Indicators of chronic noncommunicable diseases in women of reproductive age that are beneficiaries and non-beneficiaries of Bolsa Família

Bernal, Regina Tomie Ivata; Felisbino-Mendes, Mariana Santos; Carvalho, Quéren Hapuque de; Pell, Jill; Dundas, Ruth; Leyland, Alastair; Barreto, Mauricio Lima; Malta, Deborah Carvalho

doi:10.1590/1980-549720190012.supl.2

ABSTRACT:

Objective:

To evaluate the prevalence of noncommunicable disease (NCD) indicators, including laboratory tests, in the population of Brazilian women of reproductive age, according to whether or not they receive the Bolsa Família (BF) benefit.

Methods:

A total of 3,131 women aged 18 to 49 years old who participated in the National Health Survey (Pesquisa Nacional de Saúde ) laboratory examination sub-sample were considered. We compared indicators among women of reproductive age (18 to 49 years old) who reported receiving BF or not, and calculated prevalence and confidence intervals, using Pearson’s χ².

Results:

Women of reproductive age who were beneficiaries of BF had worse health outcomes, such as a greater occurrence of being overweight (33.5%) and obese (26.9%) (p < 0.001), having hypertension (13.4% versus 4.4%, p < 0.001), used more tobacco (11.2% versus 8.2%, p = 0.029), and perceived their health as worse (6.2% versus 2.4%, p < 0.001).

Conclusion:

Several NCD indicators were worse among women of childbearing age who were beneficiaries of BF. It should be emphasized that this is not a causal relationship, with BF being a marker of inequalities among women. The benefit has been directed to the population with greater health needs, and seeks to reduce inequities.

Keywords:
Socioeconomic factors; Noncommunicable diseases; Women’s Health; Health surveys; Hematologic tests

INTRODUCTION

Noncommunicable chronic diseases (NCDs) are responsible for a high number of premature deaths, the loss of quality of life, and a high degree of limitation for individuals. Furthermore, they cause negative economic impacts on families, communities and society in general, which results in worsening social inequities and poverty¹1. Malta DC, Bernal RTI. Comparison of risk and protective factors for chronic diseases in the population with and without health insurance in the Brazilian capitals, 2011. Rev Bras Epidemiol 2014; 17(Supl. 1): 241-55. http://doi.org/10.1590/1809-4503201400050019
http://doi.org/10.1590/1809-450320140005... .

The NCD epidemic has most affected low-income people because they are more exposed to risk factors and have less access to health services²2. Pearce N, Ebrahim S, McKee M, Lamptey P, Barreto ML, Matheson D, et al. Global prevention and control of NCDs: Limitations of the standard approach. J Public Health Policy 2015; 36(4): 408-25. http://doi.org/10.1057/jphp.2015.29
http://doi.org/10.1057/jphp.2015.29... . There are important differences in the distribution of morbidity and mortality of these diseases according to socioeconomic factors such as education, occupation, income, gender and ethnicity, causing differential access to services and consumption patterns, among other things²2. Pearce N, Ebrahim S, McKee M, Lamptey P, Barreto ML, Matheson D, et al. Global prevention and control of NCDs: Limitations of the standard approach. J Public Health Policy 2015; 36(4): 408-25. http://doi.org/10.1057/jphp.2015.29
http://doi.org/10.1057/jphp.2015.29... .

In Brazil, NCDs are also a major health problem, accounting for 75% of the causes of death and, although they affect individuals from all socioeconomic strata, those from vulnerable groups, such as the elderly and those with low levels of education and income, are hit the hardest³3. Malta DC, Campos MO, Oliveira MM de, Iser BPM, Bernal RTI, Claro RM, et al. Prevalência de fatores de risco e proteção para doenças crônicas não transmissíveis em adultos residentes em capitais brasileiras, 2013. Epidemiol Serv Saúde 2015; 24(3): 373-87. http://doi.org/10.5123/s1679-49742015000300004
http://doi.org/10.5123/s1679-49742015000... . Additionally, studies demonstrate a relationship between social determinants, poor socioeconomic conditions and poor health outcomes with greater susceptibility to develop NCDs and their comorbidities, in addition to higher mortality rates²2. Pearce N, Ebrahim S, McKee M, Lamptey P, Barreto ML, Matheson D, et al. Global prevention and control of NCDs: Limitations of the standard approach. J Public Health Policy 2015; 36(4): 408-25. http://doi.org/10.1057/jphp.2015.29
http://doi.org/10.1057/jphp.2015.29... ^,⁴4. Barreto ML. Desigualdades em Saúde: uma perspectiva global. Ciênc Saúde Coletiva 2017; 22(7): 2097-108. http://doi.org/10.1590/1413-81232017227.02742017
http://doi.org/10.1590/1413-81232017227.... ^,⁵5. Williams J, Allen L, Wickramasinghe K, Mikkelsen B, Roberts N, Townsend N. A systematic review of associations between non-communicable diseases and socioeconomic status within low- and lower-middle-income countries. J Global Health 2018; 8(2). http://doi.org/10.7189/jogh.08.020409
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Data from the National Household Sample Survey (Dados da Pesquisa Nacional por Amostra de Domicílio - PNAD) in 2003 already showed a high prevalence of NCDs in the female population and in other individuals with low levels of education⁶6. Barros MBA, César CLG, Carandina L, Torre GD. Desigualdades sociais na prevalência de doenças crônicas no Brasil, PNAD-2003. Ciênc Saúde Coletiva 2006; 11(4): 911-26. http://doi.org/10.1590/s1413-81232006000400014
http://doi.org/10.1590/s1413-81232006000... . The National Health Survey (Pesquisa Nacional de Saúde - PNS) also indicates that, among the NCDs analyzed in the survey, most were reported by women. Additionally, people with chronic diseases reported worse self-evaluated health⁷7. Theme Filha MM, Souza Junior PRB de, Damacena GN, Szwarcwald CL. Prevalência de doenças crônicas não transmissíveis e associação com autoavaliação de saúde: Pesquisa Nacional de Saúde, 2013. Rev Bras Epidemiol 2015; 18(Supl. 2): 83-96. http://doi.org/10.1590/1980-5497201500060008
http://doi.org/10.1590/1980-549720150006... . This may be due to the fact that women use health services more often⁸8. Malta DC, Bernal RTI, Lima MG, Araújo SSC de, Silva MMA da, Freitas MI de F, et al. Noncommunicable diseases and the use of health services: analysis of the National Health Survey in Brazil. Rev Saúde Pública 2017; 51(Supl. 1). http://doi.org/10.1590/s1518-8787.2017051000090
http://doi.org/10.1590/s1518-8787.201705... and also because they are more attentive to their health⁸8. Malta DC, Bernal RTI, Lima MG, Araújo SSC de, Silva MMA da, Freitas MI de F, et al. Noncommunicable diseases and the use of health services: analysis of the National Health Survey in Brazil. Rev Saúde Pública 2017; 51(Supl. 1). http://doi.org/10.1590/s1518-8787.2017051000090
http://doi.org/10.1590/s1518-8787.201705... .

