Black-White Achievement Gap: Role of Race, School Urbanity, and Parental Education

A dual-focus approach for evaluating contributors to chronic pain: The roles of psychosocial risk and resilience factors

There has been a predominant focus on psychosocial risk factors associated with poor pain outcomes among individuals with chronic pain. However, it is also important to identify resilience factors that may mitigate the negative impact of or confer successful adaptation to pain. We argue for a dual-focus approach that evaluates the contributions of both risk and resilience factors. Person-centered statistical techniques (cluster analysis) may be beneficial to phenotype individuals based on their psychosocial characteristics to help inform treatment selection. Identifying treatment moderators based on individual-level characteristics (race/ethnicity) may provide insight into differences in treatment efficacy. Utilizing a holistic approach can inform the development and implementation of culturally adapted and personalized treatments aimed at reducing risk and bolstering resilience factors.

Diversity-aware Population Models: Quantifying Associations between Socio-Spatial Factors and Cognitive Development in the ABCD Cohort

Population-level analyses are inherently complex due to a myriad of latent confounding effects that underlie the interdisciplinary topics of research interest. Despite the mounting demand for generative population models, the limited generalizability to underrepresented groups hinders their widespread adoption in downstream applications. Interpretability and reliability are essential for clinicians and policymakers, while accuracy and precision are prioritized from an engineering standpoint. Thus, in domains such as population neuroscience, the challenge lies in determining a suitable approach to model population data effectively. Notably, the traditional strata-agnostic nature of existing methods in this field reveals a pertinent gap in quantitative techniques that directly capture major sources of population stratification. The emergence of population-scale cohorts, like the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study, provides unparalleled opportunities to explore and characterize neurobehavioral and sociodemographic relationships comprehensively. We propose diversity-aware population modeling, a framework poised to standardize systematic incorporation of diverse attributes, structured with respect to intrinsic population stratification to obtain holistic insights. Here, we leverage Bayesian multilevel regression and poststratification, to elucidate inter-individual differences in the relationships between socioeconomic status (SES) and cognitive development. We constructed 14 varying-intercepts and varying-slopes models to investigate 3 cognitive phenotypes and 5 sociodemographic variables (SDV), across 17 US states and 5 race subgroups. SDVs exhibited systemic socio-spatial effects that served as fundamental drivers of variation in cognitive outcomes. Low SES was disproportionately associated with cognitive development among Black and Hispanic children, while high SES was a robust predictor of cognitive development only among White and Asian children, consistent with the minorities' diminished returns (MDRs) theory. Notably, adversity-susceptible subgroups demonstrated an expressive association with fluid cognition compared to crystallized cognition. Poststratification proved effective in correcting group attribution biases, particularly in Pennsylvania, highlighting sampling discrepancies in US states with the highest percentage of marginalized participants in the ABCD Study©. Our collective analyses underscore the inextricable link between race and geographic location within the US. We emphasize the importance of diversity-aware population models that consider the intersectional composition of society to derive precise and interpretable insights across applicable domains.

Immigration Status, Socioeconomic Status, and Self-Rated Health in Europe

The literature has established a protective effect of socioeconomic status (SES) indicators on health. However, at least in the US, these SES indicators tend to generate fewer health gains for marginalized groups including immigrants. As this literature mainly originated in the US, it is necessary to study whether these indicators similarly correlate with the health of foreign-born and native-born individuals in Europe. The current study was based on the Marginalization-related Diminished Returns (MDRs) theory and compared the effects of three SES indicators, namely parental education, own education and income, on self-rated health (SRH) of immigrant and native-born individuals. We used data from the European Social Survey 2020 (ESS 2020). Participants included 14,213 individuals who identified as either native-born (n = 9052) or foreign-born (n = 508). Education, income, and parental education were the independent variables. Self-rated health (SRH) was the outcome. Age and sex were covariates. Linear regression and logistic regression were used for data analysis. Overall, high education, income, and parental education were associated with lower odds of poor SRH. We documented a statistical interaction between immigration status and parental education, indicating a weaker inverse association between parental education and poor SRH for foreign-born than native-born individuals. The links between some but not all SES indicators vary across foreign-born and native-born individuals in Europe. Host countries seem to undervalue the parental educational attainment of foreign-born families. Future research should explore the role of time, period, cohort and country of origin as well as host country and associated policies in equalizing returns of SES indicators on the health of population subgroups. The results are important given that most studies on MDRs are developed in the US, and less is known about Europe. The results are also very important given the growing anti-immigrant sentiment and nationalist movements in Europe and the rest of the world.

Variations in the association between education and self-reported health by race/ethnicity and structural racism

Research has documented a longstanding association between education achievement and physical health outcomes. However, research has suggested that the health benefits gained from education differ by race, with minoritized racial groups generally experiencing poorer health and fewer health benefits from education. One potential explanation for this phenomena of “diminished returns” is the influence of structural racism. The purpose of this paper is to assess how structural factors at the state level are associated with self-reported health and the association between education and health. Utilizing a sample (N = 6819) from the NLSY dataset, measures of structural racism (political participation, employment and job status, education attainment and judicial treatment) were used to assess the hypotheses. Results indicated significant differences in key areas, with some nuanced findings – indicating that structural racism is an important health factor. These indicators of structural racism are discussed in the context of complexity of linked lives. Further research regarding structural racism, education, health and developmental stages is warranted.

Parental Education and Children’s Sleep Problems: Minorities’ Diminished Returns

Background and aims: While increased parental education reduces children’s sleep problems, less is known about racial variation in such protection. According to Minorities’ Diminished Returns (MDRs) theory, economic resources such as parental education show weaker health effects for minority groups such as Blacks and Latinos than non-Latino Whites, which is due to racism and social stratification. In this study, we investigated the association between parental education and children’s sleep problems, as a proxy of sleep problems, by race. Methods: This cross-sectional study included 11718 American children aged 9-10. All participants were recruited to the Adolescent Brain Cognitive Development (ABCD) study. The independent variable was parental education, a five-level nominal variable. The dependent variable – sleep problems, was a continuous variable. Race/ethnicity was the effect modifier. Age, sex, and marital status were the covariates. Mixed-effects regression models were used for data analysis. Results: Parental education was associated with children’s sleep problems. However, there was a weaker inverse association seen in non-Latino Black and Latino families compared to non-Latino White families. This was documented by a significant statistical interaction between race and ethnicity and parental education on children’s sleep problems. Conclusion: Diminished protective effect of parental education on children’s sleep problems for non-Latino Black and Latino families compared to non-Latino White families is similar to the MDRs in other domains. Worse than expected sleep may contribute to higher-than-expected health risks of middle-class Black and Latino children.