Current Environmental Health Reports最新文献

In this article, we summarise recent developments, identify gaps, and propose a research agenda for quantitative health impact assessment (HIA) of environmental exposures linked to urban transport and land use. This is based on a workshop of 30 experts, complemented by targeted literature identified by participants to illustrate the state of research and practice gaps. The practice of quantitative HIA in urban transport and land use interventions covers a diverse range of methods, models, and frameworks. The selection of an appropriate model depends upon the use case, i.e., the research question, resources and expertise, and application. The plurality of models can be a strength if differences are explicit and their implications are understood. A major gap in most assessments and frameworks is the lack of equity consideration. This should be integrated into all stages of the HIA, considering exposures, susceptibility, disease burden, capacity to benefit, household budgets, responsibility for harm, and participation in the process. Scenarios of environmental exposures in urban transport and land use interventions are often overly simple, while the scenario design process of spatial planning is often opaque. Researchers should specify the involvement of stakeholders and the data, evidence, or behavioural model used to construct the scenario. Recent developments in exposure assessment (remote sensing and modelling) have increased the capacity to conduct HIAs for small geographies at scale. At the same time, advances in simulation have enabled the representation of behaviours at high spatial and temporal resolution. The combination can enable person-centric measures accounting for location, activities, and behaviours, with HIA proceeding ahead of epidemiology. Most HIAs still use Comparative Risk Assessment. This is suitable for estimating the disease burdens of environmental exposures, but more advanced longitudinal methods are better suited for studying interventions. Beyond health outcomes, well-being must be incorporated. The monetisation of health outcomes through welfare economics remains contentious. Representation of uncertainty is increasingly acknowledged. Value of Information methods can inform where new data collection would most efficiently reduce final result uncertainty. In the context of the climate crisis and related environmental limits, methods are needed that consider adaptation alongside mitigation and prevention and test robustness to an increasingly unstable future.

Introduction: Environmental exposures have been linked to numerous health conditions. Personal sampling devices such as silicone wristbands have been deployed to better characterize these exposures. Few studies have investigated the use of silicone wristbands in low- and middle-income countries (LMICs). Understanding silicone wristbands in these settings is important since they have the potential to overcome certain logistical and cultural barriers that make biospecimen collection challenging. Thus, this scoping review aims to assess these studies by highlighting population, feasibility, accessibility, and ease of use.

Methods: We searched five databases for the term "silicone wristband," resulting in 265 records. We included studies if they employed silicone wristbands as a passive sampling device and included samples from LMICs. After an abstract and full-text screening, we included 17 studies in this review.

Results: The studies included data from 10 LMICs that span three continents (Africa, South America, and Asia) and represent several occupations and diverse communities, both adult and pediatric. As measured through response rate, the use of silicone wristbands as passive sampling devices was widely accepted by participants.

Conclusion: Silicone wristbands are a suitable and effective passive sampling device in LMICs. They are easily deployed, minimally invasive, and stable in travel. Employing a standardized approach to data collection and analysis may be useful for further comparability in future studies.

Purpose of review: Environmental noise has been identified as a risk factor for cardiovascular and metabolic outcomes. Its association with cancer risk remains poorly understood. This systematic review (on evidence up to February 2025) is to synthesize and meta-analyze the epidemiological evidence.

Recent findings: The studies involved over ten million participants, predominantly from Europe. The most reported outcomes were breast and colorectal cancers, with road traffic noise exposure being the most frequently assessed exposure. The pooled random-effects estimates indicated null association between road traffic noise and breast cancer incidence (RR 1.01; 95% CI 0.99-1.03) or mortality (RR 0.98; 95% CI 0.86-1.10), nor with colon cancer subtypes. Studies risk of bias was high to probably high, particularly in exposure assessment and confounding control. Overall, the available evidence does not support an association between traffic noise and cancer incidence or mortality. However, the certainty of evidence is very low due to methodological heterogeneity, high risk of bias, and the limited number of studies for most cancer sites.

Background: In utero and childhood exposure to toxic metals is associated with poor child growth, a predictor of adverse health outcomes. Most existing research focuses on exposure to single metals; the effects of metal mixtures largely remain understudied. Further, few studies consider how diet/nutrients interact with metal mixtures.

Objective: To synthesize research on the relationship between in utero and childhood metal mixture exposures, nutritional status-metal exposure interactions, and child anthropometric outcomes.

Methods: PubMed and Embase were used to search literature published in 2010-2023. Included studies consisted of at least two in utero or childhood toxic metal exposures and examined anthropometric parameters as their main outcomes. Included articles underwent full-text screenings. Information on exposures, findings, nutritional variables, and statistical methods was extracted.

