Incorporating Spatial Statistics into Examining Equity in Health Workforce Distribution: An Empirical Analysis in the Chinese Context.
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ABSTRACT:
SUBMITTER: Zhu B
PROVIDER: S-EPMC6068954 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe maldistributions of the health workforce showed great inconsistency when singly measured by population quantity or geographic area in China. Meanwhile, earlier studies mainly employed traditional econometric approaches to investigate determinants for the health workforce, which ignored spillover effects of influential factors on neighboring regions. Therefore, we aimed to analyze health workforce allocation in China from demographic and geographic perspectives simultaneously and then explore the spatial pattern and determinants for health workforce allocation taking account of the spillover effect.MethodsThe health resource density index (HRDI) equals the geometric mean of health resources per 1,000 persons and per square kilometer. First, the HRDI of licensed physicians (HRDI_P) and registered nurses (HRDI_N) was calculated for descriptive analysis. Then, global and local Moran's I indices were employed to explore the spatial features and aggregation clusters of the health workforce. Finally, four types of independent variables were selected: supportive resources (bed density and government health expenditure), healthcare need (proportion of the elderly population), socioeconomic factors (urbanization rate and GDP per capita), and sociocultural factors (education expenditure per pupil and park green area per capita), and then the spatial panel econometric model was used to assess direct associations and intra-region spillover effects between independent variables and HRDI_P and HRDI_N.ResultsGlobal Moran's I index of HRDI_P and HRDI_N increased from 0.2136 (P = 0.0070) to 0.2316 (P = 0.0050), and from 0.1645 (P = 0.0120) to 0.2022 (P = 0.0080), respectively. Local Moran's I suggested spatial aggregation clusters of HRDI_P and HRDI_N. For HRDI_P, bed density, government health expenditure, and GDP had significantly positive associations with local HRDI_P, while the proportion of the elderly population and education expenditure showed opposite spillover effects. More precisely, a 1% increase in the proportion of the elderly population would lead to a 0.4098% increase in HRDI_P of neighboring provinces, while a 1% increase in education expenditure leads to a 0.2688% decline in neighboring HRDI_P. For HRDI_N, the urbanization rate, bed density, and government health expenditure exerted significantly positive impacted local HRDI_N. In addition, the spillover effect was more evident in the urbanization rate, with a 1% increase in the urbanization rate relating to 0.9080% growth of HRDI_N of surrounding provinces. Negative spillover effects of education expenditure, government health expenditure, and elderly proportion were observed in neighboring HRDI_N.ConclusionThere were substantial spatial disparities in health workforce distribution in China; moreover, the health workforce showed positive spatial agglomeration with a strengthening tendency in the last decade. In addition, supportive resources, healthcare needs, and socioeconomic and sociocultural factors would affect the health labor configuration not only in a given province but also in its nearby provinces.
| S-EPMC9794860 | biostudies-literature
Project description:Based on the integrated model of Super-SBM model, spatial Durbin model (SDM) and Grey neural network model, this paper analyzes the panel data of various provinces in China from multiple angles and dimensions. It was found that there were significant differences in eco-efficiency between organic rice production and conventional rice production. The response of organic rice to climate change, the spatial distribution of ecological and economic benefits and the impact on carbon emission were analyzed. The results showed that organic rice planting not only had higher economic benefits, but also showed a rising trend of ecological benefits and a positive feedback effect. This finding highlights the importance of organic rice farming in reducing carbon emissions. Organic rice farming effectively reduces greenhouse gas emissions, especially carbon dioxide and methane, by improving soil management and reducing the use of fertilizers and pesticides. This has important implications for mitigating climate change and promoting soil health and biodiversity. With the acceleration of urbanization, the increase of organic rice planting area shows the trend of organic rice gradually replacing traditional rice cultivation, further highlighting the potential of organic agriculture in emission reduction, environmental protection and sustainable agricultural production. To this end, it is recommended that the Government implement a diversified support strategy to encourage technological innovation, provide guidance and training, and raise public awareness and demand for organic products. At the same time, private sector participation is stimulated to support the development of organic rice cultivation through a public-private partnership model. Through these measures, further promote organic rice cultivation, achieve the dual goals of economic benefits and environmental benefits, and effectively promote the realization of double carbon emission reduction targets.
