Human resource allocation status and equity research of Centers for Disease Control and Prevention in China from 2016 to 2020.

Background: In recent years, the development of global public health has become a matter of great concern and importance for governments worldwide. China, as the largest developing country, plays a crucial role in shaping the development of the public health and its ability to respond to sudden public health emergencies through the fairness of its human resource allocation in center for disease control and prevention (CDC). Objective: This study aims to analyze the situation of health human resource allocation in the China Centers for Disease Control and Prevention (China CDCs), assess the fairness of the allocation, and provide reference for the rational allocation of human resources. Methods: We selected data from the China Health Statistics Yearbook on healthcare technical personnel, other technical personnel, managerial personnel, and workforce technical personnel of China CDCs for the period of 2016-2020. We utilized the Health Resource Density Index to evaluate the level of human resource allocation in China CDCs. Additionally, we used the Gini coefficient and Theil index to assess the fairness of human resource allocation in China CDCs from both a population and geographical perspective. Results: Firstly, the educational qualifications and professional titles of CDC staff have improved, but the workforce is aging. Secondly, HRDI development trends vary among different personnel types and regions with varying levels of economic development. Finally, the results of the Gini coefficient and Theil index indicate that population distribution fairness is better than geographical distribution fairness. Overall, the unfair population distribution is primarily due to regional disparities. Conclusion: The China CDCs should tailor different standards for the allocation of health human resources based on regional characteristics, aiming to enhance the accessibility of health human resources in various regions and achieve equitable allocation.

Are spatial imbalances in industrial structural change widening the common wealth gap?

The evolution of China's industrial structure from 2010 to 2021 is assessed based on the rationalization and sophistication of its industries. The Theil index quantifies spatial variability, while the Quadratic Assignment Procedure (QAP) investigates if changes in industrial structure imbalance will increase wealth disparity. The study's findings indicate a noticeable spatial imbalance in industrial structure change. The overall level of common wealth is low but steadily increasing, following a stepped-down structure of "east-center-west." Additionally, the north and south regions exhibit a pattern of "high in the north and low in the south." There is a pattern of higher values in the north and lower values in the south. In terms of common wealth and its dimensions, there is a ladder-like pattern with high values at the core decreasing towards the west. Between 2010 and 2021, the common wealth development shifted from a lower level to a higher one. Beijing, Jiangsu, and Shanghai constantly ranked in the top echelon, while Guangxi remained in the fifth echelon. The speed and difficulty of transitioning between echelons vary. Moving from the fourth echelon to the third echelon takes longer, while transitioning from the third echelon to higher echelons presents tougher challenges. Spatial imbalances in industrial structure changes widen the gap in common wealth. In particular, the impact of the gap in the advanced industrial structure on the common wealth gap is significantly higher than that of the gap in industrial rationalization. Reducing disparities in advanced industrial structure is more effective in reducing the overall wealth gap.

Trend and Equity in Maternal and Child Health Resource Allocation in China Since the New Health System Reform: A Nationwide Study from 2008 to 2020.

Purpose: China has made considerable efforts to promote the development of maternal and child health (MCH) care since the new health system reform in 2009. This study aims to evaluate the trend and equity of MCH resources allocation in China from 2008 to 2020 and provide a reference for rational distribution of MCH resources. Methods: Data were collected from the China Health Statistics Yearbook and China Statistics Yearbook. The number of MCH hospitals, licensed (assistant) physicians, registered nurses and beds were selected for the measurement of the equity of MCH resources allocation. The Health Resource Agglomeration Degree and Theil index were used in evaluating MCH resource allocation equity and to compare differences among regions. Results: From 2008 to 2020, the average annual growth rates for MCH hospitals, beds, licensed (assistant) physicians, and registered nurses were 0.72%, 6.95%, 5.04%, and 9.57%, respectively. However, regional disparities in the equity of MCH resource allocation have been identified. Although the western region has shown growth in MCH resource allocation by geography, the agglomeration degree of the four indicators remains less than 1, significantly lower than the average value of greater than 2 in the eastern region. Additionally, the equity of human resource allocation in the western region is lower than the equity in the allocation of institutions. In the densely populated eastern region, the equity of MCH resource allocation by population is decreasing, with the agglomeration degree of all four indicators below 1 in 2020. The disparity in healthcare resource allocation within regions is the main cause of inequitable MCH resource allocation in China. Conclusion: The allocation of MCH resources in China has improved since 2009, however, geographic equity needs further improvement, particularly in densely populated regions. Population and geographic balances should be considered in the development and implementation of MCH resource allocation policies, and improving intraregional equity should be the focus.

