Geographic health inequalities in Norway: a Gini analysis of cross-county differences in mortality from 1980 to 2014

Deprivation and Rurality Mediate Income Inequality's Association with Colorectal Cancer Outcomes

INTRODUCTION

Income inequality is associated with poor health outcomes, but its association with colorectal cancer is not well-studied. The authors aimed to determine the association between income inequality and colorectal cancer incidence/mortality in U.S. counties, and hypothesized that this association was mediated by deprivation.

METHODS

The authors performed a cross-sectional study of U.S. counties from 2015-2019 using statewide cancer registries and the Centers for Disease Control and Prevention WONDER database. Generalized linear negative binomial regression was performed in 2024 to estimate the association between Gini coefficient (income inequality) and colorectal cancer incidence/mortality using incidence rate ratios (IRRs) for the entire cohort and stratified by rurality.

RESULTS

A total of 697,981 colorectal cancer cases were diagnosed in the 5-year study period. On adjusted regression, for every 0.1 higher Gini coefficient, there was an 11% higher risk of both colorectal cancer incidence and mortality (IRR 1.11, 95%CI 1.03,1.19 and IRR 1.11, 95%CI 1.05, 1.18 respectively). The association between income inequality and incidence/mortality peaked in more rural counties, however there was not an overall dose-dependent relationship between rurality and these associations. Deprivation mediated the association between income inequality and colorectal cancer incidence (indirect effect B coefficient 0.088, p<0.001) and mortality (B coefficient 0.088, p<0.001). The magnitude and direction of the direct, indirect, and total effects differed in each rurality strata.

CONCLUSIONS

Much of income inequality's association with colorectal cancer outcomes operates through deprivation. Rural counties have a stronger association between higher income inequality and higher mortality, which works in tandem with deprivation.

Examining geographical inequalities for malaria outcomes and spending on malaria in 40 malaria-endemic countries, 2010-2020

BACKGROUND

While substantial gains have been made in the fight against malaria over the past 20 years, malaria morbidity and mortality are marked by inequality. The equitable elimination of malaria within countries will be determined in part by greater spending on malaria interventions, and how those investments are allocated. This study aims to identify potential drivers of malaria outcome inequality and to demonstrate how spending through different mechanisms might lead to greater health equity.

METHODS

Using the Gini index, subnational estimates of malaria incidence and mortality rates from 2010 to 2020 were used to quantify the degree of inequality in malaria burden within countries with incidence rates above 5000 cases per 100,000 people in 2020. Estimates of Gini indices represent within-country distributions of disease burden, with high values corresponding to inequitable distributions of malaria burden within a country. Time series analyses were used to quantify associations of malaria inequality with malaria spending, controlling for country socioeconomic and population characteristics.

RESULTS

Between 2010 and 2020, varying levels of inequality in malaria burden within malaria-endemic countries was found. In 2020, values of the Gini index ranged from 0.06 to 0.73 for incidence, 0.07 to 0.73 for mortality, and 0.00 to 0.36 for case fatality. Greater total malaria spending, spending on health systems strengthening for malaria, healthcare access and quality, and national malaria incidence were associated with reductions in malaria outcomes inequality within countries. In addition, government expenditure on malaria, aggregated government and donor spending on treatment, and maternal educational attainment were also associated with changes in malaria outcome inequality among countries with the greatest malaria burden.

CONCLUSIONS

The findings from this study suggest that prioritizing health systems strengthening in malaria spending and malaria spending in general especially from governments will help to reduce inequality of the malaria burden within countries. Given heterogeneity in outcomes in countries currently fighting to control malaria, and the challenges in increasing both domestic and international funding allocated to control and eliminate malaria, the efficient targeting of limited resources is critical to attain global malaria eradication goals.

Our health, our research. Identifying public health research priorities among children and youth in a multiethnic population: protocol for a community-based participatory health research priority survey

INTRODUCTION

Emphasis on public involvement (PI) in health research has increased in the last 20 years. However, there is limited literature on PI in planning and conducting population-based health research. This study aims to identify child and adolescent health research priorities among children and stakeholder groups in Northern Norway by inviting PI groups to collaborate with researchers to develop and conduct a research priority survey.

