Capturing Poverty Through a Gender- and Age-Sensitive Lens
By UNICEF - Clara Ceravolo, Clara Praschl, Charlotte Bilo, Lauren Whitehead, Lauren Pandolfelli, Enrique Delamónica, Solrun Engilbertsdottir and Seda Karaca Macauley
Imagine a 15-year-old girl living in poverty. Her family, struggling with limited resources, had to pull her out of school to prioritize her two brothers' education. Now, she stays home to help with household chores, facing uncertain prospects for her future. Sadly, this scenario is a harsh reality for many girls around the world.
“Girls, boys, women and men experience poverty differently. When we group their experiences together, we lose sight of the specific impacts of poverty based on age and gender.”
A gap in reliable detailed data on the specific needs of different populations makes it challenging to design effective policies, such as social protection programmes. Fortunately, many countries collect and harmonize data that captures these age and gender differential experiences and properly measure poverty at the individual child level, which allows for comparisons among boys and girls. However, in most countries additional efforts are needed.
1. Who is most likely to live in poverty and why?
Globally, women and girls are more likely to live in monetary poverty than men and boys across the life course. For example, 9.8 per cent of women and girls struggle to survive on less than PPPU$2.15 per day, compared to 7.6 per cent of men and boys. This means over 24.3 million more females are in this situation. Climate change worsens this; food insecurity is projected to affect 236 million more women and girls, compared to 131 million more men and boys, impacting their livelihoods and economic opportunities, and pushing many further into poverty.
This pattern is rooted in historic and systemic gender discrimination contributing to the feminization of poverty. For example, despite progress in education, in 2023, 60 million more girls were out of school at the upper secondary level. Globally, adolescent girls aged 15-19 are more likely than boys to not be in education, employment, or training (28 per cent vs. 13 per cent). The lack of education and employment opportunities combined with unequal distribution of unpaid care and domestic work affects a young woman’s labor force participation and lifetime earnings. Up to 708 million women are outside the labor force due to care responsibilities, making unpaid care work a clear gender barrier to economic security. Women who continue working are disproportionately represented in the informal sector where wages are lower, fewer protections exist, and benefits such as pensions and workplace family-friendly policies are out of reach. These factors drastically increase the risk of poverty throughout their lives.
Age is another major factor in poverty, with nearly 1 billion children living in multidimensional poverty and over 300 million surviving on less than PPPUS$ 2.15 per day. Children are twice as likely as adults to live in households in this situation. Child poverty is a global issue, affecting even high-income regions like Europe, where one in eight children live in poverty.
When age, gender, and other factors intersect, the risk of inequality and poverty increases, especially for adolescent girls. Girls face discriminatory social norms and gender and age barriers from the early years. For example, young girls are more likely than boys to be drawn into child marriage with older partners. Nearly 1 in 3 women and adolescent girls aged 15 and above have experienced intimate partner violence. Around 500 million women and girls lack access to menstrual products or hygiene, and 427 million children lack basic sanitation at their school. This limits mobility and access to education especially for adolescent girls who are often kept at home to perform chores as a result. Additionally, households that cannot afford school fees often favour to send boys rather than girls to school due to gender norms and earnings expectations, with a steeper drop off for girls at secondary school levels.
Child marriage, often linked to dropping out of education, is driven by poverty. In Eastern and Southern Africa, 47 per cent of women aged 20 to 24 in the poorest quintile were married before age 18, compared to 14 per cent within the wealthiest quintile. Poverty and gender also disadvantage boys, with child labour higher for boys (97 million) than girls (63 million), driven by poverty.
2. What is the main data challenge?
A major challenge to measuring poverty from a gender perspective is that most data is collected at the household level. While efforts have shifted to focus on individuals, current indicators still provide limited insights into gender- and age-specific experiences, often making certain dimensions invisible.
For example, monetary measures often rely on household-level data assuming equal resource distribution among members, which is often not the case. This means even per capita measures fail to capture the gender- and age-specific needs, like higher caloric requirements or varying healthcare and education expenses. While equivalence scales can better reflect individual needs, their use in global poverty monitoring is complex due to a lack of consensus on the best scale across different countries.
Monetary poverty assessments often miss the complex experience of women and girls. Multidimensional child poverty measures which include deprivations in education, health, nutrition, housing, and WASH do capture the material deprivations experienced by each child , independent of parents’ income. These measures help us understand which children within households are deprived since the data are collected at the individual, not household, level as well as the connection between child poverty and non-material deprivations like the effects of gender-based violence or time poverty due to caregiving, which disproportionately affect women and girls.
However, until recent innovations in MICS modules, many surveys omitted critical issues such as period poverty, which have economic and social consequences. Period poverty prevents girls from attending school or work, increases stigma and harmful social norms and can lead to early sexual debut, early pregnancy, and child marriage.
3. What can be done to strengthen data collection and use on poverty?
To address the lack of sex- and age-disaggregated data on monetary poverty, we need more routine disaggregation by household composition. Disaggregating household-level data by sex or age alone is inadequate. It is encouraging to see efforts to collect consumption and expenditure data at the individual level, although this is more resource-intensive and complex. Another important area is measuring individual asset ownership to construct wealth profiles. The UNSD EDGE project[1] on measuring asset ownership helps highlight gender disparities in economic security and resource control.
For multidimensional child poverty, sex- and age-disaggregated data collection is essential for a more accurate understanding of poverty dynamics. This is one of the main reasons why, for years, UNICEF has been advocating for—and actively measuring—a child-centered metric of poverty that goes beyond simply disaggregating or extending household poverty estimates. When data availability allows such measurement, intra-household differences and sub-population trends can be better analyzed. Specific indicators relevant to women and girls should be included. For example, UNICEF’s Multiple Indicator Cluster Surveys (MICS) measure menstrual hygiene management through access to menstrual products and a secure, clean place to change. Analysis shows higher poverty rates among adolescent girls than boys when these factors are considered. For instance, in Suriname, girls experience 80 per cent higher poverty rates, while in Kiribati and Sierra Leone, the gap is around 20 per cent. Including more gender-informed indicators can better capture differences in material deprivation due to inequality.
To collect gender- and age-relevant data, we must think carefully about how to make the invisible visible. This means finding cost-effective ways to complement multidimensional poverty surveys with more targeted approaches, such as Time-Use Surveys, Social Norms Surveys, and Violence and Safety Surveys. These surveys can be expensive and resource-intensive, but modular approaches added to existing surveys can help.
Better data collection can help us design effective social protection policies that address age- and gender-specific deprivations. When done right, these policies and programmes can advance gender equality, economic security and reduce child poverty.
“Join us at UNICEF in our mission to enhance data collection and ensure that the diverse needs of all age and gender groups are recognized and addressed.
This effort is not just about better data - it is about creating a world where every child, regardless of gender or age, can live free from poverty. Together, we can create an inclusive future for all.”
[1] UNSD EDGE Project, led by the United Nations Statistics Division and UN Women, is an initiative aiming at improving the integration of gender issues into the regular production of official statistics for better, evidence-based policies.
About the authors (all UNICEF):
Clara Ceravolo, Social Protection and Gender Consultant
Clara Praschl, Carlo Schmid Fellow (at the time of writing)
Charlotte Bilo, Child Poverty and Social Protection Consultant
Lauren Whitehead, Social Protection and Gender Lead
Lauren Pandolfelli, Statistics Specialist
Enrique Delamónica, Senior Adviser, Statistics and Monitoring
Solrun Engilbertsdottir, Social Policy Specialist
Seda Karaca Macauley, Communication Specialist