Biology shows that disadvantage can accelerate aging, undermining not only health, but also children’s chances in school, their future work, and overall well-being
People the same age can age very differently. One may seem older, tired, and in poor health, while another feels youthful and full of energy. These differences are not just about the number of birthdays: they reflect biological aging, the rate at which our bodies wear down. Understanding why some people age faster than others, even in childhood, can help explain differences in health, education, and economic opportunity.
This is where epigenetics comes in. Although our DNA is fixed at conception, the way our genes are expressed can be influenced by our environment and experiences. This process, called epigenetics, works like a set of light switches turning our genes on or off. Factors like stress, poverty, parenting, and lifestyle leave marks on the “epigenome,” and these marks can affect long-term health, behavior, and development.
One of the most promising tools to measure this is the epigenetic clock. These clocks use changes in the epigenome to estimate a person’s biological age. If your biological age is higher than your chronological age, it suggests you’re aging faster, something that has been linked to worse health, higher risk of early death, and lower brain function. In this way, epigenetic clocks provide a powerful window into how life’s hardships “get under the skin.”
For economists, this opens new doors. Research has long shown that family background, education, and social conditions shape life chances. Epigenetic clocks add a biological layer: they help track how early-life experiences and inequality affect not just opportunities, but our bodies and brains themselves. In short, epigenetics offers a biological bridge between childhood environments and adult outcomes.
But there’s a challenge: different epigenetic clocks sometimes give different answers, making it hard to know which one to trust. In a recent IZA Discussion Paper, we address this by building a new, more reliable tool: the Multi EpiGenetic Age (MEGA) clock. This clock combines the signals from several widely used epigenetic clocks into a single, stronger measure, reducing noise and improving accuracy.
We applied the MEGA clock to a large UK study that has tracked children and their families over time. Three findings stand out. First, children exposed to abuse before adolescence show signs of accelerated aging, about half a year older biologically than their peers. Second, school entry rules matter: children from disadvantaged families who start school later than their peers display faster biological aging by age seven. Third, adolescents with accelerated biological aging are more likely, as young adults, to struggle with education, employment, and mental health.
These results suggest that biological aging is about more than health: it is closely linked to the development of skills, emotional well-being, and long-term success. Disadvantage does not just disrupt school performance; it can become biologically embedded, with lasting effects on a person’s life path.
By integrating epigenetic measures into economics, we gain a richer picture of inequality and human development. The MEGA clock helps make this possible by providing a more reliable and accessible measure of biological aging. Looking ahead, the challenge is to use these insights to design policies that improve early environments, protect children from adversity, and promote healthier, more productive lives.
© Giorgia Menta, Pietro Biroli, Divya Mehta, Conchita D'Ambrosio, and Deborah A. Cobb-Clark
Giorgia Menta is postdoctoral Researcher at the Luxembourg Institute of Socio-Economic Research (LISER), Luxembourg, and IZA Research Affiliate
Pietro Biroli is Associate Professor at University of Bologna, Italy, and IZA Research Fellow
Divya Mehta is Professor at the Queensland University of Technology (QUT)
Conchita D'Ambrosio is Professor at the Université du Luxembourg, Luxembourg
Deborah A. Cobb-Clark is Professor at the University of Sydney, Australia, and IZA Research Fellow
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We recognize that IZA World of Labor articles may prompt discussion and possibly controversy. Opinion pieces, such as the one above, capture ideas and debates concisely, and anchor them with real-world examples. Opinions stated here do not necessarily reflect those of the IZA.
Related IZA World of Labor content:
https://wol.iza.org/articles/what-is-the-role-for-molecular-genetic-data-in-public-policy by Weili Ding and Steven F. Lehrer
https://wol.iza.org/articles/early-life-medical-care-and-human-capital-accumulation by N. Meltem Daysal and Jonas Cuzulan Hirani
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