Nitrate and nitrite contamination of groundwater and surface water is a global public health concern, often linked to the increasing use of nitrogen-based fertilizers. In Jordan's Ghor region, where agriculture is intensive and fertilizer use is widespread, the issue is particularly relevant. This study aimed to investigate the relationship between serum nitrate and nitrite levels with low birth weight and preterm birth. A total of 659 participants were enrolled, comprising 452 controls (normal birth weight and full-term delivery) and 207 cases (low birth weight/preterm delivery). High maternal serum nitrite levels were significantly associated with increased odds of low birth weight delivery in both the unadjusted model (odds ratio [OR] = 1.43, 95% CI: 1.14-1.80, P = 0.002) and the a priori confounder set adjusted model (OR = 1.33, 95% CI: 1.02-1.74, P = 0.038). Nitrite levels were also significantly associated with the combined outcome of preterm and/or low birth weight delivery in the unadjusted model (OR = 1.26, 95% CI: 1.01-1.57, P = 0.036), and this association remained significant after a priori adjustment in a multiple-imputation sensitivity analysis (OR = 1.29, 95% CI: 1.03-1.63, P = 0.029). In conclusion, although metabolically interrelated, nitrite and nitrate levels in pregnant women may differentially impact pregnancy outcomes in the largely low income agricultural communities in the Ghor region in Jordan.
Digital health tools, including mobile device location-based health (mHealth) applications, have been adopted to augment conventional contact tracing during recent epidemics and pandemics, yet quantitative evidence about their added epidemiological value remains limited. Using aggregated, privacy-preserving mHealth data from six Chinese cities (July 2021-May 2022), we modelled transmission dynamics of emerging respiratory infections to quantify the heterogeneous effects of mHealth-triggered movement restrictions and risk-based quarantines across viral variants. We found that the mHealth-assisted interventions, together with population-wide lockdowns, could rapidly reduce the effective infection rate and drive daily incidence toward zero within two weeks, which was rarely achieved through traditional contact tracing alone. Scenario simulations further showed that in the absence of mHealth interventions, infections consistently propagated to connected cities across a wide range of epidemiological assumptions, contradicting the reality. These results suggest that early integration of geolocated mHealth tools with traditional epidemiological investigations enhances outbreak containment at both local and regional scales, providing quantitative, spatially explicit evidence to inform scalable mHealth integration strategies for future infectious threats with pandemic potential.
Abstract The intensification of extreme heat events in the Mediterranean basin poses growing threats to public health, particularly in climate‐vulnerable regions like the Valencian Region (eastern Spain). Despite the implementation of provincial and municipal heat prevention plans, their efficacy remains unevaluated, and most studies have focused on provincial capitals, potentially overlooking subregional variability. This study addresses these gaps by quantifying moderate and extreme heat‐attributable mortality across 28 thermoclimatic areas (TAs)—a climatic subdivision of the Valencian Region— from 1975 to 2019, using a two‐stage time‐series analysis of high‐resolution temperature and mortality data. Results reveal a distinct coastal–inland gradient, with significantly higher mortality impacts in inland TAs compared to coastal provincial capitals. Areas most impacted by extreme heat are concentrated in interior regions, while coastal capitals exhibit lower risks. These findings underscore the limitations of relying on administrative boundaries for public health surveillance and adaptation planning. The study highlights the value of climatically coherent zones, such as TAs, for improving the spatial resolution of early warning systems and tailoring heat prevention strategies. This scalable methodological framework provides critical insights for enhancing the design of heat adaptation plans not only in Spain but also in other Mediterranean and climate‐sensitive regions.
