GIS mapping of agricultural plastic waste in southern Europe.

The escalating use of plastics in agriculture, driven by global population growth and increasing food demand, has concurrently led to a rise in Agricultural Plastic Waste (APW) production. Effective waste management is imperative, prompting this study to address the initial step of management, that is the quantification and localization of waste generated from different production systems in diverse regions. Focused on four Southern European countries (Italy, Spain, Greece, and Portugal) at the regional level, the study uses Geographic Information System (GIS), land use maps, indices tailored to each specific agricultural application and each crop type for plastic waste mapping. Furthermore, after the data was employed, it was validated by relevant stakeholders of the mentioned countries. The study revealed Spain, particularly the Andalusia region, as the highest contributor to APW equal to 324,000 tons per year, while Portugal's Azores region had the lowest estimate equal to 428 tons per year. Significantly, this research stands out as one of the first to comprehensively consider various plastic applications and detailed crop cultivations within the production systems, representing a pioneering effort in addressing plastic waste management in Southern Europe. This can lead further on to the management of waste in this area and the transfer of the scientific proposition to other countries.

Spectral enhancement of PlanetScope using Sentinal-2 images to estimate soybean yield and seed composition.

Soybean is an essential crop to fight global food insecurity and is of great economic importance around the world. Along with genetic improvements aimed at boosting yield, soybean seed composition also changed. Since conditions during crop growth and development influences nutrient accumulation in soybean seeds, remote sensing offers a unique opportunity to estimate seed traits from the standing crops. Capturing phenological developments that influence seed composition requires frequent satellite observations at higher spatial and spectral resolutions. This study introduces a novel spectral fusion technique called multiheaded kernel-based spectral fusion (MKSF) that combines the higher spatial resolution of PlanetScope (PS) and spectral bands from Sentinel 2 (S2) satellites. The study also focuses on using the additional spectral bands and different statistical machine learning models to estimate seed traits, e.g., protein, oil, sucrose, starch, ash, fiber, and yield. The MKSF was trained using PS and S2 image pairs from different growth stages and predicted the potential VNIR1 (705 nm), VNIR2 (740 nm), VNIR3 (783 nm), SWIR1 (1610 nm), and SWIR2 (2190 nm) bands from the PS images. Our results indicate that VNIR3 prediction performance was the highest followed by VNIR2, VNIR1, SWIR1, and SWIR2. Among the seed traits, sucrose yielded the highest predictive performance with RFR model. Finally, the feature importance analysis revealed the importance of MKSF-generated vegetation indices from fused images.

Using GPS-defined venue-based affiliation networks among Black sexually minoritized men and transgender women to identify locations for HIV prevention interventions.

PURPOSE: HIV biomedical intervention uptake is suboptimal among Black sexually minoritized men (SMM) and transgender women (TW). Venues where people meet and interact shape HIV-related risk and prevention behaviors. We aimed to construct GPS-defined venue-based affiliation networks and identify the unique set of venues that could maximize reach of HIV biomedical interventions among Black SMM and TW. METHODS: We used baseline survey and GPS data from 272 Black SMM and TW in the Neighborhoods and Networks (N2) Cohort Study in Chicago, Illinois (2018-2019). We mapped participants' GPS data to the nearest pre-identified SMM- and TW-friendly venue (n = 222) to construct affiliation networks. Network analyses were performed to identify influential venues that can yield high reach to intervention candidates. RESULTS: Participants were affiliated with 75.5 % of all pre-identified venues based on GPS data. Two influential venues were identified in the non-PrEP use network, which when combined, could reach 52.5 % of participants not taking PrEP. Participants that could be reached through these two influential venues reported more non-main sex partners than participants not affiliated with either venue (p = 0.049). CONCLUSION: We demonstrate a potential for GPS-defined venue-based affiliation networks to identify unique combinations of venues that could maximize the impact of HIV prevention interventions.

Analyses of LULC dynamics in a socio-ecological system of the Bale Mountains Eco Region of Southeast Ethiopia.