On the other hand, few studies address the magnitude of NCDs among women of reproductive age ⁹9. Peters SAE, Woodward M, Jha V, Kennedy S, Norton R. Women’s health: a new global agenda. BMJ Global Health 2016; 1: e000080. http://doi.org/10.1136/bmjgh-2016-000080
http://doi.org/10.1136/bmjgh-2016-000080... ^,¹⁰10. Bonita R, Beaglehole R. Women and NCDs: Overcoming the neglect. Global Health Action 2014; 7(1): 23742. http://doi.org/10.3402/gha.v7.23742
http://doi.org/10.3402/gha.v7.23742... ^,¹¹11. Mpofu JJ, de Moura L, Farr SL, Malta DC, Iser BM, Ivata Bernal RT, et al. Associations between noncommunicable disease risk factors, race, education, and health insurance status among women of reproductive age in Brazil - 2011. Prev Med Rep 2016; 3: 333-7. http://doi.org/10.1016/j.pmedr.2016.03.015
http://doi.org/10.1016/j.pmedr.2016.03.0... , since the predominant approach to research on this specific group is related to reproductive issues such as family planning, prenatal care, prevention and screening for gynecological cancers. Research dealing with NCDs shows how much these diseases increasingly affect women¹⁰10. Bonita R, Beaglehole R. Women and NCDs: Overcoming the neglect. Global Health Action 2014; 7(1): 23742. http://doi.org/10.3402/gha.v7.23742
http://doi.org/10.3402/gha.v7.23742... ^,¹¹11. Mpofu JJ, de Moura L, Farr SL, Malta DC, Iser BM, Ivata Bernal RT, et al. Associations between noncommunicable disease risk factors, race, education, and health insurance status among women of reproductive age in Brazil - 2011. Prev Med Rep 2016; 3: 333-7. http://doi.org/10.1016/j.pmedr.2016.03.015
http://doi.org/10.1016/j.pmedr.2016.03.0... ^,¹²12. Araújo FG. Tendência da prevalência de sobrepeso, obesidade, diabetes e hipertensão em mulheres brasileiras em idade reprodutiva, Vigitel 2008-2015 [dissertação]. Belo Horizonte: Universidade Federal de Minas Gerais; 2018., even though they are young. Consequently, they also affect reproductive issues¹³13. Denny CH, Floyd RL, Green PP, Hayes DK. Racial and Ethnic Disparities in Preconception Risk Factors and Preconception Care. J Womens Health 2012; 21(7): 720-9. http://doi.org/10.1089/jwh.2011.3259
http://doi.org/10.1089/jwh.2011.3259... .

There is still a significant gap in research regarding possible inequities, i.e. whether women with unfavorable socioeconomic conditions are more susceptible to NCDs and their risk factors. A previous study with the Surveillance of Risk Factors and Protection for Chronic Diseases by Telephone Survey (Vigilância de Fatores de Risco e Proteção para Doenças Crônicas por Inquérito Telefônico - Vigitel) found that women of reproductive age with low levels of education were more inactive, and had higher levels of smoking and hypertension¹¹11. Mpofu JJ, de Moura L, Farr SL, Malta DC, Iser BM, Ivata Bernal RT, et al. Associations between noncommunicable disease risk factors, race, education, and health insurance status among women of reproductive age in Brazil - 2011. Prev Med Rep 2016; 3: 333-7. http://doi.org/10.1016/j.pmedr.2016.03.015
http://doi.org/10.1016/j.pmedr.2016.03.0... . Cardiovascular diseases are also treated and prevented to a lesser extent among women, especially those who are in positions of social vulnerability¹⁴14. Aggarwal NR, Patel HN, Mehta LS, Sanghani RM, Lundberg GP, Lewis SJ, et al. Sex Differences in Ischemic Heart Disease. Circulation 2018; 11(2). http://doi.org/10.1161/circoutcomes.117.004437
http://doi.org/10.1161/circoutcomes.117.... . Moreover, due to gender inequality, sexist practices place women in unfavorable situations, which are further aggravated by economic inequality¹⁵15. Sousa LPD, Guedes DR. A desigual divisão sexual do trabalho: um olhar sobre a última década. Estud Av 2016; 30(87): 123-39. http://doi.org/10.1590/s0103-40142016.30870008
http://doi.org/10.1590/s0103-40142016.30... ^,¹⁶16. Lima CRN de A. Gênero, trabalho e cidadania: função igual, tratamento salarial desigual. Rev Estud Fem 2018; 26(3). http://doi.org/10.1590/1806-9584-2018v26n347164
http://doi.org/10.1590/1806-9584-2018v26... .

