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1.
PLoS One ; 19(6): e0305345, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38889132

RESUMO

Conducting this research contributes to a deeper understanding of the correlation between atmospheric environmental quality and lung cancer incidence, and provides the scientific basis for formulating effective environmental protection and lung cancer prevention and control strategies. Lung cancer incidence in China has strong spatial variation. However, few studies have systematically revealed the characteristics of the spatial variation in lung cancer incidence, and have explained the causes of this spatial variation in lung cancer incidence from the perspectives of multiple components of the atmospheric environment to explain this spatial variation in lung cancer incidence. To address research limitations, we first analyze the spatial variation and spatial correlation characteristics of lung cancer incidence in China. Then, we build a spatial regression model using GeoDa software with lung cancer incidence as the dependent variable, five atmospheric environment factors-particulate matter 2.5 (PM2.5) concentration, temperature, atmospheric pressure, and elevation as explanatory variables, and four socio-economic characteristics as control variables to systematically analyze the influence and intensity of these factors on lung cancer incidence. The results show that lung cancer incidence in China has apparent changes in geographical and spatial unevenness, and spatial autocorrelation characteristics. In China, the lung cancer incidence is relatively high in Northeast China, while some areas of high lung cancer incidence still exist in Central China, Southwest China and South China, although the overall lung cancer incidence is relatively low. The atmospheric environment significantly affects lung cancer incidence. Different elements of the atmospheric environment vary in the direction and extent of their influence on the development of lung cancer. A 1% increase in PM2.5 concentration is associated with a level of 0.002975 increase in lung cancer incidence. Atmospheric pressure positively affects lung cancer incidence, and an increase in atmospheric pressure by 1% increases lung cancer incidence by a level of 0.026061. Conversely, a 1% increase in temperature is linked to a level of 0.006443 decreases in lung cancer incidence, and a negative correlation exists between elevation and lung cancer incidence, where an increase in elevation by 1% correlates with a decrease in lung cancer incidence by a level of 0.000934. The core influencing factors of lung cancer incidence in the seven geographical divisions of China exhibit variations. This study facilitates our understanding of the spatial variation characteristics of lung cancer incidence in China on a finer scale, while also offering a more diverse perspective on the impact of the atmospheric environment on lung cancer incidence.


Assuntos
Neoplasias Pulmonares , Material Particulado , Neoplasias Pulmonares/epidemiologia , Neoplasias Pulmonares/etiologia , China/epidemiologia , Incidência , Humanos , Material Particulado/análise , Material Particulado/efeitos adversos , Atmosfera/química , Pressão Atmosférica , Temperatura , Análise Espacial , Poluição do Ar/efeitos adversos , Poluição do Ar/análise
2.
Zhonghua Liu Xing Bing Xue Za Zhi ; 45(6): 844-851, 2024 Jun 10.
Artigo em Chinês | MEDLINE | ID: mdl-38889985

RESUMO

Objective: To understand the characteristics and trends of acute myocardial infarction (AMI) in Shandong Province and to provide evidence for formulating prevention and control strategies. Methods: Data were derived from the AMI incidence reports of Shandong Province's Chronic Disease Surveillance Information Management System in 2012-2021. The crude and standardized incidence rates were used as indicators to describe the incidence level of AMI. Joinpoint regression analysis was used to analyze the trends in the incidence and age of onset over the years. The contribution of population aging to the increase in AMI incidence was assessed using the rate difference decomposition method. The incidence of AMI in each district (county) in Shandong Province was visualized using ArcGIS 10.8 software, and global and local spatial autocorrelation analysis was performed using DeoDa 1.12 software. Results: From 2012 to 2021, 198 233 cases of AMI were reported from 19 provincial monitoring sites in Shandong Province, of which 53.13% were males and 97.12% were ≥45 years old. The reported crude incidence increased from 90.12 per 100 000 in 2012 to 176.54 per 100 000 in 2021, with an average annual increase of 7.01% (Z=7.35, P<0.001). There was no significant upward trend in standardized incidence (Z=1.64, P=0.140), but the standardized incidence of male residents showed an increasing trend (Z=2.76, P=0.028). Before 2014, the reported crude incidence of males was similar to that of females, but after 2014, the reported crude incidence of males was continuously higher than that of females. However, males' standardized incidence was higher than females in all years. Both crude and standardized incidence rates were higher in rural residents than in urban areas. The median onset of AMI increased from 71.6 years old in 2012 to 73.5 years old in 2021. The median age of onset in males was lower than that in females in all years, and in most years, the median age of onset in urban residents was lower than that in rural residents. The incidence of AMI in males showed a trend in younger age groups. According to the seasonal decomposition, the incidence peak of AMI was in January, and the trough was in September. The contribution of aging population to the increase in crude incidence of AMI increased from 8.63% in 2013 to 52.58% in 2021. The global spatial autocorrelation analysis showed that the incidence of AMI presented an obvious spatial clustering distribution. Local spatial autocorrelation analysis found that the high-incidence areas (counties) were mainly concentrated in Liaocheng City and Dezhou City in the northwest region of Shandong Province and Heze City in the southwest. Conclusions: The incidence of AMI among residents in Shandong Province was rising, with spatial clustering and seasonal clustering characteristics. People aged 45 years and older, male residents, and rural residents were at high risk of developing AMI. There was a certain trend of younger age at onset among men. Targeted prevention and control measures should be taken for high-incidence seasons, high-risk groups, and high-incidence clustering areas in northwestern Shandong Province.


