ENVINT-D-20-01309: Long-term exposure to air pollution, road traffic noise, residential greenness, and prevalent and incident metabolic syndrome: Results from the population-based KORA F4/FF4 cohort in Augsburg, Germany

BACKGROUND

A growing number of epidemiological studies show associations between environmental factors and impaired cardiometabolic health. However, evidence is scarce concerning these risk factors and their impact on metabolic syndrome (MetS). This analysis aims to investigate associations between long-term exposure to air pollution, road traffic noise, residential greenness, and MetS.

METHODS

We used data of the first (F4, 2006-2008) and second (FF4, 2013-2014) follow-up of the population-based KORA S4 survey in the region of Augsburg, Germany, to investigate associations between exposures and MetS prevalence at F4 (N = 2883) and MetS incidence at FF4 (N = 1192; average follow-up: 6.5 years). Residential long-term exposures to air pollution - including particulate matter (PM) with a diameter < 10 µm (PM₁₀), PM < 2.5 µm (PM_2.5), PM between 2.5 and 10 µm (PM_coarse), absorbance of PM_2.5 (PM2.5_abs), particle number concentration (PNC), nitrogen dioxide (NO₂), ozone (O₃) - and road traffic noise were modeled by land-use regression models and noise maps. For greenness, the Normalized Difference Vegetation Index (NDVI) was obtained. We estimated Odds Ratios (OR) for single and multi-exposure models using logistic regression and generalized estimating equations adjusted for confounders. Joint Odds Ratios were calculated based on the Cumulative Risk Index. Effect modifiers were examined with interaction terms.

RESULTS

We found positive associations between prevalent MetS and interquartile range (IQR) increases in PM₁₀ (OR: 1.15; 95% confidence interval [95% CI]: 1.02, 1.29), PM_2.5 (OR: 1.14; 95% CI: 1.02, 1.28), PM_coarse (OR: 1.14; 95% CI: 1.02, 1.27), and PM_2.5abs (OR: 1.17; 95% CI: 1.03, 1.32). Results further showed negative, but non-significant associations between exposure to greenness and prevalent and incident MetS. No effects were seen for exposure to road traffic noise. Joint Odds Ratios from multi-exposure models were higher than ORs from models with only one exposure.

A case-control analysis of traceback investigations for Vibrio parahaemolyticus infections (vibriosis) and pre-harvest environmental conditions in Washington State, 2013-2018

BACKGROUND

Vibrio parahaemolyticus is a major cause of seafood-borne illness. It is naturally prevalent in brackish waters and accumulates in shellfish. Vibriosis cases are rising globally, likely due to rising temperatures.

OBJECTIVES

To identify associations between vibriosis in Washington State and pre-harvest environmental and V. parahaemolyticus genetic measurements sampled from shellfish.

METHODS

Successful vibriosis traceback investigations were spatiotemporally matched to routine intertidal oyster (Crassostrea gigas) sampling events, which included measurements of temperature, salinity, and V. parahaemolyticus genetic targets (thermolabile hemolysin: tlh; thermostable direct hemolysin: tdh; thermostable direct-related hemolysin: trh). Unmatched sampling events were treated as controls. Associations were evaluated using logistic regression models.

RESULTS

Systematic differences were observed across Washington harvesting zones. These included positive associations between the odds of vibriosis and all three genetic targets in South Puget Sound, with a large odds ratio (OR) = 13.0 (95% CI: 1.5, 115.0) for a 1-log₁₀ increase in tdh when total bacterium abundance was low (tlh < 1 log₁₀ MPN/g). A positive association also occurred for a 1 °C increase in tissue temperature OR = 1.20 (95% CI: 1.10, 1.30) while a negative association occurred for a similar increase in water temperature OR = 0.70 (95% CI: 0.59, 0.81). In contrast, the coastal bays displayed positive associations for water temperature OR = 2.16 (95% CI, 1.15, 4.05), and for a 1-log₁₀ increase in the tdh:trh ratio OR = 5.85 (95% CI, 1.06, 32.26).

DISCUSSION

The zonal variation in associations indicates unique pathogenic strain prominence, suggesting tdh+/trh+ strains in South Puget Sound, such as the O4:K12 serotype, and tdh+/trh- strains in the coastal bays. The temperature discrepancy between water and oyster tissue suggests that South Puget Sound pathogenic strains flourish with exposure to relatively warm air during low tide. These findings identify new ecological risk factors for vibriosis in Washington State that can be used in future prevention efforts.

Practical Methods and Technologies in Environmental Epidemiology

Environmental epidemiology is a science that applies traditional epidemiology methods and combines the characteristics of the relationship between environment and population health, and studies the relationship between external environmental factors and population health from a macro perspective. The following methods are usually used. (1) Descriptive research: including ecological research and current situation research. (2) Analytical research: including case-control research and group research. (3) Experimental epidemiological research. In this section, according to the short-term and long-term effects of studying environmental risk factors, it is divided into two parts. Short-term effect methods include time series study, case-crossover study, and panel study. Long-term effect methods include cross-sectional study, case-control study, and cohort study.

New insights into modeling exposure measurements below the limit of detection

In environmental epidemiology, it is of interest to assess the health effects of environmental exposures. Some exposure analytes present values that are below the laboratory limit of detection (LOD). There have been many methods proposed for handling this issue to incorporate exposures subject to LOD in risk modeling using logistic regression. We present a fresh look at proposed methods to handle exposure analytes that present values that are below the LOD.

Examining the relationship between ambient carbon monoxide, nitrogen dioxide, and mental health-related emergency department visits in California, USA

Growing evidence suggests air pollutants may harm the central nervous system, potentially impacting mental health. However, such impacts of air pollutants on mental health and the sub-populations most affected remain poorly understood, especially in California. We examined the relationship between short-term ambient carbon monoxide (CO), nitrogen dioxide (NO₂), and mental health-related emergency department (ED) visits in California from 2005 to 2013. Daily mean concentrations of the pollutants were acquired from the U.S. Environmental Protection Agency Air Quality System Data Mart ground monitoring data. Moving averages of pollutant concentrations were linked to counts of ED visits obtained from the California Office of Statewide Health Planning and Development. Seven mental health outcomes, defined by International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, were studied: all mental disorders, bipolar disorder, depression, schizophrenia, substance abuse, homicide/inflicted injury, and suicide/self-harm. Monitor-level associations were estimated with quasi-Poisson regression models and combined using random-effects meta-analysis. CO and NO₂ were found to be positively associated with ED visits due to homicide/inflicted injury, with the warm season (May-October) driving the CO association. An interquartile range (IQR) (0.28 ppm) increase in two-day average CO during the warm season was associated with a 3.13% (95% confidence interval (CI): 1.43, 4.84) elevation in risk of an ED visit due to homicide/inflicted injury (n = 122,749 ED visits). An IQR (10.79 ppb) increase in two-day average NO₂ was associated with a 2.60% (95% CI: 1.17, 4.05) elevation in risk of an ED visit due to homicide/inflicted injury (n = 206,919 ED visits). Subgroup analyses indicated children, Hispanics, and males were particularly vulnerable. Except for an inverse relationship between NO₂ and substance abuse, neither pollutant was robustly associated with visits due to other mental health morbidities. Our results suggest short-term elevations in CO and NO₂ may promote violent behavior. Further investigation in other populations and ranges of air pollution exposure is warranted.

Exposure to endocrine disruptor alkylphenols and the occurrence of endometrial cancer

Exposure to environmental chemicals with oestrogenic effects has been associated with the development of endometrial cancer (EMCa). EMCa has become the most commonly diagnosed cancer of the female genital tract. To further understand the potential association between exposure to environmental endocrine disruptors and the occurrence of EMCa, we performed a case-control study between 2011 and 2014. We aimed to detect and compare concentrations of a known hormone disruptor, alkylphenol, between women diagnosed with either EMCa or uterine leiomyoma, and those who did not have either of these. Subjects were women diagnosed with either EMCa or uterine leiomyoma (LM) and healthy controls. A structured questionnaire was administered to collect information on lifestyle and health status. Gas chromatography/mass spectrometry was used to measure urinary NP and OP concentrations in participants. Multiple regression analysis was used to examine the association between exposure and outcomes. Overall, 397 women were recruited, including 49 with EMCa, 247 with LM, and 101 controls. Among them, 73.6% showed detectable levels of NP and 61.0% showed detectable levels of OP. The EMCa group had a significantly higher NP concentration than the control group. Higher OP concentrations were also found in participants with EMCa than those with LM and controls. In addition, women in the upper tertile of the NP group had a significantly increased risk of EMCa occurrence (odds ratio [95% confidence interval] = 4.47 [1.69-11.84] for EMCa vs. control). The same was found in the group of women with more than the median level of OP (odds ratio [95% confidence interval] = 4.32 [2.01-9.30] for EMCa vs. LM). Stratification of pre- and post-menopausal groups resulted in a similar association. The results show that NP/OP exposure is associated with EMCa. Further investigations and exposure minimisation are suggested.

