Environmental Epidemiology最新文献

Background: Antibiotic consumption is influenced by multiple factors, including environmental conditions. In tropical regions, climate variability may contribute to seasonal patterns of infectious diseases and prescribing behaviors. This study examined the association between climatic variables and antibiotic use in a tertiary hospital in southern Thailand.

Methods: We analyzed 7,696 prescriptions of tetracyclines (n = 971), beta-lactams and penicillins (n = 4,208), and macrolides (n = 2,517) dispensed from 2021 to 2023. Defined daily doses (DDDs) were modeled using generalized additive models and distributed lag nonlinear models to assess associations with temperature, humidity, and rainfall, incorporating delayed and nonlinear effects.

Results: Tetracycline use peaked in January with over 120 DDDs/biweek and declined sharply thereafter. Distributed lag nonlinear models revealed a 45-60% increase in tetracycline use following temperature drops of ≥2 °C after 3-4 biweeks. Beta-lactam use rose by 20-30% in response to rising temperatures within 1-2 biweeks. Macrolide prescribing decreased by up to 25% in periods of high humidity (>80%) and increased with sudden temperature fluctuations. Increased rainfall (>100 mm/biweek) was significantly associated with higher beta-lactam DDDs.

Conclusion: Climatic factors influence antibiotic consumption patterns in class-specific ways. Incorporating environmental surveillance into antimicrobial stewardship programs may improve preparedness and resource allocation. Further multicenter studies are needed to confirm these findings and assess pathogen-specific implications.

Background: Novel evidence suggests an association of wildfire smoke exposure with preterm birth (PTB). However, the mechanism and exposure timing of this association are poorly understood.

Objective: We estimate the association of wildfire smoke on PTB phenotypes (spontaneous PTB [sPTB] and medically indicated PTB [mPTB]) as well as hypertensive disorders of pregnancy (HDP).

Study design: Birth cohort data from singleton livebirths in California from 2007 to 2012 were combined with daily zip code-level estimates of wildfire smoke intensity. Satellite-based estimates of wildfire smoke plume boundaries and high-resolution gridded estimates of surface particulate matter 2.5 (PM_2.5) concentrations were used to calculate smoke exposure from 4 weeks preconception through gestational week 20. The two primary exposures were (1) wildfire smoke exposure at distinct gestational ages and (2) concentration of wildfire smoke exposure. Logistic regression models assessed associations between the number of wildfire smoke-exposed days and PTB phenotypes. HDP were also assessed as an outcome, given their major contribution to mPTB. Four primary outcomes were used: (1) overall PTB (<37 weeks), (2) sPTB, (3) mPTB, and (4) HDP.

Results: Of 2,548,347 eligible pregnant individuals, 86% were exposed to at least 1 day of wildfire smoke of any PM_2.5 intensity during the exposure period. Wildfire smoke of any intensity was significantly associated with sPTB during the exposure period (odds ratios [OR] [95% confidence intervals (CI)]: 1.003 [1.0021, 1.0039]). Each additional day of smoke exposure conferred 0.3% increased odds of sPTB. We did not observe an association of wildfire smoke with HDP. Only smoke exposure of any intensity between 14 and 20 weeks was associated with increased odds of mPTB OR CI (95%) (1.0038 [1.0008, 1.0069]). Wildfire smoke exposure of any intensity in the gestational period of smoke exposure was associated in increased odds of all PTB, except for the preconception period.

Conclusions: Our study found an association of wildfire smoke exposure with PTB, which was largely driven by sPTB.

Background: The link between prenatal exposure to metal(loid)s and childhood lung function, including sex-specific effects, has not been completely elucidated. We aimed to examine sex-specific individual and joint effects of prenatal metal(loid)s exposure on children's lung function.

Methods: Analyses included 438 mother-child dyads from the Programming Research in Obesity, Growth, Environment, and Social Stressors birth cohort in Mexico City. Metal(loid)s levels (As, Cd, Co, Cu, Mn, Ni, Pb, Se, and Zn) were measured in maternal blood collected during the second and third trimesters. Lung function in children was assessed once at ages 8-14 years. Multiple linear regression was performed to evaluate individual associations. Mixture effects were assessed through repeated holdout weighted quantile sum regression and hierarchical Bayesian kernel machine regression. Effect modification by sex was examined.

