Abstract

We investigated whether racial discrimination accelerates the weight and Body Mass Index (BMI) gain in Blacks and Browns participants of the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) in four years of follow-up. We compared body weight and BMI between the 1st (2008-2010) and 2nd visit (2012-2014) of 5,983 Blacks and Browns participants. Exposure to racial discrimination and covariates (age, sex, education, and research center) were obtained at the 1st visit. Linear mixed effects models stratified by race/skin color were used. Report of racial discrimination was more frequent among Blacks (32.1%) than Browns (6.3%). During the follow-up period, Blacks and Browns gained an average of 1.4kg and 1.2kg, respectively. This increase was greater among those who reported discrimination when compared to those who did not, both in Blacks (2.1kg vs.1.0kg, p < 0.001) and Browns (1.9kg vs. 1.1kg, p < 0.05). The results of the interaction between racial discrimination and time showed that Blacks, but not Browns, who reported racial discrimination had greater weight and BMI gains between visits. Our results suggest that reducing racial discrimination would contribute to prevent and/or control obesity increase in the country.

Palavras-chave:
Discriminação racial; Racismo; Ganho de peso; Estudos de coorte

Resumo

Investigou-se se a discriminação racial acelera o ganho de peso corporal e o Índice de Massa Corporal (IMC) em pretos e pardos participantes do Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil) em quatro anos de seguimento. Comparou-se o peso corporal e o IMC entre a 1ª (2008-2010) e a 2ª visita (2012-2014) de 5.983 participantes pretos e pardos. A exposição à discriminação racial e às covariáveis ​​(idade, sexo, escolaridade e centro de pesquisa) foram obtidas na 1ª visita. Foram utilizados modelos lineares de efeitos mistos estratificados por raça/cor da pele. O relato de discriminação racial foi mais frequente entre pretos (32,1%) do que em pardos (6,3%). Durante o período de acompanhamento, pretos e pardos ganharam uma média de 1,4kg e 1,2kg, respectivamente. Esse aumento foi maior entre os que relataram discriminação, quando comparados aos que não relataram, tanto em pretos (2,1 kg vs. 1,0 kg, p < 0,001) quanto em pardos (1,9kg vs. 1,1kg, p < 0,05). Após ajustes, os pretos, mas não os pardos, que relataram discriminação racial apresentaram maiores ganhos de peso e IMC entre as visitas. Nossos resultados sugerem que a redução da discriminação racial pode contribuir para prevenir e/ou controlar o aumento da obesidade no país.

Palavras-chave:
Discriminação racial; Racismo; Ganho de peso; Estudos de coorte

Introduction

Black individuals and other minorities are disproportionately affected by overweight and obesity characterizing a deep racial inequality in prevalence¹1 D'Agostino-McGowan L, Gennarelli RL, Lyons SA, Goodman, MS. Using small-area analysis to estimate county-level racial disparities in obesity demonstrating the necessity of targeted interventions. Int J Environ Res Public Health 2014; 11(1):418-428.

2 Wong RJ, Chou C, Ahmed A. Long term trends and racial/ethnic disparities in the prevalence of obesity. J Commu-nity Health 2014; 39(6):1150-1160.

3 Qobadi M, Payton M. Racial disparities in obesity prevalence in Mississippi: role of socio-demographic characteris-tics and physical activity. Int J Environ Res Public Health 2017; 14(3):258.^-44 Araujo MC, Baltar VT, Yokoo EM, Sichieri R. The association between obesity and race among Brazilian adults is de-pendent on sex and socio-economic status. Public Health Nutr 2018; 21(11):2096-2102. and incidence⁵5 Cozier YC, Yu J, Coogan PF, Bethea TN, Rosenberg L, Palmer JR. Racism, segregation, and risk of obesity in the black women's health study. Am J Epidemiol 2014; 179(7):875-883.^,66 Machado AV, Camelo LV, Chor D, Griep RH, Guimarães JMN, Giatti L, Barreto SM. Racial inequality, racial discrimi-nation and obesity incidence in adults from the ELSA-Brasil cohort. J Epidemiol Community Health 2021; 75:695-701. of these two outcomes in different countries. The exposure to racial discrimination might explain, at least in part, this inequity⁷7 Paradies Y, Ben J, Denson N, Elias A, Priest N. Racism as a determinant of health: a systematic review and meta-analysis. PLoS One 2015; 10(9):e0138511.. In North American studies, perceived racial discrimination has been associated with higher BMI⁵5 Cozier YC, Yu J, Coogan PF, Bethea TN, Rosenberg L, Palmer JR. Racism, segregation, and risk of obesity in the black women's health study. Am J Epidemiol 2014; 179(7):875-883.^,88 Cozier YC, Wise LA, Palmer JR, Rosenberg L. Perceived racism in relation to weight change in the Black Women's Health Study. Ann Epidemiol 2009; 19(6):379-387.

