ABSTRACT

OBJECTIVE

To 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.

METHODS

We 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.

RESULTS

A 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.

CONCLUSIONS

No 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.

DESCRIPTORS
Poverty; Poverty Areas; Socioeconomic Factors; Social Inequity, classification; Social Indicators; Review

INTRODUCTION

Brazil is a country with high rates of inequality, with the benefits of economic growth having been distributed inequitably¹1. Bittencourt M. Financial development and inequality: Brazil 1985–1994. Econ Change Restruc. 2010;43(2):113-30. https://doi.org/10.1007/s10644-009-9080-x
https://doi.org/10.1007/s10644-009-9080-... ^,22. Marmot M, Bell R. Social inequalities in health: a proper concern of epidemiology. Ann Epidemiol. 2016;26(4):238-40. https://doi.org/10.1016/j.annepidem.2016.02.003
https://doi.org/10.1016/j.annepidem.2016... . Although overall poverty rates have declined and global measures of socioeconomic conditions, such as the Human Development Index (HDI), have been showing consistent improvements in recent decades, internal disparities remain substantial. These disparities exist across both urban and rural contexts and have persisted during urbanization³3. Bassanesi SL. O1-1.1 Urbanisation and spatial inequalities in health in Brazil. J Epidemiol Community Health. 2011;65 Suppl 1:A8. https://doi.org/10.1136/jech.2011.142976a.14
https://doi.org/10.1136/jech.2011.142976...

4. Chandola T. Spatial and social determinants of urban health in low-, middle-and high-income countries. Public Health. 2012;126(3):259-61. https://doi.org/10.1016/j.puhe.2011.12.008
https://doi.org/10.1016/j.puhe.2011.12.0... ^-55. Marques E. Urban poverty, segregation and social networks in São Paulo and Salvador, Brazil. Int J Urban Reg Res. 2015;39(6):1067-83. https://doi.org/10.1111/1468-2427.12300
https://doi.org/10.1111/1468-2427.12300... .

Given that socioeconomic status is one of the most consistent determinants of health⁶6. Diez Roux AV, Mair C. Neighborhoods and health. Ann N Y Acad Sci. 2010;1186(1):125-45. https://doi.org/10.1111/j.1749-6632.2009.05333.x
https://doi.org/10.1111/j.1749-6632.2009... ^,77. Szwarcwald CL, Bastos FI, Barcellos C, Pina MF, Esteves MAP. Health conditions and residential concentration of poverty: a study in Rio de Janeiro, Brazil. J Epidemiol Community Health. 2000;54(7):530-6. https://doi.org/10.1136/jech.54.7.530
https://doi.org/10.1136/jech.54.7.530... , identifying those sub-populations that are still living in poverty, and being left behind despite economic growth, is an important task. Such identification allows the monitoring of health inequalities, the understanding of their causes and facilitates the evaluation of the impact of social programs on health inequalities – all of which helps achieve health equity.

To achieve this goal, several studies have sought to calculate poverty and deprivation indexes. In this review, our aim is to establish the current state of scientific knowledge about measures of deprivation for the Brazilian population, through a scoping review of scientific databases and grey literature.

