The missing data of older women

As experts from across the world came together this month for the UN’s largest gathering on gender equality and women’s empowerment, the 68th Commission on the Status of Women , I reflected on the great women who have inspired me throughout my life. I was blessed to be guided by two grandmothers, both fiercely independent in their own way. A mother, both tough and kind, who has taught me so much and is the glue that holds our family together. An incredible older sister to look up to throughout my life, my number one rival but always ready to catch me if I fall. Matriarchs are the foundation of many families and society more broadly, so why is it that when we look at the data and statistics that underpin both our world and international development, the insight, needs and value of these matriarchs are so hard to find?

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It was back in the distant days before the pandemic that I first read the incredible book Invisible Women by Caroline Criado Perez – a text that made me so angry I could only read it in short bursts! Criado Perez laid bare the data gap around women and the impact that living in a world designed and shaped by data on men has on women. From the size of smartphones and the length of toilet queues, to misdiagnosed heart attacks and serious road traffic injuries, data informs decisions that create the world around us.

This gap in data on women has led to systemic discrimination and a profound negative impact on women’s lives. This is especially true for older women who are among the most invisible in data. Just one example of policy decision-making not being informed by data from my home country is the National Health Service in the UK ceasing smear tests for cervical cancer once patients reach 60, as highlighted by broadcaster Mariella Frostrup . This is despite the fact that one in five women diagnosed with cervical cancer are aged over 65 .

The theme of this year's Commission on the Status of Women is ‘accelerating the achievement of gender equality and the empowerment of all women and girls by addressing poverty and strengthening institutions and financing with a gender perspective ’ and I believe that better documenting older women’s needs and experiences is essential in achieving this.

Why accounting for older women in development is so important, and why it’s lagging behind

The world is aging rapidly; the global median age increased from just over 20 years in 1970 to just over 30 years in 2022. In 2018, the number of people aged 65 years and above surpassed the number of children aged under five years for the first time in history. Of this aging population, women represent the majority of older people, especially at advanced ages . Not only are there many more older women, but the role they play in families and society is important and will only grow as society continues to age.

Older women are essential members of family and community units, providing both support and leadership. They take care of younger and older family members, grow food, and earn money, often in labour-intensive informal work. They contribute to communities’ social capital as well as directly to the economy. Research has shown the vast impact older women have, especially when contributing to the labour force. In low- and middle-income countries one in seven women over 65 is part of the labour force, increasing to two in five in areas across sub-Saharan Africa.

But these women tend to be invisible to policymakers due to the double hindrance of significant gaps in gender data and data on older people. The gender data gap means that less than half the data needed to measure progress against Sustainable Development Goal 5 on gender equality is available. Women face barriers to inclusion in even the most basic data, which is exacerbated as women get older. For example, efforts to improve Civil Registration and Vital Statistics (CRVS) often focus on birth registrations, but the lack of data on marriages, divorces and cause of death has a significant impact on both the rights of older women and our understanding of their health outcomes.

When data on older people is captured it often focuses on purely economic indicators, with a common focus being the importance of counteracting an aging population to ensure the working age population has fewer ‘dependent’ people to support. But even the economic data is painting an incomplete and incorrect picture. For example, the ‘working-age’ population frequently has arbitrary cut-off points such as 60 or 65 when we know that many people continue to work long past this age and labour force surveys invariably underestimate informal work, the majority of which is carried out by women globally. Data on the care economy regularly leaves out grandmother carers and focuses on older women only as people that need care, rather than providing it.

Despite these glaring gaps around the lived realities of older women, when we bring the voices of women into international policy processes such as the 2030 Agenda’s Sustainable Development Goals (SDGs) and the Generation Equality campaign, the voices of older women are often absent, and their concerns neglected . The development community must improve this.

How the development community can do better by older women

We at Development Initiatives have been thinking about how we can address some of these key gender and age data gaps. What is clear is that the development sector needs to be better at implementing an intersectional lens that uncovers the needs, outcomes and experiences of women throughout their lives. This would mean:

• Taking a life-course approach to foundational data ecosystems by creating longitudinal datasets that track and capture data on individuals throughout the course of their lives. For civil registration and vital statistics, this means focusing not only on birth registration but also on the registration of marriages, divorces and deaths.
• Going beyond traditional household surveys to use alternative data sources collected at the individual level , thus facilitating better disaggregation of data by sex and at ages over 50.
• Harnessing a citizen- and community-driven data approach as a way to create meaningful consultation with older women and facilitate targeted action at the community level that is empowering and creates agency.

We have been looking at assessing gender data throughout its lifecycle – from collection and storage to analysis and use – and have identified opportunities to address power imbalances and issues of rights, privacy and ownership of data at all stages: from participation in decision-making around data policies, governance and financing, to involvement in decisions around data accessibility and use. At each of these stages we can apply an intersectional gender and age perspective to improve the data ecosystem and ensure women are represented in all stages of their life. Changes would include:

• Examining gender inequalities in the staffing and leadership of data agencies such as national statistics offices.
• Looking at how processes for data collection can be more sensitive to cultural and social stereotypes that may introduce bias into the data.
• Trying to advance the use of data, particularly by women’s rights organizations .
• Ensuring practical guides and tools such as The Gender Data Compass are fully adopted and mainstreamed by national statistical offices.

Older women serve their communities as sisters, daughters, mothers, grandmothers, workers, carers and much more, yet documenting their vast experiences and contributions remains, unfortunately, unprioritised. At the time of writing, the 68th Commission on the Status of Women has not acknowledged explicitly the need to invest more in representing older women, despite including language in the zero draft on the need to disaggregate data by a wide range of factors, one of which was age. I hope that as the conclusions are agreed there are concrete recommendations to address this gap and strengthen the gender data ecosystems to ensure that no one – including older women – is left behind.

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Read more from Claudia Wells on X.

This blog was first published by the Global Partnership for Sustainable Development Data in their Data Values Digest .