9 Cunningham TJ, Berkman LF, Kawachi I, Jacobs DR Jr, Seeman TE, Kiefe CI, Gortmaker SL. Changes in waist circum-ference and body mass index in the US Cardia cohort: fixed-effects associations with self-reported experiences of racial/ethnic discrimination. J Biosoc Sci 2013; 45(2):267-278.^-1010 Gee GC, Ro A, Gavin A, Takeuchi DT. Disentangling the effects of racial and weight discrimination on body mass in-dex and obesity among Asian Americans. Am J Public Health 2008; 98(3):493-500. and waist circumference⁹9 Cunningham TJ, Berkman LF, Kawachi I, Jacobs DR Jr, Seeman TE, Kiefe CI, Gortmaker SL. Changes in waist circum-ference and body mass index in the US Cardia cohort: fixed-effects associations with self-reported experiences of racial/ethnic discrimination. J Biosoc Sci 2013; 45(2):267-278.^,1111 Tull SE, Wickramasuriya T, Taylor J, Smith-Burns V, Brown M, Champagnie G, Daye K, Donaldson K, Solomon N, Walker S, Fraser H, Jordan OW. Relationship of internalized racism to abidominal obesity and blood pressure in Af-ro-Caribbean women. J Natl Med Assoc 1999; 91(8):447-452.

