Survival analysis with functions of mis-measured covariate histories: the case of chronic air pollution exposure in relation to mortality in the Nurses\u27 Health Study

Environmental epidemiologists are often interested in estimating the effect of functions of time-varying exposure histories, such as the 12-month moving average, in relation to chronic disease incidence or mortality. The individual exposure measurements that comprise such an exposure history are usually mis-measured, at least moderately, and, often, more substantially. To obtain unbiased estimates of Cox model hazard ratios for these complex mis-measured exposure functions, an extended risk set regression calibration (RRC) method for Cox models is developed and applied to a study of long-term exposure to the fine particulate matter ($PM_{2.5}$) component of air pollution in relation to all-cause mortality in the Nurses\u27 Health Study. Simulation studies under several realistic assumptions about the measurement error model and about the correlation structure of the repeated exposure measurements were conducted to assess the finite sample properties of this new method, and found that the method has good performance in terms of finite sample bias reduction and nominal confidence interval coverage. User-friendly software has been developed and is available to the general public on the senior author\u27s website

Workplace secondhand smoke exposure in the U.S. trucking industry.

BackgroundAlthough the smoking rate in the United States is declining because of an increase of smoke-free laws, among blue-collar workers it remains higher than that among many other occupational groups.ObjectivesWe evaluated the factors influencing workplace secondhand smoke (SHS) exposures in the U.S. unionized trucking industry.MethodsFrom 2003 through 2005, we measured workplace SHS exposure among 203 nonsmoking and 61 smoking workers in 25 trucking terminals. Workers in several job groups wore personal vapor-phase nicotine samplers on their lapels for two consecutive work shifts and completed a workplace SHS exposure questionnaire at the end of the personal sampling.ResultsMedian nicotine level was 0.87 microg/m3 for nonsmokers and 5.96 microg/m3 for smokers. As expected, smokers experienced higher SHS exposure duration and intensity than did nonsmokers. For nonsmokers, multiple regression analyses indicated that self-reported exposure duration combined with intensity, lack of a smoking policy as reported by workers, having a nondriver job, and lower educational level were independently associated with elevated personal nicotine levels (model R2 = 0.52). Nondriver job and amount of active smoking were associated with elevated personal nicotine level in smokers, but self-reported exposure, lack of a smoking policy, and lower educational level were not.ConclusionsDespite movements toward smoke-free laws, this population of blue-collar workers was still exposed to workplace SHS as recently as 2005. The perceived (reported by the workers), rather than the official (reported by the terminal managers), smoking policy was associated with measured SHS exposure levels among the nonsmokers. Job duties and educational level might also be important predictors of workplace SHS exposure

Secondhand smoke exposure and inflammatory markers in nonsmokers in the trucking industry.

BackgroundFew studies have directly assessed the association of secondhand smoke (SHS) with cardiovascular disease-related inflammatory markers, and the findings are inconsistent.ObjectivesWe assessed the association between SHS exposure and the inflammatory markers high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and soluble intercellular adhesion molecule-1 (sICAM-1) in 199 nonsmoking U.S. trucking industry workers.MethodsParticipants provided blood samples either by mail (blood drawn at local health care provider near home) or at the work site (blood drawn by research staff on-site) and completed a health and work history questionnaire at the time of blood draw. Exposure to SHS was measured by plasma cotinine concentrations. We used multivariate regression analyses to assess the associations between levels of cotinine and inflammatory markers.ResultsThe median cotinine level was 0.10 ng/mL (interquartile range, 0.04-0.23 ng/mL). The odds ratios of elevated hs-CRP (above highest CRP tertile, 1.5 mg/L) were 2.85 [95% confidence interval (CI), 1.03-7.89] for the high-cotinine group (> 0.215 ng/mL) and 2.80 (95% CI, 1.11-7.10) for the moderate-cotinine group (0.05-0.215 ng/mL), compared with the low-cotinine group (< 0.05 ng/mL), adjusting for age, sex, race, educational level, obesity, previous smoking history, job title, and medical history. Plasma cotinine levels were not associated with IL-6 or sICAM-1.ConclusionsSHS exposure, as assessed by plasma cotinine, was positively associated with hs-CRP in this group of blue-collar workers. The strength of the association with hs-CRP depended on the cut points selected for analysis

