Spatial disparities and dynamic evolution of professional public health resource supply level in Beijing, China.

BACKGROUND: This study aims to explore the development status of the supply level of professional public health resources in Beijing Municipality, analyze the areal differences and spatial distribution characteristics of the supply level in 16 districts, and provide a scientific basis for promoting the balanced development of the supply level of professional public health resources in each district of Beijing Municipality. METHODS: Based on panel data from Statistical Yearbook of Health Work in Beijing Municipality and Health and Family Planning Work in Beijing Municipality from 2014 to 2022. Using the entropy method to measure the supply level of professional public health resources in Beijing, employing the Dagum Gini coefficient and Kernel density estimation method to analyze the spatial differentiation characteristics and dynamic evolution process of the supply level, and using heat maps to display the spatial distribution of the supply level in various districts of Beijing. RESULTS: The Dagum Gini coefficient of the supply level of professional public health resources in Beijing Municipality decreased continuously from 0.3419 in 2014 to 0.29736 in 2020, then gradually increased, showing a trend of initially decreasing and then increasing overall spatial differences. The spatial differences mainly stem from differences between areas. The kernel density curve shows that the supply level of professional public health resources in Beijing Municipality gradually increased, slightly decreased after 2021, and did not form a situation of two or multi-level differentiation. CONCLUSION: From 2014 to 2022, the supply level of professional public health resources in Beijing Municipality showed an overall upward trend, but attention should be paid to the decline after 2021; spatial differences initially decreased and then increased, and the differences between areas is the main source of the overall difference in Beijing. Therefore, the Beijing Municipal Government should focus on narrowing the differences between areas, determine the allocation and management of public health resources based on the actual situation of core areas, promote coordinated development within and outside areas, and thus enhance the supply level of professional public health resources.

Accessibility of TB diagnostic services at primary healthcare clinics in the eThekwini district, South Africa: a geospatial analysis.

BACKGROUND: Improving geographic access can aid in managing tuberculosis (TB) by enabling early diagnosis and treatment initiation. Although geospatial techniques have been used to map the transmission patterns of drug-resistant TB in South Africa, fewer studies have investigated the accessibility of TB diagnostic services. This study evaluated the accessibility of TB diagnostic services and disease distribution in the eThekwini district of South Africa. METHODS: In this cross-sectional study, population data for 2021 were disaggregated into smaller analysis units and then re-aggregated through the dasymetric mapping technique. Data on notified TB patients, including Global Positioning System coordinates of clinics, were obtained from the District of Health Information System, exported to ArcGIS 10.8.2 and used to calculate distances to the nearest clinics and hospitals. RESULTS: 92% of the population (3 730 494 people) in eThekwini could access TB diagnostic services within 5 km. Patients travelled an average distance of 4.7 km (range: 0.1-26.9 km). TB diagnostic services were highly accessible in the Northern and Central regions and moderately accessible in the predominately rural Western and Southern regions. The smallest population of eThekwini resides in rural areas; however, 40.7% of its residents live >5 km from a diagnosing facility, with patients in the South having to travel up to 44.5 km. TB incidence was higher in the predominately rural West and South regions compared with the Central and North regions which are mainly comprised of urban and suburban areas. Our findings also showed that 98.4% of the clinics in eThekwini were located within 30 km of a hospital at an average distance of 9.6 km within the district. However, the distribution of these hospitals does not demonstrate equitable access as the majority are located within the Central region, and fewer are found in the other three regions of eThekwini. CONCLUSIONS: Addressing the disparities in access to TB diagnostic services is required in the eThekwini district. Leveraging the existing mobile health clinics can assist with this, particularly, in rural areas with inadequate access. Additionally, active-case finding should be intensified in these regions since they had a higher TB burden per population. Prioritising interventions in these areas is crucial for reducing the impact of the disease on affected communities.

Long-Term Effect of Temperature Increase on Liver Cancer in Australia: A Bayesian Spatial Analysis.

