Theil Index Research Articles

Spatiotemporal Differences in Marine Environment Quality in China and the Influencing Factors

Based on 2011–2020 panel data for China’s coastal cities and provinces, this study used the entropy method and Theil index to measure marine environment quality (MEQ) and construct MEQ indicators. We used the Theil index to measure heterogeneity in regional MEQ and a geographic detector model to explore the driving factors of MEQ. Our study resulted in the following findings: (1) MEQ increased in waves, but the overall quality was relatively low, forming a spatial distribution pattern of high in the north and south, and low in the east. Moreover, MEQ was polarized between provinces. (2) Regional MEQ showed a distribution pattern of significant differences between the east and the north but small differences in the south. The regional gap was significant but gradually narrowing, with the contribution rate of intra-regional differences reaching over 90%. Meanwhile, interregionalinter-regional differences were relatively small and showed a balanced development trend. (3) Agricultural and aquaculture pollution were found to be the main factors affecting MEQ. The effect of marine engineering pollution was significantly increasing while that of environmental regulation intensity was relatively weak. The interaction between different driving factors mainly manifested as dual-factor enhancement and nonlinear enhancement.

Investigating the Inequality Trend in Health Resource Distribution in Iran: A Case Study in Bushehr Province

Background: Equity in access to health resources is a fundamental goal of health systems worldwide. Objectives: This study aims to assess the distribution of essential health resources necessary for healthcare provision in Bushehr Province. Methods: This cross-sectional study spans ten years and utilizes several widely recognized indices in health resource distribution equity and equality, including the Gini Coefficient, Concentration Index, Horizontal Inequity, Robin Hood Index, Theil Index, Atkinson Index, and Quantile Ratio. These indices were calculated based on both the population level and the proposed resource allocation model (PRAM) using Excel Software 2018 and Stata version 18. Results: The findings indicate a degree of inequality in the distribution of all health resources examined, with special beds exhibiting much higher levels of inequality than others. The sensitivity of the studied indices varied across the distributed resources. Moreover, the trend of inequality generally decreased for all examined resources. The PRAM results suggest that adopting a different approach to resource distribution can significantly reduce inequality levels. Conclusions: Despite a downward trend in the inequality of health resource distribution, significant disparities persist. Altering the resource distribution system from the conventional geographical division could aid in achieving equity and equality in healthcare. Such changes could also reduce the costs associated with the health system.

County-level factors associated with a mismatch between opioid overdose mortality and availability of opioid treatment facilities.

Opioid overdose deaths in the United States remain a major public health crisis. Little is known about counties with high rates of opioid overdose mortality but low availability of opioid use disorder (OUD) treatment facilities. We sought to identify characteristics of United States (US) counties with high rates of opioid overdose mortality and low rates of opioid treatment facilities. Rates of overdose mortality from 3,130 US counties were compared with availability of opioid treatment facilities that prescribed or allowed medications for OUD (MOUD), from 2018-2019. The outcome variable, "risk-availability mismatch" county, was a binary indicator of a high rate (above national average) of opioid overdose mortality with a low (below national average) rate of opioid treatment facilities. Covariates of interest included county-level sociodemographics and rates of insurance, unemployment, educational attainment, poverty, urbanicity, opioid prescribing, depression, heart disease, Gini index, and Theil index. Multilevel logistic regression, accounting for the clustering of counties within states, was used to determine associations with being a "risk-availability mismatch" county. Of 3,130 counties, 1,203 (38.4%) had high rates of opioid overdose mortality. A total of 1,098 counties (35.1%) lacked a publicly-available opioid treatment facility in 2019. In the adjusted model, counties with an additional 1% of: white residents (odds ratio, OR, 1.02; 95% CI, 1.01-1.03), unemployment (OR, 1.11; 95% CI, 1.05-1.19), and residents without insurance (OR, 1.04; 95% CI, 1.01-1.08) had increased odds of being a mismatch county. Counties that were metropolitan (versus non-metropolitan) had an increased odds of being a mismatch county (OR, 1.85; 95% CI, 1.45-2.38). Assessing mismatch between treatment availability and need provides useful information to characterize counties that require greater public health investment. Interventions to reduce overdose mortality are unlikely to be effective if they do not take into account diverse upstream factors, including sociodemographics, disease burden, and geographic context of communities.

Inequality characteristics and influencing factors of CO2 emissions per capita in Jiangsu Province, China.