A spatiotemporal analysis of personal casualty accidents in China's electric power industry.

The electric power industry in China has experienced significant growth in recent years. Despite efforts to improve safety management in the industry, accidents still occur frequently. This study aimed to analyze the personal casualty accidents in the electric power industry from 2012 to 2021. Specific methods used include descriptive analysis, principal component analysis, and Theil index model. The results indicated that fall, electric shock, and collapse were the primary types of accidents, accounting for 59.65 % of all accidents. Accidents were higher in April and August, but lower in February. While the accident rate was relatively low on Mondays, the fatality rate was higher on Mondays, Thursdays, and Fridays. Taking into account accidents, workload, and labor, we found that Ningxia, Hainan, and Guangxi exhibited subpar levels of safety management within the electric power industry. The overall difference in the number of deaths in 31 provinces was significant in 2012 and 2016. It was significantly reduced in 2021. In terms of the proportion of intraregional and interregional differences, there were significant differences in the number of accidents and fatalities between provinces in the Central China and North China regions. This study provides valuable insights for enterprises to formulate accident prevention strategies and for the government to develop relevant policies.

Equality of healthcare resource allocation between impoverished counties and non-impoverished counties in Northwest China: a longitudinal study.

BACKGROUND: The Health and Medical Assistance Program for Poverty Alleviation is part of China's targeted poverty elimination strategy, which aims to protect poor people's right to health and prevent them from becoming trapped in or returning to poverty because of illness. Many tasks have been defined in this program, including raising the medical insurance level, providing a triage system, improving medical and health services, and enhancing people's health. One pivotal aspect of this initiative involves equitable health resource allocation, a key measure aimed at bolstering medical and health services. This study aimed to analyze and compare health resource allocations in different counties in Northwest China after the implementation of the program. METHODS: The Gini coefficient quantifies the level of distributional equality, the Theil index assesses the sources of inequality, and the Health Resource Agglomeration Degree gauges the accessibility of health resources. RESULTS: 1) The health resource allocation distributed based on population(Gini Coefficient < 0.45) was more equitable than that distributed based on area(Gini Coefficient > 0.35) among counties in Northwest China. 2) The contribution rate within non-impoverished counties is higher than that of impoverished counties, which means the inequality within non-impoverished counties. 3) The allocation of beds in medical institutions by area in non-impoverished counties was better than that in impoverished counties, and accessibility to health services for residents in non-impoverished counties was better than that in impoverished counties. CONCLUSION: The analysis of health resource allocation among the five provinces in Northwest China revealed significant differences in equality among the five provinces in Northwest China, and the differences were mainly derived from the non-impoverished counties. Although the equality is gradually improving, the number of health resources in impoverished counties remain lower than that in non-impoverished counties.Subsequently, it is essential to ensure equitable distribution of healthcare resources while also taking into account their utilization and quality.

Ethnic disparities and temporal trends in health resource allocation: a retrospective decadal analysis in Sichuan, a multi-ethnic Province of Southwest China (2009-2019).