Analysis of land use and land cover (LULC) change and its drivers and impacts in the biodiversity hotspot of Bale Mountain's socio-ecological system is crucial for formulating plausible policies and strategies that can enhance sustainable development. The study aimed to analyze spatio-temporal LULC changes and their trends, extents, drives, and impacts over the last 48 years in the Bale Mountain social-ecological system. Landsat imagery data from the years 1973, 1986, 1996, 2014, and 2021 together with qualitative data were used. LULC classification scheme employed a supervised classification method with the application of the maximum likelihood algorithm technique. In the period between 1973 and 2021, agriculture, bare land, and settlement showed areal increment by 153.13%, 295.57%, and 49.03% with the corresponding increased annual rate of 1.93%, 2.86%, and 0.83%, respectively. On the contrary, forest, wood land, bushland, grass land, and water body decreased by 29.97%, 1.36%, 28.16%, 8.63%, and 84.36% during the study period, respectively. During the period, major LULC change dynamics were also observed; the majority of woodland was converted to agriculture (757.8 km2) and grassland (531.3 km2); and forests were converted to other LULC classes, namely woodland (766.5 km2), agriculture (706.1 km2), grassland (34.6 km2), bushland (31.9 km2), settlement (20.5 km2), and bare land (14.3 km2). LULC changes were caused by the expansion of agriculture, settlement, overgrazing, infrastructure development, and fire that were driven by population growth and climate change, and supplemented by inadequate policy and institutional factors. Social and environmental importance and values of land uses and land covers in the study area necessitate further assessment of potential natural resources' user groups and valuation of ecosystem services in the study area. Hence, we suggest the identification of potential natural resource-based user groups, and assessment of the influence of LULC changes on ecosystem services in Bale Mountains Eco Region (BMER) for the sustainable use and managements of land resources.

Urban Pedestrian Routes' Accessibility Assessment Using Geographic Information System Processing and Deep Learning-Based Object Detection.

The need to establish safe, accessible, and inclusive pedestrian routes is considered one of the European Union's main priorities. We have developed a method of assessing pedestrian mobility in the surroundings of urban public buildings to evaluate the level of accessibility and inclusion, especially for people with reduced mobility. In the first stage of assessment, artificial intelligence algorithms were used to identify pedestrian crossings and the precise geographical location was determined by deep learning-based object detection with satellite or aerial orthoimagery. In the second stage, Geographic Information System techniques were used to create network models. This approach enabled the verification of the level of accessibility for wheelchair users in the selected study area and the identification of the most suitable route for wheelchair transit between two points of interest. The data obtained were verified using inertial sensors to corroborate the horizontal continuity of the routes. The study findings are of direct benefit to the users of these routes and are also valuable for the entities responsible for ensuring and maintaining the accessibility of pedestrian routes.

Cross-Sectional Study of Flood Damage Assumptions in Medical Facilities Using Geographic Information Systems.

Introduction Floods not only directly damage medical facilities but also hinder access to medical facilities, potentially disrupting local medical services. The scale of damage that medical facilities suffer from floods in Japan is unknown. In this study, we assessed the potential impact of floods on Japanese healthcare facilities by facility characteristics. Methods We conducted a cross-sectional study involving medical facilities registered in the Japan Medical Association Regional Medical Information System. Geographic data for the inundation area was obtained from open data of the Japanese government. Facilities that overlap with flooded areas were designated as affected facilities. The primary outcomes were the percentage of damaged facilities and beds. We calculated odds ratios (OR) and 95% confidence intervals (95%CI) using the Wald method to assess the impact of disaster base hospital designation on damage extent. Results We included 140,826 general clinics and 8,126 hospitals, which had 137,731 and 1,483,347 beds, respectively. The planned scale of flooding is estimated to affect 8.0% of general clinics and 10.8% of their beds. For hospitals, these figures were 8.8% and 7.8%, respectively. The maximum potential scale of flooding is estimated to affect 23.6% of general clinics and 23.9% of their beds. For hospitals, these figures were 22.5% and 20.6%, respectively. At the planned scale of flooding, there was no difference found in the rate of damaged facilities between disaster base hospitals and non-disaster base hospitals, and the rate of damaged beds was lower at non-disaster base hospitals (OR = 0.92, 95%CI = 0.71-1.18 for damaged facilities and OR = 0.79, 95%CI = 0.78-0.80 for damaged beds). At the maximum potential scale of flooding, there was no difference found in the expected damage between disaster base hospitals and non-disaster base hospitals (OR = 1.14, 95%CI = 0.95-1.38 for damaged facilities and OR = 0.99, 95%CI = 0.98-1.00 for damaged beds). Conclusion In Japan, floods can hinder nationwide medical functions, particularly in certain regions. Healthcare professionals should assess potential flood damage in advance and ensure that their workplace's business continuity plan includes appropriate countermeasures.