Analyzing the inequality characteristics and influencing factors of CO2 emissions per capita (CEPC) is conducive to balancing regional development and CO2 emissions reduction. This study applied the Gini coefficient and Theil index to investigate the CEPC inequalities during 2005-2017 at the county level in Jiangsu Province, China. Considering the spatial spillover and interaction effects, the factors influencing CEPC were analyzed by a hierarchical spatial autoregressive model. The results showed that the inequalities in CEPC first increased and then decreased at the inter-regional, and inter-county levels. The spatial pattern of CEPC was stable, and there was a significantly positive spatial autocorrelation of CEPC at the county level. The High-High type counties were mainly located in Sunan (southern Jiangsu). The spatial interaction effects of the CEPC between the prefecture and county levels indicated that governments at the prefecture level should integrate their county governments to reduce the CEPC. Moreover, carbon intensity, GDP per capita, land urbanization, and industrial structure play an important role in reducing CEPC. Our findings provide a scientific basis for formulating reasonable and effective carbon emission reduction policies.

Analysis of regional differences and spatial and temporal evolution of tourism carbon emissions in China: considering carbon sink effect

ABSTRACT The purpose of this study is to analyze the regional differences and spatial-temporal evolutionary characteristics of carbon dioxide emissions of tourism in China during 2001–2022 from the perspective of carbon sink effect by using an econometric modeling approach. The findings show that CO2 emissions from China's tourism industry exhibit non-equilibrium spatial characteristics or non-linear relationships. Secondly, the results of Theil's index show that the intra-regional differences in tourism CO2 emissions are greater than the inter-regional differences and exhibit a gradient of ‘West > Central > East’. Finally, under the condition of considering the existence of spatial regional heterogeneity, it is found that tourism CO2 emissions have significant spatial agglomeration, with high CO2 emission regions primarily clustered within the eastern region and the economically developed regions, and low CO2 emission regions distributed centrally within the central region and less developed areas of the tourism economy. It is worth noting that the intra-regional differences mainly come from the eastern belt, and that there are large regional differences in tourism CO2 emissions within the eastern region, while the western region is the next largest and the central region the smallest.

Spatial-temporal differentiation of urban eco-efficiency and its driving factors: A comparison of five major urban agglomerations in China.

This paper utilizes an improved undesirable output DEA model to measure the eco-efficiency of cities in five major urban agglomerations in China during 2006-2020. It employs the Theil Index and Geodetector to investigate the spatial-temporal distribution differentiation characteristics and driving factors of urban eco-efficiency. The main findings are as follows. Firstly, the eco-efficiency of all urban agglomerations showed a fluctuating upward trend, but the eco-efficiency performance of different urban agglomerations in China shows a stratification characteristic. Specifically, the Pearl River Delta urban agglomeration consistently ranks first in China, while the mean values of the Yangtze River Delta urban agglomeration, Beijing-Tianjin-Hebei urban agglomeration, and Chengdu-Chongqing urban agglomeration are lower than the national average. Secondly, the overall differences in the urban eco-efficiency of all sample cities show a consistently fluctuating downward trend. The factor that affects the level differences of eco-efficiency in different cities is the intra-regional differences. Last but not least, the top three factors affecting the spatial distribution difference of urban eco-efficiency in the whole sample are environmental pollution control investments, innovation level, and environmental infrastructure investments. In the end, this paper proposes that reducing the intra-regional differences is the primary task to achieve the coordinated improvement of urban eco-efficiency in urban agglomerations, and then puts forward some policy suggestions to improve eco-efficiency for the five major urban agglomerations.

Suitability Index for the Placement of Solar Plants Based on Inequality Measurements and on Satellite Images

The selection of a certain location for the placement of a solar facility depends on the solar resource availability, which is generally assessed though exceedance probabilities. However, the choice of the specific exceedance probability is arbitrary and the assessment will be different depending on the choice taken. Furthermore, exceedance probabilities do not reflect seasonal variability, which affects radiation availability. Therefore, in this work we present a new index, the suitability index based on Theil (SIT), which allows us to assess with a single value the degree of suitability of a site for installing a solar plant. Obtained from the Theil index, it considers the availability of the resource and its seasonal variability, based as it is on the proportion of the given radiation in each month. As we will see, the new index is clearly more sensitive to the amount of radiation expressed in terms of the 50th percentile than to the variability, as given by the interquartile range. This is a quality to be pondered since scarcity of radiation will always be a greater disadvantage for a solar installation than high variability. The results obtained in the study, grounded in the application of satellite images, show that the index adequately reflects the radiation characteristics in the study area. The territory is broken into areas associated with such characteristics through a cluster analysis, so that geographical and economic elements can be considered when choosing the final location for a solar installation. Furthermore, the new index may include the effects of energy storage during the months in which a certain demand is exceeded.