The Bolsa Familia (BF) program, a conditional cash transfer program (um programa de transferência condicionada de renda - PTCR), was created in Brazil in 2003 with the objective of increasing guaranteed social protection and reducing poverty. It is an act of positive discrimination that aims to break the intergenerational cycle of poverty, and reduce vulnerabilities and social inequalities¹⁷17. Castiñeira BR, Nunes LC, Rungo P. Impacto de los programas de transferencia condicionada de renta sobre el estado de salud: el Programa Bolsa Familia de Brasil. Rev Esp Salud Publica 2009; 83(1): 85-97.^,¹⁸18. Souza LP. Bolsa Família: socializando cuidados e mudando as relações de gênero? [dissertação]. Niterói: Universidade Federal Fluminense; 2015.. Most of the beneficiaries of BF are poor and socially disadvantaged women¹⁹19. Dantas C, Neri E. As consequências do programa de transferência de renda condicionada Bolsa Família na vida das suas beneficiárias. Rev Gênero Direito 2013; 2(1): 96-110.^,²⁰20. De Souza LP, Waltenbeg FD. Bolsa Família e assimetrias de gênero: reforço ou mitigação? Rev Bras Estud Popul 2016; 33(3): 517-39. http://doi.org/10.20947/s0102-30982016c0004
http://doi.org/10.20947/s0102-30982016c0... ^,²¹21. Campara JP, Vieira KM, Potrich ACG. Satisfação Global de Vida e Bem-estar Financeiro: desvendando a percepção de beneficiários do Programa Bolsa Família. Rev Adm Pública 2017; 51(2): 182-200. http://doi.org/10.1590/0034-7612156168
http://doi.org/10.1590/0034-7612156168... . The program aims to reduce social inequities and focus on social determinants and the context in which everyone lives⁴4. Barreto ML. Desigualdades em Saúde: uma perspectiva global. Ciênc Saúde Coletiva 2017; 22(7): 2097-108. http://doi.org/10.1590/1413-81232017227.02742017
http://doi.org/10.1590/1413-81232017227.... ^,²¹21. Campara JP, Vieira KM, Potrich ACG. Satisfação Global de Vida e Bem-estar Financeiro: desvendando a percepção de beneficiários do Programa Bolsa Família. Rev Adm Pública 2017; 51(2): 182-200. http://doi.org/10.1590/0034-7612156168
http://doi.org/10.1590/0034-7612156168... ^,²²22. Duncan BB, Chor D, Aquino EML, Bensenor IM, Mill JG, Schmidt MI, et al. Doenças crônicas não transmissíveis no Brasil: prioridade para enfrentamento e investigação. Rev Saúde Pública 2012; 46(Supl. 1): 126-34. http://doi.org/10.1590/s0034-89102012000700017
http://doi.org/10.1590/s0034-89102012000... .

We hypothesized that women receiving BF would have less access to health services and worse health indicators. Thus, this study aimed to evaluate the prevalence of NCD indicators, including laboratory tests, in the population of Brazilian women of reproductive age according to whether they receive BF. It is believed that this unprecedented assessment can identify inequalities among women and provide more knowledge of the occurrence of these diseases in this specific subset of the population.

METHODS

This research is a descriptive cross-sectional study based on secondary PNS data. The PNS is a household survey that is part of the Integrated Household Survey System of the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística - IBGE)²³23. Souza-Júnior PRB de, Freitas MPS de, Antonaci G de A, Szwarcwald CL. Desenho da amostra da Pesquisa Nacional de Saúde 2013. Epidemiol Serv Saúde 2015; 24(2): 207-16. http://dx.doi.org/10.5123/S1679-49742015000200003
http://dx.doi.org/10.5123/S1679-49742015... ^,²⁴24. Szwarcwald CL, Malta DC, Azevedo C, Souza Júnior PRB, Rozemberg LG. Exames laboratoriais da pesquisa nacional de saúde: Metodologia de amostragem, coleta, e análise dos dados. Rev Bras Epidemiol 2019. (no prelo)..

The PNS uses a three-stage cluster sampling process. Census sectors or sets of sectors form the primary sampling units (PSUs); households form the second stage units; and residents 18 and older form the third stage units. 60,202 individuals with a response rate of 86% were interviewed and, because it is a complex sample, expansion factors or sample weights were defined for the PSUs, for the households, for all of their residents, as well as for the selected resident. More details on sampling and data collection are available in other publications²³23. Souza-Júnior PRB de, Freitas MPS de, Antonaci G de A, Szwarcwald CL. Desenho da amostra da Pesquisa Nacional de Saúde 2013. Epidemiol Serv Saúde 2015; 24(2): 207-16. http://dx.doi.org/10.5123/S1679-49742015000200003
http://dx.doi.org/10.5123/S1679-49742015... .

A laboratory research module was included in the PNS and a subsample containing 25% of the census tracts was defined. However, the laboratory subsample obtained comprised 8,952 people. Several factors caused sample losses, such as the hired laboratory having difficulty finding addresses, the refusal of the selected resident to perform biological material collection, and the long period of time that elapsed between the interview and the laboratory collection. Post-stratification weights according to gender, age, education and region were used to correct possible biases²³23. Souza-Júnior PRB de, Freitas MPS de, Antonaci G de A, Szwarcwald CL. Desenho da amostra da Pesquisa Nacional de Saúde 2013. Epidemiol Serv Saúde 2015; 24(2): 207-16. http://dx.doi.org/10.5123/S1679-49742015000200003
http://dx.doi.org/10.5123/S1679-49742015... ^,²⁴24. Szwarcwald CL, Malta DC, Azevedo C, Souza Júnior PRB, Rozemberg LG. Exames laboratoriais da pesquisa nacional de saúde: Metodologia de amostragem, coleta, e análise dos dados. Rev Bras Epidemiol 2019. (no prelo). in the statistical analyses.

The concept of women of childbearing age or reproductive age refers to those aged 15 to 49 years old²⁵25. World Health Organization. Women Today’s Evidence Tomorrow’s Agenda. Genebra: World Health Organization; 2009.^,²⁶26. Brasil. Ministério da Saúde. Secretaria de Atenção à Saúde. Departamento de Ações Programáticas Estratégicas. Política nacional de atenção integral à saúde da mulher: princípios e diretrizes. Brasília: Ministério da Saúde; 2004., however, the present study only analyzed data from women aged 18 to 49 years old, since the cutoff point used in the PNS is an adult population aged 18 years or older. The sociodemographic distributions of the sample were detailed.

Regarding laboratory analysis, the PNS subsample was 8,952 respondents. Therefore, the current study included 3,131 women aged 18 to 49 years old who participated in this laboratory sub-sample.

Data referring to the individual questionnaire, as well as laboratory data, were used to compose the CNCD indicators for this study.

HbA1c was collected in a tube with ethylenediamine tetraacetic acid (EDTA) and dosed by high pressure liquid chromatography (HPLC) by ionic exchange. The World Health Organization (WHO) cut-off point was used, and the American Diabetes Association recommends HbA1c ≥ 6.5% for the diagnosis of diabetes mellitus²⁷27. The International Expert Committee. International expert committee report on the role of the A1c assay in the diagnosis of diabetes. Diabetes Care 2009; 32(7): 1327-34. https://dx.doi.org/10.2337%2Fdc09-9033
https://dx.doi.org/10.2337%2Fdc09-9033... ^,²⁸28. World Health Organization. Use of glycated haemoglobin (HbA1c) in the diagnosis of diabetes mellitus [internet]. World Health Organization; 2011. Disponível em: http://www.who.int/diabetes/publications/report-hba1c_2011.pdf
http://www.who.int/diabetes/publications... .

