Geohealth最新文献

Peer-review is the foundation and the safeguard of scientific research. Without the dedication of our reviewers, the journal would not have been successful. In 2023, 269 reviewers completed 434 reviews for the 174 manuscripts submitted to GeoHealth. Our reviewers are from all continents except Antarctica. Besides reviewers from North America, China, Europe, and China, we started to have reviewers from India, Latin America, and Africa. GeoHealth editorial board is committed to expanding the readership, authorship, and reviewership to other countries. If you have already reviewed for us, no matter where or who you are, we hope you and your colleagues will consider GeoHealth a home for your work. Below is the list of reviewers who completed more than two reviews or have outstanding quality reviews. Two of our reviewers are being nominated for AGU best reviewers awards.

Hand, Foot, and Mouth Disease (HFMD) is an infectious disease that primarily affects young children. In densely populated Jiangsu Province in China, the impact of extreme meteorological factors on HFMD is a concern. We aimed to examine the association between extreme meteorological variables and HFMD infection risk using daily HFMD infections and meteorological data from 2010 to 2017 in Jiangsu Province. We used distributed lag non-linear model (DLNM) to analyze the data, which can effectively capture the nuanced non-linear dynamics and lag effects in the relationship between HFMD and extreme meteorological factors. Comparing the 10th and 90th percentiles of meteorological variables with their respective median values, our results showed that extremely low temperatures and high humidity were significantly associated with increased HFMD infection risk. The greatest effect of extremely low temperatures was observed at a lag of 1–2 days, elevating the risk by 18 ∼ 33% (RR = 1.18 ∼ 1.33). Extremely high humidity was found to increase the risk of infection, starting at a lag of 4 days. In contrast, extremely high temperatures, low humidity, and high wind speed were associated with reduced risk of infection at lag of 0–12 days, with the range of RR values being 0.60–0.98 for extremely high temperatures, 0.69–0.89 for extremely low humidity, and 0.84–0.98 for extremely high wind speed respectively. Our findings suggest that extreme meteorological factors can significantly impact the incidence of HFMD in Jiangsu Province, and highlight the need for effective public health protection measures during the periods of extreme meteorological condition, particularly for vulnerable populations.

Using street view data, in replace of remotely sensed (RS) data, to study the health impact of greenspace has become popular. However, direct comparisons of these two methods of measuring greenspace are still limited, and their findings are inconsistent. On the other hand, almost all studies of greenspace focus on urban areas. The effectiveness of greenspace in rural areas remains to be investigated. In this study, we compared measures of greenspace based on the Google Street View data with those based on RS data by calculating the correlation between the two and evaluating their associations with birth outcomes. Besides the direct measures of greenness, we also compared the measures of environmental diversity, calculated with the two types of data. Our study area consists of the States of New Hampshire and Vermont, USA, which are largely rural. Our results show that the correlations between the two types of greenness measures were weak to moderate, and the greenness at an eye-level view largely reflects the immediate surroundings. Neither the street view data- nor the RS data-based measures identify the influence of greenspace on birth outcomes in our rural study area. Interestingly, the environmental diversity was largely negatively associated with birth outcomes, particularly gestational age. Our study revealed that in rural areas, the effectiveness of greenspace and environmental diversity may be considerably different from that in urban areas.

Prescribed fires (fires intentionally set for mitigation purposes) produce pollutants, which have negative effects on human and animal health. One of the pollutants produced from fires is fine particulate matter (PM_2.5). The Flint Hills (FH) region of Kansas experiences extensive prescribed burning each spring (March-May). Smoke from prescribed fires is often understudied due to a lack of monitoring in the rural regions where prescribed burning occurs, as well as the short duration and small size of the fires. Our goal was to attribute PM_2.5 concentrations to the prescribed burning in the FH. To determine PM_2.5 increases from local burning, we used low-cost PM_2.5 sensors (PurpleAir) and satellite observations. The FH were also affected by smoke transported from fires in other regions during 2022. We separated the transported smoke from smoke from fires in eastern Kansas. Based on data from the PurpleAir sensors, we found the 24-hr median PM_2.5 to increase by 3.0–5.3 μg m⁻³ (based on different estimates) on days impacted by smoke from fires in the eastern Kansas region compared to days unimpacted by smoke. The FH region was the most impacted by smoke PM_2.5 compared to other regions of Kansas, as observed in satellite products and in situ measurements. Additionally, our study found that hourly PM_2.5 estimates from a satellite-derived product aligned with our ground-based measurements. Satellite-derived products are useful in rural areas like the FH, where monitors are scarce, providing important PM_2.5 estimates.

