# extent across countries.

Globally, the evidence on disability prevalence and on disability gaps in education, employment, living conditions and more has grown in recent decades. Regarding prevalence, as part of the Global Burden of Disease (GBD) study (Murray and Lopez 1996), disability prevalence is regularly estimated: it is inferred from data on health conditions and impairments alone using assumptions on distributions of limitations that may result from health conditions and impairments. The World Health Survey has also been used to develop disability prevalence estimates based on core functional domains (seeing, concentrating, moving around, self-care) (Mitra and Sambamoorthi 2014) or based on an index with information on eight domains (vision, mobility, cognition, self-care, pain, interpersonal relationships, sleep and energy, affect) (WHO- World Bank 2011).

Regarding disability gaps in well-being outcomes, while most of the evidence a decade ago pertained to high income countries (HICs), there has been growing evidence that persons with disabilities in LMICs are disproportionately more likely to experience multidimensional poverty, i.e. experience multiple deprivations, are less likely to work and to have ever attended school and more likely to experience morbidity (e.g. Banks et al 2017; Mitra 2018; Pinilla-Roncancio et al 2020; United Nations 2019). For instance, in a systematic review on poverty and disability in LMICs, Banks et al 2017 find that <mark>81% of studies found evidence of a positive association between disability and a poverty marker. This relationship persisted when results were disaggregated by gender, measure of poverty used and impairment types. By age group, the proportion of studies reporting a positive association between disability and poverty was lowest for older adults and highest for working-age adults (69% vs. 86%).</mark> However, deriving any definitive conclusion on inequalities across disability status remains problematic in this literature that uses varying measures for disability, well-being indicators, data sources, and methodologies. Some studies measure disability through broad activity limitations (e.g., Mitra, 2008) or impairments <mark>(Pinilla-Roncancio & Alkire 2020) while more and more use the WG recommended questions (Mitra 2018, Pinilla-Roncancio et al 2020).</mark> Studies using impairments <mark>(PinillaRoncancio & Alkire 2020)</mark> have results on the disability gap in outcomes that are less consistent across countries than those using the WG questions (Mitra 2018; <mark>Pinilla-Roncancio et al 2020)</mark> .

Several studies (Mitra et al 2013; WHO-World Bank 2011) rely on the World Health Survey (WHS) that was designed to collect a detailed health and disability profile of individuals but provide only summary measures of economic well-being, for instance on employment and household expenditures. Besides, not every individual in a household in the WHS was interviewed, only one individual per household. Hence, differences across disability status may be underestimated for household well-being indicators. Finally, and more importantly, results vary across well-being dimensions, making the evidence mixed. Studies relying on traditional poverty measures based on consumption expenditures or asset ownership data do not find any consistent significant association between disability and poverty, while studies on multidimensional poverty measures tend to (United Nations 2019). This is surprising given the consistent evidence found in HICs, whatever the measure of poverty (United Nations 2019).

More research is therefore needed on inequalities that might be associated with disabilities for LMICs using internationally comparable disability questions. The aim of this paper is to contribute to filling this gap. The rest of the paper is organized as follows: Section 2 presents the 3