Individual Socioeconomic Position and Area Deprivation

Area-based deprivation indexes have been used in the UK⁸8. Brown D, Allik M, Dundas R, Leyland AH. Carstairs scores for Scottish postcode sectors, datazones and output areas from the 2011 Census. Glasgow: University of Glasgow; 2014.^,99. Morgan O, Baker A. Measuring deprivation in England and Wales using 2001 Carstairs scores. Health Stat Q. 2006;(31):28-33. for over 30 years, and they are also available for many other countries, such as New Zealand¹⁰10. Salmond CE, Crampton P. Development of New Zealand's deprivation index (NZDep) and its uptake as a national policy tool. Can J Public Health. 2012;103(8 Suppl 2):S7-11. https://doi.org/10.17269/cjph.103.3195
https://doi.org/10.17269/cjph.103.3195... , Canada¹¹11. Pampalon R, Hamel D, Gamache P, Raymond G. A deprivation index for health planning in Canada. Chronic Dis Can. 2009;29(4):178-91.^,1212. Pampalon R, Raymond G. A deprivation index for health and welfare planning in Quebec. Chronic Dis Can. 2000;21(3):104-13., France¹³13. Havard S, Deguen S, Bodin J, Louis K, Laurent O, Bard D. A small-area index of socioeconomic deprivation to capture health inequalities in France. Soc Sci Med. 2008;67(12):2007-16. https://doi.org/10.1016/j.socscimed.2008.09.031
https://doi.org/10.1016/j.socscimed.2008... and Germany¹⁴14. Maier W, Fairburn J, Mielck A. [Regional deprivation and mortaliy in Bavaria]. Gesundheitswesen. 2012;74(7):416-25. German. https://doi.org/10.1055/s-0031-1280846
https://doi.org/10.1055/s-0031-1280846... . These deprivation indices are important to understand social inequalities in general and health inequalities. They describe the socioeconomic characteristics of an area that comprises individuals and not the individuals themselves. This feature demonstrates the utility of the deprivation index as it can be used in situations where the individual-level variables of socioeconomic position are not available or are poorly recorded for certain subgroups (e.g., occupational social class of elderly people who have not worked for a number of years)⁹9. Morgan O, Baker A. Measuring deprivation in England and Wales using 2001 Carstairs scores. Health Stat Q. 2006;(31):28-33.. Area deprivation measures are also used when individual-level measures are available; individual socioeconomic position and area deprivation can both have an effect on outcomes, independent of each other¹⁵15. Fairley L, Dundas R, Leyland AH. The influence of both individual and area based socioeconomic status on temporal trends in Caesarean sections in Scotland 1980-2000. BMC Public Health. 2011;11:330. https://doi.org/10.1186/1471-2458-11-330
https://doi.org/10.1186/1471-2458-11-330... . Area-based deprivation indicators can be linked to routinely collected administrative data, such as mortality and hospitalizations, where there is typically no information about the socioeconomic position of the individual. These can then be used to describe the extent of inequalities in the health outcome. Area-based deprivation indices are also used by policymakers to focus policies, funding or interventions on those most in need.

Individual Socioeconomic Position and Area Deprivation in Brazil

While we prefer the term deprivation to describe area-based measures of socioeconomic position, the term poverty is used extensively in the Brazilian literature. The use of income-based indicators of poverty are still dominant in the Brazilian literature and in the official government measures, but there is no consensus on the optimum measure¹⁶16. Cobo B, Athias L, Mattos GG. Multidimensional poverty in Brazil through fundamental social rights realization: an analytic proposal. In: IARIW-IBGE Conference on Income, Wealth and Well-Being in Latin America; 2013 Sept 12; Rio de Janeiro, Brazil. Rio de Janeiro: IBGE; 2013.. The Bolsa Família eligibility criteria defines as poor or extremely poor all families with per capita income below 170 Reais and 85 Reais, respectively¹⁷17. Ministério do Desenvolvimento Social (BR). Bolsa Família: o que é? Como funciona? 2013. Brasília (DF); 2013 [cited 2018 May 29]. Available from: http://mds.gov.br/assuntos/bolsa-familia/o-que-e/como-funciona/como-funciona
http://mds.gov.br/assuntos/bolsa-familia... , while the Brazilian Institute of Geography and Statistics (IBGE) defines per capita income of one-quarter of the minimum wage (234.25 Reais) as extreme poverty and one-half of the minimum wage (468.50) as poverty, based on the average living cost for the Brazilian population¹⁸18. Instituto Brasileiro de Geografia e Estatística. Síntese de indicadores sociais: uma análise das condições de vida da população brasileira. Rio de Janeiro: IBGE; 2016..

The main source for the calculation of such indicators for Brazil has been the Brazilian National Household Sample Survey (PNAD), conducted annually by IBGE since 1981. PNAD investigates several characteristics of the population such as household composition, education, labor, income and fertility. However, the PNAD collects data only about the families’ expenditures on basic needs, not allowing the study of other forms of deprivation beyond income, such as the different levels of multidimensional poverty¹⁹19. Osorio RG, Soares SSD, Souza PHGF. Erradicar a pobreza extrema: um objetivo ao alcance do Brasil. Brasília (DF): IPEA; 2011 [cited 2018 May 29]. (Texto para Discussão, 1619). Available from: http://www.ipea.gov.br/portal/index.php?option=com_content&view=article&id=9610
http://www.ipea.gov.br/portal/index.php?... .

The study of multidimensional measures of poverty and deprivation for the Brazilian population has mainly been conducted by the Brazilian Institute of Geography and Statistics²⁰20. Instituto Brasileiro de Geografia e Estatística. Síntese de indicadores sociais: uma análise das condições de vida da população brasileira. Rio de Janeiro: IBGE; 2012. and the Ministry of Social Development, who released a series of technical reports on how to calculate and apply such measures using census data or social registry data²¹21. Vaz AC, Jannuzzi PM. Pobreza multidimensional: série histórica 2001 a 2013 e caracterização dos diferentes perfis. Brasília (DF): Ministério do Desenvolvimento Social e Combate à Fome; 2014 [cited 2018 May 29]. (Estudo Técnico, 18/2014). Available from: http://acervodigital.mds.gov.br/xmlui/handle/123456789/380
http://acervodigital.mds.gov.br/xmlui/ha...

