Stronger Association between Nucleus Accumbens Density and Body Mass Index in Low-Income and African American Children

Background: The nucleus accumbens’ (NAc) size, function, and density influence individuals’ body mass index (BMI). However, little is known about racial and socioeconomic status (SES) differences in the role of NAc density as a predictor of childhood BMI. Objectives: We used the Adolescent Brain Cognitive Development (ABCD) data to investigate racial and SES differences in the effect of NAc density on childhood BMI. Methods: This cross-sectional study included 9497 children between ages 9 and 10. Mixed-effects regression models were used to analyze the data. The predictor variable was NAc density measured using diffusion MRI (dMRI). The outcome variable was BMI, operationalized as a continuous variable. Covariates included sex, age, ethnicity, family structure, and parental education. Race (White, African American, Asian, and Other/mixed) and household income (< 50k, 50-100 k, and 100+ k) were the moderators. Results: High NAc diffusion tension (density) was predictive of higher BMI, net of covariates. However, the positive association between NAc density and BMI was stronger in African Americans than in White, and in low-income than in high-income children. Conclusions: Our findings suggest that although high NAc has implications for children’s BMI, this effect varies across racial and SES groups. More research should be performed on the role of obesogenic environments in altering the effect of NAc on childhood BMI.


Background
High body mass index (BMI) is not randomly distributed throughout our society. High BMI is more common in African American and low socioeconomic status (SES) individuals than White and high SES people (Jones, 2018). African American children, particularly African American girls, have the highest BMI across all racial and ethnic groups (Jones, 2018). As high childhood, BMI is a predictor of poor health outcomes across domains, and as childhood BMI predicts the future health of adults, there is a need to understand the social and biological mechanisms that contribute to BMI inequalities across race and SES groups. Such research may help us eliminate racial and SES inequalities in childhood BMI, which itself is a contributing factor to health disparities later in life (Igel, Saunders, & Fins, 2018).
As SES and race predict the social and environmental contexts in which people live, it is important to explore racial and SES variations in the contributions of various risk and protective factors that shape BMI and obesity in children (Assari, Thomas, Caldwell, & Mincy, 2018). This is because the effects of race and SES are not limited to their direct and main effects but also their indirect effects through changing vulnerability to various risk and protective factors (Assari et al., 2018).
Theoretically speaking, the salience of the NAc on childhood BMI may vary across populations (Lowe et al., 2019;Marqué s-Iturria et al., 2013;Ronan et al., 2020;Sharkey et al., 2015;Vainik et al., 2018), because individuals live in neighborhoods and contexts that differ in their obesogenic conditions. While a large body of research has connected brain structures and their shape and function, such as cortical thickness (CT) (Lowe et al., 2019;Marqué s-Iturria et al., 2013;Ronan et al., 2020;Sharkey et al., 2015;Vainik et al., 2018) and NAc density (Silvah et al., 2020;van de Giessen, de Bruin, la Fleur, van den Brink, & Booij, 2012;van de Giessen et al., 2013), to high BMI in children and adults, very little is known about the heterogeneity of these effects.

Objectives
This epidemiological study compares racial and income groups of 9-10 years old American children for the predictive role of NAc density on BMI. Our first hypothesis was that NAc density is associated with BMI (Lowe et al., 2019;Marqué s-Iturria et al., 2013;Ronan et al., 2020;Sharkey et al., 2015;Vainik et al., 2018). Our second hypothesis was that the effect of NAc density on children's BMI is stronger in www.scholink.org/ojs/index.php/rhs Research in Health Science Vol. 5, No. 2, 2020 109 Published by SCHOLINK INC.
disadvantaged (African American and low-income) than socially privileged (White and high-income) families.

