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Medicine and Health Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

Western University

Epidemiology

2020

Intersectionality

Articles 1 - 2 of 2

Full-Text Articles in Medicine and Health Sciences

Intersectional Social Inequalities And Cognitive Functioning Among Community-Dwelling Older Adults In England: A Decomposition Analysis Of The Mediating Role Of Loneliness, Chantel Walwyn Dec 2020

Intersectional Social Inequalities And Cognitive Functioning Among Community-Dwelling Older Adults In England: A Decomposition Analysis Of The Mediating Role Of Loneliness, Chantel Walwyn

Electronic Thesis and Dissertation Repository

Normative cognitive decline is an emerging public health issue for older adult populations. It is necessary that we take an intersectional approach to examining heterogeneity in cognitive health outcomes. Using complex longitudinal survey data from the English Longitudinal Study of Ageing (ELSA), multiple linear regression models were used to examine the relationship between intersectional group membership based on age, education, and sex, and change in cognitive functioning domains (memory function, and executive function) over an 8-year period. Three-way decomposition analysis was also used to examine the mediating effect of loneliness on the association between intersectional group membership and the change …


Evaluating Quantitative Methods For Intercategorical-Intersectionality Research: A Simulation Study, Mayuri Mahendran Apr 2020

Evaluating Quantitative Methods For Intercategorical-Intersectionality Research: A Simulation Study, Mayuri Mahendran

Electronic Thesis and Dissertation Repository

This study evaluated eight quantitative methods for their predictive accuracy for intersectionally-defined subgroups, via a simulation study. The methods included two forms of single-level regression with interaction terms, cross-classification, multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA), and four decision tree methods: classification and regression trees (CART), conditional inference trees, chi-square automatic interaction detector, and random forest. The simulated datasets varied by outcome variable type, input variable types, sample size, and size and direction of the effects. Predictive accuracy improved with increasing sample size for all methods except CART. At small sample sizes, random forest and MAIHDA generally created …