12 Chambers EC, Tull ES, Fraser HS, Mutunhu NR, Sobers N, Niles E. The relationship of internalized racism to body fat distribution and insulin resistance among African adolescent youth. J Natl Med Assoc 2004; 96(12):1594-1598.^-1313 Butler C, Tull ES, Chambers EC, Taylor J. Internalized racism, body fat distribution, and abnormal fasting glucose among African-Caribbean women in Dominica, West Indies. J Natl Med Assoc 2002; 94(3):143-1488.. However, most previous studies included only women⁵5 Cozier YC, Yu J, Coogan PF, Bethea TN, Rosenberg L, Palmer JR. Racism, segregation, and risk of obesity in the black women's health study. Am J Epidemiol 2014; 179(7):875-883.^,88 Cozier YC, Wise LA, Palmer JR, Rosenberg L. Perceived racism in relation to weight change in the Black Women's Health Study. Ann Epidemiol 2009; 19(6):379-387.^,99 Cunningham TJ, Berkman LF, Kawachi I, Jacobs DR Jr, Seeman TE, Kiefe CI, Gortmaker SL. Changes in waist circum-ference and body mass index in the US Cardia cohort: fixed-effects associations with self-reported experiences of racial/ethnic discrimination. J Biosoc Sci 2013; 45(2):267-278.^,1111 Tull SE, Wickramasuriya T, Taylor J, Smith-Burns V, Brown M, Champagnie G, Daye K, Donaldson K, Solomon N, Walker S, Fraser H, Jordan OW. Relationship of internalized racism to abidominal obesity and blood pressure in Af-ro-Caribbean women. J Natl Med Assoc 1999; 91(8):447-452.^,1313 Butler C, Tull ES, Chambers EC, Taylor J. Internalized racism, body fat distribution, and abnormal fasting glucose among African-Caribbean women in Dominica, West Indies. J Natl Med Assoc 2002; 94(3):143-1488. and only four studies were longitudinal⁵5 Cozier YC, Yu J, Coogan PF, Bethea TN, Rosenberg L, Palmer JR. Racism, segregation, and risk of obesity in the black women's health study. Am J Epidemiol 2014; 179(7):875-883.^,66 Machado AV, Camelo LV, Chor D, Griep RH, Guimarães JMN, Giatti L, Barreto SM. Racial inequality, racial discrimi-nation and obesity incidence in adults from the ELSA-Brasil cohort. J Epidemiol Community Health 2021; 75:695-701.^,88 Cozier YC, Wise LA, Palmer JR, Rosenberg L. Perceived racism in relation to weight change in the Black Women's Health Study. Ann Epidemiol 2009; 19(6):379-387.^,99 Cunningham TJ, Berkman LF, Kawachi I, Jacobs DR Jr, Seeman TE, Kiefe CI, Gortmaker SL. Changes in waist circum-ference and body mass index in the US Cardia cohort: fixed-effects associations with self-reported experiences of racial/ethnic discrimination. J Biosoc Sci 2013; 45(2):267-278.. A recent Brazilian study conducted with ELSA-Brasil participants demonstrated that racial discrimination increases the obesity incidence in Black individuals with low education⁶6 Machado AV, Camelo LV, Chor D, Griep RH, Guimarães JMN, Giatti L, Barreto SM. Racial inequality, racial discrimi-nation and obesity incidence in adults from the ELSA-Brasil cohort. J Epidemiol Community Health 2021; 75:695-701.. However, we do not know if the exposure to racial discrimination can modify the trajectory of weight and BMI, accelerating the weight gain in exposed Black and Brown individuals vis-à-vis those not exposed. This investigation is important because weight gain, even when the gain is below the obesity cutoff, the upward trend can have negative health repercussions¹⁴14 Zheng Y, Manson JE, Yuan C, Liang MH, Grodstein F, Stampfer MJ, Willett WC, Hu FB. Associations of weight gain from early to middle adulthood with major health outcomes later in life. J Am Med Assoc 2017; 318(3):255-269.. Moderate weight gains over time tend to be unnoticed and delay individuals and health professionals concerns and adoptions of control measures¹⁴14 Zheng Y, Manson JE, Yuan C, Liang MH, Grodstein F, Stampfer MJ, Willett WC, Hu FB. Associations of weight gain from early to middle adulthood with major health outcomes later in life. J Am Med Assoc 2017; 318(3):255-269.. Thus, the identification of groups susceptible to greater weight gains over time is important to promote actions to prevent an early onset of obesity and related health problems¹⁴14 Zheng Y, Manson JE, Yuan C, Liang MH, Grodstein F, Stampfer MJ, Willett WC, Hu FB. Associations of weight gain from early to middle adulthood with major health outcomes later in life. J Am Med Assoc 2017; 318(3):255-269.. We investigated whether racial discrimination accelerates weight and BMI gain in Black and Brown ELSA-Brasil participants after four years of follow-up.