Results: Second-trimester Ni was inversely associated with FEV₁/FVC ratio in the overall sample and in females, while Pb was linked to lower FEV₁ z-score in females. Third-trimester Co and Pb were also negatively associated with FVC z-score in females, with Pb also associated with lower FEV₁ z-score in females. Higher metal mixture concentrations were associated with lower FEV₁/FVC ratio (β = -0.33, 95% confidence interval: -0.48, -0.16) and FEF_25%-75% z-score (β = -0.22, 95% confidence interval: -0.39, -0.07) in females, with similar sex-specific patterns of association in weighted quantile sum and Bayesian kernel machine regression models.

Conclusions: Second-trimester metal mixture exposure is associated with lower childhood lung function; females are potentially more susceptible to these exposures, which underscores the need to understand critical windows of exposure and sex-specific differences.

Background: Patients with Alzheimer's disease and related dementias (ADRD) are vulnerable to environmental stressors such as extreme heat and air pollution, yet their combined health effects remain poorly understood.

Methods: We assessed the joint impact of extreme heat and fine particulate matter exposure (PM_2.5) on the risk of all-cause hospitalization among an ADRD cohort of Medicare beneficiaries aged ≥65 years. Using a time-stratified case-crossover design, we analyzed data from beneficiaries with prior ADRD-related hospitalizations across the contiguous US in 2000-2016. Daily heat index and PM_2.5 concentrations were linked to residential ZIP codes, and conditional logistic regression models were applied to estimate same-day associations during the warm season (May-September), including interaction terms to explore potential synergistic effects.

Results: We found a linear association between heat and hospitalization, with an odds ratio (OR) of 1.017 (95% confidence interval [CI] = 1.004, 1.031) on extreme heat days (99th percentile) versus median. The PM_2.5-hospitalization relationship was nonlinear, with stronger effects at lower concentrations (10 vs. 5 µg/m³ OR = 1.010; 95% CI = 1.005, 1.015). When accounting for changes in PM_2.5, the OR on extreme heat days versus the median was 1.016 (95% CI = 1.001, 1.032).

Conclusion: These findings underscore the need to consider both environmental stressors when assessing health risks in ADRD populations.

Background: Industrially contaminated areas (ICA) are areas hosting or that have hosted industrial human activities (including industrial agriculture and mining) that have produced or might produce, directly or indirectly, chemical contamination of soil, surface or groundwater, air, or food chains, resulting in ecosystem and/or human health impacts.Pollution in ICA can derive from multiple sources and be closely interrelated with social and economic deprivation of affected communities. Furthermore, these populations may experience health criticalities, limited access to health care and ecosystem resources, and can be considered overburdened or environmental justice (EJ) communities.

Objectives: This commentary stems from the discussion at the symposium "Assessing Environmental Justice for Communities Living in Industrially Contaminated Areas: Sharing Approaches and Experiences" (36th Conference of the International Society for Environmental Epidemiology-Santiago de Chile, 2024). The objective being to propose an international network to share research experiences on EJ in ICA in Europe and in the Latin American regions to enable more consistent knowledge and better policy responses to address the objectives of the 2030 United Nations Sustainable and Development Goals Agenda, specifically reducing inequality within and among countries.

Discussion and policy implication: EJ associated with ICA has been observed in different countries, as investigated through single-site or nationwide assessments. Procedural aspects of EJ include misrecognition of the rights of affected communities to be informed through inclusive communication. This implies the marginalization of the communities in the decision-making process addressing the health impacts of ICA. We propose an international effort based on collaborative work to identify experiences in diversified contexts, research needs, and intervention priorities.