Assuntos
Infarto do Miocárdio , Humanos , Infarto do Miocárdio/epidemiologia , China/epidemiologia , Incidência , Masculino , Feminino , Pessoa de Meia-Idade , Idoso , Prevalência , Análise Espacial
3.
PLoS One ; 19(6): e0305397, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38870132

RESUMO

PURPOSE: The National Fitness Plan (NFP) is a vital initiative aimed at realizing Healthy China 2030. This study assessed spatial heterogeneity in the NFP development and the socioeconomic factors contributing to this inequality. METHODS: Data from 31 administrative regions in 2021 were analyzed using four NFP development metrics. Spatial autocorrelation was evaluated using global Moran's I, followed by global and local regression models for non-random spatial patterns. RESULTS: National physical fitness exhibited significant clustering (z = 5.403), notably a high-high cluster in East China. The global regression model identified three socioeconomic factors in the geographically weighted regression model: per capita disposable income and the number of public buses positively affected national physical fitness, while general public budget expenditure had a negative impact. CONCLUSIONS: Persistent unequal NFP development is projected due to income disparities in economically backward regions. To promote the NFP effectively, a cost-efficient strategy includes creating 15-minute fitness circles, especially by establishing public sports facilities in Western China communities. These findings inform policy priorities for advancing the NFP towards Healthy China 2030.


Assuntos
Aptidão Física , China , Humanos , Fatores Socioeconômicos , Análise Espacial
4.
PLoS One ; 19(6): e0302598, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38870179

RESUMO

In the context of emerging international trade regulations on deforestation-free commodities, the drivers of households' deforestation in conservation landscapes are of interest. The role of households' livelihood strategies including cocoa production, and the effects of human-elephant conflict are investigated. Using a unique dataset from a survey of 1035 households in the Tridom landscape in the Congo basin, the spatial autoregressive model shows that: (1) Households imitate the deforestation decisions of their neighbors; (2) A marginally higher income from cocoa production-based livelihood portfolios is associated with six to seven times higher deforestation compared to other livelihood strategies with a significant spillover effect on neighboring households' deforestation. The increase in income, mainly from cocoa production-based livelihoods in open-access systems can have a negative effect on forests. Households with a higher share of auto-consumption are associated with lower deforestation. If economic development brings better market access and lower auto-consumption shares, this is likely to positively influence deforestation. Without proper land use planning/zoning associated with incentives, promoting sustainable agriculture, such as complex cocoa agroforestry systems, may lead to forest degradation and deforestation.


Assuntos
Cacau , Conservação dos Recursos Naturais , Congo , Humanos , Análise Espacial , Agricultura/economia , Florestas , Características da Família , Renda
5.
Spat Spatiotemporal Epidemiol ; 49: 100646, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38876556

RESUMO

In practice, survival analyses appear in pharmaceutical testing, procedural recovery environments, and registry-based epidemiological studies, each reasonably assuming a known patient population. Less commonly discussed is the additional complexity introduced by non-registry and spatially-referenced data with time-dependent covariates in observational settings. In this short report we discuss residual diagnostics and interpretation from an extended Cox proportional hazard model intended to assess the effects of wildfire evacuation on risk of a secondary cardiovascular events for patients of a specific healthcare system on the California's central coast. We describe how traditional residuals obscure important spatial patterns indicative of true geographical variation, and their impacts on model parameter estimates. We briefly discuss alternative approaches to dealing with spatial correlation in the context of Bayesian hierarchical models. Our findings/experience suggest that careful attention is needed in observational healthcare data and survival analysis contexts, but also highlights potential applications for detecting observed hospital service areas.


