Relationship between social indicators and food insecurity: a systematic review

Lignani, Juliana de Bem; Palmeira, Poliana de Araujo; Antunes, Marina Maria Leite; Salles-Costa, Rosana

doi:10.1590/1980-549720200068

ABSTRACT:

Introduction:

The relationships between the social indicators (SIs) that determine food insecurity (FI) have not been described yet. This systematic review aims to identify which SIs are associated with FI in Brazilian households and how these relationships are explained.

Methods:

The research protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO - CRD42018106527). Three independent researchers performed the search in the Latin American and Caribbean Health Sciences Literature (LILACS) and National Library of Medicine (PubMed) databases (June/2018). The study included articles that used the Brazilian Household Food Insecurity Measurement Scale (Escala Brasileira de Insegurança Alimentar - EBIA) to assess FI and that evaluated the association between SIs and FI.

Results:

We included 18 articles in this review. The Kappa concordance index between the researchers was 0.72 (95%CI 0.42 - 1.00). Most articles were cross-sectional and used multivariate regression for the statistical analysis. At least one income-related SI had a significant association with FI, and, in most studies, they presented the highest values of association measures. We organized the authors’ explanation about the relationships between SIs and FI in a conceptual model. The study identified three possible justifications for the association between SIs and FI: direct relationship, relationship mediated by income, or relationship mediated by another SI and income.

Conclusion:

Income assumed a central role in the mediation between several SIs and FI. However, the analysis methods of the studies did not allow us to investigate this mediation. Therefore, improving data analysis to isolate and understand the effect of SIs on FI is still necessary.

Keywords:
Food and nutrition security; Food supply; Social indicators; Review

RESUMO:

Introdução:

As relações existentes entre os indicadores sociais (IS) que determinam a insegurança alimentar (IA) ainda não foram descritas. Esta revisão sistemática se propõe a identificar os IS que se associam com a IA em domicílios brasileiros e como essa relação é explicada.

Metodologia:

O protocolo de pesquisa foi registrado no PROSPERO (CRD42018106527). A busca dos artigos foi realizada por três pesquisadoras independentes nas bases Lilacs e PubMed (junho/2018). O estudo incluiu artigos que utilizaram a Escala Brasileira de Insegurança Alimentar (EBIA) para avaliar a IA e que analisaram a associação entre IS e IA.

Resultados:

18 artigos foram incluídos nessa revisão. O índice de concordância Kappa entre as pesquisadoras foi de 0,72 (IC95% 0,42 - 1,00). A maioria dos artigos foram do tipo transversais e utilizaram regressão multivariada para análise de dados. Pelo menos um IS relacionado à renda teve associação significativa com a IA e, na maioria dos estudos, eles foram os que apresentaram os maiores valores das medidas de associação. A justificativa dos autores sobre as relações entre IS e IA foram organizadas em um modelo conceitual. O estudo identificou 3 possibilidades de explicar a associação entre IS e IA: relação direta, relação mediada pela renda, ou por outro IS e renda.

Conclusão:

A renda assumiu um papel central na mediação de diversos IS com IA. Entretanto, os métodos de análise dos estudos não possibilitaram lidar com essa mediação, portanto aprimoramentos nas análises de dados são necessários para isolar e compreender o efeito dos IS na IA.

Palavras-chave:
Segurança alimentar e nutricional; Abastecimento de alimentos; Indicadores sociais; Revisão

INTRODUCTION

The Brazilian Household Food Insecurity Measurement Scale (Escala Brasileira de Insegurança Alimentar - EBIA), validated in 2003¹1. Pérez-Escamilla R, Segall-Corrêa AM, Maranha LK, Sampaio MFA, Marin-León L, Panigassi G. An adapted version of the U.S. Department of Agriculture Food Insecurity module is a valid tool for assessing household food insecurity in Campinas, Brazil. J Nutr 2004; 134(8): 1923-8. https://doi.org/10.1093/jn/134.8.1923
https://doi.org/https://doi.org/10.1093/... , enables us to measure the food stability and access dimensions in the household food insecurity (FI) diagnosis. EBIA is an instrument composed of 14 dichotomous (yes/no) items, including household information of the previous three months, elaborated based on the Household Food Security Survey Module (HFSSM)¹1. Pérez-Escamilla R, Segall-Corrêa AM, Maranha LK, Sampaio MFA, Marin-León L, Panigassi G. An adapted version of the U.S. Department of Agriculture Food Insecurity module is a valid tool for assessing household food insecurity in Campinas, Brazil. J Nutr 2004; 134(8): 1923-8. https://doi.org/10.1093/jn/134.8.1923
https://doi.org/https://doi.org/10.1093/... ^,²2. Segall-Corrêa AM, Marin-León L, Melgar-Quiñonez H, Pérez-Escamilla R. Refinement of the Brazilian household food insecurity measurement scale: recommendation for a 14-item EBIA. Rev Nutr 2014; 27(2): 241-51. https://doi.org/10.1590/1415-52732014000200010
https://doi.org/https://doi.org/10.1590/... . Each affirmative answer corresponds to one point. The final score is analyzed based on cut-off points that classify the households into four categories: food security, mild FI (concern about or no guarantee of access to sufficient quality food), moderate FI (lack of quality food for consumption or limited amount of food for adults), and severe FI (hunger or lack of food for adults and children)¹1. Pérez-Escamilla R, Segall-Corrêa AM, Maranha LK, Sampaio MFA, Marin-León L, Panigassi G. An adapted version of the U.S. Department of Agriculture Food Insecurity module is a valid tool for assessing household food insecurity in Campinas, Brazil. J Nutr 2004; 134(8): 1923-8. https://doi.org/10.1093/jn/134.8.1923
https://doi.org/https://doi.org/10.1093/... ^,²2. Segall-Corrêa AM, Marin-León L, Melgar-Quiñonez H, Pérez-Escamilla R. Refinement of the Brazilian household food insecurity measurement scale: recommendation for a 14-item EBIA. Rev Nutr 2014; 27(2): 241-51. https://doi.org/10.1590/1415-52732014000200010
https://doi.org/https://doi.org/10.1590/... . Two recent studies³3. Reichenheim M, Interlenghi GS, Moraes CL, Segall-Correa AM, Pérez-Escamilla R, Salles-Costa R. A Model-Based Approach to Identify Classes and Respective Cutoffs of the Brazilian Household Food Insecurity Measurement Scale. J Nutr 2016; 146(7): 1356-64. https://doi.org/10.3945/jn.116.231845
https://doi.org/https://doi.org/10.3945/... ^,⁴4. Interlenghi G, Reichenheim M, Segall-Correa AM, Pérez-Escamilla R, Moraes CL, Salles-Costa R. Modeling Optimal Cutoffs for the Brazilian Household Food Insecurity Measurement Scale in a Nationwide Representative Sample. J Nutr 2017; 147(7): 1356-65. https://doi.org/10.3945/jn.117.249581
https://doi.org/https://doi.org/10.3945/... evaluated the psychometric quality of EBIA and identified that the scale has well-defined categories, specifically those of major severity. This finding reinforces the use of EBIA as an instrument to determine household FI.

Internationally, the Food and Agriculture Organization of the United Nations (FAO) has been evaluating FI with the Food Insecurity Experience Scale (a scale similar to EBIA)⁵5. Food and Agriculture Organization, International Fund for Agricultural Development, United Nations Children’s Fund, World Food Programme, World Health Organization. The State of Food Security and Nutrition in the World 2019. Safeguarding against economic slowdowns and downturns. Rome: FAO; 2019.. The most recent FAO report informed that more than 700 million people experienced severe FI in the world in 2018⁵5. Food and Agriculture Organization, International Fund for Agricultural Development, United Nations Children’s Fund, World Food Programme, World Health Organization. The State of Food Security and Nutrition in the World 2019. Safeguarding against economic slowdowns and downturns. Rome: FAO; 2019..