Results: After deduplication and title and abstract screening, 95 publications were included; 70 on prenatal growth and 25 on postnatal growth. Nutritional status/diet was assessed as an effect modifier in 4.3% studies on prenatal and 12% studies on postnatal growth. Birthweight (91.4%), and height and body mass index (64%) were common indicators of prenatal and postnatal growth, respectively. Finally, 41.4% of studies on prenatal and 20% on postnatal growth included statistical models that tested for mixture effects.

Conclusion: Although many studies included multiple metals, their mixture effects largely remain untested. Additionally, inclusion of nutritional status/dietary intakes in statistical models is rare, highlighting the need for further research.

Purpose of review: Geospatial analysis is an essential tool for research on the role of environmental exposures and health, and critical for understanding impacts of environmental risk factors on diseases with long latency (e.g. cardiovascular disease, dementia, cancers) as well as upstream behaviors including sleep, physical activity, and cognition. There is emerging interest in leveraging machine learning and artificial intelligence (AI) for environmental epidemiology research. In this review, we provide an accessible overview of recent advances.

Recent findings: There have been two major recent shifts in geospatial data types and analytic methods. First, novel methods for statistical prediction, combining geospatial analysis with machine learning and artificial intelligence (GeoAI), allow for scalable geospatial exposure assessment within large population health databases (e.g. cohorts, administrative claims). Second, the widespread adoption of smartphones and wearables with global positioning systems and other sensors has allowed for passive data collection from people, and when combined with geographic information systems, enables exposure assessment at finer spatial scales and temporal resolution than ever before. Illustrative examples include refining models for predicting outdoor air pollution exposure, characterizing populations susceptible to water pollution, and use of deep learning to classify Street View image-derived measures of greenspace. While these tools and approaches may facilitate more rapid, higher quality objective exposure measures, they pose challenges with respect to participant privacy, representativeness of collected data, and curation of high quality validation sets for training of GeoAI algorithms. GeoAI approaches are beginning to be used for environmental exposure assessment and behavioral outcome ascertainment with higher spatial and temporal precision than before. Epidemiologists should continue to apply critical assessment of measurement accuracy and design validity when incorporating these new tools into their work.

Purpose of review: Many people in high-income countries obtain considerable portions of their diets from gardening, hunting, fishing, foraging, and raising animals. Yet food security research in these countries has focused on the roles of commercial and charitable food systems, ignoring non-market food self-provisioning. This review brings together existing evidence to build a holistic understanding of how home and wild food procurement (HWFP) interacts with various dimensions of food security in high-income societies.

Recent findings: HWFP impacts food security in multiple ways. It can increase food availability, improve dietary quality, provide access to otherwise unaffordable foods, and support the stability of household food supplies through personal hardships and societal shocks, though further research is needed to substantiate when, where, and how these relationships hold. Engaging in HWFP provides people with agency over their food sources and can contribute to shrinking the ecological consequences of food sourcing. However, researchers have identified numerous food safety risks associated with HWFP, as well as ways in which these practices can threaten the sustainability of food systems. More research is needed regarding HWFP's potential to contribute to the overall food supplies of high-income countries, during crises as well as in periods of stability. HWFP clearly contributes to food security in high-income countries, but many of the concrete contours of this contribution remain to be revealed. Food security researchers should further account for the effects of HWFP, and scholars studying HWFP activities should consider food security as both a driver and potential consequence of engaging in these practices.

Purpose of review: Heat Health Warning Systems (HHWS) reduce heat-related morbidity and mortality. We reviewed scientific studies on HHWS that use meteorological variables, local climate-epidemiological evidence, personalization, and built environment factors to determine heat stress thresholds. We identified key factors to enhance their precision and effectiveness.

Recent findings: We categorized the findings into three groups. First, most HHWS rely on temperature-mortality relationships. Second, future HHWS should integrate climate-epidemiology data, including cause-specific mortality and morbidity. Third, improvements can be made by incorporating local, built environment, and personalized factors. Our findings highlight a diverse range of factors that can influence the nature of heat warnings and contribute to improving HHWS. Temperature based HHWS are predominantly used across the world while other meteorological variables that include humidity and take actual health impact outcomes based on heat stress indices should be included for better protection. The precision of HHWS can be improved by tapping advancements in digital technologies to develop more targeted HHWS without the need for authorities to issue warnings, and by considering built environment, and personalized factors. The effectiveness of HHWS can be further improved by considering local climate-epidemiological evidence including morbidity and actual health outcomes.