22. Vaz ACN. Pobreza multidimensional: subsídios para discussão à luz do MPI/OPHI. Brasília (DF): Ministério do Desenvolvimento Social e Combate à Fome; 2014 [cited 2018 May 29]. (Estudo Técnico, 09/2014). Available from: http://acervodigital.mds.gov.br/xmlui/handle/123456789/360
http://acervodigital.mds.gov.br/xmlui/ha... ^-2323. Jannuzzi PM, Souza MF, Melo LMC. Pobreza multidimensional: uma análise a partir do índice proposto pela Comissão Econômica para a América Latina e Caribe (Cepal) Brasília (DF): Ministério do Desenvolvimento Social e Combate à Fome; 2015 [cited cited 2018 May 29]. (Estudo Técnico, 02/2015). Available from: http://acervodigital.mds.gov.br/xmlui/handle/123456789/519
http://acervodigital.mds.gov.br/xmlui/ha... . Barros et al. have also developed a multidimensional poverty index by family, called IDF (Family Development Index)²⁴24. Barros RP, Carvalho M, Franco S. Pobreza multidimensional no Brasil. Rio de Janeiro: IPEA; 2006 [cited 2018 May 29]. (Texto para discussão, 1227). Availabe from: http://www.ipea.gov.br/portal/images/stories/PDFs/TDs/td_1227.pdf
http://www.ipea.gov.br/portal/images/sto... , and Kageyama and Hoffman have proposed the study of the spatial distribution of poverty in the country, based on the Basic Human Needs approach²⁵25. Kageyama A, Hoffmann R. Pobreza no Brasil: uma perspectiva multidimensional. Econ Soc. 2006 [cited 2018 May 29];15(1):79-112. Available from: https://periodicos.sbu.unicamp.br/ojs/index.php/ecos/article/view/8642922/10492
https://periodicos.sbu.unicamp.br/ojs/in... .

The purpose of this review is to inform the development of a small-area deprivation index for Brazil. Therefore, the aim is to review the literature to describe currently used area-based measures of socioeconomic inequalities in Brazil and assess the scope for using area-level deprivation measures for health research in Brazil. Specific research questions (RQ) are

RQ1 – What is the population coverage of the measure?

RQ2 – What area level is the measure operationalized at?

RQ3 – What dimensions of poverty are included in the measure?

RQ4 – What years and data sources are used in the measure?

METHODS

To describe the existing evidence on deprivation indexes for the Brazilian population, we performed a scoping review²⁶26. Levac D, Colquhoun H, O’Brien KK. Scoping studies: advancing the methodology. Implement Sci. 2010;5:69. https://doi.org/10.1186/1748-5908-5-69
https://doi.org/10.1186/1748-5908-5-69...

27. Arksey H, O’Malley L. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. 2005;8(1):19-32. https://doi.org/10.1080/1364557032000119616
https://doi.org/10.1080/1364557032000119... ^-2828. Colquhoun HL, Levac D, O’Brien KK, Straus S, Tricco AC, Perrier L, et al. Scoping reviews: time for clarity in definition, methods, and reporting. J Clin Epidemiol 2014;67(12):1291-4. https://doi.org/10.1016/j.jclinepi.2014.03.013
https://doi.org/10.1016/j.jclinepi.2014.... . Sources were considered for inclusion in the scoping review when they were consistent with the Population, Concept and Context (PCC). In this review, the population was areas in Brazil, the concept was measures of multiple deprivations and the context was small areas (i.e., finer geography than country-level) in Brazil.

Databases and Search Strategies

We searched five electronic databases (SCOPUS, PubMed, Web of Science, SocINDEX, Latin American and Caribbean Health Sciences Literature [LILACS]) on 1st September 2017, with no date restrictions for searches. Additional records and grey literature were retrieved through targeted searches (search terms: poverty/pobreza, deprivation/privação, small areas/pequenas áreas, census/censo) on the websites of Brazilian research institutions and governmental agencies, such as Getúlio Vargas Foundation (FGV), Brazilian Institute of Advanced Economic Research (IPEA), Pan-American Health Organization (OPAS/OMS), Ministry of Social Development (MDS), Brazilian Institute of Geography and Statistics (IBGE), World Bank and Repositório ARCA-FIOCRUZ. Potentially eligible references cited by included articles were also screened for inclusion. The predefined search strategies were built in an adaptive form to each search platform. Search strings one to four were used in SCOPUS, PubMed, SocINDEX, Web of Science and LILACS, and search string five was used only on PubMed.