METHODS AND ANALYSIS

This is a community-based participatory research project. The methods for research prioritisation are informed by those developed by the James Lind Alliance. In addition, the survey design and engagement plans are developed in extensive collaboration with child and youth stakeholder groups. Nine PI groups have met three times to develop an anonymous child and youth health research priority survey, as well as strategies for recruitment and dissemination of results. All 5th-10th grade pupils in the Finnmark region will be invited to participate in the survey, as well as caretakers and adults working for and with children and youth. The survey results will be analysed in collaboration with the PI groups, and research priorities checked with existing research literature.

ETHICS AND DISSEMINATION

The study is registered and approved by the Data Protection Authorities at the Finnmark Hospital Trust and the Expert Committee for Sami Health Research. Descriptions of methods applied and the survey results will be published in popular and scientific publications.

County level study of the interaction effect of PM2.5 and climate sustainability on mortality in China

Introduction

PM2.5 and climate change are two major public health concerns, with majority of the research on their interaction focused on the synergistic effect, particularly for extreme events such as hot or cold temperatures. The climate sustainability index (CLS) was introduced to comprehensively explore the impact of climate change and the interactive effect on human health with air pollution.

Methods

In this study, a county-level panel data in China was collected and used. The generalized additive model (GAM) and geographically and temporally weighted regression (GTWR) was used to explore the interactive and spatial effect on mortality between CLS and PM2.5.

Results and discussions

Individually, when CLS is higher than 150 or lower than 50, the mortality is higher. Moreover, when PM2.5 is more than 35 μg/m3, the influence on mortality is significantly increased as PM2.5 concentration rises; when PM2.5 is above 70 μg/m3, the trend is sharp. A nonlinear antagonistic effect between CLS and PM2.5 was found in this study, proving that the combined adverse health effects of climate change and air pollution, especially when CLS was lower (below 100) and PM2.5 was higher (above 35 μg/m3), the antagonistic effect was much stronger. From a spatial perspective, the impact of CLS and PM2.5 on mortality varies in different geographical regions. A negative and positive influence of CLS and PM2.5 was found in east China, especially in the northeastern and northern regions, -which were heavily polluted. This study illustrated that climate sustainability, at certain level, could mitigate the adverse health influence of air pollution, and provided a new perspective on health risk mitigation from pollution reduction and climate adaptation.

Greece since the 1960s: the mortality transition revisited: a joinpoint regression analysis

Mortality transition in Greece is a well-studied phenomenon in several of its aspects. It is characterised by an almost constant increase in life expectancy at birth and other ages and a parallel decrease in death probabilities. The scope of this paper is a comprehensive assessment of the mortality transition in Greece since 1961, in the light of holistic analysis. Within this paper, life tables by gender were calculated and the temporal trends of life expectancy at several ages were examined. Moreover, a cluster analysis was used in order to verify the temporal changes in the mortality patterns. The probabilities of death in large age classes are presented. Furthermore, the death distribution was analysed in relation to various parameters: the modal age at death, mode, left and right inflexion points and the length of the old age heap. Before that, a non-linear regression method, originating from the stochastic analysis, was applied. Additionally, the Gini coefficient, average inter-individual differences, and interquartile range of survival curves were examined. Finally, the standardised rates of the major causes of death are presented. All the analysis variables were scholastically examined for their temporal trends with the method of Joinpoint Regression analysis. Mortality transition in Greece after the year 1961 is asymmetrical with a gender and an age-specific component, leading to the elevation of life expectancy at birth over time. During this period, the older ages' mortality decreases, but at a slower pace than that of the younger ones. The modal age at death, mode, the left and right inflexion points and the width of the old age heap denote the compression of mortality in the country. The old age death heap shifts towards older ages, while at the same time, the variability of ages at death decreases, being verified by the Gini Coefficient and average inter-individual differences. As a result, the rectangularization of survival curves is evident. These changes have a different pace of transition over time, especially after the emergence of the economic crisis. Finally, the major causes of death were the diseases of the circulatory system, neoplasms, diseases of the respiratory system and others. The temporal trends of these diseases differ according to the diseases and gender. Greece's mortality transition is an asymmetrical stepwise process characterised by its gender and age-specific characteristics. This process, despite being a continuous one, is not linear. Instead, a combination of serious developments over time governs the country's modern mortality regime. The evaluation of Greece's mortality transition through the lens of more advanced analytical methods may provide new insights and methodological alternatives for assessing mortality transition in other countries of the world.

