Spatial disparity and structural inequality in disability patterns across Tianjin municipality: a multiple deprivation perspective

Reducing the spatial disparities and structural inequalities faced by disabled people is a global challenge in both developed and developing countries that requires an understanding of disability-driven deprivation. This study aims to develop and validate a conceptual framework for analysing the structural inequality and spatial disparity of disability-related deprivation. To achieve this goal, an Index of Disability-Related Multiple Deprivation (IDMD) based on six specific domains, including employment, education, marital status, health, services and barrier-free environments, is proposed. The IDMD was calculated at the sub-district level within the Tianjin municipality using aggregated registration information from the Tianjin Disability Database in 2020. Principal component analysis (PCA) was used to assign the weight of each indicator of IDMD. Moran I and LISA analysis were used to quantify the spatial disparity of IDMD across the municipality. Multi-Scale Geographically Weighted Regression (MGWR) was used to model the structural factors shaping the spatial disparity of disability-related deprivation in terms of gender, age, and disability types. Three key findings have been generated as follows. The spatial variability of IDMD revealed significant urban-rural disparity across the municipality, highlighting the difficulties faced by vulnerable and disadvantaged disabled people in rural areas. Men, working age groups and those with intellectual disability contributed most to the structural inequalities of IDMD. Thirdly, the location of greatest deprivation varied for different groups; working age groups faced the highest levels of deprivation in the urban centre, males faced the most deprivation in the urban fringe and those with intellectual, limb, visual, speech or mental disabilities were most deprived in rural areas. These findings reflect the complexity of structural factors affecting disability-related deprivation at the municipality scale. This study points to the need for informed, targeted welfare facilities planning and management strategies to improve spatial equity and social justice for disabled people

Emerging, transitory or residual ? One-person household in Viet Nam

BACKGROUND: The rise of one-person households in Viet Nam remains poorly documented, in spite of its significant growth since the 1990s and its relevance to the understanding of social and demographic change. OBJECTIVE: We aim to present a systematic analysis of the growing number of one-person households, interpret recent trends and describe the main characteristics of the population living alone. METHODS: Our research is drawn from the 2009 census. Cross-tabulations are followed by regression analysis modelling of the probability of living alone. A cluster analysis identifies the profiles of people in one-person households. Finally an in-depth analysis of the most vulnerable type of one-person households is done. RESULTS AND CONCLUSIONS: Our analysis stresses the heterogeneity of the population living alone, in which we can identify four distinct profiles. The largest cluster is comprised of elderly widows and widowers. It arguably constitutes the most fragile population segment, as illustrated by several health and economic indicators. The second cluster comprises a more heterogeneous population, but only composed of persons who have not moved during the last five years. The third and fourth clusters are made up of migrants. Along with age, marital status tends to be the primary factor explaining the probability of a person living alone in Viet Nam. However, the rise in one-person households may be as much related to the gradual changes in marital status, illustrated by delayed marriage, as to the increase in mobility and the relative weakening of traditional family patterns

Challenges to Economic Resiliency and Performance: Measuring the Regional Impacts of Rurality and Space

It is commonly observed that there are inequalities found in economic growth, development, and performance between different regions. Because of this, it is vital for regional planners to have knowledge to which economic problems are present (Armstrong and Taylor, 2000; Martin, 2005). With such knowledge, planners are able to tailor and implement regional policies in an informed manner that is better suited to address economic problems. Found in this work are two studies that contextualize separate economic problems which have been extensively discussed within regional sciences and rural studies. The first study seeks to assess how a county’s degree of rurality affects its capacity to resist and rebound from economic shocks. Rurality is a variable that challenging to define, but is nonetheless important to understand because identifying how regions can be rural provides necessary context for the justification of policy intervention (Cloke and Edwards, 1986; Beynon et al., 2016). We use county-level data from a series of federal agencies over the period of 2011 through 2015 to statistically estimate and visualize an urban-rural landscape of New England. Using this measure, we further test to see if a county’s degree of rurality had an impact on its relative recovery speed in employment growth. Over the same period of 2011 to 2015, we test how these counties recovered from two years and beyond after the Great Recession. The findings suggest overall a county’s degree of rurality corresponded with slower levels of recovery in terms of employment in comparison to overall U.S. levels. The second study seeks to explain how spatial factors such as market access and geographical remoteness influences a region’s differential economic performance. While the discussion of factors contributing to economic performance is expansive for large areal units like nations, there is a need for more understanding on how factors that dampen economic performance at a granular level can influence the greater region’s performance (Porter, 2003; Agarwal et al., 2009). We use data from the Census Bureau, National Park Service, and Google Geocoding Service in the one-year period of 2016 to: (1) estimate economic output as a proxy for performance in a system of equations, and (2) to see how such performance differentiates across geographic space. To approach this problem, we used a novel method of extracting and translating geographic data into distance measures at the census tract level to investigate how spatial factors influence economic performance. Overall, the findings from our jointly estimated system of equations highlight that larger distances to market access and remoteness negatively influences economic performance at the census tract level. Similarly, higher levels in variables such as workplace disability and the old-age dependency ratio had other dampening impacts

Four futures of Europe

Europe is at a crossroads. The enlargement with ten new members forces the European Union to reform its decision making process and to reconsider its policies. At the same time, developments such as ageing force EU member states to reform their welfare states. Read also the accompanying press release .Where will this bring the European Union and its members states ten or twenty years from now? And how should policy makers deal with this uncertainty when deciding about policies with long-lasting consequences? This study develops four scenarios on the future of Europe. They serve as tools for analysing these questions. Moreover, the study elaborates on the policy agenda of international organisations and European governments in response to the various challenges during the next two decades.