Linking physical and social environments with mental health in old age: a multisensor approach for continuous real-life ecological and emotional assessment

Background

Urban stress is mentioned as a plausible mechanism leading to chronic stress, which is a risk factor of depression. Yet, an accurate assessment of urban stressors in environmental epidemiology requires new methods. This article discusses methods for the sensor-based continuous assesment of geographic environments, stress and depressive symptoms in older age. We report protocols of the promoting mental well-being and healthy ageing in cities (MINDMAP) and Healthy Aging and Networks in Cities (HANC) studies nested in the RECORD Cohort as a background for a broad discussion about the theoretical foundation and monitoring tools of mobile sensing research in older age. Specifically, these studies allow one to compare how older people with and without depression perceive, navigate and use their environment; and how the built environments, networks of social contacts, and spatial mobility patterns influence the mental health of older people.

Methods

Our research protocol combines (1) Global Positioning System (GPS) and accelerometer tracking and a GPS-based mobility survey to assess participants’ mobility patterns, activity patterns and environmental exposures; (2) proximity detection to assess whether household members are close to each other; (3) ecological momentary assessment to track momentary mood and stress and environmental perceptions; and (4) electrodermal activity for the tentative prediction of stress. Data will be compared within individuals (at different times) and between persons with and without depressive symptoms.

Conclusion

The development of mobile sensing and survey technologies opens an avenue to improve understanding of the role of momentary stressors and resourcing features of residential and non-residential environments for older populations’ mental health. However, validation, privacy and ethical aspects are important issues to consider.

Interactions between environmental pollutants and dietary nutrients: current evidence and implications in epidemiological research

Environmental pollutants and nutrients may be present in the same foodstuffs or dietary patterns; share internal mechanisms of transport, metabolism and cellular uptake; or target the same molecular signalling pathways and biological functions. Lipophilic pollutants and nutrients, like dioxins and polyunsaturated fatty acids, may often converge at all aforementioned levels and thus the interactions become more likely. Despite this fact, the topic seems overlooked in mainstream epidemiological research. In this essay, we illustrate different levels of documented interactions between pollutants and nutrients with experimental, interventional and epidemiological evidence, paying special attention to lipophilic chemicals. We first describe common pollutants and nutrients encountered in diets and the internal lipophilic interface such as adipose tissue and serum lipids. Next, we discuss the preventive effects of nutrients against absorption and the toxic effects of pollutants, as well as the pollutant-induced perturbation of nutrient metabolism. Finally, we discuss the implications of nutrient-pollutant interactions in epidemiology, providing some examples of negative confounding, modification effect and statistical interactions reported for different outcomes including fetal growth, diabetes and cancer. The evidence discussed in this essay supports that the health impacts of chemicals have likely been underestimated due to the high risk of residual and coexposure confounding in diseases where interactions between pollutants and nutrients may occur.

What is new in the exposome?

The exposome concept refers to the totality of exposures from a variety of external and internal sources including chemical agents, biological agents, or radiation, from conception onward, over a complete lifetime. It encompasses also "psychosocial components" including the impact of social relations and socio-economic position on health. In this review we provide examples of recent contributions from exposome research, where we believe their application will be of the greatest value for moving forward. So far, environmental epidemiology has mainly focused on hard outcomes, such as mortality, disease exacerbation and hospitalizations. However, there are many subtle outcomes that can be related to environmental exposures, and investigations can be facilitated by an improved understanding of internal biomarkers of exposure and response, through the application of omic technologies. Second, though we have a wealth of studies on environmental pollutants, the assessment of causality is often difficult because of confounding, reverse causation and other uncertainties. Biomarkers and omic technologies may allow better causal attribution, for example using instrumental variables in triangulation, as we discuss here. Even more complex is the understanding of how social relationships (in particular socio-economic differences) influence health and imprint on the fundamental biology of the individual. The identification of molecular changes that are intermediate between social determinants and disease status is a way to fill the gap. Another field in which biomarkers and omics are relevant is the study of mixtures. Epidemiology often deals with complex mixtures (e.g. ambient air pollution, food, smoking) without fully disentangling the compositional complexity of the mixture, or with rudimentary approaches to reflect the overall effect of multiple exposures or components. From the point of view of disease mechanisms, most models hypothesize that several stages need to be transitioned through health to the induction of disease, but very little is known about the characteristics and temporal sequence of such stages. Exposome models reinforce the idea of a biography-to-biology transition, in that everyone's disease is the product of the individual history of exposures, superimposed on their underlying genetic susceptibilities. Finally, exposome research is facilitated by technological developments that complement traditional epidemiological study designs. We describe in depth one such new tools, adductomics. In general, the development of high-resolution and high-throughput technologies interrogating multiple -omics (such as epigenomics, transcriptomics, proteomics, adductomics and metabolomics) yields an unprecedented perspective into the impact of the environment in its widest sense on disease. The world of the exposome is rapidly evolving, though a huge gap still needs to be filled between the original expectations and the concrete achievements. Perhaps the most urgent need is for the establishment of a new generation of cohort studies with appropriately specified biosample collection, improved questionnaire data (including social variables), and the deployment of novel technologies that allow better characterization of individual environmental exposures, ranging from personal monitoring to satellite based observations.

Residential green space and medication sales for childhood asthma: A longitudinal ecological study in Belgium

BACKGROUND

Living in green environments has been associated with various health benefits, but the evidence for positive effects on respiratory health in children is ambiguous.

OBJECTIVE

To investigate if residential exposure to different types of green space is associated with childhood asthma prevalence in Belgium.

METHODS

Asthma prevalence was estimated from sales data of reimbursed medication for obstructive airway disease (OAD) prescribed to children between 2010 and 2014, aggregated at census tract level (n = 1872) by sex and age group (6-12 and 13-18 years). Generalized log-linear mixed effects models with repeated measures were used to estimate effects of relative covers of forest, grassland and garden in the census tract of the residence on OAD medication sales. Models were adjusted for air pollution (PM₁₀), housing quality and administrative region.

RESULTS

Consistent associations between OAD medication sales and relative covers of grassland and garden were observed (unadjusted parameter estimates per IQR increase of relative cover, range across four strata: grassland, β = 0.15-0.17; garden, β = 0.13-0.17). The associations remained significant after adjusting for housing quality and chronic air pollution (adjusted parameter estimates per IQR increase of relative cover, range across four strata: grassland, β = 0.10-0.14; garden, β = 0.07-0.09). There was no association between OAD medication sales and forest cover.

CONCLUSIONS

Based on aggregated data, we found that living in close proximity to areas with high grass cover (grasslands, but also residential gardens) may negatively impact child respiratory health. Potential allergic and non-allergic mechanisms that underlie this association include elevated exposure to grass pollen and fungi and reduced exposure to environmental biodiversity. Reducing the dominance of grass in public and private green space might be beneficial to reduce the childhood asthma burden and may simultaneously improve the ecological value of urban green space.

Building capacity for air pollution epidemiology in India

Air pollution represents a major public health threat in India affecting 19% of the world's population at extreme levels. Despite this, research in India lags behind in large part due to a lack of comprehensive air pollution exposure assessment that can be used in conjunction with health data to investigate health effects. Our vision is to provide a consortium to rapidly expand the evidence base of the multiple effects of ambient air pollution. We intend to leapfrog current limitations of exposure assessment by developing a machine-learned satellite-informed spatiotemporal model to estimate daily levels of ambient fine particulate matter measuring less than 2.5 µm (PM2.5) at a fine spatial scale across all of India. To catalyze health effects research on an unprecedented scale, we will make the output from this model publicly available. In addition, we will also apply these PM2.5 estimates to study the health outcomes of greatest public health importance in India, including cardiovascular diseases, chronic obstructive pulmonary disease, pregnancy (and birth) outcomes, and cognitive development and/or decline. Thus, our efforts will directly generate actionable new evidence on the myriad effects of air pollution on health that can inform policy decisions, while providing a comprehensive and publicly available resource for future studies on both exposure and health effects. In this commentary, we discuss the motivation, rationale, and vision for our consortium and a path forward for reducing the enormous burden of disease from air pollution in India.

Role of perceived neighbourhood crime in the longitudinal association between perceived built environment and type 2 diabetes mellitus: a moderated mediation analysis

BACKGROUND

We examined to what extent perceived neighbourhood crime moderates, associations between type 2 diabetes mellitus (T2DM) and perceived local amenities, recreational facilities, footpaths and public transit, and potential mediation of environmental characteristics-T2DM association by physical activity, social contact, sleep and body mass index (BMI).

METHODS

The 45 and Up Study data of 36, 224 individuals collected from 2010 to 2015 were analysed in 2019 using multilevel logistic regression to examine the association between T2DM and clustering of unfavourable built environment, and any difference in the association with increasing unfavourable environment and area disadvantage. We performed causal mediation analyses stratified by crime to examine whether crime moderated the strength of identified local amenities-T2DM pathways.

RESULTS

The results showed that irrespective of crime, perceived lack of local amenities was associated with increased odds of developing T2DM, and BMI mediated 40% and 30.3% of this association among those who reported unsafe and safe daytime crime, respectively. The proportion mediated by BMI among those who reported unsafe and safe night-time crime was 27.3% and 35.1%, respectively. Walking mediated 5.7% of the local amenities-T2DM association among those who reported safe daytime crime. The odds of T2DM increased with rising unfavourable environment and area disadvantage.