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.

Changes in life expectancy and disease burden in Norway, 1990–2019: an analysis of the Global Burden of Disease Study 2019

Background

Methods

Findings

Interpretation

Funding

Changes in regional variation in mortality over five decades - The contribution of age and socioeconomic population composition

Existing evidence suggests that within-country area variation in mortality has increased in several high-income countries. Little is known about the role of changes in the population composition of areas in these trends. In this study, we look at mortality variation across Finnish municipalities over five decades. We examine trends by sex, age categories and two broad cause of death groups and assess the role of individual-level compositional factors. Analyses rely on individual-level register data on the total Finnish population aged 30 years and over. We estimated two-level Weibull survival-models with individuals nested in areas for 10 periods between 1972 and 2018 to assess municipal-level variation in mortality. Median hazard ratio (MHR) was used as our summary measure and analyses were adjusted for age and socioeconomic characteristics. The results show a clear overall growth in area variation in mortality with MHR increasing from 1.14 (95% CI 1.12-1.15) to 1.28 (CI 1.26-1.30) among men and 1.17 (CI 1.15-1.18) to 1.30 (CI 1.27-1.32) among women. This growth, however, was fully attenuated by adjustment for age. Area differentials were largest and increased most among men at ages 30-49, and particularly for external causes. This increase was largely due to increasing differentiation in the socioeconomic composition of municipalities. In conclusion, our study shows increases in mortality differentials across municipalities that are mostly attributable to increasing differentiation between municipalities in terms of individual compositional factors.

Socioeconomic disparity in global vision loss burden due to diabetic retinopathy: an analysis on time trends from 1990 to 2017

PURPOSE

To describe the trends of socioeconomic disparity in global vision loss burden associated with diabetic retinopathy (DR) based on prevalence and years lived with disability (YLDs).

METHODS

In the Global Burden of Disease (GBD) 2017 study, we extracted global, regional, national, and World Bank categorical epidemiological data in vision impairment by time and age. We searched the Human development index (HDI) from the Human Development Report. Pearson correlation, linear regression, and Kruskal-Wallis test were conducted to analyze the correlation between YLD rates and HDI. We used the Gini coefficient and concentration index to evaluate the socioeconomic inequality trendency.

RESULTS

The global and World Bank categorical prevalence and YLDs increased from 1990 to 2017, and rose with ageing. The age-standardized prevalence and YLD rates varied geographically and highest in the Eastern Mediterranean countries. Higher vision loss burden of DR was concentrated in countries with medium level of socioeconomic development, including lower/upper middle-income and medium/high-HDI countries. The Gini coefficient decreased from 0.572 in 1990 to 0.542 in 2017, showing the decreasing between-country inequality. The concentration index decreased from 0.153 in 2000 to 0.061 in 2017, showing the reducing socioeconomic-associated disparity.

CONCLUSION

The vision loss burden of DR increased in the past few decades, with a notable declining socioeconomic disparity since 2000. Our results highlight the necessity to provide more services to reduce the vision loss burden.

Inequality indices to monitor geographic differences in incidence, mortality and fatality rates over time during the COVID-19 pandemic

BACKGROUND

It is of interest to explore the variability in how the COVID-19 pandemic evolved geographically during the first twelve months. To this end, we apply inequality indices over regions to incidences, infection related mortality, and infection fatality rates. If avoiding of inequality in health is an important political goal, a metric must be implemented to track geographical inequality over time.

METHODS

The relative and absolute Gini index as well as the Theil index are used to quantify inequality. Data are taken from international data bases. Absolute counts are transformed to rates adjusted for population size.

RESULTS

Comparing continents, the absolute Gini index shows an unfavorable development in four continents since February 2020. In contrast, the relative Gini as well as the Theil index support the interpretation of less inequality between European countries compared to other continents. Infection fatality rates within the EU as well as within the U.S. express comparable improvement towards more equality (as measured by both Gini indices).

CONCLUSIONS

The use of inequality indices to monitor changes in geographic inequality over time for key health indicators is a valuable tool to inform public health policies. The absolute and relative Gini index behave complementary and should be reported simultaneously in order to gain a meta-perspective on very complex dynamics.