1. (Poverty AND (measurement OR index) AND Brazil)

2. ((Poverty OR Poor) AND (measurement OR index) AND Brazil)

3. ((“Poverty measurement”) OR (“poverty index”) AND Brazil)

4. ((“Poverty measurement”) OR (“poverty index”) OR (“multidimensional poverty”) AND Brazil)

5. ((“Poverty”[Mesh] OR poverty[TIAB]) AND (Brazil”[Mesh] OR Brazil[TIAB]) AND (MEASUREMENT OR INDEX))

Eligibility Criteria

We reviewed abstracts and full texts of retrieved articles according to the following inclusion criteria: 1) included Brazil (or parts of Brazil); 2) were defined at the area level (e.g., not individual socioeconomic status) and; 3) reported a measure of social stratification (e.g., area-based poverty or deprivation or inequality). The exclusion criteria were: I) published in a language other than English, Portuguese or Spanish; and II) full text not available. There was no restriction by publication year. There were no restrictions on the sources of information that could contribute to the scoping review; all types of existing literature from the databases searched were included.

Data

All relevant data were extracted from the full texts by two reviewers, DR and RD. The data extracted related to the aim of the scoping review to identify the measures that have been used to report area-based deprivation in Brazil. We extracted data on study characteristics (publication year, journal and authors), name of the deprivation measure, area level (e.g., municipalities, census tracts), geographical coverage (e.g., the proportion of the Brazilian population that has a valid measure available), variables used to calculate the index and whether it was used to report on a health outcome.

Analysis

We did not critically appraise the included studies, as is common in scoping reviews²⁶26. Levac D, Colquhoun H, O’Brien KK. Scoping studies: advancing the methodology. Implement Sci. 2010;5:69. https://doi.org/10.1186/1748-5908-5-69
https://doi.org/10.1186/1748-5908-5-69... ^,2929. Peters MD, Godfrey CM, Khalil H, McInerney P, Parker D, Soares CB. Guidance for conducting systematic scoping reviews. Int J Evid Based Healthc. 2015;13(3):141-6. https://doi.org/10.1097/XEB.0000000000000050
https://doi.org/10.1097/XEB.000000000000... ^,3030. Katikireddi SV, Egan M, Petticrew M. How do systematic reviews incorporate risk of bias assessments into the synthesis of evidence? A methodological study. J Epidemiol Community Health. 2015;69(2):189-95. https://doi.org/10.1136/jech-2014-204711
https://doi.org/10.1136/jech-2014-204711... . Data were managed with the assistance of Endnote X3 for reference management and Microsoft® Excel 2010 for data extraction and summarising findings. A narrative summary approach to data analysis was undertaken³¹31. Popay J, Roberts H, Sowden A, Petticrew M, Arai L, Rodgers M, et al. Guidance on the conduct of narrative synthesis in systematic reviews.:a product from the ESRC Methods Programme. Lancaster (UK): Lancaster University; 2006.. Results were tabulated according to the area-level that the deprivation measure was created for and dimensions of deprivation or poverty included in the measures. We summarised the different deprivation measures available, highlighting their utility for applying to public health research. In particular, we summarised information according to the population coverage of the measure, the area level used, dimensions of deprivation incorporated, and the data sources used.

RESULTS

A total of 7,199 records were retrieved. Of these, 3,808 were duplicates, and 3,265 were excluded after title screening, leaving a total of 126 full-text articles for assessment. Reasons for exclusion during full-text review appear in Figure, with most of the studies excluded because they did not focus on area-level measurements (inclusion criteria #2, n = 69), extracting information only from individual or household level data. After all the screening stages and inclusion/exclusion criteria, a final list of 30 articles was selected.

As shown in Table, 15 studies were published from 2000–2010 and 15 from 2011–2017. There were four main area-levels that were considered in the papers: municipalities (with an average population of 37,000)³²32. Barata RB, Ribeiro MCSA. [Correlation between homicide rates and economic indicators in Sao Paulo, Brazil, 1996]. Rev Panam Salud Publica. 2000;7(2):118-23. Portuguese.

33. Bezerra Filho JG, Pontes LRFSK, Miná DL, Barreto ML. Infant mortality and sociodemographic conditions in Ceará, Brazil, 1991 and 2000. Rev Saude Publica. 2007;41(6):1023-31. https://doi.org/10.1590/S0034-89102007000600018
https://doi.org/10.1590/S0034-8910200700...