Material and methods

Study design and population

We used data from the 1st (2008-2010) and 2nd visit (2012-2014) of ELSA-Brasil, which is a prospective multicenter study, carried out with 15105 civil servants, aged between 35 and 74 years old, from universities and research institutions located in six Brazilian capitals¹⁵15 Aquino EM, Barreto SM, Bensenor IM, Carvalho MS, Chor D, Duncan BB, Lotufo PA, Mill JG, Molina Mdel C, Mota EL, Passos VM, Schmidt MI, Szklo M. Brazilian Longitudinal Study of Adult Health (ELSA-Brasil): objectives and design. Am J Epidemiol 2012; 175(4):315-324.. The ELSA-Brasil cohort comprises of voluntary participants and efforts were made to recruit similar amounts of men and women, as well as predefined proportions of age groups and occupational categories. The sample size calculation was performed considering two main ELSA outcomes of interest: type 2 diabetes and myocardial infarction¹⁵15 Aquino EM, Barreto SM, Bensenor IM, Carvalho MS, Chor D, Duncan BB, Lotufo PA, Mill JG, Molina Mdel C, Mota EL, Passos VM, Schmidt MI, Szklo M. Brazilian Longitudinal Study of Adult Health (ELSA-Brasil): objectives and design. Am J Epidemiol 2012; 175(4):315-324.. An alpha value of 5%, statistical power of 80%, exposure prevalence of 20%, and a relative risk of 2.0 was considered, reaching an estimate of 6,400 participants¹⁵15 Aquino EM, Barreto SM, Bensenor IM, Carvalho MS, Chor D, Duncan BB, Lotufo PA, Mill JG, Molina Mdel C, Mota EL, Passos VM, Schmidt MI, Szklo M. Brazilian Longitudinal Study of Adult Health (ELSA-Brasil): objectives and design. Am J Epidemiol 2012; 175(4):315-324.. To enable the evaluation of sex-specific analyzes and to compensate for possible losses of follow-up, a desirable sample size of 15,000 participants was estimated¹⁵15 Aquino EM, Barreto SM, Bensenor IM, Carvalho MS, Chor D, Duncan BB, Lotufo PA, Mill JG, Molina Mdel C, Mota EL, Passos VM, Schmidt MI, Szklo M. Brazilian Longitudinal Study of Adult Health (ELSA-Brasil): objectives and design. Am J Epidemiol 2012; 175(4):315-324.. This study was approved by the ethics committees of all institutions involved, and volunteers gave written consent to participate. Further study design and cohort profile details have been given elsewhere¹⁵15 Aquino EM, Barreto SM, Bensenor IM, Carvalho MS, Chor D, Duncan BB, Lotufo PA, Mill JG, Molina Mdel C, Mota EL, Passos VM, Schmidt MI, Szklo M. Brazilian Longitudinal Study of Adult Health (ELSA-Brasil): objectives and design. Am J Epidemiol 2012; 175(4):315-324.^,1616 Schmidt MI, Duncan BB, Mill JG, Lotufo PA, Chor D, Barreto SM, Aquino EM, Passos VM, Matos SM, Molina Mdel C, Carvalho MS, Bensenor IM. Cohort profile: Longitudinal Study of Adult Health (ELSA-Brasil). Int J Epidemiol 2015; 44(1):68-75..

Of the 15105 participants of the 1st visit, 223 (1.5%) have died during the follow-up period and 868 (5.7%) did not attend the 2nd visit. All participants who declared themselves as Black or Brown and who attended both visits (n = 6100) were eligible to participate in this analysis. Brazilian indigenous (n = 145) and Asian descendent (n = 351) were excluded due to the small number of individuals, limiting the precision of estimates. Whites (n = 7258) were also not eligible, as racial discrimination primarily affects individuals of race/skin color historically stigmatized. Moreover, it is possible that racial discrimination reported by Whites (n = 64) has a different meaning and impact than that reported by Blacks/Browns¹⁷17 Cunningham TJ, Berkman LF, Gortmaker SL, Kiefe CI, Jacobs DR Jr, Seeman TE, Kawachi I. Assessment of differential item functioning in the experiences of discrimination index: the Coronary Artery Risk Development in Young Adults (CARDIA) Study. Am J Epidemiol 2011; 174(11):1266-1274..

We also excluded participants with missing data for racial discrimination (n = 11), weight (n = 39) or BMI (n = 23) and those who underwent bariatric surgery (n = 44). Thus, the final sample was composed of 5983 Black and Brown participants.

Outcome assessment

Body weight and BMI were measured at the 1st and 2nd study visits. Body weight was measured using an electronic scale with a maximum capacity of 200 kg and an accuracy of 50 g (Toledo, São Bernardo do Campo, Brazil) and height was measured using a fixed stadiometer with a precision of 0.1 cm (Seca-SE-216, Hamburg, Germany), following standard techniques¹⁸18 Mill JG, Pinto K, Griep RH, Goulart A, Foppa M, Lotufo PA, Maestri MK, Ribeiro AL, Andreão RV, Dantas EM, Oliveira I, Fuchs SC, Cunha RS, Bensenor IM. Aferições e exames clínicos realizados nos participantes do ELSA-Brasil. Rev Saude Publica 2013; 47(Supl. 2):54-62.. BMI was calculated by dividing weight (kg) by height squared (m²).