Total cholesterol, low density lipoprotein (LDL) and high density lipoprotein (HDL) were collected in a gel tube. The following cutoff points for total cholesterol (TC) and fractions were established: TC ≥ 200 mg/dL; LDL ≥ 130 mg/dL and HDL <40 mg/dL, following the clinical treatment parameters recommended by the Adult Treatment Panel III²⁹29. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). Jama 2001; 285(19): 2486-97. https://doi.org/10.1001/jama.285.19.2486
https://doi.org/10.1001/jama.285.19.2486... .

Serum creatinine was collected in a gel tube and dosed by the Jaffé method without deproteinization. For the dichotomous analysis, the values ≥ 1.3 mg/dL were considered to be altered. The glomerular filtration rate (GFR) was calculated for creatinine by using predictive equations that utilize correction factors (age, gender, race and weight)³⁰30. Kidney International. References. Kidney International Supplements 2013; 3(3): 303-5. http://doi.org/10.1038/kisup.2013.42
http://doi.org/10.1038/kisup.2013.42... ^,³¹31. Stevens LA, Coresh J, Greene T, Levey AS. Assessing Kidney Function - Measured and Estimated Glomerular Filtration Rate. New Engl J Med 2006; 354: 2473-83. http://doi.org/10.1056/nejmra054415
http://doi.org/10.1056/nejmra054415... . Estimated GFR <60 mL/min/ 1.73 m² was calculated based on separate creatinine for women.

Red series tests were analyzed, and at this time anemia was considered when hemoglobin was <12 g/dL, the WHO standard³²32. World Health Organization. Haemoglobin concentrations for the diagnosis of anaemia and assessment of severity. Vitamin and Mineral Nutrition Information System [Internet]. Genebra: World Health Organization ; 2011 [acessado em 10 set. 2018]. Disponível em: Disponível em: http://www.who.int/vmnis/indicators/haemoglobin.pdf
http://www.who.int/vmnis/indicators/haem... .

Urine samples were collected at different times throughout the day. Urinary sodium was measured using the sensitive electrode method. The frequency of the population above the 75th percentile of salt intake was taken into account.

For laboratory tests, prevalence, 95% confidence interval (95% CI), and age-adjusted prevalence ratio (PR) were calculated, comparing whether or not they received BF.

Receipt of BF was taken from question F012 of the PNS questionnaire: “In July (reference month), does any resident of this household receive income from the Bolsa Familia Program?”. In the PNS laboratory database, IBGE incorporated variables related to NCDs, which were analyzed here, and compared the prevalence and 95% CI among women of reproductive age (18 to 49 years) who said they received BF or not. The indicators included in this study were risk and protection factors against NCDs:

anthropometric measurements: weight and height were measured by scale and anthropometers, and body mass index (BMI) was calculated - overweight: BMI between ≥ 25 and <30 kg/m²; obese: BMI ≥ 30 kg/m²);
smokers: report smoking regardless of the number of cigarettes;
consumption of excess meat fat: eats red meat with visible fat or chicken with skin;
regular consumption of soft drinks or artificial juices five or more days a week;
bean consumption five or more days a week;
alcohol abuse, five or more doses on one occasion in the last 30 days;
self-evaluated health: three categories were classified to assess health status - very good, fair and poor.

The following morbidity indicators previously diagnosed by the physician were considered:

arterial hypertension;
diabetes;
cholesterol;
arthritis or rheumatism;
renal insufficiency.

The indicators of access to health services included:

mentioning whether or not they had health or dental insurance;
saying they have looked for health services in the last year;
hospitalization in the last 12 months.

Thus, the study estimated and compared prevalences and 95% confidence intervals (CI) using Pearson’s χ², and analyses were performed using Stata, version 13. The PNS questionnaire and the variables have already been published in previous publications, and more details can be found in other publications⁸8. Malta DC, Bernal RTI, Lima MG, Araújo SSC de, Silva MMA da, Freitas MI de F, et al. Noncommunicable diseases and the use of health services: analysis of the National Health Survey in Brazil. Rev Saúde Pública 2017; 51(Supl. 1). http://doi.org/10.1590/s1518-8787.2017051000090
http://doi.org/10.1590/s1518-8787.201705... ^,²³23. Souza-Júnior PRB de, Freitas MPS de, Antonaci G de A, Szwarcwald CL. Desenho da amostra da Pesquisa Nacional de Saúde 2013. Epidemiol Serv Saúde 2015; 24(2): 207-16. http://dx.doi.org/10.5123/S1679-49742015000200003
http://dx.doi.org/10.5123/S1679-49742015... .

As provided in the research protocol and in the Ethics Committee, all test results were reported to the user by the laboratory, and in case of indicative results, the participants were advised to seek medical attention in the public health system. In cases of extreme risk, participants were contacted directly by the laboratory or the Ministry of Health, encouraging participants to seek immediate care.

The PNS was approved by the National Research Ethics Commission, under No. 328,159, of June 26, 2013. All individuals were consulted, informed and agreed to participate in the research.

RESULTS

Among the 3,131 women studied, 924 (23.3%) were beneficiaries of the BF program. Regarding sociodemographic characteristics, 1,087 (40.8%) were between 18 and 29 years old, 1,769 (50.9%) were between 30 and 44 years old, and 275 (8.3%) were between 45 and 49 years old. Women receiving BF were less educated, 49.6% had from zero to eight years of schooling, while among non-beneficiaries only 16.2% had up to eight years of schooling and more than half had 12 or more years of schooling. Most women receiving BF self-reported as light-skinned black and dark-skinned black, and the majority of non-beneficiaries said they were white (51.1%). Women receiving BF were more concentrated in the Northeast (50.2%), followed by the Southeast (26.7%). Most non-beneficiaries lived in the Southeast (45.6%) (Table 1).

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Table 1.
Distribution of women between 18 and 49 years old that received and did not receive Bolsa Família, according to age, educational level, skin color and region of residence. Brazil, National Health Survey (PNS), 2014-2015.

Table 2 shows the prevalence of indicators for NCDs, and there was a higher occurrence of diseases among women who benefit from BF. The beneficiaries had a higher prevalence of being overweight (33.5%) and being obese (26.9%) (p <0.001). They also showed higher tobacco consumption, but lower alcohol consumption. Bean consumption was higher (75%) among BF beneficiaries (p <0.001). Missing information on risk factors ranged from 0.09 to 5%, data not shown.