Since its validation, EBIA has been used as a household FI evaluation instrument in national surveys⁶6. Instituto Brasileiro de Geografia e Estatística (IBGE). Diretoria de pesquisas. Coordenação de população e indicadores sócias. Pesquisa Nacional por Amostra de Domicílios - Segurança Alimentar 2004. Rio de Janeiro: IBGE; 2006.^,⁷7. Instituto Brasileiro de Geografia e Estatística (IBGE). Diretoria de pesquisas. Coordenação de população e indicadores sócias. Pesquisa Nacional por Amostra de Domicílios - Segurança Alimentar 2004/2009. Rio de Janeiro: IBGE; 2010.^,⁸8. Instituto Brasileiro de Geografia e Estatística (IBGE). Diretoria de pesquisas. Coordenação de população e indicadores sociais. Pesquisa Nacional por Amostra de Domicílios - Segurança Alimentar 2013. Rio de Janeiro: IBGE ; 2014. and local studies. The most recent national survey showed that 22.6% of Brazilian households experienced some degree of FI⁸8. Instituto Brasileiro de Geografia e Estatística (IBGE). Diretoria de pesquisas. Coordenação de população e indicadores sociais. Pesquisa Nacional por Amostra de Domicílios - Segurança Alimentar 2013. Rio de Janeiro: IBGE ; 2014.. Although this number seems large, it underlines the decreasing trend in FI in Brazil since 2004⁸8. Instituto Brasileiro de Geografia e Estatística (IBGE). Diretoria de pesquisas. Coordenação de população e indicadores sociais. Pesquisa Nacional por Amostra de Domicílios - Segurança Alimentar 2013. Rio de Janeiro: IBGE ; 2014.. Studies that investigated household FI in Brazil emphasized that this condition is related to social disparities⁹9. Marín-León L, Segall-Corrêa AM, Panigassi G, Maranha LK, Sampaio MFA, Pérez-Escamilla R. A percepção de insegurança alimentar em famílias com idosos em Campinas, São Paulo, Brasil. Cad Saúde Pública 2005; 21(5): 1433-40. https://doi.org/10.1590/S0102-311X2005000500016
https://doi.org/https://doi.org/10.1590/... ^,¹⁰10. Panigassi G, Segall-Correa AM, Marin-Leon L, Perez-Escamilla R, Sampaio MFA, Maranha LK. Insegurança alimentar como indicador de inequidade: análise de inquérito populacional. Cad Saúde Pública 2008; 24(10): 2376-84. https://doi.org/10.1590/S0102-311X2008001000018
https://doi.org/https://doi.org/10.1590/... ^,¹¹11. Marin-Leon L, Francisco PMSB, Segall-Correa AM, Panigassi G. Bens de consumo e insegurança alimentar: diferenças de gênero, cor de pele autorreferida e condição socioeconômica. Rev. Bras Epidemiol 2011; 14(3): 398-410. https://doi.org/10.1590/S1415-790X2011000300005
https://doi.org/https://doi.org/10.1590/... , reinforcing the evidence of the associations between the FI measured by EBIA and social indicators (SI). Identifying the life conditions associated with FI is fundamental to recognize its determinants.

In 2011, Kepple and Segall-Correa¹²12. Kepple AW, Segall-Correa AM. Conceituando e medindo segurança alimentar e nutricional. Ciênc Saúde Coletiva 2011; 16(1): 187-99. https://doi.org/10.1590/S1413-81232011000100022
https://doi.org/https://doi.org/10.1590/... proposed a conceptual model for the determinants of FI based on some SIs. However, we highlight that, in the conceptual model presented by the authors, some determinants may influence and/or be influenced by another determinant, especially at the household level.

Among the several studies that have found relationships between SIs and FI measured by EBIA, none has been identified if these SIs cause or influence each other. Consequently, the relationships between all SIs that determine FI have not been described. Such an analysis would be important to define the determinants of household FI, making it possible to focus on actions that are likely to reduce FI.

This systematic review aims to identify which SIs are associated with FI in Brazilian households and how these relationships are explained.

METHODS

This systematic review protocol was registered on the International Prospective Register of Systematic Reviews (PROSPERO) under the registration no. CRD42018106527. Three independent researchers performed the literature search in the Latin American and Caribbean Health Sciences Literature (LILACS) and National Library of Medicine (PubMed) databases. The terms searched in both databases were: “food supply” (MeSH terms); OR “food insecurity” (title); OR “food security” (title); OR “household food insecurity” (title, abstract); OR “household food security” (title, abstract); AND “Brazil” (title, abstract). Since EBIA was validated in 2003-2004, the search involved studies published between 2003 and June 2018 (final data search). We included studies published in Portuguese, English, or Spanish.

The inclusion criteria were:

cross-sectional or observational cohort studies,
studies conducted in the Brazilian population;
studies that used EBIA to assess household FI;
studies that evaluated the association between SIs and household FI.

We excluded literature reviews, experimental studies, qualitative studies, validation of questionnaires for investigation of household FI (or analyses of EBIA cut-off points or concordance between scales of household FI), studies whose main outcome was not household FI, and studies that used SIs only as sample descriptors and/or adjustment variables for the data analysis.

After the literature search, duplicate articles were excluded. The remaining works were evaluated according to the inclusion criteria based on the title and abstract. In the second step, the articles were read in full to assess if the content met the exclusion criteria. The third step involved the quality assessment of the selected articles following the recommendation of the instrument Quality Assessment Tool For Quantitative Studies published by the research group of the Effective Public Health Practice Project¹³13. Effective Public Health Practice Project. Quality Assessment Tool For Quantitative Studies [Internet]. Hamilton: Effective Public Health Practice Project; 1998 [accessed on Jul. 5, 2018]. Available from: Available from: https://merst.ca/ephpp/
https://merst.ca/ephpp/... . We chose this instrument because its items are more appropriate for cross-sectional observational studies, which were the types of studies evaluated (except for one cohort study). In addition to the items present in this instrument, we included questions considered relevant when using EBIA to assess household FI, according to Pérez-Escamilla et al.¹1. Pérez-Escamilla R, Segall-Corrêa AM, Maranha LK, Sampaio MFA, Marin-León L, Panigassi G. An adapted version of the U.S. Department of Agriculture Food Insecurity module is a valid tool for assessing household food insecurity in Campinas, Brazil. J Nutr 2004; 134(8): 1923-8. https://doi.org/10.1093/jn/134.8.1923
https://doi.org/https://doi.org/10.1093/... . These authors declare that:

EBIA must be answered by the person responsible for the food in the household or, in their absence, by someone able to provide information about the subject;
the household must be used as the research domain.

Three independent researchers selected the full articles. Two of them performed quality selection and data extraction, also independently. Any disagreements were resolved by consensus between the researchers. In the absence of consensus, a third evaluator with expertise on the issue was consulted. The agreement between the researchers was evaluated at all times by the kappa calculator. Concordance was determined when the two researchers chose to exclude or include the same article.

After defining which articles to include in this review, we reviewed the studies independently for data extraction. The information to be extracted was previously established. The data collected were year of publication, year of data collection, study population, statistical analysis method, categorization of the dependent variable (household FI), information about the SIs used as independent variables, their categories of analysis, and the significant associations with household FI (when the category of analysis was FI) or with moderate/severe household FI (when it was possible to select these categories). The justifications presented by the authors for the associations found between SIs and household FI were also extracted. In case of doubt, the authors were contacted for clarification; four authors replied with the requested information.

The flow diagram elaborated based on the PRISMA protocol¹⁴14. Moher D, Liberati A, Tetzlaff J, Altman DG. The Prisma Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PloS Med 2009; 6(7): e1000097. https://doi.org/10.1371/journal.pmed.1000097
https://doi.org/https://doi.org/10.1371/... presents the steps for article selection (published as supplemental material). We found 275 original articles. We excluded 214 of them, 78 (28%) for being duplicates and 136 (46%) because they did not meet the inclusion criteria (literature reviews n = 5; qualitative studies n = 19; analysis of policies and/or national government programs - National Food and Nutrition Policy, National Food and Nutrition Security Policy, and National School Feeding Program - n = 17; analyses of family farming and food production n = 35; validations or psychometric analyses of FI scales or analyses of EBIA cut-off points n = 9; articles on food safety n = 8; articles on health or food consumption n = 29; or articles that did not use EBIA as the household FI evaluation scale n = 9, did not evaluate SIs as independent variables n = 3, or did not perform a statistical analysis of the associations between SIs and household FI n = 2). The remaining 61 studies were read in full.

In the next step, we excluded 36 studies because they did not use household FI as the main outcome; did not evaluate SIs or used them only as adjustment variables; or did not analyze the association between SIs and household FI. At the end of this step, 25 articles were evaluated according to quality criteria. Seven studies were excluded: 5 of them did not meet the quality criteria of the instrument Quality Assessment Tool for Quantitative Studies¹³13. Effective Public Health Practice Project. Quality Assessment Tool For Quantitative Studies [Internet]. Hamilton: Effective Public Health Practice Project; 1998 [accessed on Jul. 5, 2018]. Available from: Available from: https://merst.ca/ephpp/
https://merst.ca/ephpp/... , and 2 did not indicate if the EBIA respondent was the person responsible for the food in their household.

This study did not require ethical approval since it was based on secondary data analyses. This paper used the PRISMA guideline¹⁴14. Moher D, Liberati A, Tetzlaff J, Altman DG. The Prisma Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PloS Med 2009; 6(7): e1000097. https://doi.org/10.1371/journal.pmed.1000097
https://doi.org/https://doi.org/10.1371/... to improve the reporting and did not receive any financial support.

RESULTS

This review included 18 articles. The kappa concordance index between the researchers was 0.72 (95%CI 0.42 - 1.00), indicating moderate agreement¹⁵15. Shrout PE. Measurement reliability and agreement in psychiatry. Stat Methods Med Res 1998; 7(3): 301-17. https://doi.org/10.1177/096228029800700306
https://doi.org/https://doi.org/10.1177/... .

