Investigating Healthcare Disparities in Vitiligo

Overview

Vitiligo is an acquired, non contagious skin disorder characterised by depigmented patches of skin that may appear in a localised or very generalised distribution, and affecting 0.5-2.0% of the global population.There are however, limited population-based studies on the burden of vitiligo and disparities across people of different ethnicities and deprivation. The overall purpose of this study is to provide an estimate of the lifetime risk of vitiligo in the population overall and by sociodemographic subgroups. Moreover, to do a subgroup analysis in the vitiligo population to identify health-related disparities across people in different sex, age, deprivation and ethnicity. A detailed understanding of the burden of disease in different sociodemographic groups is vital to plan resource provision.

This study will provide estimate of the cumulative lifetime risk of vitiligo in the population overall, and by important sociodemographic groups, including age, sex, ethnicity and deprivation, which will prevalent key data to show the relative burden of vitiligo across the aforementioned groups. These approaches allow creation of cumulative lifetime risk plots which provide an excellent and accessible way to display the relative disease burden across groups. The cumulative lifetime risk of vitiligo will be estimated at age 80 years (approximate lifetime expectancy in the UK) using survival models, with age as the timescale and accounting for competing risk of death. This study will also perform a subgroup analysis in the vitiligo population to identify health-related disparities across people in different deprivation, sex and ethnic groups. The disparities that will be considered are: Mental health conditions; healthcare utilisation; and work impact (time off work and unemployment), The assessment of any associations with baseline characteristics and the outcome of interest will be used using Cox proportional hazards models (time to event outcomes) and generalised linear models.

Conditions