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Table 2.
Prevalence of risk factors for chronic non-communicable diseases (NCDs) in women between 18 and 49 years of age, according to whether or not they received Bolsa Família. National Health Survey (PNS) 2013, Brazil.

Women who receive the benefit are about three times as likely as non-beneficiaries to rate their health as poor (p <0.001), and the vast majority of women who benefitted from BF had no health or dental insurance (94.4%) (p <0.001). It is also worth noting that the beneficiary women had a higher prevalence of hypertension, especially during pregnancy (p <0.001). It was found that 15% of respondents did not have information on high cholesterol, and 10% did not have information on diabetes, data not shown (Table 3).

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Table 3.
Prevalence of access indicators and self-reported chronic non-communicable diseases (NCDs) in women between 18 and 49 years of age, according to whether or not they received Bolsa Família. National Health Survey (PNS) 2013, Brazil.

Regarding the laboratory tests, it was observed that although beneficiary women had a higher prevalence of renal failure, increased creatinine, HDL, diabetes, and anemia, the difference was only significant for HDL cholesterol (Table 4). That is, women who receive BF had 41% higher prevalence of HDL cholesterol <40 mg / dL than those who did not receive the benefit.

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Table 4.
Laboratory results in women between 18 and 49 years of age, according to whether or not they receive Bolsa Família. National Health Survey (PNS) 2014 - 2015**, Brazil.

DISCUSSION

The results of this study show that women of reproductive age who benefit from BF have less education, are mostly light and dark-skinned black people and are concentrated in the Northeast region of the country. These women also perform worse on NCD indicators such as having a higher incidence of being overweight and obese, having hypertension, using more tobacco, having a poorer perception of their health and having higher cholesterol levels when compared to non-beneficiary women.

These findings point to a positive and indirect evaluation of BF, since it seems that those who receive it also have worse health, as well as worse socioeconomic circumstances. Therefore, the importance of social programs in the form of income transfer is once again emphasized, as they are designed to increase the guarantee of social protection, addressing poverty and breaking its intergenerational cycle, and thus reducing social inequalities¹⁷17. Castiñeira BR, Nunes LC, Rungo P. Impacto de los programas de transferencia condicionada de renta sobre el estado de salud: el Programa Bolsa Familia de Brasil. Rev Esp Salud Publica 2009; 83(1): 85-97..

Given this fact, it is internationally agreed that, to improve health and reduce mortality in the population, it is necessary to plan interventions that address social determinants of health⁴4. Barreto ML. Desigualdades em Saúde: uma perspectiva global. Ciênc Saúde Coletiva 2017; 22(7): 2097-108. http://doi.org/10.1590/1413-81232017227.02742017
http://doi.org/10.1590/1413-81232017227.... . Thus, PTCRs, by providing income to poor households, can reduce inequalities among beneficiary families³³33. Roque DM, Ferreira MAM. O que realmente importa em programas de transferência condicionada de renda? Abordagens em diferentes países. Saúde Soc 2015; 24(4): 1193-207. http://doi.org/10.1590/s0104-12902015138971
http://doi.org/10.1590/s0104-12902015138... ^,³⁴34. Rasella D, Aquino R, Santos CA, Paes-Sousa R, Barreto ML. Effect of a conditional cash transfer programme on childhood mortality: a nationwide analysis of Brazilian municipalities. The Lancet 2013; 382(9886): 57-64. http://doi.org/10.1016/s0140-6736(13)60715-1
http://doi.org/10.1016/s0140-6736(13)607... . Currently, BF is the largest PTCR not just in Brazil, but in the world, in relative and absolute terms³³33. Roque DM, Ferreira MAM. O que realmente importa em programas de transferência condicionada de renda? Abordagens em diferentes países. Saúde Soc 2015; 24(4): 1193-207. http://doi.org/10.1590/s0104-12902015138971
http://doi.org/10.1590/s0104-12902015138... ^,³⁵35. Quadros MT de, Santos GMNC dos. Obstáculos na procura pela esterilização feminina entre mulheres do Bolsa Família. Cad Saúde Pública 2017; 33(4). http://doi.org/10.1590/0102-311x00152515
http://doi.org/10.1590/0102-311x00152515... ^,³⁶36. Rasella D, Basu S, Hone T, Paes-Sousa R, Ocké-Reis CO, Millett C. Child morbidity and mortality associated with alternative policy responses to the economic crisis in Brazil: A nationwide microsimulation study. PLoS Med 2018; 15(5): e1002570. http://doi.org/10.1371/journal.pmed.1002570
http://doi.org/10.1371/journal.pmed.1002... .

It is also emphasized that the cause of these disparities is multifactorial and is associated with low levels of education and income. Some studies have previously demonstrated these inequities for cardiovascular disease¹⁴14. Aggarwal NR, Patel HN, Mehta LS, Sanghani RM, Lundberg GP, Lewis SJ, et al. Sex Differences in Ischemic Heart Disease. Circulation 2018; 11(2). http://doi.org/10.1161/circoutcomes.117.004437
http://doi.org/10.1161/circoutcomes.117.... , for example, and also for some of the most prevalent risk factors among women with low levels of education¹¹11. Mpofu JJ, de Moura L, Farr SL, Malta DC, Iser BM, Ivata Bernal RT, et al. Associations between noncommunicable disease risk factors, race, education, and health insurance status among women of reproductive age in Brazil - 2011. Prev Med Rep 2016; 3: 333-7. http://doi.org/10.1016/j.pmedr.2016.03.015
http://doi.org/10.1016/j.pmedr.2016.03.0... . Additionally, they have shown the high prevalence of obesity¹²12. Araújo FG. Tendência da prevalência de sobrepeso, obesidade, diabetes e hipertensão em mulheres brasileiras em idade reprodutiva, Vigitel 2008-2015 [dissertação]. Belo Horizonte: Universidade Federal de Minas Gerais; 2018., usually associated with low-income populations and racial inequalities¹³13. Denny CH, Floyd RL, Green PP, Hayes DK. Racial and Ethnic Disparities in Preconception Risk Factors and Preconception Care. J Womens Health 2012; 21(7): 720-9. http://doi.org/10.1089/jwh.2011.3259
http://doi.org/10.1089/jwh.2011.3259... ^,³⁷37. Strutz KL, Richardson LJ, Hussey JM. Selected Preconception Health Indicators and Birth Weight Disparities in a National Study. Womens Health Issues 2014; 24(1): e89-97. http://doi.org/10.1016/j.whi.2013.10.001
http://doi.org/10.1016/j.whi.2013.10.001... .