The articles were published between 2008 and 2018. Data were collected between 2004 and 2015. The articles selected consisted of cross-sectional studies and only one cohort study¹⁶16. Cabral MJ, Vieira KA, Sawaya AL, Florêncio TMMT. Perfil socioeconômico, nutricional e de ingestão alimentar de beneficiários do Programa Bolsa Família. Estud Av 2013; 27(78): 71-87. https://doi.org/10.1590/S0103-40142013000200006
https://doi.org/https://doi.org/10.1590/... . The samples used in the articles were local populations (from metropolitan and rural areas), data from national surveys carried out in global populations [National Household Survey (Pesquisa Nacional por Amostra de Domicílios - PNAD) and National Survey on Demography and Health (Pesquisa Nacional de Demografia e Saúde - PNDS)], and specific population groups (Quilombola Census).

As to data analysis (Table 1), 88.8% (n = 16) of the studies used multivariate regression models, including Poisson regression (n = 8), logistic regression (n = 6), multinomial logistic regression (n = 1), and log-binomial regression (n = 1). Only one of these studies¹⁷17. Santos TG, Silveira JAC, Longo-Silva G, Ramires EKNM, Menezes RCE. Tendência e fatores associados à insegurança alimentar no Brasil: Pesquisa Nacional por amostra de Domicílios 2004, 2009 e 2013. Cad Saúde Pública 2018; 34(4): e00066917. https://doi.org/10.1590/0102-311x00066917
https://doi.org/https://doi.org/10.1590/... conducted a hierarchical analysis. Household FI was evaluated as the outcome in different ways. The study by Segall-Correa et al.¹⁸18. Segall-Corea AM, Marin-Leon L, Helito H, Perez-Escamilla R, Santos LMP, Paes-Sousa R. Transferência de renda e segurança alimentar no Brasil: análise dos dados nacionais. Rev Nutr 2008; 21(Suppl.): S39-S51. was the only one that used food security + mild FI as the category for the dependent variable. The other articles used one of the following combinations: mild FI + moderate FI + severe FI (n = 4)¹⁹19. Sperandio N, Priore SE. Prevalência de insegurança alimentar domiciliar e fatores associados em famílias com pré-escolares, beneficiárias do Programa Bolsa Família de Viçosa, Minas Gerais, Brasil. Epidemiol Serv Saúde 2015; 24(4): 739-48. https://doi.org/10.5123/S1679-49742015000400016
https://doi.org/https://doi.org/10.5123/... ^,²⁰20. Vianna RPT, Segall-Correa AM. Insegurança alimentar das famílias residentes em municípios do interior do estado da Paraíba, Brasil. Rev Nutr 2008; 21(Suppl.): S111-S22.^,²¹21. Peixoto MRG, Ramos K, Martins KA, Schincaglia RM, Braudes-Silva LA. Insegurança alimentar na área de abrangência do Núcleo de Apoio à Saúde da Família em Itumbiara, Goiás. Epidemiol Serv Saúde 2014; 23(2): 327-36. https://doi.org/10.5123/S1679-49742014000200014
https://doi.org/https://doi.org/10.5123/... ^,²²22. Silva EKP, Medeiros DS, Martins PC, Sousa LA, Lima GP, Rêgo MAS, et al. Insegurança alimentar em comunidades rurais no Nordeste brasileiro: faz diferença ser quilombola? Cad Saúde Pública 2017; 33(4): e00005716. https://doi.org/10.1590/0102-311x00005716
https://doi.org/https://doi.org/10.1590/... ; moderate FI+severe FI (n = 11)¹⁶16. Cabral MJ, Vieira KA, Sawaya AL, Florêncio TMMT. Perfil socioeconômico, nutricional e de ingestão alimentar de beneficiários do Programa Bolsa Família. Estud Av 2013; 27(78): 71-87. https://doi.org/10.1590/S0103-40142013000200006
https://doi.org/https://doi.org/10.1590/... ^,¹⁷17. Santos TG, Silveira JAC, Longo-Silva G, Ramires EKNM, Menezes RCE. Tendência e fatores associados à insegurança alimentar no Brasil: Pesquisa Nacional por amostra de Domicílios 2004, 2009 e 2013. Cad Saúde Pública 2018; 34(4): e00066917. https://doi.org/10.1590/0102-311x00066917
https://doi.org/https://doi.org/10.1590/... ^,²³23. Sabóia RCB, Santos MM. Prevalência de insegurança alimentar e fatores associados em domicílios cobertos pela Estratégia Saúde da Família em Teresina, Piauí, 2012-2013. Epidemiol Serv Saúde 2015; 24(4): 749-58. https://doi.org/10.5123/S1679-49742015000400017
https://doi.org/https://doi.org/10.5123/... ^,²⁴24. De Souza Bittencourt L, Dos Santos SMC, Pinto EJ, Aliaga MA, Ribeiro-Silva RC. Factors associated with food insecurity in households of public students of Salvador city, Bahia, Brazil. J Health Popul Nutr 2013; 31(4): 471-9.^,²⁵25. Ferreira HS, Souza MEDCA, Moura FA, Horta BL. Prevalência e fatores associados à Insegurança Alimentar e Nutricional em famílias dos municípios do norte de alagoas, Brazil, 2010. Ciênc Saúde Coletiva 2014; 19(5): 1533-42. https://doi.org/10.1590/1413-81232014195.06122013
https://doi.org/https://doi.org/10.1590/... ^,²⁶26. Souza BFNJ, Marin-Leon L, Camargo DFM, Segall-Correa AM. Demographic and socioeconomic conditions associated with food insecurity in households in Campinas, SP, Brazil. Rev Nutr 2016; 29(6): 845-57. https://doi.org/10.1590/1678-98652016000600009
https://doi.org/https://doi.org/10.1590/... ^,²⁷27. Gubert MB, Segall-Correa AM, Spaniol AM, Pedroso J, Coelho SEAC, Perez-Escamilla R. Household food insecurity in black-slaves descendant communities in Brazil: has the legacy of slavery truly ended? Public Health Nutr 2017; 20(8): 1513-22. https://doi.org/10.1017/s1368980016003414
https://doi.org/https://doi.org/10.1017/... ^,²⁸28. Facchini LA, Nunes BP, Motta JVS, Tomasi E, Silva SM, Thumé E, et al. Insegurança alimentar no Nordeste e Sul do Brasil: magnitude, fatores associados e padrões de renda per capita para redução das inequidades. Cad Saude Pública 2014; 30(1): 161-74. https://doi.org/10.1590/0102-311X00036013
https://doi.org/https://doi.org/10.1590/... ^,²⁹29. Pedraza DF, Gama JSFA. Segurança alimentar e nutricional de famílias com crianças menores de cinco anos do município de Campina Grande, Paraíba. Rev Bras Epidemiol 2015; 18(4): 906-17. https://doi.org/10.1590/1980-5497201500040018
https://doi.org/https://doi.org/10.1590/... ^,³⁰30. Poblacion AP, Cook JT, Marin-Leon L, Segall-Correa AM, Silveira JAC, Konstantyner T, et al. Food insecurity and the negative impact on brazilian children’s health - why does food security matter for our future prosperity? Brazilian National Survey (PNDS 2006/07). Food Nutr Bull 2016; 37(4): 585-98. https://doi.org/10.1177/0379572116664167
https://doi.org/https://doi.org/10.1177/... ^,³¹31. Guerra LDS, Espinosa MM, Bezerra ACD, Guimarães LV, Lima-Lopes MA. Insegurança alimentar em domicílios com adolescentes da Amazônia Legal Brasileira: prevalência e fatores associados. Cad Saúde Pública 2013; 29(2): 335-48. https://doi.org/10.1590/S0102-311X2013000200020
https://doi.org/https://doi.org/10.1590/... ; or severe FI (n = 2)³²32. Gubert MB, Benício MHDA, Silva JP, Rosa TEC, Santos SM, Santos LMP. Use of a predictive model for food insecurity estimates in Brazil. Arch Latinoam Nutr 2010; 60(2): 119-25.^,³³33. Salles-Costa R, Pereira R, Vasconcellos MTL, Veiga GV, Marins VMR, Jardim BC, et al. Associação entre fatores socioeconômicos e insegurança alimentar: estudo de base populacional na Região Metropolitana do Rio de Janeiro, Brasil. Rev Nutr 2008; 21 (Suppl. 0): S99-S109..

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Table 1.
General characteristics and main results of the studies included in the systematic review. 2018.

Household FI was associated with lower monthly per capita income; living in unfinished houses or houses with poor-quality construction material; a large number of residents per household or bedroom; a large number of residents under 18 years of age per household; lower educational level of the head of household; female, black and/or multiracial, older, unemployed, or informally employed head of household; living in urban areas or the North or Northeast regions; not having a refrigerator or other major household goods; participating in a conditional cash transfer program; worse socioeconomic classification; head of household living without a partner; untreated drinking water; being local (when the region had many migrants); being a descendant of black slaves (quilombola); living in houses with few rooms; and lack of public water supply, public sewer, or toilet at home (Table 1).

The discussions of the studies were analyzed to identify how the authors explained the relationships found between SIs and FI. We organized these explanations in a conceptual model (Figure 1) to help visualize the relationships and systematize the associations. Figure 1 shows three possibilities to justify the way SIs and household FI are associated: (A) direct relationship between SIs and FI, (B) relationship between SIs and FI mediated by income, and (C) relationship between SIs and FI mediated by another social indicator and income. Based on Figure 1, income had a central role in the associations with FI.

