Examining the roles of socioeconomic status and relevant health correlates (body mass index, diet quality, and inflammation) for neuropsychological function in young adults.

BACKGROUND

In this cross-sectional analysis, we examined associations between socioeconomic status (SES), body mass index (BMI), inflammation, diet, and cognitive performance. While low SES is associated with lower cognitive scores, the present study investigated whether these variables - specifically BMI, inflammatory biomarkers, and dietary intake - statistically mediate this relationship.

METHODS

The final sample included 109 young adults (mean age = 21.31; 65% female; 45% white). Analyses utilized a comprehensive neuropsychological battery, including the NIH Cognitive Toolbox and Kaufman Brief Intelligence Test, alongside biomarkers of inflammation (Interleukin (IL)-1β, IL-6, and tumor necrosis factor-α (TNF-α)), and self-reported dietary intake via the National Cancer Institute's Diet History Questionnaire - Third Edition. A pre-registered analysis using bootstrapped standard errors across 5,000 bootstrapped replications in 'lavaan' tested whether (i) associations between SES and executive functioning and episodic memory were statistically mediated by a higher BMI and (ii) associations between BMI and executive functioning and episodic memory were statistically mediated by elevated inflammation and sugar or fat intake.

RESULTS

BMI did not account for the association between SES and cognition; however, BMI, fat intake, and sugar intake were inversely correlated with cognitive functioning. Sugar intake mediated the association between BMI and cognition, though this finding was not significant after adjusting for covariates. Inflammation did not mediate the relationship between BMI and cognition.

CONCLUSIONS

These results provide support for a link between BMI and cognitive performance and preliminary evidence of a mediating role of sugar intake. Further longitudinal and experimental research is needed to extend these findings and characterize underlying mechanisms.