Prevalence and factors associated with metabolic syndrome in vulnerable population in northern Brazil: a cross-sectional study
DOI:
https://doi.org/10.36311/jhgd.v31.11410Keywords:
obesity , cardiovascular disease , lifestyle , vulnerable populationAbstract
Introduction: metabolic syndrome (SM) is a set of metabolic imbalances that are associated with the development of cardiovascular diseases, type 2 diabetes mellitus, in addition to other chronic non-communicable diseases. SM has been gaining prominence in the scientific community mainly due to link with the increase of the obesity epidemic in the world.
Objective: To analyze the factors associated with metabolic syndrome and its prevalence in a vulnerable population in the Northern Region of Brazil.
Methods: This is a cross-sectional study with artisanal fishers from the state of Tocantins, and data collected between 2016 and 2017 were used. The outcome variable for MS was defined according to the criteria of the International Diabetes Federation. The following variables were assessed: socioeconomic and demographic information, fish consumption, and smoking. For statistical and data analysis, the Shapiro–Wilk test, Poisson regression, Student's t-test, and interquartile regression were evaluated.
Results: The general prevalence rate (PR) of MS was 31.9% higher in women than in men. The factors associated with MS were economic class and smoking, and there was an association between socioeconomic class and smoking (p=0.015). The most prevalent component was abdominal obesity with a rate of 62.5% (95% confidence interval [CI]: 54.5, 70.5). The prevalence of MS in terms of sex (PR=2.27, 95% 1.04 CI, 4.92, p=0.037), smoking (PR=2.40, 95% CI, 30, p=0.003) and years of professional experience (>10 PR=2.07, 95% CI 1.06, 4.05, p=0.033) was also assessed.
Conclusion: In the present study, the prevalence of SM was associated with smoking and socioeconomic status, which is considered high when compared to the worldwide prevalence. These findings highlight the importance of looking at public policies so that health services can develop actions that generate greater adherence to good health practices by the population.
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References
Relatório de status global sobre álcool e saúde 2018 [Internet]. [citado 1º de abril de 2021]. Disponível em: https://www.who.int/publications-detail-redirect/9789241565639
Saad MAN, Cardoso GP, Martins W de A, Velarde LGC, Cruz Filho RA da. Prevalence of metabolic syndrome in elderly and agreement among four diagnostic criteria. Arquivos Brasileiros de Cardiologia [Internet]. 2014 [citado 1º de abril de 2021]; Disponível em: http://www.gnresearch.org/doi/10.5935/abc.20140013
The IDF consensus worldwide definition of the metabolic syndrome. Obes metabol. 15 de setembro de 2005; 2(3): 47–9.
Barbosa IR, Gonçalves RCB, Santana RL. Mapa da vulnerabilidade social do município de Natal-RN em nível de setor censitário. J Hum Growth Dev. 6 de maio de 2019; 29(1): 48–56.
Freitas ICM de, Moraes SA de. O efeito da vulnerabilidade social sobre indicadores antropométricos de obesidade: resultados de estudo epidemiológico de base populacional. Rev bras epidemiol. junho de 2016; 19(2): 433–50.
Pena PGL, Gomez CM. Health of subsistence fishermen and challenges for Occupational Health Surveillance. Ciênc saúde coletiva. dezembro de 2014; 19(12): 4689–98.
Silva ELP da, Wanderley MB, Conserva M de S. Proteção social e território na pesca artesanal do litoral paraibano. Serv Soc Soc. março de 2014; (117): 169–88.
Faraco LFD, Filho JMA, Daw T, Lana P da C, Teixeira CF. Vulnerabilidade de pescadores no litoral sul do Brasil e sua relação com áreas marinhas protegidas em um cenário de declínio da pesca. Desenvolvimento e Meio Ambiente [Internet]. 31 de agosto de 2016 [citado 1º de abril de 2021]; 38(0). Disponível em: https://revistas.ufpr.br/made/article/view/45850
Barros MB de A, César CLG, Carandina L, Torre GD. Desigualdades sociais na prevalência de doenças crônicas no Brasil, PNAD-2003. Ciênc saúde coletiva. dezembro de 2006; 11(4): 911-26.
Zangirolami-Raimundo J, Echeimberg JDO, Leone C. Research methodology topics: Cross-sectional studies. J Hum Growth Dev. 28 de novembro de 2018; 28(3): 356–60.
Critério brasil - abep [Internet]. [citado 1º de abril de 2021]. Disponível em: http://www.abep.org/criterio-brasil
Maciel E da S, Vasconcelos JS, Silva LKS da, Sonati JG, Galvão J, Silva D da, et al. Designing and validating the methodology for the Internet assessment of fish consumption at a university setting. Food Sci Technol (Campinas). junho de 2014; 34(2): 315–23.