BACKGROUND: While some evidence has potentially linked climate change to carcinogenic factors, the long-term effect of climate change on liver cancer risk largely remains unclear. OBJECTIVES: Our objective is to evaluate the long-term relationship between temperature increase and liver cancer incidence in Australia. METHODS: We mapped the spatial distribution of liver cancer incidence from 2001 to 2019 in Australia. A Bayesian spatial conditional autoregressive (CAR) model was used to estimate the relationships between the increase in temperature at different lags and liver cancer incidence in Australia, after controlling for chronic hepatitis B prevalence, chronic hepatitis C prevalence, and the Index of Relative Socio-economic Disadvantage. Spatial random effects obtained from the Bayesian CAR model were also mapped. RESULTS: The research showed that the distribution of liver cancer in Australia is spatially clustered, most areas in Northern Territory and Northern Queensland have higher incidence and relative risk. The increase in temperature at the lag of 30 years was found to correlate with the increase in liver cancer incidence in Australia, with a posterior mean of 30.57 [95% Bayesian credible interval (CrI): 0.17, 58.88] for the univariate model and 29.50 (95% CrI: 1.27, 58.95) after controlling for confounders, respectively. The results were not highly credible for other lags. DISCUSSION: Our Bayesian spatial analysis suggested a potential relationship between temperature increase and liver cancer. To our knowledge, this research marks the first attempt to assess the long-term effect of global warming on liver cancer. If the relationship is confirmed by other studies, these findings may inform the development of prevention and mitigation strategies based on climate change projections. https://doi.org/10.1289/EHP14574.

Exploring Cesarean Section Delivery Patterns in South India: A Bayesian Multilevel and Geospatial analysis of Population-Based Cross-Sectional Data.

BACKGROUND: This paper focuses on the period from 2019 to 2021 and investigates the factors associated with the high prevalence of C-section deliveries in South India. We also examine the nuanced patterns, socio-demographic associations, and spatial dynamics underlying C-section choices in this region. A cross-sectional study was conducted using large nationally representative survey data. METHODS: National Family Health Survey data (NFHS) from 2019 to 2021 have been used for the analysis. Bayesian Multilevel and Geospatial Analysis have been used as statistical methods. RESULTS: Our analysis reveals significant regional disparities in C-section utilization, indicating potential gaps in healthcare access and socio-economic influences. Maternal age at childbirth, educational attainment, healthcare facility type size of child at birth and ever pregnancy termination are identified as key determinants of method of C-section decisions. Wealth index and urban residence also play pivotal roles, reflecting financial considerations and access to healthcare resources. Bayesian multilevel analysis highlights the need for tailored interventions that consider individual household, primary sampling unit (PSU) and district-level factors. Additionally, spatial analysis identifies regions with varying C-section rates, allowing policymakers to develop targeted strategies to optimize maternal and neonatal health outcomes and address healthcare disparities. Spatial autocorrelation and hotspot analysis further elucidate localized influences and clustering patterns. CONCLUSION: In conclusion, this research underscores the complexity of C-section choices and calls for evidence-based policies and interventions that promote equitable access to quality maternal care in South India. Stakeholders must recognize the multifaceted nature of healthcare decisions and work collaboratively to ensure more balanced and effective healthcare practices in the region.

Spatial distribution characteristics and influencing factors of tourism resources based on point of interest data.

The agglomeration and dispersion of tourist attractions in space greatly affect the development of regional tourism resources and the consumption choice of tourism market. At present, the research on the spatial distribution characteristics of tourist attractions and their influencing factors mainly adopts induction and investigation, and there is a lack of effective statistical models for the research on the spatial distribution of tourist attractions and their influencing factors in some historical and cultural ancient cities. This paper uses Internet technology to obtain the spatial distribution data of tourist attractions in Shaoxing city, and uses mean nearest neighbor analysis, nuclear density analysis, imbalance index analysis, standard deviation ellipse and other spatial statistical analysis techniques and geographical detector methods to study the spatial distribution characteristics and influencing factors of tourist attractions in Shaoxing City. This paper studied the distribution characteristics of tourist attractions in Shaoxing city, such as spatial aggregation, distribution equilibrium and spatial orientation, and applied geographical detector to study the influencing factors of the spatial distribution of scenic spots. It was concluded that the spatial distribution pattern of scenic spots was affected by various factors such as natural environment, social environment and economic environment. The explanatory power of two-factor interaction is obviously stronger than that of single factor. The research results provide scientific basis for the planning, layout and development of tourist attractions in Shaoxing and its similar cities, and then promote the high-quality development of tourism in Shaoxing and its similar historical and cultural ancient cities.