Assuntos
Teorema de Bayes , Modelos de Riscos Proporcionais , Humanos , Análise de Sobrevida , California/epidemiologia , Incêndios Florestais , Doenças Cardiovasculares/mortalidade , Doenças Cardiovasculares/epidemiologia , Análise Espacial
6.
Spat Spatiotemporal Epidemiol ; 49: 100654, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38876557

RESUMO

BACKGROUND: Spatial modeling of disease risk using primary care registry data is promising for public health surveillance. However, it remains unclear to which extent challenges such as spatially disproportionate sampling and practice-specific reporting variation affect statistical inference. METHODS: Using lower respiratory tract infection data from the INTEGO registry, modeled with a logistic model incorporating patient characteristics, a spatially structured random effect at municipality level, and an unstructured random effect at practice level, we conducted a case and simulation study to assess the impact of these challenges on spatial trend estimation. RESULTS: Even with spatial imbalance and practice-specific reporting variation, the model performed well. Performance improved with increasing spatial sample balance and decreasing practice-specific variation. CONCLUSION: Our findings indicate that, with correction for reporting efforts, primary care registries are valuable for spatial trend estimation. The diversity of patient locations within practice populations plays an important role.


Assuntos
Atenção Primária à Saúde , Sistema de Registros , Humanos , Atenção Primária à Saúde/estatística & dados numéricos , Masculino , Feminino , Adulto , Pessoa de Meia-Idade , Análise Espacial , Infecções Respiratórias/epidemiologia , Idoso , Adolescente , Modelos Logísticos , Criança , Modelos Estatísticos , Adulto Jovem , Pré-Escolar
7.
Spat Spatiotemporal Epidemiol ; 49: 100643, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38876553

RESUMO

Dementia is a major global public health concern that is increasingly leading to morbidity and mortality among older adults. While studies have focused on the risk factors and care provision, there is currently limited knowledge about the spatial risk pattern of the disease. In this study, we employ Bayesian spatial modelling with a stochastic partial differential equation (SPDE) approach to model the spatial risk using complete residential history data from the Danish population and health registers. The study cohort consisted of 1.6 million people aged 65 years and above from 2005 to 2018. The results of the spatial risk map indicate high-risk areas in Copenhagen, southern Jutland and Funen. Individual socioeconomic factors and population density reduce the intensity of high-risk patterns across Denmark. The findings of this study call for the critical examination of the contribution of place of residence in the susceptibility of the global ageing population to dementia.


Assuntos
Demência , Sistema de Registros , Análise Espacial , Humanos , Dinamarca/epidemiologia , Demência/epidemiologia , Idoso , Masculino , Feminino , Idoso de 80 Anos ou mais , Fatores de Risco , Estudos de Coortes , Teorema de Bayes , Características de Residência/estatística & dados numéricos , Fatores Socioeconômicos
8.
Spat Spatiotemporal Epidemiol ; 49: 100647, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38876560

RESUMO

A factor constraining the elimination of dog-mediated human rabies is limited information on the size and spatial distribution of free-roaming dog populations (FRDPs). The aim of this study was to develop a statistical model to predict the size of free-roaming dog populations and the spatial distribution of free-roaming dogs in urban areas of Nepal, based on real-world dog census data from the Himalayan Animal Rescue Trust (HART) and Animal Nepal. Candidate explanatory variables included proximity to roads, building density, specific building types, human population density and normalised difference vegetation index (NDVI). A multivariable Poisson point process model was developed to estimate dog population size in four study locations in urban Nepal, with building density and distance from nearest retail food establishment or lodgings as explanatory variables. The proposed model accurately predicted, within a 95 % confidence interval, the surveyed FRDP size and spatial distribution for all four study locations. This model is proposed for further testing and refinement in other locations as a decision-support tool alongside observational dog population size estimates, to inform dog health and public health initiatives including rabies elimination efforts to support the 'zero by 30' global mission.


Assuntos
Doenças do Cão , Densidade Demográfica , Raiva , Animais , Cães , Nepal/epidemiologia , Raiva/epidemiologia , Raiva/veterinária , Raiva/prevenção & controle , Doenças do Cão/epidemiologia , Humanos , População Urbana/estatística & dados numéricos , Análise Espacial , Modelos Estatísticos
9.
Spat Spatiotemporal Epidemiol ; 49: 100660, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38876554

RESUMO

OBJECTIVES: Belgium experienced multiple COVID-19 waves that hit various groups in the population, which changed the mortality pattern compared to periods before the pandemic. In this study, we investigated the geographical excess mortality trend in Belgium during the first year of the COVID-19 pandemic. METHODS: We retrieved the number of deaths and population data in 2020 based on gender, age, and municipality of residence, and we made a comparison with the mortality data in 2017-2019 using a spatially discrete model. RESULTS: Excess mortality was significantly associated with age, gender, and COVID-19 incidence, with larger effects in the second half of 2020. Most municipalities had higher risks of mortality with a number of exceptions in the northeastern part of Belgium. Some discrepancies in excess mortality were observed between the north and south regions. CONCLUSIONS: This study offers useful insight into excess mortality and will aid local and regional authorities in monitoring mortality trends.


