Social Inequity, Place of Residence and All-Cause Premature Death in Argentina
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ORIGINAL ARTICLE CME Social Inequity, Place of Residence and All-Cause Premature Death in Argentina Inequidad social, lugar de residencia y muerte prematura por cualquier causa en la Argentina ALEJANDRO MACCHIA, JAVIER MARIANIMTSAC, DANIEL NULMTSAC, HUGO GRANCELLIMTSAC, HERNÁN C. DOVALMTSAC ABSTRACT Background: Although the relationship between premature death and socioeconomic status has been recently reported in Argentina, there are no analyses on the impact of this condition in different regions of the country. Objective: The aim of this study was to describe the influence of socioeconomic status on the incidence of premature death rate in different provinces of Argentina, from 2000 to 2010. Methods: An ecological model was used to evaluate standardized premature death rates (≤74 years) during the period between 2000 and 2010. In addition, the relationship between socioeconomic status, measured in deciles of unmet basic needs at geographic departmental level, and premature death was examined. The units of analysis were the 512 Argentine departments and the 15 com- munes of the city of Buenos Aires. Results: Socioeconomic status was significantly associated with premature death rate in Argentina during the study period. A linear gradient was observed between premature death and socioeconomic status in all provinces and regions. However, the slope index of inequality varied significantly between departments. While the absolute difference in standardized premature death rate between the extreme components of socioeconomic status was 10 deaths (range: 7.81-12.36) per 10,000 persons per year in all Argentina, in the city of Buenos Aires this difference was 61 deaths (range: 53-69). The Southern communes of Buenos Aires were the areas with the highest social and health inequalities of Argentina. Conclusions: Although social inequity had a significant impact on premature death rate throughout Argentina during the study period, the city of Buenos Aires was the most unequal region. Key words: Mortality - Vital Statistics - Social Class - Epidemiology - Argentina RESUMEN Introducción: Aunque recientemente se reportó la relación entre la muerte prematura y la condición socioeconómica en la Argentina, no existen análisis sobre el impacto que dicha condición tiene en distintas regiones del país. Objetivo: Describir el impacto que la condición socioeconómica presentó sobre la incidencia de muerte prematura en las distintas provincias de la Argentina durante el período 2000-2010. Material y métodos: Se utilizó un modelo ecológico, que evaluó las tasas estandarizadas de muerte prematura (≤ 74 años) durante el período 2000-2010. Asimismo, se examinó la relación entre la condición socioeconómica medida en deciles de necesidades básicas insatisfechas por departamento geográfico y la muerte prematura. La unidad de análisis fueron los 512 departamentos de la Argen- tina y las 15 comunas de la ciudad de Buenos Aires. Resultados: La condición socioeconómica estuvo significativamente asociada con la muerte prematura en la Argentina durante el período analizado. En todas las provincias y regiones se observó un gradiente lineal entre la muerte precoz y la condición socioec- onómica. Sin embargo, la pendiente de desigualdad entre los componentes de la condición socioeconómica varió significativamente entre los distintos departamentos. Mientras que en toda la Argentina la diferencia absoluta en la tasa estandarizada de muerte pre- matura entre los componentes extremos de condición socioeconómica fue de 10 muertes (rango: 7,81-12,36) por cada 10.000 personas por año, en la ciudad de Buenos Aires esa diferencia fue de 61 muertes (rango: 53-69). Las comunas del sur de la ciudad de Buenos Aires fueron las zonas con mayor desigualdad social y sanitaria de la Argentina. Conclusiones: Aunque la inequidad social tuvo un impacto significativo en la muerte prematura en todo el período en toda la Argen- tina, la ciudad de Buenos Aires se mostró como la región más desigual. Palabras clave: Mortalidad - Estadísticas vitales - Clase social - Epidemiología - Argentina Abbreviations CABA Autonomous City of Buenos Aires SII Slope index of inequality ECLAC Economic Commission for Latin America and the Caribbean INDEC National Institute of Statistics and Censuses SES Socioeconomic status RII Relative index of inequality DEIS Bureau of Vital Statistics and Health Information UBN Unmet basic needs REV ARGENT CARDIOL 2016;84:108-113. http://dx.doi.org/10.7775/RAC.V84.I2.8267 Received: 12/18/2015 - Accepted: 01/27/2016 Address for reprints: Alejandro Macchia - Fundación GESICA (Grupo de Estudio Sobre Investigación Clínica en Argentina) - Av. Rivadavia 2431, Entrada 4, Piso 4, Oficina 