Toxics Use Reduction: Pro and Con

With the Massachusetts Toxics Use Reduction Act as an example, important issues related to the goals and effectiveness of TUR are examined. The benefits as claimed by proponents are contrasted with shortcomings outlined by opponents in point-counterpoint style. Ultimately, the authors call for more balanced analysis

The Concentration-Response Relation Between PM2.5_{2.5} and Daily Deaths.

Particulate air pollution at commonly occurring concentrations is associated with daily deaths. Recent attention has focused on the shape of the concentration-response curve, particularly at low doses. Several recent articles have reported that particulate matter with aerodynamic diameter $\leq 10 \mu$m PM$_{10}$) was associated with daily deaths with no evidence of a threshold. These reports have used smoothing or spline methods in individual cities and pooled the results across multiple cities to obtain estimates that are more robust. To date, fine particulate matter (aerodynamic diameter $\leq 2.5 \mu$m; PM$_{2.5}$), a component of PM$_{10}$, has not been examined in this regard. We examined this association in a hierarchical model in six U.S. cities. In the first stage, we fit log-linear models including smooth functions of PM$_{2.5}$ in each city, controlling for season, weather, and day of the week. These smooth functions allowed for nonlinearities in the city-specific associations. We combined the estimated curves across cities using a hierarchical model that allows for heterogeneity. We found an essentially linear relationship down to 2 $\mu$g/m$_3$. The same approach was applied to examine the concentration response to traffic particles, controlling for particles from other sources. Once again, the association showed no sign of a threshold. The magnitude of the association suggests that controlling fine particle pollution would result in thousands of fewer early deaths per year

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

A Bayesian localised conditional auto-regressive model for estimating the health effects of air pollution

Estimation of the long-term health effects of air pollution is a challenging task, especially when modeling spatial small-area disease incidence data in an ecological study design. The challenge comes from the unobserved underlying spatial autocorrelation structure in these data, which is accounted for using random effects modeled by a globally smooth conditional autoregressive model. These smooth random effects confound the effects of air pollution, which are also globally smooth. To avoid this collinearity a Bayesian localized conditional autoregressive model is developed for the random effects. This localized model is flexible spatially, in the sense that it is not only able to model areas of spatial smoothness, but also it is able to capture step changes in the random effects surface. This methodological development allows us to improve the estimation performance of the covariate effects, compared to using traditional conditional auto-regressive models. These results are established using a simulation study, and are then illustrated with our motivating study on air pollution and respiratory ill health in Greater Glasgow, Scotland in 2011. The model shows substantial health effects of particulate matter air pollution and nitrogen dioxide, whose effects have been consistently attenuated by the currently available globally smooth models

Latent profile analysis of accelerometer-measured sleep, physical activity, and sedentary time and differences in health characteristics in adult women.

ObjectivesIndependently, physical activity (PA), sedentary behavior (SB), and sleep are related to the development and progression of chronic diseases. Less is known about how rest-activity behaviors cluster within individuals and how rest-activity behavior profiles relate to health. In this study we aimed to investigate if adult women cluster into profiles based on how they accumulate rest-activity behavior (including accelerometer-measured PA, SB, and sleep), and if participant characteristics and health outcomes differ by profile membership.MethodsA convenience sample of 372 women (mean age 55.38 + 10.16) were recruited from four US cities. Participants wore ActiGraph GT3X+ accelerometers on the hip and wrist for a week. Total daily minutes in moderate-to-vigorous PA (MVPA) and percentage of wear-time spent in SB was estimated from the hip device. Total sleep time (hours/minutes) and sleep efficiency (% of in bed time asleep) were estimated from the wrist device. Latent profile analysis (LPA) was performed to identify clusters of participants based on accumulation of the four rest-activity variables. Adjusted ANOVAs were conducted to explore differences in demographic characteristics and health outcomes across profiles.ResultsRest-activity variables clustered to form five behavior profiles: Moderately Active Poor Sleepers (7%), Highly Actives (9%), Inactives (41%), Moderately Actives (28%), and Actives (15%). The Moderately Active Poor Sleepers (profile 1) had the lowest proportion of whites (35% vs 78-91%, p < .001) and college graduates (28% vs 68-90%, p = .004). Health outcomes did not vary significantly across all rest-activity profiles.ConclusionsIn this sample, women clustered within daily rest-activity behavior profiles. Identifying 24-hour behavior profiles can inform intervention population targets and innovative behavioral goals of multiple health behavior interventions

Chronic Exposure to Fine Particles and Mortality: An Extended Follow-up of the Harvard Six Cities Study from 1974 to 2009

Background: Epidemiologic studies have reported associations between fine particles (aerodynamic diameter ≤ 2.5 µm; PM:2.5) and mortality. However, concerns have been raised regarding the sensitivity of the results to model specifications, lower exposures, and averaging time. Objective: We addressed these issues using 11 additional years of follow-up of the Harvard Six Cities study, incorporating recent lower exposures. Methods: We replicated the previously applied Cox regression, and examined different time lags, the shape of the concentration–response relationship using penalized splines, and changes in the slope of the relation over time. We then conducted Poisson survival analysis with time-varying effects for smoking, sex, and education. Results: Since 2001, average PM:2.5 levels, for all six cities, were < 18 µg/m3. Each increase in PM2.5 (10 µg/m3) was associated with an adjusted increased risk of all-cause mortality (PM2.5 average on previous year) of 14% [95% confidence interval (CI): 7, 22], and with 26% (95% CI: 14, 40) and 37% (95% CI: 7, 75) increases in cardiovascular and lung-cancer mortality (PM2.5 average of three previous years), respectively. The concentration–response relationship was linear down to PM2.5 concentrations of 8 µg/m3. Mortality rate ratios for PM2.5 fluctuated over time, but without clear trends despite a substantial drop in the sulfate fraction. Poisson models produced similar results. Conclusions: These results suggest that further public policy efforts that reduce fine particulate matter air pollution are likely to have continuing public health benefits

Urinary naphthalene and phenanthrene as biomarkers of occupational exposure to polycyclic aromatic hydrocarbons.