Gender and Socioeconomic Disparities in Global Burden of Epilepsy: An Analysis of Time Trends From 1990 to 2017

Objective: The objective of the study is to investigate the gender and socioeconomic disparities in the global burden of epilepsy by prevalence and disability-adjusted life-years (DALYs).

Methods: The global, regional, and national gender-specific prevalence and DALYs caused by epilepsy by year and age were extracted from the Global Burden of Disease (GBD) Study 2017. The Gini coefficient and concentration index (CI) were calculated to demonstrate the trends in between-country inequality in the epilepsy burden from 1990 to 2017. Paired Wilcoxon signed rank test, Pearson correlation, and linear regression analyses were performed to analyze the association of gender disparity in epilepsy and socio-demographic index (SDI).

Results: The DALYs number of epilepsies increased from 1990 to 2017 by 13.8%, whereas age-standardized DALY rates showed a substantial reduction (16.1%). Men had a higher epilepsy burden than women of the same period. The epilepsy burden appeared to be higher in countries with lower socioeconomic development (CI < 0). The Gini coefficient decreased from 0.273 in 1995 to 0.259 in 2017, representing a decline in the between-country gap. Age-standardized prevalence and DALY rates of men were higher than those of women in each SDI-based country group (p < 0.0001). Male-minus-female difference (r = −0.5100, p < 0.0001) and male-to-female ratio (r = −0.3087, p < 0.0001) of age-standardized DALY rates were negatively correlated with SDI.

Conclusion: Although global health care of epilepsy is in progress, the epilepsy burden was concentrated in males and developing countries. Our findings highlight the importance of formulating gender-sensitive health policies and providing more services in developing countries.

Global patterns in vision loss burden due to vitamin A deficiency from 1990 to 2017

OBJECTIVE

To investigate the vision loss burden due to vitamin A deficiency (VAD) at the global, regional and national levels by year, age, sex and socio-economic status using prevalence and years lived with disability (YLD).

DESIGN

International, retrospective, comparative burden-of-disease study.

SETTING

Prevalence and YLD data were extracted from the Global Burden of Disease (GBD) Study 2017. The association of age-standardised YLD rates and human development index (HDI) was tested by Pearson correlation and linear regression analyses. The Gini coefficient and concentration index (CI) were calculated to demonstrate the trends in between-country inequality in vision loss burden due to VAD.

PARTICIPANTS

All participants met the GBD inclusion criteria.

RESULTS

The age-standardised prevalence rate increased by 9·2 %, while the age-standardised YLD rates rose by 10·8 % from 1990 to 2017. Notably, the vision loss burden caused by VAD showed a declining trend since 2014. The vision loss burden was more concentrated in the post-neonatal age group and decreased with increasing age. The age-standardised YLD rates were inversely correlated with HDI (r = -0·2417, P = 0·0084). The CI and Gini coefficients indicated that socio-economic-related and between-country inequality declined from 2000 to 2017. VAD was the eighth leading cause of the age-standardised prevalence rate and ninth leading cause of age-standardised YLD rate among fifteen causes of vision loss in 2017.

CONCLUSION

VAD has become one of the significant leading causes of vision loss globally. Efforts to control vision impairment related to VAD are needed, especially for children in countries with lower socio-economic status.

Emergence of a mortality disparity between a marginal rural area and the rest of Denmark, 1968-2017

BACKGROUND

Lolland-Falster is a rural area of Denmark, where the life expectancy is presently almost six years lower than in the rich capital suburbs. To determine the origin of this disparity, we analysed changes in mortality during 50 years in Lolland-Falster.

METHODS

Annual population number and number of deaths at municipality level were retrieved from StatBank Denmark and from Statistics Denmark publications, 1968-2017. For 1974-2017, life expectancy at birth by sex and 5-year calendar period was calculated. From 1968 to 2017, standardised mortality ratio (SMR) for all-cause mortality was calculated by sex, 5-year calendar period and municipality, with Denmark as standard and including 95% confidence intervals (CI).

RESULTS

In 1968-2017, life expectancy in Lolland-Falster increased, but less so than in the rest of Denmark. Fifty years ago, Lolland-Falster had a mortality similar to the rest of Denmark. The increasing mortality disparity developed gradually starting in the late 1980s, earlier in Lolland municipality (western part) than in Guldborgsund municipality (eastern part), and earlier for men than for women. By 2013-2017, the SMR had reached 1.25 (95% CI 1.19-1.31) for men in the western part, and 1.11 (95% CI 1.08-1.16) for women in the eastern part. Increasing mortality disparity was particularly seen in people aged 20-69 years.