Urban tree canopy is known to mitigate ambient heat and improve physical and mental health but the longitudinal interactions and impacts of tree canopy, temperature, and mortality are not well understood. Using high resolution tree canopy estimates, temperature, mortality, and demographic data from 2011 to 2021, we implemented negative binomial generalized estimating equations to model all-cause and disease-specific mortality based on tree canopy cover, year-to-year changes in tree canopy cover, and maximum temperature, adjusting for area-level demographics in Chicago, IL. We used K-means clustering to identify patterns of canopy, temperature, and mortality disparities across Chicago community areas. There were 220,711 decedents during the study period (115,974 male, 104,734 female; mean age at death: 69.4 ± 19.9 years). Existing canopy coverage was not statistically significantly associated with mortality (incidence rate ratio [IRR] = 0.995, 95% confidence interval [CI] = 0.984-1.007). However, each year-to-year percent increase in canopy was associated with around a 10% reduction in mortality (IRR = 0.902, [0.871-0.935]) with significant associations for cause-specific cardiovascular (IRR = 0.908, [0.869-0.948]), mental health (IRR = 0.836, [0.784-0.892]), musculoskeletal (IRR = 0.907, [0.832-0.989]), and respiratory (IRR = 0.887, [0.833-0.945]) diseases. Cluster analysis identified that neighborhoods on Chicago's South and West sides were characterized by high temperatures, greater absolute canopy loss despite elevated baseline canopy levels, and increased mortality. Among the hottest neighborhoods, canopy-temperature interaction models demonstrated that areas experiencing larger year-to-year canopy losses had higher yearly mortality. Protecting tree canopy cover from losses over time, particularly in vulnerable areas with higher temperatures, may present a key opportunity to reduce mortality and mitigate impacts of climate change.
Abstract Autism spectrum disorder (ASD) in children is a major public health challenge. The potential epidemiological links between heavy metal exposure and ASD remains a controversial issue. This critical review examines the epidemiological discrepancies, including variations in exposure assessment, study design, and population differences that contribute to the ongoing debate. Key research gaps, such as the need for longitudinal studies and mechanistic insights, are addressed. Finally, we outline future priorities to advance understanding of heavy metals' role in ASD. Lead (Pb), cadmium (Cd), mercury (Hg), and arsenic (As) were selected heavy metals. The PubMed and Scopus databases, as well as the Google Scholar search engine, were searched to retrieve original research articles on human epidemiological studies that utilized the selected “exposure keywords” in conjunction with the “outcome keywords.” Finally, 36 full‐length articles, irrespective of age, sex, regions, and race/ethnicity, were included for the present review. We revealed inconsistent associations between prenatal and childhood urinary, blood, and hair, As and Cd exposure, and ASD outcomes. In contrast, elevated prenatal and early childhood Pb and Hg concentrations in blood and hair samples showed a significant consistent association with both increased ASD risk and symptom severity, even after adjustment for key demographic and environmental confounders. The findings are inconsistent across metals and studies, and should be interpreted with caution due to potential residual confounding and heterogeneity in exposure assessment methods. Large prospective cohort studies are needed to clarify causal relationships. The path analysis of relevant biomarkers is also warranted to establish biological mechanism.
Abstract Dengue, commonly known as breakbone fever, has been prevalent in Bangladesh since 2000. Monsoon conditions and warmer temperatures create suitable breeding environment for the vectors Aedes aegypti and Aedes albopictus. Although dengue outbreaks peak during the post‐monsoon months (September and October), 2023 showed an unusual shift, with cases peaking as early as June. The case fatality rate (0.54%) in 2023 was the highest in the past two decades. This study offers an exhaustive examination of the spatiotemporal dynamics of dengue incidence clusters and composite risk across Bangladesh using daily dengue case data from 2019 to 2024. Spatial autocorrelation analysis (Local Moran's I) revealed that the central and south coastal districts, especially Dhaka, Manikganj, and Barisal were the major dengue hotspots during the peak outbreak years (2019, 2023, and 2024). Jaccard Similarity Index (JSI) analysis further indicated strong seasonal and interannual reorganization of dengue hotspots, especially during the post‐monsoon season, with increasing hotspot concentration in coastal districts after 2020. To assess hazard, vulnerability and risk, we applied a GIS‐based multi‐criteria decision‐making model (MCDM) framework and compared both weighted (AHP‐based) and unweighted approaches. The weighted AHP model was more accurate (AUC = 0.75) than the unweighted model (AUC = 0.55) in predicting dengue risk zones. A negative binomial mixed‐effects regression showed that lagged temperature, precipitation and population density increased dengue incidence, while higher normalized difference built‐up index was associated with lower incidence. These findings emphasize the need for integrated dengue control strategies targeting high‐risk areas and equal healthcare access.