| S-EPMC11008895 | biostudies-literature
Project description: Not available
| S-EPMC10553346 | biostudies-literature
Project description:Spatial conservation prioritization is used worldwide for designing marine protected areas (MPA) that achieve set conservation objectives with minimal impacts to marine users. People involved in small-scale fisheries (SSF) may incur negative and disproportionate impacts from implementing MPAs, yet limited available data often restricts their representation in MPA planning. Using a Philippines case study, we focus here on the systematic design of a MPA network that aims to minimize and distribute costs equitably for SSF whilst achieving representation targets for biodiversity conservation. The objectives of the study are to: (1) document a participatory mapping approach for collecting SSF data for prioritization using the local knowledge of fishers; and (2) examine how the completeness and resolution of SSF data may affect prioritization outputs in terms of biodiversity representation, spatial efficiency, and distribution equity. In the data-poor region, we conducted participatory mapping workshops with fishers in 79 communities to collect data on the spatial distribution patterns of different SSF fisheries and communities, and employed remote sensing techniques to define coastal habitats, which were targeted for inclusion in MPAs. The datasets were integrated within the decision-support tool Marxan with Zones to develop three scenarios. The SSF data incorporated in each scenario varied based on their completeness (considered all fishing methods or only dominant methods) and resolution (fishing methods itemized by community or municipality). All scenarios derived MPA plans that met representation targets with similar area coverage. The outputs, however, varied in terms of distribution equity, measured by the distribution of opportunity costs (loss of fishing grounds) across different fisheries and communities. Scenarios that did not include minority fisheries or variations between communities, led to inequitable costs. These results highlight the need to incorporate detailed data on SSF at appropriate resolutions, and how this can be achieved through participatory approaches.
| S-EPMC7237002 | biostudies-literature
Project description:ObjectivesIn this longitudinal study, we examined changes in the geographical distribution of physicians in Japan from 2000 to 2014 by clinical specialty with adjustments for healthcare demand based on population structure.MethodsThe Japanese population was adjusted for healthcare demand using health expenditure per capita stratified by age and sex. The numbers of physicians per 100 000 demand-adjusted population (DAP) in 2000 and 2014 were calculated for subprefectural regions known as secondary medical areas. Disparities in the geographical distribution of physicians for each specialty were assessed using Gini coefficients. A subgroup analysis was conducted by dividing the regions into four groups according to urban-rural classification and initial physician supply.ResultsOver the study period, the number of physicians per 100 000 DAP decreased in all specialties assessed (internal medicine: -6.9%, surgery: -26.0%, orthopaedics: -2.1%, obstetrics/gynaecology (per female population): -17.5%) except paediatrics (+33.3%) and anaesthesiology (+21.1%). No reductions in geographical disparity were observed in any of the specialties assessed. Geographical disparity increased substantially in internal medicine, surgery and obstetrics and gynaecology(OB/GYN). Rural areas with lower initial physician supply experienced the highest decreases in physicians per 100 000 DAP for all specialties assessed except paediatrics and anaesthesiology. In contrast, urban areas with lower initial physician supply experienced the lowest decreases in physicians per 100 000 DAP in internal medicine, surgery, orthopaedics and OB/GYN, but the highest increase in anaesthesiology.ConclusionBetween 2000 and 2014, the number of physicians per 100 000 DAP in Japan decreased in all specialties assessed except paediatrics and anaesthesiology. There is also a growing urban-rural disparity in physician supply in all specialties assessed except paediatrics. Additional measures may be needed to resolve these issues and improve physician distribution in Japan.
| S-EPMC5781009 | biostudies-literature
Project description:In publicly funded health care systems, decision makers must continually balance often conflicting priorities of efficiency and equity. Health economists have developed a set of highly sophisticated analytical methods for assessing efficiency, but less attention has been paid to formally incorporating equity considerations into analyses. As a result, where equity is considered is often informal, ad hoc and/or simplistic. This paper is a proposal for a mechanism for formally incorporating equity within the decision process. It begins with an overview of the current literature on equity weighting. It then considers the case of a single equity domain and illustrates how this is currently applied in practice by the UK's National Institute for Health and Care Excellence. It then proposes a more comprehensive method for considering the multi-attribute equity state, where a population exhibits more than one trait considered worthy of differential weighting. Finally, the paper proposes a mechanism by which this could be applied in practice, and concludes with a discussion of the challenges for applying multi-attribute equity weighting.
| S-EPMC5913380 | biostudies-literature
Project description:Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community.