This commentary highlights the need for actionable and context-appropriate research on air pollution and health that will continue to drive policies to reduce exposures and disease burden. Research on air pollution and health has been substantial in high-income countries (HIC), leading to causal conclusions on the adverse effects of air pollution. Despite bearing the greatest disease burden from air pollution, low- and middle-income countries (LMICs) have had scant research funding, a trend that may well be aggravated due to changing political priorities in some HICs. High-quality data from LMICs is urgently needed to help motivate local, subnational, and national policies to raise awareness and identify priority actions to improve health. The new evidence will also provide a more complete understanding of air pollution and health globally. We highlight a framework for moving from research to action and address how this framework differs in HIC and LMIC contexts. We propose a hierarchy of research needs that begins with having the necessary air pollution monitoring and health data, and the capacity to use the data for informative analytics, risk assessment, valuation, and policy formulation. Building technical capacity may be needed for this purpose, as will development of a functioning regulatory system in parallel. We call for greater emphasis on surveillance studies to demonstrate the benefits of action and address barriers to action. The global community would benefit from a broad research agenda with priorities and adequate funding dedicated to building evidence that leads to positive policy change. We urge priority for advancing actionable research and improving research capacity in LMICs, including investments in routine collection of relevant data, emphasizing the foundation of risk monitoring and health data systems, and building a cadre of researchers and informed policy-makers.

Background: In 2024, the US Environmental Protection Agency tightened the Mercury and Air Toxics Standards (MATS) for emissions of filterable particulate matter (fPM) from coal-fired power plants to 0.010 lb/MMBtu. In April 2025, a presidential proclamation stated that 47 specific power plant companies received a 2-year exemption from the new requirements. The proclamation provided no estimates of the resulting health impacts.

Methods: Our approach applies conventional risk-assessment calculations for mortality from inhalation of filterable PM_2.5 (fPM_2.5) emissions, for "with" versus "without" the exemption, across four steps: (1) calculate fPM_2.5 emissions, based on government databases; (2) calculate the change in ambient PM_2.5 concentrations, using the Intervention Model for Air Pollution (InMAP) source-receptor matrix (ISRM); (3) calculate mortality impacts from inhalation of PM_2.5, using the Orellano et al., 2024 concentration-response function (CRF; relative risk (RR) per 10 μg/m³: 1.095, 95% confidence interval (CI) = 1.064, 1.127; in sensitivity analyses, we employ other CRFs); (4) aggregate results (e.g., by US state).

Results: Most (83%) of the exempted power plant facilities already have sufficient control technology installed that they operate below the new MATS limit, indicating that much of that fleet already adopted cleaner technologies. For the remaining 17% of facilities, the proclamation will increase total fPM_2.5 emissions to ~6,900 tons, from ~4,400 tons. We estimate that the additional ~2,500 tons emitted will lead to 32 (95% CI = 22, 43) deaths. The highest mortality is in St. Louis, Missouri, (population: 2.2 million) with an estimated 14 (95% CI = 10,19) deaths. The increased mortality is, for some states (e.g., Missouri, and Pennsylvania), caused by mostly in-state emissions; for other states (e.g., Illinois, Maryland, New Jersey, and Virginia), the cause is out-of-state emissions.

Discussion: Results here quantify a portion of the health impacts but leave unquantified nonmortality impacts, impacts from hazardous air pollutant (HAP) exposures, and noninhalation pathways. The reduced computational demands of the air pollution model employed here allows for more timely investigation of government actions than would traditional air dispersion modeling. Sensitivity analyses yielded mortality results that ranged from 47% lower to 169% higher than the core findings.

Conclusions: We estimate that a 2-year delay in MATS emission reductions of fPM_2.5 at the exempted coal-fired power plants will lead to 32 (95% CI = 22, 43) additional deaths.

Background: Childhood obesity is a complex and multifaceted public health issue. Several studies have found that children living in greener neighborhoods have a lower body mass index (BMI); however, evidence on longitudinal exposure remains limited. This study examined the relationship between Enhanced Vegetation Index (EVI), green space, and children's weight status using linked environmental and national health data.

