How to collect and report data by sex, age and disability

What is disaggregated data and why does it matter?

Disaggregated data is data split into groups. Instead of "1,200 people received training", you report how many were women and men, how many were children, adults and older people, and how many had a disability. The humanitarian short form is SADDD: sex, age and disability disaggregated data.

Totals can hide problems. A project may report that it reached 80 percent of its target while missing almost every older person or person with a disability. Without a split, you cannot see it. IFRC guidance describes SADDD as a way to make programmes more inclusive and more effective. It is also a common donor requirement.

What should you collect?

Collect these three items for each person your project reaches, or for each person in a household you survey:

• Sex. Record female or male, as your donor and context require. Ask the person, rather than assuming.
• Age. Record the age, or put it into bands. Use the same bands in every form and report. The Myanmar cash working group PDM tool, for example, uses 0 to 17, 18 to 59 and 60 and over. Check what your donor asks for, and add finer bands, such as splitting children by age, if you need them.
• Disability. Use a standard method, described next.

Record these at the individual level. A household-level answer such as "this household has a disabled member" does not tell you which person, or how many.

How do you measure disability?

The Washington Group Short Set (WG-SS) is the standard tool used by many agencies. It asks adults six questions about difficulty doing basic activities, even when wearing glasses or using a hearing aid: seeing, hearing, walking or climbing steps, remembering or concentrating, self-care such as washing or dressing, and communicating in the person's usual language. Each has four answers: no difficulty, some difficulty, a lot of difficulty, or cannot do at all.

Points to remember, from World Bank and Washington Group guidance:

1. Ask all six questions. In a very rushed assessment, the first four may be used as a second-best option, but this will miss some people and must be reported openly.
2. Use the usual cut-off. The Washington Group recommends "a lot of difficulty" or "cannot do at all" for the main disability measure. Including "some difficulty" gives a broader group, which can help if your aim is wide inclusion.
3. Do not say the word "disability" first. Mentioning disability before the questions can change the answers. Train enumerators to read the questions as written.
4. Know the limits. The questions do not identify every person with a disability and do not tell you about health conditions. They are a screening tool, not a diagnosis. They should be complemented by information on barriers and accessibility.
5. Use the child module for children. A separate Washington Group and UNICEF module exists for children aged 2 to 17.

Should you always collect it? Five checks

The Washington Group and WFP researchers suggest five questions before you start:

1. Purpose. Do we know why we need this data and how it will help the programme?
2. Buy-in. Are the staff who collect and use it willing and trained?
3. Feasibility. Can we collect it properly in our time and setting?
4. Quality. Can we pilot the questions and check the data?
5. Analysis and action. Do we have a plan to use the results?

A "no" is not a reason to skip disaggregation. It shows what to fix first. In one example from the WFP review, staff collected disability data from hotline callers but never analysed it, so they moved the collection to post-distribution monitoring, where it better served their aim.

How do you report it?

1. Show the split in every key table. Do not leave it in an annex. A table of "people reached" should have columns for sex and age band, with disability marked.
2. Compare with the population. If women are 52 percent of the target community but 30 percent of participants, ask why.
3. Check that the numbers look reasonable. Disability is generally more common among women and older people, and is often more common after conflict. If your data shows the opposite, check for errors.
4. Explain gaps and actions. Write what you will change, such as moving a venue, changing the time of day or adding a sign language interpreter.
5. Mind small numbers. If a group has only a handful of people, report counts rather than percentages, and avoid details that could identify someone.

Our guide on post-distribution monitoring shows where the split fits in a survey, and disability inclusion in humanitarian action goes deeper on programming.

How do you keep the data safe?

Sex, age and disability are sensitive. In some places, disability data could cause stigma. Collect it with consent, tell people why you ask, store it securely, remove names before sharing datasets and limit who can see raw records.

How EMPO can help

EMPO is a reliable training and consultancy provider in Yangon and one of Myanmar's leading names in practical training for NGOs and CSOs, with 1,200+ people trained and 15 partner organisations. We train teams in MEAL, gender equality and data collection, online or in person across Myanmar, in English and Burmese. See our training services or contact us to plan a session.

Sources

• Disability Data — IFRC Protection, Gender and Inclusion
• Should you use the WG questions in your humanitarian programming? A tool to help you decide — Washington Group on Disability Statistics, 2022