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China has complex natural conditions and is rich in biodiversity. Based on the geographical distribution and species composition of terrestrial mammals, we explored the characteristics and geographic partitioning of mammal populations in different regions of China. We used a clustering algorithm, combined with the spatial distribution data and taxonomic characteristics of mammals, to geographically partition the terrestrial mammals in China. We found 10 zoogeographic regions of terrestrial mammals in China: Northeast region, North China region, Eastern grassland region, Western region, Northwest region, Qiangtang plateau region, Eastern Qinghai-Tibet Plateau region, Himalayan region, South China region, and Taiwan-Hainan region. We found a new geographical zoning pattern for terrestrial mammals in China, examined the variability and characteristics of species composition among different regions, and quantified the association between species distribution and environmental factors. We proposed a method of incorporating taxonomic information into cluster analysis, which provided a new idea for zoogeographic region studies, a new perspective for understanding species diversity, and a scientific basis for animal conservation and habitat planning.

Future Possible Changes in Medically Underserved Areas in Japan: A Geographic Information System-Based Simulation Study.

BACKGROUND: A decrease in populations could affect healthcare access and systems, particularly in medically underserved areas (MUAs) where depopulation is becoming more prevalent. This study aimed to simulate the future population and land areas of MUAs in Japan. METHODS: This study covered 380,948 1 km meshes, 87,942 clinics, and 8354 hospitals throughout Japan as of 2020. The areas outside a 4 km radius of medical institutions were considered as MUAs, based on the measure of areas in the current Japanese Medical Care Act. Based on the population estimate for a 1 km mesh, the population of mesh numbers of MUAs was predicted for every 10 years from 2020 to 2050 using geographic information system analysis. If the population within a 4 km radius from a medical institution fell below 1000, the institution was operationally assumed to be closed. RESULTS: The number of MUAs was predicted to decrease from 964,310 (0.77% of the total Japanese population) in 2020 to 763,410 (0.75%) by 2050. By 2050, 48,105 meshes (13% of the total meshes in Japan) were predicted to be new MUAs, indicating a 31% increase in MUAs from 2020 to 2050. By 2050, 1601 medical institutions were tentatively estimated to be in close proximity. CONCLUSIONS: In Japan, the population of MUAs will decrease, while the land area of MUAs will increase. Such changes may reform rural healthcare policy and systems.

Assessment of vulnerability to flood risk in the Padma River Basin using hydro-morphometric modeling and flood susceptibility mapping.

