We are continuously exposed to dynamic mixtures of airborne contaminants that vary by location. Understanding the compositional diversity of these complex mixtures and the levels to which we are each exposed requires comprehensive exposure assessment. This comprehensive analysis is often lacking in population-based studies due to logistic and analytical challenges associated with traditional measurement approaches involving active air sampling and chemical-by-chemical analysis. The objective of this review is to provide an overview of wearable passive samplers as alternative tools to active samplers in environmental health research. The review highlights the advances and challenges in using wearable passive samplers for assessing personal exposure to organic chemicals and further presents a framework to enable quantitative measurements of exposure and expanded use of this monitoring approach to the population scale. Overall, wearable passive samplers are promising tools for assessing personal exposure to environmental contaminants, evident by the increased adoption and use of silicone-based devices in recent years. When combined with high throughput chemical analysis, these exposure assessment tools present opportunities for advancing our ability to assess personal exposures to complex mixtures. Most designs of wearable passive samplers used for assessing exposure to semi-volatile organic chemicals are currently uncalibrated, thus, are mostly used for qualitative research. The challenge with using wearable samplers for quantitative exposure assessment mostly lies with the inherent complexity in calibrating these wearable devices. Questions remain regarding how they perform under various conditions and the uncertainty of exposure estimates. As popularity of these samplers grows, it is critical to understand the uptake kinetics of chemicals and the different environmental and meteorological conditions that can introduce variability. Wearable passive samplers enable evaluation of exposure to hundreds of chemicals. The review presents the state-of-the-art of technology for assessing personal exposure to environmental chemicals. As more studies calibrate wearable samplers, these tools present promise for quantitatively assessing exposure at both the individual and population levels.

Purpose of ReviewThis review aims to better understand the utility of machine learning algorithms for predicting spatial patterns of contaminants in the United States (U.S.) drinking water.Recent FindingsWe found 27 U.S. drinking water studies in the past ten years that used machine learning algorithms to predict water quality. Most studies (42%) developed random forest classification models for groundwater. Continuous models show low predictive power, suggesting that larger datasets and additional predictors are needed. Categorical/classification models for arsenic and nitrate that predict exceedances of pollution thresholds are most common in the literature because of good national scale data coverage and priority as environmental health concerns. Most groundwater data used to develop models were obtained from the United States Geological Survey (USGS) National Water Information System (NWIS). Predictors were similar across contaminants but challenges are posed by the lack of a standard methodology for imputation, pre-processing, and differing availability of data across regions.SummaryWe reviewed 27 articles that focused on seven drinking water contaminants. Good performance metrics were reported for binary models that classified chemical concentrations above a threshold value by finding significant predictors. Classification models are especially useful for assisting in the design of sampling efforts by identifying high-risk areas. Only a few studies have developed continuous models and obtaining good predictive performance for such models is still challenging. Improving continuous models is important for potential future use in epidemiological studies to supplement data gaps in exposure assessments for drinking water contaminants. While significant progress has been made over the past decade, methodological advances are still needed for selecting appropriate model performance metrics and accounting for spatial autocorrelations in data. Finally, improved infrastructure for code and data sharing would spearhead more rapid advances in machine-learning models for drinking water quality.

Exposure to endocrine disrupting chemicals through personal care products (PCPs) is widespread and may disrupt hormone-sensitive endpoints, such as timing of puberty. Given the well-documented (and ongoing) decline in age at menarche in many populations, we conducted a systematic review of the epidemiological literature on exposure to chemicals commonly found in PCPs (including certain phthalates, phenols, and parabens) in relation to girls' pubertal development. The preponderance of research on this topic has examined phthalate exposures with the strongest evidence indicating that prenatal monoethyl phthalate (MEP) concentrations may be associated with slightly earlier timing of puberty, including age at menarche. Findings examining peri-pubertal phthalate exposures and pubertal outcomes were less consistent as were studies of prenatal and peri-pubertal phenol exposures. Very few studies had examined parabens in relation to girls' pubertal development. Common study limitations included potential exposure misclassification related to use of spot samples and/or mistimed biomarker assessment with respect to the outcomes. The role of body size as a mediator in these relationships remains unresolved. Overall, evidence of associations between chemical exposures in PCPs and girls' pubertal development was conflicting. When associations were observed, effect sizes were small. Nevertheless, given the many environmental, social, and behavioral factors in the modern environment that may act synergistically to accelerate timing of puberty, even marginal changes may be cause for concern, with implications for cancer risk, mental health, and cardiometabolic disease in later life.