CONCLUSIONS

This study is the first to report on increasing geographical segregation in all-cause mortality in a Nordic welfare state. Development of the mortality disparity between Lolland-Falster and the rest of Denmark followed changes in agriculture, industrial company closure, a shipyard close-down, administrative centralisation, and a decreasing population size.

The Gini coefficient as a useful measure of malaria inequality among populations

Background

Understanding inequality in infectious disease burden requires clear and unbiased indicators. The Gini coefficient, conventionally used as a macroeconomic descriptor of inequality, is potentially useful to quantify epidemiological heterogeneity. With a potential range from 0 (all populations equal) to 1 (populations having maximal differences), this coefficient is used here to show the extent and persistence of inequality of malaria infection burden at a wide variety of population levels.

Methods

First, the Gini coefficient was applied to quantify variation among World Health Organization world regions for malaria and other major global health problems. Malaria heterogeneity was then measured among countries within the geographical sub-region where burden is greatest, among the major administrative divisions in several of these countries, and among selected local communities. Data were analysed from previous research studies, national surveys, and global reports, and Gini coefficients were calculated together with confidence intervals using bootstrap resampling methods.

Results

Malaria showed a very high level of inequality among the world regions (Gini coefficient, G = 0.77, 95% CI 0.66–0.81), more extreme than for any of the other major global health problems compared at this level. Within the most highly endemic geographical sub-region, there was substantial inequality in estimated malaria incidence among countries of West Africa, which did not decrease between 2010 (G = 0.28, 95% CI 0.19–0.36) and 2018 (G = 0.31, 0.22–0.39). There was a high level of sub-national variation in prevalence among states within Nigeria (G = 0.30, 95% CI 0.26–0.35), contrasting with more moderate variation within Ghana (G = 0.18, 95% CI 0.12–0.25) and Sierra Leone (G = 0.17, 95% CI 0.12–0.22). There was also significant inequality in prevalence among local village communities, generally more marked during dry seasons when there was lower mean prevalence. The Gini coefficient correlated strongly with the standard coefficient of variation, which has no finite range.

Conclusions

The Gini coefficient is a useful descriptor of epidemiological inequality at all population levels, with confidence intervals and interpretable bounds. Wider use of the coefficient would give broader understanding of malaria heterogeneity revealed by multiple types of studies, surveys and reports, providing more accessible insight from available data.

Spatio-Temporal Comprehensive Measurements of Chinese Citizens' Health Levels and Associated Influencing Factors

Health is the basis of a good life and a guarantee of a high quality of life. Furthermore, it is a symbol of social development and progress. How to further improve the health levels of citizens and reduce regional differences in citizens’ health status has become a research topic of great interest that is attracting attention globally. This study takes 31 provinces (municipalities and autonomous regions) of China as the research object. Through using GIS (Geographic Information System) technology, the entropy method, spatial autocorrelation, stepwise regression, and other quantitative analysis methods, measurement models and index systems are developed in order to perform an analysis of the spatio-temporal comprehensive measurements of Chinese citizens’ health levels. Furthermore, the associated influencing factors are analyzed. It has important theoretical and practical significance. The conclusions are as follows: (1) Between 2002 and 2018, the overall health levels of Chinese citizens have generally exhibited an upward trend. Moreover, for most provinces, the health levels of their citizens have improved dramatically, although some provinces, such as Tianjin and Henan, showed a fluctuating downward trend, suggesting that the health levels of citizens in these regions displayed a tendency to deteriorate. (2) The health levels of citizens from China’s various provinces showed clear spatial distribution characteristics of clustering, as well as an obvious spatial dependence and spatial heterogeneity. As time goes by, the degree of spatial clustering with regard to citizens’ health levels tends to weaken. The health levels of Chinese citizens have developed a certain temporal stability, the overall health status of Chinese citizens shows a spatial differentiation of a northeast–southwest distribution pattern. (3) The average years of education and urbanization rate have a significant positive effect on the improvement of citizens’ health levels. The increase of average years of education and urbanization rate can promote the per capita income, which certainly could help improve citizens’ health status. The Engel coefficient, urban–rural income ratio, and amount of wastewater discharge all pose a significant negative effect on the improvement of citizens’ health levels, these three factors have played important roles in hindering the improvements of citizen health.