Differences in Carbon Intensity of Energy Consumption and Influential Factors between Yangtze River Economic Belt and Yellow River Basin

The Yangtze River Economic Belt and the Yellow River Basin are significant economic and ecological zones in China, contributing over 70% of the nation’s total carbon emissions, crucial for achieving “peak carbon” and “carbon neutrality” targets. This study examines data spanning 2000 to 2020 from 19 provinces, employing time-series analysis and the Theil index to compare carbon intensity variations in energy consumption between the regions. Findings reveal mean Theil index values of 0.0482 and 0.1699 for the Yangtze and Yellow River Basins, respectively. While the Yangtze River basin displays modest carbon intensity differences with remaining intra-basin disparities, the Yellow River Basin exhibits substantial discrepancies, attributed to both inter-basin and intra-basin factors. Our geodetector underscores the significance of government regulation, population size, and economic development in influencing carbon intensity within the Yangtze River Economic Belt, with impact coefficients exceeding 0.75 while carbon intensity in the Yellow River Basin is influenced by population size, energy consumption, and government regulation, with impact coefficients surpassing 0.8. Additionally, interactions among these factors significantly affect disparities in carbon intensity, suggesting a synergistic effect. We propose leveraging key factors from both basins to orchestrate emissions reduction efforts.

The inequity of urban green space availability between urban villages and residential quarters: An empirical study in Shenzhen, China

During the rapid urbanization process, the unequal distribution of green spaces (GS) has become a prominent topic in academic discussions due to its implications for social justice. Nonetheless, the equity of GS availability among different types of residential neighborhoods remains unclear, posing a challenge to achieving environmental justice in urban greening practices. This study, taking Shenzhen as a case study, examines the equity of GS availability between urban villages (UV) and residential quarters (RQ), two common residential neighborhood types in Chinese cities. We initially categorized both inner-GS and outer-GS based on their location inside or outside the boundary of residential neighborhoods and assessed GS availability at various accessible distances. Subsequently, the Theil index was applied to evaluate the inequity of GS availability, encompassing both the inequities within and between UV and RQ. Our findings reveal that UV exhibited higher GS inequity than RQ across all accessible distances. Furthermore, within UV, GS inequity decreased as the accessible distance increased, while the opposite trend was observed for RQ. Notably, although significant inequities existed in inner-GS availability between UV and RQ, outer-GS played a crucial role in mitigating this imbalance. These results provide valuable insights into GS equity across different residential neighborhood types and offer recommendations for enhancing/balancing the equity of GS availability in Shenzhen.

Diversifying the export basket of creative products and accelerating economic growth

Export product diversification accelerates economic growth by helping the nations to escape the commodity dependence trap, reducing the volatility of terms of trade, and stabilizing export revenues. Creative industries are the emerging and evolving industrial sectors that affect the export basket's composition of nations and its growth effects. In this paper, for the first time, we calculated the diversification level of creative products’ export basket using three measures including Theil and GINI inequality indices and Herfindahl–Hirschman concentration index for the top ten exporters including China, the US, France, Italy, the UK, Germany, India, Switzerland, Singapore, and the Netherlands. In addition, we analyzed the effects of diversification of creative products’ export basket on the economic growth of the countries over the period 2002–2020. Our results indicate the diversification level of the creative products’ basket in Switzerland, the US, France, and China decreased over the period, while for Germany and the Netherlands, it increased over recent years. For other countries, the indexes do not show significant fluctuations. By estimating a Barro-type growth regression model and also panel Granger non-causality test, we found creative products’ diversification acts as a pro-growth factor in the countries.