BACKGROUND: Research on health resource allocation trends in ethnic minority and impoverished areas in China is limited since the 2009 Medical Reform. This study aimed to investigate the variations and inequalities in health resource distribution among ethnic minority, poverty-stricken, and non-minority regions in Sichuan Province, a multi-ethnic province in Southwest China, from 2009 to 2019. METHODS: The numbers of beds, doctors and nurses were retrospectively sourced from the Sichuan Health Statistics Yearbook between 2009 and 2019. All the 181 counties in Sichuan Province were categorized into five groups: Yi, Zang, other ethnic minority, poverty-stricken, and non-minority county. The Theil index, adjusted for population size, was used to evaluate health resource allocation inequalities. RESULTS: From 2009 to 2019, the number of beds (Bedp1000), doctors (Docp1000), and nurses (Nurp1000) per 1000 individuals in ethnic minority and poverty-stricken counties consistently remained lower than non-minority counties. The growth rates of Bedp1000 in Yi (140%) and other ethnic minority counties (127%) were higher than in non-minority counties (121%), while the growth rates of Docp1000 in Yi (20%) and Zang (11%) counties were lower than non-minority counties (61%). Docp1000 in 33% and 50% of Yi and Zang ethnic counties decreased, respectively. Nurp1000 in Yi (240%) and other ethnic minority (316%) counties increased faster than non-minority counties (198%). The Theil index for beds and nurses declined, while the index for doctors increased. Key factors driving increases in bed allocation include preferential policies and economic development levels, while health practitioner income, economic development levels and geographical environment significantly influence doctor and nurse allocation. CONCLUSIONS: Preferential policies have been successful in increasing the number of beds in health facilities, but not healthcare workers, in ethnic minority regions. The ethnic disparities in doctor allocation increased in Sichuan Province. To increase the number of doctors and nurses in ethnic minority and poverty-stricken regions, particularly in Yi counties, more preferential policies and resources should be introduced.

The impact of regional policy implementation on the decoupling of carbon emissions and economic development.

The contradiction between economic growth demands and the achievement of the "dual-carbon" goals at the regional level is a pressing issue in China. As a significant economic and cultural center in the western region of China, the Guanzhong Plain urban agglomeration has experienced rapid development and urbanization, making it one of the key areas for national development. Therefore, greater attention should be given to carbon emission reduction in this region. This study focuses on the dataset from 2010 to 2019 in the Guanzhong Plain urban agglomeration, utilizing an input-output table to construct a carbon dioxide emission inventory. The research investigates the impact of regional classification on carbon emission levels within the Guanzhong Plain urban agglomeration. Furthermore, the Tapio decoupling analysis method is employed to assess the decoupling coefficient between regional economic development and carbon emissions. Additionally, the Theil index inequality analysis method is utilized to measure the disparities in per capita carbon emissions among cities within the region. Research findings indicate the following: 1) The regional classification of the Guanzhong Plain urban agglomeration is an effective policy for reducing regional carbon emissions and promoting carbon emissions reduction. 2) There exist variations in energy and industrial structures among cities within the urban agglomeration, necessitating tailored measures for low-carbon transition based on the specific circumstances of each city. 3) The regional classification of the urban agglomeration significantly influences the degree of decoupling between economic development and carbon emissions, with a trend towards stronger decoupling. The study suggests that cities within the Guanzhong Plain urban agglomeration should adopt measures aligned with their natural conditions and economic characteristics to achieve a low-carbon transition. Leveraging the regional cooperation capacity of the urban agglomeration is crucial to decouple economic development from carbon emissions, thereby promoting sustainable economic growth and environmental protection in a mutually beneficial manner.

Regional inequality in China's educational development: An urban-rural comparison.

In the past two decades, regional inequality in China's educational development, especially between urban and rural areas, has continued to narrow. An in-depth discussion of this phenomenon and the mechanisms behind it will not only help China build a high-quality educational system, but also draw lessons from Chinese practices to guide the reduction of global educational inequality. The comprehensive evaluation results show that China's rural EDL surpassed urban EDL in 2013; in 2003-2019, the urban/rural EDL increased from 0.29 to 0.22 to 0.50 and 0.54, respectively, and the urban-rural EII decreased from 1.31 to 0.92. Spatially, urban/rural EDL in the eastern and northeastern regions is higher than that in the central and western regions, the urban-rural EII in the eastern and northeastern regions is lower than that in the central and western regions. The CV and Theil index show that regional disparity in national urban/rural EDL has been narrowing, and regional inequality in urban-rural EII has also been declining; the decomposition of the Theil index indicates that these decreases in inequality are mainly from the reduction of the urban/rural educational development gap within the regions. The large-scale population migration driven by rapid industrialization and urbanization, and the adjustment of urban-rural and regional relationship promoted by the transformation of national policies such as regional coordinated development strategy and hukou system reform, are the main reasons for the evolution of regional inequality in China's urban and rural educational development.

Multidimensional analysis of the regional inequalities in indirect carbon emissions from China's residential consumption.

