Geohealth最新文献

Over the past two decades, the surge in warehouse construction near seaports and in economically lower-cost land areas has intensified product transportation and e-commerce activities, particularly affecting air quality and health in nearby socially disadvantaged communities. This study, spanning from 2000 to 2019 in Southern California, investigated the relationship between ambient concentrations of PM_2.5 and elemental carbon (EC) and the proliferation of warehouses. Utilizing satellite-driven estimates of annual mean ambient pollution levels at the ZIP code level and linear mixed effect models, positive associations were found between warehouse characteristics such as rentable building area (RBA), number of loading docks (LD), and parking spaces (PS), and increases in PM_2.5 and EC concentrations. After adjusting for demographic covariates, an Interquartile Range increase of the RBA, LD, and PS were associated with a 0.16 μg/m³ (95% CI = [0.13, 0.19], p < 0.001), 0.10 μg/m³ (95% CI = [0.08, 0.12], p < 0.001), and 0.21 μg/m³ (95% CI = [0.18, 0.24], p < 0.001) increase in PM_2.5, respectively. For EC concentrations, an IQR increase of RBA, LD, and PS were each associated with a 0.021 μg/m³ (95% CI = [0.019, 0.024], p < 0.001), 0.014 μg/m³ (95% CI = [0.012, 0.015], p < 0.001), and 0.021 μg/m³ (95% CI = [0.019, 0.024], p < 0.001) increase. The study also highlighted that disadvantaged populations, including racial/ethnic minorities, individuals with lower education levels, and lower-income earners, were disproportionately affected by higher pollution levels.

Childhood stunting is a serious public health concern in Rwanda. Although stunting causes have been documented, we still lack a more in-depth understanding of their local factors at a more detailed geographic level. We cross-sectionally examined 615 height-for-age prevalence observations in the Northern Province of Rwanda, linked with their related covariates, to explore the spatial heterogeneity in the low height-for-age prevalence by fitting linear and non-linear spatial regression models and explainable machine learning. Specifically, complemented with generalized additive models, we fitted the ordinary least squares (OLS), a standard geographically weighted regression (GWR), and multiscale geographically weighted regression (MGWR) models to characterize the imbalanced distribution of stunting risk factors and uncover the nonlinear effect of significant predictors, explaining the height-for-age variations. The results reveal that 27% of the children measured were stunted, and that likelihood was found to be higher in the districts of Musanze, Gakenke, and Gicumbi. The local MGWR model outperformed the ordinary GWR and OLS, with coefficients of determination of 0.89, 0.84, and 0.25, respectively. At specific ranges, the study shows that height-for-age decreases with an increase in the number of days a child was left alone, elevation, and rainfall. In contrast, land surface temperature is positively associated with height-for-age. However, variables like the normalized difference vegetation index, slope, soil fertility, and urbanicity exhibited bell-shaped and U-shaped non-linear associations with the height-for-age prevalence. Identifying areas with the highest rates of stunting will help determine the most effective measures for reducing the burden of undernutrition.

Unpredictable emergency department (ED) admissions challenge healthcare systems, causing resource allocation inefficiencies. This study analyses associations between air pollutants, meteorological factors, and 2,655,861 cause-specific ED admissions from 2014 to 2018 across 12 categories. Generalized additive models were used to assess non-linear associations for each exposure, yielding Incidence Rate Ratios (IRR), while the population attributable fraction (PAF) calculated each exposure's contribution to cause-specific ED admissions. IRRs revealed increased risks of ED admissions for respiratory infections (IRR: 1.06, 95% CI: 1.01–1.11) and infectious and parasitic diseases (IRR: 1.09, 95% CI: 1.03–1.15) during increased rainfall (13.21–16.97 mm). Wind speeds >12.73 km/hr corresponded to increased risks of ED admissions for respiratory infections (IRR: 1.12, 95% CI: 1.03–1.21) and oral diseases (IRR: 1.58, 95% CI: 1.31–1.91). Higher concentrations of air pollutants were associated with elevated risks of cardiovascular disease (IRR: 1.16, 95% CI: 1.05–1.27 for PM₁₀) and respiratory infection-related ED admissions (IRR: 2.78, 95% CI: 1.69–4.56 for CO). Wind speeds >12.5 km/hr were predicted to contribute toward 10% of respiratory infection ED admissions, while mean temperatures >28°C corresponded to increases in the PAF up to 5% for genitourinary disorders and digestive diseases. PM₁₀ concentrations >60 μg/m³ were highly attributable toward cardiovascular disease (PAF: 10%), digestive disease (PAF: 15%) and musculoskeletal disease (PAF: 10%) ED admissions. CO concentrations >0.6 ppm were highly attributable to respiratory infections (PAF: 20%) and diabetes mellitus (PAF: 20%) ED admissions. This study underscores protective effects of meteorological variables and deleterious impacts of air pollutant exposures across the ED admission categories considered.