Chronic Obstructive Pulmonary Disease Mortality in Diesel-Exposed Railroad Workers

Diesel exhaust is a mixture of combustion gases and ultrafine particles coated with organic compounds. There is concern whether exposure can result in or worsen obstructive airway diseases, but there is only limited information to assess this risk. U.S. railroad workers have been exposed to diesel exhaust since diesel locomotives were introduced after World War II, and by 1959, 95% of the locomotives were diesel. We conducted a case–control study of railroad worker deaths between 1981 and 1982 using U.S. Railroad Retirement Board job records and next-of-kin smoking, residential, and vitamin use histories. There were 536 cases with chronic obstructive pulmonary disease (COPD) and 1,525 controls with causes of death not related to diesel exhaust or fine particle exposure. After adjustment for age, race, smoking, U.S. Census region of death, vitamin use, and total years off work, engineers and conductors with diesel-exhaust exposure from operating trains had an increased risk of COPD mortality. The odds of COPD mortality increased with years of work in these jobs, and those who had worked ≥ 16 years as an engineer or conductor after 1959 had an odds ratio of 1.61 (95% confidence interval, 1.12–2.30). These results suggest that diesel-exhaust exposure contributed to COPD mortality in these workers. Further study is needed to assess whether this risk is observed after exposure to exhaust from later-generation diesel engines with modern emission controls

Air Pollution Exposures During Adulthood and Risk of Endometriosis in the Nurses’ Health Study II

Background: Particulate matter and proximity to large roadways may promote disease mechanisms, including systemic inflammation, hormonal alteration, and vascular proliferation, that may contribute to the development and severity of endometriosis. Objective: Our goal was to determine the association of air pollution exposures during adulthood, including distance to road, particulate matter < 2.5 μm, between 2.5 and 10 μm, and < 10 μm, (PM2.5, PM10–2.5, PM10), and timing of exposure with risk of endometriosis in the Nurses’ Health Study II. Methods: Proximity to major roadways and outdoor levels of PM2.5, PM10–2.5, and PM10 were determined for all residential addresses from 1993 to 2007. Multivariable-adjusted time-varying Cox proportional hazard models were used to estimate the relation between these air pollution exposures and endometriosis risk. Results: Among 84,060 women, 2,486 incident cases of surgically confirmed endometriosis were identified over 710,230 person-years of follow-up. There was no evidence of an association between endometriosis risk and distance to road or exposure to PM2.5, PM10–2.5, or PM10 averaged over follow-up or during the previous 2- or 4-year period. Conclusions: Traffic and air pollution exposures during adulthood were not associated with incident endometriosis in this cohort of women. Citation: Mahalingaiah S, Hart JE, Laden F, Aschengrau A, Missmer SA. 2014. Air pollution exposures during adulthood and risk of endometriosis in the Nurses’ Health Study II. Environ Health Perspect 122:58–64; http://dx.doi.org/10.1289/ehp.130662

Lung Cancer in Railroad Workers Exposed to Diesel Exhaust

Diesel exhaust has been suspected to be a lung carcinogen. The assessment of this lung cancer risk has been limited by lack of studies of exposed workers followed for many years. In this study, we assessed lung cancer mortality in 54,973 U.S. railroad workers between 1959 and 1996 (38 years). By 1959, the U.S. railroad industry had largely converted from coal-fired to diesel-powered locomotives. We obtained work histories from the U.S. Railroad Retirement Board, and ascertained mortality using Railroad Retirement Board, Social Security, and Health Care Financing Administration records. Cause of death was obtained from the National Death Index and death certificates. There were 43,593 total deaths including 4,351 lung cancer deaths. Adjusting for a healthy worker survivor effect and age, railroad workers in jobs associated with operating trains had a relative risk of lung cancer mortality of 1.40 (95% confidence interval, 1.30–1.51). Lung cancer mortality did not increase with increasing years of work in these jobs. Lung cancer mortality was elevated in jobs associated with work on trains powered by diesel locomotives. Although a contribution from exposure to coal combustion products before 1959 cannot be excluded, these results suggest that exposure to diesel exhaust contributed to lung cancer mortality in this cohort