CONCLUSIONS

The results suggest that the availability of neighbourhood amenities may lower T2DM risk by increasing walking and reducing BMI regardless of area crime. Policies to enhance access to local amenities and prevent crime, especially in disadvantaged areas, may support healthy behaviour and physical health that can potentially reduce T2DM risk.

Early life exposure to green space and insulin resistance: An assessment from infancy to early adolescence

BACKGROUND

Recent studies suggest that greater exposure to natural vegetation, or "green space" is associated with lower diabetes risk, possibly through increasing physical activity. However, there is limited research on green space and insulin resistance in youth. We hypothesized greater green space at early-life sensitive time periods would be associated with lower insulin resistance in youth.

METHODS

We used data from Project Viva (N = 460), a pre-birth cohort study that recruited pregnant women in eastern Massachusetts, 1999-2002, and followed offspring into adolescence. We defined residential green space exposure at infancy (median age - 1.1 years), early childhood (3.2 years), mid-childhood (7.7 years), and early adolescence (12.8 years), using 30 m resolution Landsat satellite imagery to estimate the Normalized Difference Vegetation Index [NDVI]. Our main outcome was early adolescence estimated insulin resistance (HOMA-IR). We used multiple imputation to account for missing data and multiple linear regression models adjusted for age, sex, race/ethnicity, parental education, household income, and neighborhood median household income.

RESULTS

The highest green space tertile had the highest percentage of white participants (85%), college-educated mothers (87%) and fathers (85%), and households with income higher than US$70,000 (86%). Unadjusted models showed that participants living in the highest green space tertile at infancy had a 0.15 unit lower HOMA-IR (95% CI: -0.23, -0.06) in early adolescence, than those living in the lowest tertile. However, in adjusted models, we did not observe evidence of associations between green space from infancy to early adolescence and HOMA-IR in early adolescence, although some point estimates were in the hypothesized direction. For example, participants in the highest green space tertile in infancy had 0.03 units lower HOMA-IR (95%CI: -0.14, 0.08) than those living in the lowest tertile.

CONCLUSIONS

Exposure to green space at early life sensitive time periods was not associated with HOMA-IR in youth. Early-life longitudinal studies across diverse populations are needed to confirm or refute our results.

A Systematic Review of Environmental Health Outcomes in Selected American Indian and Alaska Native Populations

BACKGROUND

Economic and social marginalization among American Indians and Alaska Natives (AI/ANs) results in higher chronic disease prevalence. Potential causal associations between toxic environmental exposures and adverse health outcomes within AI/AN communities are not well understood.

OBJECTIVES

This review examines epidemiological literature on exposure to toxicants and associated adverse health outcomes among AI/AN populations.

METHODS

PubMed, Embase, Cochrane, Environment Complete, Web of Science Plus, DART, and ToxLine were searched for English-language articles. The following data were extracted: lead author's last name, publication year, cohort name, study location, AI/AN tribe, study initiation and conclusion, sample size, primary characteristic, environmental exposure, health outcomes, risk estimates, and covariates.

RESULTS

About 31 articles on three types of environmental exposures met inclusion criteria: persistent organic pollutants (POPs), heavy metals, and open dumpsites. Of these, 17 addressed exposure to POPs, 10 heavy metal exposure, 2 exposure to both POPs and heavy metals, and 2 exposure to open dumpsites. Studies on the Mohawk Nation at Akwesasne; Yupik on St. Lawrence Island, Alaska; Navajo Nation; Gila River Indian Community; Cheyenne River Sioux; 197 Alaska Native villages; and 13 tribes in Arizona, Oklahoma, North Dakota, and South Dakota that participated in the Strong Heart Study support associations between toxicant exposure and various chronic conditions including cardiovascular conditions, reproductive abnormalities, cancer, autoimmune disorders, neurological deficits, and diabetes.

DISCUSSION

The complex interplay of environmental and social factors in disease etiology among AI/ANs is a product of externally imposed environmental exposures, systemic discrimination, and modifiable risk behaviors. The connection between environmental health disparities and adverse health outcomes indicates a need for further study.

[Combined effects of different environmental factors on health: air pollution, temperature, green spaces, pollen, and noise]

Environmental factors affect the health and wellbeing of urban residents. However, they do not act individually on humans, but instead show potential synergistic or antagonistic effects. Questions that arise from this are: How does a combination of air pollutants with other environmental factors impact health? How well are these associations evidenced? What methods can we use to look at them? In this article, methodical approaches regarding the effects of a combination of various environmental factors are first described. Environmental factors are then examined, which together with different air pollutants, have an impact on human health such as ambient temperature, noise, and pollen as well as the effect of green spaces. Physical activity and nutrition are addressed regarding the attenuation of health effects from air pollution.While there is often clear evidence of health effects of single environmental stressors, there are still open questions in terms of their interaction. The research methods required for this still need to be further developed. The interrelationship between the different environmental factors make it clear that (intervention) measures for reducing single indicators are also interlinked. Regarding traffic, switching from passive to active transport (e.g., due to safe cycle paths and other measures) leads to less air pollutants, smaller increases in temperature in the long term, and at the same time improved health of the individual. As a result, sensible planning of the built environment has great potential to reduce environmental stressors and improve people's health and wellbeing.

Exposure to particulate matter (PM2.5) and prevalence of diabetes mellitus in Indonesia

BACKGROUND

Recently emerging evidence suggests an association between particulate matter less than 2.5 µm in diameter (PM_2.5) exposure and diabetes risk. However, evidence from Asia is limited. Here, we evaluated the association between PM_2.5 exposure and the prevalence of diabetes mellitus in one of the most populated countries in Asia, Indonesia.

METHODS

We used the 2013 Indonesia Basic Health Research, which surveyed households in 487 regencies/municipalities in all 33 provinces in Indonesia (n = 647,947). We assigned individual exposure to PM_2.5 using QGIS software. Multilevel logistic regression with a random intercept based on village and cubic spline analysis were used to assess the association between PM_2.5 exposure and the prevalence of diabetes mellitus. We also assessed the lower exposure at which PM_2.5 has potential adverse effects.

RESULTS

We included 647,947 subjects with a mean age of 41.9 years in our study. Exposure to PM_2.5 levels was associated with a 10-unit increase in PM_2.5 (fully adjusted odds ratio: 1.09; 95% confidence interval: 1.05-1.14). The findings were consistent for quartile increases in PM_2.5 levels and the cubic spline function. Even when we restricted to those exposed to PM_2.5 concentrations of less than 10.0 µg/m³ in accordance with the recommended guidelines for annual exposure to PM_2.5 made by the World Health Organization, the association remained elevated, especially among subjects living in the urban areas. Hence, we were unable to establish a safe threshold for PM_2.5 and the risk of diabetes.

CONCLUSIONS

Our findings suggest a positive association between PM_2.5 exposure and prevalence of diabetes mellitus, which is possibly below the current recommended guidelines. Further studies are needed to ascertain the causal association of this finding.

Risk of 30-day mortality and its association with alcohol concentration level among driver victims of motor vehicle crashes: comparison of population- and hospital-based designs

BACKGROUND

Although blood alcohol concentration (BAC) is undoubtedly associated with increased risk of injury among driver victims involved in motor vehicle crashes (MVCs), some studies noted that high BAC was associated with reduced risk of mortality after injury. In addition, most of the previous studies included only injured patients admitted, which may lead to potential selection bias arising from exclusion of those with minor injury and those who died at the accident scene of MVC.

METHOD

The population-based design included 2586 driver victims with BAC equivalent >0 and 10 307 matched controls (BAC equivalent =0) selected from the Police-reported Traffic Accident Registry from 1 July to 31 December 2016 in Taiwan. The hospital-based design comprised a subset sample, which included 517 driver victims with BAC equivalent >0 and 662 with BAC equivalent =0 hospitalised on the same day the MVCs occurred. Conditional logistic regression models with adjustment for potential confounders were used to estimate the ORs and 95% CIs of 30-day mortality associated with BAC equivalent level.

RESULTS

In the population-based design, a positive dose-gradient relationship was observed between BAC equivalent level and 30-day mortality, with a covariate-adjusted OR of 3.77 (95% CI 1.84 to 7.72), 6.19 (95% CI 3.13 to 12.26) and 7.75 (95% CI 4.51 to 13.32) for low, moderate and high BAC equivalent levels, respectively. By contrast, the hospital-based design revealed no significant association between 30-day mortality and alcohol concentration regardless of the BAC equivalent level.

CONCLUSION

The association between BAC equivalent level and short-term mortality could have been overlooked in hospital-based studies that excluded MVC-related deaths outside hospital settings.

Association between air pollution and lung development in schoolchildren in China

Background

China has been facing nationwide air pollution at unprecedented high levels primarily from fossil–fuel combustion in the past decade. However, few studies have been conducted on the adverse effect of severe air pollution on lung development in school-age children.

Methods

Using wellness check and air pollution data from 2014 to 2017, we conducted a retrospective analysis of lung development in 21 616 school-age children from Shijiazhuang and Qingdao from North China with severe vs mild air pollution. Linear mixed effects model was performed to assess the effect of air pollution on forced vital capacity (FVC) growth.