17-09 Assessing the Impact of Air Pollution on Public Health Along Transit Routes

Transportation sources account for a large proportion of the pollutants found in most urban areas. Also, transportation activity and intensity appear likely to contribute to the risk of respiratory disease occurrence. This research investigates the impacts of transportation, urban design and socioeconomic characteristics on the risk of air pollution-related respiratory diseases in two of the biggest MSAs (Metropolitan Statistical Areas) in the US, Dallas-Fort Worth (DFW) and Los Angeles at the block group (BG) level, by considering the US Environmental Protection Agency’s respiratory hazard quotient (RHQ) as the dependent variable. The researchers identify thirty candidate indicators of disease risk from previous studies and use them as independent variables in the model. The study applies a three-step modeling including Principal Component Analysis (PCA), Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR) to reach the final model. The results of this study demonstrate strong spatial correlations in the variability in both MSAs which help explain the impact of the indicators such as socioeconomic characteristics, transit access to jobs, and automobile access on the risk of respiratory diseases. The populations living in areas with higher transit access to jobs in urbanized areas and greater automobile access in more rural areas appear more prone to respiratory diseases after controlling for demographic characteristics

Longitudinal Aging Study in India: Vision, Design, Implementation, and Some Early Results

India is poised to experience a dramatic rise in its aging population in coming decades, yet comprehensive research and effective policy to confront this transition are lacking. According to projections constructed by the United Nations Population Division, the share of Indians aged 60 and over will increase from 8% today to 19% by 2050 (representing 323 million people, more than the entire US population in 2011). This demographic shift will pose significant challenges. India’s traditional reliance on private family networks to provide older people with care, companionship, and financial support will be stressed not only by the increasing number of aging Indians who rely on it, but also by changing household dynamics and patterns of spatial mobility among younger family members. The Longitudinal Aging Study in India (LASI) is intended to inform the design and expansion of a new generation of institutions – public and private – for the care and support of India’s population of older people by providing comprehensive data to the scientific and policy community. LASI is an evidence base for analyzing the (1) health, (2) economic and financial resources, and (3) living arrangements and social connections of older Indians. It enhances opportunities for cross-national analysis by adding India to the growing number of countries with harmonized data on their older populations. LASI surveys will be carried out every two years, providing longitudinal data to support research and policy development. This paper provides an overview of the conception and content of the 2010 LASI pilot survey that was conducted in four states: Punjab, Rajasthan, Karnataka, and Kerala. We highlight key aspects of the field work, such as response rates and interview duration, and discuss the breadth and quality of the economic, health, and social data collected. We pay close attention to the cultural and geographic diversity LASI is able to capture, and bring to light interesting patterns in, and relationships among, measures of health, social connectedness, labor force participation, and hardship among the elderly.aging, longitudinal, India

How important is access to jobs? Old question - improved answer

We study the impact of job proximity on individual employment and earnings. The analysis exploits a Swedish refugee dispersal policy to get exogenous variation in individual locations. Using very detailed data on the exact location of all residences and workplaces in Sweden, we find that having been placed in a location with poor job access in 1990–91 adversely affected employment in 1999. Doubling the number of jobs in the initial location in 1990–91 is associated with 2.9 percentage points higher employment probability in 1999. The analysis suggests that residential sorting leads to underestimation of the impact of job access.Spatial mismatch; endogenous location; natural experiment

The impact of disability-related deprivation on employment opportunity at the neighborhood level: does family socioeconomic status matter?

IntroductionDifficulties in attaining employment significantly contribute to socioeconomic poverty among individuals with disabilities. However, our understanding of how socioeconomic deprivation experienced by individuals and families with disabilities influences employment opportunities remains incomplete. This study aims to explore the relationship between index of disability-related multiple deprivation (IDMD) and employment opportunities (EMPO), while also investigating the role of family socioeconomic status (FSES) in shaping this relation.MethodsThis study explores the heterogeneous effects of IDMD, FSES, and the interaction between IDMD*FSES on EMPO among four disabled population groups categorized by IDMD and FSES.ResultsResults reveal that IDMD has a significant negative impact on EMPO, suggesting that persons with disabilities are confronted with a poverty trap resulting from the relationship between IDMD and EMPO. Furthermore, FSES demonstrates an effective moderating role in the IDMD-EMPO relationship, with the greatest impact observed among disabled population groups characterized by high IDMD and low FSES.DiscussionThe findings suggest that family-level support is crucial for vulnerable groups of disabled individuals to overcome the poverty trap, surpassing the reliance on individual-level assistance alone. This study supports a paradigm shift in comprehending disability-related deprivation by acknowledging its association with families, thereby presenting opportunities to enhance the welfare of people with disabilities