Lung Cancer and Vehicle Exhaust in Trucking Industry Workers

Background: An elevated risk of lung cancer in truck drivers has been attributed to diesel exhaust exposure. Interpretation of these studies specifically implicating diesel exhaust as a carcinogen has been limited because of limited exposure measurements and lack of work records relating job title to exposure-related job duties. Objectives: We established a large retrospective cohort of trucking company workers to assess the association of lung cancer mortality and measures of vehicle exhaust exposure.Methods Work records were obtained for 31,135 male workers employed in the unionized U.S. trucking industry in 1985. We assessed lung cancer mortality through 2000 using the National Death Index, and we used an industrial hygiene review and current exposure measurements to identify jobs associated with current and historical use of diesel-, gas-, and propane-powered vehicles. We indirectly adjusted for cigarette smoking based on an industry survey.Results Adjusting for age and a healthy-worker survivor effect, lung cancer hazard ratios were elevated in workers with jobs associated with regular exposure to vehicle exhaust. Mortality risk increased linearly with years of employment and was similar across job categories despite different current and historical patterns of exhaust-related particulate matter from diesel trucks, city and highway traffic, and loading dock operations. Smoking behavior did not explain variations in lung cancer risk. Conclusions: Trucking industry workers who have had regular exposure to vehicle exhaust from diesel and other types of vehicles on highways, city streets, and loading docks have an elevated risk of lung cancer with increasing years of work.Statistic

Particulate matter and risk of parkinson disease in a large prospective study of women

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

Spatio-temporal modeling of particulate air pollution in the conterminous United States using geographic and meteorological predictors

Background: Exposure to atmospheric particulate matter (PM) remains an important public health concern, although it remains difficult to quantify accurately across large geographic areas with sufficiently high spatial resolution. Recent epidemiologic analyses have demonstrated the importance of spatially- and temporally-resolved exposure estimates, which show larger PM-mediated health effects as compared to nearest monitor or county-specific ambient concentrations. Methods: We developed generalized additive mixed models that describe regional and small-scale spatial and temporal gradients (and corresponding uncertainties) in monthly mass concentrations of fine (PM2.5), inhalable (PM10), and coarse mode particle mass (PM2.5–10) for the conterminous United States (U.S.). These models expand our previously developed models for the Northeastern and Midwestern U.S. by virtue of their larger spatial domain, their inclusion of an additional 5 years of PM data to develop predictions through 2007, and their use of refined geographic covariates for population density and point-source PM emissions. Covariate selection and model validation were performed using 10-fold cross-validation (CV). Results: The PM2.5 models had high predictive accuracy (CV R2=0.77 for both 1988–1998 and 1999–2007). While model performance remained strong, the predictive ability of models for PM10 (CV R2=0.58 for both 1988–1998 and 1999–2007) and PM2.5–10 (CV R2=0.46 and 0.52 for 1988–1998 and 1999–2007, respectively) was somewhat lower. Regional variation was found in the effects of geographic and meteorological covariates. Models generally performed well in both urban and rural areas and across seasons, though predictive performance varied somewhat by region (CV R2=0.81, 0.81, 0.83, 0.72, 0.69, 0.50, and 0.60 for the Northeast, Midwest, Southeast, Southcentral, Southwest, Northwest, and Central Plains regions, respectively, for PM2.5 from 1999–2007). Conclusions: Our models provide estimates of monthly-average outdoor concentrations of PM2.5, PM10, and PM2.5–10 with high spatial resolution and low bias. Thus, these models are suitable for estimating chronic exposures of populations living in the conterminous U.S. from 1988 to 2007