Results

Exposure to severe air pollution was associated with a dramatic reduction in annual FVC growth rate (−71.3 mL,  p< 0.001). In addition, every 10 μg/m³ increase in annual PM_2.5 level was associated with a reduction of annual FVC growth by 12.2 mL ( p< 0.001). Sex discrepancy (boys vs girls) in FVC growth was greater in Qingdao (35.4 mL/year, 95% CI: 26.0 to 44.7) than in Shijiazhuang (19.8 mL/year, 95% CI: 9.3 to 30.3) (p for interaction=0.063). Exposure to indoor coal- or wood-burning stove heating (−79.4 mL,  p< 0.001) and secondhand smoke at home (−59.3 mL,  p= 0.003) were inversely associated with FVC growth.

Conclusion

Our study raised serious alarm over the threat of severe air pollution to lung development in school-age children. Sex discrepancy in lung development was reduced dramatically in heavily polluted area.

Income, income inequality and schizophrenia in China: a population-based multilevel analysis

BACKGROUND

Previous studies have suggested that socio-environmental factors interact with genetic risk in the genesis of schizophrenia. This study aimed to investigate the relationship between income, income inequality and schizophrenia and its heterogeneity among different geographic scales and subgroups.

METHODS

We used data from the Second China National Sample Survey on Disability (2006). The sample consisted of 1 909 205 participants aged 18 years or older. Individuals who were suspected to be psychiatrically disabled were administered the WHO Disability Assessment Schedule, Version II and the International Statistical Classification of Diseases, Tenth Revision Symptom Checklist for Mental Disorders by trained clinical psychiatrists to diagnose schizophrenia. Gross household income per capita was used to calculate the Gini coefficient to measure income inequality. Multilevel logistic regression with cross-level interaction was applied to examine the association of income, income inequality and schizophrenia.

RESULTS

A total of 7 628 persons (0.40%) were identified as having schizophrenia. Income was independently associated with schizophrenia. At the province level, greater income inequality was significantly associated with a higher risk of schizophrenia (OR, 1.03; 95% CI 1.00 to 1.06), and no significant association was observed at the county level. The analysis with cross-level interaction showed that the association at the province level was most pronounced in the highest income quartile (OR, 1.02; 95% CI 1.00 to 1.03).

CONCLUSION

The significant association between income and schizophrenia was consistent with the absolute income hypothesis. The adverse effect of income inequality on the risk of schizophrenia starts to operate at a larger area level, and it is more pronounced for the affluent population in China. This finding further supports the relative income hypothesis and social causation pathway for schizophrenia and calls attention to the vulnerability of high-income groups.

Perinatal urinary benzophenone-3 concentrations and glucose levels among women from a fertility clinic

BACKGROUND

Subfertile women have higher risk of glucose intolerance during pregnancy. Studies suggest associations between several endocrine disrupting chemicals (EDCs) and pregnancy glucose levels. However, the association between benzophenone-3 (BP-3), an EDC widely found in sunscreen, and pregnancy glucose levels remains unclear. We aimed to assess the association between perinatal exposures to BP-3 and pregnancy glucose levels in subfertile women.

METHODS

We evaluated 217 women from a prospective cohort based at a fertility clinic who had urinary BP-3 concentrations measured during 3-month preconception, first and/or second trimesters, and blood glucose measured at glucose load tests (GLTs) during late pregnancy. Multivariable linear and logistic regression models were used to assess associations between time-specific BP-3 in quartiles (Q1 - Q4) and mean glucose levels, as well as odds of abnormal GLT (glucose level ≥ 140 mg/dL), adjusting for potential confounders. Effect modification was assessed by age, season, BMI, infertility diagnosis, sex of fetus (es) and physical activity.

RESULTS

Women with higher first trimester BP-3 concentrations had lower mean glucose levels [mean glucose (95% CI) for Q4 vs Q1 = 103.4 (95.0, 112.5) vs. 114.6 (105.8, 124.2) mg/dL]. Women with higher second trimester BP-3 concentrations had lower odds of abnormal GLT [OR (95% CI) for Q3 vs. Q1 = 0.12 (0.01, 0.94)]. The associations between BP-3 and glucose levels were modified by several factors: women with female-factor infertility, urine collected during summer, older age, lower BMI, or carried female fetus (es) had the strongest inverse associations between BP-3 and glucose levels, while no associations were observed in the remaining subgroups.

CONCLUSIONS

Time-specific inverse associations between BP-3 and pregnancy glucose levels existed in subfertile women, and especially among certain subgroups of this high-risk-population.

The contribution of residential greenness to mortality among men with prostate cancer: a registry-based cohort study of Black and White men

Black men with prostate cancer (CaP) experience excess mortality compared with White men. Residential greenness, a health promoting contextual factor, could explain racial disparities in mortality among men with CaP.

Applying the exposome concept in birth cohort research: a review of statistical approaches

The exposome represents the totality of life course environmental exposures (including lifestyle and other non-genetic factors), from the prenatal period onwards. This holistic concept of exposure provides a new framework to advance the understanding of complex and multifactorial diseases. Prospective pregnancy and birth cohort studies provide a unique opportunity for exposome research as they are able to capture, from prenatal life onwards, both the external (including lifestyle, chemical, social and wider community-level exposures) and the internal (including inflammation, metabolism, epigenetics, and gut microbiota) domains of the exposome. In this paper, we describe the steps required for applying an exposome approach, describe the main strengths and limitations of different statistical approaches and discuss their challenges, with the aim to provide guidance for methodological choices in the analysis of exposome data in birth cohort studies. An exposome approach implies selecting, pre-processing, describing and analyzing a large set of exposures. Several statistical methods are currently available to assess exposome-health associations, which differ in terms of research question that can be answered, of balance between sensitivity and false discovery proportion, and between computational complexity and simplicity (parsimony). Assessing the association between many exposures and health still raises many exposure assessment issues and statistical challenges. The exposome favors a holistic approach of environmental influences on health, which is likely to allow a more complete understanding of disease etiology.

Learning from Sisyphus: time to rethink our current, ineffective strategy on neurodevelopmental environmental toxicants

BACKGROUND

The overwhelming number of potentially toxic chemicals in consumer products and in our daily environment makes it unrealistic to carry out in-depth analyses of each product with the objective of banning and eliminating toxic chemicals from our environment.

OBJECTIVES

To present the challenges that environmental toxicology and epidemiology are currently facing in the context of ubiquitous chemical pollution.

DISCUSSION

We propose a realistic and pragmatic approach to this Herculean problem.

Effects of ambient particulate matter on fasting blood glucose: A systematic review and meta-analysis

Studies have found that ambient particulate matter (PM) affects fasting blood glucose. However, the results are not consistent. We conducted a systematic review and meta-analysis to determine the relationship between PM with an aerodynamic diameter of 10 μm or less (PM₁₀) and PM with an aerodynamic diameter of 2.5 μm or less (PM_2.5) and fasting blood glucose. We searched PubMed, Web of Science, the Wanfang Database and the China National Knowledge Infrastructure up to April 1, 2019. A total of 24 papers were included in the review, and 17 studies with complete or convertible quantitative information were included in the meta-analysis. The studies were divided into groups by PM size fractions (PM₁₀ and PM_2.5) and length of exposure. Long-term exposures were based on annual average concentrations, and short-term exposures were those lasting less than 28 days. In the long-term exposure group, fasting blood glucose increased 0.10 mmol/L (95% CI: 0.02, 0.17) per 10 μg/m³ of increased PM₁₀ and 0.23 mmol/L (95% CI: 0.01, 0.45) per 10 μg/m³ of increased PM_2.5. In the short-term exposure group, fasting blood glucose increased 0.02 mmol/L (95% CI: -0.01, 0.04) per 10 μg/m³ of increased PM₁₀ and 0.08 mmol/L (95% CI: 0.04, 0.11) per 10 μg/m³ of increased PM_2.5. Further prospective studies are needed to explore the relationship between ambient PM exposure and fasting blood glucose.

Acute respiratory effects of livestock-related air pollution in a panel of COPD patients

Living close to livestock farms has been associated with increased symptoms in patients with chronic obstructive pulmonary disease (COPD). The causes of these effects are still poorly understood. This panel study attempts to assess the acute effects of livestock-related air pollution in patients with COPD living in an area with intensive livestock farming in the Netherlands. Between February 2015 and July 2016, 82 participants took spirometry measurements twice daily (morning and evening) during a 3-month period, resulting in 12,672 FEV₁ and PEF records. Participants also kept a diary on respiratory symptoms as well as livestock-related odor annoyance. Daily average ammonia (NH₃) (a proxy for livestock-related air pollution) and fine particulate matter (PM₁₀) levels were collected from monitoring stations in the area. Lung function was analyzed as decrements of >10% and >20% from their median as well as absolute values. Self-reported odor annoyance was analyzed as a dichotomous variable. All analyses were done using generalized estimated equations. We adjusted for humidity, temperature, linear trend, and took multiple testing into account. We found an odds ratio of 1.14 95%CI [1.05; 1.25] for decrements >20% in morning FEV₁ per interquartile range (12 µg/m³) increase in NH₃ concentration (lag 2). Odor annoyance was negatively associated with evening PEF (-4.46 l/min 95%CI [-7.59; -1.33]). Sensitivity analyses showed a stronger effect in participants with worse baseline lung function. No associations with symptoms were found. Our results show acute effects of livestock-related air pollution on lung function in COPD patients living in close proximity to livestock farms.

