Search Results (90)

The transition toward integrated urban–rural development represents a complex socio-technical challenge in post-poverty alleviation China. This study examines how the reform of agricultural service systems—especially the rollout of full-process socialization services—reshapes urban–rural integration by embedding new institutional, technological, and organizational structures into rural production. Drawing on staggered provincial pilot programs, we apply a double machine learning framework to assess the causal impact of service reform on the urban–rural income gap, labor reallocation, and agricultural productivity. Results show that agricultural socialization services enhance systemic efficiency by reducing labor bottlenecks, increasing technology diffusion, and fostering large-scale coordination in agricultural operations. These effects are most pronounced in provinces with stronger institutional capacity and higher levels of mechanization. The findings highlight agricultural service reform as a systemic intervention that alters resource allocation logics, drives institutional change, and fosters structural convergence across urban and rural domains. This research contributes to the understanding of agricultural modernization as a systems-engineered solution for regional inequality. Full article

The Roma population is one of Europe’s largest ethnic minorities, often living in inadequate living conditions, worse than those of the majority population. They frequently lack access to essential services, even in high-income countries. This lack of basic services—particularly in combination with proximity to (stray) animals and human and solid waste—significantly increases environmental health risks, and leads to a higher rate of endoparasitic infections. Our study sheds light on the living conditions and health situation in Roma communities in Slovakia, focusing on the prevalence of intestinal endoparasitic infections across various settlement localisations. It highlights disparities and challenges in access to safe drinking water, sanitation, and hygiene (WASH) and other potentially disease-exposing factors among these marginalised populations. This study combines a comprehensive review of living conditions as per national data provided through the Atlas of Roma communities with an analysis of empirical data on parasitological infection rates in humans, animals, and the environment in settlements, applying descriptive statistical methods. It is the first study in Europe to provide detailed insights into how living conditions vary and cause health risks across Roma settlements, ranging from those integrated within villages (inside, urban), to those isolated on the outskirts (edge, sub-urban) or outside villages (natural/rural). Our study shows clear disparities in access to services, and in health outcomes, based on where people live. Our findings underscore the fact that (i) place—geographical centrality in particular—in an already challenged population group plays a major role in health inequalities and disease exposure, as well as (ii) the urgent need for more current and comprehensive data. Our study highlights persistent disparities in living conditions within high-income countries and stresses the need for greater attention and more sensitive targeted health-promoting approaches with marginalised communities in Europe that take into consideration any and all of the humans, ecology, and animals affected (=One Health). Full article

Enhancing human well-being is a core priority of the Sustainable Development Goals. Understanding urban–rural well-being disparities is crucial for bridging gaps and improving social harmony. However, most existing studies focus on either urban or rural residents’ well-being, neglecting their disparities. This study quantified and compared the spatiotemporal patterns of the well-being of urban and rural residents in the Yangtze River Delta (YRD) urban agglomeration from 2000 to 2020 using the human development index (HDI). Results show the following: (1) Urban and rural well-being improved markedly from 2000 to 2020, with urban HDI increasing from 0.66 to 0.83 and rural HDI from 0.55 to 0.74. (2) Urban education and rural income inequalities were more pronounced, with the average Gini coefficients over 2000–2020 more than threefold and twofold those of urban and rural health, respectively. (3) Although disparities existed between urban and rural well-being, rural HDI had grown faster between 2000 and 2020, narrowing the urban–rural gap. From 2000 to 2020, the growth rate for rural HDI (34.55%) exceeded that for urban HDI (27.13%). To foster the shared urban and rural well-being, this study recommends diversifying rural industries, optimizing educational resources, and enhancing rural healthcare infrastructure in the YRD and beyond. Full article