OBJECTIVES: The study investigated the utility of unmetabolised naphthalene (Nap) and phenanthrene (Phe) in urine as surrogates for exposures to mixtures of polycyclic aromatic hydrocarbons (PAHs). METHODS: The report included workers exposed to diesel exhausts (low PAH exposure level, n = 39) as well as those exposed to emissions from asphalt (medium PAH exposure level, n = 26) and coke ovens (high PAH exposure level, n = 28). Levels of Nap and Phe were measured in urine from each subject using head space-solid phase microextraction and gas chromatography-mass spectrometry. Published levels of airborne Nap, Phe and other PAHs in the coke-producing and aluminium industries were also investigated. RESULTS: In post-shift urine, the highest estimated geometric mean concentrations of Nap and Phe were observed in coke-oven workers (Nap: 2490 ng/l; Phe: 975 ng/l), followed by asphalt workers (Nap: 71.5 ng/l; Phe: 54.3 ng/l), and by diesel-exposed workers (Nap: 17.7 ng/l; Phe: 3.60 ng/l). After subtracting logged background levels of Nap and Phe from the logged post-shift levels of these PAHs in urine, the resulting values (referred to as ln(adjNap) and ln(adjPhe), respectively) were significantly correlated in each group of workers (0.71 < or = Pearson r < or = 0.89), suggesting a common exposure source in each case. Surprisingly, multiple linear regression analysis of ln(adjNap) on ln(adjPhe) showed no significant effect of the source of exposure (coke ovens, asphalt and diesel exhaust) and further suggested that the ratio of urinary Nap/Phe (in natural scale) decreased with increasing exposure levels. These results were corroborated with published data for airborne Nap and Phe in the coke-producing and aluminium industries. The published air measurements also indicated that Nap and Phe levels were proportional to the levels of all combined PAHs in those industries. CONCLUSION: Levels of Nap and Phe in urine reflect airborne exposures to these compounds and are promising surrogates for occupational exposures to PAH mixtures

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

Multivariate space-time modelling of multiple air pollutants and their health effects accounting for exposure uncertainty

The long-term health effects of air pollution are often estimated using a spatio-temporal ecological areal unit study, but this design leads to the following statistical challenges: (1) how to estimate spatially representative pollution concentrations for each areal unit; (2) how to allow for the uncertainty in these estimated concentrations when estimating their health effects; and (3) how to simultaneously estimate the joint effects of multiple correlated pollutants. This article proposes a novel 2-stage Bayesian hierarchical model for addressing these 3 challenges, with inference based on Markov chain Monte Carlo simulation. The first stage is a multivariate spatio-temporal fusion model for predicting areal level average concentrations of multiple pollutants from both monitored and modelled pollution data. The second stage is a spatio-temporal model for estimating the health impact of multiple correlated pollutants simultaneously, which accounts for the uncertainty in the estimated pollution concentrations. The novel methodology is motivated by a new study of the impact of both particulate matter and nitrogen dioxide concentrations on respiratory hospital admissions in Scotland between 2007 and 2011, and the results suggest that both pollutants exhibit substantial and independent health effects

A cross-sectional study of secondhand smoke exposure and respiratory symptoms in non-current smokers in the U.S. trucking industry: SHS exposure and respiratory symptoms

Background: Previous studies have suggested associations of adult exposures to secondhand smoke (SHS) with respiratory symptoms, but no study has focused on blue-collar industrial environments. We assessed the association between SHS and respiratory symptoms in 1,562 non-current smoking U.S. trucking industry workers. Methods: Information on SHS exposure and respiratory health was obtained by questionnaire. Multiple logistic regression analyses were used to assess the associations of recent and lifetime exposures to SHS with chronic phlegm, chronic cough, and any wheeze, defined by American Thoracic Society criteria. Results: In analyses adjusted for age, gender, race, childhood SHS exposure, former smoking, pack-years of smoking and years since quitting, body mass index, job title, region of the country, and urban residence, recent exposures to SHS were associated with all three respiratory symptoms (odds ratio (OR) = 1.46; 95% confidence interval (CI) = 1.00-2.13) for chronic cough, 1.55 (95% CI = 1.08-2.21) for chronic phlegm, and 1.76 (95% CI = 1.41-2.21) for any wheeze). Workplace exposure was the most important recent exposure. Childhood exposure to SHS was also associated with all three symptoms, but only statistically significantly for chronic phlegm (OR = 1.84; 95% CI = 1.24-2.75). Additional years of living with a smoker were associated with an increased risk, but there was no evidence of a dose–response, except for chronic phlegm. Conclusions: In this group of trucking industry workers, childhood and recent exposures to SHS were related to respiratory symptoms