GBD Risk Factor Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020;396(10258):1223–49. https://doi.org/10.1016/S0140-6736(20)30752.

Article  Google Scholar 

NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants. Lancet. 2021;398(10304):957–980. https://doi.org/10.1016/S0140-6736(21)01330-1

Schutte AE, Venkateshmurthy NS, Mohan S, Prabhakaran D. Hypertension in low- and middle-income countries. Circ Res. 2021;128(7):808–26. https://doi.org/10.1161/CIRCRESAHA.120.318729.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Stringhini S, Bovet P. Socioeconomic status and risk factors for non-communicable diseases in low-income and lower-middle-income countries. Lancet Glob Health. 2017;5(3):e230–1. https://doi.org/10.1016/S2214-109X(17)30053-3.

Article  PubMed  Google Scholar 

Leng B, Jin Y, Li G, Chen L, Jin N. Socioeconomic status and hypertension: a meta-analysis. J Hypertens. 2015;33(2):221–9. https://doi.org/10.1097/HJH.0000000000000428.

Article  CAS  PubMed  Google Scholar 

Nakagomi A, Yasufuku Y, Ueno T, Kondo K. Social determinants of hypertension in high-income countries: a narrative literature review and future directions. Hypertens Res. 2022;45(10):1575–81. https://doi.org/10.1038/s41440-022-01072-4.

Article  PubMed  PubMed Central  Google Scholar 

Kirschbaum TK, Sudharsanan N, Manne-Goehler J, De Neve JW, Lemp JM, Theilmann M, et al. The association of socioeconomic status with hypertension in 76 low- and middle-income countries. J Am Coll Cardiol. 2022;80(8):804–17. https://doi.org/10.1016/j.jacc.2022.06.012.

Article  PubMed  Google Scholar 

Coelho DM, Andrade ACS, Silva UM, Lazo M, Slesinski SC, Quistberg A, et al. Gender differences in the association of individual and contextual socioeconomic status with hypertension in 230 Latin American cities from the SALURBAL study: a multilevel analysis. BMC Public Health. 2023;23:1532. https://doi.org/10.1186/s12889-023-16400-z.

Article  PubMed  PubMed Central  Google Scholar 

Tumas N, López SR, Bilal U, Ortigoza F, Roux AVD. Urban social determinants of non-communicable diseases risk factors in Argentina. Health Place. 2021;77: 102611. https://doi.org/10.1016/j.healthplace.2021.102611.

Article  PubMed  Google Scholar 

Buys DR, Howard VJ, McClure LA, Buys KC, Sawyer P, Allman RM, et al. Association between neighborhood disadvantage and hypertension prevalence, awareness, treatment, and control in older adults: results from the University of Alabama at Birmingham Study of Aging. Am J Public Health. 2015;105(6):1181–8. https://doi.org/10.2105/AJPH.2014.302452.

Article  PubMed  PubMed Central  Google Scholar 

Claudel SE, Adu-Brimpong J, Banks A, Ayers C, Albert MA, Das SR, et al. Association between neighborhood-level socioeconomic deprivation and incident hypertension: a longitudinal analysis of data from the Dallas Heart Study. Am Heart J. 2018;204:109–18. https://doi.org/10.1016/j.ahj.2018.06.010.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chaix B, Bean K, Leal C, Thomas F, Havard S, Evans D, et al. Individual/neighborhood social factors and blood pressure in the RECORD Cohort Study: which risk factors explain the associations? Hypertension. 2010;55(3):769–75. https://doi.org/10.1161/HYPERTENSIONAHA.109.141234.

Article  CAS  PubMed  Google Scholar 

Lê-Scherban F, Ballester L, Castro JC, Cohen S, Melly S, Moore K, et al. Identifying neighborhood characteristics associated with diabetes and hypertension control in an urban African American population using geo-linked electronic health records. Prev Med Rep. 2019;15: 100953. https://doi.org/10.1016/j.pmedr.2019.100953.

Article  PubMed  PubMed Central  Google Scholar 

Alves RFS, Faerstein E. Educational inequalities in hypertension: complex patterns in intersections with gender and race in Brazil. Int J Equity Health. 2016;15(1):146. https://doi.org/10.1186/s12939-016-0440-7.

Article  PubMed  PubMed Central  Google Scholar 

Wagner KJP, Boing AF, Subramanian SV, Bastos JL, André C, d’Orsi E. Effects of neighborhood socioeconomic status on blood pressure in older adults. Rev Saude Publica. 2016;50:78. https://doi.org/10.1590/S01518-8787.2016050006373.

Article  PubMed  PubMed Central  Google Scholar 

Bento IC, Mambrini JVDM, Peixoto SV. Contextual and individual factors associated with arterial hypertension among Brazilian older adults (National Health Survey–2013). Rev Bras Epidemiol. 2020;23: e200078. https://doi.org/10.1590/1980-549720200078.

Article  PubMed  Google Scholar 

Gustafsson PE, Hammarström A, San SM. Cumulative contextual and individual disadvantages over the life course and adult functional somatic symptoms in Sweden. Eur J Public Health. 2015;25(4):592–7. https://doi.org/10.1093/eurpub/cku189.

