There is extensive evidence on the consequences of lacking safe water on the health and well-being of populations, which justifies the need to advance in the construction of new measurement instruments. The objective of this study is to evaluate the face validity of the HWISE Scale to measure water insecurity in Argentina. Four focus groups were implemented with 24 women residing in vulnerable areas of Greater Buenos Aires, to whom the scale was administered. The results reflect the breadth of dimensions of the phenomenon in the participants’ discourse, and the items’ wording was understood. The HWISE scale represents the phenomenon from the perspective of women in situations of social vulnerability but requires adjustments. The ítems are understood and cover the comprehensiveness of the phenomenon, although areas for improving its precision are identified.

Introduction: Mortality in the first months of life is a key demographic indicator for the analysis of socioeconomic development, which in the Argentine case reflects large provincial asymmetries due to socioeconomic, health and environmental factors. Objectives: This article analyzes the evolution of infant mortality rates (IMR) in Argentina in a recent time frame (2016-2022) and examines the social and environmental factors associated with its prevalence at the provincial level. Methodology: A longitudinal ecological study using birth and death data from the National Ministry of Health and the Permanent Household Survey (Total Urbano, INDEC). Annual rates and provincial coefficients of variation were calculated, and multiple linear regression models were applied to estimate associations with socioeconomic variables and basic infrastructure. Results: The IMR showed a downward trend, with persistent regional inequalities. The lowest rates were recorded in the south (Tierra del Fuego, Neuquén), and the highest in the northeast (Formosa, Corrientes). Neonatal mortality was mainly associated with maternal age, quality of health infrastructure, and exposure to flood zones, while postneonatal mortality was more closely associated with maternal educational level, access to mains gas, and sanitation conditions. In both cases, better basic services were associated with lower rates. Conclusions: The incorporation of housing and basic services indicators into the analysis of infant mortality provides novel evidence for Argentina. Political policies to improve health infrastructure are required to reduce territorial asymmetries.

La privación medioambiental residencial constituye una dimensión relevante aunque frecuentemente subrepresentada en el análisis de las desigualdades sociales y urbanas. El objetivo de este artículo es proponer y aplicar una estrategia empírica para medir dicha privación a partir de datos de encuestas de hogares, contribuyendo a los debates sobre la incorporación de la dimensión ambiental en enfoques de pobreza multidimensional. Se utilizan datos de la Encuesta de la Deuda Social Argentina (ODSA/UCA) para el período 2017–2023 y se emplea Análisis de Componentes Principales para Datos Categóricos (CATPCA) con el fin de identificar la estructura empírica de la privación medioambiental. La metodología permite distinguir dos dimensiones principales -carencias estructurales del hábitat y exposición a riesgos ambientales del entorno- a partir de las cuales se construye un índice sintético continuo. Los resultados indican que la privación medioambiental se asocia significativamente con la posición socioeconómica de los hogares y con la condición de pobreza, así como con características del entorno urbano -en particular el tipo de trazado residencial- incluso al controlar por variables sociodemográficas y temporales. La evidencia muestra, además, que la dimensión ambiental del hábitat no se reduce a déficits de infraestructura doméstica, sino que incorpora exposiciones territoriales a riesgos ambientales. Entre las limitaciones del estudio se señala que las encuestas multipropósito facilitan la identificación de patrones estructurales de privación ambiental, pero presentan restricciones para captar procesos ambientales dinámicos o experienciales, como la intensidad o variabilidad de ciertos riesgos. Abstract Residential environmental deprivation is a relevant, though frequently underrepresented, dimension in the analysis of social and urban inequalities. This article proposes and applies an empirical strategy to measure housing environmental deprivation using household survey data that may contribute to debates on incorporating the environmental dimension into multidimensional poverty approaches. Data from the Argentine Social Debt Survey (ODSA/UCA) for the period 2017–2023 are used, and Principal Component Analysis for Categorical Data (CATPCA) is employed to identify the empirical structure of environmental deprivation. The methodology distinguishes two main dimensions -structural deficiencies in the habitat and exposure to environmental risks in the residential surroundings- from which a continuous synthetic index is constructed. Results show that environmental deprivation is significantly associated with household socioeconomic status and poverty as well as with urban environment characteristics, particularly the type of residential layout, even after controlling for sociodemographic and temporal variables. The evidence also indicates that the environmental dimension of habitat is not limited to deficits in domestic infrastructure but incorporates territorial exposure to environmental risks. Among the study's limitations, multipurpose surveys facilitate the identification of structural patterns of environmental deprivation but have limited capacity to capture dynamic or experiential environmental processes, such as the intensity or variability of certain risks.

The objective is to evaluate the validity and reliability of the Household Water Insecurity Experiences (HWISE) Scale as a tool to assess the experiences of households and the Argentine population regarding insecurity of access to water. Addressing water insecurity is critical for advancing several Sustainable Development Goals (SDGs), particularly SDG 6 (Clean Water and Sanitation), SDG 3 (Good Health and Well-Being), and SDG 1 (No Poverty), given the strong links between access to safe water, health, and poverty reduction. The scale was administered as part of the Argentine Social Debt Survey (EDSA), on a probabilistic sample of 5799 households. The HWISE Scale demonstrated high reliability both overall and at the item level (Cronbach’s alpha of 0.95 at a total level and greater than 0.94 for each of the items) and criterion validity in terms of correlation with a broad set of indicators: social deprivations, sanitary infrastructure, food insecurity, and psychological health. Finally, the scale showed internal consistency, with a total omega coefficient value of 0.96, suggesting that all scale indicators refer to the same concept of deprivation in water access. In sum, the HWISE Scale applied to the case of Argentina is deemed appropriate for estimating household water insecurity.

Este estudio estima la pobreza multidimensional extrema por localidades y departamentos de los hogares argentinos en 2022, definida como el riesgo de concentración de inseguridad alimentaria en hogares particulares. A partir de un diseño que combina la Encuesta de la Deuda Social Argentina (EDSA-UCA) y el Censo Nacional de Población, Hogares y Viviendas 2022, se identificaron variables clave mediante un modelo de regresión logística y se construyó un Índice de Pobreza Multidimensional Extrema (IPME) en escala 0 a 100, aplicable a niveles de radio censal, departamento, provincia y región. El IPME integra dimensiones de condiciones materiales de la vivienda, acceso a servicios básicos, composición sociodemográfica, nivel educativo del jefe de hogar, situación laboral y región de residencia. Los resultados evidencian un patrón territorial persistente: las regiones Noroeste (NOA) y Noreste (NEA) presentan los niveles más altos de pobreza multidimensional extrema (39,5 y 38,1 respectivamente), mientras que la Patagonia registra el valor más bajo (29,6). Se observa una fuerte asociación entre mayor pobreza multidimensional extrema y mayor presencia de hogares con niños, niñas y adolescentes (NNyA), particularmente en departamentos con alta ruralidad. El índice permite localizar núcleos de vulnerabilidad estructural y constituye una herramienta para el análisis territorial de desigualdades.