Living in a disadvantaged neighborhood is linked to poorer health outcomes, including brain health. Studies have shown an association between disadvantaged neighborhoods and decreased brain volume, yet the underlying mechanisms remain unclear. Obesity is a potential pathway, as individuals in these neighborhoods often face higher risks due to limited access to healthy food and environments that discourage physical activity. Neighborhood disadvantage is associated with increased consumption of calories from trans-fatty acids (TFAs) and sodium, both contributing factors to obesity, particularly abdominal obesity. Chronic neighborhood stressors also impact eating habits, leading to cravings for highly palatable but unhealthy foods as a coping mechanism. Previous research indicates that high body mass index (BMI) mediates the effect of living in a disadvantaged neighborhood on reduced brain volume. Neighborhood disadvantage, high BMI, and chronic stress also influence cortical microstructure, as measured by the T1-weighted/T2-weighted (T1w/T2w) ratio, a proxy for intracortical myelination. Intracortical myelination affects neural synchrony and cognitive function. While the T1w/T2w ratio is not perfectly specific to myelin, it shows sensitivity to myelin content and is useful in studying cortical maturation and cognition. Different cortical layers have varied cell populations and information processing functions; therefore, examining microstructure at multiple levels can reveal how adverse environments affect these processes. This study investigated the relationship between the area deprivation index (ADI) and cortical microstructure, using the T1w/T2w ratio at various cortical levels, along with potential mediating factors such as BMI and stress. The researchers also explored the relationship between TFA intake and the T1w/T2w ratio. The hypothesis was that worse ADI would be linked to higher BMI, an obesogenic diet (high TFA intake), higher stress levels, and negative effects on cortical microstructure in brain regions related to reward, emotion regulation, and cognition.

Existing literature establishes a connection between neighborhood disadvantage and negative health outcomes, including brain health. Studies have demonstrated a correlation between living in disadvantaged areas and reduced brain volume. Obesity emerges as a potential mediating factor, with residents of such neighborhoods exhibiting higher obesity rates due to limited access to healthy food options and environments that discourage physical activity. Research highlights the association between neighborhood disadvantage and increased consumption of less healthy foods, including those high in trans-fatty acids (TFAs) and sodium. TFAs, often found in fried fast foods, contribute significantly to obesity. Moreover, the chronic stress associated with living in disadvantaged neighborhoods influences eating habits, often leading to increased consumption of highly palatable, yet unhealthy, food choices as a coping mechanism. Previous studies have indicated that high body mass index (BMI) mediates the negative effects of living in a disadvantaged neighborhood on brain volume. Furthermore, research shows that neighborhood disadvantage, high BMI, and chronic stress impact cortical microstructure, as assessed by the T1w/T2w ratio, an indicator of myelin content. Intracortical myelination plays a critical role in neural synchrony and cognitive functions. The T1w/T2w ratio, while not exclusively specific to myelin, is a valuable tool for assessing cortical maturation patterns and cognitive abilities. Studies have utilized this ratio to examine the effects of various factors, including stress, on brain structure and function.

This study included 92 adults (27 men, 65 women) from the Los Angeles area who underwent neuroimaging (T1w and T2w scans) between October 30, 2019, and July 14, 2022. Participants provided their residential addresses. Neighborhood disadvantage was measured using the 2020 California State Area Deprivation Index (ADI), with higher scores indicating greater disadvantage. The T1w/T2w ratio was calculated at four cortical ribbon levels (deep, lower-middle, upper-middle, and superficial). Perceived stress was assessed using the Perceived Stress Scale (PSS), and BMI was calculated from weight and height measurements. Dietary data, including trans-fatty acid (TFA) intake, were collected from 81 participants using the VioScreen Graphical Food Frequency System. Image quality was assessed using the MRI Quality Control tool (MRIQC). Partial correlation coefficients, controlling for sex and age, were calculated to examine associations between ADI, BMI, PSS, and TFA intake using SPSS. Non-rotated partial least squares correlational (PLSC) analysis was used to identify brain regions correlated with ADI at different cortical levels. Structural equation modeling (SEM) investigated the mediation of relationships between ADI and findings from PLSC analysis, including BMI and stress as potential mediators. The SEM was performed in R Studio using the lavaan package. Model fit was assessed using the chi-squared p-value, comparative fit index, and standardized root mean square residual. Correlations between TFA intake and the T1w/T2w ratio were also analyzed.

The study found a positive correlation between worse ADI and higher BMI (r = 0.27, p = 0.01) and perceived stress (r = 0.22, p = 0.04). PLSC analysis revealed that worse ADI was associated with increased T1w/T2w ratio in medial prefrontal and cingulate regions (superficial cortex), areas involved in reward processing, emotion regulation, and higher cognition (p < 0.001). Conversely, worse ADI was associated with a decreased T1w/T2w ratio in supramarginal, middle temporal, and primary motor regions (middle/deep cortex), components of the mirror neuron system involved in social interaction (p < 0.001). SEM analysis indicated that increased BMI partially mediated the relationship between worse ADI and increased T1w/T2w ratio in the medial prefrontal and cingulate regions (indirect effect, p = 0.02), accounting for 29% of the total effect. Stress did not significantly mediate this relationship. Furthermore, total TFA intake, particularly elaidic acid, showed a positive correlation with increased T1w/T2w ratio in the medial prefrontal and cingulate regions (p = 0.01).

The findings suggest that obesogenic aspects of neighborhood disadvantage, including poor dietary quality, may negatively impact information processing flexibility in brain regions crucial for reward, emotion regulation, and cognition. The partial mediation by BMI highlights the role of obesity in linking neighborhood disadvantage to alterations in cortical microstructure. The correlation between TFA intake and increased T1w/T2w ratio in specific brain regions supports the hypothesis that a diet high in TFAs, a feature often associated with disadvantaged neighborhoods, may contribute to these observed changes. The decreased T1w/T2w ratio in regions of the mirror neuron system suggests potential impacts on social interaction and understanding others' actions. These findings contribute to our understanding of how neighborhood disadvantage can affect brain health, with potential implications for interventions targeting dietary improvements and obesity prevention in disadvantaged communities.

This study demonstrates an association between neighborhood disadvantage and altered cortical microstructure, partially mediated by BMI and linked to trans-fatty acid intake. The findings highlight the impact of obesogenic factors prevalent in disadvantaged neighborhoods on brain regions involved in crucial cognitive and social functions. Future research should explore the long-term effects of neighborhood disadvantage on brain development and investigate the specific mechanisms by which poor diet and obesity contribute to alterations in cortical microstructure. Further research with larger, more diverse samples and longitudinal data is needed to confirm these findings and explore potential interventions.

The study has several limitations. The biological basis of the T1w/T2w ratio alterations remains uncertain. While sensitive to myelin content, it also reflects other factors, such as neurite or synaptic density. The cross-sectional design limits causal inferences; longitudinal studies are needed. BMI, while widely used, is not a perfect measure of body adiposity and doesn't reflect fat distribution. A potential selection bias exists due to the racial composition of the sample differing from the overall population. The use of a single time point for ADI assessment limits the understanding of long-term exposure effects.