Testing the Association Between Neighborhood Disadvantage and White Matter Hyperintensities

Background Social determinants of health—the conditions in the places where people live, learn, work, and play—have been shown to affect a broad range of health outcomes, including risk for Alzheimer’s disease and related dementias (ADRD). However, the biological mechanisms by which socio‐contextual...

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Veröffentlicht in:Alzheimer's & dementia 2022-12, Vol.18 (S11), p.n/a
Hauptverfasser: Merkel, Emily X., Ennis, Gilda E., Cadman, Robert V., Koscik, Rebecca Langhough, Ma, Yue, Asthana, Sanjay, Johnson, Sterling C., Kind, Amy J., Bendlin, Barbara B.
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Sprache:eng
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Zusammenfassung:Background Social determinants of health—the conditions in the places where people live, learn, work, and play—have been shown to affect a broad range of health outcomes, including risk for Alzheimer’s disease and related dementias (ADRD). However, the biological mechanisms by which socio‐contextual factors increase risk for ADRD are poorly known. Higher levels of neighborhood disadvantage have been linked with increased cardiovascular disease (CVD) risk. CVD risk has been associated with white matter lesions known as white matter hyperintensities (WMH) because they produce increased signal on fluid‐attenuated inversion recovery (FLAIR) MRI scans. WMH have been associated with increased risk for stroke, cognitive decline, and dementia. We investigated whether greater neighborhood‐level disadvantage was associated with greater WMH volume. Method Participants (n = 804) were enrolled in the Wisconsin Registry for Alzheimer’s Prevention and Wisconsin Alzheimer’s Disease Research Center Clinical Core. MRI was performed at 3 T to acquire T2‐weighted FLAIR images which were then processed using the lesion prediction algorithm from the Lesion Segmentation Toolbox to measure WMH volume. Area Deprivation Index (ADI) distributions from the state of Wisconsin were used to create a dichotomous variable that compared the highest state‐ranked quintile (most disadvantaged neighborhoods) to the lowest 4 state‐ranked quintiles (least disadvantaged neighborhoods). Multiple linear regression tested ADI as a predictor of natural log‐transformed WMH volume. Age, sex, education, intracranial volume, MRI head coil, and study cohort were controlled. Result Four percent (n = 33) of participants were identified as living in the most disadvantaged neighborhoods (see Table 1). The association between neighborhood‐level disadvantage and log‐transformed WMH volume was not statistically significant (see Table 2 and Figure 1). Conclusion Neighborhood disadvantage was not related to WMH volume in this study. This finding contrasts with previous studies demonstrating associations between increased neighborhood disadvantage and reduced cerebral and hippocampal volume (Hunt et al., 2020) and increased odds for AD neuropathology (Powell et al., 2020). Statistical power to assess the primary effect was likely limited by the small number of participants from the most disadvantaged neighborhoods. This illustrates the need for additional research and increased population‐representative recruitment
ISSN:1552-5260
1552-5279
DOI:10.1002/alz.069324