Rationale: Adverse effects of exposures to ambient air pollution on lung function are well documented, but evidence in racial/ethnic minority children is lacking.Objectives: To assess the relationship between air pollution and lung function in minority children with asthma and possible modification by global genetic ancestry. Methods:The study population consisted of 1,449 Latino and 519 African American children with asthma from five different geographical regions in the mainland United States and Puerto Rico. We examined five pollutants (particulate matter <10 mm and <2.5 mm in diameter, ozone, nitrogen dioxide, and sulfur dioxide), derived from participant residential history and ambient air monitoring data, and assessed over several time windows. We fit generalized additive models for associations between pollutant exposures and lung function parameters and tested for interaction terms between exposures and genetic ancestry. Measurements and Main Results:A 5 mg/m 3 increase in average lifetime particulate matter less than or equal to 2.5 mm in diameter exposure was associated with a 7.7% decrease in FEV 1 (95% confidence interval = 211.8 to 23.5%) in the overall study population. Global genetic ancestry did not appear to significantly modify these associations, but percent African ancestry was a significant predictor of lung function.Conclusions: Early-life particulate exposures were associated with reduced lung function in Latino and African American children with asthma. This is the first study to report an association between exposure to particulates and reduced lung function in minority children in which racial/ethnic status was measured by ancestry-informative markers.

Ambient particulate matter (PM) has been shown to have short- and long-term effects on cardiorespiratory mortality and morbidity. Most of the risk is associated with fine PM (PM(2.5)); however, recent evidence suggests that desert dust outbreaks are major contributors to coarse PM (PM(10-2.5)) and may be associated with adverse health effects. The objective of this study was to investigate the risk of total, cardiovascular and respiratory mortality associated with PM concentrations during desert dust outbreaks. We used a time-series design to investigate the effects of PM(10) on total non-trauma, cardiovascular and respiratory daily mortality in Cyprus, between 1 January 2004 and 31 December 2007. Separate PM(10) effects for non-dust and dust days were fit in generalized additive Poisson models. We found a 2.43% (95% CI: 0.53, 4.37) increase in daily cardiovascular mortality associated with each 10-μg/m(3) increase in PM(10) concentrations on dust days. Associations for total (0.13% increase, 95% CI: -1.03, 1.30) and respiratory mortality (0.79% decrease, 95% CI: -4.69, 3.28) on dust days and all PM(10) and mortality associations on non-dust days were not significant. Although further study of the exact nature of effects across different affected regions during these events is needed, this study suggests adverse cardiovascular effects associated with desert dust events.

The epidemiologic study of pregnancy and birth outcomes may be hindered by several unique and challenging issues. Pregnancy is a time-limited period in which severe cohort attrition takes place between conception and birth and adverse outcomes are complex and multi-factorial. Biases span those familiar to epidemiologists: selection, confounding and information biases. Specific challenges include conditioning on potential intermediates, how to treat race/ethnicity, and influential windows of prolonged, seasonal and potentially time-varying exposures. Researchers studying perinatal outcomes should be cognizant of the potential pitfalls due to these factors and address their implications with respect to formulating questions of interest, choice of an appropriate analysis approach and interpretations of findings given assumptions. In this article, we catalogue some of the more important potential sources of bias in perinatal epidemiology that have more recently gained attention in the literature, provide the epidemiologic context behind each issue and propose practices for dealing with each issue to the extent possible.

Background: The health burden from exposure to air pollution has been studied in many parts of the world. However, there is limited research on the health effects of air quality in arid areas where sand dust is the primary particulate pollution source. Objective: Study the risk of mortality from exposure to poor air quality days in Kuwait. Methods: We conducted a time-series analysis using daily visibility as a measure of particulate pollution and non-accidental total mortality from January 2000 through December 2016. A generalized additive Poisson model was used adjusting for time trends, day of week, and temperature. Low visibility (yes/no), defined as visibility lower than the 25th percentile, was used as an indicator of poor air quality days. Dust storm events were also examined. Finally, we examined these associations after stratifying by gender, age group, and nationality (Kuwaitis/non-Kuwaitis). Results: There were 73,748 deaths from natural causes in Kuwait during the study period. The rate ratio comparing the mortality rate on low visibility days to high visibility days was 1.01 (95% CI: 0.99–1.03). Similar estimates were observed for dust storms (1.02, 95% CI: 1.00–1.04). Higher and statistically significant estimates were observed among non-Kuwaiti men and non-Kuwaiti adolescents and adults. Conclusion: We observed a higher risk of mortality during days with poor air quality in Kuwait from 2000 through 2016.