High Cancer Risk in US Naval Personnel Serving in Nuclear Powered Ships

The USA Defense Threat Reduction Agency provided data in 2014 on the health status, including cancer, of the 4,843 sailors on the nuclear-powered United States Ship (USS) Ronald Reagan over the 2.55-year period from May 12, 2011 to Dec 31, 2013. Also provided were data on a matched control group of 65,269 US Navy personnel. Examination of the control population relative to the US national data gives a relative risk for all malignancies of RR = 9.2 (95% CI 8.48 < 9.2 < 9.96). The result suggests a significant cancer risk associated with serving on a nuclear-powered ship, one which is not predicted by the science underlying current radiation protection legislation.

The impact of long-term PM2.5 exposure on specific causes of death: exposure-response curves and effect modification among 53 million U.S. Medicare beneficiaries

BACKGROUND

The shape of the exposure-response curve for long-term ambient fine particulate (PM_2.5) exposure and cause-specific mortality is poorly understood, especially for rural populations and underrepresented minorities.

METHODS

We used hybrid machine learning and Cox proportional hazard models to assess the association of long-term PM_2.5 exposures on specific causes of death for 53 million U.S. Medicare beneficiaries (aged ≥65) from 2000 to 2008. Models included strata for age, sex, race, and ZIP code and controlled for neighborhood socio-economic status (SES) in our main analyses, with approximately 4 billion person-months of follow-up, and additionally for warm season average of 1-h daily maximum ozone exposures in a sensitivity analysis. The impact of non-traffic PM_2.5 on mortality was examined using two stage models of PM_2.5 and nitrogen dioxide (NO₂).

RESULTS

A 10 μg /m³ increase in 12-month average PM_2.5 prior to death was associated with a 5% increase in all-cause mortality, as well as an 8.8, 5.6, and 2.5% increase in all cardiovascular disease (CVD)-, all respiratory-, and all cancer deaths, respectively, in age, gender, race, ZIP code, and SES-adjusted models. PM_2.5 exposures, however, were not associated with lung cancer mortality. Results were not sensitive to control for ozone exposures. PM_2.5-mortality associations for CVD- and respiratory-related causes were positive and significant for beneficiaries irrespective of their sex, race, age, SES and urbanicity, with no evidence of a lower threshold for response or of lower Risk Ratios (RRs) at low PM_2.5 levels. Associations between PM_2.5 and CVD and respiratory mortality were linear and were higher for younger, Black and urban beneficiaries, but were largely similar by SES. Risks associated with non-traffic PM_2.5 were lower than that for all PM_2.5 and were null for respiratory and lung cancer-related deaths.

CONCLUSIONS

PM_2.5 was associated with mortality from CVD, respiratory, and all cancer, but not lung cancer. PM_2.5-associated risks of CVD and respiratory mortality were similar across PM_2.5 levels, with no evidence of a threshold. Blacks, urban, and younger beneficiaries were most vulnerable to the long-term impacts of PM_2.5 on mortality.

Phthalate exposure and prostate cancer in a population-based nested case-control study

BACKGROUND

Phthalic acid esters are established as endocrine disruptors. The study aimed to evaluate the association between urinary phthalate metabolites and prostate cancer occurrence.

METHODS

The study was based on the Taiwan Community-Based Cancer Screening Program, which was set up in 1991-1992 and followed periodically. By 2010, 80 incident prostate cancer cases were identified in the 12,020 men. For each case, 2 controls were randomly selected, matched by age (±3 years), urine collection date (±3 months), and residential township. Frequently used phthalate metabolites from the urine samples were quantified by liquid chromatography/electrospray ionization tandem mass spectrometry. Logistic regression was conducted to assess the association between the exposure levels and prostate cancer occurrence.

RESULTS

Exposure to di (2-ethylhexyl), butyl-benzyl and di-isobutyl phthalates (DEHP, BBzP, DiBP) was positively associated with prostate cancer in men with waist circumference (WC) ≥90 cm but not in the leans. Odds ratio for the DEHP metabolite summary score (upper tertile compared to the rest) and prostate cancer were 7.76 (95% CI = 1.95-30.9) for WC ≥ 90 cm.

CONCLUSIONS

DEHP, BBzP, and DiBP exposure were associated with prostate cancer occurrence in abdominally obese men. The main limitation remains the lack of mechanistic experiments and comparable toxicological data.

Blood Harmane (1-Methyl-9H-Pyrido[3,4-b]indole) and Mercury in Essential Tremor: A Population-Based, Environmental Epidemiology Study in the Faroe Islands

BACKGROUND

Essential tremor (ET) is among the most prevalent neurological diseases. Its environmental determinants are poorly understood. Harmane (1-methyl-9H-pyrido[3, 4-b]indole), a dietary tremor-producing neurotoxin, has been linked to ET in a few studies in New York and Madrid. Mercury, also a tremor-producing neurotoxin, has not been studied in ET. The Faroe Islands have been the focus of epidemiological investigations of numerous neurological disorders.

OBJECTIVE

In this population-based, case-control study, we directly measured blood harmane concentrations (HA) and blood mercury concentrations (Hg) in ET cases and controls.

METHODS

In total, 1,328 Faroese adults were screened; 26 ET cases were identified whose (HA) and (Hg) were compared to 197 controls.

RESULTS

Although there were no statistically significant differences between diagnostic groups, median (HA) was 2.7× higher in definite ET (4.13 g-10/mL) and 1.5× higher in probable ET (2.28 g-10/mL) than controls (1.53 g-10/mL). Small sample size was a limitation. For definite ET versus controls, p = 0.126. (Hg) were similar between groups.

CONCLUSIONS

We demonstrated marginally elevated (HA) in definite and probable ET. These data are similar to those previously published and possibly extend etiological links between this neurotoxin and ET to a third locale. The study did not support a link between mercury and ET.

Statistical spatial-temporal modeling of ambient ozone exposure for environmental epidemiology studies: A review

BACKGROUND

Studies have discovered the adverse health impacts of ambient ozone. Most epidemiological studies explore the relationship between ambient ozone and health effects based on fixed site monitoring data. Fine modeling of ground-level ozone exposure conducted by statistical models has great advantages for improving exposure accuracy and reducing exposure bias. However, there is no review summarizing such studies.

OBJECTIVES

A review is presented to summarize the basic process of model development and to provide some suggestions for researchers.

METHODS

A search of PubMed, Web of Science and the Wanfang Database was performed for dates through July 1, 2019 to obtain relevant studies worldwide. We also examined the references of the articles of interest to ensure that as many articles as possible were included.

RESULTS

The land use regression model (LUR model), random forest model and artificial neural network model have been used in this field. We summarized these studies in terms of model selection, data preparation, simulation scale selection, and model establishment and validation. Multiparameters are a major feature of models. Parameters that influence the formation of ground-level ozone concentrations and parameters that have been extremely important in previous articles should be considered first. The process of model establishment and validation is essentially a process of continuously optimizing the model performance, but there are certain differences in the specific models.

CONCLUSION

This review summarized the basic process of the statistical model for ambient ozone exposure. We gave the applicable conditions and application scope of different models and summarized the advantages and disadvantages of various models in ozone modeling research. In the future, research is still needed to explore this area based on its own research purposes and capabilities.

Mortality associated with wildfire smoke exposure in Washington state, 2006-2017: a case-crossover study

BACKGROUND

Wildfire events are increasing in prevalence in the western United States. Research has found mixed results on the degree to which exposure to wildfire smoke is associated with an increased risk of mortality.

METHODS

We tested for an association between exposure to wildfire smoke and non-traumatic mortality in Washington State, USA. We characterized wildfire smoke days as binary for grid cells based on daily average PM2.5 concentrations, from June 1 through September 30, 2006-2017. Wildfire smoke days were defined as all days with assigned monitor concentration above a PM2.5 value of 20.4 μg/m3, with an additional set of criteria applied to days between 9 and 20.4 μg/m3. We employed a case-crossover study design using conditional logistic regression and time-stratified referent sampling, controlling for humidex.

RESULTS

The odds of all-ages non-traumatic mortality with same-day exposure was 1.0% (95% CI: - 1.0 - 4.0%) greater on wildfire smoke days compared to non-wildfire smoke days, and the previous day's exposure was associated with a 2.0% (95% CI: 0.0-5.0%) increase. When stratified by cause of mortality, odds of same-day respiratory mortality increased by 9.0% (95% CI: 0.0-18.0%), while the odds of same-day COPD mortality increased by 14.0% (95% CI: 2.0-26.0%). In subgroup analyses, we observed a 35.0% (95% CI: 9.0-67.0%) increase in the odds of same-day respiratory mortality for adults ages 45-64.

CONCLUSIONS

This study suggests increased odds of mortality in the first few days following wildfire smoke exposure. It is the first to examine this relationship in Washington State and will help inform local and state risk communication efforts and decision-making during future wildfire smoke events.