Spatial distribution patterns and factors influencing rural tourism destinations: An empirical study of China's agritainment resorts.

Agritainment is one of the essential aspects of rural tourism and plays an important role in the economic transformation and revitalization of rural areas. Taking 9200 agritainment resorts in China as a research object, this paper systematically uses geospatial analysis methods to analyze their spatial distribution patterns and influencing mechanisms. The results indicate: (1) All types of agritainment have a condensed distribution in space and are oriented in the northeast-southwest direction, with a central axis generally located in the Beijing-Zhengzhou-Wuhan line. (2) The distribution of agritainment is uneven across different spatial scales, and there are high-density clusters in the Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Sichuan-Chongqing region as the core, and sub-high-density distribution areas in the Shaanxi-Gansu-Ningxia border, the southern coastal region, and the Xiangan-Jiang-Hubei border, manifesting prominent spatial distribution characteristics of large agglomeration and low dispersion. (3) Agritainment has a significant positive spatial autocorrelation. The Matthew effect is highly significant in space. The distribution of cold hot spots in the agritainment space shows a distribution pattern of "hot in the south and cold in the north." (4) The spatial distribution of agritainment is influenced by human factors such as society, economy, and the tourism industry as well as natural factors such as terrain, water systems, and climate. The intensity of influence of first-level human factors on the spatial distribution of agritainment ranks as follows: tourism industry factors (0.69) > social factors (0.37) > economic factors (0.30). The natural distribution of agritainment tends to be in humid plain and hilly areas with an altitude below 1000 m and annual precipitation above 800 mm. Agritainment is mainly distributed in the subtropical monsoon climate area adjacent to rivers. The research findings offer valuable insights for optimizing the spatial distribution pattern of agritainment in China, promoting the high-quality development of agritainment, and the sustainable development of rural tourism.

Changing seroprevalence of schistosomiasis japonica in China from 1982 to 2020: A systematic review and spatial analysis.

BACKGROUND: Schistosomiasis is a global public health issue. In China, while the seroprevalence of Schistosomiasis japonica has currently reduced to a relatively low level, risk of infection still exists in certain areas. However, there has been a lack of comprehensive research on the long-term trends of national seroprevalence, changes across age groups, and characteristics in spatial distribution, which is crucial for effectively targeting interventions and achieving the goal of eliminating schistosomiasis by 2030. Our study aimed to address this gap by analyzing the long-term trends of Schistosomiasis japonica seroprevalence in China from 1982 to 2020 based on the data from diverse sources spanning a period of 39 years. METHODOLOGY: Seroprevalence data were collected from literature databases and national schistosomiasis surveillance system. Meta-analysis was conducted to estimate the seroprevalence. Joinpoint model was used to identify changing trend and inflection point. Inverse distance weighted interpolation was used to determine the spatial distribution of seroprevalence. PRINCIPAL FINDINGS: The seroprevalence decreased from 34.8% in 1982 to 2.4% in 2020 in China. Before 2006, the seroprevalence was higher in the middle age group, and a pattern of increasing with age was observed afterwards. The areas with high seroprevalence existed in Dongting Lake, Poyang Lake, Jianghan Plain, the Anhui branch of the Yangtze River and some localized mountainous regions in Sichuan and Yunnan provinces. CONCLUSIONS/SIGNIFICANCE: There was a significant decline in the seroprevalence of Schistosomiasis japonica from 1982 to 2020 in China. Nevertheless, schistosomiasis has not been eradicated; thus, implementing precise and personalized monitoring measures is crucial for the elimination of schistosomiasis, especially in endemic areas and with a particular focus on the elderly.

A framework integrating affinity propagation algorithm and spatial bivariate analysis for enhanced identification and localisation of soil heavy metals pollution sources.