Methods: We derived annual EVI values from Landsat 8 satellite imagery (30 m resolution) within 300 m of a child's residence in Wales from 2008 to 2019. Mean EVI exposure was calculated for the 4 years preceding BMI measurement. We utilized 2017 Ordnance Survey Open Greenspace data to identify green spaces within 800 m of a child's residence. BMI obtained from the Child Measurement Programme for Wales (2012/13 to 2018/19) for children aged 4-5 years was used to define healthy versus overweight/obesity. We used logistic regression to evaluate associations between residential greenness, green spaces, and childhood weight status.

Results: The final cohort consisted of 200,237 children. A one-unit increase in EVI was associated with a 20% higher likelihood of being overweight or obese (OR = 1.20, 95% CI = 1.05, 1.37). For every additional green space within 800 m, the likelihood of having an unhealthy weight increased by 0.3%.

Conclusions: Our findings suggest that EVI and access to green spaces should be interpreted with care, as they may not capture how young children interact with nearby green environments. Future work investigating the impact of greenness and greenspace on child weight status should use measures tailored to more accurately represent age-specific behaviors.

Background: To mitigate the health impact of high temperatures, heat plans (HPs) have become widespread around the world. Our aim was to evaluate the temperature-mortality associations and estimate the temperature-related deaths in the Netherlands in the years before (2000-2009) and after (2010-2019) the first activation of the national HP.

Methods: We obtained data about daily all-cause mortality (2000-2019) for the entire Dutch population, and by age, sex, neighborhood socioeconomic status, and urbanization. We linked the daily maximum temperature based on 23 monitoring stations across the Netherlands. Time-series Poisson regression models with a distributed lag nonlinear model, adjusted for long-term and seasonal trends and day of the week, were used to assess relative risks (RRs, 95% confidence intervals [CIs]) in the warm months (May-September). Temperature-attributable mortality fractions for high-temperature exposures and potential HP days were calculated.

Results: We observed positive associations between daily maximum temperature and mortality in 2000-2009 and in 2010-2019. Associations of high temperatures (28.9 °C-95th percentile) were weaker in 2010-2019 (RR: 1.07, 95% CI: 1.05, 1.09) than in 2000-2009 (RR: 1.17, 95% CI: 1.15, 1.20). The attenuation in temperature-mortality risk was strongest for the elderly, women, and individuals living in low-socioeconomic status neighborhoods. The estimated mortality attributable fractions of high temperatures (≥28.9 °C) were lower in 2010-2019 (0.72, 95% CI: 0.60, 0.84) than in 2000-2009 (1.21%, 95% CI: 1.07, 1.33).

Conclusion: The impact of high temperatures on mortality attenuated in the Netherlands. This might be due to the implementation of the national HP, but other factors may have played a role as well.

Background: Recent reports indicate that the occurrence of appendicitis follows a seasonal pattern and that there is an association between increased incidence and warmer weather. It is noteworthy that a reduction in the incidence of appendicitis has been observed in the Northern Hemisphere. The objective of this study is to present the epidemiological profile of appendicitis at the national level in France.

Methods: This retrospective observational study, based on data from the French National Discharge Database, encompasses all hospitalizations for appendicitis diagnosis between 2013 and 2022. The progression of appendicitis over time was assessed through time-series models. The incidence of appendicitis was also compared depending on year, gender, age, and latitude.

Results: It is noteworthy that the incidence of appendectomy in France exhibited a significant decrease between 2013 and 2022, with an average reduction of 2.1% annually. There was a significant decrease in the number of appendectomies performed on patients ≤20, while there was an increase in those >60. Furthermore, there was a seasonal pattern in the incidence of appendicitis, with a peak during the summer months. The seasonality remained consistent over time. Furthermore, there was a south-north gradient, with a higher number of appendectomies performed in the south.

Conclusion: Seasonality (summer vs. winter) and latitude (south vs. north) could be considered as a proxy for temperature. However, temperature alone cannot explain the observed variations in appendicitis occurrence, since the latter decreases over time, in parallel with global warming. It is likely that other environmental and ecological parameters may be responsible for these variations.