Intersectional inequality of obesity and weight management services (360G-Wellcome-324226_Z_25_Z)

Background: Obesity is increasing in prevalence, which is an important factor in multiple diseases. Obesity rates are greatest in areas of high deprivation. GLP-1 agonists are a promising new medication to address obesity, however inequality in their distribution or effectiveness is poorly known. Intersectionality describes how people exist at the intersection of multiple social identities which combine to create a unique impact. Little is known about intersectionality in this context. Multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) has recently been developed which has advantages over traditional techniques for modelling intersectionality. Aim: To analyse the intersectional inequality of obesity prevalence and health outcomes, as well as the distribution and effectiveness of GLP-1 agonists. Method: Large biomedical databases will be used. Cross- sectional MAIHDA will be used to analyse the prevalence of obesity and distribution of GLP-1 agonists. MAIHDA will be extended to survival analysis and difference-in-differences to analyse obesity related cardiovascular disease and the effect of GLP-1 agonists. Outcome: This will deliver a greater understanding of the inequality of obesity and GLP-1 agonists, which may provide opportunities to improve public policy. Further, extending MAIHDA has the potential for cross-discipline methodological improvements. Key words: Obesity, Inequality, Multilevel Analysis, Incretins