Social Science & Medicine 116 (2014) 251e252
Contents lists available at ScienceDirect
Social Science & Medicine journal homepage: www.elsevier.com/locate/socscimed
Commentary
Skin color, interviewer-ascribed ethnoracial classification, racial/ ethnic self-identification & discrimination: Commentary on Perreira and Telles (2014) Kasim Ortiz Vanderbilt University, Department of Sociology, PMB 351811, Nashville, TN 37235-1811, USA
a r t i c l e i n f o Article history: Received 1 July 2014 Accepted 5 July 2014 Available online 6 July 2014 Keywords: Racial/ethnic identification Discrimination Skin tone Latin American populations
The recently accepted manuscript in Social Science and Medicine, Perreira and Telles (2014), employed the 2010 Project on Ethnicity and Race in Latin American (PERLA) data to examine associations between skin color, ethnoracial classification and discrimination among Latin American populations. Of particular interest were understanding differences in discrimination based upon skin tone, self-reported race/ethnicity, and interviewer ascribed race/ethnicity in explaining self-rated health among Latino Americans adults (ages 18e65). In addition the authors examine associations of observer-ascribed skin color with perceived skin color discrimination, class discrimination, and socioeconomic status. The paper makes an important contribution to the wealth of research on discrimination and consequent health outcomes by addressing the fundamental question: how does skin tone explain the relationship between discrimination and health among Latin American populations in developing nations? To investigate these relationships the authors utilize a series of logistic regression models testing for moderating effects to distinguish between the various forms of discrimination and racial/ethnic identification. The authors find a strong gradient in health by skin color, which remained after adjusting for both self-identification of race/ethnicity as well as interviewer ascribed race/ethnicity. Yet
DOI of original article: http://dx.doi.org/10.1016/j.socscimed.2014.05.054. E-mail addresses: [email protected], [email protected]. http://dx.doi.org/10.1016/j.socscimed.2014.07.013 0277-9536/© 2014 Elsevier Ltd. All rights reserved.
after adjusting for skin color, self-identified race/ethnicity had no relationship with self-rated health. Thus, leading the authors to conclude that their findings suggest that ethnoracial selfidentifications do not mediate the influence of skin color on health. The innovative theoretical and methodological advancement supplied by Perreira and Telles (2014) calls into question whether we are actually capturing racism and the effects of discrimination on health most sufficiently in our so called “postracial” America (Harris and Lieberman, 2013; Hughey, 2014). This research inevitably raises the important question, how can we reconcile the conclusions of Perreira and Telles (2014) with evidence in existing studies? 1. Discrimination & racial/ethnic classification: theoretical linkages I agree with Perreira and Telles (2014) that measurement of race/ethnicity should be guided by strong theoretical considerations. The authors argue that such measurements should take into consideration the personal cultural associations of individuals in self-identifying with a particular race/ethnicity while simultaneously capturing social dimensions that shape identification. To address this potential theoretical linkage we can ask another fundamental question: how does the social construction of race/ ethnicity influence self-identification with a particular race and/or ethnicity? Jones (2000, 2002) argues that race should be formally understood as a social construct that shapes life opportunities based upon how one looks which ultimately influences health. More pointedly, Jones et al. (2008) argue and demonstrate the usefulness of utilizing a measurement that captures socially ascribed race/ethnicity as a tool in elucidating the effects of racism on health. Perreira and Telles (2014) outline the socio-historical development of racial classification within Latin American countries whereby census enumerators often were tasked with determining racial distinctions. Through political processes advocating social mixing, increasing identifications with Afro-descent identities, and inconsistent heterogeneity in racial/ethnic self-identification individually, disentangling racial classification and consequent health