Purpose of ReviewIncreasing wildfire size and severity across the western United States has created an environmental and social crisis that must be approached from a transdisciplinary perspective. Climate change and more than a century of fire exclusion and wildfire suppression have led to contemporary wildfires with more severe environmental impacts and human smoke exposure. Wildfires increase smoke exposure for broad swaths of the US population, though outdoor workers and socially disadvantaged groups with limited adaptive capacity can be disproportionally exposed. Exposure to wildfire smoke is associated with a range of health impacts in children and adults, including exacerbation of existing respiratory diseases such as asthma and chronic obstructive pulmonary disease, worse birth outcomes, and cardiovascular events. Seasonally dry forests in Washington, Oregon, and California can benefit from ecological restoration as a way to adapt forests to climate change and reduce smoke impacts on affected communities.Recent FindingsEach wildfire season, large smoke events, and their adverse impacts on human health receive considerable attention from both the public and policymakers. The severity of recent wildfire seasons has state and federal governments outlining budgets and prioritizing policies to combat the worsening crisis. This surging attention provides an opportunity to outline the actions needed now to advance research and practice on conservation, economic, environmental justice, and public health interests, as well as the trade-offs that must be considered.SummaryScientists, planners, foresters and fire managers, fire safety, air quality, and public health practitioners must collaboratively work together. This article is the result of a series of transdisciplinary conversations to find common ground and subsequently provide a holistic view of how forest and fire management intersect with human health through the impacts of smoke and articulate the need for an integrated approach to both planning and practice.

Parental occupational exposures might be associated with neurodevelopmental disorders (NDDs) in offspring. We aimed to conduct a systematic review and meta-analysis to summarize and synthesize the current literature and to estimate the pooled magnitude of the underlying association(s) between parental occupational exposures and subsequent risk of NDDs. In the meta-analysis of 20 included studies, significant associations were found between parental occupational exposure to pesticides or solvents and the risk of attention deficit hyperactivity disorder in offspring. Prenatal occupational exposure to pesticides was significantly associated with motor development or cognition disorders in children. Furthermore, some evidence showed that metals might have a role in the development of autism spectrum disorders. Further studies need to identify the level of parental occupational exposures that can be significantly associated with NDDs. Moreover, utilizing standardized outcome and exposure scales is recommended to incorporate paternal, maternal, and parental as well as both prenatal and postnatal exposure in future studies.

Purpose of ReviewThe developmental origins of health and disease (DOHaD) hypothesis posits that the perinatal environment can impact fetal and later life health. The placenta is uniquely situated to assess prenatal exposures in the context of DOHaD because it is an essential ephemeral fetal organ that manages the transport of oxygen, nutrients, waste, and endocrine signals between the mother and fetus. The purpose of this review is to summarize recent studies that evaluated the DOHaD hypothesis in human placentas using epigenomics, including DNA methylation and transcriptomic studies of mRNA, lncRNA, and microRNAs.Recent FindingsBetween 2016 and 2021, 28 articles evaluated associations between prenatal exposures and placental epigenomics across broad exposure categories including maternal smoking, psychosocial stressors, chemicals, air pollution, and metals. Sixteen of these studies connected exposures to health outcome such as birth weight, fetal growth, or infant neurobehavior through mediation analysis, identification of shared associations between exposure and outcome, or network analysis. These aspects of infant and childhood health serve as a foundation for future studies that aim to use placental epigenetics to understand relationships between the prenatal environment and perinatal complications (such as preterm birth or fetal growth restriction) or later life childhood health.SummaryPlacental DNA methylation and RNA expression have been linked to numerous prenatal exposures, such as PM2.5 air pollution, metals, and maternal smoking, as well as infant and childhood health outcomes, including fetal growth and birth weight. Placental epigenomics provides a unique opportunity to expand the DOHaD premise, particularly if research applies novel methodologies such as multi-omics analysis, sequencing of non-coding RNAs, mixtures analysis, and assessment of health outcomes beyond early childhood.