The accurate identification of pollutant sources and their spatial distribution is crucial for mitigating soil heavy metals (SHMs) pollution. However, the receptor model struggles to effectively categorize pollutant sources and pinpoint their locations and dispersion trends. We propose a novel comprehensive framework that combines a receptor model, random forest (RF), affinity propagation (AP) algorithm, and bivariate local indicator of spatial association (BLISA), to optimize the traditional approach for tracing SHMs sources in industrial regions. We apportioned SHMs sources using a receptor model combined with RF, while BLISA combined with AP methods were employed to accurately locate the source areas and identify their dispersion tendencies. The results revealed that SHMs originated from mixed sources of equipment manufacturing agglomeration and agricultural activities (59.0%), geological background (30.5%), and emissions from heavily-polluting industries (10.5%). The pollution sources of soil Cd and Pb were located near specific industries, showing characteristics of multi-site concurrent pollution diffusion influenced by their proximity to industrial sites. The spatial distribution of Cr, Cu, and Zn sources was concentrated in high-density urban industrial areas, transitioning from point to nonpoint sources, with diffusion patterns influenced by the spatial agglomeration effect of industries. Our enhanced framework accurately identifies the location of SHMs sources and their dispersion tendencies, thereby improving regional soil pollution management.

Spatial distribution and associated factors of cesarean section in Ethiopia using mini EDHS 2019 data: a community based cross-sectional study.

Maternal health is a major public health tricky globally. Cesarean section delivery reduces morbidity and mortality when certain complications occur throughout pregnancy and labor. Cesarean section subjected to the availability and use of essential obstetric services in regional factors in Ethiopia. There was a scarcity of studies that assess the spatial distribution and associated factors of cesarean section. Consequently, this study aimed to assess the spatial variation of cesarean section and associated factors using mini EDHS 2019 national representative data. A community based cross-sectional study was conducted in Ethiopia from March to June 2019. A two-stage stratified sampling design was used to select participants. A Global Moran's I and Getis-Ord Gi* statistic hotspot analysis was used to assess the spatial distribution. Kuldorff's SaTScan was employed to determine the purely statistically significant spatial clusters. A multilevel binary logistic regression model fitted to identify factors. A total of 5753 mothers were included. More than one-fourth of mothers delivered through cesarean section at private health institutions and 54.74% were not educated. The proportion of cesarean section clustered geographically in Ethiopia and hotspot areas were observed in Addis Ababa, Oromia, Tigray, Derie Dewa, Amhara, and SNNR regions. Mothers' age (AOR = 1.07, 95% CI 1.02-1.12), mother's had secondary education (AOR = 2.113, 95% CI 1.414, 3.157), mother's higher education (2.646, 95% CI 1.724, 4.063), Muslim religion followers (AOR = 0.632, 95% CI 0.469, 0.852), poorer (AOR = 1.719, 95% CI 1.057, 2.795), middle wealth index (AOR = 1.769, 95% CI 1.073, 2.918), richer (AOR = 2.041, 95% CI 1.246, 3.344), richest (AOR = 3.510, 95% CI 2.197, 5.607), parity (AOR = 0.825, 95% CI 0.739, 0.921), and multiple pregnancies (AOR = 4.032, 95% CI 2.418, 6.723) were significant factors. Therefore, geographically targeted interventions are essential to reduce maternal and infant mortality with WHO recommendations for those Muslim, poorest and not educated mothers.

Combining molecular transmission network analysis and spatial epidemiology to reveal HIV-1 transmission pattern among the older people in Nanjing, China.

BACKGROUND: In China, the problem of HIV infection among the older people has become increasingly prominent. This study aimed to analyze the pattern and influencing factors of HIV transmission based on a genomic and spatial epidemiological analysis among this population. METHODS: A total of 432 older people who were aged ≥ 50 years, newly diagnosed with HIV-1 between January 2018 and December 2021 and without a history of ART were enrolled. HIV-1 pol gene sequence was obtained by viral RNA extraction and nested PCR. The molecular transmission network was constructed using HIV-TRACE and the spatial distribution analyses were performed in ArcGIS. The multivariate logistic regression analysis was performed to analyze the factors associated with clustering. RESULTS: A total of 382 sequences were successfully sequenced, of which CRF07_BC (52.3%), CRF01_AE (32.5%), and CRF08_BC (6.8%) were the main HIV-1 strains. A total of 176 sequences entered the molecular network, with a clustering rate of 46.1%. Impressively, the clustering rate among older people infected through commercial heterosexual contact was as high as 61.7% and three female sex workers (FSWs) were observed in the network. The individuals who were aged ≥ 60 years and transmitted the virus by commercial heterosexual contact had a higher clustering rate, while those who were retirees or engaged other occupations and with higher education degree were less likely to cluster. There was a positive spatial correlation of clustering rate (Global Moran I = 0.206, P < 0.001) at the town level and the highly aggregated regions were mainly distributed in rural area. We determined three large clusters which mainly spread in the intra-region of certain towns in rural areas. Notably, 54.5% of cases in large clusters were transmitted through commercial heterosexual contact. CONCLUSIONS: Our joint analysis of molecular and spatial epidemiology effectively revealed the spatial aggregation of HIV transmission and highlighted that towns of high aggregation were mainly located in rural area. Also, we found vital role of commercial heterosexual contact in HIV transmission among older people. Therefore, health resources should be directed towards highly aggregated rural areas and prevention strategy should take critical persons as entry points.