252
K. Ortiz / Social Science & Medicine 116 (2014) 251e252
effects have become increasingly difficult among Latin American populations (Telles and Flores, 2013). Similarly in U.S. contexts, sociology theorist of race scholarship have utilized the term colorblind racism to signify changes in race relations whereby explicitly identifying racism has become increasingly difficult (Bonilla-Silva, 1997, 2004, 2006; Bonilla-Silva et al., 2004; Burton et al., 2010). Colorblind scholarship has focused a great deal of attention to the ways in which race and racism have changed predicated upon dominant cultural perceptions structurally. Also this scholarship evokes how those within minority populations are also explicitly and sometimes implicitly assigning varying social constructions to race and ethnicity as well. The culmination of these changing dynamics makes it even more difficult to measure the health effects of racism. A major contribution of Perreira and Telles (2014) work is that they utilize a myriad of measures for ascertaining racial/ethnic identification. Their deployment of interviewer ascribed race/ ethnicity and self-identification of racial/ethnicity provides a multifaceted approach in measurements for illuminating the effects of discrimination on health, in conjunction with skin tone variation. Much more efforts as such are needed as dynamics of race, race relations, and consequent racism are continuously changing that warrant health measurements that can most efficiently help us best understand how to capture the social conditioning of race and ethnicity. 2. Methodological advancements Within their study Perreira and Telles (2014) also make use of a wealth index that captures expenditure-based economic indicators instead of income-based economic indicators, highlighting its' sardova, 2009; McKenzie, 2005). liency for developing nations (Co Again, this methodological innovation more broadly captures socioeconomic status (SES), aligning itself with a multidimensional poverty index approach (Battiston et al., 2013). The measurement details found in the supplementary materials of the manuscript uniquely identify the usefulness of this approach to SES that could have relevance in developed nations as well. For example, a considerable amount of attention in the U.S. has been given to cumulative disadvantage and SES gradients in explaining health (Ferraro and Shippee, 2009; Ferraro et al., 2006; Frank et al., 2003). However, such measurements of SES often rely on income-based economic indicators which may underestimate the gross effect of wealth and/or poverty comprehensively on health. Health datasets within the U.S. that include measures for expenditure-based economic indicators are not as vastly used. However, the contribution of this paper highlights greater need for more comprehensive measurements of SES to further illuminate wealth and poverty effects on health. 3. Concluding remarks Indeed, Perreira and Telles (2014) contribution to the scholarship on discrimination and health is highly warranted. Adopting
the multifaceted approach in racial/ethnic identification might solicit more nuanced understanding of the effects of discrimination on health. Particularly, studies that deploy skin tone measures might unmask difficulty in capturing discrimination in colorblind societies. Moreover, the contribution of the wealth index again suggests more nuanced approaches within developed nations might produce greater understanding of SES gradients on health. Most importantly, the contribution of Perreira and Telles (2014) provides much needed clarification to an understudied phenomena of discrimination and health within developing Latin American nations. Their work could encourage even more research in U.S. contexts per Latino populations in elucidating health effects of discrimination via utilization of skin tone measurements. Ethics statement Ethics approval was not needed for this manuscript as it did not include human subjects research. References Battiston, D., Cruces, G., Lopez-Calva, L.F., Lugo, M.A., Santos, M.E., 2013. Income and beyond: multidimensional poverty in six Latin American countries. Soc. Indic. Res. 112, 291e314. Bonilla-Silva, E., 1997. Rethinking racism: toward a structural interpretation. Am. Sociol. Rev., 465e480. Bonilla-Silva, E., 2004. From bi-racial to tri-racial: towards a new system of racial stratification in the USA. Ethn. Racial Stud. 27, 