Racial discrimination

Perception of racial discrimination throughout life was assessed at the 1st visit of the study using a modified version of the Lifetime Major Events Scale¹⁹19 Williams DR, Gonzalez HM, Williams S, Mohammed SA, Moomal H, Stein DJ. Perceived discrimination, race and health in South Africa. Soc Sci Med 2008; 67(3):441-452.. This instrument measures unfair treatment in different contexts, such as public or workplaces, police stations, educational institutions and place of residence. More details of the scale have been given elsewhere⁶6 Machado AV, Camelo LV, Chor D, Griep RH, Guimarães JMN, Giatti L, Barreto SM. Racial inequality, racial discrimi-nation and obesity incidence in adults from the ELSA-Brasil cohort. J Epidemiol Community Health 2021; 75:695-701..

Respondents who reported unfair treatment in any domains motivated by race/skin color were classified in the present study as having experience of racial discrimination. A study that evaluated the reliability of this modified version of the scale in a population similar to ELSA-Brasil obtained a Kappa coefficient of 0.85 (95%CI 0.72-0.98)²⁰20 Faerstein E, Chor D, Werneck GL, Lopes CS, Kaplan G. Race and perceived racism, education, and hypertension among Brazilian civil servants: the Pró-Saúde Study. Rev Bras Epidemiol 2014; 17(Suppl. 2):81-87..

Study covariates

Variables considered in the present study were: age (considered as a categorical variable in descriptive analysis and as a continuous variable in regression models), sex, education (university degree, high school, complete elementary school and incomplete elementary school), and research center (São Paulo, Rio de Janeiro, Minas Gerais, Espírito Santo, Bahia and Rio Grande do Sul).

Data analysis

Descriptive analyzes were performed using proportions, means and standard deviation. The racial discrimination prevalence was described separately by race/skin color and according to each characteristic evaluated.

To assess whether racial discrimination predicts changes in trajectory of weight and BMI over time, we used linear mixed-effects models, which is an adequate model for analysis of unbalanced spaced longitudinal data over time²¹21 Fausto MA, Carneiro M, Antunes CMF, Pinto JA, Colosimo EA. O modelo de regressão linear misto para dados longitudinais: uma aplicação na análise de dados antropométricos desbalanceados. Cad Saude Publica 2008; 24(3):513-524.. Racial discrimination and covariates were included in the models as fixed effects, and age variation was modeled as random effect to index time. All models included random effects on the intercept and slope allowing the individual’s initial value and longitudinal trajectory to vary in relation to the average and the population trajectory²¹21 Fausto MA, Carneiro M, Antunes CMF, Pinto JA, Colosimo EA. O modelo de regressão linear misto para dados longitudinais: uma aplicação na análise de dados antropométricos desbalanceados. Cad Saude Publica 2008; 24(3):513-524.. Estimation of linear mixed effects models was made using the maximum restricted likelihood method (MLR)²²22 Cnaan A, Laird NM, Slasor P. Using the general linear mixed model to analyze unbalanced repeated measures and longitudinal data. Stat Med 1997; 16(20):2349-2380.^,2323 Diggle P, Heagerty P, Liang KY, Zeger S. Analysis of longitudinal data. Oxford: Clarendon Press; 2004..

To verify the association of racial discrimination with BMI and weight, we included in the model covariates pointed out in the literature as potential confounders of this association, such as age, sex, education and research center²⁴24 Chor D, Pereira A, Pacheco AG, Santos RV, Fonseca MJM, Schmidt MI, Duncan BB, Barreto SM, Aquino EML, Mill JG, Molina MD, Giatti L, Almeida MD, Bensenor I, Lotufo PA. Context-dependence of race self-classification: results from a highly mixed and unequal middle-income country. PLoS One 2019; 14(5):e0216653.

25 Dailey AB, Kasl SV, Holford TR, Lewis TT, Jones BA. Neighborhood and individual level socioeconomic variation in perceptions of racial discrimination. Ethn Heal 2010; 15(2):145-163.