Measurement, Spatial-Temporal Evolution, and Optimization Path of the Level of Coordinated Development of Ecological Civilisation: The Case of China

Based on the energy–economy–environment–society (3E1S) system theory, this paper constructed a comprehensive evaluation system for the coordinated development of China’s ecological civilisation construction using panel data from 31 provinces and cities from 2005 to 2020, which is specifically divided into four sub-systems, namely, energy, economy, environment, and society, and covers 10 ordinal covariates and 40 ordinal variable indicators. In terms of measurement and evaluation methods, this paper adopted the composite system synergy model to measure the level of coordinated development of ecological civilisation construction of the country as a whole and 31 provinces and cities and adopted Arcgis maps, standard deviation ellipses, kernel density curves, and Theil index methods to explore the spatial-temporal evolution characteristics and regional differences in the level of coordinated development of ecological civilisation construction. It was found that the coordinated development level of China’s ecological civilisation construction increased year by year from 2005 to 2020, with the most obvious upward trend from 2011 to 2015, with an average increase of 26.5%. Secondly, the spatial distribution pattern of the coordinated development level of China’s ecological civilisation construction was relatively stable, basically showing a dominant southwest–northeast direction, but the spatial centre of gravity shows a trajectory shifting towards the southwest. Finally, there were large regional differences in the level of coordinated development of China’s ecological civilisation, with an overall decreasing regional pattern of “Central-Northeast-East-West”. However, the overall differences among the four regions showed a decreasing trend. The overall differences among the four regions were mainly intra-regional, with the western region having the greatest intra-regional differences and contributing to the overall differences. Although this paper takes China as a case study, its research methodology and conclusions can provide references for the construction of ecological civilisation and green sustainable development in other countries.

Regional disparities, dynamic evolution, and spatial spillover effects of urban-rural carbon emission inequality in China

ObjectiveThis study recalculates the carbon emissions of urban and rural residents in China, analyzing the dynamic evolution trends of urban and rural carbon emissions. It explores the spatial spillover effects centered around the inequality in carbon emissions between urban and rural areas.MethodsThe study calculates the carbon emissions of urban and rural residents in each province based on the IPCC method. Non-parametric kernel density estimation is employed to depict the dynamic evolution characteristics of national, urban, and rural carbon emissions. The Theil Index is used to measure the disparities in urban and rural carbon emissions in major strategic regions, further applying the Theil Index to evaluate the inequality of urban and rural carbon emissions across provinces. This helps identify the driving factors affecting the inequality of urban and rural carbon emissions and their spatio-temporal effects.FindingCarbon emissions from urban and rural residents in China present a divergent development pattern. Urban emissions have increased, with inter-provincial disparities widening; rural emissions tend to stabilize, with slight growth in inter-provincial gaps. The overall inequality of carbon emissions in various regions of China experiences a three-phase journey of rise, decline, and stabilization. Urban inequality first increases then decreases, while rural inequality gradually lessens, showing clear regional and urban-rural differences. Market and government factors significantly impact the inequality of urban and rural carbon emissions. The development of the digital economy aids in reducing inequality and generates significant spatial spillover effects. The relationship between economic development level and carbon emission inequality is U-shaped. Industrial structure optimization can reduce urban-rural inequality, but its spatial spillover effect is not significant. Government intervention has limited effects, while environmental regulations may increase inequality. Opening up to the outside world helps reduce inequality, and the impact of population density is complex.

Progress towards health equity in Vietnam: evidence from nationwide official health statistics, 2010-2020

IntroductionOne of the ultimate goals of strengthening the health system is to achieve health equity. Vietnam is considered one of the ‘fast-track countries’ to achieve the health-related Millennium Development Goals,...

ECONOMIC INEQUALITY OF THE REGIONAL DEVELOPMENT OF POLAND, SPAIN AND UKRAINE

The current work analyzes uneven regional economic development in Poland, Spain and Ukraine. It was determined that the unevenness of the economic development of the regions of the studied countries can be assessed by comparing statistical indicators, namely the index of the unevenness of the economic development of the countries, the dynamics of changes in the population of the studied countries and the comparison of regional economic statistics, in particular the indicators of the gross regional product. In order to identify the unevenness of regional economic development and justify the possible ways of their smoothing or levelling, the article uses such integral indicators as the coefficient of variation or Williamson’s coefficient of variation, weighted coefficient of variation, relative mean deviation and Theil Index. The study of the indicated indicators made it possible to reveal contradictions in their analysis and the need to calculate additional indicators, as well as the influence of factors of direct and indirect influence on the economic unevenness of the regional development of the studied European countries.

