This reading assignment included the article “Racial disparities in renal function: the role of racial discrimination. The Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)” by Camelo et al. (2018). In this scientific article, the authors aimed to investigate the relationship between the racial discrimination experienced by respondents and estimated glomerular filtration rates (eGFR). It is worth clarifying that eGFR is a measure of kidney function: a low eGFR indicates that the intensity of kidney function is impaired, and, as a result, there are severe threats to the development of chronic kidney disease. The authors used data from a longitudinal study from ELSA-Brasil for the study, and the final sample size was 14,355 participants after removing respondents who did not fit the sampling criteria. This was mainly for the removal of those participants who were indigenous or had no eGFR data. The mean age for white participants (n = 7771) was 52.5; for brown participants (n = 4191), it was 51.7, and finally, 51.8 was the mean age for black respondents.
The article “Identifying and Avoiding Bias in Research” by Pannucci & Wilkins (2010) describes several forms of bias that scientists may encounter when conducting academic research; some of which are applicable to this paper from Camelo et al. Specifically, the sample collected included skilled workers employed in Brazilian universities. Obviously, such respondents have higher incomes and may face a different amount of racial discrimination than the non-intellectual task population. In addition, the data themselves may be biased for the current agenda: the data were collected during 2008-2010, while only being accepted for analysis in 2018 when the article by Camelo et al. was released. In the ten years between data collection and processing, the public agenda regarding racial discrimination may have changed. As a consequence, results published as early as 2018 may not be relevant because they are based on outdated data.
The Camelo et al. paper makes some interesting findings that shed light on the link between racial discrimination and eGFR. The authors report that “mean eGFR differences between Black and White individuals were reduced by 31% when exposure to racial discrimination was taken into account” (Camelo et al., 2018). It follows that racial discrimination is a statistically significant (p <.05) predictor of the effect on eGFR. As the authors additionally show, eGFR was lower in blacks, and perceptions of racial discrimination were significantly higher — that is, racial discrimination did negatively affect kidney performance and could be predictors of the development of chronic kidney disease. Another interesting finding was that among black respondents, claims of experiencing racial discrimination in their direction dropped 11.4 percentage points when moving from the 55-64 age group to the 65-74 group. Two different conclusions may follow from this: on the one hand, it may indicate that the perception of racial discrimination decreases as age increases, that is, older Black people experience less pressure from racial discrimination. Another interpretation of this result is that older black respondents actually experience less discrimination in their lives than their younger counterparts.
This paper has demonstrated a surprising relationship between racial discrimination and the effect on kidney performance. The surprising thing about the findings is that the article was able to show how discrimination has a practical effect on body condition, which means that it is not just the kidneys that can be expected to be vulnerable in those respondents who regularly experience discrimination on the basis of their background. It does seem appalling that such immoral behavior by society affects not only the mental well-being but also the physiological characteristics of individuals.
References
Camelo, L. V., Giatti, L., Ladeira, R. M., Griep, R. H., Mill, J. G., Chor, D., & Barreto, S. M. (2018). Racial disparities in renal function: the role of racial discrimination. The Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). The Journal of Epidemiology and Community Health, 72(11), 1027-1032. Web.
Pannucci, C. J., & Wilkins, E. G. (2010). Identifying and avoiding bias in research. Plastic and Reconstructive Surgery, 126(2), 619-625. Web.