Inequality of health stock and the relation to national wealth

BACKGROUND

The decline in global and between-country health inequality is a major challenge to overcome. However, few studies have systematically investigated the relationship between inequality of health stock and national wealth. From an economic perspective, health can be viewed as a durable capital stock that produces an output of healthy time. Therefore, in this paper, we focused on health capital to investigate the relationship between inequalities of national health and national wealth.

METHODS

Based on health stock data from 1990 to 2015 for 140 countries, we estimated Gini coefficients of health stock to investigate associations with a well-known economic flow indicator, Gross Domestic Product (GDP), stock-based national wealth indicator, Inclusive Wealth Index (IWI), and firm-level net income.

RESULTS

The estimated Gini coefficient of global health stock shows that health stock has experienced a global decline. The Gini coefficient for low-income countries (LICs) showed the fastest decline in health stock, dropping from 0.69 to 0.66 in 25 years. Next, rapid population growth and the rise in the youth share of the working-age population in LICs were most likely contributing factors to the decline in inequality. Most countries that experienced positive health stock growth also indicated a strong positive relationship with GDP and IWI. However, some countries showed a negative relationship with natural capital, which is a part of IWI. In addition, firm-level net income showed no obvious associations with health stock, GDP and IWI.

CONCLUSIONS

We argue that a negative relationship between health stock and natural capital is a sign of unstable development because sustainable development involves maintaining not only GDP but also IWI, as it is a collective set of assets or wealth comprising human, produced and natural capital. Moreover, in our analysis of firm-level income data, we also discuss that income will be influenced by other factors, such as innovations, human resources, organization culture and strategy. Therefore, the paper concludes that health stock is a vital component in measuring health inequality and health-related Sustainable Development Goals (SDGs). Thus, IWI is more comprehensive in measuring national wealth and can complement GDP in measuring progress toward sustainable development.

Inequalities in healthcare resources and outcomes threatening sustainable health development in Ethiopia: panel data analysis

OBJECTIVE

To measure inequalities in the distributions of selected healthcare resources and outcomes in Ethiopia from 2000 to 2015.

DESIGN

A panel data analysis was performed to measure inequalities in distribution of healthcare workforce, infrastructure, outcomes and finance, using secondary data.

SETTING

The study was conducted across 11 regions in Ethiopia.

PARTICIPANTS

Regional population and selected healthcare workforce.

OUTCOMES MEASURED

Aggregate Theil and Gini indices, changes in inequalities and elasticity of healthcare resources.

RESULTS

Despite marked inequality reductions over a 16 year period, the Theil and Gini indices for the healthcare resources distributions remained high. Among the healthcare workforce distributions, the Gini index (GI) was lowest for nurses plus midwives (GI=0.428, 95% CI 0.393 to 0.463) and highest for specialist doctors (SPDs) (GI=0.704, 95% CI 0.652 to 0.756). Inter-region inequality was the highest for SPDs (95.0%) and the lowest for health officers (53.8%). The GIs for hospital beds, hospitals and health centres (HCs) were 0.592(95% CI 0.563 to 0.621), 0.460(95% CI 0.404 to 0.517) and 0.409(95% CI 0.380 to 0.439), respectively. The interaction term was highest for HC distributions (47.7%). Outpatient department visit per capita (GI=0.349, 95% CI 0.321 to 0.377) and fully immunised children (GI=0.307, 95% CI 0.269 to 0.345) showed inequalities; inequality in the under 5 years of age mortality rate increased overtime (P=0.048). Overall, GI for government health expenditure (GHE) was 0.596(95% CI 0.544 to 0.648), and the estimated relative GHE share of the healthcare workforce and infrastructure distributions were 46.5% and 53.5%, respectively. The marginal changes in the healthcare resources distributions were towards the advantaged populations.

CONCLUSION

This study revealed high inequalities in healthcare resources in favour of the advantaged populations which can hinder equal access to healthcare and the achievements of healthcare outcomes. The government should strengthen monitoring mechanisms to address inequalities based on the national healthcare standards.