Transcript 2023

Hello everyone! Is the sound okay? This talk is going to be available in the link that Dena is going to include in the chat box very shortly.

Here you go, it’s in the chat box now. So, I’m a woman in my 50s with gray hair, white skin and wearing a pink blouse and very happy to be here with you.

So what I’m going to present is the work of a large team based in different parts of the world.

So first I would like to acknowledge my co—editors, Jill, GVS, Michael, Monica, Minerva and it is also the work of several research assistants and contributors to the data analysis.

I would like to highlight in particular, the work of Katherine, Ph.D student at Fordham University who analyzed a lot of micro data. Also very grateful to the steering committee for the disability initiative for strategic guidance and feedback on the report draft and to the well spring philanthropic fund for their funding.

So, I want to share with you the key findings from the 202 in the Disability Data Initiative. It is https: Forward slash, forward slash, disability data dot ace dot Fordham dot edu for the slash.

Report is in three parts with key findings in the main text and selected country findings in country briefs for each country, we have comprehensive results in big results, tables and in Excel file.

I’m not going to use slides, a couple times will share my screen to highlight tables and figures on the website and links will be in the chat box.

So, as background since 2006,186 countries have adopted, ratified the convention on the rights of persons with disabilities. The CRPD. And in 2015, Governments have adopted the sustainable development goals, policy agenda promising to leave no one behind.

So, in that context, the disability data report has two objectives. First it reviews what data is available to identify persons with disabilities all over the world so that we know to what extent persons with disabilities are potentially visible and accounted for in national statistics.

I say potentially, because the fact that disability data is collected does not necessarily mean that it is analyzed and used.

In fact, we already know that statistics on human rights and development continue to be very rarely disaggravated by disability status. Is it because the data is not collected. So that is the first question we try to answer.

Then we focus on countries that collect disability data and answer the question: What is feasible in terms of disaggregating indicators? Is it that the data is collected, but perhaps does not lend itself to disaggregation by disability status?

Or is it that the disaggregation work is yet to be done.

Finally, we analyze the data and we have findings on the share of adults with disabilities and on disability disaggregated indicators at national and sub national levels in 15 countries.

So, producing both national and sub national statistics on the situation of persons with disabilities is important because the CRPD may be a tool used by national and local Governments to make their policies inclusive of people with disabilities.

In fact, in countries that have not ratified the CRPD like the U.S., sub national estimates can inform policies as some local Governments use the CRPD to uphold disability rights.

Recent evidence also shows that the COVID—19 pandemic and the climate emergency have varied effects depending on geography and that persons with disabilities are more at risk during disasters and extreme climate events.

Due to a lack of inclusive planning, lack of accessible information, early warning systems and transportation and due to discriminatory attitudes.

Producing local statistics can help inform local policies and programs.

So first regarding our review of data sets, this report examines the questionnaires of close to 13 hundred data sets from 188 countries to identify those with functional difficulty questions. For example, questions on difficulty seeing, hearing, walking, concentrating or remembering.

So, why functional difficulty questions? Because functional difficulty questions follow the United Nations guidelines for disability measurement in censuses.

We also specifically track surveys and censuses that use the internationally comparable and tested Washington group short set (WG—SS) which has questions related to difficulty seeing, hearing, walking, concentrating/remembering, self—care and communicating.

So, the WG—SS enables the monitoring of disability rights and the production of internationally comparable statistics. What do we find. About one in five data sets reviewed for the 2009 to 2022 period have functional difficulty questions.

125 countries were identified as having at least one data set with functional difficulty questions, including 70 countries with at least one data set with the WG—SS.

So this is progress compared to where we were 10,20 years ago in terms of data availability.

In fact, global trends suggest an increase in the share of data sets with the WG—SS during the 2010s.

In the early 2020s, high frequency phone surveys rolled out by countries and international organizations during the pandemic, how often did not include the WG—SS.

The results also show a lot of variation in the collection of functional difficulty questions across world regions. For instance, in Europe and central Asia, functional difficulty questions continue to be rare in surveys and censuses, while in sub—Saharan Africa Middle East and north Africa East Asia and Pacific their availability has markedly increased.

So, as a result despite a lot of progress there is still a need for more data collection in countries where data is lacking and in countries where we find data, but such data is yet to be collected on an on a regular basis.

So, we recommend a couple of things. That it should become standard for questions functional difficulties such as the WG—SS to be included in national surveys and population censuses, including during emergencies, such as pandemics to track the inequalities persons with disabilities experience and to inform and monitor policies.

In some countries, more resources may be needed to strengthen the national capacity to collect functional disability data through surveys and censuses.

Now for countries with data, what can be done with it? So I will now move to our analysis of data in 15 countries to explore the potential to disaggregate indicators by disability status at both national and sub national levels.

I will start with a bit of background on the method we use. Persons with disabilities are a diverse group, in many ways for instance, in terms of disability type, degree of functional difficulty, gender, age, where they live.

So, in terms of degree, disability statistics on prevalence and inequalities can be estimated using different cut—offs on the degree of functional difficulties based on the WG—SS.

So, the four point answer scale for each question is: No difficulty, some difficulty, a lot of difficulty, and unable to do.

For instance, one could have two groups: Persons with no and some difficulty together and then persons with a lot of difficulty and unable to do in another group.

We show results using three ways of categorizing disability and results are in tables in gigantic and perhaps scary—looking tables.

But the way we find to be most informative is to distinguish three groups: Persons with no difficulty, persons with some difficulty, and persons with a lot of difficulty or unable to do.