Background: Adherence to iron supplementation is influenced by systemic barriers, including poor healthcare infrastructure, shortage of healthcare providers, and limited access to antenatal care (ANC) services. These challenges are more pronounced in rural areas. However, evidence on urban–rural disparities in non-adherence to iron supplementation remains limited, particularly in sub-Saharan Africa. This study examined these regional differences, stratified by income levels and national contexts. Method: This analysis utilised Demographic Health Survey (DHS) data conducted between 2015 and 2023 from 26 sub-Saharan African countries, including 287,642 women from urban (n = 91,566) and rural areas (n = 196,076). The outcome of this study was non-adherence to iron supplementation, defined as taking iron supplementation for less than 90 days during pregnancy. This study examines urban–rural differences in non-adherence stratified by country income levels based on World Bank 2022 income classifications and national context. A chi-square test was used to assess urban–rural differences, with a p-value of <0.05 considered statistically significant. Results: Non-adherence was significantly higher in rural areas (68.42%) than in urban areas (51.32%) (p < 0.001), with the disparity more pronounced in low-income countries (LICs). Ethiopia, Madagascar, Uganda, and Burundi were among the countries with the highest rural non-adherence, reflecting severe poverty and limited access to ANC. In contrast, Zimbabwe showed an inverse trend, where rural adherence was higher than urban. Conclusions: Rural sub-Saharan Africa has significantly higher non-adherence to iron supplementation, particularly in LICs, likely driven by systemic barriers such as poor infrastructure and limited access to healthcare. This non-adherence in rural areas undermines efforts to improve pregnancy and birth outcomes across the region. Targeted interventions, like those in Zimbabwe, can help address these inequities and improve maternal health outcomes. Full article

Background: Health inequality is seen as a challenge for implementing the Healthy China Strategy. This study analyzes the income-related health inequality among urban–rural resident basic medical insurance (URRBMI) participants. Methods: This study utilized data from the 2019 China Household Finance Survey (CHFS), and the concentration index (CI) was employed to estimate the effects of income-related health inequality on participants. Results: Our findings provide clear evidence that health inequality among participants has fluctuated—narrowing, widening, and then narrowing again—in the areas of the contribution, medical treatment, and reimbursement of URRBMI, respectively. Overall, the analysis indicates a widening of health inequality post-reimbursement, with results remaining consistent. A heterogeneity analysis shows that health inequality is most pronounced among women and those with less than a middle school education. Finally, our study reveals a pro-rich trend in the actual utilization of medical services among participants, with persistent disparities in outpatient and inpatient service usage even after standardization, further exacerbating income-related health inequality. Conclusions: We recommend that the URRBMI design take participants’ income levels into account, with policies favoring disadvantaged individuals to enhance their medical security, improve access to healthcare services, and ultimately reduce health inequality. Full article

Objectives: Survival from lung cancer is worse in the UK than in some other countries, with late stage at diagnosis implicated in poor prognosis. The route and referral urgency by which patients obtain a diagnosis influence outcomes. This study investigated whether socio-demographic factors are associated with lung cancer routes to diagnosis in England. Materials and Methods: A total of 181,763 primary invasive lung cancers (ICD-10 C34.0-C34.9) diagnosed from 1 January 2012 to 31 December 2016 were abstracted from the English National Cancer Registration Database. Multivariable logistic regression was used to examine associations between patients’ socio-demographic characteristics and likelihood (adjusted odds ratios) of (i) emergency presentation versus all primary care-initiated routes and (ii) urgent (“two-week wait”/2WW) versus standard primary care-initiated referral. Models included the following factors: deprivation quintile of area of residence at diagnosis (IMD income domain); sex; age; ethnic group; rural/urban residence; and (in the emergency model) region. Results: Socio-demographic variations in diagnosis routes were observed. Patients presenting as emergencies (35.2%) were more likely to be 80 years of age or older, female, of non-White ethnicity, and resident in areas of greater deprivation or the London region. In contrast, 2WW patients (28.3%) were more likely to be aged between 50 and 69 years old, of White ethnicity, and resident in an area of greater deprivation or resident outside of an urban centre; diagnosis through 2WW did not vary by sex. Conclusions: Routes to diagnosis are subject to distinct socio-demographic patterning. Action is needed to ensure that new referral guidelines and lung cancer screening roll-out do not widen socio-demographic inequalities in diagnosis. Full article

The choice of carbon inequality metrics can significantly influence demand-side mitigation policies and their equity outcomes. We propose integrated carbon inequality metrics, including juxtaposing carbon inequality with economic inequality, disparity ratios across income and age groups, and structural income–urbanization inequality patterns. We then apply these new metrics and use the household expenditure survey data from China Family Panel Studies as a case study to examine household consumption-based carbon emissions in China. We assess the extent to which household consumption patterns, household expenditure, age, and urbanization contribute to the gap in per-capita household carbon footprints (CF) across income groups. We find that in relative terms, the top 20% income group accounts for 38% of total emissions, whereas the bottom 20% emit about 8% in China. Per-capita CFs vary slightly widely in their inequality than expenditure. The CF disparity ratios of all eight consumption categories across provinces concentrate around 4.5. CF disparity ratios of households with elderly members range from 1 to 3 and decrease with increasing household size. Rural CF-Gini exhibit a slightly wider range (0.15 to 0.52) than urban CF-Gini (0.16 to 0.42). Per capita CF of urban inhabitants was substantially larger than that of the rural ones, with 8.83 tCO₂ per capita in urban regions vs. 2.68 tCO₂ in rural regions. This study provides a nuanced understanding of within-country disparities to inform equitable demand-side mitigation solutions. Full article