34. Drachler ML, Lobato MAO, Lermen JI, Fagundes S, Ferla AA, Drachler CW, et al. Desenvolvimento e validação de um índice de vulnerabilidade social aplicado a políticas públicas do SUS. Cienc Saude Coletiva. 2014;19(9):3849-58. https://doi.org/10.1590/1413-81232014199.12012013
https://doi.org/10.1590/1413-81232014199... ^-3535. Ottonelli J, Mariano JL. [Multidimensional poverty in the cities of the Northeast Region in Brazil]. Rev Adm Publica. 2014;48(5):1253-79. Portuguese. https://doi.org/10.1590/0034-76121724
https://doi.org/10.1590/0034-76121724... ; census tracts (average population 660)⁷7. Szwarcwald CL, Bastos FI, Barcellos C, Pina MF, Esteves MAP. Health conditions and residential concentration of poverty: a study in Rio de Janeiro, Brazil. J Epidemiol Community Health. 2000;54(7):530-6. https://doi.org/10.1136/jech.54.7.530
https://doi.org/10.1136/jech.54.7.530... ^,3636. Bonfim C, Aguiar-Santos AM, Pedroza Jr D, Costa TR, Portugal JL, Oliveira ZMC, et al. Social deprivation index and lymphatic filariasis: a tool for mapping urban areas at risk in northeastern Brazil. Int Health. 2009;1(1):78-84. https://doi.org/10.1016/j.inhe.2009.06.007
https://doi.org/10.1016/j.inhe.2009.06.0...

37. Bonfim C, Alves A, Costa TR, Alencar F, Pedroza D, Portugal JL, et al. Spatial analysis and privation index to identify urban areas with a high risk of lymphatic filariasis. Trop Med Int Health. 2011;16(6):748-55. https://doi.or/10.1111/j.1365-3156.2011.02758.x
https://doi.or/10.1111/j.1365-3156.2011.... ^-3838. Hino P, Scatena Villa TC, Cunha TN, Santos CB. [Spatial patterns of tuberculosis and its association with living conditions in the city of Ribeirão Preto in the State of São Paulo. Cienc Saude Coletiva. 2011;16(12):4795-802. Portuguese. https://doi.org/10.1590/S1413-81232011001300028
https://doi.org/10.1590/S1413-8123201100... ; districts (average population 20,000)³⁶36. Bonfim C, Aguiar-Santos AM, Pedroza Jr D, Costa TR, Portugal JL, Oliveira ZMC, et al. Social deprivation index and lymphatic filariasis: a tool for mapping urban areas at risk in northeastern Brazil. Int Health. 2009;1(1):78-84. https://doi.org/10.1016/j.inhe.2009.06.007
https://doi.org/10.1016/j.inhe.2009.06.0... ^,3939. Antunes JLF, Frazão P, Narvai PC, Bispo CM, Pegoretti T. Spatial analysis to identify differentials in dental needs by area-based measures. Community Dent Oral Epidemiol. 2002;30(2):133-42. https://doi.org/10.1034/j.1600-0528.2002.300207.x
https://doi.org/10.1034/j.1600-0528.2002...

40. D’Ambrosio C, Rodrigues RI. Deprivation in the São Paulo districts: evidence from 2000. World Dev. 2008;36(6):1094-112. https://doi.org/10.1016/j.worlddev.2007.10.007
https://doi.org/10.1016/j.worlddev.2007....

41. Lima MLC, Ximenes RAA, Souza ER, Luna CF, Albuquerque MFPM. Spatial analysis of socioeconomic determinants of homicide in Brazil. Rev Saude Publica. 2005;39(2):176-82. https://doi.org/10.1590/S0034-89102005000200006
https://doi.org/10.1590/S0034-8910200500... ^-4242. Oliveira JS, Lira PIC, Veras ICL, Maia SR, Lemos MCC, Andrade SLLS, et al. Estado nutricional e insegurança alimentar de adolescentes e adultos em duas localidades de baixo índice de desenvolvimento humano. Rev Nutr. 2009;22(4):453-65. https://doi.org/10.1590/S1415-52732009000400002
https://doi.org/10.1590/S1415-5273200900... ; and neighborhoods⁴³43. Holanda ER, Galvão MTG, Pedrosa NL, Paiva SS, Almeida RLF. Spatial analysis of infection by the human immunodeficiency virus among pregnant women. Rev Latino Am Enfermagem. 2015;23(3):441-9. https://doi.org/10.1590/0104-1169.0481.2574
https://doi.org/10.1590/0104-1169.0481.2...