Assuntos
COVID-19 , Mortalidade , Pandemias , SARS-CoV-2 , Análise Espaço-Temporal , Humanos , Bélgica/epidemiologia , COVID-19/mortalidade , COVID-19/epidemiologia , Masculino , Feminino , Pessoa de Meia-Idade , Idoso , Adulto , Mortalidade/tendências , Adolescente , Lactente , Pré-Escolar , Criança , Adulto Jovem , Idoso de 80 Anos ou mais , Recém-Nascido , Incidência , Análise Espacial
10.
Spat Spatiotemporal Epidemiol ; 49: 100649, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38876562

RESUMO

The incidence of low birthweight is a common measure of public health due to the increased risk of complications associated with infants having low and very low birthweights. Moreover, many factors that increase the risk of an infant having a low birthweight can be linked to the mother's socioeconomic status, leading to large racial/ethnic disparities in its incidence. Our objective is thus to analyze the incidence of low and very low birthweight in Pennsylvania counties by race/ethnicity. Due to the small number of births in many Pennsylvania counties when stratified by race/ethnicity, our methods must walk a fine line: While we wish to leverage spatial structure to improve the precision of our estimates, we also wish to avoid oversmoothing the data, which can yield spurious conclusions. As such, we develop a framework by which we can measure (and control) the informativeness of our spatial model. To analyze the data, we first model the Pennsylvania birth data using the conditional autoregressive model to demonstrate the extent to which it can lead to oversmoothing. We then reanalyze the data using our proposed framework and highlight its ability to detect (or not detect) evidence of racial/ethnic disparities in the incidence of low birthweight.


Assuntos
Recém-Nascido de Baixo Peso , Análise Espacial , Humanos , Pennsylvania/epidemiologia , Incidência , Recém-Nascido , Feminino , Disparidades nos Níveis de Saúde , Masculino , Grupos Raciais/estatística & dados numéricos , Etnicidade/estatística & dados numéricos
11.
Spat Spatiotemporal Epidemiol ; 49: 100656, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38876567

RESUMO

Disparities in care access for health conditions where physiotherapy can play a major role are abetting health inequities. Spatial analyses can contribute to illuminating inequities in health yet the geographic accessibility to physiotherapy care across New Zealand has not been examined. This population-based study evaluated the accessibility of the New Zealand physiotherapy workforce relative to the population at a local scale. The locations of 5,582 physiotherapists were geocoded and integrated with 2018 Census data to generate 'accessibility scores' for each Statistical Area 2 using the newer 3-step floating catchment area method. For examining the spatial distribution and mapping, accessibility scores were categorized into seven levels, centered around 0.5 SD above and below the mean. New Zealand has an above-average physiotherapy-to-population ratio compared with other OECD countries; however, this workforce is maldistributed. This study identified areas (and locations) where geographic accessibility to physiotherapy care is relatively low.


Assuntos
Acessibilidade aos Serviços de Saúde , Modalidades de Fisioterapia , Nova Zelândia , Acessibilidade aos Serviços de Saúde/estatística & dados numéricos , Humanos , Modalidades de Fisioterapia/estatística & dados numéricos , Masculino , Feminino , Análise Espacial , Disparidades em Assistência à Saúde/estatística & dados numéricos
12.
Spat Spatiotemporal Epidemiol ; 49: 100652, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38876565

RESUMO

Racialized economic segregation, a key metric that simultaneously accounts for spatial, social and income polarization in communities, has been linked to adverse health outcomes, including morbidity and mortality. Due to the spatial nature of this metric, the association between health outcomes and racialized economic segregation could also change with space. Most studies assessing the relationship between racialized economic segregation and health outcomes have always treated racialized economic segregation as a fixed effect and ignored the spatial nature of it. This paper proposes a two-stage Bayesian statistical framework that provides a broad, flexible approach to studying the spatially varying association between premature mortality and racialized economic segregation while accounting for neighborhood-level latent health factors across US counties. The two-stage framework reduces the dimensionality of spatially correlated data and highlights the importance of accounting for spatial autocorrelation in racialized economic segregation measures, in health equity focused settings.


