Biogeographic Ancestry, Cognitive Ability and Socioeconomic Outcomes

Abstract

The cause(s) of ubiquitous cognitive differences between American self-identified racial/ethnic groups (SIREs) is uncertain. Evolutionary-genetic models posit that ancestral genetic selection pressures are the ultimate source of these differences. Conversely, sociological models posit that these differences result from racial discrimination. To examine predictions based on these models, we conducted a global admixture analysis using data from the Pediatric Imaging, Neurocognition, and Genetics Study (PING; N = 1,369 American children). Specifically, we employed a standard methodology of genetic epidemiology to determine whether genetic ancestry significantly predicts cognitive ability, independent of SIRE. In regression models using four different codings for SIRE as a covariate, we found incremental relationships between genetic ancestry and both general cognitive ability and parental socioeconomic status (SES). The relationships between global ancestry and cognitive ability were partially attenuated when parental SES was added as a predictor and when cognitive ability was the outcome. Moreover, these associations generally held when subgroups were analyzed separately. Our results are congruent with evolutionary-genetic models of group differences and with certain environmental models that mimic the predictions of evolutionary-genetic ones. Implications for research on race/ethnic differences in the Americas are discussed, as are methods for further exploring the matter.

Research Practices in Differential Psychology: Comments and a Correction to Winston

“…Nisbett [40] for example, argued, based on a rather selective review of 20th century studies, that admixture research constitutes direct evidence against Rushton and Jensen's hereditary hypothesis. However, we showed, using self-reported data, phenotype, and modern genetic methods, that the results conform to Rushton and Jensen's prediction [41,42]; though, we do not consider this direct evidence either way. However, Nisbett at least attempted to address the empirical issues.…”

The Effect of Biracial Status and Color on Crystallized Intelligence in the U.S.-Born African–European American Population

“…While self-reported mixed-race status need not correspond with intermediate genetic admixture, it happens to in the case of U.S. self-identifying biracial Black-White individuals (e.g., [30], Table 3). Given the results, the most parsimonious explanation is that European genetic ancestry correlates with cognitive ability among self-identifying African Americans, as found by Kirkegaard et al (2019) [28]. This interpretation is consistent with a large number of-though not all-older studies [6] and with studies on the relation between genetic ancestry and individual SES [8].…”

“…While some have argued that effect sizes between rs = 0.10 and 0.20 are inconsistent with the hypothesis of a large effect associated with ancestry [26,27], this is incorrect. As Kirkegaard, Woodley of Menie, Williams, Fuerst, and Meisenberg (2019) demonstrated, the expected correlation between a good measure of genetic ancestry and trait would be small for the given population owing to restriction of the range in ancestry [28]. Any reduction in validity of the measure of ancestry would further bias the association with ancestry towards zero.…”

Linear and partially linear models of behavioral trait variation using admixture regression

“…Descriptive statistics for the SIRE groups are shown in Table S1 The racial and ethnic variables were then recoded to create interval categories for which individuals are assigned a percentage of each SIRE category based on the number of responses chosen (Liebler & Halpern-Manners, 2008;Kirkegaard et al, 2019). By this coding, if someone was marked as White and Hispanic, they were assigned scores of .5 for white and .5 for Hispanic and 0 for the Socioeconomic status was based on seven indicators: financial adversity, area deprivation index, neighborhood safety protocol, parental education, parental income, parental marital status, and parental employment status.…”

“…From this we created an additional ethnic category. The racial and ethnic variables were then recoded to create interval categories for which individuals are assigned a percentage of each SIRE category based on the number of responses chosen (Liebler & Halpern-Manners, 2008;Kirkegaard et al, 2019). By this coding, if someone was marked as White and Hispanic, they were assigned scores of .5 for white and .5 for Hispanic and 0 for the other 5 categories.…”