The impact of spatial structure on the Urban-Rural income gap varies across regions and scales. Much of the current literature focuses on urban agglomerations, highlighting the need for more in-depth exploration of specific regions. Using LandScan population data, this paper investigates urban spatial structure from the perspective of monocentricity and polycentricity, investigating their respective impacts and mechanisms on the Urban-Rural income gap in Northeast China. The findings are as follows: (1) The development of a monocentric spatial structure in Northeast China significantly reduces the Urban-Rural income gap, a conclusion verified through robustness testing. (2) A mediation effect test confirms that this spatial structure reduces the gap by increasing urban labor productivity. (3) The urban spatial structure of Northeast China also has positive spillover effects, reducing income inequality between urban and rural areas in neighboring regions. Further exploration of the relationship between Urban-Rural income inequality and spatial structure is crucial for achieving shared prosperity. Additionally, this research provides policy support for developing a novel framework for land use planning and conservation. Full article

An in-depth understanding of the impact of green innovation on the urban–rural income gap is essential for developing countries seeking to address urban–rural imbalances and promote sustainable economic development. This study focuses on China, utilizing provincial panel data from 2007 to 2022, and employs the two-way fixed effects model, the mediating effects model, and the moderating effects model. The study’s key findings are: (1) Green innovation positively reduces the urban–rural income gap. Specifically, the regression results indicate that a one-unit increase in green innovation corresponds to a 0.017-unit reduction in the urban–rural income gap. (2) The heterogeneity analysis reveals that the effect of green innovation on the urban–rural income gap is more pronounced in regions with higher levels of economic development, in non-food-producing areas, and when green utility patents are adopted. Additionally, green innovation narrows the urban–rural income gap predominantly in high-skill regions. (3) Examining the influencing mechanism confirms that green innovation reduces the urban–rural income gap by promoting population urbanization, eco-urbanization, labor force restructuring, and mitigating wage income inequality. (4) The moderating effects analysis indicates that environmental pollution exacerbates the impact of green innovation on the urban–rural income gap; specifically, higher levels of environmental pollution amplify the effect of green innovation in reducing the gap. These findings offer valuable insights for addressing urban–rural income inequality and fostering sustainable socio-economic development in developing countries. Full article

The development of digital infrastructure plays a crucial role in addressing regional disparities, especially in bridging urban–rural gaps. This paper evaluates the impact of the “Broadband China Strategy” (BCS), which exogenously accelerated broadband infrastructure expansion in both urban and rural areas. Using a staggered difference-in-differences (DID) approach, we assess the long-term effects of broadband adoption on labor market outcomes. Our findings show that BCS increased rural wages by 7% to 9%, with no significant impact on urban wages. The wage increase in rural areas is primarily driven by job creation and human capital accumulation, both of which contribute to narrowing the urban–rural wage gap. Additionally, the study uncovers heterogeneity in BCS effects, with stronger impacts observed in underdeveloped regions and among vulnerable groups. These results highlight that targeted digital infrastructure initiatives like BCS can help reduce urban–rural income inequality and promote more inclusive economic growth. Full article

The economic inequalities impede the equal distribution of water among various household groups, potentially leading to inequal access to this vital resource. By integrating a multi-regional input–output model with household expenditure, we investigate the water footprint (WF) for ten income groups in each of the provinces and evaluate water inequality among regions, households, and expenditure categories comprehensively. Our findings reveal significant disparities in water footprints, with urban households exhibiting nearly three times the WF of rural residents. Wealthier eastern provinces show higher per capita consumption-based WFs compared to the less developed western regions. The interregional trade exacerbates water inequality because water-intensive goods are produced in less developed regions and are being consumed in more developed provinces. This study underscores the importance of targeted policies to address water inequality, achieve sustainable water management, and promote equitable water use in the face of increasing water demand and supply imbalances. Full article