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Figure 1.
Conceptual model of the relationships between social indicators and food insecurity. Systematic review. 2018.

Table 1 shows that, in 16 articles (88.9%), at least one income-related SI (monthly income/per capita income, participating in a conditional cash transfer program, socioeconomic classification, and/or not having major household goods) had a significant association with FI. In most of these studies (66.7%, n = 12), these SIs presented the strongest correlations. Thus, income-related SIs were the main determinants of FI. The role of income as a mediator in the association between SIs and FI (as presented in Figure 1) may explain this result. It is important to consider whether the mediation role played by income increases the strength of its association with FI.

DISCUSSION

The use of EBIA in population studies enables researchers to identify households where the quality and quantity of food consumed among the residents is compromised¹1. Pérez-Escamilla R, Segall-Corrêa AM, Maranha LK, Sampaio MFA, Marin-León L, Panigassi G. An adapted version of the U.S. Department of Agriculture Food Insecurity module is a valid tool for assessing household food insecurity in Campinas, Brazil. J Nutr 2004; 134(8): 1923-8. https://doi.org/10.1093/jn/134.8.1923
https://doi.org/https://doi.org/10.1093/... , allowing us to verify relationships with social inequalities in the country. In the last 15 years, the identification of SIs related to FI has contributed to defining the characteristics of households experiencing difficulties in accessing food of sufficient quality and quantity⁵5. Food and Agriculture Organization, International Fund for Agricultural Development, United Nations Children’s Fund, World Food Programme, World Health Organization. The State of Food Security and Nutrition in the World 2019. Safeguarding against economic slowdowns and downturns. Rome: FAO; 2019.. Studies on the subject have highlighted that FI measured by EBIA correlates with unfavorable social conditions, represented by SIs. Since these indicators are used to evaluate adverse living conditions, as well as to characterize poverty³⁴34. Soligo V. Indicadores: conceito e complexidade do mensurar em estudos de fenômenos sociais. Est Aval Educ 2012; 23(52): 12-25., their use in studies that analyze FI is necessary for identifying possible knowledge areas linked to FI.

The studies included in this review show how FI measured by EBIA, especially in its most alarming forms (moderate and severe FI), can reach a range of social inequalities. It was also possible to identify income as a convergence point for the relationship between several SIs and FI.

Regarding the direct relationship, the studies by Gubert et al.³²32. Gubert MB, Benício MHDA, Silva JP, Rosa TEC, Santos SM, Santos LMP. Use of a predictive model for food insecurity estimates in Brazil. Arch Latinoam Nutr 2010; 60(2): 119-25., Cabral et al.¹⁶16. Cabral MJ, Vieira KA, Sawaya AL, Florêncio TMMT. Perfil socioeconômico, nutricional e de ingestão alimentar de beneficiários do Programa Bolsa Família. Estud Av 2013; 27(78): 71-87. https://doi.org/10.1590/S0103-40142013000200006
https://doi.org/https://doi.org/10.1590/... , and Sabóia e Santos²³23. Sabóia RCB, Santos MM. Prevalência de insegurança alimentar e fatores associados em domicílios cobertos pela Estratégia Saúde da Família em Teresina, Piauí, 2012-2013. Epidemiol Serv Saúde 2015; 24(4): 749-58. https://doi.org/10.5123/S1679-49742015000400017
https://doi.org/https://doi.org/10.5123/... revealed that lower incomes compromise the acquisition of food of sufficient quality and quantity. The lower educational level of the head of household has an impact on FI since it can affect the financial administration and maintenance of adequate food intake, including the choice of quality food²⁴24. De Souza Bittencourt L, Dos Santos SMC, Pinto EJ, Aliaga MA, Ribeiro-Silva RC. Factors associated with food insecurity in households of public students of Salvador city, Bahia, Brazil. J Health Popul Nutr 2013; 31(4): 471-9.^,²⁵25. Ferreira HS, Souza MEDCA, Moura FA, Horta BL. Prevalência e fatores associados à Insegurança Alimentar e Nutricional em famílias dos municípios do norte de alagoas, Brazil, 2010. Ciênc Saúde Coletiva 2014; 19(5): 1533-42. https://doi.org/10.1590/1413-81232014195.06122013
https://doi.org/https://doi.org/10.1590/... ^,²⁶26. Souza BFNJ, Marin-Leon L, Camargo DFM, Segall-Correa AM. Demographic and socioeconomic conditions associated with food insecurity in households in Campinas, SP, Brazil. Rev Nutr 2016; 29(6): 845-57. https://doi.org/10.1590/1678-98652016000600009
https://doi.org/https://doi.org/10.1590/... . In turn, untreated drinking water and the lack of public water supply (also included in sanitation) compromises the access to water, an essential food²⁵25. Ferreira HS, Souza MEDCA, Moura FA, Horta BL. Prevalência e fatores associados à Insegurança Alimentar e Nutricional em famílias dos municípios do norte de alagoas, Brazil, 2010. Ciênc Saúde Coletiva 2014; 19(5): 1533-42. https://doi.org/10.1590/1413-81232014195.06122013
https://doi.org/https://doi.org/10.1590/... . The studies by Segall-Correa et al.¹⁸18. Segall-Corea AM, Marin-Leon L, Helito H, Perez-Escamilla R, Santos LMP, Paes-Sousa R. Transferência de renda e segurança alimentar no Brasil: análise dos dados nacionais. Rev Nutr 2008; 21(Suppl.): S39-S51., Gubert et al.²⁷27. Gubert MB, Segall-Correa AM, Spaniol AM, Pedroso J, Coelho SEAC, Perez-Escamilla R. Household food insecurity in black-slaves descendant communities in Brazil: has the legacy of slavery truly ended? Public Health Nutr 2017; 20(8): 1513-22. https://doi.org/10.1017/s1368980016003414
https://doi.org/https://doi.org/10.1017/... , and Santos et al.¹⁷17. Santos TG, Silveira JAC, Longo-Silva G, Ramires EKNM, Menezes RCE. Tendência e fatores associados à insegurança alimentar no Brasil: Pesquisa Nacional por amostra de Domicílios 2004, 2009 e 2013. Cad Saúde Pública 2018; 34(4): e00066917. https://doi.org/10.1590/0102-311x00066917
https://doi.org/https://doi.org/10.1590/... reported that households located in urban areas and the North/Northeast regions had worse living conditions, higher expenditure on non-food items, and greater difficulties in accessing food not produced in those respective areas.

The area of residence (urban/rural) presents a dual consideration, since both areas can have a direct relationship with FI or food security. In some studies, rural areas are a protective factor against FI due to the greater possibility of food production for family consumption and lower expenses on transportation, clothing, and others³²32. Gubert MB, Benício MHDA, Silva JP, Rosa TEC, Santos SM, Santos LMP. Use of a predictive model for food insecurity estimates in Brazil. Arch Latinoam Nutr 2010; 60(2): 119-25.^,¹⁸18. Segall-Corea AM, Marin-Leon L, Helito H, Perez-Escamilla R, Santos LMP, Paes-Sousa R. Transferência de renda e segurança alimentar no Brasil: análise dos dados nacionais. Rev Nutr 2008; 21(Suppl.): S39-S51.. In other articles, families living in rural areas a had higher risk of FI because they did not have direct access to food, nor the possibility of comparing prices in different grocery stores²⁷27. Gubert MB, Segall-Correa AM, Spaniol AM, Pedroso J, Coelho SEAC, Perez-Escamilla R. Household food insecurity in black-slaves descendant communities in Brazil: has the legacy of slavery truly ended? Public Health Nutr 2017; 20(8): 1513-22. https://doi.org/10.1017/s1368980016003414
https://doi.org/https://doi.org/10.1017/... .