Abstract Tropical cyclones pose a substantial threat to the health and welfare of communities across the United States. While existing research has focused primarily on the short‐term impacts of tropical cyclones, typically within days or months after exposure, there remains a gap in understanding their long‐term effects on the socioeconomic and demographic composition of communities–a crucial factor in measuring community resilience and recovery. In this study, we conducted a synthetic control analysis using data from all tropical cyclones that occurred in the United States during 2005–2018. We provide evidence that social vulnerability initially increased after tropical cyclones, but exposed regions recovered over time and became less socially vulnerable in the long term. For exposed regions, the social vulnerability index (SVI) increased by 2.4% (95% confidence interval (CI), 0.7%–4.1%) in the year after tropical cyclones, and persisted at elevated levels for at least 5 years. However, SVI decreased over time and, 12 years after exposure, fell even lower than expected in the absence of a tropical cyclone, decreasing to −1.0% (95% CI, −1.9%–0.0%). Our study suggests that this long‐term trend may reflect post‐cyclone gentrification, where vulnerable communities are displaced and replaced by more affluent, less vulnerable populations.
Abstract Communicating the risks posed by extreme weather events remains a challenge for researchers and policy makers. This study evaluates the gap between public perceptions on climate risk and scientific estimates of mortality burden from climate‐related extreme weather events. Results show each mortality risk perception gap follows a similar spatial pattern to the observed attributable mortality rate. The perception that “global warming is happening” was significantly associated with smaller risk perception gaps for all extreme weather events. Improving population‐level understanding of climate change is critical to reducing health risks associated with extreme weather events and to motivate climate‐oriented actions.
Abstract Medical geology (MG) examines the interactions between geological materials, environmental processes, and human health, with particular importance in disaster‐prone regions, where rapid geological changes can abruptly intensify geogenic exposures and necessitate immediate public health responses. Geological events such as earthquakes, volcanic eruptions, landslides, and dust storms can mobilize hazardous geogenic materials, enhancing atmospheric dispersion and inhalation exposure. Although the relevance of disaster‐driven geogenic hazards is increasingly recognized, quantitative evidence of the thematic transition from mineral‐pathology to integrated exposure science remains limited. This study presents a bibliometric science‐mapping analysis of disaster‐related MG research using 64 publications indexed in the Web of Science Core Collection (1980–2025). Using keyword co‐occurrence networks, temporal trend analysis, and conceptual structure mapping, the field's intellectual organization, thematic development, and global collaboration patterns were examined. The results indicate that the literature is structured around three major thematic domains: (a) naturally occurring fibrous minerals and associated disease outcomes; (b) disaster‐triggered exposure pathways; and (c) environmental particulates and population‐level health impacts. While mineral‐specific diseases such as mesothelioma remain central, publications from 2022 to 2025 show a clear shift toward exposure‐oriented frameworks, with “exposure” emerging as the most frequent Keywords Plus term ( n = 6). This transition is particularly evident in temporal overlay visualizations and multiple correspondence analysis conceptual maps. Overall, disaster‐related MG research has evolved from a predominantly disease‐centered perspective toward an integrated exposure science positioned at the interface of geosciences, atmospheric processes, and public health. These findings underscore the importance of incorporating geogenic exposure metrics into disaster risk reduction and environmental health governance.