Assuntos
Teorema de Bayes , Mortalidade Prematura , Segregação Social , Humanos , Estados Unidos/epidemiologia , Análise Espacial , Masculino , Feminino , Características de Residência/estatística & dados numéricos
13.
Spat Spatiotemporal Epidemiol ; 49: 100655, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38876566

RESUMO

Nigeria grapples with a formidable public health concern, as approximately 14 million individuals partake in illicit drug use (IDU). This predicament significantly impacts psychiatric disorders, suicides, disability, and mortality rates. Despite previous investigations into predictors and remedies, the role of financial inclusion (FI) remains inadequately explored. Leveraging existing literature on FI and population health, this study asserts that bolstering FI could be instrumental in mitigating IDU prevalence in Nigeria. We employ spatial analysis to scrutinize the influence of FI and other social factors on IDU, revealing a 14.4 % national prevalence with spatial variations ranging from 7 % in Jigawa state to 33 % in Lagos state. Significant IDU hotspots were identified in the southwest states, while cold spots were observed in the Federal Capital Territory and Nassarawa. Multivariate spatial analysis indicates that FI, income, unemployment, and the proportion of the young population are pivotal predictors of IDU nationwide, explaining approximately 67 % of the spatial variance. Given these findings, the study advocates heightened levels of FI and underscores the need for intensified government initiatives to prevent and address illicit drug use.


Assuntos
Drogas Ilícitas , Transtornos Relacionados ao Uso de Substâncias , Nigéria/epidemiologia , Humanos , Transtornos Relacionados ao Uso de Substâncias/epidemiologia , Masculino , Feminino , Adulto , Drogas Ilícitas/economia , Prevalência , Fatores Socioeconômicos , Análise Espacial , Adulto Jovem , Adolescente , Pessoa de Meia-Idade
14.
Front Public Health ; 12: 1344089, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38864011

RESUMO

Background: Despite the Ethiopian government included the Pneumococcal Conjugate Vaccine (PCV) in the national expanded program for immunization in 2011, only 56% of children aged 12-23 months received the full dose of PCV. Despite some studies on PCV uptake in Ethiopia, there was a dearth of information on the geographical distribution and multilevel factors of incomplete PCV uptake. Hence, this study aimed to identify the spatial variations and predictors of incomplete PCV uptake among children aged 12-35 months in Ethiopia. Methods: The study was based on an in-depth analysis of 2016 Ethiopia Demographic Health Survey data, using a weighted sample of 3,340 women having children aged 12-35 months. Arc-GIS version 10.7 and SaTScan version 9.6 statistical software were used for the spatial analysis. To explore spatial variation and locate spatial clusters of incomplete PCV, the Global Moran's I statistic and Bernoulli-based spatial scan (SaTScan) analysis were carried out, respectively. A multilevel mixed-effect multivariable logistic regression was done by STATA version 16. Adjusted odds ratio (AOR) with its corresponding 95% CI was used as a measure of association, and variables with a p < 0.05 were deemed as significant determinants of incomplete PCV. Results: The overall prevalence of incomplete PCV in Ethiopia was found to be 54.0% (95% CI: 52.31, 55.69), with significant spatial variation across regions (Moran's I = 0.509, p < 0.001) and nine most likely significant SaTScan clusters. The vast majority of Somali, southeast Afar, and eastern Gambela regions were statistically significant hot spots for incomplete PCV. Lacking ANC visits (AOR = 2.76, 95% CI: 1.91, 4.00), not getting pre-birth Tetanus injections (AOR = 1.84, 95% CI: 1.29, 2.74), home birth (AOR = 1.72, 95% CI: 1.23, 2.34), not having a mobile phone (AOR = 1.64, 95% CI: 1.38, 1.93), and residing in a peripheral region (AOR = 4.63; 95% CI: 2.34, 9.15) were identified as statistically significant predictors of incomplete PCV. Conclusion: The level of incomplete PCV uptake was found to be high in Ethiopia with a significant spatial variation across regions. Hence, the federal and regional governments should collaborate with NGOs to improve vaccination coverage and design strategies to trace those children with incomplete PCV in peripheral regions. Policymakers and maternal and child health program planners should work together to boost access to maternal health services like antenatal care and skilled delivery services to increase immunization coverage.


Assuntos
Análise Multinível , Vacinas Pneumocócicas , Análise Espacial , Vacinas Conjugadas , Humanos , Etiópia , Lactente , Feminino , Vacinas Pneumocócicas/administração & dosagem , Pré-Escolar , Vacinas Conjugadas/administração & dosagem , Masculino , Infecções Pneumocócicas/prevenção & controle , Adulto , Vacinação/estatística & dados numéricos , Cobertura Vacinal/estatística & dados numéricos , Inquéritos Epidemiológicos
15.
Front Public Health ; 12: 1351849, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38864022