Disparities in the real-world prescription pattern of oral anticoagulants for US Medicare beneficiaries: a geospatial analysis.

OBJECTIVES: This study was conducted to examine urban-rural differences in the real-world prescribing pattern of oral anticoagulants and geographic variations in the prescribing pattern among clinicians serving Medicare beneficiaries in the USA. DESIGN: A cross-sectional study. SETTING: A real-world setting. PARTICIPANTS: 232 665 clinicians who prescribed oral anticoagulants for Medicare beneficiaries from the 2020 Medicare Provider Utilisation and Payment Data were classified as warfarin only, direct oral anticoagulants (DOACs) only or warfarin+DOAC prescribers. MAIN OUTCOME MEASURES: Urban-rural differences in the prescribing patterns were examined using multivariate multinominal logistic regression analysis. A geospatial analysis was conducted to estimate standardised prescriber ratios (SPR) for DOAC only or warfarin only prescribers versus warfarin+DOAC prescribers to illustrate hot and cold spots for DOAC adoption in the USA. RESULTS: 92% of clinicians who prescribed oral anticoagulants prescribed DOAC in 2020. Clinicians from rural regions were more likely to prescribe warfarin only (adjusted OR=1.335, 95% CI=(1.281 to 1.391)) and DOAC only (adjusted OR=2.052, 95% CI=(1.999 to 2.106)), compared with clinicians from urban regions. Hot spots for SPR of DOAC only versus warfarin+DOAC prescribers were mostly found in California, southern and southeastern states; cold spots were mostly found in Minnesota and Iowa. Hot spots for SPR of warfarin only versus warfarin+DOAC prescribers were mostly found in several metropolitan areas on the west coast and in Midwest; cold spots were mostly found on the east coast. CONCLUSIONS: Urban-rural status of clinicians was associated with their prescribing patterns of oral anticoagulants. The study identifies geographical heterogeneity in DOAC adoption and highlights gaps that may need to be addressed for increased accessibility of DOAC for patients in need.

[Spatial Distribution Characteristics of Plant Community and the Identification of Driving Factors in Riparian Zone of the Three-River Headwaters Region, China].

The unique geographical and climatic conditions in the Three-River Headwaters Region gave birth to distinctive plant species and vegetation types. To reveal the spatial distribution of plant communities and soil habitats along the riparian zone of the Sanjiangyuan Region and their influencing mechanisms, 14 survey plots were set up （ten from the Yangtze River source, two from the Lancang River source, and two from the Yellow River source）, and the effects of soil nutrient characteristics （especially soil phosphorus morphology）, climate factors, and river topography on plant community characteristics were quantitatively analyzed. The results showed that the plant community composition in the riparian zone of the source of the three rivers was dominated by perennial herbs （72.2%）, followed by annual herbs （20.4%） and shrubs （7.4%）. The dominant plants were Stipa purpurea, Polygonum orbiculatum, Carex parvula, Potentilla anserina, and Gentiana straminea. The average plant coverage, Shannon-Wiener index, and Pielou index were （64.4% ±23.6%）, （1.31 ±0.42）, and （0.84 ±0.08）, respectively. The plant community diversity index was the highest in the Yangtze River source, followed by that in the Lancang River source, and the lowest in the Yellow River source. The soil pH of the riparian zone of the Yangtze River source was significantly higher than that of the Lancang River source, whereas the mean contents of organic matter, total nitrogen, and Fe-Al combined phosphorus were significantly lower than those of the Lancang River source. The calcium and magnesium-combined phosphorus was the main form of phosphorus in riparian soil （63.89%）. Temperature, soil organic phosphorus content, and pH had significant effects on plant composition in the riparian zone of the Three-River Headwaters Region, whereas soil calcium and magnesium-combined phosphorus content had significant effects on plant community diversities. These results may deepen the scientific understanding of the evolution trend and genetic mechanism of plant communities in the riparian zone of the Three-River Headwaters Region.