In 2022, New Mexico (NM) experienced a number of wildfires, including the state's largest, Calf Canyon/Hermit's Peak. This study aimed to evaluate how different exposure estimate methods and referent period selection impacted associations between wildfire smoke and health outcomes using a case-crossover study design. We investigated associations with exposure to fine particulate matter (PM2.5) from wildfire smoke and cardiorespiratory-related emergency department (ED) visits in NM during 2022. Our study compared a range of exposure methods: (a) PM2.5 from the Environmental Protection Agency (EPA) regulatory-grade monitors, (b) PM2.5 from both the EPA regulatory-grade monitors and low-cost PurpleAir observations, (c) modeled 24-hr average wildfire smoke PM2.5 from the Community Multiscale Air Quality Modeling System (CMAQ), and (d) CMAQ daily 1-hr maximum wildfire smoke PM2.5. The magnitude and statistical significance of health outcome associations varied substantially across exposure estimates and referent period selections. CMAQ-based exposure estimates produced odds ratios with wider confidence intervals (CIs), while the product that leveraged both regulatory and bias-corrected PurpleAir measurements improved the PM2.5 measurement spatial coverage and yielded epidemiological estimates with narrower CIs. This highlights the importance of low-cost sensors in rural regions. Our findings emphasize the need to critically assess the inputs used in epidemiological studies for accurate and meaningful results, emphasizing the need for careful consideration of exposure assessment methods and study design when evaluating wildfire smoke health impacts.
Abstract Farmworkers are particularly vulnerable to heat stress, which can escalate into heat‐related illnesses such as heat exhaustion or heat stroke, and can also impact productivity loss. Heat exposure varies considerably depending on season, work‐shift timing, acclimatization, and workload. We examine the frequency of heat stress exceedance in the Imperial and Coachella Valleys of southern California using wet bulb globe temperature (WBGT) calculated using the outputs from Weather Research and Forecasting (WRF) model for a reference year of 2020. The critical WBGT threshold of 80℉ is exceeded for more than 500 hr in August, with considerable exceedance in all key harvesting months of April, May, and June. The threshold is exceeded most frequently in August, with daytime (nighttime) exceedance of 96.3% (38.0%) in the Imperial and 72.5% (11.9%) in the Coachella Valleys. Occupational WBGT limits are also exceeded in most crop environments for unacclimatized workers, and even for acclimatized workers during date and sugarcane harvests. Adjusting the work schedule to an early morning or late evening shift can reduce workers' productivity loss by up to 40%. Based on our findings, we propose several strategies to mitigate heat risks among farmworkers: (a) adjusting work hours to include cooler morning or evening hours (b) using WBGT instead of air temperature to monitor heat exposure (c) adopting variable rest‐break schedules (d) reducing nighttime heat exposure during summer to allow recovery from daytime heat (e) taking extra precaution in high‐risk crop zones (f) avoiding nighttime irrigation during summer, and (g) revising thresholds and definitions used to identify heatwaves.
Wildfires are a source of air pollution, including PM 2.5 . Exposure to PM 2.5 from wildfire smoke is associated with adverse health effects including premature death and respiratory morbidity. Air quality modeling was performed to quantify seasonal wildfire‐PM 2.5 exposure across Canada for 2019–2023, and the annual acute and chronic health impacts and economic valuation due to wildfire‐PM 2.5 exposure were estimated. Exposure to wildfire‐PM 2.5 varied geospatially and temporally. For 2019–2023, the annual premature deaths attributable to wildfire‐PM 2.5 ranged from 49 (95% CI: 0–73) to 400 (95% CI: 0–590) due to acute exposure and 660 (95% CI: 340–980) to 5,400 (95% CI: 2,800–7,900) due to chronic exposure, along with numerous non‐fatal cardiorespiratory health outcomes. Per year, the economic valuation of the health burden ranged from $550M (95% CI: $19M–$1.2B) to $4.4B (95% CI: $150M–$9.9B) for acute impacts and $6.4B (95% CI: $2.2B–$12.9B) to $52B (95% CI: $18B–$100B) for chronic impacts. Additionally, a long‐term average annual exposure for 2013–2023 was estimated using air quality modeling. From this, more than 80% of the population had an average seasonal wildfire‐PM 2.5 exposure of at least 1.0 μg/m 3 and there were 1,900 (95% CI: 980–2,800) attributable premature deaths and a total economic valuation of $18B (95% CI: $6.1B–$36B), per year. Evaluating and understanding the health impacts of wildfire‐PM 2.5 is important given the sizable contribution of wildfire smoke to air pollution in Canada, as well as the anticipated increases in wildfire activity due to climate change.
