Impact of individual and neighborhood dimensions of socioeconomic status on the prevalence of mild cognitive impairment over seven-year follow-up

Abstract

Objectives: There is strong evidence about the association between low socioeconomic status (SES) and higher risk of dementia. However, it has not been conveniently addressed so far the role of SES on the incidence of mild cognitive impairment (MCI). This study examines the impact of individual and neighbourhood dimensions of SES, as well as their interaction, on the risk of developing MCI in a sample of older adults. Method: Data from the Vallecas Project cohort, an ongoing community-based longitudinal study for early detection of cognitive impairment and dementia, were used to build two indices of SES namely individual and neighbourhood, as well as a global SES as a combination of both, and to investigate their effects on MCI conversion by means of a multivariate-adjusted Cox proportional hazard model. Results: A total of 1180 participants aged 70 years and older were enrolled in this study. Of these, 199 cases of MCI (16.9%) were diagnosed at any point of the follow-up. The individual and neighbourhood dimensions of SES played different roles in the dynamics of the MCI occurrence through aging. Most importantly, the risk of developing MCI was almost double for lower SES quartiles when compared to the highest one. Conclusion:The incidence of MCI in older adults was related to both individual characteristics and socioeconomic context. Public health strategies should be holistic and focus not only on promoting the classical individual preventive measures, but also on reducing social inequalities to foster healthy aging and reduce dementia burden.

Selecting the most important self-assessed features for predicting conversion to mild cognitive impairment with random forest and permutation-based methods

“…In our algorithm, some features have the capacity to confer cognitive reserve such as years of schooling, total years of work, or socioeconomic status. Those features might act as protective factors against the development of MCI as expected according to available evidence [85][86][87] . This work has important limitations that need to be laid out.…”

A comparative analysis of automated MRI brain segmentation in a large longitudinal dataset: Freesurfer vs. FSL

“…The dataset for this work was collected by a longitudinal study about healthy aging based in Madrid, Spain [Gómez-Ramírez et al, 2019], [Fernández-Blázquez et al, 2020] conceived to investigate the effect of aging on the human brain. The dataset is part of single-center, observational, longitudinal cohort study that started in 2011 and it is still ongoing.…”

Inequalities in Cognitive Impairment Among Older Adults in China and the Associated Social Determinants: A Decomposition Approach

“…As the increasing demand for care of older adults with dementia, the problems related to cognitive impairment have aroused great attention, but little is known about the inequality in cognitive impairment. Existing few studies have mainly concentrated on the current status of inequalities in cognitive impairment [6,7], or the relationship between related factors and inequalities in cognitive impairment [8,9]. For instance, a study has indicated that women and rural populations have unfavorable inequalities in cognitive impairment compared with men and urban populations [7], and studies have suggested that the inequalities in cognitive impairment were related to individual characteristics and socioeconomic context [8][9][10].…”

“…Existing few studies have mainly concentrated on the current status of inequalities in cognitive impairment [6,7], or the relationship between related factors and inequalities in cognitive impairment [8,9]. For instance, a study has indicated that women and rural populations have unfavorable inequalities in cognitive impairment compared with men and urban populations [7], and studies have suggested that the inequalities in cognitive impairment were related to individual characteristics and socioeconomic context [8][9][10]. Although researchers have found that cognitive impairment is unequally distributed among socioeconomic groups, namely, people of disadvantaged socioeconomic status are at greater risk for cognitive impairment, these studies did not assess the degree of health inequalities or determine how much of it was explained by proposed factors.…”