Produção Nacional
Revisado por pares
Self-declared ethnicity associated with risk factors of cardiovascular diseases in an urban sample of the Brazilian population: The role of educational status in the association
2013; Elsevier BV; Volume: 168; Issue: 3 Linguagem: Inglês
10.1016/j.ijcard.2013.04.115
ISSN1874-1754
AutoresHadassa Rodrigues Santos, Tiago M. Fragoso, George Luiz Lins Machado-Coelho, Raimundo Marques Nascimento, José Geraldo Mill, José Eduardo Krieger, Alexandre C. Pereira,
Tópico(s)Genetic Associations and Epidemiology
ResumoThe incidence of cardiovascular diseases (CVDs) does not follow the same pattern among different ethnic groups, in the same way the socioeconomic status of an individual may be related to which ethnic group he/she belongs. Studies show that low socioeconomic status is associated with factors such as poor nutrition, and stress which increases the chances of developing CVD [[1]Sloan R. Huang M.-H. Sidney S. Liu K. Williams O.D. Seeman T. Socioeconomic status and health: is parasympathetic nervous system activity an intervening mechanism?.Int J Epidemiol. 2005; 34: 309-315Crossref PubMed Scopus (41) Google Scholar]. Brazil is a country with a highly admixture population and the three main ancestral populations are European, African and Amerindian, reflecting the history of the country's colonization [[2]Giolo S.R. Soler J.M.P. Greenway S.C. et al.Brazilian urban population genetic structure reveals a high degree of admixture.Eur J Hum Genet. 2011; : 1-6Google Scholar]. The three main self-reported ethnicities are White, Mulatto (mixed ethnicity) and Black. Thus, the aim of this study was to access the association between risk factors for CVD with self-reported ethnicity, and understand the influence of socioeconomic factors on these associations in a representative sample of the urban Brazilian population. We analyzed self-reported data of 2531 individuals aged 17–88 year from 72 urban regions of Brazil. Ethnicity/color was self-reported as White, Black, Mulattoes (mixed ethnicity) or others. The variables analyzed in this study were the following risk factors for CVDs: arterial hypertension, hypercholesterolemia and stroke. The covariates in this study are alcohol consumption, smoking habits, physical activity, family income and educational level. Income and educational levels were divided into several categories. However, such parameterization divided the sample into many different classes, unreliable estimates for the effects and making the interpretation of the results difficult, we represented these covariates in two ways, categorically and continuously. These variables were all self-reported. We performed logistic regressions to assess the association between arterial hypertension, hypercholesterolemia and stroke with self-reported ethnicity. The logistic regression models were fitted using these risk factors as a dependent variable adjusting for possible confounders of the association. For the variable stroke, another regression was performed by adding hypertension as a confounder of the association. The analyses were performed using the glm function available in the R Statistical Software [[3]R Development Core Team R: a language and environment for statistical computing.R Foundation for Statistical Computing, Vienna, Austria. 2012Google Scholar]. Results with p-value < 0.05 were considered significant. The study population comprised 51.56% of White individuals, 10.27% Black, 36.31% Mulattoes, and 1.86% other ethnicities. Table 1 shows the distribution of the proportion of cardiovascular risk factors and general characteristics of the studied sample between the different ethnicities. In this table, we can observe significant differences between ethnic groups regarding educational level, specifically for individuals with a university degree.Table 1Characteristics of the Brazilian population stratified by ethnicity.Black (n = 260)White (n = 1305)Mulatto (n = 919)Others (n = 47)p-ValueAge, years40.07 ± 14.5041.85 ± 15.2839.89 ± 14.4339.51 ± 16.23 0.05 Female48.0852.4949.9544.68Educational level % No formal education7.313.456.642.13<0.05 Primary56.9238.8549.5144.68 High school27.3138.4736.3431.91 University degree8.4619.237.5121.28Income % Up to 1 MW16.926.9013.2810.64 0.05 Stroke2.310.772.720.00<0.05 Hypercholesterolemia9.6216.8614.3617.02 0.05 Sedentary lifestyle80.7778.0181.8376.60>0.05 Alcohol consumption41.5435.5637.7640.43>0.05 Open table in a new tab We can see in our data that educational level and economic status were significantly different between ethnic groups. Blacks and Mulattoes are more likely to