Residential indirect carbon emissions (RICE) are the major contributor to carbon emissions from the household sector. Regional RICE inequality has gradually become the focus of current issues. This paper has accounted for the RICE level of each province in China from 2010 to 2020 and assessed the RICE inequality at different regional scales employing the Theil index. Additionally, this paper presents a comprehensive analysis of RICE inequality across three dimensions: region, consumption category, and driving factors, illustrating the principal sources and determinants of RICE inequality. The results indicate the following: (1) RICE inequality in China is generally on a downward trend. (2) The gap between eastern China and the other regions is the dominant source of RICE inequality. (3) Residence consumption affects RICE inequality far more than other consumption categories. (4) Disposable income and the urban-rural structure of the population are the predominant factors affecting RICE inequality for most regions. The consumption propensity effect has a relatively pronounced impact on RICE inequality in the central and western regions. Based on the analysis, local governments ought to focus on economic construction, promote urbanization, and regulate the housing market to alleviate the RICE inequality.

[Spatial-temporal Evolution of Ecological Vulnerability in Beijing-Tianjin-Hebei Region Based on PSRM Model].

As one of the three major urban agglomerations in China, the Beijing-Tianjin-Hebei Region has strong economic strength but its ecological fragility is very prominent. To pursue the comprehensive development of economy and ecology, it is very important to analyze the ecological environment in the Beijing-Tianjin-Hebei Region. Here, the Beijing-Tianjin-Hebei Region was selected as the research area, and 19 indicators were selected to construct an evolution system based on the PSRM model. The temporal and spatial evolution characteristics of ecological vulnerability in the Beijing-Tianjin-Hebei Region were explored by combining the order relation method, CRITIC method, Theil index, and hot spot analysis, and the influencing factors were calculated via geographic detector. The results showed that:① the ecological vulnerability first increased and then decreased in the Beijing-Tianjin-Hebei Region. The vulnerable areas showed a northeast-southwest trend, and the ecological environment in the northeast and southwest regions was better than that in the central and southern regions. The area of slight vulnerability in 2014 increased by 6803.01 km2 compared with that in 2009. The area of mild vulnerability decreased by 130.41 km2, and the area of moderate vulnerability decreased by 26537.31 km2 compared with that in 2009. The areas of severe and extremely vulnerable status increased by 19512.9 km2 and 351.81 km2, respectively, compared with those in 2009. The habitat situation in the Beijing-Tianjin-Hebei Region improved significantly from 2014 to 2019. Compared with that in 2014, the areas of mild, moderate, severe, and extremely vulnerable decreased by 2248.29 km2, 2220.21 km2, 7988.67 km2, and 55.98 km2, respectively. The light area increased by 12513.15 km2 compared with that in 2014. ② According to the calculation results of the Theil index, the spatial correlation degree of ecological vulnerability in the Beijing-Tianjin-Hebei Region exhibited a V-shaped fluctuation, and the spatial pattern of the cold and hot areas was predominantly consistent with that of the vulnerability. ③ Biological abundance, PM10, and the human disturbance index had a significant influence on the spatial differentiation of ecological vulnerability in the Beijing-Tianjin-Hebei Region. Based on the results of ecological vulnerability analysis, some suggestions on the ecological environment and sustainable development in the Beijing-Tianjin-Hebei Region were proposed.

Inequality Measure of Leaf Area Distribution for a Drought-Tolerant Landscape Plant.

Measuring the inequality of leaf area distribution per plant (ILAD) can provide a useful tool for quantifying the influences of intra- and interspecific competition, foraging behavior of herbivores, and environmental stress on plants' above-ground architectural structures and survival strategies. Despite its importance, there has been limited research on this issue. This paper aims to fill this gap by comparing four inequality indices to measure ILAD, using indices for quantifying household income that are commonly used in economics, including the Gini index (which is based on the Lorenz curve), the coefficient of variation, the Theil index, and the mean log deviation index. We measured the area of all leaves for 240 individual plants of the species Shibataea chinensis Nakai, a drought-tolerant landscape plant found in southern China. A three-parameter performance equation was fitted to observations of the cumulative proportion of leaf area vs. the cumulative proportion of leaves per plant to calculate the Gini index for each individual specimen of S. chinensis. The performance equation was demonstrated to be valid in describing the rotated and right shifted Lorenz curve, given that >96% of root-mean-square error values were smaller than 0.004 for 240 individual plants. By examining the correlation between any of the six possible pairs of indices among the Gini index, the coefficient of variation, the Theil index, and the mean log deviation index, the data show that these indices are closely related and can be used interchangeably to quantify ILAD.