In cases where sample sizes are small for the disaggregated analysis, for instance when we compare people with different types of disabilities with survey data, then we contrast persons with no difficulty to persons with any level of difficulty.

So that is some, a lot or unable to do all together.

To get a sense of the size of the disabled community, we also consider persons with any level of difficulty, some, a lot or unable to do.

Based on our research, in many countries, persons with some difficulty are also at risk of deprivations and exclusion and therefore we think should be considered as persons with disabilities.

So we analyzed demographic and health survey data, (DHS) data for 12 countries Cambodia, Haiti Maldives Mali, Nigeria, Pakistan, Rwanda, Senegal, South Africa, and Uganda. We also analyzed census data for 3 countries, Guatemala, Kenya and Tonga, what do we find in terms of what feasible for disaggravation.

We show that it is possible to produce disability disaggregated indicators as the national level as well as at the regional level to document within country inequalities.

And for intersectional sub groups of people with disabilities, urban residents and by age group. With census data, disaggregators based on disability and for intersectional groups, at national, regional, as well as district level.

So, what are the implications of being able to do such disaggregation at national and sub national level.

We recommend that DHS and population censuses should be regularly used to document and under understand the inequalities people with disabilities experience at national and sub national levels.

Overall in four sub groups, sub groups by sex, rural urban residence and age. Another implication is that a lot more disability disaggregated indicators could be used.

Many of the data sets in 125 countries have at least one data set with functional difficulty questions are designed to be representative of their populations at both national and regional levels.

So, data sets that were not analyzed in this report, could be explored for their potential to produce disability disaggregated indicators at subnational levels.

Finally, national Governments and international organizations need to allocate ongoing resources and capacity building towards disability data analysis for national statistics offices, and other stakeholders to analyze a growing body of data that can produce disability it disaggregated statistics at both national and subnational levels.

So, now, let me share a few of the results from the data analysis. Let’s start with the share of adults with functional difficulties.

First at the national level, the share of adults with any difficulty range in the 15 countries ranges across countries from 12% in Cambodia, to almost 33% in Uganda.

Within countries the share of adults with functional difficulties does vary from region to region. But at this sizable, meaning above 5% in the regions of the 15 countries.

So in other words, people with disabilities are not highly concentrated in certain regions and absent in other regions. They are spread out. So, I will show on my screen a table for Kenya.

We’re going to put the link in the chat box.

So, one moment. So you should see my screen and the table for Kenya.

So, for Kenya, the national share of persons with disabilities, stands at 12.7%.

And seeing and walking difficulties tend to be the most common types of difficulties nationally and within regions that a finding we have for other countries as well.

So, for example, here the first region in the table is the —— Baringo and 5.5 have seeing difficulties.

Scrolling down, in Nairobi,8.2% of adults have functional difficulties, while in the ——  16.7% have difficulties in the Migori region. There is some variation in the share of adults with difficulties across regions.

So, what are these implications, implications of these results.

For policy and research. So for policy disability rights as per the CRPD need to be uphold within countries in all regions, districts and villages.

Local policy making in general, or insect tors from education to poverty reduction needs to be inclusive of people with disabilities.

And take into account disability inequalities across and within geographies.

So we need more research as well on the variation of the share of persons with functional difficulties within countries to find out the extent to which demographic factors, resources, and environmental factors contribute to the variation.

Last but not least I will share in findings on disability gaps so that is inequalities, that we find when analyzing disability disaggravated indicators. So, we calculated the share of persons with who are multi dimensionally poor, that means persons who experience several deprivations such as having low educational attainment, not being employed, not having adequate living conditions, such as having poor quality flooring or not having electricity.

The multi dimensional poverty rate among persons with functional difficulties in the 15 countries is consistently high, so meaning above 50% at both national and regional levels.

And we find association between multi dimensional poverty and degree of functional difficulties in all the countries so in other words, persons with some difficulty have higher poverty head counts than persons with no difficulty, but lower rates of multidimensional poverty than persons with at least a lot of difficulty.

So I will just show you another map for —— analysis for Guatemala these maps represent the multi dimensional poverty rates the map to the left is the multi dimensional poverty rate of persons with disabilities in the middle it is for persons with some difficulty, and then to the right is for persons with at least a lot of difficulty.

So, the darker colors in the map in the middle and to the right illustrate how multi dimensional poverty is more common as a degree of functional difficulty increases.

So, this pattern is found for all regions of Guatemala, including in remote regions in the north.

But we also find it at the more local level when we do the analysis at the municipality level as I want to highlight briefly here on these maps.

So, in addition we find that among people with disabilities, adults and people in rural areas have average higher multi dimensional poverty head counts, many adults and people in urban areas respectively. For some indicators results suggest that disability gaps are consistently experienced.

Across and within countries. So that is for educational attainment, multi dimensional poverty for other indicators such as having safely managed water in house hold results do vary within and across countries and so perhaps here national estimates can hide a lot of variation within countries.

So, I will conclude with some implications of these results in relation to inequalities people with disabilities experience.

So, we need more research and data analysis, including mapping exercises to zoom in on the rights of persons with disabilities at the local level.

The barriers, people with disabilities face and the resources they have such as access to assistive technology and information vary across geographies and may contribute to diverse inequality.

Human rights outcomes within countries so understanding the drivers of inequality as well as enablers of inclusion is important to inform policies and reduce disability gaps.

Then finally, policies, programs and practices, no matter where they take place within a country, need to be inclusive of people with disabilities. At both national and subnational levels, people with disabilities and their representative organizations should be included in the policy making.

So, thank you very much. That was a little longer than planned, but thank you so much!