Spatial analysis of ischemic stroke in Spain: the roles of accessibility to healthcare and economic development.

Ischemic stroke is a major cause of mortality worldwide; however, few studies have been conducted to measure the impact of the distribution of healthcare services on ischemic stroke fatality. This study aimed to explore the relationship between three ischemic stroke outcomes (incidence, mortality, and fatality) and accessibility to hospitals in Spain, considering its economic development. A cross-sectional ecological study was performed using data on hospital admissions and mortality due to ischemic stroke during 2016-2018. Gross geographic product (GGP) per capita was estimated and a healthcare accessibility index was created. A Besag-York-Mollié autoregressive spatial model was used to estimate the magnitude of association between ischemic stroke outcomes and economic development and healthcare accessibility. GGP per capita showed a geographical gradient from southwest to northeast in Spain. Mortality and case-fatality rates due to ischemic stroke were higher in the south of the country in both women and men aged 60+ years. In women and men aged 20-59 years a EUR 1,000 increase in GGP per capita was associated with decreases in mortality of 5% and 4%, respectively. Fatality decreased 3-4% with each EUR 1,000 increase of GGP per capita in both sexes and in the 20-59 and 60+ age groups. Decreased healthcare accessibility was associated with higher fatality in the population aged 60+. Economic development in southwest Spain would not only improve employment opportunities but also reduce ischemic stroke mortality. New health related strategies to improve hospital accessibility should be considered in more sparsely populated regions or those with worse transport and/or healthcare infrastructure.

Tuberculosis in Aceh Province, Indonesia: a spatial epidemiological study covering the period 2019-2021.

The purpose of this study was to determine whether there were any TB clusters in Aceh Province, Indonesia and their temporal distribution during the period of 2019-2021. A spatial geo-reference was conducted to 290 sub-districts coordinates by geocoding each sub-district's offices. By using SaTScan TM v9.4.4, a retrospective space-time scan statistics analysis based on population data and annual TB incidence was carried out. To determine the regions at high risk of TB, data from 1 January 2019 to 31 December 2021 were evaluated using the Poisson model. The likelihood ratio (LLR) value was utilized to locate the TB clusters based on a total of 999 permutations were performed. A Moran's I analysis (using GeoDa) was chosen for a study of both local and global spatial autocorrelation. The threshold for significance was fixed at 0.05. At the sub-district level, the spatial distribution of TB in Aceh Province from 2019-2021 showed 19 clusters (three most likely and 16 secondary ones), and there was a spatial autocorrelation of TB. The findings can be used to provide thorough knowledge on the spatial pattern of TB occurrence, which is important for designing effective TB interventions.

Performance of a negative binomial-GLM in spatial scan statistic: a case study of low-birth weights in Pakistan.

Spatial cluster analyses of health events are useful for enabling targeted interventions. Spatial scan statistic is the stateof- the-art method for this kind of analysis and the Poisson Generalized Linear Model (GLM) approach to the spatial scan statistic can be used for count data for spatial cluster detection with covariate adjustment. However, its use for modelling is limited due to data over-dispersion. A Generalized Linear Mixed Model (GLMM) has recently been proposed for modelling this kind of over-dispersion by incorporating random effects to model area-specific intrinsic variation not explained by other covariates in the model. However, these random effects may exhibit a geographical correlation, which may lead to a potential spatial cluster being undetected. To handle the over-dispersion in the count data, this study aimed to evaluate the performance of a negative binomial- GLM in spatial scan statistic on real-world data of low birth weights in Khyber-Pakhtunkhwa Province, Pakistan, 2019. The results were compared with the Poisson-GLM and GLMM, showing that the negative binomial-GLM is an ideal choice for spatial scan statistic in the presence of over-dispersed data. With a covariate (maternal anaemia) adjustment, the negative binomial-GLMbased spatial scan statistic detected one significant cluster covering Dir lower district. Without the covariate adjustment, it detected two clusters, each covering one district. The district of Peshawar was seen as the most likely cluster and Battagram as the secondary cluster. However, none of the clusters were detected by GLMM spatial scan statistic, which might be due to the spatial correlation of the random effects in GLMM.

