22/11/2022 - 13:10 - 14:40
CC6.2 - DESIGUALDADES E ALIMENTAÇÃO |
40119 - SPATIAL INEQUITIES IN LIFE EXPECTANCY IN SMALL AREAS OF BUENOS AIRES, ARGENTINA 2015-2017
ANDRÉS TROTTA - INSTITUTE OF COLLECTIVE HEALTH, NATIONAL UNIVERSITY OF LANUS. BUENOS AIRES, ARGENTINA., USAMA BILAL - URBAN HEALTH COLLABORATIVE, DORNSIFE SCHOOL OF PUBLIC HEALTH, DREXEL UNIVERSITY. PHILADELPHIA, USA., BINOD ACHARYA - URBAN HEALTH COLLABORATIVE, DORNSIFE SCHOOL OF PUBLIC HEALTH, DREXEL UNIVERSITY. PHILADELPHIA, USA., HARRISON QUICK - URBAN HEALTH COLLABORATIVE, DORNSIFE SCHOOL OF PUBLIC HEALTH, DREXEL UNIVERSITY. PHILADELPHIA, USA., KARI MOORE - URBAN HEALTH COLLABORATIVE, DORNSIFE SCHOOL OF PUBLIC HEALTH, DREXEL UNIVERSITY. PHILADELPHIA, USA., MÓNICA SERENA PERNER - INSTITUTE OF COLLECTIVE HEALTH, NATIONAL UNIVERSITY OF LANUS. BUENOS AIRES, ARGENTINA., MARCIO ALAZRAQUI - INSTITUTE OF COLLECTIVE HEALTH, NATIONAL UNIVERSITY OF LANUS. BUENOS AIRES, ARGENTINA., ANA V DIEZ RRUX - URBAN HEALTH COLLABORATIVE, DORNSIFE SCHOOL OF PUBLIC HEALTH, DREXEL UNIVERSITY. PHILADELPHIA, USA.
Apresentação/Introdução
Studies of life expectancy (LE) in small areas of cities are relatively common in high-income countries, but rare in Latin American countries. Small area estimation (SAE) methods can help capture inequalities in LE between neighborhoods and quantify associations with socioeconomic characteristics.
Objetivos
To analyze the distribution and spatial patterning of life expectancy across small areas (fracciones censales) of Ciudad Autónoma de Buenos Aires (CABA), Argentina and its association with socioeconomic characteristics of these small areas.
Metodologia
As part of the SALURBAL project we used georeferenced death certificates in 2015-2017 for CABA, the capital of Argentina. We used a spatial Bayesian Poisson model using the TOPALS method to estimate age- and sex-specific mortality rates. We used life tables to estimate LE at birth and at ages 20, 40, and 60 for each neighborhood. We also obtained data on neighborhood socioeconomic characteristics from the 2010 census to analyze their associations with LE using linear regression models.
Resultados
Overall, LE at birth was higher for women (81.1 years) compared to men (76.7 years). We found wide variability between neighborhoods, with a 9.3-year gap (76.6 to 85.9) for women, and a 14.9-year gap (68.1 to 83.0) for men. We also observed a North (higher LE) – South (lower LE) spatial pattern. Better socioeconomic characteristics (higher educational attainment, school attendance, and access to water, and lower unemployment and overcrowding) were associated with higher LE. These patterns held for LE at 20, 40 and 60 years.
Conclusões/Considerações
We found large spatial inequalities in LE across neighborhoods of a large city in Latin America highlighting the importance of place-based policies to address this gap.
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