An evaluation of flood vulnerability is needed to identify flood risk locations and determine mitigation methods. This research introduces an integrated method combining hydro-morphometric modeling and flood susceptibility mapping to assess Padma River Basin's flood risk. Flood zoning, flooding classes, and resource flood risk were explicitly analyzed in this river basin study. Flood risk was calculated using GIS-based hydro-morphometric modeling. Using Horton's and Strahler's methods, drainage density, stream density, and stream order of the Padma River Basin were determined. The Padma River Basin has five sub-basins: A, B, C, D, and E, with stream densities of 0.53 km-2, 0.13 km-2, 0.25 km-2, 0.30 km-2, and 0.28 km-2 and drainage densities of 0.63 km-1, 0.16 km-1, 0.29 km-1, 0.35 km-1, and 0.33 km-1, respectively. Sub-basin A is the most prone to floods due to its high stream and drainage density, whereas B and C are the least susceptible. This study used elevation, TWI, slope, precipitation, NDVI, distance from road, drainage density, distance from river, LU/LC, and soil type to create a flood vulnerability map incorporating GIS and AHP with pair-wise comparison matrix (PCM). The study's flood zoning shows that the northeastern part of this basin is more likely to flood than the southwestern part due to its elevation and high-order streams. Moderate River Flooding, the region's most hazardous flood class, covers 48.19% of the flooding area, including 1078.30 km2 of agricultural land, 94.86 km2 of bare soil, 486.39 km2 of settlements, 586.42 km2 of vegetation cover, and 39.34 km2 of water bodies. The developed hydro-morphometric model, the flood susceptibility map, and the analysis of this data may be utilized to offer long-term advance alarm insight into areas potentially to be invaded by a flood catastrophe, boosting hazard mitigation and planning.

Comparative Analysis of Out-of-Hospital Cardiac Arrest Outcomes in Health Clinics, Nursing Homes, and Public Places: Implications for Optimizing Automated External Defibrillator Strategies.

Purpose: Various factors, such as event location and response time, influence the outcomes of out-of-hospital cardiac arrest (OHCA). Very few studies have explored the delivery of basic life support (BLS) to patients having OHCA at health clinics or nursing homes-settings with professional BLS providers. Thus, in this study, we compared prognostic and survival outcomes between health clinics, nursing homes, and other public places (eg, workplaces and sports facilities/recreational areas) to offer insights for optimizing OHCA outcomes. Patients: This study included adults who had nontraumatic OHCA in Taoyuan City between January 2017 and December 2022. Methods: We collected data on patient characteristics, emergency medical service parameters, onsite patient management, automated external defibrillator (AED) locations, OHCA prognosis, and survival outcomes. Multivariate analyses were performed to predict survival to discharge (primary outcome) and neurological outcomes at discharge (secondary outcome). Results: During the study period, the numbers of OHCA events at health clinics, nursing homes, and other public places were 158, 208, and 1986, respectively. The mean age of OHCA in health medical clinics, nursing home and other public places were 63.4, 81.5 and 64.7, respectively (P value<0.001). The proportion of witnessed events, rate of bystander resuscitation, and frequency of AED utilization were the highest for health clinics (53.2% (84/158), 83.4% (132/158), and 13.3% (21/158), respectively, P value<0.001). The average AED-scene distances and response times were the lowest for health clinics (388.8 m and 5.4 min, respectively). In initial shockable rhythm group, the probabilities of survival to discharge at discharge were the highest for health clinics (aOR=1.41, 95% CI=1.04-1.81, P value=0.041)) and lowest for nursing homes (aOR=0.84, 95% CI=0.76-0.93, P value=0.024). Conclusion: Our research shows that OHCA patients at medical health clinics have higher rates of witnessing and bystander CPR and AED usage than other public places. However, while survival rates for patients with shockable rhythms are slightly better at health clinics, the neurological outcomes are not significantly different. The AED-scene distances are too far to be used effectively.

Combined biomass network design: A new integrated approach based on ArcGIS.

In light of contemporary energy and environmental objectives, a pivotal transformation of the energy system, encompassing biomass energy, is imperative. A notable challenge in biomass energy facility layout planning is the trade-off between high-efficiency production and the associated investment costs. To harmonize energy efficiency with economy viability, a hybrid layout with the simultaneous construction of centralized and decentralized biomass energy facilities has emerged as a crucial strategic solution. However, the delineation methods for these two layouts lack explicit data support. This study established a population density threshold (PDT) suitable for selecting the distributed layout and employed population density as the criterion for delineating the two layouts. Taking Fuxin City as an example, hybrid layout planning schemes were generated under different PDTs, and a cost and energy benefit analysis framework was developed for these schemes. The results indicated that the scheme with a PDT of 145 person/km2 exhibited the highest energy and economic comprehensive benefits. Compared to a single layout, the planning strategy proposed in this study could achieve nearly the same energy surplus level while saving an investment cost ranging from 2403.9 million CNY to 25,000.23 million CNY. The findings are applicable to other regions with similar conditions, and the analysis framework proposed in this study can be utilized in formulating biomass development strategies for other countries and regions.