RESUMO

Background: Healthcare resources are necessary for individuals to maintain their health. The Chinese government has implemented policies to optimize the allocation of healthcare resources and achieve the goal of equality in healthcare for the Chinese people since the implementation of the new medical reform in 2009. Given that no study has investigated regional differences from the perspective of healthcare resource agglomeration, this study aimed to investigate China's healthcare agglomeration from 2009 to 2017 in China and identify its determinants to provide theoretical evidence for the government to develop and implement scientific and rational healthcare policies. Methods: The study was conducted using 2009-2017 data to analyze health-resource agglomeration on institutions, beds, and workforce in China. An agglomeration index was applied to evaluate the degree of regional differences in healthcare resource allocation, and spatial econometric models were constructed to identify determinants of the spatial agglomeration of healthcare resources. Results: From 2009 to 2017, all the agglomeration indexes of healthcare exhibited a downward trend except for the number of institutions in China. Population density (PD), government health expenditures (GHE), urban resident's disposable income (URDI), geographical location (GL), and urbanization level (UL) all had positive significant effects on the agglomeration of beds, whereas both per capita health expenditures (PCHE), number of college students (NCS), and maternal mortality rate (MMR) had significant negative effects on the agglomeration of institutions, beds, and the workforce. In addition, population density (PD) and per capita gross domestic product (PCGDP) in one province had negative spatial spillover effects on the agglomeration of beds and the workforce in neighboring provinces. However, MMR had a positive spatial spillover effect on the agglomeration of beds and the workforce in those regions. Conclusion: The agglomeration of healthcare resources was observed to remain at an ideal level in China from 2009 to 2017. According to the significant determinants, some corresponding targeted measures for the Chinese government and other developing countries should be fully developed to balance regional disparities in the agglomeration of healthcare resources across administrative regions.


Assuntos
Recursos em Saúde , China , Humanos , Estudos Longitudinais , Recursos em Saúde/estatística & dados numéricos , Modelos Econométricos , Alocação de Recursos , Gastos em Saúde/estatística & dados numéricos , Análise Espacial
16.
JMIR Public Health Surveill ; 10: e55418, 2024 Jun 12.
Artigo em Inglês | MEDLINE | ID: mdl-38865169

RESUMO

A study on infertility in China found that while 543 health care institutions are approved for assisted reproductive technology (ART), only 10.1% offer all ART services, with a significant skew toward the eastern regions, highlighting the accessibility challenges faced by rural and remote populations; this study recommends government measures including travel subsidies and education initiatives to improve ART access for economically disadvantaged individuals.


Assuntos
Acessibilidade aos Serviços de Saúde , Técnicas de Reprodução Assistida , China/epidemiologia , Humanos , Técnicas de Reprodução Assistida/estatística & dados numéricos , Acessibilidade aos Serviços de Saúde/estatística & dados numéricos , Disparidades em Assistência à Saúde/estatística & dados numéricos , Análise Espacial , População Rural/estatística & dados numéricos , Feminino
17.
Environ Monit Assess ; 196(7): 603, 2024 Jun 08.
Artigo em Inglês | MEDLINE | ID: mdl-38850374

RESUMO

Ground-level ozone (O3) pollution has emerged as a significant concern impacting air quality in urban agglomerations, primarily driven by meteorological conditions and social-economic factors. However, previous studies have neglected to comprehensively reveal the spatial distribution and driving mechanism of O3 pollution. Based on the O3 monitoring data of 41 cities in the Yangtze River Delta (YRD) from 2014 to 2021, a comprehensive analysis framework of spatial analysis-spatial econometric regression was constructed to reveal the driving mechanism of O3 pollution. The results revealed the following: (1) O3 concentrations in the YRD exhibited a general increasing and then decreasing trend, indicating an improvement in pollution levels. The areas with higher O3 concentration are mainly the cities concentrated in central and southern Jiangsu, Shanghai, and northern Zhejiang. (2) The change of O3 concentration and distribution is the result of various factors. The effect of urbanization on O3 concentrations followed an inverted U-shaped curve, which implies that achieving higher quality urbanization is essential for effectively controlling urban O3 pollution. Traffic conditions and energy consumption have significant direct positive influences on O3 concentrations and spatial spillover effects. The indirect pollution contribution, considering economic weight, accounted for about 35%. Thus, addressing overall regional energy consumption and implementing traffic source regulations are crucial paths for O3 pollution control in the YRD. (3) Meteorological conditions play a certain role in regulating the O3 concentration. Higher wind speed will promote the diffusion of O3 and increase the O3 concentration in the surrounding city. These findings provide valuable insights for designing effective policies to improve air quality and mitigate ozone pollution in urban agglomeration area.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Cidades , Monitoramento Ambiental , Ozônio , Ozônio/análise , China , Poluentes Atmosféricos/análise , Poluição do Ar/estatística & dados numéricos , Rios/química , Urbanização , Análise Espacial
18.
PLoS One ; 19(6): e0298182, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38833434