Prenatal lead exposure and childhood executive function and behavioral difficulties in project viva

BACKGROUND

Lead is an established neurotoxicant and early life exposure to lead is associated with detrimental impacts on IQ and several neurobehavioral domains. Less is known, however, about effects of prenatal lead exposure below 5 μg/dL on executive function and on social, emotional and self-regulatory behaviors in childhood.

OBJECTIVES

To examine the association between prenatal lead exposure and childhood executive function and social, emotional and self-regulatory behaviors.

METHODS

We included 1006 mother-child pairs from the Project Viva prospective pre-birth cohort. We measured prenatal maternal lead in second-trimester erythrocytes. In mid-childhood (median 7.7 years), parents and teachers rated executive function related behaviors using the Behavior Rating Inventory of Executive Function (BRIEF) and behavioral difficulties using the Strengths and Difficulties Questionnaire (SDQ). We used multivariable linear regression models adjusted for maternal, paternal, and child characteristics and metal co-exposures.

RESULTS

Mean maternal erythrocyte lead concentration was 1.2 μg/dL (interquartile range [IQR] 0.8-1.5 μg /dL), equivalent to approximately 0.4 μg/dL in whole blood. In adjusted models, associations with parent and teacher-rated scales were largely null, although effect estimates were consistently positive, suggesting worse scores with increasing lead levels. For an IQR increase in lead, BRIEF Global Executive Composite (GEC) was 0.73 (95% CI: -0.06, 1.52) points higher for parent-rated scores and 0.42 (95% CI: -0.39, 1.23) points higher for teacher-rated scores. Associations were strongest for parent-rated BRIEF plan/organize (β = 0.85; 95% CI: 0.12, 1.59) and shift (β = 0.88; 95% CI: 0.01, 1.75) subscales, as well as the SDQ emotional problems subscale (β = 0.18; 95% CI: 0.03, 0.33).

DISCUSSION

In this cohort with lead levels commonly experienced by U.S. women, there were few statistically significant associations with childhood executive function and behavior. However, there was a trend of worse neurobehavioral scores with increasing prenatal lead concentrations, in particular for childhood emotional problems and capacity to plan/organize and shift. Our results highlight the importance of continuing efforts to eliminate lead exposure in the general population.

A case-crossover analysis of the relationship of air pollution with out-of-hospital sudden unexpected death in Wake County, North Carolina (2013-2015)

Out-of-hospital sudden unexpected deaths are non-accidental deaths that occur without obvious underlying causes and may account for 10% of natural deaths before age 65. Short-term exposure to ambient air pollution is associated with all-cause (non-accidental) and cause-specific (e.g., cardiovascular) mortality, and with immediate exposures often yielding the highest magnitude risk estimates. Few studies have focused on short-term exposure to air pollution and sudden unexpected deaths. Using the University of North Carolina Sudden Unexpected Death in North Carolina population, we examine associations between short-term criteria air pollutant exposures with sudden unexpected deaths using a time-stratified case-crossover design, with data on criteria air pollutants from the Environmental Protection Agency's Air Quality System. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression with air pollutant exposures scaled to roughly inter-quartile ranges; models were adjusted for average temperature and relative humidity on event day and preceding 3 days. Potential for confounding by co-pollutants were examined in two pollutant models. ORs for PM_2.5 at lag day 1 were elevated (adjusted OR for 5 μg/m³ increase: 1.17 (0.98, 1.40)), and were robust to co-pollutant adjustment. Elevated odds were observed for SO₂ at lag day 0, and reduced odds for O₃ at lag day 0; however, these associations were somewhat attenuated toward the null (SO₂) or were not robust (O₃) to co-pollutant adjustment. This analysis in a racially and socioeconomically diverse cohort, with a more inclusive definition of sudden unexpected death than is typically employed offers evidence that PM_2.5 may be a clinically relevant trigger of sudden unexpected deaths in susceptible individuals.

Repeated holdout validation for weighted quantile sum regression

Weighted Quantile Sum (WQS) regression is a method commonly used in environmental epidemiology to assess the impact of chemical mixtures in relation to a health outcome of interest. Data are partitioned into a single training and test set to reduce sample-specific chemical weights. However, in typical epidemiology sample sizes, this may produce unstable chemical weights and WQS index estimates, and investigators may resort to training and testing on the same data. To solve this problem, we propose repeated holdout validation whereby data are randomly partitioned 100 times, producing a distribution of validated results. Taking the mean as the final estimate, confidence estimates may also be calculated for inference. Further, this method helps characterize the variability in chemical weights, aiding in the identification of chemicals of concern. This is important since it may direct future research into specific chemicals.

Using data from 718 mother-child pairs in the Swedish Environmental Longitudinal, Mother and Child, Asthma and Allergy (SELMA) study, we assessed the association between prenatal exposure to 26 endocrine disrupting chemicals and child Intelligence Quotient (IQ). Results using a single partition were unstable, varying by random seed. The WQS index estimate was significant when all data was used (e.g. no partition) (β = −2.2 CI = −3.43, −0.98), but attenuated and nonsignificant using repeated holdout validation (β = −0.82 CI = −2.11, 0.45). When implementing WQS in epidemiologic studies with limited sample sizes, repeated holdout validation is a viable alternative to using a single, or no partitioning. Repeated holdout can both stabilize results and help characterize the uncertainty in identifying chemicals of concern, while maintaining some of the the rigor of holdout validation.

•

Repeated holdout validation improves the stability of WQS estimates in finite study samples

•

Uncertainty in identifying toxic chemicals of concern is acknowledged and characterized

Wrangling environmental exposure data: guidance for getting the best information from your laboratory measurements

BACKGROUND

Environmental health and exposure researchers can improve the quality and interpretation of their chemical measurement data, avoid spurious results, and improve analytical protocols for new chemicals by closely examining lab and field quality control (QC) data. Reporting QC data along with chemical measurements in biological and environmental samples allows readers to evaluate data quality and appropriate uses of the data (e.g., for comparison to other exposure studies, association with health outcomes, use in regulatory decision-making). However many studies do not adequately describe or interpret QC assessments in publications, leaving readers uncertain about the level of confidence in the reported data. One potential barrier to both QC implementation and reporting is that guidance on how to integrate and interpret QC assessments is often fragmented and difficult to find, with no centralized repository or summary. In addition, existing documents are typically written for regulatory scientists rather than environmental health researchers, who may have little or no experience in analytical chemistry.

OBJECTIVES

We discuss approaches for implementing quality assurance/quality control (QA/QC) in environmental exposure measurement projects and describe our process for interpreting QC results and drawing conclusions about data validity.

DISCUSSION

Our methods build upon existing guidance and years of practical experience collecting exposure data and analyzing it in collaboration with contract and university laboratories, as well as the Centers for Disease Control and Prevention. With real examples from our data, we demonstrate problems that would not have come to light had we not engaged with our QC data and incorporated field QC samples in our study design. Our approach focuses on descriptive analyses and data visualizations that have been compatible with diverse exposure studies with sample sizes ranging from tens to hundreds of samples. Future work could incorporate additional statistically grounded methods for larger datasets with more QC samples.

CONCLUSIONS

This guidance, along with example table shells, graphics, and some sample R code, provides a useful set of tools for getting the best information from valuable environmental exposure datasets and enabling valid comparison and synthesis of exposure data across studies.

The effect of ambient temperature on cardiovascular mortality in 27 Brazilian cities

BACKGROUND

There is limited evidence on the relationship between temperature and cardiovascular mortality in middle and low-income countries, particularly in Latin America. In this study, we investigated the total effect of temperature on cardiovascular mortality in 27 Brazilian cities, and the effect modification by geographic, socioeconomic, demographic and infrastructure characteristics within cities.

METHODS

In the city-specific analysis, we used time-series analyses to estimate the relationship between mean temperature and daily cardiovascular mortality using quasi-Poisson generalized linear models combined with distributed lag non-linear models. In the second stage, a meta-analysis was used to pool the effects of temperature on cardiovascular mortality for Brazil and its five regions (Central-West, North, Northeast, South, and Southeast). We used a meta-regression to examine the effect modification of city-specific geographic, socioeconomic, demographic and infrastructure-related variables.

RESULTS

The risks associated with temperature varied across the locations. Higher cardiovascular mortality was associated with low and high temperatures in most of the cities, Brazil and the Central-West, North, South, and Southeast regions. The overall relative risk (RR) for Brazil was 1.26 (95% confidence interval [CI]: 1.17-1.35) for the 1st percentile of temperature and 1.07 (95% CI: 1.01-1.13) for the 99th percentile of temperature versus the 79th percentile (27.7 °C), where RR was lowest. The temperature range was the variable that best explained the variation in effects among the cities, with greater effects in locations having a broader range.

CONCLUSIONS

The results indicate effects of low and high temperatures on the risk of cardiovascular mortality in most of Brazil's capital cities, besides a pooled effect for Brazil and the Central-West, North, South, and Southeast regions. These findings can help inform public policies addressing the health impact of temperature extremes, especially in the context of climate change.