Tracing the Untraceables: A Joint Outbreak Investigation With Law Enforcement Using a Geographic Information System.

The application of geospatial data often allows the tracing of people who are involved in activities of an illegal nature. In June 2021, we estimated the true magnitude of the spread of COVID-19 within the networks of escort-karaoke bars in Seoul, Republic of Korea, using geographic information system (GIS)-based contact tracing that was applied to our epidemiological investigation. Our joint rapid response team, composed of epidemic investigation officers and police personnel, identified 19 paper-traced cases and 158 GIS-traced cases from 5,692 confirmed cases in Seoul during the study period (June to July 2021). Our findings suggest that collaboration with law enforcement agencies and the use of overlaid satellite imagery in outbreak investigations enhances high vigilance and reduces the risk of potential breaches of human rights in the process.

Quantifying land change dynamics, resilience and feedback: A comparative analysis of the lake Chad basin in Africa and Aral Sea basin in Central Asia.

The intricate interaction of natural and anthropogenic factors drives changes in land and water in response to societal demands and climate change. However, there has been insufficient information on the feedback effects in dryland hotspots altered by land change dynamics. This research compared two transboundary inland lakes, the Lake Chad basin (LCB) in Africa and the Aral Sea basin (ASB) in Central Asia, using remote sensing and geographic information system techniques to analyze and quantify present and future land cover dynamics, resilience, and their feedback effects. The study integrated Cellular Automata, Markov Chain, and Multilayer Perceptron models to predict LULC changes up to 2030. Descriptive statistics, ordinary least squares regression, hotspot Gi-Bin, trend analysis, and advanced geostatistical methods were utilized to identify relationships, patterns, magnitudes, and directions of observed changes in the feedback effects. From 2000 to 2030, the analysis unveils intriguing trends, including an increase in cropland from 48% to 51% and a decrease in shrubland from 18% to 15% in the LCB. The grassland increased from 21% to 22%, and the settlement expanded from 0.10 to 0.60% in the ASB. Water bodies remained stable at 1.60 % in LCB, while in ASB, it declined from 3% to 2%. These changes were significantly influenced by population, elevation, and temperature in both basins, with irrigation also playing a significant role in the ASB and slope in LCB. The study further revealed discernible shifts in normalized difference vegetation index, temperature, and precipitation linked to specific land cover conversions, suggesting alterations in surface properties and vegetation health. This study underscores the complex interplay between land cover dynamics, resilience, climate variability, and feedback mechanisms in LCB and ASB.

Dynamic analysis of carbon emissions from construction and demolition activities in Japan: Revealed by high-resolution 4D-GIS modeling.

To meet the 2050 decarbonization target of the global buildings and construction sector, more attention is needed to reduce carbon emissions from construction and demolition. However, current national carbon accounting studies for these activities remain limited in spatial granularity and localized applicability. This study developed a bottom-up spatiotemporal database of carbon emissions from building construction and demolition in Japan via integrating a geographic information system-based building stock model, statistical data, and survey information. Focusing on municipal-level emissions, the Logarithmic Mean Divisia Index approach was used to decompose spatiotemporal variations and identify the contributing factors. Results indicate that carbon emissions from Japan's construction and demolition activities fell by more than 50% between 2005 and 2020, largely due to declining new/demolished-to-stock ratio, suggesting a transition to a stock-based society. Central cities' reliance on carbon-intensive buildings positively contributed to spatial variations in their construction emissions, underscoring the importance of sustainable materials and timber designs. Differences between prefectures in demolition emission intensity highlighted the strategic placement of recycling facilities in key regions to curb transportation-related emissions. Overall, these findings provided data reference for local governments to devise tailored policies for managing construction and demolition emissions.