The present study proposes a high-resolution, multi-component framework to estimate human exposure to air pollution in tropical urban environments, addressing complex topography and limited historical mobility and exposure data. This framework is applied to the city of Medellín in the Aburrá Valley in Colombia. To assess population exposure to particulate matter, numerical simulations, mobility and toxicity data were integrated. The LOTOS-EUROS Chemical Transport Model, driven by the Weather Research and Forecasting (WRF) model, was used to simulate air quality at a spatial resolution of 1 km × 1 km for the year 2019. Mobility dynamics were derived from the Origin-Destination Survey (ODS), comprising over 180,000 trips across 240 traffic analysis zones. The utilisation of this data set facilitated the estimation of time-weighted exposure levels for diverse demographic groups during weekdays. The morpho-chemical properties of the particulate matter samples were analyzed to determine the presence of metals and carbonaceous fractions due to significant health implications. The exposure model is a weighted model that integrates exposure time, PM 2.5 and PM 10 concentration, and cytogenotoxic indicators. The application of cluster analysis to the available data, resulted in the identification of areas of elevated health risk, indicating that the central and southern zones, approximately 60% of the metropolitan population and main highway corridors, exhibited mean particulate matter exposure levels that exceeded 40 μg/m3 during peak hours, thus surpassing the WHO air quality guidelines. These zones demonstrated the highest levels of exposure, as indicated by cluster significance levels, suggesting more epidemiological studies and public health interventions.
Abstract Out‐of‐hospital cardiac arrests (OHCAs) represent a significant global health challenge, with a survival rate <10%. Recent research has demonstrated that geomagnetic activity (GMA) can disrupt the circadian rhythm. Therefore, GMA may affect patient outcomes after an OHCA event wherein resuscitation is attempted. This study involved a retrospective analysis of the Emergency Medical Services (EMS) patient call records and clinical data collected from the Kaunas (Lithuania) EMS digital databases from 1 January 2016 to 31 December 2021. Multivariate logistic regression was used to analyze the association between GMA and the risk of absence of return of spontaneous circulation (ROSC) on the scene, adjusting for potential confounders. Among the 1,507 patients evaluated, 66.6% were male and 47.2% were aged <70 years. A shockable rhythm (SHR) was identified in 436 patients (28.9%), while only 19.9% of patients in the unsuccessful resuscitation group had an SHR. In patients without SHR, a lower rate of ROSC was observed during the period from the second and subsequent days of a geomagnetic storm (GS) to 2 days after the end of the GS. During these days and on days with higher GMA, SHR was associated with a higher probability of achieving ROSC. The impact of SHR on the ROSC was statistically non‐significant in the days of GS onset. The association between the risk of absence of ROSC at the scene and higher GMA levels or different GS periods was modified by SHR, with a stronger effect modification observed in males and in patients with a presumed cardiac cause.
Abstract Geomagnetic activity (GMA), particularly during auroras, has emerged as an intriguing area of research due to its potential health impact. Prior studies indicate that fluctuations in geomagnetic fields can affect diverse physiological and psychological outcomes. The aim of this article is to comprehensively review the impact of GMA on neurological health with an emphasis on implications for patients potentially undergoing a neurosurgical procedure or neurologic/psychiatric assessment. A comprehensive literature review was therefore performed, examining peer‐reviewed articles sourced from PubMed and Google Scholar. The focus was on evaluating potential correlations between geomagnetic disturbances (GMDs) and a range of health outcomes, particularly in relation to neurosurgical, neurological and neuropsychiatric contexts. Reported associations included: increased seizure frequency in patients with epilepsy, sleep disturbances affecting recovery, and cognitive impairments that may complicate patient consent processes. Additionally, heightened stress and anxiety levels during geomagnetic storms could pose challenges for patient management in surgical settings. This review underlines that such disturbances can potentially result in significant postoperative complications, particularly in the elderly, necessitating enhanced monitoring and tailored care strategies. Understanding the diverse effects of GMA on health is essential for optimizing patient outcomes, particularly in surgical procedures. This review highlights the need for further research to elucidate underlying GMA‐triggered molecular mechanisms and establish evidence‐based guidelines that consider geomagnetic conditions in neurological/neuropsychiatric evaluations, surgical planning and postoperative care, especially for vulnerable populations. An enhanced awareness among neurosurgeons, psychiatrist, neurologist and healthcare providers is essential to mitigate potential adverse effects of GMA on patient health and optimize recovery.