We underline that among the SIs with association explained by income, the direction was always inverse. Namely, the worse the SI level, the lower the household income, and, consequently, the greater the household FI¹⁸18. Segall-Corea AM, Marin-Leon L, Helito H, Perez-Escamilla R, Santos LMP, Paes-Sousa R. Transferência de renda e segurança alimentar no Brasil: análise dos dados nacionais. Rev Nutr 2008; 21(Suppl.): S39-S51.^,²⁴24. De Souza Bittencourt L, Dos Santos SMC, Pinto EJ, Aliaga MA, Ribeiro-Silva RC. Factors associated with food insecurity in households of public students of Salvador city, Bahia, Brazil. J Health Popul Nutr 2013; 31(4): 471-9.^,²⁵25. Ferreira HS, Souza MEDCA, Moura FA, Horta BL. Prevalência e fatores associados à Insegurança Alimentar e Nutricional em famílias dos municípios do norte de alagoas, Brazil, 2010. Ciênc Saúde Coletiva 2014; 19(5): 1533-42. https://doi.org/10.1590/1413-81232014195.06122013
https://doi.org/https://doi.org/10.1590/... ^,²⁶26. Souza BFNJ, Marin-Leon L, Camargo DFM, Segall-Correa AM. Demographic and socioeconomic conditions associated with food insecurity in households in Campinas, SP, Brazil. Rev Nutr 2016; 29(6): 845-57. https://doi.org/10.1590/1678-98652016000600009
https://doi.org/https://doi.org/10.1590/... ^,²⁷27. Gubert MB, Segall-Correa AM, Spaniol AM, Pedroso J, Coelho SEAC, Perez-Escamilla R. Household food insecurity in black-slaves descendant communities in Brazil: has the legacy of slavery truly ended? Public Health Nutr 2017; 20(8): 1513-22. https://doi.org/10.1017/s1368980016003414
https://doi.org/https://doi.org/10.1017/... ^,²⁸28. Facchini LA, Nunes BP, Motta JVS, Tomasi E, Silva SM, Thumé E, et al. Insegurança alimentar no Nordeste e Sul do Brasil: magnitude, fatores associados e padrões de renda per capita para redução das inequidades. Cad Saude Pública 2014; 30(1): 161-74. https://doi.org/10.1590/0102-311X00036013
https://doi.org/https://doi.org/10.1590/... ^,²⁹29. Pedraza DF, Gama JSFA. Segurança alimentar e nutricional de famílias com crianças menores de cinco anos do município de Campina Grande, Paraíba. Rev Bras Epidemiol 2015; 18(4): 906-17. https://doi.org/10.1590/1980-5497201500040018
https://doi.org/https://doi.org/10.1590/... ^,³⁴34. Soligo V. Indicadores: conceito e complexidade do mensurar em estudos de fenômenos sociais. Est Aval Educ 2012; 23(52): 12-25..

For the SIs explained by the mediation of another SI and income, the relationship between them and FI was initially mediated either by the employment status or the educational level of the head of household, which would correlate with lower income and could, in turn, justify the FI. When the head of household had a lower educational level or was female, they were more likely to have a lower employment status or worse working conditions, leading to lower family income¹⁹19. Sperandio N, Priore SE. Prevalência de insegurança alimentar domiciliar e fatores associados em famílias com pré-escolares, beneficiárias do Programa Bolsa Família de Viçosa, Minas Gerais, Brasil. Epidemiol Serv Saúde 2015; 24(4): 739-48. https://doi.org/10.5123/S1679-49742015000400016
https://doi.org/https://doi.org/10.5123/... ^,²³23. Sabóia RCB, Santos MM. Prevalência de insegurança alimentar e fatores associados em domicílios cobertos pela Estratégia Saúde da Família em Teresina, Piauí, 2012-2013. Epidemiol Serv Saúde 2015; 24(4): 749-58. https://doi.org/10.5123/S1679-49742015000400017
https://doi.org/https://doi.org/10.5123/... ^,²⁴24. De Souza Bittencourt L, Dos Santos SMC, Pinto EJ, Aliaga MA, Ribeiro-Silva RC. Factors associated with food insecurity in households of public students of Salvador city, Bahia, Brazil. J Health Popul Nutr 2013; 31(4): 471-9.^,²⁶26. Souza BFNJ, Marin-Leon L, Camargo DFM, Segall-Correa AM. Demographic and socioeconomic conditions associated with food insecurity in households in Campinas, SP, Brazil. Rev Nutr 2016; 29(6): 845-57. https://doi.org/10.1590/1678-98652016000600009
https://doi.org/https://doi.org/10.1590/... ^,²⁷27. Gubert MB, Segall-Correa AM, Spaniol AM, Pedroso J, Coelho SEAC, Perez-Escamilla R. Household food insecurity in black-slaves descendant communities in Brazil: has the legacy of slavery truly ended? Public Health Nutr 2017; 20(8): 1513-22. https://doi.org/10.1017/s1368980016003414
https://doi.org/https://doi.org/10.1017/... ^,³²32. Gubert MB, Benício MHDA, Silva JP, Rosa TEC, Santos SM, Santos LMP. Use of a predictive model for food insecurity estimates in Brazil. Arch Latinoam Nutr 2010; 60(2): 119-25.. Similarly, black or multiracial heads of households tended to have a lower educational level³²32. Gubert MB, Benício MHDA, Silva JP, Rosa TEC, Santos SM, Santos LMP. Use of a predictive model for food insecurity estimates in Brazil. Arch Latinoam Nutr 2010; 60(2): 119-25.^,²⁷27. Gubert MB, Segall-Correa AM, Spaniol AM, Pedroso J, Coelho SEAC, Perez-Escamilla R. Household food insecurity in black-slaves descendant communities in Brazil: has the legacy of slavery truly ended? Public Health Nutr 2017; 20(8): 1513-22. https://doi.org/10.1017/s1368980016003414
https://doi.org/https://doi.org/10.1017/... , and, consequently, these households had a lower family income.

All relationships presented as explanations for the associations of SIs with household FI reported by the authors of the articles included in this review can be found in national surveys³⁵35. Instituto Brasileiro de Geografia e Estatística (IBGE). Diretoria de pesquisas. Coordenação de população e indicadores sociais. Síntese de indicadores sociais: uma análise das condições de vida da população brasileira 2017. Rio de Janeiro: IBGE ; 2017.^,³⁶36. Instituto Brasileiro de Geografia e Estatística (IBGE). IBGE inicia a Pesquisa de Orçamentos Familiares (POF) 2017/2018 [Internet]. Rio de Janeiro: IBGE ; 2017 [accessed on Ago. 5, 2018]. Available at: Available at: https://agenciadenoticias.ibge.gov.br/agencia-sala-de-imprensa/2013-agencia-de-noticias/releases/10448-ibge-inicia-a-pesquisa-de-orcamentos-familiares-pof-2017-2018.html
https://agenciadenoticias.ibge.gov.br/ag... . Some SIs had a relationship with FI that was explained in more than one way. Therefore, we emphasize the need to elaborate a theoretical conceptual model indicating which relationships are more appropriate for analyses whose outcome is FI.

This review also detected that the analyses published to date are not enough to understand the SI effects on the causality of FI. We suggest the use of new analysis models to improve the understanding of the causal relationships between SIs and household FI and clearly identify the determinants of FI.

Despite the methodological rigor in the search for articles that support the analysis of the association between SIs and household FI, the present study has some limitations. The option of restricting the analysis to studies that used EBIA to identify household FI may interfere with the SIs associated with FI, besides limiting the evaluations to investigations conducted in Brazil. However, as EBIA is a valid instrument for the household domain¹1. Pérez-Escamilla R, Segall-Corrêa AM, Maranha LK, Sampaio MFA, Marin-León L, Panigassi G. An adapted version of the U.S. Department of Agriculture Food Insecurity module is a valid tool for assessing household food insecurity in Campinas, Brazil. J Nutr 2004; 134(8): 1923-8. https://doi.org/10.1093/jn/134.8.1923
https://doi.org/https://doi.org/10.1093/... ^,⁴4. Interlenghi G, Reichenheim M, Segall-Correa AM, Pérez-Escamilla R, Moraes CL, Salles-Costa R. Modeling Optimal Cutoffs for the Brazilian Household Food Insecurity Measurement Scale in a Nationwide Representative Sample. J Nutr 2017; 147(7): 1356-65. https://doi.org/10.3945/jn.117.249581
https://doi.org/https://doi.org/10.3945/... and used in national surveys and many local studies⁸8. Instituto Brasileiro de Geografia e Estatística (IBGE). Diretoria de pesquisas. Coordenação de população e indicadores sociais. Pesquisa Nacional por Amostra de Domicílios - Segurança Alimentar 2013. Rio de Janeiro: IBGE ; 2014., we decided to adopt it to detect household FI in this review. We also opted not to perform a meta-analysis because our objective was to identify the SIs related to household FI and not to find the impact of SIs on household FI.

CONCLUSION

The SIs associated with FI measured by EBIA also characterize the family’s poverty. Therefore, this review demonstrated relationships between adverse social conditions and FI. We could also identify that, while some SIs were directly related to FI, others presented relationships mediated by income and/or another SI. Income assumed a central role in the mediation between several SIs and FI. However, the analysis methods of the studies included in this review did not allow us to investigate this mediation.

In this context, although the present systematic review has detected the causality generated by determinants of household FI, we need to improve data analysis to isolate the effect of each SI on FI of Brazilian families, and, consequently, understand the relationships between them. Thus, household FI measured by EBIA is a broad and consistent social vulnerability index.