have no formal education than Whites, and in all income levels above 1 MW (minimal wage), Whites had a greater chance, and the odds increased with socioeconomic status (unpublished results). The analysis of the association between hypertension and self-reported ethnicity was significant in both logistic regression models. In the first model, Black individuals showed 39% higher risk of having hypertension than White individuals (Table 2). For the second model, the odds ratio (OR) was similar. The association between ethnicity and hypercholesterolemia was also significant in both models, individuals of Black ethnicity had a 43% lower risk than White (Table 2).Table 2Multiple logistic regression analysis of risk factors associated with hypertension, hypercholesterolemia and stroke in adult individual of Brazilian population sample.Risk factorsOdds ratios (95% confidence intervals)HypertensionHypercholesterolemiaStroke1Stroke2hAdjusted by hypertension.EthnicityaAdjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, educational level and income. (vs. Whites) Blacks1.39 (1.018–1.901)p-Value<0.05.0.57 (0.356–0.905)p-Value<0.05. Mulattoes1.02 (0.831–1.258)0.96 (0.741–1.240)__IncomebAdjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, educational level and ethnicity. (vs. up to 1 MW) 1 to 5 MW1.14 (0.836–1.571)1.17 (0.782–1.748)__ 5 to10 MW0.83 (0.641–1.071)0.91 (0.660–1.244) 10 to 20 MW1.14 (0.780–1.682)0.90 (0.563–1.441) Above 20 MW0.78 (0.443–1.387)0.80 (0.400–1.602)Educational levelcAdjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, income and ethnicity. (vs. no formal education) Primary0.82 (0.542–1.252)0.63 (0.396–1.009)__ High school0.75 (0.597–0.934)p-Value<0.05.1.32 (0.992–1.759) University degree1.18 (0.857–1.634)1.38 (0.946–2.013)Behavior risk factor dAdjusted by gender, age, educational level, income and ethnicity. Sedentary lifestyle (vs. Physically active)1.03 (0.813–1.306)1.05 (0.788–1.409)__ Smoking habits (vs. no smoking)0.82 (0.654–1.024)0.76 (0.564–1.024) Alcohol consumption (vs. less or no consumption)0.95 (0.771–1.164)0.86 (0.655–1.121)Model 2 with income and educational level as continuous variables.EthnicityeAdjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, educational level and income. (vs. Whites) Blacks1.41 (1.037–1.932)p-Value<0.05.0.57 (0.361–0.914)p-Value<0.05.2.83 (0.989–8.098)2.60 (0.897–7.517) Mulattoes1.02 (0.828–1.252)0.96 (0.746–1.245)3.37 (1.570–7.244)†p-Value<0.01.3.47 (1.607–7.491)†p-Value<0.01.IncomefAdjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, educational level and ethnicity.0.97 (0.864–1.090)0.94 (0.816–1.084)0.69 (0.429–1.104)0.69 (0.422–1.130)Educational levelgAdjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, income and ethnicity.0.87 (0.745–0.997)p-Value<0.05.1.19 (1.006–1.415)p-Value<0.05.0.68 (0.408–1.131)0.73 (0.439–1.216)† p-Value < 0.01. p-Value < 0.05.a Adjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, educational level and income.b Adjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, educational level and ethnicity.c Adjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, income and ethnicity.d Adjusted by gender, age, educational level, income and ethnicity.e Adjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, educational level and income.f Adjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, educational level and ethnicity.g Adjusted by gender, age, smoking habits, alcohol consumption, sedentary lifestyle, income and ethnicity.h Adjusted by hypertension. Open table in a new tab Similarly to our results, studies comparing cardiovascular risk factors by ethnicity among adults and young, found that Black individuals were more likely to have uncontrolled blood pressure than Whites [4Santos P.C.J.L. Alvim R.O. Ferreira N.E. et al.Ethnicity and arterial stiffness in Brazil.Am J Hypertens. 2011; 24: 278-284Crossref PubMed Scopus (51) Google Scholar, 5Quiñones A.R. Liang J. Ye W. Racial and ethnic differences in hypertension risk: new diagnoses after age 50.Ethn Dis. 2012; 22: 175-180PubMed Google Scholar]. For hypercholesterolemia, the opposite occurred, White individuals had a higher risk than Blacks, in agreement with the literature [[6]Barreira T.V. Staiano A.E. Harrington D.M. et al.Anthropometric correlates of total body fat, abdominal adiposity, and cardiovascular disease risk factors in a biracial sample of men and women.Mayo Clin Proc. 2012; 87: 452-460Abstract Full Text Full Text PDF PubMed Scopus (83) Google Scholar]. The association between stroke and ethnicity was analyzed in the second model. Stroke was significantly associated with the Mulatto ethnic group, producing a risk estimative of approximately 3.4 times higher of being affected by a stroke when compared with Whites. The models for stroke adjusted by hypertension presented similar results suggesting that the observed association was not solely explained by different prevalences of hypertension in different ethnicities (Table 2). A study conducted by Kleindorfer et al. [[7]Kleindorfer D.O. Khoury J. Moomaw C.J. et al.Stroke incidence is decreasing in whites but not in blacks: a population-based estimate of temporal trends in stroke incidence from the Greater Cincinnati/Northern Kentucky Stroke Study.Stroke. 