During the first two decades of the twenty-first century, we analyze the expansion of urban land cover, urban heat island (UHI), and urban pollution island (UPI) in the Houston Metropolitan Area (HMA) using land cover classifications derived from Landsat and land/aerosol products from NASA’s Moderate Resolution Imaging Spectroradiometer. Our approach involves both direct utilization and fusion with in situ observations for a comprehensive characterization. We also examined how social vulnerability within the HMA changed during the study period and whether the synergy of UHI, UPI, and social vulnerability enhances environmental inequalities. We found that urban land cover within the HMA increased by 1,345.09 km² and is accompanied by a 171.92 (73.93) % expansion of the daytime (nighttime) UHI. While the UPI experienced an overall reduction in particulate pollution, the magnitude of change is smaller compared to the surroundings. Further, the UPI showed localized enhancement in particulate pollution caused by increases in vehicular traffic. Our analysis found that the social vulnerability of the HMA urban regions increased during the study period. Overall, we found that the urban growth during the first two decades of the twenty-first century resulted in a synergy of UHI, UPI, and social vulnerability, causing an increase in environmental inequalities within the HMA.

Fine particulate matter 2.5 (PM_2.5) is a widely studied pollutant with substantial health impacts, yet little is known about the urban-rural differences across the United States. Trends of PM_2.5 in urban and rural census tracts between 2010 and 2019 were assessed alongside sociodemographic characteristics including race/ethnicity, poverty, and age. For 2010, we identified 13,474 rural tracts and 59,065 urban tracts. In 2019, 13,462 were rural and 59,055 urban. Urban tracts had significantly higher PM_2.5 concentrations than rural tracts during this period. Levels of PM_2.5 were lower in rural tracts compared to urban and fell more rapidly in rural than urban. Rural tract annual means for 2010 and 2019 were 8.51 [2.24] μg/m³ and 6.41 [1.29] μg/m³, respectively. Urban tract annual means for 2010 and 2019 were 9.56 [2.04] μg/m³ and 7.51 [1.40] μg/m³, respectively. Rural and urban majority Black communities had significantly higher PM_2.5 pollution levels (10.19 [1.64] μg/m³ and 9.79 [1.10] μg/m³ respectively), in 2010. In 2019, they were: 7.75 [1.1] μg/m³ and 7.09 [0.78] μg/m³, respectively. Majority Hispanic communities had higher PM_2.5 levels and were the highest urban concentration among all races/ethnicities (8.01 [1.73] μg/m³), however they were not the highest rural concentration among all races/ethnicities (6.22 [1.60] μg/m³) in 2019. Associations with higher levels of PM_2.5 were found with communities in the poorest quartile and with higher proportions of residents age<15 years old. These findings suggest greater protections for those disproportionately exposed to PM_2.5 are needed, such as, increasing the availability of low-cost air quality monitors.

The COVID-19 pandemic has profoundly influenced urban lifestyles, particularly the utilization of green spaces. While existing studies have primarily focused on the immediate effects of COVID-19-induced isolation, less attention has been given to the enduring impacts on green space usage patterns. This study addresses this gap by conducting three comprehensive surveys in Dezhou, China—before, during, and after the first wave of social isolation (December 2019, March 2020, December 2020). These surveys assessed socioeconomic conditions, commuting habits, green space usage habits, and landscape preferences, specifically focusing on usage frequency, duration of stays, and activities undertaken. Using Mann-Whitney U tests and Spearman's rho correlations, we identified significant long-term changes, including an increase in the frequency of visits by previously infrequent users, a reduction in visit durations, and a rise in high-intensity activities. These trends persisted 9 months post-isolation, highlighting the pandemic's lasting impact on green space usage and its critical role in enhancing public health and pandemic preparedness through thoughtful urban environmental design. This study not only sheds light on behavioral adaptations during a public health crisis but also offers evidence-based strategies for urban planning to bolster societal resilience in the face of future pandemics.

