Zusammenfassung
Objective: Previous studies have shown that socioeconomically deprived groups exhibit higher lesion load of the white matter (WM) in aging. The aim of this study was to (i) investigate to what extent education and income may contribute to differences in white matter hyperintensities (WMHs) and (ii) identify risk profiles related to a higher prevalence of age-associated WMH.Design and Setting: ...
Zusammenfassung
Objective: Previous studies have shown that socioeconomically deprived groups exhibit higher lesion load of the white matter (WM) in aging. The aim of this study was to (i) investigate to what extent education and income may contribute to differences in white matter hyperintensities (WMHs) and (ii) identify risk profiles related to a higher prevalence of age-associated WMH.Design and Setting: Population-based adult study of the Leipzig Research Centre for Civilization Diseases (LIFE) in Leipzig, Germany.Participants: Dementia-free sample aged 40-80 years (n = 1,185) derived from the population registry.Measurements: Information was obtained in standardized interviews. WMH (including the derived Fazekas scores) were assessed using automated segmentation of high-resolution T1-weighted anatomical and fluid-attenuated inversion recovery (FLAIR) MRI acquired at 3T.Results: Despite a significant association between income and WMH in univariate analyses, results from adjusted models (age, gender, arterial hypertension, heart disease, and APOE e4 allele) indicated no association between income and WMH. Education was associated with Fazekas scores, but not with WMH and not after Bonferroni correction. Prevalence of some health-related risk factors was significantly higher among low-income/education groups. After combining risk factors in a factor analysis, results from adjusted models indicated significant associations between higher distress and more WMH as well as between obesity and more deep WMH.Conclusions: Previously observed differences in WMH between socioeconomically deprived groups might stem from differences in health-related risk factors. These risk factors should be targeted in prevention programs tailored to socioeconomically deprived individuals.
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