Urban water security assessment: investigating inequalities using a multi-scale approach

Abstract Water security is a multi-faceted concept that encompasses dimensions such as water quantity, quality, human health, well-being, water hazards, and governance. The evaluation of water security is an important step towards understanding and improving it, particularly in urban settings where disparities resulting from unequal distribution of population and resources are present and often evade citywide assessments. To address the diversity of the urban space, we propose a multi-level assessment approach based on downscaling the spatial dimension. Using a comprehensive indicator-based framework, we evaluate the city of Campinas in Brazil across citywide and intra-city scales. Employing the Theil index to measure inequality, the results reveal nuanced disparities less apparent at broader scales. Despite an overall favourable water security condition, spatial heterogeneity is still noticeable in the urban area of Campinas. The methodology highlights different aspects, such as vegetation cover, social green areas, and wastewater collection, which are inequitably distributed in the urban area. This integrated approach, linking inequality and water security assessment, has the potential to unveil specific needs within urban areas, helping guide targeted interventions to improve water security levels for all.

A study of the impact of digital financial inclusion on multidimensional food security in China

With frequent occurrences of global public events, the prices of national grains continue to soar. As one of the countries with the largest populations globally, China has always regarded food security as a fundamental cornerstone of its development. However, with the continuous emergence of factors such as urbanization, scarcity of land resources, and climate change, China’s food security faces unprecedented challenges. Hence, this study empirically examines the impact of digital inclusive finance on multi-dimensional food security based on panel data from 30 provinces in China from 2011–2020. The research found that China’s multi-dimensional food security level from 2011–2020 showed a stable yet rising trend, with the spatial pattern of each location generally consistent with the overall trend. The Theil index for China’s multi-dimensional food security showed an upward trend from 2011–2020. Digital inclusive finance can promote multi-dimensional food security. The breadth of coverage and depth of use of digital inclusive finance have a significant promoting effect on safeguarding multi-dimensional food security, while the degree of digitization has not played a promoting role. Digital inclusive finance mainly ensures multi-dimensional food security through two pathways: promoting urbanization levels and enhancing marketization levels.

Bridging the gap: coordinating equity and efficiency in older people care resource allocation in China

BackgroundWith the increasing global aging population, how to allocate older people care resources reasonably has become an increasingly urgent international issue. China, as the largest developing country, has made many efforts to actively respond to the challenges of an aging population. However, there are still problems with uneven allocation of older people care resources and low efficiency of allocation. Therefore, this study evaluates the regional differences and dynamic evolution of the equity and efficiency of older people care resource allocation in China from 2009 to 2020, and explores ways to change the current situation.MethodsThe data used in this study were derived from the “China Statistical Yearbook” and the “China Civil Affairs Statistical Yearbook” for the period of 2010–2021. Firstly, the equity of older people care resource allocation was measured using the Gini coefficient, the Theil index, the Older People Care Resource Density Index, and the Older People Care Resource Agglomeration Degree. Secondly, the dynamic Slack-Based Measure data envelopment analysis method was adopted to evaluate efficiency. Lastly, the Z-score is used to normalize the equity index and perform classification matching with the efficiency value. Spatial autocorrelation analysis and hotspot analysis were conducted using GIS technology to examine the dynamic evolution process of older people care resource allocation equity and efficiency, as well as their spatial distribution patterns and coordination across provinces from 2009 to 2020.ResultsThe equity analysis showed that the spatial distribution of various types of older people care resources was uneven, and the differences were mainly due to internal differences within each region, with the largest equity differences observed in western provinces. Currently, older people care resources are mainly concentrated in eastern regions, while the total amount of older people care resources in western regions and some central regions is relatively small, which cannot meet the older people care needs of residents. The efficiency analysis results showed that the efficiency of older people care resource allocation has been improving over the past 12 years, and in 2020, 77.42% of provinces were located on the efficiency frontier with an average efficiency value of 0.9396. Finally, the coordination analysis results showed that there were significant spatiotemporal differences in the equity and efficiency of older people care resources allocation.ConclusionWith the development of society and economy, the total amount and service capacity of older people care resources in China have greatly improved. However, there are still significant spatiotemporal differences in the equity and efficiency of older people care resource allocation. The development of older people care services in central and eastern provinces is unbalanced, and there is a polarization trend in terms of equity and efficiency of older people care resource allocation. Most provinces in western regions face the dual dilemma of inadequate older people care resources and low utilization efficiency. It is recommended that policymakers comprehensively consider population and geographic factors in different provinces, establish relevant allocation standards according to local conditions, improve the redistribution system, and focus on increasing the total amount of older people care resources in underdeveloped provinces while promoting resource flow.