[Applications of statistical models on surveillance data in ecological study]

In recent years, with the improvement of various surveillance network, surveillance system has become an important data source for ecological study. Different data types, including cross-sectional data, time series data and panel data, containing abundant information involving exposure, outcome and confoundings. Gradually, some new statistical methods have been developed or improved for the special structural characteristics of surveillance data. In this paper, we summarized the principles of these models, preconditions, as well as their advantages and limitations.

Per- and polyfluoroalkyl substances and blood lipid levels in pre-diabetic adults-longitudinal analysis of the diabetes prevention program outcomes study

Exposure to per- and polyfluoroalkyl substances (PFASs) may interfere with lipid regulation. However, most previous studies were cross-sectional with the risk of reverse causation, suggesting a need for long-term prospective studies. We examined the relationship of baseline plasma PFAS concentrations with repeated measures of blood lipids. We included 888 prediabetic adults from the Diabetes Prevention Program (DPP) and DPP Outcomes Study, who had measurements of 6 plasma PFAS concentrations at baseline (1996-1999) and repeated measures of blood lipids over 15 years of follow-up, and were initially randomized to placebo or a lifestyle intervention. We used linear regression to examine cross-sectional associations of PFAS concentrations and lipid levels at baseline, and evaluated prospective risks of hypercholesterolemia and hypertriglyceridemia using Cox proportional hazard models, and tested for effect modification by study arm. Participants (65.9% female, 57.0% White, 65.9% aged 40-59 years) had comparable PFAS concentrations [e.g., median (IQR) perfluorooctanoic acid (PFOA) 4.9 ng/mL (3.2)] with the general U.S. population in 1999-2000. We observed higher total cholesterol at baseline per doubling of PFOA (β: 6.1 mg/dL, 95% CI: 3.1, 9.04), perfluorohexane sulfonic acid (PFHxS, β: 2.2 mg/dL, 95% CI: 0.2, 4.3), and perfluorononanoic acid (PFNA, β: 2.9 mg/dL, 95% CI: 0.7, 5.0). Prospectively, baseline concentrations of several PFASs, including PFOA, PFOS, PFHxS and PFNA, predicted higher risks of incident hypercholesterolemia and hypertriglyceridemia, but only in the placebo group and not the lifestyle intervention group. For example, participants in the placebo group with PFOA concentration > median (4.9 ng/mL) were almost twice as likely (HR: 1.90, 95% CI: 1.25, 2.88) to develop hypertriglyceridemia compared to those ≤median. Findings suggest adverse effects of some PFASs on lipid profiles in prediabetic adults. However, the detrimental effect was attenuated with a lifestyle intervention.

Planetary Epidemiology: Towards First Principles

PURPOSE OF REVIEW

To combine evolutionary principles of competition and co-operation with limits to growth models, generating six principles for a new sub-discipline, called "planetary epidemiology." Suggestions are made for how to quantify four principles.

RECENT FINDINGS

Climate change is one of a suite of threats increasingly being re-discovered by health workers as a major threat to civilization. Although "planetary health" is now in vogue, neither it nor its allied sub-disciplines have, as yet, had significant impact on epidemiology. Few if any theorists have sought to develop principles for Earth system human epidemiology, in its ecological, social, and technological milieu. The principles of planetary epidemiology described here can be used to stimulate applied, quantitative work to explore past, contemporary, and future population health, at scales from local to planetary, in order to promote enduring health. It is also proposed that global well-being will decline this century, without radical reform.

DNA Methylation Age-Environmental Influences, Health Impacts, and Its Role in Environmental Epidemiology

PURPOSE OF REVIEW

DNA methylation-based aging biomarkers are valuable tools for evaluating the aging process from a molecular perspective. These epigenetic aging biomarkers can be evaluated across the lifespan and are tissue specific. This review examines the literature relating environmental exposures to DNA methylation-based aging biomarkers and also the literature evaluating these biomarkers as predictors of health outcomes.

RECENT FINDINGS

Multiple studies evaluated the association between air pollution and DNA methylation age and consistently observed that higher exposures are associated with elevated DNA methylation age. Psychosocial exposures, e.g., traumas and adolescent adversity, and infections are also associated with epigenetic aging. DNA methylation age has been repeatedly associated with mortality, cancer, and cognitive impairment. DNA methylation age is responsive to the environment and predictive of health outcomes. Studies are still needed to evaluate whether DNA methylation age acts as a mediator or modifier of environmental health effects and to understand the impact of factors such as race, gender, and genetics.

Statistical Approaches for Investigating Periods of Susceptibility in Children's Environmental Health Research

PURPOSE OF REVIEW

Children's environmental health researchers are increasingly interested in identifying time intervals during which individuals are most susceptible to adverse impacts of environmental exposures. We review recent advances in methods for assessing susceptible periods.

RECENT FINDINGS

We identified three general classes of modeling approaches aimed at identifying susceptible periods in children's environmental health research: multiple informant models, distributed lag models, and Bayesian approaches. Benefits over traditional regression modeling include the ability to formally test period effect differences, to incorporate highly time-resolved exposure data, or to address correlation among exposure periods or exposure mixtures. Several statistical approaches exist for investigating periods of susceptibility. Assessment of susceptible periods would be advanced by additional basic biological research, further development of statistical methods to assess susceptibility to complex exposure mixtures, validation studies evaluating model assumptions, replication studies in different populations, and consideration of susceptible periods from before conception to disease onset.

Arsenic exposure and serum antibody concentrations to diphtheria and tetanus toxoid in children at age 5: A prospective birth cohort in Bangladesh

BACKGROUND

Arsenic can impair immune function. Timing of exposure can influence potential immunotoxicity of arsenic exposure. We examined the association between drinking water arsenic concentrations (W-As) measured repeatedly during different exposure windows in early life and serum concentrations of IgG antibodies against diphtheria and tetanus toxoids (diphtheria and tetanus antibody).

METHODS

A prospective cohort of pregnant women was recruited in Bangladesh (2008-2011). Averaged W-As levels were calculated for: pregnancy (W-As_pregnancy): ≤16 weeks gestation and <1 month; toddlerhood (W-As_toddlerhood): 12 and 20-40 months; and early childhood (W-As_childhood): 4-5 years. Serum was collected from 502 vaccinated children at age 5 and concentrations of diphtheria and tetanus toxoid IgG (i.e. antibody) were quantified. Antibody concentrations >0.1 IU/mL were considered clinically sufficient for protection. Associations were estimated using linear and logistic regression models.

RESULTS

Inverse associations were observed between W-As_pregnancy and serum diphtheria antibody levels, while null associations were observed between W-As and tetanus antibody. Children within the highest versus lowest tertile of W-As_pregnancy had 91% greater odds of having clinically insufficient concentrations of diphtheria antibody (Odds ratio:1.91, 95% confidence interval (CI): 1.03, 3.56). Among females, a doubling in W-As_pregnancy was associated with 12.3% (95%CI: -20.1%, -4.5%) lower median concentrations of diphtheria antibody. Tetanus antibody was only associated with W-As_pregnancy among females (percent change in median: -9.5%, 95%CI: -17.6%, -1.3%). Among children who were stunted or underweight, a doubling in W-As_pregnancy was associated with decreased diphtheria antibody of 19.8% (95%CI: -32%, -7.5%) and 14.3% (95%CI: -26.7%, -2%), respectively.

CONCLUSIONS

Among vaccinated children, W-As measured during pregnancy was associated with decreased diphtheria antibody levels, but not tetanus antibody. However, W-As measured during toddlerhood and early childhood were not associated with either antibody outcome. Children's sex and malnutrition status were important effect modifiers of W-As for both diphtheria and tetanus antibody levels, highlighting the importance of these factors and the timing of the exposure when evaluating the effect of arsenic on humoral immunity.

Hospital, health, and community burden after oil refinery fires, Richmond, California 2007 and 2012

INTRODUCTION

Emergency Departments experience a significant census burst after disasters. The aim of this study is to describe patient presentations at Emergency Departments in Contra Costa County, California following chemical release incidents at an oil refinery in 2007 and 2012. Specific areas of focus include hospital and community burden with an emphasis on disease classes.

METHODS

Searching 4 weeks before through 4 weeks after each event, Emergency Department abstracts identified patients living in Contra Costa County and seeking care there or in neighboring Alameda County. City and ZIP-code of residence established proximity to the refinery. This provided the following contrast groups: Event (2007, 2012), time (before, after), location (bayside, rest of county), and within bayside, warned or not warned to shelter in place. Using the Multi-Level Clinical Classification Software, we classified primary health groups recorded 4 weeks before and after the events, then summarized the data, calculated rates, and made tables, graphs, and maps to highlight findings.

RESULTS

Number of visits meeting selection criteria totalled 105020 records. Visits increased modestly but statistically significantly after the 2007 incident. After the 2012 incident, two Emergency Departments took the brunt of the surge. Censuses increased from less than 600 a week each to respectively 5719 and 3072 the first week, with the greatest number 2 days post-event. It took 4 weeks for censuses to return to normal. The most common diagnosis groups that spiked were nervous/sensory, respiratory, circulatory, and injury. Bayside communities had statistically significant increases in residents seeking care. Specifically, visits of residents in warned communities nearest the refinery increased by a factor of 3.7 while visits of residents in other nearby un-warned communities increased by a factor of 1.5.

