Pobres no Campo, Ricos na Cidade? Uma Análise Multidimensional da Pobreza

Costa, Rodolfo Ferreira Ribeiro da; Costa, Genivalda Cordeiro

doi:10.1590/1234-56781806-94790540308

Cited by 4 publications

(5 citation statements)

References 16 publications

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“…Most papers only created the area-level measure of deprivation for specific areas (e.g., states, regions, cities) within Brazil and not for the entire country. Three papers created their measure for the whole of Brazil; Costa et al and Cortellazzi et al used the municipality area-level 52 , 53 and Barros et al used the Regions and States 54 ; none of them was at the census tract level. Costa et al and Cortellazzi et al used data from 2010 Census 52 , 53 , Barros et al used data from 1991 and 2000 Census 54 .…”

Section: Resultsmentioning

confidence: 99%

Area deprivation measures used in Brazil

Ichihara¹,

Ramos²,

Rebouças³

et al. 2018

Rev. saúde pública

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OBJECTIVETo describe and assess currently used area-based measures of deprivation in Brazil for health research, to the purpose of informing the development of a future small area deprivation index.METHODSWe searched five electronic databases and seven websites of Brazilian research institutions and governmental agencies. Inclusion criteria were: studies proposing measures of deprivation for small areas (i.e., finer geography than country-level) in Brazil, published in English, Portuguese or Spanish. After data-extraction, results were tabulated according to the area level the deprivation measure was created for and to the dimensions of deprivation or poverty included in the measures. A narrative synthesis approach was used to summarize the measures available, highlighting their utility for public health research.RESULTSA total of 7,199 records were retrieved, 126 full-text articles were assessed after inclusion criteria and a final list of 30 articles was selected. No small-area deprivation measures that have been applied to the whole of Brazil were found. Existing measures were mainly used to study infectious and parasitic diseases. Few studies used the measures to assess inequalities in mortality and no studies used the deprivation measure to evaluate the impact of social programs.CONCLUSIONSNo up-to-date small area-based deprivation measure in Brazil covers the whole country. There is a need to develop such an index for Brazil to measure and monitor inequalities in health and mortality, particularly to assess progress in Brazil against the Sustainable Development Goal targets for different health outcomes, showing progress by socioeconomic groups.

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Section: Resultsmentioning

confidence: 99%

Area deprivation measures used in Brazil

Ichihara¹,

Ramos²,

Rebouças³

et al. 2018

Rev. saúde pública

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“…Por fim, apesar das mudanças, constata-se maior proporção de municípios com alto IPM nas regiões Norte e Nordeste e com baixo IPM nas regiões Sul e Sudeste. Costa & Costa (2016) utilizaram os dados do Censo Demográfico de 2010 para analisar os municípios brasileiros e observaram que, embora as políticas públicas atinjam da mesma forma os indivíduos das áreas urbanas e rurais, elas produzem os melhores resultados nas áreas urbanas, sugerindo que as especificidades de cada localidade devem ser incorporadas para um maior êxito na redução das privações.…”

Section: Fundamentação Teóricaunclassified

Pobreza multidimensional no Brasil: evidências para as áreas rurais e urbanas

Marcelino,

Cunha

2024

Rev. Econ. Sociol. Rural

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Resumo Este trabalho estudou o comportamento da pobreza multidimensional e de renda, bem como seus determinantes no Brasil, evidenciando as diferenças entre as áreas rurais e urbanas com base nas informações das Pesquisas Nacionais por Amostra de Domicílios Contínua (PNADC) de 2019. Foi utilizada a metodologia Alkire-Foster na construção de um Índice de Pobreza Multidimensional (IPM), além do modelo logit para estimar os impactos na pobreza de determinantes relacionados a características domiciliares. A dimensão saúde e saneamento foi a que mais contribuiu com o IPM, seguida da dimensão educação e condições habitacionais. A pobreza unidimensional foi maior do que a multidimensional, além disso, a pobreza nas áreas rurais foi também maior. Entre os determinantes da pobreza, estar em domicílios com chefes não brancos, mais jovens, não casados, desempregados, menos escolarizados e ser das regiões Norte e Nordeste aumentaram as chances de pobreza. Além disso, domicílios com chefes mulheres tiveram menores chances de pobreza multidimensional, embora mais chances de pobreza unidimensional.

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“…Lastly, in spite of the changes, there was higher number of cities with elevated MPR in the North and Northeast of the country and low MPR in the South and Southeast regions. Costa & Costa (2016) used data from Brazilian Demographic Census from 2010 to analyze Brazilian cities and observed that, although public policies reach individuals from urban and rural areas the same way, they produce better results in urban areas; it suggests that the characteristics of each place should be incorporated for greater success in reducing deprivations. Silva et al (2017b) observed in their study higher proportion of multidimensional poverty for the North of Brazil from 2006 to 2013.…”

Section: Theoretical Foundationsmentioning

confidence: 99%

Multidimensional poverty in Brazil: evidences for rural and urban areas

Marcelino,

Cunha

2024

Rev. Econ. Sociol. Rural

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This paper studied the behavior of multidimensional and income poverty, as well as its determinants in Brazil, in addition to rural and urban areas, based on information from the 2019 National Continuous Household Sample Survey (PNADC). The Alkire-Foster methodology was used in the construction of a Multidimensional Poverty Index (MPI), in addition to the logit model to estimate the impacts of determinants related to household characteristics on poverty. The health and sanitation dimension was the one that contributed the most to the MPI, followed by the education and housing dimensions. Unidimensional poverty was greater than multidimensional and rural poverty was also greater. Among the determinants of poverty, being in households with non-white heads, younger, unmarried, unemployed, less educated and in the North and Northeast regions increased the chances of poverty. In addition, while female heads reduced the chances of multidimensional poverty, it increased the chances of the unidimensional one.

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Pobres no Campo, Ricos na Cidade? Uma Análise Multidimensional da Pobreza

Cited by 4 publications

References 16 publications

Area deprivation measures used in Brazil

Area deprivation measures used in Brazil

Pobreza multidimensional no Brasil: evidências para as áreas rurais e urbanas

Multidimensional poverty in Brazil: evidences for rural and urban areas

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