Abstract Metrological variations strongly influence malaria transmission by affecting mosquito breeding and survival. Côte d'Ivoire, located within a tropical climate zone, is particularly vulnerable to metrological variations that can alter disease patterns. This study aimed to assess the relationship between meteorological variations of temperature, precipitation, relative humidity and malaria incidence in Côte d'Ivoire from 2021 to 2023. This was a retrospective ecological time‐series study that used data from the National Malaria Control Program (NMCP) and meteorological data from SODEXAM. Monthly data was analyzed by ecological zones and age groups. Pearson's correlation and multiple linear regression models were used to examine associations between metrological variation factors and malaria incidence. Malaria incidence peaked during the rainy season (May–August) across all regions, with children under five representing 39% of total cases. Precipitation and relative humidity were positively and significantly correlated with malaria incidence (r = 0.583–0.698, p < 0.05), while temperature showed a significant negative correlation (r = −0.539 to −0.600, p < 0.05). Interaction analysis revealed that the effect of precipitation and humidity was strongest in the northern zone, where malaria transmission risk increased significantly (β = 22.51, p = 0.01). Malaria transmission in Côte d'Ivoire is strongly associated with metrological variability, particularly rainfall and humidity. Elevated precipitation and humidity increase malaria morbidity, whereas high temperatures above 28°C suppress transmission. Integrating meteorological surveillance into malaria early warning systems can improve prediction and control strategies, especially among vulnerable populations such as children under five.
Abstract Research increasingly demonstrates relationships between higher apparent temperatures, inclusive of heat and humidity, and greater rates of preterm birth (PTB), term low birth weight (tLBW), and stillbirth cases. Through leveraging available epidemiological studies, we estimated the change in burden of these outcomes across the contiguous United States (CONUS) and throughout the 21st century during warm season months (i.e., May through September or October). We projected an additional 4,500 PTBs, 3,800 tLBWs, and 420 stillbirths annually at 1°C of CONUS warming attributable to changes in apparent temperature relative to baseline climatic conditions (1986–2005). These cases increased to 22,000 PTBs, 18,000 tLBWs, and 2,000 stillbirths annually with 4°C of warming relative to the baseline. We projected the most significant changes in per capita rates to occur in Gulf Coast states, where baseline risks of these birth outcomes currently are among the highest in CONUS. Across the three outcomes, we projected an increase in short‐term healthcare costs following birth of approximately US$690 million annually at 1°C of warming, increasing to US$3.3 billion annually at 4°C (2023 dollars). When considering the economic burden of the infant deaths resulting from PTB and tLBW cases, we projected additional costs on the order of US$3.9 billion annually at 1°C, and US$35.8 billion annually at 4°C. Due to data availability, our valuation could not account for potential longer‐term health and productivity implications or pain and suffering that families may experience following the adverse birth outcomes analyzed.