Analysis of Regional Social–Economic Spatial Pattern and Evolution along the Beijing–Hangzhou Grand Canal

With the proposal of the Beijing–Hangzhou Grand Canal Cultural Belt, the Beijing–Hangzhou Grand Canal has become an indispensable component of China’s economic development pattern. Despite relatively high regional-economic-development levels along the canal, there still exists a common imbalance in regional development which will hinder the high-quality collaborative development of the region, highlighting the importance of measuring this disparity. This study adopts the district and county as spatial scales and selects five dimensions: economic growth, livelihood benefits, green ecology, innovation drive, and food guarantee in order to construct a comprehensive socio-economic index. Entropy weight method, Moran index, and Theil index analyses are used to examine the recent ten-year evolution laws in regional socio-economic spatial patterns along the Beijing–Hangzhou Grand Canal. Results indicate that socio-economic indicators designed for each dimension effectively measure both individual districts’ and counties’ economic situations as well as those of entire regions. In 2021, limited significance was observed regarding the level of regional economic agglomeration along the Grand Canal region, suggesting a tendency towards fragmented development rather than forming a well-coordinated model. Over the decade from 2011 to 2021, there was an increase in social and economic agglomeration. From a city unit perspective, developmental disparities among districts and counties within cities follow three distinct patterns. Cities at different stages of development can learn from each other’s models to enhance integration cooperation and collectively promote high-quality economic advancements in the Grand Canal region.

Research on Coupling Coordination of China’s Urban Resilience and Tourism Economy—Taking Yangtze River Delta City Cluster as an Example

Urban resilience provides the foundation and guarantee for the tourism economy, and the development of the tourism industry provides new opportunities and impetus for urban resilience. The coordinated development of urban resilience (UR) and the tourism economy (TE) contributes to the high-quality development of the regional economy. This study takes 27 cities in the Yangtze River Delta (YRD) urban agglomeration as an example. Various analytical techniques, including the entropy method, coupling coordination degree model (CCDM), kernel density estimation, Theil index, and obstacle degree model, are employed to investigate the spatiotemporal evolution patterns and influencing factors that affect the coupling coordination degree (CCD) between UR and TE. The findings indicate that: (1) The urban resilience and tourism economy exhibited an increasing trend denoted by “N” and “M”, respectively. (2) The coupling coordination level has undergone a development phase of “Moderate disorder–Bare coordination–Moderate disorder”. (3) The level of coordination has been enhanced, with intra-regional differences identified as the primary source of variation. (4) The number of Internet users, the number of students in institutions of higher learning, per capita public financial expenditure, science and technology expenditures as a share of fiscal expenditures, urban per capita disposable income, foreign exchange earnings from tourism, and the number of inbound tourists is the main factors affecting the CCD of urban resilience and tourism economy.

Assessing inequalities in urban water security through geospatial analysis

Water security, which is key for sustainable development, has been broadly investigated through different spatial scales, time frames and perspectives, as a multi-dimensional concept. Fast growth and the diversity of the urban environment add to the challenges of reaching good levels of water security in cities. Yet, few studies have focused on evaluating the heterogeneous distribution of water security in urban areas, which is a key step to highlight where inequalities in large cities are present and how to best guide interventions. The objective of this research is to investigate the spatial heterogeneity of urban water security as well as quantifying inequalities using the new assessment presented in this paper. A holistic indicator-based evaluation framework to intra-urban sectors of the city of Campinas in Brazil is applied, followed by an inequality analysis to describe the distribution of water security aspects. A spatial correlation analysis is then carried out to identify patterns for high inequality indicators. Results show that even though Campinas has established good overall water security conditions, spatial heterogeneity is still noticeable in the urban area. Quantification of inequality by the Theil index highlighted aspects, such as vegetation cover, social green areas, and wastewater collection, that are inequitably distributed in the urban area. The subsequent analysis of spatial patterns exposed areas on the outskirts of the city where infrastructure challenges and social vulnerability coincide. This novel approach has been therefore successfully validated in a city in Brazil, and it has been demonstrated that our water security assessment framework identifies what are the main water security challenges and where they are in the city. For the first time we show that associating spatial and inequality analysis with conventional evaluation of urban water security has the potential to help target areas in need and tackle specific water security issues in the urban area. This is crucial to inform urban planning and policy making for a sustainable and inclusive urban water management strategy.