Studying inequities becomes relevant because it reinforces the need to expand population subgroups’ access to health care, actions and programs. Women in Brazil generally receive lower wages and have unfavorable working situations, which reinforces historical gender inequality, and in turn, aggravates their health situation¹⁵15. Sousa LPD, Guedes DR. A desigual divisão sexual do trabalho: um olhar sobre a última década. Estud Av 2016; 30(87): 123-39. http://doi.org/10.1590/s0103-40142016.30870008
http://doi.org/10.1590/s0103-40142016.30... ^,¹⁶16. Lima CRN de A. Gênero, trabalho e cidadania: função igual, tratamento salarial desigual. Rev Estud Fem 2018; 26(3). http://doi.org/10.1590/1806-9584-2018v26n347164
http://doi.org/10.1590/1806-9584-2018v26... .

This research points out worse health indicators among women that benefit from BF and shows the importance of taking ownership of the benefit granted to them, as they have been identified as more responsible and cautious³³33. Roque DM, Ferreira MAM. O que realmente importa em programas de transferência condicionada de renda? Abordagens em diferentes países. Saúde Soc 2015; 24(4): 1193-207. http://doi.org/10.1590/s0104-12902015138971
http://doi.org/10.1590/s0104-12902015138... ^,³⁸38. Moreira NC, Ferreira MAM, Lima AAT de FC, Ckagnazaroff IB. Empoderamento das mulheres beneficiárias do Programa Bolsa Família na percepção dos agentes dos Centros de Referência de Assistência Social. Rev Adm Pública 2012; 46(2): 403-23. http://doi.org/10.1590/s0034-76122012000200004
http://doi.org/10.1590/s0034-76122012000... . Ultimately, this benefit can mitigate the disparities described here. This governmental action is based on the concept of positive discrimination, considered by Souza¹⁸18. Souza LP. Bolsa Família: socializando cuidados e mudando as relações de gênero? [dissertação]. Niterói: Universidade Federal Fluminense; 2015. to be necessary in order to benefit more vulnerable populations. The goal is to reduce inequalities, such as those faced by poor and socially disadvantaged women, the profile of BF beneficiaries¹⁹19. Dantas C, Neri E. As consequências do programa de transferência de renda condicionada Bolsa Família na vida das suas beneficiárias. Rev Gênero Direito 2013; 2(1): 96-110.^,²⁰20. De Souza LP, Waltenbeg FD. Bolsa Família e assimetrias de gênero: reforço ou mitigação? Rev Bras Estud Popul 2016; 33(3): 517-39. http://doi.org/10.20947/s0102-30982016c0004
http://doi.org/10.20947/s0102-30982016c0... ^,²¹21. Campara JP, Vieira KM, Potrich ACG. Satisfação Global de Vida e Bem-estar Financeiro: desvendando a percepção de beneficiários do Programa Bolsa Família. Rev Adm Pública 2017; 51(2): 182-200. http://doi.org/10.1590/0034-7612156168
http://doi.org/10.1590/0034-7612156168... .

Socioeconomic inequality is a factor that in itself leads to an increase in NCDs in low-income populations. Global analyses across countries suggest that living in a low-income country is associated with a marked risk of developing chronic diseases⁴4. Barreto ML. Desigualdades em Saúde: uma perspectiva global. Ciênc Saúde Coletiva 2017; 22(7): 2097-108. http://doi.org/10.1590/1413-81232017227.02742017
http://doi.org/10.1590/1413-81232017227.... ^,⁵5. Williams J, Allen L, Wickramasinghe K, Mikkelsen B, Roberts N, Townsend N. A systematic review of associations between non-communicable diseases and socioeconomic status within low- and lower-middle-income countries. J Global Health 2018; 8(2). http://doi.org/10.7189/jogh.08.020409
http://doi.org/10.7189/jogh.08.020409... .

Another point that reinforces the increase in NCDs in this particular population is that social determinants extrapolate biological mechanisms by generating living standards that reflect social inequities, ultimately causing problems that accumulate over one’s lifetime⁴4. Barreto ML. Desigualdades em Saúde: uma perspectiva global. Ciênc Saúde Coletiva 2017; 22(7): 2097-108. http://doi.org/10.1590/1413-81232017227.02742017
http://doi.org/10.1590/1413-81232017227.... ^,²²22. Duncan BB, Chor D, Aquino EML, Bensenor IM, Mill JG, Schmidt MI, et al. Doenças crônicas não transmissíveis no Brasil: prioridade para enfrentamento e investigação. Rev Saúde Pública 2012; 46(Supl. 1): 126-34. http://doi.org/10.1590/s0034-89102012000700017
http://doi.org/10.1590/s0034-89102012000... . In addition, young women that are still in their reproductive age have significant risk factors and chronic health problems, and these conditions may determine poor reproductive outcomes and have repercussions for their children’s health through transgenerational transfer³⁹39. Felisbino-Mendes MS, Villamor E, Velasquez-Melendez G. Association of Maternal and Child Nutritional Status in Brazil: A Population Based Cross-Sectional Study. PLoS One 2014; 9(1): e87486. http://doi.org/10.1371/journal.pone.0087486
http://doi.org/10.1371/journal.pone.0087... . However, there are not many studies that focus on investigating these diseases in women of reproductive age⁹9. Peters SAE, Woodward M, Jha V, Kennedy S, Norton R. Women’s health: a new global agenda. BMJ Global Health 2016; 1: e000080. http://doi.org/10.1136/bmjgh-2016-000080
http://doi.org/10.1136/bmjgh-2016-000080... ^,¹⁰10. Bonita R, Beaglehole R. Women and NCDs: Overcoming the neglect. Global Health Action 2014; 7(1): 23742. http://doi.org/10.3402/gha.v7.23742
http://doi.org/10.3402/gha.v7.23742... . They are even more scarce in the Brazilian context, showing the need to make this public health problem visible and to make advances toward a comprehensive approach to women’s health.

Finally, it is important to highlight monitoring and NCD surveillance that includes vulnerable populations. Specifically, the implementation of the PNS in 2013 that included the question about receipt of BF allowed for this type of analysis and information on risk and morbidity to be available for this group.