931e950. Bonilla-Silva, E., 2006. Racism Without Racists: Color-blind Racism and the Persistence of Racial Inequality in the United States. Rowman & Littlefield Publishers. Bonilla-Silva, E., Lewis, A., Embrick, D., 2004. “I did not get that job because of a black man…”: the story lines and testimonies of color-blind racism. Sociol. Forum 19, 555e581. Burton, L.M., Bonilla-Silva, E., Ray, V., Buckelew, R., Hordge Freeman, E., 2010. Critical race theories, colorism, and the decade's research on families of color. J. Marriage Fam. 72, 440e459. rdova, A., 2009. Methodological Note: Measuring Relative Wealth Using HouseCo hold Asset Indicators. Insights Series No. I0806. Ferraro, K.F., Shippee, T.P., 2009. Aging and cumulative inequality: how does inequality get under the skin? Gerontologist 49, 333e343. Ferraro, K.F., Thorpe, R.J., McCabe, G.P., Kelley-Moore, J.A., Jiang, Z., 2006. The color of hospitalization over the adult life course: cumulative disadvantage in black and white? J. Gerontol. Ser. B Psychol. Sci. Soc. Sci. 61, S299eS306. Frank, J.W., Cohen, R., Yen, I., Balfour, J., Smith, M., 2003. Socioeconomic gradients in health status over 29 years of follow-up after midlife: the Alameda county study. Soc. Sci. Med. 57, 2305e2323. Harris, F.C., Lieberman, R.C., 2013. Beyond Discrimination: Racial Inequality in a Post-racist Era. Russell Sage Foundation. Hughey, M.W., 2014. White backlash in the ‘post-racial’ United States. Ethn. Racial Stud. 37, 721e730. Jones, C., 2000. Levels of racism: a theoretic framework and a gardener's tale. Am. J. Public Health 90, 1212e1215. Jones, C.P., 2002. Confronting institutionalized racism. Phylon, 7e22. Jones, C.P., Truman, B.I., Elam-Evans, L.D., Jones, C.A., Jones, C.Y., Jiles, R., et al., 2008. Using “socially assigned race” to probe white advantages in health status. Ethn. Dis. 18, 496e504. McKenzie, D.J., 2005. Measuring inequality with asset indicators. J. Popul. Econ. 18, 229e260. Perreira, K.M., Telles, E.E., 2014. The color of health: skin color, ethnoracial classification, and discrimination in the health of Latin Americans. Soc. Sci. Med.. Telles, E., Flores, R., 2013. Not just color: whiteness, nation, and status in Latin America. Hispanic Am. Hist. Rev. 93, 411e449.
Contents lists available at ScienceDirect
Social Science & Medicine journal homepage: www.elsevier.com/locate/socscimed
Commentary
Skin color, interviewer-ascribed ethnoracial classification, racial/ ethnic self-identification & discrimination: Commentary on Perreira and Telles (2014) Kasim Ortiz Vanderbilt University, Department of Sociology, PMB 351811, Nashville, TN 37235-1811, USA
a r t i c l e i n f o Article history: Received 1 July 2014 Accepted 5 July 2014 Available online 6 July 2014 Keywords: Racial/ethnic identification Discrimination Skin tone Latin American populations
The recently accepted manuscript in Social Science and Medicine, Perreira and Telles (2014), employed the 2010 Project on Ethnicity and Race in Latin American (PERLA) data to examine associations between skin color, ethnoracial classification and discrimination among Latin American populations. Of particular interest were understanding differences in discrimination based upon skin tone, self-reported race/ethnicity, and interviewer ascribed race/ethnicity in explaining self-rated health among Latino Americans adults (ages 18e65). In addition the authors examine associations of observer-ascribed skin color with perceived skin color discrimination, class discrimination, and socioeconomic status. The paper makes an important contribution to the wealth of research on discrimination and consequent health outcomes by addressing the fundamental question: how does skin tone explain the relationship between discrimination and health among Latin American populations in developing nations? To investigate these relationships the authors utilize a series of logistic regression models testing for moderating effects to distinguish between the various forms of discrimination and racial/ethnic identification. The authors find a strong gradient in health by skin color, which remained after adjusting for both self-identification of race/ethnicity as well as interviewer ascribed race/ethnicity. Yet
DOI of original article: http://dx.doi.org/10.1016/j.socscimed.2014.05.054. E-mail addresses: [email protected], [email protected]. http://dx.doi.org/10.1016/j.socscimed.2014.07.013 0277-9536/© 2014 Elsevier Ltd. All rights reserved.