Menopause marks the end of a woman's reproductive lifetime. On average, natural menopause occurs at 51years of age. However, some women report an earlier age of menopause than the national average. This can be problematic for women who delay starting a family. Moreover, early onset of menopause is associated with increased risk of cardiovascular disease, depression, osteoporosis, and premature death. This review investigates associations between exposure to endocrine-disrupting chemicals (EDCs) and earlier onset of menopause. Recent data suggest exposure to certain EDCs may accelerate reproductive aging and contribute to earlier onset of menopause. Human and rodent-based studies identify positive associations between exposure to certain EDCs/environmental contaminants and reproductive aging, earlier onset of menopause, and occurrence of vasomotor symptoms. These findings increase our understanding of the detrimental effects of EDCs on female reproduction and will help lead to thedevelopment of strategies for the treatment/prevention of EDC-induced reproductive aging.

Parkinson's disease (PD) is the most prevalent motor disorder and is characterized by loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) region of the brain. Though the pathology of PD is well established, the cause of this neuronal loss is not well understood. Approximately 90% of PD cases are sporadic, and the environment plays a significant role in disease pathogenesis. The etiology of PD is highly complex, with neuroinflammation being one of the most critical factors implicated in PD. However, the signaling mechanisms underlying neuroinflammation and its interaction with environmental factors are unclear. Astroglia and microglia are the two principal cells that play an essential role in maintaining neuronal health in many ways, including through immunological means. Exposure to environmental stressors from various sources affects these glial cells leading to chronic and sustained inflammation. Recent epidemiological studies have identified an interaction among environmental factors and glial genes in Parkinson's disease. Mechanistic studies have shown that exposure to pesticides like rotenone and paraquat, neurotoxic metals like manganese and lead, and even diesel exhaust fumes induce glial activation by regulating various key inflammatory pathways, including the inflammasomes, NOX pathways, and others. This review aims to discuss the recent advances in understanding the mechanism of glial induction in response to environmental stressors and discuss the potential role of gene-environment interaction in driving glial activation.

The aim of this study was to understand the influence of the physical environment on the physical activity (PA) behavior of preschool children (aged 2 to 6 years), in order to provide an overview of these influences from the perspective of the ecological model. PA is of great importance for the prevention of obesity and cardiovascular diseases since childhood. The physical environment has a direct relationship with the different domains, where people can spend their time being physically active. Nonetheless, despite the importance of the physical environment to engagement in PA, very few reviews have focused on this relationship in the context of the growing problem of physical inactivity among preschool children. Studies that had analyzed the school domain had found that greater availability of a wider variety of portable play equipment, presence of certain fixed playground equipment, and presence of open spaces had favored PA levels. Furthermore, different studies had shown that the natural environment and the presence of hills were important for children's PA. Thus, despite the associations with PA we were able to identify in this review, new studies will still be needed to link the physical environment with PA levels, especially regarding transportation and leisure time. In conclusion, promoting studies on this subject from an early age will allow us to obtain information that could allow the adaptation, design, and construction of healthier homes, neighborhoods, and schools that promote children's health.

Purpose of ReviewThe study aims to provide an understanding of health cost assessments of different transport modes in urban contexts, and their relevance for transport planning and political decision-making.Recent FindingsThere is strong evidence that motorized transportation imposes a high health cost on society, and specifically children. In contrast, active transport is a very significant health benefit.SummaryEconomic analyses support urban change in favor of compact neighborhoods and public transit, as well as infrastructure exclusively devoted to active transport. Private cars need to be restricted because of the high cost they impose on society.