Local retail food environment exposure and diet quality in rural and urban adults: A longitudinal analysis of the ORISCAV-LUX cohort study.

Despite growing interest in understanding how food environments shape dietary behaviors, European longitudinal evidence is scarce. We aimed to investigate the associations of 9-year average and change in exposure to local retail food environments with the diet quality of residents in Luxembourg. We used data from 566 adults enrolled in both waves of the nationwide ORISCAV-LUX study (2007-2017). Dietary quality was assessed by the Diet Quality Index-International (DQI-I). Exposure to "healthy" and "less healthy" food outlets was assessed by both absolute and relative GIS-based measurements. The results showed a 56.3% increase in less healthy food outlets over the period. In adjusted linear mixed models, high (vs. low) 9-year average exposure to less healthy food outlets was associated with lower DQI-I, when examining spatial access (ß = -1.25, 95% CI: -2.29, -0.22) and proportions (ß = -1.24, 95% CI: -2.15, -0.33). Stratified analyses showed these associations to be significant only among urban residents. There was no association between change in exposure to less healthy food outlets and DQI-I. Increased exposure to healthy outlets in rural areas, using absolute measurements, was associated with worsened DQI-I. Neighborhood socioeconomic status did not moderate the above associations. Findings suggest that the proliferation of less healthy food outlets may have contributed to the deterioration of the diet quality of urban residents, and support the use of relative measurements to fully capture the healthiness of food environments.

Optimizing coal mine planning and design for sustainable development in the context of mass exploitation of coal deposits.

Sustainable mining practices is a concept that embeds the principles of sustainable development into the whole mine life-cycle, from exploration, extraction and processing through to mine closure. The optimization of coal mine planning and the developing a standardized design for its sustainable development is very challenging and requires more effort. The present research attempts to address the conditions of sustainability and necessary measures for sustainable development, thereby providing appropriate solutions for each stage of mining operation besides expressing the necessity of sustainable development integration at different stages of mining life cycle (MLC). The approach of systems engineering is essential to assist the sustainability goals which are integrated with the expected results. Hence a method depending more on systems engineering principles and optimization can be incorporated to attain better results. Several socio-environmental factors associated with sustainability depends on the geographic condition and few mining engineering considerations such as mine location, topography, coal seam characteristics and so on. These systems engineering approach can be further enhanced by incorporating tools like Geographic Information System (GIS), which provides more accuracy and precision of the geographic conditions of the site identified for the coal mining plan. In order to begin this way of approach towards the sustainability development and mining planning, the appropriate optimization parameters should be identified. The outcome of these optimization parameters can be also achieved by optimizing coal mining system models.

GIS-based spatial analysis for lightning scenario in Bangladesh.

Bangladesh has witnessed alarmingly rising lightning frequency, particularly during pre-monsoon and monsoon seasons. This has resulted in significant annual death tolls from lightning strikes over the past decade. Recognizing this crisis, the country officially declared lightning casualties a natural disaster in 2016. This study delves deeper into the landscape of lightning fatalities and causalities in Bangladesh. Utilizing secondary data sources, this research introduces a unique approach by integrating Bangladesh Meteorological Department (BMD) data and NASA's Lightning Imaging Sensor (LIS) data from the International Space Station's (ISS) Near-real Time (NRT) mission. This combined dataset allows for a more comprehensive analysis. Furthermore, Geographic Information Systems (GIS) was employed to analyze spatial distributions and generate maps. The Inverse Distance Weighted (IDW) interpolation tool was used to create detailed spatial distribution maps of lightning fatalities, thunderstorm days (TSDs), and lightning flash frequency (LFF) across Bangladesh. The analysis revealed that farmers and fishermen were the most vulnerable populations, with the northeastern regions experiencing the highest impact. Sylhet division emerged as the area with the most fatalities, highlighting the northeastern zone's susceptibility. The study also identified monsoons as the period with the highest occurrences of lightning deaths and injuries. By combining innovative data integration and spatial analysis, this study offers valuable insights into the alarming trend of lightning fatalities in Bangladesh. These findings can inform targeted prevention strategies and interventions to safeguard vulnerable populations and communities.

