Disability Disaggregation

1.1 Disaggregation Based on Disability

We compare indicators across groups by disability status. Disaggregating an indicator (e.g. ever attended school rate) by disability status aims to establish the size of the gap that may be associated with disability, i.e. the disability gap, or inequalities associated with disability.

Disability is measured by functional difficulty questions and measures. First, disaggregation is done for persons with no difficulty vs any difficulty (disaggregation a). Second, we use a three-way disaggregation: persons with no difficulty vs some difficulty vs at least a lot of difficulty (disaggregation b). Third, we compare persons with no difficulty and some difficulty vs at least a lot of difficulty (disaggregation c).

In Results Tables, the difference between groups and its statistical significance is typically noted in a separate column. A disability gap represents a statistically significant disadvantage for persons with functional difficulties compared to persons with no functional difficulty. Statistical significance is based on a t-test (*, **, and *** at the 10%, 5% and 1% levels respectively). As indicators reflect achievements (e.g. employment population ratios) or deprivations (multidimensional poverty), a disability gap may be reflected in a positive or a negative difference.

This study uses national household surveys and censuses. Censuses typically include all people in a country, irrespective of their disability status. In contrast, household surveys are constructed out of sampling from censuses often with complex sampling design. It should be noted that none of the household surveys under study is sampled to be representative of persons with disabilities. Censuses are thus better able to represent the situation of persons with disabilities than household surveys, which may not be representative of all persons with disabilities due to their sampling.

Besides, for each dataset with a sample, we set 50 observations as the minimum required to produce estimates for subgroups following common practice. For censuses with the full population, we set this minimum at 20.

Due to this constraint, for a given data set, disaggregation may be possible for some indicators but not others, especially when some indicators are constructed particularly for subsamples such as youth.

1.2 Disaggregation Based on Disability and Demographic Characteristics

There may be patterns of intersectional disadvantage that affect subgroups of people with disabilities and their households, such as women or rural residents. For each data set under consideration, we disaggregate results at the individual level based on disability as well as sex, rural/urban residence and age group. Double disaggregation tables by disability and a demographic characteristic (sex, rural/urban, age group) are available in Results Tables.

For data sets with the full population or random sampling, disaggregation is feasible based on sex, age groups, rural/urban as long as information on sex, age and rural/urban residence is available. For data sets with complex survey design, disaggregation based on sex, age groups, rural/urban is feasible if sex, age, rural/urban residence were used as part of the stratification of the survey.