Sex, age, and disability data disaggregation (SADDD) – at first glance – does not look like an approach to simplify our work. And even at second glance, neither “sex” nor “age, let alone “disability” are straightforward categories.
If sex disaggregation uses a dichotomous approach of female/male, trans- or inter-sexual individuals or communities may be excluded. For instance, I recently came across an example from South Asia, where a group of transsexual people, living isolated from the rest of the community, were excluded from disaster-preparedness training, because in the specific cultural context, they could neither join the women’s nor the men’s group. And there was no budget for a third training. In other circumstances, however, it might put enumerators at risk if they even asked about “other” sexes.
For age, I think it’s pretty self-evident that there cannot be a uniform set of categories. While for a health or nutrition intervention we might need to know more about the situation of “infants” as a group, data collection related to livelihoods most probably needs a “youth” category. Age categories also have to take into account the local context – whether in terms of legal age (e.g. of consent), access to services (e.g. education) or life expectancy.
Finally, disabilities might be difficult for community members, local stakeholders or enumerators to identify when inquired about directly. It can also be challenging to draw the line between disabilities and chronic conditions. In addition, in many contexts, different types of disabilities may carry stigma, and, as a consequence, disabilities may be underreported.
Indeed, the devil is in the detail.
But why the hassle? Simply because an older woman, an adult man with a physical disability, a baby boy or a girl who is hard of hearing experience humanitarian emergencies differently. Or in other words: who do we program for if we don’t know who the affected individuals are? By basing our programming on SADDD, we can better know and meet different needs, and support individual coping and recovery. Our response becomes more specific and, thus, more effective.
Point taken?
So, how do we take the devilish complexity out of SADDD?
By copying from the experts.
Let’s look at disability. To get an instant boost in your data collection tool’s ability to identify disabilities, look at the Short Set of Disability Questions developed by the Washington Group on Disability Statistics. This six-question-tool provides a simple approach to identifying disabilities along core functional domains.
Try it out the Short Set of Disability Questions, and share your experience with us.
And remember: according to WHO, approximately 15% of the wold’s population lives with a disability. In the aftermath of a humanitarian emergency, the share of people with disabilities among the population is likely to increase due to injury and negative impacts on mental health. So, if the share of people with disabilities your data collection has identified is significantly below 15% – your tool might need improvement.
In this case – maybe we can help?