CONCLUSIONS

The 2012 Emergency Department census peaked in the first week and did not return to normal for 4 weeks. Diagnoses changed to reflect conditions associated with reactions to chemical exposures. Surrounding communities and nearby hospitals experienced significant emergent burdens. In addition to changes from such events in patient diagnoses and community burden, the discussion highlights the long-term implications of failures to require adequate monitoring and warning systems and failures of health planning.

Historical evidence of glyphosate exposure from a US agricultural cohort

In response to the recent review by Gillezeau et al., The evidence of human exposure to glyphosate: A review, Environmental Health 1/19/19, here we report additional glyphosate biomonitoring data from a repository of urine samples collected from United States farmers in 1997-98. To determine if glyphosate exposure could be identified historically, we examined urine samples from a biorepository of specimens collected from US dairy farmers between 1997 and 98. We compared samples from farmers who self-reported glyphosate application in the 8 h prior to sample collection to samples from farm applicators who did not report using glyphosate. Of 18 applicator samples tested, 39% showed detectable levels of glyphosate (mean concentration 4.04 μg/kg; range:1.3-12) compared to 0% detections among 17 non glyphosate applicator samples (p-value < 0.01). One of the applicator samples that tested positive for glyphosate also tested positive for AMPA. Concentrations of glyphosate were consistent with levels reported in the prior occupational biomonitoring studies reviewed by Gillezeau et al.Accurately detecting both glyphosate and AMPA in this small sample of Wisconsin farmers demonstrates a) glyphosate exposures among farmers were occurring 20 years ago, which was prior to the widespread planting of genetically engineered glyphosate tolerant crops first approved in 1996; and b) liquid chromatography tandem mass spectrometry (LC-MS/MS) can be used for sensitive characterization in cryopreserved urine samples. These data offer an important historical benchmark to which urinary levels from current and future biomonitoring studies can be compared.

Healthy worker, healthy citizen: the place of occupational health within public health research in Switzerland

OBJECTIVES

To assess the state of Swiss occupational health (OH) research over the period 2008-2017.

METHODS

Two types of indicators were constructed, focused, respectively, on resources available for OH research and its output. Data for their assessment were gathered from specialized research institutions, professional associations, and the Swiss Federal Statistical Office.

RESULTS

Thirty-two of 317 Ph.D./M.D.-Ph.D. theses delivered were in the field of OH. The number of OH physicians progressed substantially, but the density of OH professionals per number of active workers showed important variations between OH disciplines and geographical regions. The number of yearly peer-reviewed publications increased substantially but represented 6% of publications in public health in 2017. Psychological and respiratory health conditions were the most studied topics, while papers on cancers accounted for only 10%.

CONCLUSIONS

This study suggests a limited place of OH research in the Swiss public health landscape and the need for a national research effort in OH. This requires an improved collaboration between regional and federal authorities and communication/coordination between public health authorities and OH executive institutions belonging to the economic sector.

The metabolome: A key measure for exposome research in epidemiology

PURPOSE OF REVIEW

Application of omics to study human health has created a new era of opportunities for epidemiology research. However, approaches to characterize exogenous health triggers have largely not leveraged advances in analytical platforms and big data. In this review, we highlight the exposome, which is defined as the cumulative measure of exposure and biological responses across a lifetime as a cornerstone for new epidemiology approaches to study complex and preventable human diseases.

RECENT FINDINGS

While no universal approach exists to measure the entirety of the exposome, use of high-resolution mass spectrometry methods provide distinct advantages over traditional biomonitoring and have provided key advances necessary for exposome research. Application to different study designs and recommendations for combining exposome data with novel data analytic frameworks to study complex interactions of multiple stressors are also discussed.

SUMMARY

Even though challenges still need to be addressed, advances in methods to characterize the exposome provide exciting new opportunities for epidemiology to support fundamental discoveries to improve public health.

Ambient ozone and fine particulate matter exposures and autism spectrum disorder in metropolitan Cincinnati, Ohio

BACKGROUND

Epidemiological studies report fairly consistent associations between various air pollution metrics and autism spectrum disorder (ASD), with some elevated risks reported for different prenatal and postnatal periods.

OBJECTIVES

To examine associations between ASD and ambient fine particulate matter (PM_2.5) and ozone concentrations during the prenatal period through the second year of life in a case-control study.

METHODS

ASD cases (n = 428) diagnosed at Cincinnati Children's Hospital Medical Center were frequency matched (15:1) to 6420 controls from Ohio birth records. We assigned daily PM_2.5 and ozone estimates for 2005-2012 from US EPA's Fused Air Quality Surface Using Downscaling model to each participant for each day based on the mother's census tract of residence at birth. We calculated adjusted odds ratios (aORs) using logistic regression across continuous and categorical exposure window averages (trimesters, first and second postnatal years, and cumulative measure), adjusting for maternal- and birth-related confounders, both air pollutants, and multiple temporal exposure windows.

RESULTS

We detected elevated aORs for PM_2.5 during the 2nd trimester, 1st year of life, and a cumulative period from pregnancy through the 2nd year (aOR ranges across categories: 1.41-1.44, 1.54-1.84, and 1.41-1.52 respectively), and for ozone in the 2nd year of life (aOR range across categories: 1.29-1.42). Per each change in IQR, we observed elevated aORs for ozone in the 3rd trimester, 1st and 2nd years of life, and the cumulative period (aOR range: 1.19-1.27) and for PM_2.5 in the 2nd trimester, 1st year of life, and the cumulative period (aOR range: 1.11-1.17).

DISCUSSION

We saw limited evidence of linear exposure-response relationships for ASD with increasing air pollution, but the elevated aORs detected for PM_2.5 in upper exposure categories and per IQR unit increases were similar in magnitude to those reported in previous studies, especially for postnatal exposures.

Associations between repeated measure of plasma perfluoroalkyl substances and cardiometabolic risk factors

BACKGROUND

Perfluoroalkyl substances (PFAS) are persistent synthetic chemicals that may affect components of metabolic risk through the peroxisome proliferator-activated receptor but epidemiological data remain scarce and inconsistent.

OBJECTIVE

To estimate associations between repeated measurements of the main PFAS in plasma and total cholesterol, triglycerides and hypertension among the control subjects from a population-based nested case-control study on diabetes type 2 in middle-aged women and men.

METHODS

Participants (n = 187) were free of diabetes at both baseline and follow-up visits to the Västerbotten Intervention Programme, 10 years apart: during 1990 to 2003 (baseline) and 2001 to 2013 (follow-up). Participants left blood samples, completed questionnaires on diet and lifestyle factors, and underwent medical examinations, including measurement of blood pressure. PFAS and lipids were later determined in stored plasma samples. Associations for the repeated measurements were assessed using generalized estimating equations.

RESULTS

Six PFAS exceeded the limit of quantitation. Repeated measures of PFAS in plasma, cardiometabolic risk factors and confounders, showed an average decrease of triglycerides from -0.16 mmol/l (95% confidence interval [CI]: -0.33, 0.02 for PFOA) to -0.26 mmol/l (95% CI: -0.50, -0.08 for PFOS), when comparing the highest tertile of PFAS plasma levels with the lowest. Associations based on average PFAS measurements and follow-up triglycerides revealed similar inverse associations, although attenuated. The estimates for cholesterol and hypertension were inconsistent and with few exception non-significant.

CONCLUSIONS

This study found inverse associations between PFAS and triglycerides, but did not support any clear link with either cholesterol or hypertension.

Approaches for incorporating environmental mixtures as mediators in mediation analysis

Mediation analysis offers an essential and rapidly expanding tool in environmental health studies to investigate the contribution of environmental factors towards observed associations between risk factors and health outcomes. When evaluating environmental factors, there may be particular interest in quantifying the impact of exposure to environmental mixtures on human health. In this context, evaluating the joint effect of multiple chemicals or pollutants, rather than individual examination, allows accurate identification of risk factors, assessment of interactions, and ultimately development of more targeted public health interventions. While mediation analysis has been extended to incorporate several methodological complexities specific to environmental factors, little attention has been given to integrating the analysis of environmental mixtures. The aim of this review is to present some of the available methods for environmental mixtures, and discuss how these methods can be integrated within a mediation analysis framework. By incorporating these methods into a mediation framework, investigators will be able to evaluate the contribution of environmental mixtures as mediators of exposure-outcome associations, based on methodologies that are currently available. While standard regression-based methods for multiple mediators can be used, these can easily become unstable as the number of mixture components increases. Summary and classification methods, or hierarchical modeling, can reduce the number of mediators by creating scores or possibly uncorrelated subgroups. This approach allows retrieving indirect effects due to the mixture or to a specific subgroup, but makes identification of component-specific effects and interactions complicated. Finally, one can use various approaches for analyzing mixtures in a two-stage fashion, selecting relevant mediators to be included in the final model. We focused this review on techniques that have been presented to the environmental health community and that can be conducted with major statistical software. We encourage researchers to move beyond the evaluation of one environmental factor at a time to the assessment of the joint effects of environmental mixtures when a mediation model is of interest. Available methods target different aspects related to environmental mixtures and the choice of the suitable approach will depend on data structures and the research question of interest.