Analysis of Micro Datasets: Method
This report uses population census and Demographic and Health Survey (DHS) data for 15 countries in Sub-Saharan Africa, Asia & the Pacific, and Latin America & the Caribbean. Countries are predominantly lower-middle income countries. All countries have a Human Development Index rank above 90 and all except Tonga have ratified the CRPD (Appendix 2b).
We use three population census datasets of the 2020 census round (2015 to 2024): Guatemala (2018), Kenya (2018) and Tonga (2016). We use data from the DHS program for 12 countries: Cambodia (2014), Haiti (2016-17), Maldives (2009), Mali (2018), Mauritania (2019-2021), Nigeria (2018), Pakistan (2017-18), Rwanda (2019), Senegal (2018), South Africa (2016), Timor Leste (2016) and Uganda (2016). The 15 countries were selected given the availability of a dataset representative at both national and regional levels and has the WG-SS,. We focus on adults 15 years and older as the WG-SS may not be adequate to capture disability among children (Loeb et al 2018).
What indicators does the report produce?
This report produces various indicators to capture the rights and human development situation of persons with disabilities. The indicators are in Table 4.1 and are further described in Method Brief #1. The list of indicators was developed by reviewing the questionnaires of datasets in light of the provisions of the CRPD and the SDGs that they could capture (IWGHS 2018; OHCHR 2021). Indicators reflect a variety of achievements (e.g., access to safely managed water) and deprivations (e.g., less than primary school completion). Taking the difference of indicators between persons with no difficulties and persons with difficulties may give a gap associated with disability, i.e. the disability gap or inequalities associated with disability. How indicators are disaggregated by disability status is explained in Box 1.
Box 1: How were indicators disaggregated by disability status? |
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All the datasets have the WG-SS. The WG-SS measures functional difficulties for individuals in six domains: (a) seeing, (b) hearing, (c) walking/climbing stairs, (d) concentrating or remembering things, (e) selfcare, and (f) communication. A household respondent reports the degree of difficulty in each domain on a four-point answer scale: 1-‘No difficulty’, 2-‘Some difficulty’, 3-‘A lot of difficulty’, and 4-‘Unable to do’.
To identify functional difficulty status groups, at least one cutoff has to be set on the answer scale of functional difficulties. Where the threshold is set can lead to varying results and may answer different data needs. This report’s results tables consistently present disaggregations using three ways to categorize individuals based on functional status and place them into mutually exclusive categories. In disaggregation a, individuals are in two categories: In the results described below, we mostly use disaggregations a and b. Due to sample size constraints, disaggregation a is useful to compare persons with no difficulty to persons with any level of difficulty to enable disaggregations by functional domains and also for some subgroups (e.g. by sex, age). Disaggregation b is able to identify potential deprivations among persons with some difficulty and compare them to those experienced by persons with at least a lot of difficulty. |
Table 4.1: Indicators under study
Indicator | CRPD Article | SDG indicator | Indicator reference in results tables |
Prevalence | |||
Adults with functional difficulties | P1 | ||
Adults with functional difficulties by type of functional difficulty | P2 | ||
Households with functional difficulties | P3 | ||
Education | |||
Adults who have ever attended school | 24 | E1 | |
Adults who have less than primary school completion | 24 | E2 | |
Adults who have completed primary school | 24 | E3 | |
Adults who have completed secondary school or higher | 24 | E4 | |
Adults who can read and write in any language | 24 | 4.6.1 | E5 |
Personal activities | |||
Employment population ratio | 27 | W1 | |
Youth idle rate (NEET) | 27 | 8.6.1 | W2 |
Working individuals in manufacturing | 27 | 9.2.2 | W3 |
Women in managerial positions | 27 | 5.5.2 | W4 |
Working individuals in informal work | 27 | 8.3.1 | W5 |
Adults who used a computer recently | 9 | PA2 | |
Adults who used the internet recently | 9 | PA3 | |
Adults who own a mobile phone | 9 | 5.b.1 | PA4 |
Health | |||
Adults in households using safely managed drinking water | 25 | 6.1.1 | H1 |
Adults in households using safely managed sanitation services | 25 | 6.2.1 | H2 |
Standard of living | |||
Adults in households with electricity | 28 | 7.1.1 | S1 |
Adults in households with clean cooking fuel | 28 | 7.1.2 | S2 |
Adults in households with adequate housing | 28 | S3 | |
Assets owned by individual’s household (%) | 28 | S4 | |
Adults in households with a mobile phone | 28 | 5.b.1 | S5 |
Multidimensional analysis | |||
Adults who experience multidimensional poverty, i.e. deprivations in more than one dimension of wellbeing (education, health, work, standard of living) | 24, 25, 27, 28 | M1 |
Notes: Relevant SDG indicators are listed. The SDG indicators may be different from the indicators measured in this report. For instance, indicator 8.3.1 measures Proportion of informal employment in total employment while this report measures the proportion of workers doing informal work. All indicators are proportions except the one on assets. Indicator reference numbers follow those in the 2021 and the 2022 Disability Data Reports (PA1 was skipped due to a lack of data on exposure to mass media.