Document Type : Research Articles
Authors
1
Institute of Health Sciences Research (INICSA), Faculty of Medical Sciences, National Scientific and Technical Research Council (CONICET), University of Córdoba, Tandil, Argentina.
2
Biostatistics Unit, School of Nutrition, Faculty of Medical Sciences, University of Córdoba, Tandil, Argentina.
3
Institute of Geography, History and Social Sciences (IGEHCS), National Scientific and Technical Research Council (CONICET), National University of the Center of the Province of Buenos Aires, Tandil, Argentina.
Abstract
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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