Counting what matters: why child marriage data is more than numbers
Our Senior Data, Evidence and Policy Officer, Rachael Hongo, reflects on the importance of non-traditional data sources for surfacing hidden realities – and what's currently going right in the child marriage data landscape.
This is part one of our blog series 'Counting what matters: reflections on the child marriage data landscape'. Read part two here
Two years ago, in Bungoma County, west Kenya, Sally Wuodi and her team at Rural Women Peace Link noticed a troubling rise in teen pregnancies. But this wasn’t flagged in any national survey. The data came from community scorecards, from conversations with elders, from listening. What they uncovered was a deeply rooted belief: that older men could regain youthfulness by marrying younger girls. It was painful. And it wasn’t in any database.
Meanwhile, more than 8,000 kilometres away, in Jharkhand state, east India, Priyanka Paul and her colleagues at Savera Foundation work in mica mining communities where birth certificates are rare and school records often manipulated. Verifying a girl’s age, which is essential in child marriage cases, is nearly impossible. With limited resources and capacity, Priyanka’s team have instead had to build their own data systems, grounded in trust and survivor networks.
"[Citizen-generated] data is doing more than just filling gaps: it’s also challenging power structures and making invisible realities visible."
Rachael Hongo, Senior Data, Evidence and Policy Officer at Girls Not Brides
These aren’t just stories; they’re lived realities shared by two Girls Not Brides members during our recent learning webinar ‘Beyond the usual data: using alternative sources of evidence to address child marriage’. They remind us that data is not only about measurement, but also about meaning. It’s about who gets seen, whose experiences get recorded, and who gets left out.
This blog series is my reflection on those realities. It’s about what’s working, what’s not, and what we must do to build data systems that truly count girls in.
The wins: what’s working
Over the past two decades, the child marriage data landscape has expanded in a number of meaningful ways:
National surveys are reaching more people
Surveys like the Demographic and Health Surveys (DHS) and Unicef’s Multiple Indicator Cluster Surveys (MICS) have expanded their reach and now include more disaggregated data by age, region, and sometimes even marital status. This has helped paint a clearer picture of where child marriage is most prevalent and who is most affected.
Example:
The DHS and MICS programmes have been instrumental in generating comparable national statistics on child marriage in nearly 200 countries, making it possible to compare regions, and informing what’s happening globally. This has helped governments and NGOs target interventions more effectively.
Unicef use this data to collate and communicate prevalence and burden statistics. And at Girls Not Brides, we in turn draw on this for our ‘Child marriage atlas’, which presents the statistics with contextual information for 203 countries and regions around the world.
Unfortunately, however, these systems are currently under threat due to funding cuts – something that has highlighted the fragility of the child marriage data infrastructure. Going forward, we may need to look to alternative data sources to determine country prevalence and burden.
Routine data systems are growing – and legal identity is key
Countries are increasingly investing in routine data systems like child protection information management systems (CPIMS), school attendance tracking systems, and health facility reporting systems. These allow for more real-time monitoring and can be integrated into programme design and used to monitor child marriage risks.
Example:
In Kenya and Malawi, CPIMS have helped local child protection officers track cases and link them to services – something that isn’t possible with periodic surveys alone.
But one foundational element is often overlooked: legal identity.
A well-functioning civil registration and vital statistics (CRVS) system can prevent child marriage by:
- Providing legal proof of age through birth registration.
- Requiring formal registration of all marriages.
- Enabling implementation of marriage laws and other relevant laws.
In many countries, CRVS reforms are helping link birth and marriage records, making it harder to falsify age and easier to flag underage marriage attempts before harm occurs. Legal identity isn’t just a technical fix; it’s a protective tool. Without it, child marriages are more likely to go untracked, unchallenged, and unaddressed.
Citizen-generated data is gaining recognition
UN Women’s Women Count initiative and the Global Partnership for Sustainable Development Data (GPSDD) are helping shift the narrative around gender data. They emphasise the importance of citizen-generated data – such as the community scorecards used by Sally Wuodi and her team in Bungoma County, Kenya – to fill gaps and influence policy.
But this kind of data is doing more than just filling gaps: it’s also challenging power structures and making invisible realities visible.
Example:
In Kenya, Women Count supported the country’s first time-use survey and national care assessment. This helped surface the invisible labour and gendered inequalities that traditional data systems often overlook.
GPSDD’s work in the Global South, meanwhile, has shown how citizen data can drive policy change, especially when local voices are integrated into national systems. Their ‘People Power’ initiative highlights how inclusive data practices can lead to more equitable decisions.
More importantly, governments and NGOs increasingly recognise that averages conceal inequality. Breaking down data by age, location, or socioeconomic status has sharpened programmes and advocacy.
Data used as evidence for advocacy and learning
Data is now central to shaping laws, policies, and investment priorities. For instance, child marriage prevalence statistics have informed global campaigns and country strategies alike. There’s growing recognition that “data is power”. Organisations are using evidence, not just for reporting, but also to influence budgets, policies, and public discourse.
Example:
In Kenya’s Bungoma and Uasin Gishu counties, local data collected by civil society groups helped secure increased budget allocations for gender-based violence prevention and child protection.
But as Priyanka Paul from Savera Foundation reminds us:
“We have to create our own evidence, because the systems don’t see us."
Her words underscore that, even as availability grows, communities still have to innovate to fill the gaps left by formal systems.
Read part two of this blog series to find out what's not working, and what we need to do about it.
In the time it has taken to read this article 60 girls under the age of 18 have been married
Each year, 12 million girls are married before the age of 18
That is 23 girls every minute
Nearly 1 every 2 seconds
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