| S-EPMC4901350 | biostudies-literature
Project description:ObjectivesTo reveal the equity of health workforce distribution in urban community health service (CHS), and to provide evidence for further development of community health service in China.MethodsA community-based, cross-sectional study was conducted in China from September to December 2011. In the study, 190 CHS centers were selected from 10 provinces of China via stratified multistage cluster sampling. Human resources profiles and basic characteristics of each CHS centers were collected. Lorenz curves and Gini Coefficient were used to measure the inequality in the distribution of health workforce in community health service centers by population size and geographical area. Wilcoxon rank test for paired samples was used to analyze the differences in equity between different health indicators.ResultsOn average, there were 7.37 health workers, including 3.25 doctors and 2.32 nurses per 10,000 population ratio. Significant differences were found in all indicators across the samples, while Beijing, Shandong and Zhejiang ranked the highest among these provinces. The Gini coefficients for health workers, doctors and nurses per 10,000 population ratio were 0.39, 0.44, and 0.48, respectively. The equity of doctors per 10,000 population ratio (G = 0.39) was better than that of doctors per square kilometer (G = 0.44) (P = 0.005). Among the total 6,573 health workers, 1,755(26.7%) had undergraduate degree or above, 2,722(41.4%)had junior college degree and 215(3.3%) had high school education. Significant inequity was found in the distribution of workers with undergraduate degree or above (G = 0.52), which was worse than that of health works per 10000 population (P<0.001).ConclusionsHealth workforce inequity was found in this study, especially in quality and geographic distribution. These findings suggest a need for more innovative policies to improve health equity in Chinese urban CHS centers.
| S-EPMC4281229 | biostudies-literature
Project description:ObjectiveDetermine the geographic and per capita distribution of otology-neurotology physician-surgeons within the United States.Study designNational database review.SettingUnited States.MethodsThe American Neurotology Society and ENThealth.org membership databases were queried to identify otology-neurotology physician-surgeons within the United States. Physician-surgeons were divided by regional national census areas, state, and by largest population statistical area based on 2019 US Census population estimates. The number of otology-neurotology physician-surgeons per 1 million persons was calculated for each population designation.ResultsFour-hundred eighty-two physician-surgeons were identified, representing 49 states and the District of Columbia. The New England division (Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island) was the most concentrated region (1.89), whereas the West-South-Central (Texas, Oklahoma, Arkansas, Louisiana) was the least concentrated region (1.23) per million persons. The highest concentration of physician-surgeons by state is within the District of Columbia (4.25), Vermont (3.21), North Dakota (2.62), Massachusetts (2.61), and New York (2.21) (per million), whereas Mississippi (0.67), Georgia (0.66), Idaho (0.56), New Mexico (0.48), and Wyoming (0.0) were the least concentrated per million persons. Increasing number of physician-surgeons was significantly correlated by state (r2 = 0.9; P < 0.0001), largest statistical area (r2 = 0.88; P < 0.0001), and census region (r2 = 0.95; P < 0.0005).ConclusionsOtology-neurotology physician-surgeons are evenly distributed across the United States; however, certain areas are likely underrepresented. Variability in clinical practice may account for under or overrepresentation not captured in this analysis.
| S-EPMC10969502 | biostudies-literature
Project description:ObjectivesTo comprehend the relationship between various indicators of health service equity and patients' health expenditure poverty in different regions of China, identify areas where equity in health service is lacking and provide ideas for improving patients' health expenditure poverty.MethodData from China Family Panel Studies (CFPS) in 2018 and the HFGT index formula were used to calculate the health expenditure poverty index of each province. Moreover, Global Moran's I and Local Moran's I test are applied to measure whether there is spatial aggregation of health expenditure poverty. Finally, an elastic net regression model is established to analyze the impact of health service equity on health expenditure poverty, with the breadth of health expenditure poverty as the dependent variable and health service equity as the independent variable.ResultsIn the developed eastern provinces of China, the breadth of health expenditure poverty is relatively low. There is a significant positive spatial agglomeration. "Primary medical and health institutions per 1,000 population", "rural doctors and health workers per 1,000 population", "beds in primary medical institutions per 1,000 population", "proportion of government health expenditure" and "number of times to participate in medical insurance (be aided) per 1,000 population" have a positive impact on health expenditure poverty. "Number of health examinations per capita" and "total health expenditure per capita" have a negative impact on health expenditure poverty. Both effects passed the significance test.ConclusionTo enhance the fairness of health resource allocation in China and to alleviate health expenditure poverty, China should rationally plan the allocation of health resources at the grassroots level, strengthen the implementation of hierarchical diagnosis and treatment and encourage the investment in business medical insurance industry. Meanwhile, it is necessary to increase the intensity of medical assistance and enrich financing methods. All medical expenses of the poorest should be covered by the government.
| S-EPMC8293547 | biostudies-literature