This study has some limitations, including losses in the collection of laboratory tests, making it necessary to use post-stratification weights to reduce representation bias. After these procedures, the PNS laboratory results can be estimated for the Brazilian adult population. Laboratory tests may also have been lost due to hemolysis and insufficient material. Thus, there were differences between the number of women who performed biological material collection and the number of women who answered the questionnaire. It is also worth noting that the risk factor indicators were self-reported and may have resulted in memory bias.

CONCLUSION

The results of this study show that several NCD indicators perform worse among BF beneficiary women of reproductive age. It is worth noting that this is not a causal relationship, and points to the importance of BF as a marker of inequality among women. The BF program addresses the population with the greatest health needs, and therefore needs to be maintained in order to reduce health inequities.

It should be highlighted that the present investigation analyzed the prevalence of NCD indicators among women of reproductive age who benefit from BF for the first time in Brazil. This may support the view that BF is being applied appropriately, but mainly it demonstrates that groups in the worst social and economic situations have the worst health conditions. These data should be considered when defining the health priorities for the Brazilian population, especially with regard to women’s health.

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» http://doi.org/10.1590/s0104-12902015138971
³⁴
Rasella D, Aquino R, Santos CA, Paes-Sousa R, Barreto ML. Effect of a conditional cash transfer programme on childhood mortality: a nationwide analysis of Brazilian municipalities. The Lancet 2013; 382(9886): 57-64. http://doi.org/10.1016/s0140-6736(13)60715-1
» http://doi.org/10.1016/s0140-6736(13)60715-1
³⁵
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» http://doi.org/10.1590/0102-311x00152515
³⁶
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» http://doi.org/10.1371/journal.pmed.1002570
³⁷
Strutz KL, Richardson LJ, Hussey JM. Selected Preconception Health Indicators and Birth Weight Disparities in a National Study. Womens Health Issues 2014; 24(1): e89-97. http://doi.org/10.1016/j.whi.2013.10.001
» http://doi.org/10.1016/j.whi.2013.10.001
³⁸
Moreira NC, Ferreira MAM, Lima AAT de FC, Ckagnazaroff IB. Empoderamento das mulheres beneficiárias do Programa Bolsa Família na percepção dos agentes dos Centros de Referência de Assistência Social. Rev Adm Pública 2012; 46(2): 403-23. http://doi.org/10.1590/s0034-76122012000200004
» http://doi.org/10.1590/s0034-76122012000200004
³⁹
Felisbino-Mendes MS, Villamor E, Velasquez-Melendez G. Association of Maternal and Child Nutritional Status in Brazil: A Population Based Cross-Sectional Study. PLoS One 2014; 9(1): e87486. http://doi.org/10.1371/journal.pone.0087486
» http://doi.org/10.1371/journal.pone.0087486

Financial support: This research was funded by the National Institute for Health Research (NIHR) (GHRG /16/137/99) using aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care. The Social and Public Health Sciences Unit is core funded by the Medical Research Council (MC_UU_12017/13) and the Scottish Government Chief Scientist Office (SPHSU13). CIDACS is supported by grants from CNPq/MS/Gates Foundation (401739/2015-5) and the Wellcome Trust, UK (202912/Z/16/Z). EE UFMG is supported by grants from the Health Surveillance Secretariat, Ministry of Health. TED 66-2018.

Publication Dates

Publication in this collection
07 Oct 2019
Date of issue
2019

History

Received
13 Jan 2019
Reviewed
09 Mar 2019
Accepted
12 Mar 2019

Este é um artigo publicado em acesso aberto sob uma licença Creative Commons

[1] ¹
Malta DC, Bernal RTI. Comparison of risk and protective factors for chronic diseases in the population with and without health insurance in the Brazilian capitals, 2011. Rev Bras Epidemiol 2014; 17(Supl. 1): 241-55. http://doi.org/10.1590/1809-4503201400050019
» http://doi.org/10.1590/1809-4503201400050019

[2] ²
Pearce N, Ebrahim S, McKee M, Lamptey P, Barreto ML, Matheson D, et al. Global prevention and control of NCDs: Limitations of the standard approach. J Public Health Policy 2015; 36(4): 408-25. http://doi.org/10.1057/jphp.2015.29
» http://doi.org/10.1057/jphp.2015.29

[3] ³
Malta DC, Campos MO, Oliveira MM de, Iser BPM, Bernal RTI, Claro RM, et al. Prevalência de fatores de risco e proteção para doenças crônicas não transmissíveis em adultos residentes em capitais brasileiras, 2013. Epidemiol Serv Saúde 2015; 24(3): 373-87. http://doi.org/10.5123/s1679-49742015000300004
» http://doi.org/10.5123/s1679-49742015000300004

[4] ⁴
Barreto ML. Desigualdades em Saúde: uma perspectiva global. Ciênc Saúde Coletiva 2017; 22(7): 2097-108. http://doi.org/10.1590/1413-81232017227.02742017
» http://doi.org/10.1590/1413-81232017227.02742017

[5] ⁵
Williams J, Allen L, Wickramasinghe K, Mikkelsen B, Roberts N, Townsend N. A systematic review of associations between non-communicable diseases and socioeconomic status within low- and lower-middle-income countries. J Global Health 2018; 8(2). http://doi.org/10.7189/jogh.08.020409
» http://doi.org/10.7189/jogh.08.020409

