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      Mensuração de desigualdades sociais em saúde: conceitos e abordagens metodológicas no contexto brasileiro Translated title: Medición de las desigualdades sociales en salud: conceptos y abordajes metodológicos en el contexto brasilero Translated title: Measurement of social inequalities in health: concepts and methodological approaches in the Brazilian context

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          Abstract

          Resumo O objetivo deste artigo é apresentar os principais métodos de mensuração e monitoramento das desigualdades sociais em saúde e ilustrar suas aplicações. Foram revisadas as medidas mais frequentemente empregadas na literatura. Dados de cobertura e qualidade do cuidado pré-natal no Brasil, provenientes da Pesquisa Nacional de Demografia e Saúde da Criança e da Mulher (PNDS-2006) e da Pesquisa Nacional de Saúde (PNS-2013), foram utilizados para exemplificar as aplicações. Medidas de desigualdade absoluta e relativa foram apresentadas, destacando-se sua complementaridade. Apesar dos avanços evidenciados nos indicadores nacionais de pré-natal, importantes desigualdades foram identificadas entre subgrupos da população, sem que houvesse redução da magnitude dessas diferenças no período estudado. O Brasil apresenta importantes desigualdades sociais, que ainda se refletem em persistentes desigualdades em saúde. A descrição e monitoramento dessas desigualdades são fundamentais para o direcionamento de políticas de saúde, com foco em grupos mais vulneráveis que vêm sendo deixados para trás.

          Translated abstract

          Resumen El objetivo de este artículo es presentar los principales métodos de medición y monitoreo de las desigualdades sociales en salud, y demostrar sus aplicaciones prácticas. Se realizó una revisión de los métodos más frecuentemente utilizados en la literatura. Datos sobre cobertura y calidad de la atención prenatal en Brasil, provenientes de la Encuesta Nacional de Demografía y Salud del Niño y la Mujer (PNDS-2006) y de la Encuesta Nacional de Salud (PNS-2013) fueran usados como ejemplo. Fueron presentadas medidas de desigualdad absoluta y relativa, destacando su complementariedad. A pesar de los avances evidenciados en los indicadores de atención prenatal en Brasil, fueron identificadas desigualdades importantes, sin que hubiese una reducción de la magnitud de esas diferencias en el periodo estudiado. Brasil presenta desigualdades sociales importantes, que aún se ven reflejadas en las persistentes desigualdades en salud. Su descripción y seguimiento son fundamentales para el direccionamiento de políticas en salud, focalizadas en grupos más vulnerables que han sido relegados.

          Translated abstract

          Abstract This study aims to describe methodological approaches to measure and monitor health inequalities and to illustrate their applicability. The measures most frequently used in the literature were reviewed. Data on coverage and quality of pre-natal care in Brazil, from the Demographic and Maternal and Child Health Survey (PNDS-2006) and the National Health Survey (PNS-2013) were used to illustrate their applicability. Absolute and relative measures of inequalities were presented, highlighting their complementary character. Despite the progress achieved in the national indicators of pre-natal care, important inequalities were still identified between population subgroups, with no change in the magnitude of the differences throughout the studied period. Brazil has important social inequalities, whose consequences still lead to health inequalities. Their description and monitoring are highly relevant to support polices focused on those vulnerable population groups who have been left behind.

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          Estimating wealth effects without expenditure data--or tears: an application to educational enrollments in states of India.

          Using data from India, we estimate the relationship between household wealth and children's school enrollment. We proxy wealth by constructing a linear index from asset ownership indicators, using principal-components analysis to derive weights. In Indian data this index is robust to the assets included, and produces internally coherent results. State-level results correspond well to independent data on per capita output and poverty. To validate the method and to show that the asset index predicts enrollments as accurately as expenditures, or more so, we use data sets from Indonesia, Pakistan, and Nepal that contain information on both expenditures and assets. The results show large, variable wealth gaps in children's enrollment across Indian states. On average a "rich" child is 31 percentage points more likely to be enrolled than a "poor" child, but this gap varies from only 4.6 percentage points in Kerala to 38.2 in Uttar Pradesh and 42.6 in Bihar.
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            Estimating wealth effects without expenditure data—or tears: An application to educational enrollments in states of India

            Using data from India, we estimate the relationship between household wealth and children’s school enrollment. We proxy wealth by constructing a linear index from asset ownership indicators, using principal-components analysis to derive weights. In Indian data this index is robust to the assets included, and produces internally coherent results. State-level results correspond well to independent data on per capita output and poverty. To validate the method and to show that the asset index predicts enrollments as accurately as expenditures, or more so, we use data sets from Indonesia, Pakistan, and Nepal that contain information on both expenditures and assets. The results show large, variable wealth gaps in children’s enrollment across Indian states. On average a “rich” child is 31 percentage points more likely to be enrolled than a “poor” child, but this gap varies from only 4.6 percentage points in Kerala to 38.2 in Uttar Pradesh and 42.6 in Bihar.
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              • Record: found
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              Explaining trends in inequities: evidence from Brazilian child health studies.

              There is considerable international concern that child-health inequities seem to be getting worse between and within richer and poorer countries. The "inverse equity hypothesis" is proposed to explain how such health inequities may get worse, remain the same, or improve over time. We postulate that as new public-health interventions and programmes initially reach those of higher socioeconomic status and only later affect the poor, there are early increases in inequity ratios for coverage, morbidity, and mortality indicators. Inequities only improve later when the rich have achieved new minimum achievable levels for morbidity and mortality and the poor gain greater access to the interventions. The hypothesis was examined using three epidemiological data sets for time trends in child-health inequities within Brazil. Time trends for inequity ratios for morbidity and mortality, which were consistent with the hypothesis, showed both improvements and deterioration over time, despite the indicators showing absolute improvements in health status between rich and poor.
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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Role: ND
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                Role: ND
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                Journal
                ress
                Epidemiologia e Serviços de Saúde
                Epidemiol. Serv. Saúde
                Secretaria de Vigilância em Saúde - Ministério da Saúde do Brasil (Brasília, DF, Brazil )
                1679-4974
                2237-9622
                March 2018
                : 27
                : 1
                : e000100017
                Affiliations
                [1] Pelotas Rio Grande do Sul orgnameUniversidade Federal de Pelotas orgdiv1Programa de Pós-graduação em Epidemiologia orgdiv2Centro Internacional de Equidade em Saúde Brazil
                Article
                S2237-96222018000101000
                10.5123/s1679-49742018000100017
                6188b956-bcbb-417c-80f9-7ecb842193b2

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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                SciELO Brazil


                Fatores Socioeconômicos,Medidas, Métodos e Teorias,Desigualdades en Salud/Métodos,Health Inequalities/methods,Factores Socioeconómicos,Medidas, Métodos y Teorías,Socioeconomic Factors,Measurements, Methods and Theories,Desigualdades em Saúde/Métodos

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