Large but overlooked carbon differentiations inside China's provinces matters to mitigation strategies design: Evidence from county-level analysis.

In China, wide variations exist not only among different provinces, but also inside provinces. Therefore, intensive policy adjustments are essential for promoting carbon neutral in China, which calls for a clear understanding of carbon emission disparities in each individual province. Based on panel data of 2001 county-level administrative areas from 2004 to 2017, we use Theil index and spatial regression models to measure contributions and distributions of intra-provincial carbon inequality, as well as effects of intra-provincial economic inequality on intra-provincial carbon inequality, in order to design provincial specific strategies considering carbon differentiations inside each province. Our main contributions are studying China's carbon inequality from intra- instead of inter-provincial perspectives and exploring spatial connections of carbon inequality, which has not been fully discussed in previous studies. The empirical results indicate that intra- rather than inter- provincial carbon inequality contributes the majority of China's overall carbon inequality. Intra-provincial inequality shows high levels of regional clustering and decrease from west to east, although their differences are smaller in 2017 than 2004, mainly because carbon inequality levels experience large declines in some central and western provinces. Low carbon inequality levels in eastern provinces are mainly attributed to very negative correlation between development levels and carbon intensity. Intra-provincial economic development inequality plays nonnegligible roles in intra-provincial carbon inequality in all provinces, although they are not the major driving factors in some provinces. There also exist positive spatial spillover effects of intra-provincial economic inequality on intra-provincial carbon inequality. We provide specific policy suggestions on key areas of carbon emission reductions and demand degree of economic transitions for each individual province and also evaluate effects of "common prosperity" measures, which have been frequently discussed recently, on intra-provincial carbon distributions.

Spatiotemporal evolution and characteristics of worldwide life expectancy.

Exploring global differences in life expectancy can facilitate the development of strategies to narrow regional disparities. However, few researchers have systematically examined patterns in the evolution of worldwide life expectancy over a long time period. Spatial differences among 181 countries in 4 types of worldwide life expectancy patterns from 1990 to 2019 were investigated via geographic information system (GIS) analysis. The aggregation characteristics of the spatiotemporal evolution of life expectancy were revealed by local indicators of spatial association. The analysis employed spatiotemporal sequence-based kernel density estimation and explored the differences in life expectancy among regions with the Theil index. We found that the global life expectancy progress rate shows upward then downward patterns over the last 30 years. Female have higher rates of spatiotemporal progression in life expectancy than male, with less internal variation and a wider spatial aggregation. The global spatial and temporal autocorrelation of life expectancy shows a weakening trend. The difference in life expectancy between male and female is reflected in both intrinsic causes of biological differences and extrinsic causes such as environment and lifestyle habits. Investment in education pulls apart differences in life expectancy over long time series. These results provide scientific guidelines for obtaining the highest possible level of health in countries around the world.

Measuring the inequalities in healthcare resource in facility and workforce: A longitudinal study in China.

Objective: The study aimed to measure time trends of inequalities of the geographical distribution of health facilities and workforce in Shanghai from 2010 to 2016 and used a spatial autocorrelation analysis method to precisely detect the priority areas for optimizing health resource reallocation in metropolises like Shanghai in developing countries. Methods: The study used secondary data from the Shanghai Health Statistical Yearbook and the Shanghai Statistical Yearbook from 2011 to 2017. Five indicators on health resources, namely, health institutions, beds, technicians, doctors, and nurses, were employed to quantitatively measure the healthcare resource in Shanghai. The Theil index and the Gini coefficient were applied to assess the global inequalities in the geographic distribution of these resources in Shanghai. Global and local spatial autocorrelation was performed using global Moran's index and local Moran's index to illustrate the spatial changing patterns and identify the priority areas for two types of healthcare resource allocation. Results: Shanghai's healthcare resources showed decreasing trends of inequalities at large from 2010 to 2016. However, there still existed an unchanged over-concentration distribution in healthcare facilities and workforce density among districts in Shanghai, especially for doctors at the municipal level and facility allocation at the rural level. Through spatial autocorrelation analysis, it was found that there exhibited a significant spatial autocorrelation in the density distribution of all resources, and some identified priority areas were detected for resource re-allocation policy planning. Conclusion: The study identified the existence of inequality in some healthcare resource allocations in Shanghai from 2010 to 2016. Hence, more detailed area-specific healthcare resource planning and distribution policies are required to balance the health workforce distribution at the municipal level and institution distribution at the rural level, and particular geographical areas (low-low and low-high cluster areas) should be focused on and fully considered across all the policies and regional cooperation to ensure health equality for municipal cities like Shanghai in developing countries.