RESUMO

BACKGROUND: Hospitalizations due to diabetes complications are potentially preventable with effective management of the condition in the outpatient setting. Diabetes-related hospitalization (DRH) rates can provide valuable information about access, utilization, and efficacy of healthcare services. However, little is known about the local geographic distribution of DRH rates in Florida. Therefore, the objectives of this study were to investigate the geographic distribution of DRH rates at the ZIP code tabulation area (ZCTA) level in Florida, identify significant local clusters of high hospitalization rates, and describe characteristics of ZCTAs within the observed spatial clusters. METHODS: Hospital discharge data from 2016 to 2019 were obtained from the Florida Agency for Health Care Administration through a Data Use Agreement with the Florida Department of Health. Raw and spatial empirical Bayes smoothed DRH rates were computed at the ZCTA level. High-rate DRH clusters were identified using Tango's flexible spatial scan statistic. Choropleth maps were used to display smoothed DRH rates and significant high-rate spatial clusters. Demographic, socioeconomic, and healthcare-related characteristics of cluster and non-cluster ZCTAs were compared using the Wilcoxon rank sum test for continuous variables and Chi-square test for categorical variables. RESULTS: There was a total of 554,133 diabetes-related hospitalizations during the study period. The statewide DRH rate was 8.5 per 1,000 person-years, but smoothed rates at the ZCTA level ranged from 0 to 101.9. A total of 24 significant high-rate spatial clusters were identified. High-rate clusters had a higher percentage of rural ZCTAs (60.9%) than non-cluster ZCTAs (41.8%). The median percent of non-Hispanic Black residents was significantly (p < 0.0001) higher in cluster ZCTAs than in non-cluster ZCTAs. Populations of cluster ZCTAs also had significantly (p < 0.0001) lower median income and educational attainment, and higher levels of unemployment and poverty compared to the rest of the state. In addition, median percent of the population with health insurance coverage and number of primary care physicians per capita were significantly (p < 0.0001) lower in cluster ZCTAs than in non-cluster ZCTAs. CONCLUSIONS: This study identified geographic disparities of DRH rates at the ZCTA level in Florida. The identification of high-rate DRH clusters provides useful information to guide resource allocation such that communities with the highest burdens are prioritized to reduce the observed disparities. Future research will investigate determinants of hospitalization rates to inform public health planning, resource allocation and interventions.


Assuntos
Diabetes Mellitus , Hospitalização , Humanos , Florida/epidemiologia , Hospitalização/estatística & dados numéricos , Masculino , Feminino , Pessoa de Meia-Idade , Adulto , Diabetes Mellitus/epidemiologia , Diabetes Mellitus/terapia , Idoso , Adolescente , Disparidades em Assistência à Saúde/estatística & dados numéricos , Adulto Jovem , Teorema de Bayes , Análise Espacial , Complicações do Diabetes/epidemiologia , Pré-Escolar , Criança , Fatores Socioeconômicos , Lactente
19.
PLoS One ; 19(6): e0304982, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38833494

RESUMO

BACKGROUND: Although the dissemination of health information is one of the pillars of HIV prevention efforts in Ethiopia, a large segment of women in the country still lack adequate HIV/AIDS knowledge, attitude, and behaviours. Despite many studies being conducted in Ethiopia, they mostly focus on the level of women's knowledge about HIV/AIDS, failing to examine composite index of knowledge, attitude, and behaviour (KAB) domains comprehensively. In addition, the previous studies overlooked individual and community-level, and spatial predictors. Hence, this study aimed to estimate the prevalence, geographical variation (Hotspots), spatial predictors, and multilevel correlates of inadequate HIV/AIDS-Knowledge, Attitude, and Behaviour (HIV/AIDS-KAB) among Ethiopian women. METHODS: The study conducted using the 2016 Ethiopian Demographic and Health Survey data, included 12,672 women of reproductive age group (15-49 years). A stratified, two-stage cluster sampling technique was used; a random selection of enumeration areas (clusters) followed by selecting households per cluster. Composite index of HIV/AIDS-KAB was assessed using 11 items encompassing HIV/AIDS prevention, transmission, and misconceptions. Spatial analysis was carried out using Arc-GIS version 10.7 and SaTScan version 9.6 statistical software. Spatial autocorrelation (Moran's I) was used to determine the non-randomness of the spatial variation in inadequate knowledge about HIV/AIDS. Multilevel multivariable logistic regression was performed, with the measure of association reported using adjusted odds ratio (AOR) with its corresponding 95% CI. RESULTS: The prevalence of inadequate HIV/AIDS-KAB among Ethiopian women was 48.9% (95% CI: 48.1, 49.8), with significant spatial variations across regions (global Moran's I = 0.64, p<0.001). Ten most likely significant SaTScan clusters were identified with a high proportion of women with inadequate KAB. Somali and most parts of Afar regions were identified as hot spots for women with inadequate HIV/AIDS-KAB. Higher odds of inadequate HIV/AIDS-KAB was observed among women living in the poorest wealth quintile (AOR = 1.63; 95% CI: 1.21, 2.18), rural residents (AOR = 1.62; 95% CI: 1.18, 2.22), having no formal education (AOR = 2.66; 95% CI: 2.04, 3.48), non-autonomous (AOR = 1.71; 95% CI: (1.43, 2.28), never listen to radio (AOR = 1.56; 95% CI: (1.02, 2.39), never watched television (AOR = 1.50; 95% CI: 1.17, 1.92), not having a mobile phone (AOR = 1.45; 95% CI: 1.27, 1.88), and not visiting health facilities (AOR = 1.46; 95% CI: 1.28, 1.72). CONCLUSION: The level of inadequate HIV/AIDS-KAB in Ethiopia was high, with significant spatial variation across regions, and Somali, and Afar regions contributed much to this high prevalence. Thus, the government should work on integrating HIV/AIDS education and prevention efforts with existing reproductive health services, regular monitoring and evaluation, and collaboration and partnership to tackle this gap. Stakeholders in the health sector should strengthen their efforts to provide tailored health education, and information campaigns with an emphasis on women who lack formal education, live in rural areas, and poorest wealth quintile should be key measures to enhancing knowledge. enhanced effort is needed to increase women's autonomy to empower women to access HIV/AIDS information. The media agencies could prioritise the dissemination of culturally sensitive HIV/AIDS information to women of reproductive age. The identified hot spots with relatively poor knowledge of HIV/AIDS should be targeted during resource allocation and interventions.