Methods
A secondary analysis was performed with a cross-sectional design. We used data from the Adolescent Brain Cognitive Development (ABCD) study (Alcohol Research: Current Reviews Editorial, 2018;B. J. Casey et al., 2018). The ABCD only included children who were between the ages of 9 and 10 years. The ABCD children were enrolled from multiple cities across multiple states. Children were recruited into the ABCD study from 21 sites. The primary strategy for sampling in the ABCD study was sampling through school systems (Garavan et al., 2018). Other/mixed race, and White. Ethnicity was 1 for Hispanics and 0 for non-Hispanics. Parents reported their schooling: less than high school, high school, some college, college graduate, and graduate studies.
The Data Analysis and Exploration Portal (DEAP), which operates based on the R statistical package, was applied for data analysis. The DEAP is available at the NIH NDA. Mean (standard deviation; SD) and frequency (relative frequency; %) of all variables were described overall and by race and family income. We also used the ANOVA and chi-square tests for bivariate analysis to compare the study variables across racial and income groups.
Appendix 1 shows our models. For multivariable modeling, we ran mixed-effects regression models. In our model, the NAc density was the predictor, BMI was the outcome, and demographic, ethnicity, family structure, and parental education were the covariates. Race and income levels were the moderators. All models were performed in the pooled sample (n = 9497). Our 1 st model was performed in the absence of any interaction terms; our 2 nd model was performed with the presence of interaction terms between race and NAc density. Our 3 rd model was performed with the presence of interaction terms between household income and NAc density. Before we perform our models, we ruled out multi-collinearity between study variables. We also explored the distribution of our predictor, outcome, residuals, and quantiles (Appendix 2). Unstandardized coefficient (b), SE, and p-value were reported for our model. A p-value of equal or less 0.05 was significant.
The ABCD study protocol received Institutional Review Board (IRB) approval from several institutions, including but not limited to the University of California, San Diego (UCSD). All participating children provided assent. All participating parents signed informed consent (Auchter et al., 2018). Our study was exempt from a full IRB review.

Descriptives
A total number of 9497, 9-10 years old children entered our analysis. In this study, 6411 children (67.5%) were White, 1321 children (13.9%) were African American, 200 individuals (2.1%) were Asian and the remaining 1565 children (16.5%) were other/mixed race.  Children from low-income families had the highest and children from high-income families had the lowest BMI.

Overall Effect of NAc Density on BMI.
In the pooled sample, NAc density was predictive of BMI. However, the associations between NAc density and BMI was more robust in African American than White and low-income than high-income children (Table 3).  Figure 1 shows the positive association between NAc density and BMI in the pooled sample. Figure 2 shows the positive association between NAc density and BMI in the pooled sample based on family income. As this figure shows, the associations between NAc density and BMI was stronger in African American than White children.    Figure 3 shows the positive association between NAc density and BMI in the pooled sample based on family income. As this figure shows, the associations between NAc density and BMI were stronger in low-income than high-income children.

Figure 3. Association between Nucleus Accumbens (NAc) Density and Body Mass Index (BMI) by
Household Income

Discussion
As our finding showed, NAc density was associated with BMI in 9-10 years old American children.
According to our study, this effect was stronger for African Americans and low-income than White and high-income children.
The effect of neural circuits (e.g., cue-triggered motivation) on obesity may depend on the degree by which one's environment promotes obesity (e.g., access to "junk-food") (Oginsky, Goforth, et al., 2016). Chronic and repeated exposure to fast food may interact with the brain mechanisms that regulate food cues (e.g., striatum) (Waeiss, Knight, Engleman, Hauser, & Rodd, 2020). That is, the NAc may show an interaction with one's environment (which may predispose an individual to obesity risk). The very same neural risk factors may show a larger effect on BMI in obesogenic environments. In contrast, when a family has access to healthy food and other buffers, food options and diet may stay healthy even when the individual seeks to eat, in response to food-related cues. Thus, to what degree an individual becomes susceptible to high BMI and obesity is not merely a function of the brain but also the intersection of brain, behaviors, and environment (Oginsky, Maust, Corthell, & Ferrario, 2016).
Many brain structures such as the NAc, striatum, and cerebral cortex regulate food-seeking behaviors and respond to food cues (Waeiss et al., 2020). The family's and neighborhood's food environment as well as available food and dietary habits may modulate the influence of the NAc on BMI because food cue-induced behaviors would be associated with different caloric intakes. Future research should investigate the interaction between food environment, food habits, and brain structures and functions such as those of the NAc, prefrontal cortex, and thalamus in shaping obesity risk through regulating food-seeking behaviors (D'Cunha et al., 2017;Sadeghzadeh, Babapour, & Haghparast, 2015;Shalev, Finnie, Quinn, Tobin, & Wahi, 2006;Shalev, Robarts, Shaham, & Morales, 2003;Tobin, Sedki, Abbas, & Shalev, 2013).

Conclusion
In this study, NAc density was associated with BMI among 9-10-year-old American children. However, this association was not the same across racial and SES groups of children. implemented the study or provided data, but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. The ABCD data repository grows and changes over time.
The current paper used Curated Annual Release 2.0, also defined in NDA Study 634

Conflicts of Interest:
The author declares no conflict of interest.