Purpose of Review We offer an in-depth discussion of the time-varying confounding and selection bias mechanisms that give rise to the healthy worker survivor effect (HWSE). Recent Findings In this update of an earlier review, we distinguish between the mechanisms collectively known as the HWSE and the statistical bias that can result. This discussion highlights the importance of identifying both the target parameter and the target population for any research question in occupational epidemiology. Target parameters can correspond to hypothetical workplace interventions; we explore whether these target parameters’ true values reflect the etiologic effect of an exposure on an outcome or the potential impact of enforcing an exposure limit in a more realistic setting. If a cohort includes workers hired before the start of follow-up, HWSE mechanisms can limit the transportability of the estimates to other target populations. Summary We summarize recent publications that applied g-methods to control for the HWSE, focusing on their target parameters, target populations, and hypothetical interventions.

Although attenuation of the relationships between CTS and some biomechanical and work psychosocial exposures was observed after adjusting for confounding, the magnitudes were small and confirmed biomechanical and work psychosocial exposures as independent risk factors for incident CTS.

BackgroundExperimental evidence suggests that inhaled particles from vehicle exhaust have systemic effects on inflammation, endothelial activation and oxidative stress. In the present study we assess the relationships of short-term exposures with inflammatory endothelial activation and oxidative stress biomarker levels in a population of trucking industry workers.MethodsBlood and urine samples were collected pre and post-shift, at the beginning and end of a workweek from 67 male non-smoking US trucking industry workers. Concurrent measurements of microenvironment concentrations of elemental and organic carbon (EC & OC), and fine particulate matter (PM2.5) combined with time activity patterns allowed for calculation of individual exposures. Associations between daily and first and last-day average levels of exposures and repeated measures of intercellular and vascular cell adhesion molecule-1 (ICAM-1 & VCAM-1), interleukin 6 (IL-6) and C-reactive protein (CRP) blood levels and urinary 8-Hydroxy-2′-Deoxyguanosine (8-OHdG) were assessed using linear mixed effects models for repeated measures.ResultsThere was a statistically significant association between first and last-day average PM2.5 and 8-OHdG (21% increase, 95% CI: 2, 42%) and first and last-day average OC and IL-6 levels (18% increase 95% CI: 1, 37%) per IQR in exposure. There were no significant findings associated with EC or associations suggesting acute cross-shift effects.ConclusionOur findings suggest associations between weekly average exposures of PM2.5 on markers of oxidative stress and OC on IL-6 levels.

Marginal structural models (MSMs) and inverse probability weighting can be used to estimate risk in a cohort of active workers if there is a time-varying confounder (e.g., health status) affected by prior exposure-a feature of the healthy worker survivor effect. We applied Cox MSMs in a study of incident ischemic heart disease and exposure to particulate matter with aerodynamic diameter of 2.5 μm or less (PM2.5) in a cohort of 12,949 actively employed aluminum workers in the United States. The cohort was stratified by work process into workers in smelting facilities, herein referred to as "smelters" and workers in fabrication facilities, herein referred to as "fabricators." The outcome was assessed by using medical claims data from 1998 to 2012. A composite risk score based on insurance claims was treated as a time-varying measure of health status. Binary PM2.5 exposure was defined by the 10th-percentile cutoff for each work process. Health status was associated with past exposure and predicted the outcome and subsequent exposure in smelters but not in fabricators. In smelters, the Cox MSM hazard ratio comparing those always exposed above the cutoff with those always exposed below the cutoff was 1.98 (95% confidence interval: 1.18, 3.32). In fabricators, the hazard ratio from a traditional Cox model was 1.34 (95% confidence interval: 0.98, 1.83). Results suggest that occupational PM2.5 exposure increases the risk of incident ischemic heart disease in workers in both aluminum smelting and fabrication facilities.