5 - (1034) Buenos Aires, Argentina - e-mail: [email protected] GESICA Foundation (Clinical Investigation in Argentina Study Group). MTSAC Full Member of the Argentine Society of Cardiology SOCIAL INEQUITY AND PREMATURE DEATH IN ARGENTINA / Alejandro Macchia et al. 109 INTRODUCTION inces and communal for CABA) of the degree of unmet basic Social inequity significantly impacts on population needs (UBN) was used to qualify SES. These data are de- quality of life and life expectancy. (1) This concept can rived from INDEC integrated sources (2001 census) and the be ascribed to all populations whose life expectancy is Economic Commission for Latin America and the Caribbean not truncated by violence, war or hunger. Moreover, (ECLAC). Unmet basic needs originate from complex attrib- utes including the following domains: income, educational it is verifiable for societies with a high level of eco- level attained, housing conditions, degree of overcrowding nomic development as for those having poorer indi- and health conditions, as described in other sources. (9) cators. Argentina is not exempt from the association Moreover, the information on social and economic condi- between economic and social deprivation and prema- tions of CABA communes was characterized with informa- ture death. (2, 3) However, the impact that economic tion provided by the city government. inequity generates on death at an early age among the With these data, each Argentine department and CABA different Argentine regions has not been sufficiently commune was classified with a percentage of UBN, repre- documented. This documentation should be relevant senting the proportion of homes in each department and commune with UBN. All departments and communes were for health planning in order to, among other things, subsequently divided into deciles of UBN, quintile 1 corre- prioritize interventions in the most vulnerable popu- sponding to less UBN (less deprived departments). lation segments. Despite Argentina reports a significant economic growth since the 2002 economic-financial crisis, the Statistical analysis Age and sex standardized rates are expressed as number of gap in health inequity has significantly increased. (4, events per 10,000 persons per year and are reported for each 5) Many of these differences are avoidable with active UBN decile. State policies; however, it is necessary to document A Poisson multivariate regression model for randomized the most vulnerable regions and populations to prior- panel data was used for the analysis. These models are used itize the necessary works to be implemented. when the estimator to be analyzed is a number of discrete The purpose of this study is to describe the socio- events (as, for example, the annual number of deaths) and economic status (SES) impact on the incidence of pre- the dependent variable has Poisson distribution (mean simi- mature death in the different provinces of Argentina lar to variance). Panel data also include an error term, and a second term which controls for non-observed time-invariant during the 2000-2010 period. characteristics in the analysis unit. In this particular analy- sis, they include but are not limited to geographical, histori- METHODS cal and socio-cultural variables of the department. An ecological design study was performed to analyze stand- Additionally, some standardized measurements of health ardized premature death rates by age and sex and their as- inequities were incorporated for this analysis. These met- sociation with SES. Premature death was defined as that rics included the slope index of inequality (SII), the relative occurring before the age of 75. index of inequality (RII) and the limited RII. (10). The SII Data were obtained from the records of all-cause deaths represents the slope of a linear regression model fitted by in Argentina in persons between 0 and 74 years, as well as weighted least squares, with the rate of premature death as the number and demographic composition of the 512 depart- the dependent variable and the average relative rank of the ments distributed in the 23 provinces of Argentina and 15 different UBN deciles by department and commune as the communes of the Autonomous City of Buenos Aires (CABA). independent variable. This average rank is called ridit and The information from the National Institute of Statistics is by definition a variable comprised between 0 (lower limit and Censuses (INDEC) derived from the 2001 and 2010 na- of the socio-economic organization) and 1, representing the tional population and household censuses was used to estab- upper limit. The slope expresses the change in the rate of lish the number of persons between 0 and 74 years living death when the independent variable (in this case UBN) is in each Argentine department and CABA commune. The modified by one unit.