be confirmed in future studies. Citation: Palacios N, Fitzgerald K, Roberts AL, Hart JE, Weisskopf MG, Schwarzschild MA, Ascherio A, Laden F. 2014. A prospective analysis of airborne metal exposures and risk of Parkinson disease in the Nurses’ Health Study Cohort. Environ Health Perspect 122:933–938; http://dx.doi.org/10.1289/ehp.1307218

Background: Exposure to air pollution has been implicated in a number of adverse health outcomes and the effect of particulate matter (PM) on the brain is beginning to be recognized. Yet, no prospective study has examined the association between PM and risk of Parkinson Disease. Thus, our goal was assess if exposure to particulate matter air pollution is related to risk of Parkinson’s disease (PD) in the Nurses’ Health Study (NHS), a large prospective cohort of women. Methods: Cumulative average exposure to different size fractions of PM up to 2 years before the onset of PD, was estimated using a spatio-temporal model by linking each individual’s places of residence throughout the study with location-specific air pollution levels. We prospectively followed 115,767 women in the NHS, identified 508 incident PD cases and used multivariable Cox proportional hazards models to estimate the risk of PD associated with each size fraction of PM independently. Results: In models adjusted for age in months, smoking, region, population density, caffeine and ibuprofen intake, we observed no statistically significant associations between exposure to air pollution and PD risk. The relative risk (RR) comparing the top quartile to the bottom quartile of PM exposure was 0.99 (95% Confidence Intervals (CI): 0.84,1.16) for PM10 (≤10 microns in diameter), 1.08 (95% CI: 0.81, 1.45) for PM2.5 (≤2.5 microns in diameter), and 0.92 (95% CI: 0.71, 1.19) for PM10–2.5 (2.5 to 10 microns in diameter). Conclusions: In this study, we found no evidence that exposure to air pollution is a risk factor for PD.

Background: Once atrial fibrillation (AF) progresses to sustained forms, adverse outcomes increase and treatment success rates decrease. Therefore, identification of risk factors predisposing to persistence of AF may have a significant impact on AF morbidity. Methods and Results: We prospectively examined the differential associations between traditional, lifestyle, and biomarker AF risk factors and development of paroxysmal versus nonparoxysmal AF (persistent/permanent) among 34 720 women enrolled in the Women's Health Study who were free of cardiovascular disease and AF at baseline. AF patterns were defined based on current guidelines and classified according to the most sustained form of AF within 2 years of diagnosis. During a median follow‐up of 16.4 years, 690 women developed paroxysmal AF and 349 women developed nonparoxysmal AF. In multivariable time‐varying competing risk models, increasing age (hazard ratio [HR] 1.11, 95% CI 1.10 to 1.13, versus HR 1.08, 1.07 to 1.09, per year), body mass index (HR 1.07, 1.05 to 1.09, versus HR 1.03, 1.02 to 1.05, per kg/m2), and weight (HR 1.30, 1.22 to 1.39, versus HR 1.14, 1.08 to 1.20, per 10 kg) were more strongly associated with the development of nonparoxysmal AF compared with paroxysmal AF. Hemoglobin A1c levels at baseline were directly related to the development of nonparoxysmal AF but inversely associated with paroxysmal AF in multivariable competing risk models (P for nonequal association=0.01). Conclusions: In women without AF or CVD at baseline, increasing age, adiposity, and higher hemoglobin A1c levels were preferentially associated with the early development of nonparoxysmal AF. These data raise the hypothesis that efforts aimed at weight reduction or glycemic control may affect the proportion of the population with sustained AF.

The following dissertation addresses of two themes: the role of vitamin D and neurodegenerative diseases and methodologic concepts related to correlated missing outcome data. In the first chapter, the relation between vitamin D (characterized by circulating levels of 25Zhydroxyvitamin D 25[OH]D) and multiple sclerosis (MS) activity and progression is assessed in a secondary analysis of a population of over 1400 relapsing remitting MS patients with multiple asynchronous assessments of 25(OH)D. Overall, using a combination of clinical and magnetic resonance imaging endpoints, higher levels of vitamin D were associated with lesser MS activity. Results were more equivocal for clinical and brain volume measures. In the second chapter, the relation between dietary vitamin D and risk of amyotrophic lateral sclerosis (ALS) is assessed in pooled analysis of five prospective cohort studies. The study included nearly 1500 cases of ALS that occurred in a population of over 1 million individuals. Using dietary intake derived from food-frequency questionnaires, no association between dietary intake of vitamin D and risk of ALS was observed in any model. Similarly null results were observed for vitamin D intake from food and supplemental vitamin D. The third chapter addresses a methodologic concern when disease outcomes can be classified into multiple subtypes. It was not well understood of how to properly address marker-specific effects of a particular risk when markers are correlated and some are missing. This was addressed using an analysis of breast cancer in the Nurses’ Health Study (NHS) considering 5 markers with varying levels of correlation and missingness. Correlation among outcome measures was addressed through the calculation of an adjusted hazard ratio and four approaches for missing data were evaluated: the complete case, inverse probability weighting, missing indicator and multiple imputation. In the NHS, 4380 cases (with pathology reports) of breast cancer occurred; however, only 1551 cases had information on all five markers. We considered a list of established breast cancer risk factors and calculate adjusted marker-specific effects addressing missing using each of the 4 approaches. Effect estimates were generally similar for each method but corresponding standard errors were smaller using the multiple imputations and missing indicator approaches. Subsequent simulation studies suggest the missing indicator approach to produce the least bias and increases in standard error compared with datasets with complete information on all markers.