Ambient long-term exposure to organophosphorus pesticides and the human gut microbiome: an observational study.

BACKGROUND: Organophosphorus pesticides (OP) have been associated with various human health conditions. Animal experiments and in-vitro models suggested that OP may also affect the gut microbiota. We examined associations between ambient chronic exposure to OP and gut microbial changes in humans. METHODS: We recruited 190 participants from a community-based epidemiologic study of Parkinson's disease living in a region known for heavy agricultural pesticide use in California. Of these, 61% of participants had Parkinson's disease and their mean age was 72 years. Microbiome and predicted metagenome data were generated by 16S rRNA gene sequencing of fecal samples. Ambient long-term OP exposures were assessed using pesticide application records combined with residential addresses in a geographic information system. We examined gut microbiome differences due to OP exposures, specifically differences in microbial diversity based on the Shannon index and Bray-Curtis dissimilarities, and differential taxa abundance and predicted Metacyc pathway expression relying on regression models and adjusting for potential confounders. RESULTS: OP exposure was not associated with alpha or beta diversity of the gut microbiome. However, the predicted metagenome was sparser and less evenly expressed among those highly exposed to OP (p = 0.04). Additionally, we found that the abundance of two bacterial families, 22 genera, and the predicted expression of 34 Metacyc pathways were associated with long-term OP exposure. These pathways included perturbed processes related to cellular respiration, increased biosynthesis and degradation of compounds related to bacterial wall structure, increased biosynthesis of RNA/DNA precursors, and decreased synthesis of Vitamin B1 and B6. CONCLUSION: In support of previous animal studies and in-vitro findings, our results suggest that ambient chronic OP pesticide exposure alters gut microbiome composition and its predicted metabolism in humans.

The regional disparities in liver disease comorbidity among elderly Chinese based on a health ecological model: the China Health and Retirement Longitudinal Study.

PURPOSE: This study aimed to investigate the risk factors for liver disease comorbidity among older adults in eastern, central, and western China, and explored binary, ternary and quaternary co-morbid co-causal patterns of liver disease within a health ecological model. METHOD: Basic information from 9,763 older adults was analyzed using data from the China Health and Retirement Longitudinal Study (CHARLS). LASSO regression was employed to identify significant predictors in eastern, central, and western China. Patterns of liver disease comorbidity were studied using association rules, and spatial distribution was analyzed using a geographic information system. Furthermore, binary, ternary, and quaternary network diagrams were constructed to illustrate the relationships between liver disease comorbidity and co-causes. RESULTS: Among the 9,763 elderly adults studied, 536 were found to have liver disease comorbidity, with binary or ternary comorbidity being the most prevalent. Provinces with a high prevalence of liver disease comorbidity were primarily concentrated in Inner Mongolia, Sichuan, and Henan. The most common comorbidity patterns identified were "liver-heart-metabolic", "liver-kidney", "liver-lung", and "liver-stomach-arthritic". In the eastern region, important combination patterns included "liver disease-metabolic disease", "liver disease-stomach disease", and "liver disease-arthritis", with the main influencing factors being sleep duration of less than 6 h, frequent drinking, female, and daily activity capability. In the central region, common combination patterns included "liver disease-heart disease", "liver disease-metabolic disease", and "liver disease-kidney disease", with the main influencing factors being an education level of primary school or below, marriage, having medical insurance, exercise, and no disabilities. In the western region, the main comorbidity patterns were "liver disease-chronic lung disease", "liver disease-stomach disease", "liver disease-heart disease", and "liver disease-arthritis", with the main influencing factors being general or poor health satisfaction, general or poor health condition, severe pain, and no disabilities. CONCLUSION: The comorbidities associated with liver disease exhibit specific clustering patterns at both the overall and local levels. By analyzing the comorbidity patterns of liver diseases in different regions and establishing co-morbid co-causal patterns, this study offers a new perspective and scientific basis for the prevention and treatment of liver diseases.