Income inequality and carbon emission are two critical challenges that need to be solved to achieve SDGs. Unfortunately, few studies have explored the effect of urban–rural income inequality (URII) on carbon emission performance (CEP) from a holistic view that integrates local and adjacent hierarchies. Utilizing provincial data spanning from 2005 to 2021 in China, this paper examines the mechanism and influence of URII on CEP by using the spatial Durbin model and a mediating effect model. The results indicate that URII and CEP display significant spatial agglomeration characteristics. URII can inhibit the CEP, which also exerts a negative spatial spillover effect on CEP. URII can not only directly affect CEP but also indirectly influence it by increasing energy consumption and widening the urban–rural consumption gap. The negative effect of URII on CEP demonstrates regional variability, with a particularly prominent effect observed in the eastern region. Full article

Carbon emission inequality has become a critical factor constraining the coordinated development of socio-economic systems and the natural environment. This inequality exacerbates the disparity in carbon emissions across regions, hindering efforts to achieve sustainable development and environmental justice. Previous research has primarily focused on the structure of carbon footprints and their influencing factors, but there has been limited quantitative research on carbon emission inequality, particularly from a multi-scale perspective. This study constructs a 250 m-high-resolution consumption-based carbon footprint grid for China and uses the Theil index to reveal significant spatial inequalities in carbon footprints. The results indicate that smaller-scale analyses better reveal the spatiotemporal heterogeneity of carbon footprints within regions. At the county level, carbon footprints exhibit significant inequalities, with hotspots concentrated in regions such as Beijing–Tianjin–Hebei, the Yangtze River Delta, and the Pearl River Delta. The top 5% of areas with the highest carbon footprints (139 cities) contributed 19.6% of the national total, indicating a concentration in a few large cities. The decomposition of the Theil index shows that county-level cities contributed 55% of the national carbon inequality. The study also reveals the complex relationship between carbon footprints and income, as well as urban-rural disparities. The underdeveloped central and western regions exhibit a pronounced spatial lag effect, with the growth rate of carbon footprints in rural areas surpassing that of urban areas. Carbon footprints in impoverished areas and inter-provincial marginal areas overlap significantly with low-emission zones, demonstrating characteristics of “low-carbon growth”. To achieve carbon peak and carbon neutrality targets, China must adopt comprehensive measures to reduce carbon footprints and their inequalities, including strengthening multi-scale carbon inequality monitoring, implementing differentiated carbon reduction policies, and promoting coordinated emission reduction development at the county level. Full article

In many countries, the urban–rural income inequality affects healthy and sustainable economic development and is a pressing issue that requires immediate attention. As a new industrial development model, rural industrial convergence can provide new ideas and impetus for alleviating the urban–rural income inequality. This study, drawing on provincial panel data from China spanning 2010 to 2022, used the entropy method and Theil index to measure the rural industrial convergence and the urban–rural income inequality, respectively, and empirically tested the effect and mechanism of rural industrial convergence on the urban–rural income inequality. The results showed the following: (1) Rural industrial convergence had a notable impact on alleviating the urban–rural income inequality. (2) Rural industrial convergence could help reduce the urban–rural income inequality by increasing the scale of land operation. (3) The government attention to green development could positively moderate the impact of rural industrial convergence on the urban–rural income inequality; the deeper the government attention to green development, the greater the role rural industrial convergence played in alleviating the urban–rural income inequality. (4) There was a threshold effect in the alleviating effect of rural industrial convergence on the urban–rural income inequality, which was gradually strengthened when the growth of the digital economy and the enhancement of the business environment were beyond the threshold point. (5) Rural industrial convergence also had significant spatial spillover effects on adjacent regions. Overall, the findings of this study enrich the research on the impact of rural industrial convergence on the urban–rural income inequality and provide insights for other similar countries. Full article

This paper presents a multivariate analysis of urban and rural residential water consumption from 2010 to 2020 using an input–output model considering consumption and income. We employed structural decomposition analysis (SDA) and structural path analysis (SPA) to identify the main drivers and pathways. The Water-Gini (W-Gini) coefficient was used to quantify inequalities in water consumption. The results showed that rural water consumption exceeded urban consumption starting in 2012, reaching 1.8 times the urban level by 2020, with Agriculture (S1) being the largest contributor. SDA indicated that the decrease in urban consumption was primarily due to the intensity effect. In SPA, the first-order path accounted for over 70% of total consumption, with urban contributions linked to “residential income → S2-Health care and medical services (M7)”. For rural areas, “residential income → F1-Food (M1)” contributed to 40% of water consumption in the first-order path, reflecting increased consumption in the middle sector. The W-Gini coefficient rose to 0.4 in 2020, driven by the income side, particularly in Agriculture (S1), which had a W-Gini of 0.61. These variations in water consumption highlight the need for policy considerations, especially regarding rural income. Full article