44. Sousa GS, Magalhães FB, Gama IS, Lima MVN, Almeida RLF, Vieira LJES, et al. Social determinants and their interference in homicide rates in a city in northeastern Brazil. Rev Bras Epidemiol. 2014;17 Supl 2:194-203. https://doi.org/10.1590/1809-4503201400060016
https://doi.org/10.1590/1809-45032014000...

45. Duarte CM, Nascimento VB, Akerman M. [Adolescent pregnancy and social exclusion: analysis of intra-urban disparities]. Rev Panam Salud Publica. 2006;19(4):236-43. Portuguese.^-4646. Lopes EM, Pedrosa NL, Holanda ER, Almeida RLF, Kerr LRFS, Galvão MTG. [AIDS in children: the influence of socioeconomic differences in Fortaleza, Ceará State, Brazil]. Cad Saude Publica. 2015;31(9):2005-16. Portuguese. https://doi.org/10.1590/0102-311X00074514
https://doi.org/10.1590/0102-311X0007451... . Six papers considered other area levels⁷7. Szwarcwald CL, Bastos FI, Barcellos C, Pina MF, Esteves MAP. Health conditions and residential concentration of poverty: a study in Rio de Janeiro, Brazil. J Epidemiol Community Health. 2000;54(7):530-6. https://doi.org/10.1136/jech.54.7.530
https://doi.org/10.1136/jech.54.7.530... ^,4747. Antunes JLF, Narvai PC, Nugent ZJ. Measuring inequalities in the distribution of dental caries. Community Dent Oral Epidemiol. 2004;32(1):41-8. https://doi.org/10.1111/j.1600-0528.2004.00125.x
https://doi.org/10.1111/j.1600-0528.2004...

48. Barbieri AF, Guedes GR, Noronha K, Queiroz BL, Domingues EP, Rigotti JIR, et al. Population transitions and temperature change in Minas Gerais, Brazil: a multidimensional approach. Rev Bras Estud Popul. 2015;32(3):461-88. https://doi.org/10.1590/S0102-3098201500000028
https://doi.org/10.1590/S0102-3098201500...

49. Rocha S. Opçöes metodológicas para a estimaçäo de linhas de indigência e de pobreza no Brasil. Rio de Janeiro: IPEA; 2000 [cited 2018 May 29]. (Texto para discussão, 720). Available from http://www.ipea.gov.br/portal/index.php?option=com_content&view=article&id=3989
http://www.ipea.gov.br/portal/index.php?...

50. Souza SF, Costa MCN, Paim JS, Natividade MS, Pereira SM, Andrade AMS, et al. Bacterial meningitis and living conditions. Rev Soc Bras Med Trop. 2012;45(3):323-8. https://doi.org/10.1590/S0037-86822012000300009
https://doi.org/10.1590/S0037-8682201200... ^-5151. Teixeira MG, Meyer MA, Costa MCN, Paim JS, Silva LMV. [Mortality due to infectious and parasitic diseases in Salvador, Bahia: evolution and intra-urban differences according to living conditions]. Rev Soc Bras Med Trop 2002;35(5):491-7. https://doi.org/10.1590/S0037-86822002000500012
https://doi.org/10.1590/S0037-8682200200... . The majority of the papers examined health outcomes by area-level deprivation; only six papers did not have a health outcome. These were mainly in the field of infectious/parasitic diseases. Two papers reported all-cause mortality and three further studies examined mortality from homicide specifically.

The Box groups the papers by the area level used and displays the dimensions of deprivation considered by each of the papers. There is a noticeable growth in the scope of the studies over time as shown by the number of dimensions used. This is a possible result of the improved availability of data and the modernization of the Brazilian information systems. Key themes are presented below in relation to each research question.

