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OBJECTIVE: To assess the association of sociodemographic and environmental factors with the obesity occurrence in Argentina from a sex- and age-comparative perspective and a multilevel approach. DESIGN: Cross-sectional study based on secondary data from the National Survey of Chronic Diseases Risk Factors (CDRF) 2018, Argentina. Two-level logistic regression models stratified by sex and age were used. SETTING: The nationwide probabilistic sample of the CDRF survey and twenty-four geographical units. PARTICIPANTS: 16 410 adult people, living in Argentine towns of at least 5000 people, nested into 24 geographical units. Sex and age groups were defined as young (aged 18-44 years), middle-aged (45-64 years) and older (65 years and older) men and women. RESULTS: Single men (all age groups) and divorced/widowed men (aged 45 years or older) had a lower obesity risk compared to married ones. In the middle-aged group, men with higher education showed a lower risk than men with incomplete primary education. In young women, a marked social gradient by educational level was observed. A low-income level coupled with highly urbanised contexts represents an unfavourable scenario for young and middle-aged women. Having a multi-person household was a risk factor for obesity (OR = 1·26, P = 0·038) in middle-aged women. Contextual factors linked to the availability of socially constructed recreational resources and green spaces were associated with obesity among young adults. CONCLUSIONS: Socio-environmental determinants of obesity seem to operate differently according to sex and age in Argentina. This entails the need to address the obesity epidemic considering gender inequalities and the socio-environmental context at each stage of life.
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RESUMEN El objetivo de este estudio fue analizar las variaciones espaciotemporales de la mortalidad por COVID-19 en adultos mayores y de la vacunación contra la COVID-19 en esta población. Se utilizaron datos de defunciones por COVID-19 y de personas de 70 a más años inmunizadas con la primera dosis de vacunas contra esta enfermedad, en partidos de la provincia de Buenos Aires, desde el 29 de diciembre del 2020 al 30 de junio de 2021. Se emplearon técnicas de escaneo espaciotemporal para detectar conglomerados. Los partidos del Gran Buenos Aires que tuvieron mayor vacunación con la primera dosis de la vacuna Sputnik V en población de 70 a más años, entre mediados de marzo y principios de abril de 2021, coincidieron mayormente en registrar una disminución de la mortalidad en esta población, entre finales de abril y finales de junio de 2021. Este estudio mostró algunos indicios del impacto positivo de la aplicación de la primera dosis de la vacuna Sputnik V en el Gran Buenos Aires.
ABSTRACT The aim of this study was to analyze the spatiotemporal variations of COVID-19 mortality and vaccination against COVID-19 in older adults. We used data from deaths due to COVID-19 and persons aged 70 years and older immunized with the first dose of vaccines against this disease, from districts of the province of Buenos Aires, between December 29, 2020, and June 30, 2021. Spatiotemporal scanning techniques were used to detect clusters. The parties of Greater Buenos Aires that had the highest vaccination rate with the first dose of the Sputnik V vaccine in population aged 70 years and older, between mid-March and early April 2021, also registered a decrease in mortality in this population, between the end of April and the end of June 2021. This study showed some signs of the positive impact associated with the application of the first dose of Sputnik V vaccine in Greater Buenos Aires.
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Humanos , Masculino , Femenino , Adulto , Persona de Mediana Edad , Anciano , Vacunación Masiva , Mortalidad , Agrupamiento Espacio-Temporal , COVID-19 , Argentina , Programas de Inmunización , Infecciones por Coronavirus , Adulto , Aglomeración Urbana , Geografía Médica , Grupos de EdadRESUMEN
The agro-industrial production of genetically modified organisms uses great amounts of pesticides, close to cities, which generates growing concern due to the numerous evidence of their negative effects on health and the environment. In a context of the lack, or inaccessibility, of official data on crop dynamics and pesticide use, environmental indicators using satellite data are needed for the proper monitoring of peri-urban areas. The objective of this research is to make a crop proximity index using satellite information to assess and monitor peri-urban agro-industrial activity. Twenty cities in Argentina and ten in the United States were selected. The CPI index is designed to evaluate a city and its peri-urban areas as a whole by taking account of the land uses and factors that can potentially influence the proximity to agro-industrial activity to the population living in those cities. Agriculture factor was weighted by proximity or remoteness using perimeter rings from the urban edge. All the necessary data for the calculation of the CPI index were obtained through the classification and processing of Sentinel 2 satellite images with software and the Google Earth Engine platform. The results show a worrying situation, 90% of cities in Argentina and 80% in the United States have a negative CPI. Most of the cities examined are extremely close to extensive areas of crops, that use a high amount of pesticides and which do not have the protection of trees or buffer zones.
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Background: With 18.6% of total deaths due to malignant tumors in 2016, cancer is the second leading death cause in Argentina. While there is a broad consensus on common risk factors at the individual cancer level, those operating at a contextual level have been poorly studied in developing countries. The objective of our study was to identify socio-environmental patterns in Argentina (2010), emphasizing quality of life, and to explore their associations with the spatial distribution of cancer mortality in the country. Methods: The study was conducted in 525 geographical divisions nested into 24 provinces. Sex-specific crude and age-standardized mortality rates (ASMR) for cancer (2009-2011 period) were calculated. Empirically derived socio-environmental patterns were identified through principal-component factor analysis on a selected set of variables: an urban scale and 29 indicators of a quality of life index in Argentina for 2010. Two-level Poisson regression models were used to estimate associations between the ASMR and the continuous factor scores for socio-environmental patterns as covariates. A random intercept was included to account for spatial variability in the ASMR distribution using Stata software. Results: Four socio-environmental patterns were identified, termed "Contexts with urban-related resources or cultural capital", "Socioeconomically prosperous contexts", "Environments with anthropic exposures" and "Plains region" (cumulative explained variance=57%). High mortality rates were found in counties characterized by socioeconomically prosperous contexts (RR=1.025 in women; 1.088 in men) and plain landscapes (RR=1.057 and 1.117, respectively). Counties featuring urban or cultural resources demonstrated increased mortality in women (RR=1.015, 95%CI=1.005-1.025), whereas rising rates associated with environments having anthropic exposures (RR=1.008, 95%CI=1.001-1.016) were observed only for men. Conclusion: This study identified four characteristic socio-environmental patterns in Argentina which incorporate features of quality of life, accounting to some extent for the differential burden of cancer mortality in this country.
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Causas de Muerte , Exposición a Riesgos Ambientales/efectos adversos , Neoplasias/mortalidad , Calidad de Vida , Factores Socioeconómicos , Distribución por Edad , Argentina , Femenino , Estudios de Seguimiento , Humanos , Masculino , Neoplasias/etiología , Neoplasias/patología , Pronóstico , Factores de Riesgo , Tasa de SupervivenciaRESUMEN
En esta obra se investigan los principales resultados del proceso de fragmentación sufrido por la sociedad y el territorio argentinos en los últimos treinta años y, más específicamente, durante el período intercensal 1991-2001. A partir de la elaboración de un índice que incorpora las dimensiones socioeconómicas y ambientales más significativas del bienestar, se determinan los respectivos mapas y se indaga en sus factores de diferencisción...