Wildfire smoke fine particles (PM_2.5) are a growing public health threat as wildfire events become more common and intense under climate change, especially in the Western United States. Studies assessing the association between wildfire PM_2.5 exposure and health typically summarize the effects over the study area. However, health responses to wildfire PM_2.5 may vary spatially. We evaluated spatially-varying respiratory acute care utilization risks associated with short-term exposure to wildfire PM_2.5 and explored community characteristics possibly driving spatial heterogeneity. Using ensemble-modeled daily wildfire PM_2.5, we defined a wildfire smoke day to have wildfire-specific PM_2.5 concentration ≥15 μg/m³. We included daily respiratory emergency department visits and unplanned hospitalizations in 1,396 California ZIP Code Tabulation Areas (ZCTAs) and 15 census-derived community characteristics. Employing a case-crossover design and conditional logistic regression, we observed increased odds of respiratory acute care utilization on wildfire smoke days at the state level (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.05, 1.07). Across air basins, ORs ranged from 0.88 to 1.57, with the highest effect estimate in San Diego. A within-community matching design and spatial Bayesian hierarchical model also revealed spatial heterogeneity in ZCTA-level rate differences. For example, communities with a higher percentage of Black or Pacific Islander residents had stronger wildfire PM_2.5-outcome relationships, while more air conditioning and tree canopy attenuated associations. We found an important heterogeneity in wildfire smoke-related health impacts across air basins, counties, and ZCTAs, and we identified characteristics of vulnerable communities, providing evidence to guide policy development and resource allocation.

It is unclear whether Gross Domestic Product (GDP) and greenness have additional modifying effects on the association between air pollution and respiratory system disease. Utilizing a time-stratified case-crossover design with a distributed lag linear model, we analyzed the association between six pollutants (PM_2.5, PM₁₀, NO_2, SO₂, O₃, and CO) and 555,498 respiratory hospital admissions in Beijing from 1st January 2016 to 31st December 2019. We employed conditional logistic regression, adjusting for meteorological conditions, holidays and influenza, to calculate percent change of hospitalization risk. Subsequently, we performed subgroup analysis to investigate potential effect modifications using a two-sample z test. Every 10 μg/m³ increase in PM_2.5, PM₁₀, NO₂, SO₂, and O₃ led to increases of 0.26% (95%CI: 0.17%, 0.35%), 0.15% (95%CI: 0.09%, 0.22%), 0.61% (95%CI: 0.44%, 0.77%), 1.72% (95%CI: 1.24%, 2.21%), and 0.32% (95%CI: 0.20%, 0.43%) in admissions, respectively. Also, a 1 mg/m³ increase in CO levels resulted in a 2.50% (95%CI: 1.96%, 3.04%) rise in admissions. The links with NO₂ (p < 0.001), SO₂ (p < 0.001), O₃ (during the warm season, p < 0.001), and CO (p < 0.001) were significantly weaker among patients residing in areas with higher levels of greenness. No significant modifying role of GDP was observed. Greenness can help mitigate the effects of air pollutants, while the role of GDP needs further investigation.

Wildfires are increasing in frequency and intensity, with significant consequences that impact human health. A scoping review was conducted to: (a) understand wildfire-related health effects, (b) identify and describe environmental exposure and health outcome data sources used to research the impacts of wildfire exposures on health, and (c) identify gaps and opportunities to leverage exposure and health data to advance research. A literature search was conducted in PubMed and a sample of 83 articles met inclusion criteria. A majority of studies focused on respiratory and cardiovascular outcomes. Hospital administrative data was the most common health data source, followed by government data sources and health surveys. Wildfire smoke, specifically fine particulate matter (PM_2.5), was the most common exposure measure and was predominantly estimated from monitoring networks and satellite data. Health data were not available in real-time, and they lacked spatial and temporal coverage to study health outcomes with longer latency periods. Exposure data were often available in real-time and provided better temporal and spatial coverage but did not capture the complex mixture of hazardous wildfire smoke pollutants nor exposures associated with non-air pathways such as soil, household dust, food, and water. This scoping review of the specific health and exposure data sources used to underpin these studies provides a framework for the research community to understand: (a) the use and value of various environmental and health data sources, and (b) the opportunities for improving data collection, integration, and accessibility to help inform our understanding of wildfires and other environmental exposures.