Per capita CO2 emission inequality of China's urban and rural residential energy consumption: A Kaya-Theil decomposition.

With the increasing affluence, the differences in CO2 emission between urban and rural residential sectors are remarkable and show an increasing trend. In case of China, residential sector accounts for a substantial share of the national CO2 emission, bringing greater pressure to achieve the goal of carbon peak. Analyzing the emission inequality trend and its drivers is essential for formulating effective CO2 emission reduction policies. However, the existing literature lacks relevant analysis from the viewpoint of urban-rural disparity. Hence, this study decomposes the CO2 emission inequality of China's urban and rural residential consumption into four factors by combining the Theil index and Kaya decomposition. The results suggest that, in 2005-2020, the per capita CO2 emission of rural residential consumption increased to a higher extent than those of urban households, with large differences in spatial distribution. Decomposition of the per capita CO2 emission inequality for residential sector shows that the primary source is the inequality within the groups, mainly from the urban intra-group inequality. Based on the static decomposition, energy intensity appears as the main factor of urban-rural inequality. The dynamic decomposition shows that there have been differences in the factors of the change in the Theil index between urban and rural areas across sub-periods.

Study on regional differences and influencing factors of energy consumption in China.

Energy is becoming more and more important in the process of development. Through cluster analysis, 30 provinces chosen from the Chinese mainland are divided into high, medium, and low energy consumption regions, and the Theil index is used to analyze the characteristics of total energy consumption and other characteristics of regional differences. Based on this, an enhanced Panel-STIRPAT model is constructed. Through data and model inspection, panel models suitable for each region are selected for comprehensive analysis. The results show that: there are regional differences in energy consumption in China, and the total regional differences mainly come from within each region. The factors affecting energy consumption in different regions are the same, but due to differences in geographical environment and stress levels, the influence of these factors on energy consumption in different regions is different. Based on this, reasonable measurements to control energy consumption in different regions are presented.

Analysis of spatiotemporal difference and driving factors of green total factor energy efficiency in RCEP members: insights from SBM-GML and Tobit models.

It is vital to determine the changing spatiotemporal patterns and driving factors of green total factor energy efficiency (GTFEE) in order to design scientific policies to promote energy efficiency in the Regional Comprehensive Economic Partnership (RCEP) region. From 2010 to 2019, the super-efficient SBM model and the global Malmquist-Luenberger index provide an appropriate framework for measuring the spatiotemporal evolution of GTFEE and the dynamics of energy productivity in RCEP countries. With the coefficient of variation and the Thiel index, an extensive view of the spatiotemporal variance in GTFEE is offered, taking regional heterogeneity into account. Furthermore, the Tobit model is introduced to investigate the factors influencing the GTFEE of RCEP members, which may address the restricted values of the dependent variable when compared to the least squares regression model. Findings suggest that (1) The GTFEE of RCEP members tends to be low and unevenly distributed spatially and temporally, with much room for improvement. (2) The energy productivity index fluctuates strongly, and the improvement primarily comes from technological progress. (3) The Non-ASEAN region possesses higher GTFEE than the ASEAN region, albeit regional variations are diminishing. (4) In terms of the major factors influencing the regional GTFEE, the non-ASEAN region looks to be distinct from the ASEAN region. The findings shed light on the trends and influencing factors of GTFEE in RCEP and serve as a resource for international energy cooperation and sustainable development.

[Analysis on the allocation equality in occupational health technology service resource in Gansu Province].