Per- and poly-fluoroalkyl substances (PFAS), which are long-lasting environmental contaminants that are released into the environment during the e-waste disassembly process, pose a threat to human health. Human milk is a complex and dynamic mixture of endogenous and exogenous substances, including steroid hormones and PFAS. Therefore, in this study, we aimed to investigate the association between PFAS and steroid hormones in human milk from women living close to an e-waste disassembly area. In 2021, we collected milk samples from 150 mothers within 4 weeks of delivery and analyzed them via liquid chromatography-tandem mass spectrometry to determine the levels of 21 perfluorinated compounds and five steroid hormones (estrone, estriol, testosterone, progesterone, and androstenedione [A-dione]). We also performed multiple linear regression analysis to clarify the association between maternal PFAS exposure and steroid hormone concentrations. Our results indicated that PFOA and PFOS were positively associated with estrone (β, 0.23; 95% CI, 0.08–0.39) and A-dione (β, 0.186; 95% CI, 0.016–0.357) concentrations in human milk, respectively. Further, the average estimated daily intake of PFOA and PFOS were 36.5 ng/kg bw/day (range, 0.52–291.7 ng/kg bw/day) and 5.21 ng/kg bw/day (range, 0.26–32.3 ng/kg bw/day), respectively. Of concern, the PFAS intake of breastfeeding infants in the study area was higher than the recommended threshold. These findings suggested that prenatal exposure to PFAS from the e-waste disassembly process can influence steroid hormones levels in human milk. Increased efforts to mitigate mother and infant exposure to environmental pollutants are also required.

The incidence of vibriosis is rising globally with evidence of climate variability influencing environmental processes that support growth of pathogenic Vibrio spp. The waterborne pathogen, Vibrio vulnificus can invade wounds and has one of the highest case fatality rates in humans. The bacterium cannot be eradicated from the aquatic environment, hence climate driven environmental conditions enhancing growth and dissemination of V. vulnificus need to be understood to provide preemptive assessment of its presence and distribution in aquatic systems. To achieve this objective, satellite remote sensing was employed to quantify the association of sea surface temperature (SST) and chlorophyll-a (chl-a) in locations with reported V. vulnificus infections. Monthly analysis was done in two populated regions of the Gulf of Mexico—Tampa Bay, Florida, and Galveston Bay, Texas. Results indicate warm water, characterized by a 2-month lag in SST, high concentration of phytoplankton, proxied for zooplankton using 1 month lagged chl-a values, was statistically linked to higher odds of V. vulnificus infection in the human population. Identification of climate and ecological processes thresholds is concluded to be useful for development of an heuristic prediction system designed to determine risk of infection for coastal populations.

Air pollution in India is a foremost environmental risk factor that affects human health. This study first investigates the geographical distribution of ambient and household air pollution (HAP) and then examines the associated mortality risk. Data on fine particulate matter (PM_2.5) concentration has been extracted from the Greenhouse Gas Air Pollution Interactions and Synergies (GAINS) model. HAP, mortality and socio-demographic data were extracted from the National Family and Health Survey-5, India, 2019–2021. Regression models were applied to see the difference in age-group mortality by different pollution parameters. The districts with PM_2.5 concentration above the National Ambient Air Quality Standard (NAAQS) level of 40 μg/m³ show a higher risk of neonatal (OR-1.86, CI 1.418–2.433), postneonatal (OR-2.04, CI 1.399–2.971), child (OR-2.19, CI 0.999–4.803) and adult death (OR-1.13, CI 1.060–1.208). The absence of a separate kitchen shows a higher probability of neonatal (OR: 1.18, CI 1.074–1.306) and adult death (OR-1.06, CI 1.027–1.088). The interaction between PM_2.5 levels above NAAQS and HAP leads to a substantial rise in mortality observed for neonatal (OR 1.19 CI 1.051–1.337), child (OR 1.17 CI 1.054–1.289), and adult (OR 1.13 CI 1.096–1.168) age groups. This study advocates that there is a strong positive association between ambient and HAP and mortality risk. PM_2.5 pollution significantly contributes to the mortality risk in all age groups. Children are more vulnerable to HAP than adults. In India, policymakers should focus on reducing the anthropogenic PM_2.5 emission at least to reach the NAAQS, which can substantially reduce disease burden and, more precisely, mortality.

Climate change is impacting many aspects of human life in many ways. In Ghana, climate change knowledge remains low and discussions linking climate change and health are scarce. In this paper, authors contribute to the shaping of discussions about climate and health with a focus on how climate change increases certain ailments. First, the paper addresses the need for research in Ghanaian communities to link climate change and health. Second, the paper suggests the development of policies to address the link. Third, public health educators are advised in this paper to educate the public.