Article  PubMed  Google Scholar 

Instituto Brasileiro de Geografia e Estatística (IBGE). Ministério do Planejamento e Orçamento. Censo Demográfico 2022. População por idade e sexo: pessoas de 60 anos ou mais de idade. Resultados do universo. Brasil, Grandes Regiões e Unidades da Federação. Rio de Janeiro: IBGE; 2023. Accessed April 1, 2025. https://biblioteca.ibge.gov.br/visualizacao/livros/liv102038.pdf

Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Departamento de Vigilância de Doenças e Agravos não Transmissíveis e Promoção da Saúde. Vigitel Brasil 2017: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico: estimativas sobre frequência e distribuição sociodemográfica de fatores de risco e proteção para doenças crônicas nas capitais dos 26 estados brasileiros e no Distrito Federal em 2017. Brasília: Ministério da Saúde; 2019. Accessed April 1, 2025. https://bvsms.saude.gov.br/bvs/publicacoes/vigitel_brasil_2017_vigilancia_fatores_risco_1ed_rev.pdf

Lima-Costa MF, Andrade FB, Souza PRB Jr, Neri AL, Duarte YAO, Castro-Costa E, et al. The Brazilian Longitudinal Study of Aging (ELSI-BRAZIL): objectives and design. Am J Epidemiol. 2018;187(7):1345–53. https://doi.org/10.1093/aje/kwx387.

Article  PubMed  PubMed Central  Google Scholar 

Galobardes B, Shaw M, Lawlor DA, Lynch JW, Davey SG. Indicators of socioeconomic position (part 2). J Epidemiol Community Health. 2006;60(2):95–101. https://doi.org/10.1136/jech.2004.028092.

Article  PubMed  PubMed Central  Google Scholar 

Instituto Brasileiro de Geografia e Estatística (IBGE). Síntese de Indicadores Sociais: uma análise das condições de vida da população brasileira: 2024. Rio de Janeiro: IBGE; 2024. Accessed April 1, 2025. https://biblioteca.ibge.gov.br/visualizacao/livros/liv102144.pdf

Allik M, Ramos D, Agranonik M, Pinto Júnior EP, Ichihara MY, Barreto ML, et al. Developing a Small-Area Deprivation Measure for Brazil. Glasgow: University of Glasgow; 2020. https://doi.org/10.36399/gla.pubs.215898

Levorato CD, Mello LM, Silva AS, Nunes AA. Factors associated with the demand for health services from a gender-relational perspective. Cien Saude Colet. 2014;19(4):1263–74. https://doi.org/10.1590/1413-81232014194.01252013.

Article  PubMed  Google Scholar 

Pasquali R. The hypothalamic-pituitary-adrenal axis and sex hormones in chronic stress and obesity: pathophysiological and clinical aspects. Ann N Y Acad Sci. 2012;1264:20–35. https://doi.org/10.1111/j.1749-6632.2012.06569.x.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Merlo J, Chaix B, Ohlsson H, Beckman A, Johnell K, Hjerpe P, et al. A brief conceptual tutorial of multilevel analysis in social epidemiology: using measures of clustering in multilevel logistic regression to investigate contextual phenomena. J Epidemiol Community Health. 2006;60(4):290–7. https://doi.org/10.1136/jech.2004.029454.

Article  PubMed  PubMed Central  Google Scholar 

Malta DC, Bernal RTI, Prates EJS, Vasconcelos NM, Gomes CS, Stopa SR, et al. Self-reported arterial hypertension, use of health services and guidelines for care in Brazilian population: national Health Survey, 2019. Epidemiol Serv Saude. 2022;31(spe1): e2021369. https://doi.org/10.1590/SS2237-9622202200012.especial.

Article  PubMed  PubMed Central  Google Scholar 

Ross CE, Mirowsky J. Gender and the health benefits of education. Sociol Q. 2010;51(1):1–19. https://doi.org/10.1111/j.1533-8525.2009.01164.x.

Article  Google Scholar 

Kandasamy S, Anand SS. Cardiovascular disease among women from vulnerable populations: a review. Can J Cardiol. 2018;34(4):450–7. https://doi.org/10.1016/j.cjca.2018.01.015.

Article  PubMed  Google Scholar 

Vega AP. Pobreza feminina desvendando suas raízes. TEL Temp Esp Linguagem. 2019;10(2):177–200. https://doi.org/10.5935/2177-6644.20190025.

Article  Google Scholar 

Bak Bak CK, Andersen PT, Bacher I, Bancila DD. The association between socio-demographic characteristics and perceived stress among residents in a deprived neighbourhood in Denmark. Eur J Public Health. 2012;22(6):787–92. https://doi.org/10.1093/eurpub/ckr135.

Article  PubMed  Google Scholar 

McEwen BS. Protective and damaging effects of stress mediators. N Engl J Med. 1998;338(3):171–9. https://doi.org/10.1056/NEJM199801153380307.