after adjusting for skin color, self-identified race/ethnicity had no relationship with self-rated health. Thus, leading the authors to conclude that their findings suggest that ethnoracial selfidentifications do not mediate the influence of skin color on health. The innovative theoretical and methodological advancement supplied by Perreira and Telles (2014) calls into question whether we are actually capturing racism and the effects of discrimination on health most sufficiently in our so called “postracial” America (Harris and Lieberman, 2013; Hughey, 2014). This research inevitably raises the important question, how can we reconcile the conclusions of Perreira and Telles (2014) with evidence in existing studies? 1. Discrimination & racial/ethnic classification: theoretical linkages I agree with Perreira and Telles (2014) that measurement of race/ethnicity should be guided by strong theoretical considerations. The authors argue that such measurements should take into consideration the personal cultural associations of individuals in self-identifying with a particular race/ethnicity while simultaneously capturing social dimensions that shape identification. To address this potential theoretical linkage we can ask another fundamental question: how does the social construction of race/ ethnicity influence self-identification with a particular race and/or ethnicity? Jones (2000, 2002) argues that race should be formally understood as a social construct that shapes life opportunities based upon how one looks which ultimately influences health. More pointedly, Jones et al. (2008) argue and demonstrate the usefulness of utilizing a measurement that captures socially ascribed race/ethnicity as a tool in elucidating the effects of racism on health. Perreira and Telles (2014) outline the socio-historical development of racial classification within Latin American countries whereby census enumerators often were tasked with determining racial distinctions. Through political processes advocating social mixing, increasing identifications with Afro-descent identities, and inconsistent heterogeneity in racial/ethnic self-identification individually, disentangling racial classification and consequent health
252
K. Ortiz / Social Science & Medicine 116 (2014) 251e252
effects have become increasingly difficult among Latin American populations (Telles and Flores, 2013). Similarly in U.S. contexts, sociology theorist of race scholarship have utilized the term colorblind racism to signify changes in race relations whereby explicitly identifying racism has become increasingly difficult (Bonilla-Silva, 1997, 2004, 2006; Bonilla-Silva et al., 2004; Burton et al., 2010). Colorblind scholarship has focused a great deal of attention to the ways in which race and racism have changed predicated upon dominant cultural perceptions structurally. Also this scholarship evokes how those within minority populations are also explicitly and sometimes implicitly assigning varying social constructions to race and ethnicity as well. The culmination of these changing dynamics makes it even more difficult to measure the health effects of racism. A major contribution of Perreira and Telles (2014) work is that they utilize a myriad of measures for ascertaining racial/ethnic identification. Their deployment of interviewer ascribed race/ ethnicity and self-identification of racial/ethnicity provides a multifaceted approach in measurements for illuminating the effects of discrimination on health, in conjunction with skin tone variation. Much more efforts as such are needed as dynamics of race, race relations, and consequent racism are continuously changing that warrant health measurements that can most efficiently help us best understand how to capture the social conditioning of race and ethnicity. 