Search Results (3)

Understanding multidimensional deprivation requires consideration not only of who experiences overlapping disadvantages but also of how those disadvantages vary geographically. This study provides a comprehensive descriptive assessment of geographic variation in multidimensional deprivation across the United States using pooled 2022–2023 American Community Survey (ACS) Public Use Microdata Sample data and a Multidimensional Deprivation Index (MDI) constructed using the Alkire–Foster methodology. The MDI incorporates eight indicators spanning four equally weighted dimensions of well-being: economic security, education, health, and housing. Variation is examined across four nested geographic scales—Census regions, Census divisions, states, and all 2487 Public Use Microdata Areas (PUMAs)—using the Headcount Ratio (H), Average Deprivation Intensity (A), and the MDI. The results reveal substantial geographic differences in multidimensional deprivation across the United States, with progressively finer geographic scales revealing increasingly localized patterns. Geographic areas with similar overall MDI values often differ substantially in the composition of deprivation, underscoring the importance of examining the composition as well as the overall level of deprivation. Across all geographic scales, differences in multidimensional deprivation primarily reflect variation in deprivation incidence rather than deprivation intensity, while the PUMA-level analysis suggests that important local variation is obscured by broader regional and state averages. The principal contribution of this study is its integrated multiscale framework. Rather than developing a new deprivation measure or evaluating formal spatial dependence, the analysis applies an established Alkire–Foster methodology to recent nationally representative ACS microdata. This framework provides a consistent descriptive assessment of multidimensional deprivation across multiple nested geographic scales. The findings establish a descriptive empirical benchmark for geographically informed policy discussions and for demonstrating that both the level and composition of multidimensional deprivation vary systematically across geographic scales and that important local variation is obscured by broader regional and state averages. Full article

Myotonic dystrophy type I (MDI) is the most common muscular dystrophy in adults. The main objectives of this study were to determine the prevalence of MDI in the Community of Madrid (CM) (Spain) and to analyze the use of public healthcare services; a population-based cross-sectional descriptive study was carried out on patients with MDI in CM and data were obtained from a population-based registry (2010–2017). A total of 1101 patients were studied (49.1% women) with average age of 47.8 years; the prevalence of MDI was 14.4/100,000 inhabitants. In the women lineal regression model for hospital admissions, being in the fourth quartile of the deprivation index, was a risk factor (regression coef (rc): 0.80; 95%CI 0.25–1.37). In the overall multiple lineal regression model for primary health care (PHC) attendance, being a woman increased the probability of having a higher number of consultations (rc: 3.99; 95%CI: 3.95–5.04), as did being in the fourth quartile of the deprivation index (rc: 2.10; 95%CI: 0.58–3.63); having received influenza vaccines was a protective factor (rc: −0.46; 95%CI: −0.66–(−0.25)). The prevalence of MDI in the CM is high compared to other settings. Moreover, having any level of risk stratification of becoming ill (high, medium or low) has a positive association with increased PHC consultations and hospital admissions. Full article

Addis Ababa is a metropolitan area faced with the challenges of Ethiopia’s urbanization, such as poverty, unemployment, informal settlements, an acute housing shortage, and environmental hazards. Yet, the non-practicality of area-based policy using the Multiple Deprivation Index (MDI) exacerbates the polarization of poverty and spatial inequality to create a divided city. The study developed the MDI for 2007 and 2016. The study’s objective was to justify the area-based policy by analyzing the overlaps of deprivations based on the relationship of pertinent indicators and components, the spatial pattern of inequality and deprivations, and the relationship of deprivation with population size and density. The findings of the study were triangulated and validated with the deductive theoretical, empirical, and SDG frameworks to replicate external validity. The research design included both descriptive and correlational methods. The inductively derived pattern using PCA (principal component analysis) and LISA (local spatial association index) of MDI components revealed spatial inequality and poverty polarization. The index of concentrated poverty was revealed by global spatial autocorrelation. The statistical and spatial trend analysis revealed concentrated poverty, especially in the inner-city slums and the peri-urban informal settlements. Most of the findings conformed to deductive theoretical and SDG frameworks, while the analysis of MDI indicators and components revealed additional slum indicators and the relevance of integrating other SDG indicators with SDG 11 for realizing sustainable urbanization. Due to spatial inequality, patterns of concentrated poverty, a large, deprived population, and easing future urbanization challenges, the study rationalized area-based policy for reducing inequality and poverty polarization. Full article