2010; 41: 1326-1331Crossref PubMed Scopus (249) Google Scholar] showed that Blacks had higher stroke incidence than Whites and, considering a long follow-up period, found a decrease in incidence among Whites, but not among Blacks, suggesting that racial disparity in stroke incidence is worsening. We also observed that individuals with high school had a lower cardiovascular risk than individuals with no formal education. The analysis of educational status as a continuous variable showed a 13% decrease in risk with each increase in educational level suggesting a protector role of education in blood pressure. This may be because individuals with high educational levels may be more exposed to messages about health, and consequently increase health knowledge, improve health behaviors [[8]Hayes D.K. Greenlund K.J. Denny C.H. Neyer J.R. Croft J.B. Keenan N.L. Racial/ethnic and socioeconomic disparities in health-related quality of life among people with coronary heart disease, 2007.Prev Chronic Dis. 2011; 8: A78PubMed Google Scholar], have improved employment opportunities, working conditions, health care, income, and being less likely to suffer complications of a chronic disease [1Sloan R. Huang M.-H. Sidney S. Liu K. Williams O.D. Seeman T. Socioeconomic status and health: is parasympathetic nervous system activity an intervening mechanism?.Int J Epidemiol. 2005; 34: 309-315Crossref PubMed Scopus (41) Google Scholar, 9Gabel J. Levitt L. Holve E. et al.Job-based health benefits in 2002: some important trends.Health Aff. 2002; 21: 143-151Crossref PubMed Scopus (61) Google Scholar]. On the other hand, hypercholesterolemia and educational level are inversely related, and our results demonstrated a 19% increase in this risk factor with each increase in educational level. Other results are presented in Table 2. In this study, Black individuals were associated with hypertension and Mulattoes were associated with stroke. These two ethnic groups were also associated with lower education, and these two risk factors were also associated with lower education. Considering the common association of the factors existing in the model of education and model of self-reported ethnicity, data suggest that part of the observed differences in health between different ethnic groups are also a consequence of the observed socioeconomic difference between these groups. Nonetheless, the associations persist even after adjusting for this potential confounder also suggesting residual risk due to ethnicity per se. Ethnic differences are evident in arterial hypertension, hypercholesterolemia and stroke prevalence in the Brazilian urban population. This may reflect greater susceptibility of particular groups to CVD. However, social and economic differences are also evident among ethnic groups and are also related to these risk factors, suggesting that ethnic differences may, in part, be reflecting much, but not all, of the socioeconomic differences existent. Authors contributions: Santos H.C. — performed the data analysis and interpretation, and wrote the manuscript. Fragoso M.T. — provided statistical support for the data analysis and interpretation. Machado-Coelho G.L., do Nascimento R.M., Mill J.G. and Krieger J.E. — participated in data collection. Pereira A.C. — participated in the concept and design of the study, provided support for data analysis and interpretation, and revised the manuscript. Acknowledgment of grant support: This study was supported by a grant from the São Paulo Research Foundation (FAPESP) to the Santos H.C. (Grant 2012/11879-0). This work was supported by Hospital Samaritano Society (Grant 25000.180.672/2011-81), through Ministry of Health to Support Program Institutional Development of the Unified Health System (SUS-PROADI). The authors of this manuscript have certified that they comply with the Principles of Ethical Publishing in the International Journal of Cardiology.
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