Population Coverage of the Measure

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-level⁵²52. Costa RFR, Costa GC. Pobres no campo, ricos na cidade? Uma análise multidimensional da pobreza. Rev Econ Sociol Rural. 2016;54(3):537-60. https://doi.org/10.1590/1234-56781806-94790540308
https://doi.org/10.1590/1234-56781806-94... ^,5353. Cortellazzi KL, Balbino EC, Guerra LM, Vazquez FL, Bulgareli JV, Ambrosano GMB, et al. Variables associated with the performance of Centers for Dental Specialties in Brazil. Rev Bras Epidemiol. 2014;17(4):978-88. https://doi.org/10.1590/1809-4503201400040015
https://doi.org/10.1590/1809-45032014000... and Barros et al. used the Regions and States⁵⁴54. Barros RP, Carvalho M, Franco S. O índice de desenvolvimento da família (IDF). Rio de Janeiro: IPEA; 2003 [cited 2018 May 29]. (Texto para discussão, 986). Available from: http://www.ipea.gov.br/portal/images/stories/PDFs/TDs/td_0986.pdf
http://www.ipea.gov.br/portal/images/sto... ; none of them was at the census tract level. Costa et al. and Cortellazzi et al. used data from 2010 Census⁵²52. Costa RFR, Costa GC. Pobres no campo, ricos na cidade? Uma análise multidimensional da pobreza. Rev Econ Sociol Rural. 2016;54(3):537-60. https://doi.org/10.1590/1234-56781806-94790540308
https://doi.org/10.1590/1234-56781806-94... ^,5353. Cortellazzi KL, Balbino EC, Guerra LM, Vazquez FL, Bulgareli JV, Ambrosano GMB, et al. Variables associated with the performance of Centers for Dental Specialties in Brazil. Rev Bras Epidemiol. 2014;17(4):978-88. https://doi.org/10.1590/1809-4503201400040015
https://doi.org/10.1590/1809-45032014000... , Barros et al. used data from 1991 and 2000 Census⁵⁴54. Barros RP, Carvalho M, Franco S. O índice de desenvolvimento da família (IDF). Rio de Janeiro: IPEA; 2003 [cited 2018 May 29]. (Texto para discussão, 986). Available from: http://www.ipea.gov.br/portal/images/stories/PDFs/TDs/td_0986.pdf
http://www.ipea.gov.br/portal/images/sto... .

Area Level of the Measure

Four main area levels were considered in the papers: municipalities; census tracts; districts; and neighborhoods. Six papers considered other areas, as follows: towns (no information provided regarding average population size), information zones (average population 2,190,849), microregions (average population 19,595,309), administrative regions (average population 5,000,000) and metropolitan regions (no information provided regarding average population size).

Dimensions of Deprivation Included in the Measure

Many papers used the Human Development Index of Municipalities (IDHM) developed by the United Nations Development Programme (UNDP). This is created using three dimensions of human development – longevity, education and income. The IDHM was used as a standalone measure and as a dimension of other measures.

Nearly all papers included income as a dimension of deprivation. Only four did not include income. Income was assessed in different ways; these include average nominal income; per capita income, proportion of people with high incomes, homes in the poverty range, proportion of heads of family in permanent private households with a mean monthly income ≤ 2 minimum salaries. The 21 studies included education as an indicator of deprivation; the main measures were illiteracy and years of education. Sanitary and housing conditions were also important dimensions of deprivation and were included in most papers. A few studies used employment as an indicator.

Other indicators included food habits and costs, access to health services and a general measure of inequality such as the concentration index or Gini coefficient. It should be noted that general measures of inequality do not measure deprivation, but measure heterogeneity of poverty concentration in a geographic location⁵⁵55. Szwarcwald CL, Andrade CLT, Bastos FI. Income inequality, residential poverty clustering and infant mortality: a study in Rio de Janeiro, Brazil. Soc Sci Med. 2002;55(12):2083-92. https://doi.org/10.1016/S0277-9536(01)00353-7
https://doi.org/10.1016/S0277-9536(01)00... .

Years of Data Collection for the Dimensions of Deprivation

Most data to create the area level deprivation indices came from the Brazil Censuses of 1990 (six papers), 2000 (eight papers) and 2010 (nine papers).

From the two papers that reported all-cause mortality and three further studies that examined mortality from homicide specifically, none of these covered the whole population of Brazil and none was at the census tract level. Two were at the district level, and the others were at the neighborhood, municipality and administrative region. These were all carried out using 1991 or 2000 Census data; none used the 2010 Census.

DISCUSSION

This review summarizes the efforts made in Brazil to create area-based deprivation indices. While we identified a few studies that developed deprivation measures applied to the whole of Brazil, none of them was based on small areas (census tracts). Three studies did cover the entire country but the “small areas” used were municipalities with an average population of 37,000. We found limited deprivation measures using the census tract area level and limited deprivation measures using the most recent 2010 Census. In addition, the small area deprivation measures were mainly used to describe inequalities in infectious and parasitic diseases. Few studies used the deprivation measure to assess inequalities in mortality and no studies used the deprivation measure to evaluate the impact of social programs designed for poor populations (e.g., Bolsa Família, Minha Casa Minha Vida).

