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. 2024 Oct 4:16:1465744.
doi: 10.3389/fnagi.2024.1465744. eCollection 2024.

Disparities in structural brain imaging in older adults from rural communities in Southern Nevada

Xiaowei Zhuang  1   2 , Dietmar Cordes  1   3 , Jessica Z K Caldwell  1 , Andrew R Bender  1 , Justin B Miller  1
Affiliations

Disparities in structural brain imaging in older adults from rural communities in Southern Nevada

Xiaowei Zhuang et al. Front Aging Neurosci. .

Abstract

Introduction: Identifying the associations between rural-living or neighborhood disadvantage and neurobiology may clarify rural-urban disparities in older adults with cognitive impairment related to Alzheimer's disease.

Methods: We examined rural-urban differences and neighborhood disadvantages in brain cortical thickness (CT) measures among 71 rural and 87 urban-dwelling older adults. Analysis of covariance was used to test each FreeSurfer-derived CT measures' associations with rural-urban living, clinical impairment status, and their interactions. Post-hoc linear regressions were used to test the association between CT measures and neighborhood disadvantage index.

Results: Rural-dwelling older adults had thinner cortices in temporal and inferior frontal regions compared to urban participants, especially among clinically normal participants, where the thinner temporal cortex further correlated with higher neighborhood disadvantage. Conversely, rural participants had thicker cortices in superior frontal, parietal and occipital regions.

Discussion: Our results suggest a complex interplay between community contexts and neurobiology. For memory-related regions, rural-living and neighborhood disadvantage might be negatively associated with subjects' brain structures.

Keywords: Alzheimer’s disease; cortical thickness; dementia; neighborhood disadvantage; rural–urban commuting area; rural–urban differences.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

Figure 1
Figure 1
Analysis of covariance (ANCOVA) results on cortical thickness measures. (A) Residency effect. Post-hoc effect-sizes (Cohen’s d) between groups (GP: Rural vs. urban) for whole-brain (Left) and regions with significant residency effect (pFDR ≤ 0.05, Right) in the ANCOVA. (B) Impairment effect. Post-hoc Cohen’s d of Normal vs. impaired for whole-brain (Left) and regions with significant impairment effect in the ANCOVA (pFDR ≤ 0.05, Right). (C) Interaction effect. Five regions showed significant interaction effect between residency and impairment (GPxDX) in the ANCOVA analysis. Thickness measures used in the post-hoc analysis and plotted here have been adjusted for age, sex and education in the ANCOVA model. GP: Residency group (i.e., rural or urban); DX: Diagnosis (i.e., clinical impairment status); FDR: false discovery rate.
Figure 2
Figure 2
Post-hoc associations between cortical thickness measures and neighborhood area deprivation index (ADI) in both normal (blue) and impaired (orange) participants. ADI ranked within Nevada was used. Regions with significant ANCOVA results were input to this association analyses, and only regions with a significant slope (p ≤ 0.05) were plotted here, including parahippocampal gyrus (A) and precuneus (B). Cortical thickness measures used in this post-hoc analysis and plotted here have been adjusted for age, sex and education in the ANCOVA model. Partial correlation values (r) with 95% confidence intervals and statistical significance levels (p-values) were listed in boxes above the plots.
See this image and copyright information in PMC

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