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Segall-Corrêa AM, Marin-León L, Melgar-Quiñonez H, Pérez-Escamilla R. Refinement of the Brazilian household food insecurity measurement scale: recommendation for a 14-item EBIA. Rev Nutr 2014; 27(2): 241-51. https://doi.org/10.1590/1415-52732014000200010
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¹⁹
Sperandio N, Priore SE. Prevalência de insegurança alimentar domiciliar e fatores associados em famílias com pré-escolares, beneficiárias do Programa Bolsa Família de Viçosa, Minas Gerais, Brasil. Epidemiol Serv Saúde 2015; 24(4): 739-48. https://doi.org/10.5123/S1679-49742015000400016
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²³
Sabóia RCB, Santos MM. Prevalência de insegurança alimentar e fatores associados em domicílios cobertos pela Estratégia Saúde da Família em Teresina, Piauí, 2012-2013. Epidemiol Serv Saúde 2015; 24(4): 749-58. https://doi.org/10.5123/S1679-49742015000400017
» https://doi.org/https://doi.org/10.5123/S1679-49742015000400017
²⁴
De Souza Bittencourt L, Dos Santos SMC, Pinto EJ, Aliaga MA, Ribeiro-Silva RC. Factors associated with food insecurity in households of public students of Salvador city, Bahia, Brazil. J Health Popul Nutr 2013; 31(4): 471-9.
²⁵
Ferreira HS, Souza MEDCA, Moura FA, Horta BL. Prevalência e fatores associados à Insegurança Alimentar e Nutricional em famílias dos municípios do norte de alagoas, Brazil, 2010. Ciênc Saúde Coletiva 2014; 19(5): 1533-42. https://doi.org/10.1590/1413-81232014195.06122013
» https://doi.org/https://doi.org/10.1590/1413-81232014195.06122013
²⁶
Souza BFNJ, Marin-Leon L, Camargo DFM, Segall-Correa AM. Demographic and socioeconomic conditions associated with food insecurity in households in Campinas, SP, Brazil. Rev Nutr 2016; 29(6): 845-57. https://doi.org/10.1590/1678-98652016000600009
» https://doi.org/https://doi.org/10.1590/1678-98652016000600009
²⁷
Gubert MB, Segall-Correa AM, Spaniol AM, Pedroso J, Coelho SEAC, Perez-Escamilla R. Household food insecurity in black-slaves descendant communities in Brazil: has the legacy of slavery truly ended? Public Health Nutr 2017; 20(8): 1513-22. https://doi.org/10.1017/s1368980016003414
» https://doi.org/https://doi.org/10.1017/s1368980016003414
²⁸
Facchini LA, Nunes BP, Motta JVS, Tomasi E, Silva SM, Thumé E, et al. Insegurança alimentar no Nordeste e Sul do Brasil: magnitude, fatores associados e padrões de renda per capita para redução das inequidades. Cad Saude Pública 2014; 30(1): 161-74. https://doi.org/10.1590/0102-311X00036013
» https://doi.org/https://doi.org/10.1590/0102-311X00036013
²⁹
Pedraza DF, Gama JSFA. Segurança alimentar e nutricional de famílias com crianças menores de cinco anos do município de Campina Grande, Paraíba. Rev Bras Epidemiol 2015; 18(4): 906-17. https://doi.org/10.1590/1980-5497201500040018
» https://doi.org/https://doi.org/10.1590/1980-5497201500040018
³⁰
Poblacion AP, Cook JT, Marin-Leon L, Segall-Correa AM, Silveira JAC, Konstantyner T, et al. Food insecurity and the negative impact on brazilian children’s health - why does food security matter for our future prosperity? Brazilian National Survey (PNDS 2006/07). Food Nutr Bull 2016; 37(4): 585-98. https://doi.org/10.1177/0379572116664167
» https://doi.org/https://doi.org/10.1177/0379572116664167
³¹
Guerra LDS, Espinosa MM, Bezerra ACD, Guimarães LV, Lima-Lopes MA. Insegurança alimentar em domicílios com adolescentes da Amazônia Legal Brasileira: prevalência e fatores associados. Cad Saúde Pública 2013; 29(2): 335-48. https://doi.org/10.1590/S0102-311X2013000200020
» https://doi.org/https://doi.org/10.1590/S0102-311X2013000200020
³²
Gubert MB, Benício MHDA, Silva JP, Rosa TEC, Santos SM, Santos LMP. Use of a predictive model for food insecurity estimates in Brazil. Arch Latinoam Nutr 2010; 60(2): 119-25.
³³
Salles-Costa R, Pereira R, Vasconcellos MTL, Veiga GV, Marins VMR, Jardim BC, et al. Associação entre fatores socioeconômicos e insegurança alimentar: estudo de base populacional na Região Metropolitana do Rio de Janeiro, Brasil. Rev Nutr 2008; 21 (Suppl. 0): S99-S109.
³⁴
Soligo V. Indicadores: conceito e complexidade do mensurar em estudos de fenômenos sociais. Est Aval Educ 2012; 23(52): 12-25.
³⁵
Instituto Brasileiro de Geografia e Estatística (IBGE). Diretoria de pesquisas. Coordenação de população e indicadores sociais. Síntese de indicadores sociais: uma análise das condições de vida da população brasileira 2017. Rio de Janeiro: IBGE ; 2017.
³⁶
Instituto Brasileiro de Geografia e Estatística (IBGE). IBGE inicia a Pesquisa de Orçamentos Familiares (POF) 2017/2018 [Internet]. Rio de Janeiro: IBGE ; 2017 [accessed on Ago. 5, 2018]. Available at: Available at: https://agenciadenoticias.ibge.gov.br/agencia-sala-de-imprensa/2013-agencia-de-noticias/releases/10448-ibge-inicia-a-pesquisa-de-orcamentos-familiares-pof-2017-2018.html
» https://agenciadenoticias.ibge.gov.br/agencia-sala-de-imprensa/2013-agencia-de-noticias/releases/10448-ibge-inicia-a-pesquisa-de-orcamentos-familiares-pof-2017-2018.html
³⁷
Banco Central do Brasil [Internet]. [cited on Oct. 26, 2017]. Available at: Available at: https://www.bcb.gov.br/acessoinformacao/legado?url=https:%2F%2Fwww4.bcb.gov.br%2Fpec%2Fconversao%2Fconversao.asp/
» https://www.bcb.gov.br/acessoinformacao/legado?url=https:%2F%2Fwww4.bcb.gov.br%2Fpec%2Fconversao%2Fconversao.asp/
³⁸
Portal Brasil. Salário mínimo [Internet]. [cited on Oct. 26, 2017]. Available at: Available at: http://www.portalbrasil.net/salariominimo.htm
» http://www.portalbrasil.net/salariominimo.htm

Financial support: none

Publication Dates

Publication in this collection
06 July 2020
Date of issue
2020

History

Received
05 Apr 2019
Reviewed
18 Aug 2019
Accepted
03 Sept 2019

This is an open-access article distributed under the terms of the Creative Commons Attribution License

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Silva EKP, Medeiros DS, Martins PC, Sousa LA, Lima GP, Rêgo MAS, et al. Insegurança alimentar em comunidades rurais no Nordeste brasileiro: faz diferença ser quilombola? Cad Saúde Pública 2017; 33(4): e00005716. https://doi.org/10.1590/0102-311x00005716
» https://doi.org/https://doi.org/10.1590/0102-311x00005716

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Sabóia RCB, Santos MM. Prevalência de insegurança alimentar e fatores associados em domicílios cobertos pela Estratégia Saúde da Família em Teresina, Piauí, 2012-2013. Epidemiol Serv Saúde 2015; 24(4): 749-58. https://doi.org/10.5123/S1679-49742015000400017
» https://doi.org/https://doi.org/10.5123/S1679-49742015000400017

[24] ²⁴
De Souza Bittencourt L, Dos Santos SMC, Pinto EJ, Aliaga MA, Ribeiro-Silva RC. Factors associated with food insecurity in households of public students of Salvador city, Bahia, Brazil. J Health Popul Nutr 2013; 31(4): 471-9.

[25] ²⁵
Ferreira HS, Souza MEDCA, Moura FA, Horta BL. Prevalência e fatores associados à Insegurança Alimentar e Nutricional em famílias dos municípios do norte de alagoas, Brazil, 2010. Ciênc Saúde Coletiva 2014; 19(5): 1533-42. https://doi.org/10.1590/1413-81232014195.06122013
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Souza BFNJ, Marin-Leon L, Camargo DFM, Segall-Correa AM. Demographic and socioeconomic conditions associated with food insecurity in households in Campinas, SP, Brazil. Rev Nutr 2016; 29(6): 845-57. https://doi.org/10.1590/1678-98652016000600009
» https://doi.org/https://doi.org/10.1590/1678-98652016000600009

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Gubert MB, Segall-Correa AM, Spaniol AM, Pedroso J, Coelho SEAC, Perez-Escamilla R. Household food insecurity in black-slaves descendant communities in Brazil: has the legacy of slavery truly ended? Public Health Nutr 2017; 20(8): 1513-22. https://doi.org/10.1017/s1368980016003414
» https://doi.org/https://doi.org/10.1017/s1368980016003414

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Facchini LA, Nunes BP, Motta JVS, Tomasi E, Silva SM, Thumé E, et al. Insegurança alimentar no Nordeste e Sul do Brasil: magnitude, fatores associados e padrões de renda per capita para redução das inequidades. Cad Saude Pública 2014; 30(1): 161-74. https://doi.org/10.1590/0102-311X00036013
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Poblacion AP, Cook JT, Marin-Leon L, Segall-Correa AM, Silveira JAC, Konstantyner T, et al. Food insecurity and the negative impact on brazilian children’s health - why does food security matter for our future prosperity? Brazilian National Survey (PNDS 2006/07). Food Nutr Bull 2016; 37(4): 585-98. https://doi.org/10.1177/0379572116664167
» https://doi.org/https://doi.org/10.1177/0379572116664167

[31] ³¹
Guerra LDS, Espinosa MM, Bezerra ACD, Guimarães LV, Lima-Lopes MA. Insegurança alimentar em domicílios com adolescentes da Amazônia Legal Brasileira: prevalência e fatores associados. Cad Saúde Pública 2013; 29(2): 335-48. https://doi.org/10.1590/S0102-311X2013000200020
» https://doi.org/https://doi.org/10.1590/S0102-311X2013000200020

[32] ³²
Gubert MB, Benício MHDA, Silva JP, Rosa TEC, Santos SM, Santos LMP. Use of a predictive model for food insecurity estimates in Brazil. Arch Latinoam Nutr 2010; 60(2): 119-25.