2. Methodological advancements Within their study Perreira and Telles (2014) also make use of a wealth index that captures expenditure-based economic indicators instead of income-based economic indicators, highlighting its' sardova, 2009; McKenzie, 2005). liency for developing nations (Co Again, this methodological innovation more broadly captures socioeconomic status (SES), aligning itself with a multidimensional poverty index approach (Battiston et al., 2013). The measurement details found in the supplementary materials of the manuscript uniquely identify the usefulness of this approach to SES that could have relevance in developed nations as well. For example, a considerable amount of attention in the U.S. has been given to cumulative disadvantage and SES gradients in explaining health (Ferraro and Shippee, 2009; Ferraro et al., 2006; Frank et al., 2003). However, such measurements of SES often rely on income-based economic indicators which may underestimate the gross effect of wealth and/or poverty comprehensively on health. Health datasets within the U.S. that include measures for expenditure-based economic indicators are not as vastly used. However, the contribution of this paper highlights greater need for more comprehensive measurements of SES to further illuminate wealth and poverty effects on health. 3. Concluding remarks Indeed, Perreira and Telles (2014) contribution to the scholarship on discrimination and health is highly warranted. Adopting
the multifaceted approach in racial/ethnic identification might solicit more nuanced understanding of the effects of discrimination on health. Particularly, studies that deploy skin tone measures might unmask difficulty in capturing discrimination in colorblind societies. Moreover, the contribution of the wealth index again suggests more nuanced approaches within developed nations might produce greater understanding of SES gradients on health. Most importantly, the contribution of Perreira and Telles (2014) provides much needed clarification to an understudied phenomena of discrimination and health within developing Latin American nations. Their work could encourage even more research in U.S. contexts per Latino populations in elucidating health effects of discrimination via utilization of skin tone measurements. Ethics statement Ethics approval was not needed for this manuscript as it did not include human subjects research. References Battiston, D., Cruces, G., Lopez-Calva, L.F., Lugo, M.A., Santos, M.E., 2013. Income and beyond: multidimensional poverty in six Latin American countries. Soc. Indic. Res. 112, 291e314. Bonilla-Silva, E., 1997. Rethinking racism: toward a structural interpretation. Am. Sociol. Rev., 465e480. Bonilla-Silva, E., 2004. From bi-racial to tri-racial: towards a new system of racial stratification in the USA. Ethn. Racial Stud. 27, 931e950. Bonilla-Silva, E., 2006. Racism Without Racists: Color-blind Racism and the Persistence of Racial Inequality in the United States. Rowman & Littlefield Publishers. Bonilla-Silva, E., Lewis, A., Embrick, D., 2004. “I did not get that job because of a black man…”: the story lines and testimonies of color-blind racism. Sociol. Forum 19, 555e581. Burton, L.M., Bonilla-Silva, E., Ray, V., Buckelew, R., Hordge Freeman, E., 2010. Critical race theories, colorism, and the decade's research on families of color. J. Marriage Fam. 72, 440e459. rdova, A., 2009. Methodological Note: Measuring Relative Wealth Using HouseCo hold Asset Indicators. Insights Series No. I0806. Ferraro, K.F., Shippee, T.P., 2009. Aging and cumulative inequality: how does inequality get under the skin? Gerontologist 49, 333e343. Ferraro, K.F., Thorpe, R.J., McCabe, G.P., Kelley-Moore, J.A., Jiang, Z., 2006. The color of hospitalization over the adult life course: cumulative disadvantage in black and white? J. Gerontol. Ser. B Psychol. Sci. Soc. Sci. 61, S299eS306. Frank, J.W., Cohen, R., Yen, I., Balfour, J., Smith, M., 2003. Socioeconomic gradients in health status over 29 years of follow-up after midlife: the Alameda county study. Soc. Sci. Med. 57, 2305e2323. Harris, F.C., Lieberman, R.C., 2013. Beyond Discrimination: Racial Inequality in a Post-racist Era. Russell Sage Foundation. Hughey, M.W., 2014. White backlash in the ‘post-racial’ United States. Ethn. Racial Stud. 37, 721e730. Jones, C., 2000. Levels of racism: a theoretic framework and a gardener's tale. Am. J. Public Health 90, 1212e1215. Jones, C.P., 2002. Confronting institutionalized racism. Phylon, 7e22. Jones, C.P., Truman, B.I., Elam-Evans, L.D., Jones, C.A., Jones, C.Y., Jiles, R., et al., 2008. Using “socially assigned race” to probe white advantages in health status. Ethn. Dis. 18, 496e504. McKenzie, D.J., 2005. Measuring inequality with asset indicators. J. Popul. Econ. 18, 229e260. Perreira, K.M., Telles, E.E., 2014. The color of health: skin color, ethnoracial classification, and discrimination in the health of Latin Americans. Soc. Sci. Med.. Telles, E., Flores, R., 2013. Not just color: whiteness, nation, and status in Latin America. Hispanic Am. Hist. Rev. 93, 411e449.