Mental distress among young people has increased in recent years. Research suggests that greenspace may benefit mental health. The objective of this exploratory study is to further understanding of place-based differences (i.e., urbanity) in the greenspace-mental health association. We leverage publicly available greenspace data sets to operationalize greenspace quantity, quality, and accessibility metrics at the community-level. Emergency department visits for young people (ages 24 and under) were coded for: anxiety, depression, mood disorders, mental and behavioral disorders, and substance use disorders. Generalized linear models investigated the association between greenspace metrics and community-level mental health burden; results are reported as prevalence rate ratios (PRR). Urban and suburban communities with the lowest quantities of greenspace had the highest prevalence of poor mental health outcomes, particularly for mood disorders in urban areas (PRR: 1.19, 95% CI: 1.16–1.21), and substance use disorders in suburban areas (PRR: 1.35, 95% CI: 1.28–1.43). In urban, micropolitan, and rural/isolated areas further distance to greenspace was associated with a higher prevalence of poor mental health outcomes; this association was most pronounced for substance use disorders (PRRUrban: 1.31, 95% CI: 1.29–1.32; PRRMicropolitan: 1.47, 95% CI: 1.43–1.51; PRRRural 2.38: 95% CI: 2.19–2.58). In small towns and rural/isolated communities, poor mental health outcomes were more prevalent in communities with the worst greenspace quality; this association was most pronounced for mental and behavioral disorders in small towns (PRR: 1.29, 95% CI: 1.24–1.35), and for anxiety disorders in rural/isolated communities (PRR: 1.61, 95% CI: 1.43–1.82). The association between greenspace metrics and mental health outcomes among young people is place-based with variations across the rural-urban continuum.

Shellfish harvesting is central to coastal Alaska Native ways of life, and tribes in Southeast Alaska are committed to preserving sustainable and safe access to subsistence foods. However, consumption of non-commercially harvested shellfish puts Alaska Native communities at elevated risk of exposure to shellfish toxins. To address a lack of state or federal toxin testing for subsistence and recreational harvesting, tribes across Southeast Alaska have formed their own toxin testing and ocean monitoring program. In this study, we interviewed environmental managers responsible for tribes' testing and others with shellfish toxin expertise to report on perceptions of barriers to tribally led testing in Southeast Alaska. Tribal staff identified 40 prospective key informants to interview, including all environmental managers responsible for shellfish toxin testing at subsistence sites in Southeast Alaska. All 40 individuals were invited to participate in an interview and 27 individuals were interviewed. The most frequently discussed barriers to shellfish toxin testing in Southeast Alaska relate to logistical and staffing difficulties associated with communities' remote locations, inconsistent and inadequate funding and funding structures that increase staff burdens, risk communication challenges related to conveying exposure risks while supporting subsistence harvesting, and implications of climate change-related shifts in toxin exposures for risk perception and risk communication. Participants stressed the social origins of perceived barriers. Disinvestment may create and sustain barriers and be most severely felt in Native communities and remote places. Climate change impacts may interact with social and cultural factors to further complicate risk management.

Compostable materials constitute roughly half of waste generated globally, but only 5% of waste is actually processed through composting, suggesting that expanding compost programs may be an effective way to process waste. Compostable waste, if properly collected and processed, has value-added end use options including: residential and park landscaping, remediation of brownfield sites, and as growing media in urban agriculture (UA). Since 2001, our lab has partnered with The Food Project, a non-profit focused on youth leadership development through urban farming. From 2006 to 2022 we collected compost materials that were delivered to the farm from a variety of local sources and analyzed a suite of biogeochemical properties including lead (Pb) concentrations, organic carbon, and grain size distribution. Pb concentrations of Boston's municipal compost always exceeded the current City of San Francisco soil and compost purchase standard (80 μg/g). In 2012 Boston's composting program was halted when it exceeded the 400 μg/g Environmental Protection Agency's Pb in soil benchmark. Urban Pb is geomobile and must be managed to minimize resuspension and transport of fines whose Pb concentration is often elevated compared to bulk compost. Consequently, urban farmers have to source lower Pb compost from suburban suppliers at significantly greater cost. Over a 15 year period and through several city vendor contracts, Pb concentrations in municipal compost remain at levels that warrant continued surveillance and risk assessment.