26 Burgard S, Castiglione DP, Lin KY, Nobre AA, Aquino EML, Pereira AC, Bensenor IJM, Barreto SM, Chor D. Differential reporting of discriminatory experiences in Brazil and the United States. Cad Saude Publica 2017; 33(Suppl. 1):e00110516.

27 Williams DR, Mohammed SA. Racism and health I: pathways and scientific evidence. Am Behav Sci 2013; 57(8):1152-1173.^-2828 Williams DR, Lawrence JA, Davis BA, Vu C. Understanding how discrimination can affect health. Health Serv Res 2019; 54(Suppl. 2):1374-1388.. To assess whether racial discrimination affected the speed of weight and BMI gains with increasing age (time), we entered an interaction term between racial discrimination*age (time) in the fully adjusted models. When the interaction term was statistically significant, the predicted means of weight and BMI gains according to racial discrimination were estimated and displayed graphically. Considering previous evidences that have showed that education²⁶26 Burgard S, Castiglione DP, Lin KY, Nobre AA, Aquino EML, Pereira AC, Bensenor IJM, Barreto SM, Chor D. Differential reporting of discriminatory experiences in Brazil and the United States. Cad Saude Publica 2017; 33(Suppl. 1):e00110516. and sex⁹9 Cunningham TJ, Berkman LF, Kawachi I, Jacobs DR Jr, Seeman TE, Kiefe CI, Gortmaker SL. Changes in waist circum-ference and body mass index in the US Cardia cohort: fixed-effects associations with self-reported experiences of racial/ethnic discrimination. J Biosoc Sci 2013; 45(2):267-278.^,2929 Stroud LR, Salovey P, Epel ES. Sex differences in stress responses: social rejection versus achievement stress. Biol Psychiatry 2002; 52(4):318-327. modified the effect of racial discrimination and obesity-related outcomes, we tested the interaction between racial discrimination and sex and between racial discrimination and education. However, these interactions were not statistically significant (p > 0.05) and variables sex and education were only used for adjustment. Adjustments were retained in the models regardless of the p-value and interaction terms were retained when p-value < 0.05.

All analyzes were performed using the Stata 14.00 software (Stata Corporation, College Station, United States), considering a significance level of 5%.

Results

Median follow-up time was 3.9 years, with an interquartile range of 3.6-4.1 years. The mean age of participants was 51 years old and 54,9% were female. Of the total participants, 63.5% were Brown and 36.5% Black. Racial discrimination was reported more frequently among Blacks (32.1%) than among Browns (6.3%). The racial discrimination prevalence was higher in men and individuals with higher education in both categories of race/skin color (Table 1).

Average weight among Blacks and Browns at the first visit was 75.3kg and 73.1kg, respectively. On average, Blacks gained 1.4kg during the follow-up period and Browns gained 1.2kg. This increase was greater among those who reported discrimination when compared to those who did not report it among both Blacks (2.1kg versus 1.0kg, p < 0.001) and Browns (1.9kg versus 1.1kg, p < 0.05).

Results of mixed-effects regression models show that the experience of racial discrimination was not an independent predictor of change in the speed of weight and BMI trajectories among Brown individuals, since the interaction term between racial discrimination*age (time) was not statistically significant in this group (Table 2). Among Blacks, the interaction term between racial discrimination*age (time) was statistically significant (Table 2), showing that Blacks who reported racial discrimination had a greater and more accelerated increase in weight and BMI gains over the follow-up period than Blacks who did not report it.

At age 35, black individuals who did not report racial discrimination were, on average, 2.6kg and 0.91 kg/m² higher than those who reported racial discrimination. However, as can be seen in Figure 1, weight gain in individuals who reported racial discrimination was more accelerated, causing this difference to disappear at age 47. Subsequently, an inversion was observed and, at the age 79, black individuals who reported racial discrimination had, on average, 6.7 kg and 2.25 kg/m² greater than those who did not report racial discrimination (Figure 1).