Objective: To investigate and analyze the allocation equality of occupational health technology service resource of Gansu disease control and prevention institutions, providing reference basis for optimizing the allocation of occupational health technology service resources. Methods: Combined with the survey data in September 2021, Gansu Province was divided into five economic regions by geographical location and economic characteristics. Taking the service number of enterprises and workers as the analysis dimensions, the allocation level of occupational health technology service resources in different regions was compared. The allocation equality was analyzed through Lorentz curve, Gini coefficient and Theil index. Results: There were 301 occupational health technicians and 1914 sampling and testing equipments of Gansu Provincial disease control and prevention institutions in 2021. All of the technicians and equipments were used for serving 1952 enterprises and 465800 workers. The curvature of Lorentz curves and Gini coefficient which measured by the service number of enterprises and workers were: occupational health technicians>radioactive factor sampling and testing equipment >physical factor sampling and testing equipment >chemical factor sampling and testing equipment, and chemical factor sampling and testing equipment>physical factor sampling and testing equipment >radioactive factor sampling and testing equipment >occupational health technicians, respectively. Theil index of occupational health technology service resources suggested that differences in regions were the main unfair reason effected the allocation of occupational health technicians and radioactive factor sampling and testing equipment, while the differences between regions were the main unfair reason effected the allocation of chemical and physical factor sampling and testing equipment. Conclusion: The allocation equality in occupational health technology service resources of Gansu Provincial disease control and prevention institutions was not enough, and the differences in regions and between regions should be considered. This study suggests that it is necessary to introduce more occupational health technicians. The allocation of occupational health technology service resources should match with the number of local enterprises and the types of potential hazard factors of enterprises as far as possible.

Decomposed Trends of Iranian Private Health Expenditures: Should Inequality be Appreciated?

Background: Inequalities in health and health care have drawn considerable attention in social determinants of health literature. This study aims to calculate the inequality of out-of-pocket health payments (OPHP) for Iranian households during the period 1984 to 2019 and provide decomposed inequality for households with different socioeconomic status. Methods: This longitudinal study utilized the Iranian Statistics Centre data on Iranian household income and expenditures survey. The analysis includes a total of 995,300 households during a 36-year period from 1984 to 2019. The Theil index and the mean logarithmic deviation were used to decompose inequality into within-group and between-group for OPHP among Iranian households. Results: The findings indicate that the mean of the Theil index for the households covered by insurance is 1.44 (SD ± 0.34), while the index was 1.35 (SD ± 0.31) for households without insurance coverage. The mean of the Theil index for rural and urban households was 1.29 (SD ± 0.29) and 1.43 (SD ± 0.33), respectively. Regardless of the fluctuations, the trends of between- group and within group inequalities in OPHP were almost similar until 2011, but they followed a different path since then. Conclusion: Households living in cities, households with insurance coverage, and households in high income levels have experienced more inequality in OPHP than other households. This study provides a novel interpretation of inequality in health care expenditures and provides a long-term time series data to assess the effectiveness of implemented policies in health care system.

Equity assessment of the distribution of mental health beds in China: based on longitudinal data from 2011 to 2020.

BACKGROUND: Mental health problems have become a public health problem that needs to be solved in China. However, medical resources for mental healthcare remain insufficient and unevenly distributed. The Chinese central government has taken many measures to address this issue over the last decade. This study aimed to evaluate the changes in equity in mental health bed allocation from 2011 to 2020. METHODS: The data of this study came from the China Health Statistical Yearbook (2012-2021) and the China National Administrative Division Information Platform. The annual growth rate was used to evaluate the time trends of mental health beds. The Lorenz curve, Gini coefficient and Theil index were used to assess equity in the demographic and geographical dimensions. The distribution of mental health beds was visualized on a map using geographic information system (GIS) software. RESULTS: The total number of mental health beds in China increased steadily from 2011 to 2020. At the national level, the Gini coefficient and Theil index all exhibited downward trends over time. The mental health bed allocation in terms of the demographic dimension was relatively equitable, with Gini values all less than 0.3; however, the Gini coefficients by geographical area were all more than 0.6, indicating inequity. Intraregional contribution rates were higher than interregional contribution rates, which were all above 60%. CONCLUSION: The overall distribution equity of mental health beds improved from 2011 to 2020. The equity of mental health beds in terms of population size is superior to that in terms of geographical area. Intraregional differences are the main source of inequity. In particular, differences within the western region need to be given attention. Thus, the findings from this study emphasize that the demographic and geographical distributions and all influencing factors should be considered when the government makes mental health resource allocation policies.