Assuntos
Infecções por HIV , Conhecimentos, Atitudes e Prática em Saúde , Humanos , Feminino , Etiópia/epidemiologia , Adulto , Adolescente , Pessoa de Meia-Idade , Infecções por HIV/epidemiologia , Infecções por HIV/prevenção & controle , Adulto Jovem , Inquéritos Epidemiológicos , Análise Multinível , Fatores Socioeconômicos , Síndrome da Imunodeficiência Adquirida/epidemiologia , Síndrome da Imunodeficiência Adquirida/prevenção & controle , Análise Espacial , Prevalência
20.
J Environ Manage ; 362: 121259, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38830281

RESUMO

Machine learning methodology has recently been considered a smart and reliable way to monitor water quality parameters in aquatic environments like reservoirs and lakes. This study employs both individual and hybrid-based techniques to boost the accuracy of dissolved oxygen (DO) and chlorophyll-a (Chl-a) predictions in the Wadi Dayqah Dam located in Oman. At first, an AAQ-RINKO device (CTD+ sensor) was used to collect water quality parameters from different locations and varying depths in the reservoir. Second, the dataset is segmented into homogeneous clusters based on DO and Chl-a parameters by leveraging an optimized K-means algorithm, facilitating precise estimations. Third, ten sophisticated variational-individual data-driven models, namely generalized regression neural network (GRNN), random forest (RF), gaussian process regression (GPR), decision tree (DT), least-squares boosting (LSB), bayesian ridge (BR), support vector regression (SVR), K-nearest neighbors (KNN), multilayer perceptron (MLP), and group method of data handling (GMDH) are employed to estimate DO and Chl-a concentrations. Fourth, to improve prediction accuracy, bayesian model averaging (BMA), entropy weighted (EW), and a new enhanced clustering-based hybrid technique called Entropy-ORNESS are employed to combine model outputs. The Entropy-ORNESS method incorporates a Genetic Algorithm (GA) to determine optimal weights and then combine them with EW weights. Finally, the inclusion of bootstrapping techniques introduces a stochastic assessment of model uncertainty, resulting in a robust estimator model. In the validation phase, the Entropy-ORNESS technique outperforms the independent models among the three fusion-based methods, yielding R2 values of 0.92 and 0.89 for DO and Chl-a clusters, respectively. The proposed hybrid-based methodology demonstrates reduced uncertainty compared to single data-driven models and two combination frameworks, with uncertainty levels of 0.24% and 1.16% for cluster 1 of DO and cluster 2 of Chl-a parameters. As a highlight point, the spatial analysis of DO and Chl-a concentrations exhibit similar pattern variations across varying depths of the dam according to the comparison of field measurements with the best hybrid technique, in which DO concentration values notably decrease during warmer seasons. These findings collectively underscore the potential of the upgraded weighted-based hybrid approach to provide more accurate estimations of DO and Chl-a concentrations in dynamic aquatic environments.


Assuntos
Qualidade da Água , Incerteza , Algoritmos , Análise Espacial , Teorema de Bayes , Análise por Conglomerados , Monitoramento Ambiental/métodos , Redes Neurais de Computação , Aprendizado de Máquina , Clorofila A/análise
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