[Spatial distribution of soil microorganisms in the Zoige Plateau peatland, Southwest China]. / 若尔盖高原泥炭沼泽土壤微生物空间分布.

Understanding the composition and spatial distribution patterns of microbial communities in plateau peatland soils is crucial for preserving the structural and functional stability of highland wetlands. We collected 50 soil samples from the core conservation area of Zoige peatland along horizontal and vertical distributions to analyze the soil bacterial and fungal diversity by using high-throughput sequencing technology, combined with Mantel tests and multiple regression on matrices (MRM) statistical methods, as well as the spatial distribution characteristics of community structure similarity at a local scale. The results showed that the dominant soil bacterial and fungal groups were Chloroflexi (accounting for 33.2% and 25.1% of the total bacterial community in horizontal and vertical directions, respectively) and Ascomycota (54.7% and 76.4%). The similarity of microbial community structure in both horizontal and vertical directions decreased with increasing spatial distance of the sampling points. The turnover rates of bacterial and fungal communities in the vertical direction were 8.8 and 8.6 times as those in the horizontal direction, respectively. Based on the relative abundance of the communities, we classified microbes into six groups. As the number of rare species in the community increased, the slope of community distance decay decreased. The conditionally rare or abundant taxa (CRAT) category group showed the most similar spatial distribution characteristics to the total microbial community. Mantel analysis indicated that soil organic carbon, total nitrogen, and available phosphorus were key factors driving the distribution of bacterial and fungal communities in the horizontal direction, while soil organic carbon, available carbon, pH, and soil bulk density were the main factors determining the vertical distribution. MRM analysis further showed that both soil physicochemical indicators and spatial distance significantly affected the assembly of microbial communities, where soil factors explained more about the vertical distribution of microbial communities than the horizontal distribution. The impact of soil factors on microbial community distribution was much greater than that of spatial factors through diffusion limitation. In summary, the microbial communities in the plateau peatland soils exhibited more pronounced vertical distribution differences and environmental response characteristics.

Assessing the spatial equity of the aged care institutions based on the improved potential model: a case study in Shanghai, China.

With the spread of an aging society, the demand for aged care institutions among older adults is increasing. The inadequate supply and distribution of aged care institutions have led to an increasing concern about spatial equity in aged care institutions. Most studies have utilized accessibility to assess spatial equity from the supply perspective, while the demand perspective has received little attention. In addition, few studies have evaluated the spatial equity of aged care institutions at grid resolution. Therefore, this study takes Shanghai as an example to analyze aged care institutions from both the supply and demand perspectives. By proposing an improved potential model, at a network resolution of 500 × 500, the spatial equity of aged care institutions is more refined. The results show that aged care institutions and the older population in Shanghai are predominantly concentrated in the downtown area and surrounding regions. However, the results obtained from the Lorenz curve and Gini coefficient indicate the allocation of pension beds based on population size is proportional across different districts of Shanghai. When considering the quality indicators of aged care institutions and introducing the improved potential energy model to calculate spatial accessibility, an imbalance between regions in Shanghai still exists and needs further optimization.

Spatial effects of township health centers' health resource allocation efficiency in China.