This scoping review has several strengths. A comprehensive search strategy was used; we searched five electronic databases, including a key repository for LILACS. A standard data extraction form was used for each paper and report included in the scoping review. This means our data should be as robust and standardized as possible. There are some limitations to the scoping review. This review needed to be as comprehensive as possible, therefore we included all studies, regardless of the quality. A risk of bias tool was not used to assess studies for quality or inclusion; all results were given the same weight and importance. It is usual to use more than one reviewer to check a proportion of the screened results and data extraction. Results were only screened by a single person (either DR, PR or RD). DR checked a minimal number of papers (n = 14), assigned to RD to screen, where the title was in English but the abstract was only available in Portuguese, but this was not a systematic approach. However, we did not identify any further articles for inclusion based on scrutinizing the references of included articles, suggesting that we have identified the existing deprivation measures within Brazil. Similarly, only one person extracted the data from each included paper; there was no cross-checking of the data extraction. The use of single persons to screen and extract the data may have introduced bias, in that some studies may have been inadvertently excluded or the wrong information extracted. However, the information to be extracted was basic information about the deprivation measure and the data used to create it. As such, we felt we did not need a second data extractor.

Advantages and Disadvantages of Using Area-Based Deprivation Measures

There are advantages and disadvantages of using area-level deprivation measures compared to individual measures of socioeconomic position. The appeal of area-level measures is that they are available for the entire population. Children and adolescents can have an area-based deprivation assigned to their area of residence, whereas these important sub-groups are usually excluded from individual-level analyses as they do not have, for example, an individual income or employment category. A further appeal of area-based measures, if they are at a suitably small area, is that policymakers can use them to target specific areas of deprivation. This targeting aims to ensure that those that are in the most need are able to access the services and policies required.

Potential disadvantages include the fact that, since it is an area measure and not a measure about the individuals, it might not reflect the circumstances of all individuals within an area; not all areas marked as deprived will contain only poor individuals and not all poor individuals live in deprived areas⁵⁶56. McLoone P. Targeting deprived areas within small areas in Scotland: population study. BMJ. 2001;323(7309):374-5. https://doi.org/10.1136/bmj.323.7309.374
https://doi.org/10.1136/bmj.323.7309.374... . This will be less of an issue the smaller the area, as areas become more homogenous in terms of deprivation. Current research using area-based measures of deprivation in Brazil are focused at the municipality level which has an average population size of 37,000, but some municipalities are large cities, such as São Paulo or Salvador with populations of 12 and 2.9 million, respectively. These areas will certainly be extremely heterogeneous in terms of deprivation; the variation in deprivation within a municipality may be as large as the variation in deprivation between different municipalities. The use of smaller areas in terms of population size will mitigate the effects of heterogeneous areas. A further disadvantage is that areas of extreme deprivation may become stigmatized and therefore the individuals within these areas may experience disadvantage as a consequence of using deprivation measures⁵⁷57. Katikireddi SV, Valles SA. Coupled ethical-epistemic analysis of public health research and practice: categorizing variables to improve population health and equity. Am J Public Health. 2015;105(1):e36-42. https://doi.org/10.2105/AJPH.2014.302279
https://doi.org/10.2105/AJPH.2014.302279... .

Utility of an Area-Based Deprivation Index for Brazil

Using IBGE Demographic Census Data, it will be possible to develop a deprivation index based on small areas (census tracts) and, in the Brazilian context, a deprivation index can be useful for a variety of reasons. These include: a) a means to identify subpopulations that are still living in poverty, regardless of the country's trends of economic growth; b) targeting groups that are at-risk for poverty-related diseases (e.g., diarrheal infections, malnutrition); c) evaluating the impact of social programs designed for poor populations (e.g., Bolsa Família, Minha Casa Minha Vida); and d) through data linkage with other health information systems, exploring the role of deprivation as a causal or associated factor for many health outcomes.

The WHO Commission on Social Determinants of Health (2008) stated that measuring and monitoring inequalities in health was key to understand how to reduce inequalities⁵⁸58. Marmot M, Friel S, Bell R, Houweling TA, Taylor S; Commission on Social Determinants of Health. Closing the gap in a generation: health equity through action on the social determinants of health. Lancet. 2008;372(9650):1661-9. https://doi.org/10.1016/S0140-6736(08)61690-6
https://doi.org/10.1016/S0140-6736(08)61... . Despite a history of social protection policies, 27% of the population was still in poverty in 2015, according to the criteria of the IBGE (household per capita income < half the minimum wage). However, using the criteria of the Ministry of Social Development, the entity responsible for social policies, such as Bolsa Família, this percentage is estimated to be of 40% (household per capita income < 140 Brazilian Reais). There is limited knowledge of where these people live and the nature of the area they live in. Area-based deprivation indicators have been in use in the UK and other countries for over 30 years. There is a need to develop a similar small-area deprivation index for Brazil that could be used to measure and monitor inequalities in health and mortality, in particular, to measure the progress in Brazil against the Sustainable Development Goals targets for different health outcomes, showing progress within socioeconomic groups.

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