[33] ³³
Salles-Costa R, Pereira R, Vasconcellos MTL, Veiga GV, Marins VMR, Jardim BC, et al. Associação entre fatores socioeconômicos e insegurança alimentar: estudo de base populacional na Região Metropolitana do Rio de Janeiro, Brasil. Rev Nutr 2008; 21 (Suppl. 0): S99-S109.

[34] ³⁴
Soligo V. Indicadores: conceito e complexidade do mensurar em estudos de fenômenos sociais. Est Aval Educ 2012; 23(52): 12-25.

[35] ³⁵
Instituto Brasileiro de Geografia e Estatística (IBGE). Diretoria de pesquisas. Coordenação de população e indicadores sociais. Síntese de indicadores sociais: uma análise das condições de vida da população brasileira 2017. Rio de Janeiro: IBGE ; 2017.

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Instituto Brasileiro de Geografia e Estatística (IBGE). IBGE inicia a Pesquisa de Orçamentos Familiares (POF) 2017/2018 [Internet]. Rio de Janeiro: IBGE ; 2017 [accessed on Ago. 5, 2018]. Available at: Available at: https://agenciadenoticias.ibge.gov.br/agencia-sala-de-imprensa/2013-agencia-de-noticias/releases/10448-ibge-inicia-a-pesquisa-de-orcamentos-familiares-pof-2017-2018.html
» https://agenciadenoticias.ibge.gov.br/agencia-sala-de-imprensa/2013-agencia-de-noticias/releases/10448-ibge-inicia-a-pesquisa-de-orcamentos-familiares-pof-2017-2018.html

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Banco Central do Brasil [Internet]. [cited on Oct. 26, 2017]. Available at: Available at: https://www.bcb.gov.br/acessoinformacao/legado?url=https:%2F%2Fwww4.bcb.gov.br%2Fpec%2Fconversao%2Fconversao.asp/
» https://www.bcb.gov.br/acessoinformacao/legado?url=https:%2F%2Fwww4.bcb.gov.br%2Fpec%2Fconversao%2Fconversao.asp/

[38] ³⁸
Portal Brasil. Salário mínimo [Internet]. [cited on Oct. 26, 2017]. Available at: Available at: http://www.portalbrasil.net/salariominimo.htm
» http://www.portalbrasil.net/salariominimo.htm