[6] ⁶
Barros MBA, César CLG, Carandina L, Torre GD. Desigualdades sociais na prevalência de doenças crônicas no Brasil, PNAD-2003. Ciênc Saúde Coletiva 2006; 11(4): 911-26. http://doi.org/10.1590/s1413-81232006000400014
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[7] ⁷
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		Bolsa Família						Total (n = 3,131)
		Yes (n = 924)			No (n = 2,207)			Total (n = 3,131)
		N	%*	95%CI	N	%*	95%CI	N	%*	95%CI
Total		924	23.28	21.50 - 25.15	2.207	76.72	74.85 - 78.50
Age (years)	18 to 29	252	31.78	27.80 - 36.04	835	43.57	40.73 - 46.45	1.087	40.83	38.44 - 43.26
	30 to 44	608	61.32	57.01 - 65.46	1.161	47.77	44.96 - 50.59	1.769	50.92	48.53 - 53.31
	45 to 49	64	6.91	5.10 - 9.29	211	8.66	7.33 - 10.21	275	8.25	7.13 - 9.54
Education (years)	0 to 8	464	49.57	45.31 - 53.82	434	16.17	14.38 - 18.13	898	23.94	22.12 - 25.87
	9 to 11	186	22.78	19.27 - 26.71	360	16.05	14.13 - 18.16	546	17.61	15.90 - 19.46
	12 or more	274	27.66	24.07 - 31.55	1.413	67.79	65.20 - 70.27	1.687	58.45	56.13 - 60.73
Skin color	White	191	26.65	22.73 - 30.98	842	51.08	48.26 - 53.90	1.033	45.4	42.98 - 47.84
	Dark-skinned black	97	10.75	8.43 - 13.61	167	8.19	6.70 - 9.99	264	8.79	7.49 - 10.29
	Light-skinned black	622	61.55	57.17 - 65.76	1.152	39.59	36.99 - 42.26	1.774	44.71	4.24 - 47.03
	Other	14	1.04	0.05 - 2.40	45	1.13	0.66 - 1.92	59	1.11	0.07 - 1.74
Region	North	294	11.62	10.15 - 13.27	635	7.6	6.92 - 8.33	929	8.53	7.90 - 9.21
	Northeast	469	50.19	45.93 - 54.45	612	21.45	19.71 - 23.31	1.081	28.14	26.41 - 29.94
	Southeast	73	26.77	22.18 - 31.92	371	45.6	42.66 - 48.57	444	41.21	38.65 - 43.82
	South	30	6.03	3.97 - 9.04	303	16.79	15.00 - 18.75	333	14.29	12.81 - 15.90
	Center West	58	5.39	4.09 - 7.06	286	8.56	7.53 - 9.72	344	7.82	6.97 - 8.77

Risk Factors for NCDs	Received Bolsa Família				Total		p*
	Yes (n = 924)		No (n = 2.207)		(n = 3.131)
	%**	95%CI	%**	95%CI	%**	95%CI
Body mass index (measured)
Overweight	33.5	29.6 - 37.6	29.3	26.8 - 32.0	30.3	28.2 - 32.5	0.001
Obese	26.9	23.1 - 31.1	21.2	18.9 - 23.6	22.5	20.6 - 24.6	0.001
Smoker
Yes	11.3	9.0 - 14.1	8.2	6.8 - 9.8	8.9	7.7 - 10.3	0.029
Consumes fatty red meat
Yes	30.3	26.2 - 34.9	25.5	23.0 - 28.2	26.6	24.5 - 28.9	0.056
Consumes sodas five or more days a week
Yes	27.0	23.2 - 31.2	27.6	25.0 - 30.3	27.5	25.3 - 29.8	0.800
Consumes alcoholic beverages once a month or more
Yes	13.4	10.6 - 16.9	18.2	16.1 - 20.6	17.1	15.3 - 19.1	0.022
Consumes beans five or more days a week
Yes	75.0	71.5 - 78.1	65.5	62.8 - 68.0	67.7	65.5 - 69.8	< 0.001

Risk factors for NCDs	Received Bolsa Família				Total		p*
	Yes (n = 924)		No (n = 2,207)		(n = 3,131)
	%**	95%CI	%**	95%CI	%**	95%CI
Self-evaluation of health
Very good	61.6	57.6 - 65.5	75.3	72.9 - 77.5	72.1	70.1 - 74.1	< 0.001
Fair	32.2	28.6 - 36.01	22.3	20.1 - 24.6	24.6	22.7 - 26.6
Poor	6.2	4.7 - 8.2	2.4	1.8 - 3.3	3.3	2.7 - 4.1
Has medical or dental insurance
Yes	5.6	3.8 - 8.1	37.1	34.3 - 39.9	29.8	27.5 - 32.1	< 0.001
Sought out health services in the past year
Yes	21.0	17.7 - 24.8	20.3	18.0 - 22.7	20.4	18.5 - 22.5	0.720
Has been hospitalized in the past 12 months
Yes	9.2	7.0 - 12.0	7.9	6.5 - 9.4	8.2	7.0 - 9.5	0.335
Self-reported hypertension
Yes	13.4	10.7 - 16.5	10.3	8.7 - 12.0	11.0	9.6 - 12.5	< 0.001
Only during pregnancy	7.4	5.09 - 10.5	3.4	2.54 - 4.47	4.3	3.43 - 5.37	< 0.001
Self-reported diabetes
Yes	2.9	1.8 - 4.6	2.1	1.4 - 3.0	2.2	1.6 - 3.0	0.134
Only during pregnancy	2.5	1.2 - 5.0	1.2	0.6 - 2.1	1.5	0.9 - 2.3	0.134
Self-reported high cholesterol
Yes	8.3	6.32 - 10.9	9.8	8.2 - 11.7	9.5	8.1 - 11.0	0.328
Self-reported arthritis or rheumatism
Yes	4.2	2.9 - 6.1	3.5	2.7 - 4.6	3.7	3.0 - 4.6	0.426
Self-reported renal insufficiency
Yes	1.6	0.7 - 3.5	1.5	0.9 - 2.6	1.6	1.0 - 2.4	0.935

NCD laboratory indicators	Bolsa Família				Adjusted PR	95%CI
	Yes		No
	%*	95%CI	%*	95%CI
Renal insufficiency (ckdepi) GFR < 60	1.84	0.74 - 2.93	1.28	0.70 - 1.86	1.49	0.69 - 3.21
Total cholesterol (TC) ≥ 200 mg/dL	23.87	20.36 - 27.37	26.28	23.76 - 28.79	0.89	0.75 - 1.06
HDL cholesterol < 40 mg/dL	28.19	24.19 - 32.19	19.72	17.51 - 21.93	1.41	1.17 - 1.69
LDL cholesterol ≥ 130 mg/dL	13.24	10.47 - 16.00	13.89	11.89 - 15.89	0.92	0.72 - 1.19
Creatinine ≥ 1.3 mg/dL	1.10	0.18 - 2.02	0.75	0.28 - 1.22	1.61	0.55 - 4.71
Glycated hemoglobin ≥ 6.5 mg/dL	4.07	2.01 - 6.13	2.72	1.84 - 3.60	1.42	0.79 - 2.54
Anemia (hemoglobin < 12 g/dL)	14.73	11.79 - 17.66	12.13	10.28 - 13.99	1.20	0.93 - 1.55
Salt consumption (>75^th percentile)	25.26	20.94 - 29.58	24.13	21.28 - 26.99	1.03	0.85 - 1.26