Abeso: Associação Brasileira para o Estudo da Obesidade e da Síndrome Metabólica [Internet]. Abeso. [citado 1º de abril de 2021]. Disponível em: https://abeso.org.br/
Faludi A, Izar M, Saraiva J, Chacra A, Bianco H, Afiune Neto A, et al. Atualização da diretriz brasileira de dislipidemias e prevenção da aterosclerose - 2017. Arquivos Brasileiros de Cardiologia [Internet]. 2017 [citado 1º de abril de 2021]; 109(1). Disponível em: http://www.gnresearch.org/doi/10.5935/abc.20170121.
Malachias MVB, Bortolotto LA, Drager LF, Borelli F a. O, Lotaif L a. D, Martins LC, et al. 7th brazilian guideline of arterial hypertension: chapter 12 - secondary arterial hypertension. Arquivos Brasileiros de Cardiologia. setembro de 2016; 107(3): 67–74.
de Carvalho Vidigal F, Bressan J, Babio N, Salas-Salvadó J. Prevalence of metabolic syndrome in Brazilian adults: a systematic review. BMC Public Health. dezembro de 2013; 13(1): 1198.
Andrew MK. Frailty and social vulnerability. Frailty in Aging. 2015; 41: 186–95.
Sun K, Liu J, Ning G. Active smoking and risk of metabolic syndrome: a meta-analysis of prospective studies. Barengo NC, organizador. PLoS ONE. 17 de outubro de 2012; 7(10): e47791.
Humphries MC, Gutin B, Barbeau P, Vemulapalli S, Allison J, Owens S. Relations of adiposity and effects of training on the left ventricle in obese youths: Medicine & Science in Sports & Exercise. setembro de 2002; 34(9): 1428–35.
Moore JX. Metabolic syndrome prevalence by race/ethnicity and sex in the united states, national health and nutrition examination survey, 1988–2012. Prev Chronic Dis [Internet]. 2017 [citado 1º de abril de 2021]; 14. Disponível em: https://www.cdc.gov/pcd/issues/2017/16_0287.htm
Moreira GC, Cipullo JP, Ciorlia LAS, Cesarino CB, Vilela-Martin JF. Prevalence of metabolic syndrome: association with risk factors and cardiovascular complications in an urban population. Barengo NC, organizador. PLoS ONE. 2 de setembro de 2014; 9(9): e105056.
Luisi C, Figueiredo FW dos S, Sousa LV de A, Quaresma FRP, Maciel E da S, Adami F. Prevalence of and factors associated with metabolic syndrome in afro-descendant communities in a situation of vulnerability in northern brazil: a cross-sectional study. Metabolic Syndrome and Related Disorders. maio de 2019; 17(4): 204–9.
Sousa LVDA, Maciel EDS, Quaresma FRP, Abreu ACG de, Paiva LDS, Fonseca FLA, et al. Quality of life and metabolic syndrome in brazilian quilombola communities: a crosssectional study. J Hum Growth Dev. 28 de novembro de 2018; 28(3): 316–28.
Sabir AA, Jimoh A, Iwuala SO, Isezuo SA, Bilbis LS, Aminu KU, et al. Metabolic syndrome in urban city of North-Western Nigeria: prevalence and determinants. The Pan African Medical Journal [Internet]. 27 de janeiro de 2016 [citado 1º de abril de 2021]; 23 (19). Disponível em: https://www.panafrican-med-journal.com/content/article/23/19/full
Gronner MF, Bosi PL, Carvalho AM, Casale G, Contrera D, Pereira MA, et al. Prevalence of metabolic syndrome and its association with educational inequalities among Brazilian adults: a population-based study. Braz J Med Biol Res. julho de 2011; 44(7): 713–9.
Rocha FL, Melo RLP de, Menezes TN de, Universidade Federal de Campina Grande, Brazil, Universidade Federal da Paraíba, Brazil, Universidade Estadual da Paraíba, Brazil. Factors associated with metabolic syndrome among the elderly in the northeast of Brazil. Rev bras geriatr gerontol. dezembro de 2016; 19(6): 978–86.
Misra A, Khurana L. Obesity and the metabolic syndrome in developing countries. The Journal of Clinical Endocrinology & Metabolism. novembro de 2008; 93 (11_supplement_1): s9–30.
Sigdel M, Yadav BK, Gyawali P, Regmi P, Baral S, Regmi SR, et al. Non-high density lipoprotein cholesterol versus low density lipoprotein cholesterol as a discriminating factor for myocardial infarction. BMC Res Notes. dezembro de 2012; 5 (1): 640.
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: The Journal of the American Medical Association. 16 de maio de 2001; 285(19): 2486–97.
Garg PR, Kabita S, Sinha E, Kalla L, Kaur L, Saraswathy KN. The association of non-HDL cholesterol with the presence of metabolic syndrome in North Indian subjects with and without CAD. Annals of Human Biology. janeiro de 2013; 40 (1): 111–5.
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Copyright (c) 2021 Mayzza Campina Rodrigues, Erika da Silva Maciel, Fernando Rodrigues Peixoto Quaresma, Luis Fernando Castagnino Sesti, Laércio da Silva Paiva, Hugo Macedo Junior, Francisco Albino de Araújo, Fernando Luiz Affonso Fonseca and Fernando Adami
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