Studies (n)	Statistical measure	Social indicators associated with food insecurity/food security*	Measure (confidence intervals)*
General HHs. PB.¹⁶16. Cabral MJ, Vieira KA, Sawaya AL, Florêncio TMMT. Perfil socioeconômico, nutricional e de ingestão alimentar de beneficiários do Programa Bolsa Família. Estud Av 2013; 27(78): 71-87. https://doi.org/10.1590/S0103-40142013000200006 https://doi.org/https://doi.org/10.1590/... (406)	χ²/proportion (%)		2005	2011
		Improvement in HH income	39.5%	24.4%
		Continued to participate in a CCTP	61.5%	45.9%
		Stopped participating in a CCTP	41.5%	19.5%
General HHs (data from PNAD). Brazil¹⁷17. Santos TG, Silveira JAC, Longo-Silva G, Ramires EKNM, Menezes RCE. Tendência e fatores associados à insegurança alimentar no Brasil: Pesquisa Nacional por amostra de Domicílios 2004, 2009 e 2013. Cad Saúde Pública 2018; 34(4): e00066917. https://doi.org/10.1590/0102-311x00066917 https://doi.org/https://doi.org/10.1590/... (2004 = 108,377; 2009 = 117,037; 2013 = 110,655)	Log-binomial regression / PR Hierarchical model	Results from the 3^rd level	2013**
		Having major HH goods	2.08 (1.99 - 2.17)
		Head of HH with ≤ 4 years of schooling	1.94 (1.86 - 2.01)
		Living in the North/Northeast regions	1.81 (1.72 - 1.91)
		Non-white head of HH	1.58 (1.52 - 1.65)
		Head of HH aged < 60 years	1.52 (1.46 - 1.59)
		> 2 residents/bedroom	1.45 (1.40 - 1.50)
		Inadequate sanitation	1.41 (1.35 - 1.48)
		Female head of HH	1.32 (1.28 - 1.37)
		Unemployed head of HH	1.26 (1.20 - 1.31)
		Living in a rural area	0.88 (0.83 - 0.93)
HHs with severe food insecurity (data from Census and PNAD). Brazil³²32. Gubert MB, Benício MHDA, Silva JP, Rosa TEC, Santos SM, Santos LMP. Use of a predictive model for food insecurity estimates in Brazil. Arch Latinoam Nutr 2010; 60(2): 119-25. (111,922)	MLR/OR	Per capita income < 1/4 MW^b	11.33 (10.08 - 12.74)
		Head of HH with < 1 year of schooling	4.76 (4.19 - 5.42)
		Living in Roraima	3.16 (2.06 - 4.83)
		Lack of public water supply	1.78 (1.59 - 1.99)
		Female head of HH	1.60 (1.50 - 1.71)
		≥ 3 residents aged < 10 years/HH	1.57 (1.42 - 1.74)
		Black and/or multiracial head of HH	1.49 (1.39 - 1.61)
		No. of residents/HH	0.93 (-)
		Living in a rural area	0.50 (0.44 - 0.58)
HHs covered by ESF. PI²³23. Sabóia RCB, Santos MM. Prevalência de insegurança alimentar e fatores associados em domicílios cobertos pela Estratégia Saúde da Família em Teresina, Piauí, 2012-2013. Epidemiol Serv Saúde 2015; 24(4): 749-58. https://doi.org/10.5123/S1679-49742015000400017 https://doi.org/https://doi.org/10.5123/... (323)	MLR/OR	Participating in a CCTP	4.10 (1.13 - 14.90)
		≤ 5 rooms/HH	3.65 (1.31 - 10.15)
		Per capita income <½ MW^g	3.52 (1.02 - 12.74)
		Unfinished house	0.34 (0.16 - 0.72)
		Female head of HH	0.14 (0.04-0.56)
HHs with children/adolescents attending public school. BA²⁴24. De Souza Bittencourt L, Dos Santos SMC, Pinto EJ, Aliaga MA, Ribeiro-Silva RC. Factors associated with food insecurity in households of public students of Salvador city, Bahia, Brazil. J Health Popul Nutr 2013; 31(4): 471-9. (1,101)	MLR/OR	Per capita income ≤ ¼ MW^d	2.63 (1.68 - 4.08)
General HHs. AL.²⁵25. Ferreira HS, Souza MEDCA, Moura FA, Horta BL. Prevalência e fatores associados à Insegurança Alimentar e Nutricional em famílias dos municípios do norte de alagoas, Brazil, 2010. Ciênc Saúde Coletiva 2014; 19(5): 1533-42. https://doi.org/10.1590/1413-81232014195.06122013 https://doi.org/https://doi.org/10.1590/... (1,444)	MPR/PR	Untreated drinking water	2.64 (1.47 - 4.74)
		Head of HH with ≤ 4 years of schooling	1.63 (1.30 - 2.05)
		≤ 4 rooms/HH	1.38 (1.16 - 1.65)
		Participating in a CCTP	1.33 (1.11 - 1.59)
		≥ 4 residents/HH	1.27 (1.08 - 1.50)
		Female head of HH	1.25 (1.06 - 1.47)
		Maternal schooling ≤ 4 years	1.21 (1.01 - 1.46)
Lower socioeconomic HHs. SP²⁶26. Souza BFNJ, Marin-Leon L, Camargo DFM, Segall-Correa AM. Demographic and socioeconomic conditions associated with food insecurity in households in Campinas, SP, Brazil. Rev Nutr 2016; 29(6): 845-57. https://doi.org/10.1590/1678-98652016000600009 https://doi.org/https://doi.org/10.1590/... (691)	MMLR/OR	Head of HH informally employed	4.51 (1.51 - 13.4)
		Participating in a CCTP	3.33 (1.22 - 9.09)
		Unfinished house	3.20 (1.38 - 7.39)
		Increase by 1 HH good	0.86 (0.80 - 0.92)
HHs participating in CCTP (data from PNAD). Brazil¹⁸18. Segall-Corea AM, Marin-Leon L, Helito H, Perez-Escamilla R, Santos LMP, Paes-Sousa R. Transferência de renda e segurança alimentar no Brasil: análise dos dados nacionais. Rev Nutr 2008; 21(Suppl.): S39-S51. (112,716)	MLR/OR	≥ 1 resident aged < 18 years/HH	1.91 (1.09 - 3.35)
		Male head of HH	1.64 (1.31 - 2.04)
		Head of HH with ≥ 4 years of schooling	1.43 (1.22 - 1.68)
		White head of HH	1.39 (1.16 - 1.64)
		≤ 5 residents/HH	1.36 (1.18 - 1.62)
		≤ 2 residents/room	1.33 (1.18 - 1.49)
		Living in a non-metropolitan area	1.22 (1.07 - 1.40)
		Increase in income by US$ 3.67ª	1.08 (1.04 - 1.12)
Quilombola HHs (data from Census Quilombola). Brazil²⁷27. Gubert MB, Segall-Correa AM, Spaniol AM, Pedroso J, Coelho SEAC, Perez-Escamilla R. Household food insecurity in black-slaves descendant communities in Brazil: has the legacy of slavery truly ended? Public Health Nutr 2017; 20(8): 1513-22. https://doi.org/10.1017/s1368980016003414 https://doi.org/https://doi.org/10.1017/... (8,856)	MLR/OR	Living in the North region	11.26 (7.83 - 16.19)
		≥ 8 residents/HH	3.52 (2.90 - 4.26)
		Per capita income < US$ 44^f	2.78 (2.36 - 3.29)
		Head of HH with ≤ 4 years of schooling	1.92 (1.29 - 2.85)
		Lack of public sewer	1.88 (1.61 - 2.19)
		Lack of public water supply	1.23 (1.10 - 1.39)
		Not participating in a CCTP	0.66 (0.58 - 0.75)
HHs with children covered by ESF. NE and S²⁸28. Facchini LA, Nunes BP, Motta JVS, Tomasi E, Silva SM, Thumé E, et al. Insegurança alimentar no Nordeste e Sul do Brasil: magnitude, fatores associados e padrões de renda per capita para redução das inequidades. Cad Saude Pública 2014; 30(1): 161-74. https://doi.org/10.1590/0102-311X00036013 https://doi.org/https://doi.org/10.1590/... (NE = 5,419 / S = 5,081)	MPR/PR	Results from the Northeast region:
		Per capita income ≤ US$ 40.98^e	8.38 (5.87 - 11.96)
		Black mother	1.50 (1.18 - 1.90)
		Maternal schooling ≤ 4 years	1.43 (1.23 - 1.66)
		Female head of HH	1.32 (1.18 - 1.47)
		≥ 3 residents aged < 7 year/HH	1.28 (1.08 - 1.51)
		Participating in a CCTP	1.26 (1.11 - 1.42)
		Results from the South region:
		Per capita income US$ 40.98-61.47^e	8.10 (5.36 - 12.25)
		Maternal schooling ≤ 4 years	1.87 (1.36 - 2.58)
		Participating in a CCTP	1.48 (1.17 - 1.87)
		Female head of HH	1.42 (1.12 - 1.80)
		Multiracial mother	1.37 (1.11 - 1.70)
HHs with children attending public school. PB²⁹29. Pedraza DF, Gama JSFA. Segurança alimentar e nutricional de famílias com crianças menores de cinco anos do município de Campina Grande, Paraíba. Rev Bras Epidemiol 2015; 18(4): 906-17. https://doi.org/10.1590/1980-5497201500040018 https://doi.org/https://doi.org/10.1590/... (793)	MPR/PR	Untreated drinking water	1.65 (1.26 - 2.17)
		Not having a refrigerator	1.54 (1.13 - 2.09)
		≥ 6 residents/HH	1.24 (1.04 - 1.64)
		Lack of toilet in the house	1.21 (1.09 - 1.63)
HHs participating in CCTP with children. MG¹⁹19. Sperandio N, Priore SE. Prevalência de insegurança alimentar domiciliar e fatores associados em famílias com pré-escolares, beneficiárias do Programa Bolsa Família de Viçosa, Minas Gerais, Brasil. Epidemiol Serv Saúde 2015; 24(4): 739-48. https://doi.org/10.5123/S1679-49742015000400016 https://doi.org/https://doi.org/10.5123/... (243)	BPR/PR	Maternal schooling < 7 years	1.86 (1.52 - 2.83)
HHs with children/adolescents. RJ³³33. Salles-Costa R, Pereira R, Vasconcellos MTL, Veiga GV, Marins VMR, Jardim BC, et al. Associação entre fatores socioeconômicos e insegurança alimentar: estudo de base populacional na Região Metropolitana do Rio de Janeiro, Brasil. Rev Nutr 2008; 21 (Suppl. 0): S99-S109. (1,085)	PR/PR	> 8 residents/HH	6.18 (1.31 - 11.06)
Low HH income PB²⁰20. Vianna RPT, Segall-Correa AM. Insegurança alimentar das famílias residentes em municípios do interior do estado da Paraíba, Brasil. Rev Nutr 2008; 21(Suppl.): S111-S22. (4,533)	MLR/OR	Per capita income ≤ US$ 10.64^c	19.10 (11.75 - 31.04)
		Unfinished house	1.98 (1.64 - 2.38)
		Lack of public water supply	1.38 (1.15 - 1.65)
HHs with children (data from PNDS). Brazil³⁰30. Poblacion AP, Cook JT, Marin-Leon L, Segall-Correa AM, Silveira JAC, Konstantyner T, et al. Food insecurity and the negative impact on brazilian children’s health - why does food security matter for our future prosperity? Brazilian National Survey (PNDS 2006/07). Food Nutr Bull 2016; 37(4): 585-98. https://doi.org/10.1177/0379572116664167 https://doi.org/https://doi.org/10.1177/... (3,923)	MPR/PR	Living in the N/NE regions	1.9 (1.7 - 2.2)
		Maternal schooling ≤ 8 years	1.9 (1.5 - 2.3)
		Socioeconomic classification D/E	1.8 (1.6 - 2.1)
HHs with children (data from PNDS). Brazil³⁰30. Poblacion AP, Cook JT, Marin-Leon L, Segall-Correa AM, Silveira JAC, Konstantyner T, et al. Food insecurity and the negative impact on brazilian children’s health - why does food security matter for our future prosperity? Brazilian National Survey (PNDS 2006/07). Food Nutr Bull 2016; 37(4): 585-98. https://doi.org/10.1177/0379572116664167 https://doi.org/https://doi.org/10.1177/... (3,923)	MPR/PR	Participating in a CCTP	1.4 (1.2 - 1.6)
		≥ 3 residents in preschool age/HH	1.4 (1.2 - 1.7)
		House with poor-quality construction materials	1.3 (1.1 - 1.4)
		Female head of HH without a partner	1.3 (1.1 - 1.5)
		Living in a rural area	0.8 (0.7 - 0.9)
		Female head of HH	2.21 (1.47 - 3.31)
		No. of residents/bedroom ≥ 3	1.91 (1.23 - 2.96)
		Living in inadequate conditions	1.84 (1.12 - 2.08)
		Head of HH with ≤ 4 years of schooling	1.68 (1.00 - 2.81)
HHs with adolescents. MT³¹31. Guerra LDS, Espinosa MM, Bezerra ACD, Guimarães LV, Lima-Lopes MA. Insegurança alimentar em domicílios com adolescentes da Amazônia Legal Brasileira: prevalência e fatores associados. Cad Saúde Pública 2013; 29(2): 335-48. https://doi.org/10.1590/S0102-311X2013000200020 https://doi.org/https://doi.org/10.1590/... (363)	MPR/PR	Monthly income ≤½ MW^d	5.60 (2.36 - 13.27)
		Black adolescent	2.37 (1.48 - 3.80)
		Untreated drinking water	2.08 (1.48 - 2.94)
		Head of HH born in the city	1.69 (1.13 - 2.51)
HHs covered by NASF. GO²¹21. Peixoto MRG, Ramos K, Martins KA, Schincaglia RM, Braudes-Silva LA. Insegurança alimentar na área de abrangência do Núcleo de Apoio à Saúde da Família em Itumbiara, Goiás. Epidemiol Serv Saúde 2014; 23(2): 327-36. https://doi.org/10.5123/S1679-49742014000200014 https://doi.org/https://doi.org/10.5123/... (356)	MPR/PR	Socioeconomic classification D/E	2.2 (1.3 - 3.2)
		Unfinished house	1.3 (1.0 - 1.5)
		Not participating in a CCTP	1.3 (1.1 - 1.6)
		≥ 5 residents/HH	1.3 (1.1 - 1.6)
General HHs BA.²²22. Silva EKP, Medeiros DS, Martins PC, Sousa LA, Lima GP, Rêgo MAS, et al. Insegurança alimentar em comunidades rurais no Nordeste brasileiro: faz diferença ser quilombola? Cad Saúde Pública 2017; 33(4): e00005716. https://doi.org/10.1590/0102-311x00005716 https://doi.org/https://doi.org/10.1590/... (459)	MPR/PR	Socioeconomic classification E	3.22 (1.95 - 5.32)
		Participating in a CCTP	1.52 (1.25 - 1.84)
		Being a quilombola	1.25 (1.06 - 1.47)
		≥ 4 residents/HH	1.20 (1.01 - 1.43)

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