Abstract The increasing frequency of climate extreme events and persistent air pollution challenges pose compound environmental risks, yet the spatiotemporal patterns and trends of compound extreme temperature‐air pollution events remain poorly understood globally. In this paper, we quantify the temporal trends and spatial distributions of compound extreme temperature‐PM2.5 pollution events across 10,067 monitor locations in 43 countries spanning 2003–2023. We find that compound extreme heat and PM2.5 pollution (heat + PM2.5) events decreased in most countries in our sample (35/43), while compound extreme cold and PM2.5 pollution (cold + PM2.5) events showed diverse trends across different nations. Despite the increase in global temperature, cold + PM2.5 events still represent a substantial component of the compound extreme temperature and PM2.5 pollution events. Sensitivity analyses using alternative thresholds and MERRA‐2 PM2.5 data sets yield generally consistent results. The spatial heterogeneity in the compound events is linked to the diverse temperature‐PM2.5 relationships, for example, we find higher PM2.5 concentrations during cold conditions in China, India, and Europe, while the USA and Australia show higher PM2.5 concentrations during hot conditions. Concentrated populations in high‐frequency regions further amplify the exposure burden, with India, Pakistan, and China exhibiting disproportionately higher exposure levels relative to the compound events. Given the likely health impacts of these compound events, our findings suggest that future policies should target temperature‐dependent emission activities that will amplify pollution under extreme temperature conditions.
Abstract While greenness has been linked to enhanced physiological and psychological health, its association with glaucoma remains unexplored. This study aims to investigate the effect of residential greenspace and domestic gardens on incident glaucoma. 357, 920 participants from the UK Biobank were included. Land use coverage percentages of greenspace and domestic gardens within 300 and 1,000 m buffers of participants' residential locations were estimated using land use databases. Cox regression models were used to estimate the association between greenness exposures and incident glaucoma. Four‐way decomposition models were used to explore potential mediators or moderators in the pathway. Gene‐environment interaction effects were tested using multi‐trait genetic polygenic risk score of glaucoma and Myocilin p.Gln368Ter genotype. During a median (IQR) follow‐up of 13.5 (12.8, 14.1) years, 4, 046 glaucoma cases occurred. After full adjustment, the fourth quartile of greenspace was associated with 17.7% (HR = 0.823, 95%CI 0.723–0.937, p = 0.003) and 19% (HR = 0.810, 95%CI 0.708–0.927, p = 0.002) lower risk of incident glaucoma in 300 and 1000 m buffer. Domestic gardens showed a similar trend (4th quartile vs. 1st quartile: 300 m HR = 0.843, 95%CI 0.742–0.957, p = 0.008; 1,000 m HR = 0.827, 95%CI 0.727–0.941, p = 0.004), though restricted cubic spline analysis showed a nonlinear association in 300 m buffer. Greenspace in 300 m buffer was associated with lower cornea‐compensated intraocular pressure. No significant mediating or interactive effects were identified for air pollution, recreational screen time, physical activities, or genetic predisposition. Residential greenspace and domestic gardens may be protective against glaucoma. Therefore, greenspace coverage should be incorporated into land use planning policies for public ocular health promotion.
The development of smoke fine particulate matter (PM2.5) exposure surfaces for estimating air pollution trends and associated health effects has advanced considerably. Currently available smoke exposure products rely on various data sources and modeling techniques, as there is no gold standard method for modeling wildfire smoke PM2.5. This study compares multiple daily smoke PM2.5 data sets developed using diverse methodologies spanning 2008-2018. Incorporating metrics for short- and long-term exposure, we compare four data sets at the census tract level in California: one using the U.S. Environmental Protection Agency's chemical transport model (CTM), the Community Multiscale Air Quality Modeling System (CMAQ); two using statistical methods, also referred to as machine learning (ML) techniques; and one combining these approaches to develop an ML-calibrated CTM-based exposure surface. Our analysis highlights differences between the data sets in terms of long-term exposure metrics, with the CTM data set estimating the highest concentrations overall, and considerable differences between estimates produced by the two ML models. An analysis of six case studies of large fires across the state finds that even data sets with similar inputs and methods produced estimates that varied several-fold, with additional differences by region and over time. Our findings have important implications for quantifying smoke PM2.5 exposures for use in population health impact studies, which rely on exposure estimates to accurately estimate health burden from pollution exposure.