Discussion

We found evidence that Blacks who reported racial discrimination presented a greater and more accelerated increase in weight compared to Blacks who did not report it, and this association was independent from sex, education and research center. As expected, the results for the BMI were similar, since with the change in weight there is also a change in the BMI, since the height of the individuals does not change significantly over time. However, we found no evidence that racial discrimination modifies weight or BMI trajectory among Browns over time.

Racial discrimination also predicted changes in BMI and waist circumference over 8 years of follow-up in CARDIA cohort, but only among Black women⁵5 Cozier YC, Yu J, Coogan PF, Bethea TN, Rosenberg L, Palmer JR. Racism, segregation, and risk of obesity in the black women's health study. Am J Epidemiol 2014; 179(7):875-883.. Additionally, the Black Women’s Health Study found that racial discrimination was associated with weight gain⁸8 Cozier YC, Wise LA, Palmer JR, Rosenberg L. Perceived racism in relation to weight change in the Black Women's Health Study. Ann Epidemiol 2009; 19(6):379-387. and obesity incidence⁵5 Cozier YC, Yu J, Coogan PF, Bethea TN, Rosenberg L, Palmer JR. Racism, segregation, and risk of obesity in the black women's health study. Am J Epidemiol 2014; 179(7):875-883. in Black women, but this study did not investigate such association among men. A previous study in ELSA-Brasil cohort found that obesity incidence was higher among Blacks who reported racial discrimination compared with peers who did not, but differently from the present study this association was observed only among men and women with low education⁶6 Machado AV, Camelo LV, Chor D, Griep RH, Guimarães JMN, Giatti L, Barreto SM. Racial inequality, racial discrimi-nation and obesity incidence in adults from the ELSA-Brasil cohort. J Epidemiol Community Health 2021; 75:695-701.. This apparent difference between previous results from ELSA-Brasil and our current results, may be explained by the greater baseline BMI of Blacks and Browns with low education (low education: 27.6 Mg/m² versus high education 26.8 Kg/m², p < 0,001, data not shown), placing them at greater risk to achieve the obesity cut off than individuals with higher education, plus the fact that the follow up time was relatively short (3.8 years on average).

In our study, the prevalence of perceived racial discriminations was higher in participants with high levels of education. These results are in line with evidence showing that individuals with high levels of education can perceive²⁶26 Burgard S, Castiglione DP, Lin KY, Nobre AA, Aquino EML, Pereira AC, Bensenor IJM, Barreto SM, Chor D. Differential reporting of discriminatory experiences in Brazil and the United States. Cad Saude Publica 2017; 33(Suppl. 1):e00110516. and suffer³⁰30 Figueiredo A. Fora do jogo: a experiência dos negros na classe média. Cad Pagu 2004; 23:199-228. more racial discrimination. Previous study also showed that education can interact with racial discrimination, changing the outcome in different ways⁶6 Machado AV, Camelo LV, Chor D, Griep RH, Guimarães JMN, Giatti L, Barreto SM. Racial inequality, racial discrimi-nation and obesity incidence in adults from the ELSA-Brasil cohort. J Epidemiol Community Health 2021; 75:695-701.. However, we did not find interaction between the two variables in our analysis.

We also investigated the role of racial discrimination experience in weight/BMI among Browns, as the Brazilian racial classification does not reproduce the binary division between Blacks and Whites found in other societies, such as the USA and 43% of the Brazilian population declares themselves as Brown³¹31 Instituto Brasileiro de Geografia e Estatística (IBGE). Censo Demográfico 2010: características da população e dos domicílios. Rio de Janeiro: IBGE; 2011.. Studies indicate that Browns, like Blacks, have a greater social disadvantages when compared to Whites³²32 Daflon VT, Carvalhaes F, Junior Feres J. Deeper than skin: Browns' and Blacks' perceptions of discrimination in Bra-zil. Dados Rev Ciências Sociais 2017; 60(2):293-330.. However, racial discrimination did not predict greater speed of weight and BMI gains among Browns in the present study, corroborating our previous findings that also failed to identify an association between perceived discrimination and obesity incidence among Browns. This finding may be related to the much lower prevalence of racial discrimination among Browns (6.3%) as compared to Blacks (32.1%).