Introduction: China is a large agricultural nation with the majority of the population residing in rural areas. The allocation of health resources in rural areas significantly affects the basic rights to life and health for rural residents. Despite the progress made by the Chinese government in improving rural healthcare, there is still room for improvement. This study aims to assess the spatial spillover effects of rural health resource allocation efficiency in China, particularly focusing on township health centers (THCs), and examine the factors influencing this efficiency to provide recommendations to optimize the allocation of health resources in rural China. Methods: This study analyzed health resource allocation efficiency in Chinese rural areas from 2012 to 2021 by using the super-efficiency SBM model and the global Malmquist model. Additionally, the spatial auto-correlation of THC health resource allocation efficiency was verified through Moran test, and three spatial econometric models were constructed to further analyze the factors influencing efficiency. Results: The key findings are: firstly, the average efficiency of health resource allocation in THCs was 0.676, suggesting a generally inefficient allocation of health resources over the decade. Secondly, the average Malmquist productivity index of THCs was 0.968, indicating a downward trend in efficiency with both non-scale and non-technical efficient features. Thirdly, Moran's Index analysis revealed that efficiency has a significant spatial auto-correlation and most provinces' values are located in the spatial agglomeration quadrant. Fourthly, the SDM model identified several factors that impact THC health resource allocation efficiency to varying degrees, including the efficiency of total health resource allocation, population density, PGDP, urban unemployment rate, per capita disposable income, per capita healthcare expenditure ratio, public health budget, and passenger traffic volume. Discussion: To enhance the efficiency of THC healthcare resource allocation in China, the government should not only manage the investment of health resources to align with the actual demand for health services but also make use of the spatial spillover effect of efficiency. This involves focusing on factors such as total healthcare resource allocation efficiency, population density, etc. to effectively enhance the efficiency of health resource allocation and ensure the health of rural residents.

Spatial pattern and determinants of non-condom use among sexually active young people in Nigeria: a population-based, cross-sectional study.

Non-condom use is known as one of the risky sexual behaviors among youth and a contributing factor to the high prevalence of HIV in Nigeria. Therefore this study aimed to assess the spatial pattern and determinants of non-condom use among sexually active young people in Nigeria. The study employed a cross-sectional analysis of population-based data involving 288 males and 780 females aged 15-24 years, giving 1068 sexually active young people drawn from the 2018 NDHS. The study adopted a multi-level and spatial analysis to identify factors associated with non-condom use in Nigeria. The prevalence of non-condom use was 57.7% in this study. The spatial analysis showed that the Northeastern and South-South regions of Nigeria had a high proportion of non-condom use among young people, while the Northwest, North-Central, and Southwestern parts had low proportions of non-condom use. On multilevel analysis, the individual and community level factors associated with non-condom use included exposure to media (AOR 0.59; 95% CI 0.39-0.91) and younger age (AOR 0.72; 95% CI 0.53-0.98). Areas with a high proportion of non-condom use should receive the most attention through the promotion of condom use and education, alongside a focus on important associated factors.

Spatially clustered patterns of suicide mortality rates in South Korea: a geographically weighted regression analysis.

BACKGROUND: Suicide mortality remains a global health concern, and community characteristics affect regional variations in suicide. This study investigated spatially clustered patterns of suicide mortality rates in South Korea and evaluated the impact of community factors on suicide. METHODS: Suicide mortality rates were estimated by sex, age group, and district, using the 2021 Cause of Death Statistics in South Korea from the MicroData Integrated Service. Community-determinant data for 2021 or the nearest year were collected from the Korean Statistical Information Service. The spatial autocorrelation of suicide by sex and age was examined based on Global Moran's I index. Geographically weighted regression (GWR) was used to discern the influence of community determinants on suicide. RESULTS: Suicide mortality rates were significantly higher among men (40.64 per 100,000) and adults over the age of 65 years (43.18 per 100,000). The male suicide mortality rates exhibited strong spatial dependence, as indicated by a high global Moran's I with p < 0.001, highlighting the importance of conducting spatial analysis. In the GWR model calibration, a subset of the community's age structure, single-person household composition, access to mental healthcare centers, and unmet medical needs were selected to explain male suicide mortality. These determinants disproportionately increased the risk of male suicide, varying by region. The GWR coefficients of each variable vary widely across 249 districts: aging index (Q1:0.06-Q3:0.46), single-person households (Q1:0.22-Q3:0.35), psychiatric clinics (Q1:-0.20-Q3:-0.01), and unmet medical needs (Q1:0.09-Q3:0.14). CONCLUSIONS: Community cultural and structural factors exacerbate regional disparities in suicide among men. The influencing factors exhibit differential effects and significance depending on the community, highlighting the need for efficient resource allocation for suicide. A regionally tailored approach is crucial for the effective control of the community's mental health management system.