According to the ecosocial theory of Nancy Krieger³³33 Krieger N. Methods for the scientific study of discrimination and health: an ecosocial approach. Am J Public Health 2012; 102(5):936-945., individuals exposed to structural and interpersonal racism can biologically incorporate exposures arising from that specific ecological and social contexts in which they live, explaining the racial inequality in weight trajectories across time. The structural racism generates inequalities in the distribution of resources, and life opportunities, since it operates in all individual’s life levels in a connected way²⁸28 Williams DR, Lawrence JA, Davis BA, Vu C. Understanding how discrimination can affect health. Health Serv Res 2019; 54(Suppl. 2):1374-1388.. The concomitant exposure to adverse social contexts and to interpersonal racism can increase the stress load²⁸28 Williams DR, Lawrence JA, Davis BA, Vu C. Understanding how discrimination can affect health. Health Serv Res 2019; 54(Suppl. 2):1374-1388., which will activate physiological adaptations in the nervous, endocrine and immune systems and trigger pro-inflammatory responses³⁴34 McEwen BS. Brain on stress: how the social environment gets under the skin. Proc Natl Acad Sci 2012; 109(Suppl. 2):17180-17185.. For example, the exposure to stress is related to increase in cortisol and other pro-inflammatory markers as a result of hyperactivity of the hypothalamic-pituitary-adrenal axis, leading to a chronic inflammatory state³⁵35 van der Valk ES, Savas M, van Rossum EFC. Stress and obesity: are there more susceptible individuals? Curr Obes Rep 2018; 7(2):193-203.. This chronic inflammation is related to fat accumulation in the abdominal region and increased appetite, generating a greater preference for consumption of caloric foods³⁵35 van der Valk ES, Savas M, van Rossum EFC. Stress and obesity: are there more susceptible individuals? Curr Obes Rep 2018; 7(2):193-203..

We must emphasize that the ELSA-Brasil population has a higher average income and education level than the general Brazilian population. It is known that individuals with higher education may have greater perception of racial discrimination than those with lower education²⁶26 Burgard S, Castiglione DP, Lin KY, Nobre AA, Aquino EML, Pereira AC, Bensenor IJM, Barreto SM, Chor D. Differential reporting of discriminatory experiences in Brazil and the United States. Cad Saude Publica 2017; 33(Suppl. 1):e00110516.. However, a representative study of the Brazilian population aged 16 or over³²32 Daflon VT, Carvalhaes F, Junior Feres J. Deeper than skin: Browns' and Blacks' perceptions of discrimination in Bra-zil. Dados Rev Ciências Sociais 2017; 60(2):293-330. found greater prevalence of racial discrimination than the observed in ELSA-Brasil baseline. Thus, if the reporting of racial discrimination is underestimated in this study in relation to the Brazilian population, this would cause a dilution in the estimated associations, as some exposed individuals would be misclassified as not exposed, leading to a reduction in the magnitudes of the observed associations with weight and BMI gains herein. In addition, as we chose to continuously assess weight gain and BMI over time, our study does not make it possible to assess how racial discrimination influences the change in the classification of the weight status of individuals, that is, it is not possible to indicate by this study if racial discrimination influences an increase in the prevalence and incidence of obesity. However, weight gain can have negative repercussions for health even when the individual does not reach the cutoff point that characterizes obesity¹⁴14 Zheng Y, Manson JE, Yuan C, Liang MH, Grodstein F, Stampfer MJ, Willett WC, Hu FB. Associations of weight gain from early to middle adulthood with major health outcomes later in life. J Am Med Assoc 2017; 318(3):255-269..

Our results are important for a better understanding of the complex relationships between racial discrimination and obesity, and reinforce the evidence that racial discrimination can be an important component of persistent racial inequality in health. The knowledge generated by this work add evidences that support the development of actions seeking to reduce racial inequalities, such as the expansion of affirmative action policies and the development of other public policies to promote equity. Besides, these results prompt the need of expanding access to quality health services of Blacks and Browns, an essential ingredient to reduce racial inequalities in health in Brazil.

Acknowledgements

We thank all ELSA-Brasil participants for their invaluable contribution to this study.

References

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