12 min
Nature, nurture and our later life outcomes: new insights on inequality over the lifecourse DIAL
-
- Educación
In Episode 2 of Series 4 of the DIAL Podcast, we are in discussion with Professor Hans van Kippersluis from the Erasmus University in Rotterdam. Hans, a professor of applied economics, is the Principal Investigator on the DIAL project, Gene Environment Interplay in the Generation of Health and Education Inequalities, which has used innovative methods and data to explore the interplay between nature and nurture in generating health and education inequalities.
Transcript
Christine Garrington 0:00
Welcome to DIAL, a podcast where we tune in to evidence on inequality over the life course. In series four, we're looking at what's been learned from some of the DIAL projects about how and when inequality manifests in our lives, and what its longer term consequences might be. For this second episode of the series, we're delighted to be joined by Hans van Kippersluis, Professor of Applied Economics at the Erasmus University in Rotterdam. And Principal Investigator of the DIAL project, Gene Environment Interplay in the Generation of Health and Education Inequalities - put more simply nature versus nurture. So Hans, welcome to the podcast. And I wonder if you can start by talking us through what researchers working on this project have actually been looking into.
Hans van Kippersluis 0:42
What we've been doing in this project is essentially incorporating the recent availability of genetic data into social science and most prominently economic analysis. And so most of our work has focused on the interplay between genes and the environment. So in the introduction, you mentioned nature versus nurture, but actually more accurately, what we're doing is nature and nurture jointly into how they shape essentially education and health outcomes. And I think this is also the main innovation of our project, because biologists have studied nature before; social scientists have of course, extensively studied nurture, but not many have studied the interplay, the interaction between the two. And I think this was sort of the main innovation for why we got the funding some five years ago. And so what we have done is mostly studying this interplay. But along the way, we have also made some methodological contributions to a field which is very new. Then we've also used genetic data to test all their theories, and also, I think, enrich the framework of equality of opportunity.
Christine Garrington 1:35
Yeah, fantastic project. And as you've just said, you've made unprecedented use of genomic as well as survey data in the research, tell us a bit more about the information that you've been able to access? And how you've been able to use it?
Hans van Kippersluis 1:47
Yeah, sure. So the interesting thing is that more and more social science datasets, so data sets that have been traditionally used by social scientists, and these are mostly extensive surveys, are now collecting DNA information from their respondents. And this is often from blood or saliva. And what they did is basically, so more than 99% of DNA is the same across human beings. And so what we are using is only this remaining less than 1% of the variation. And these are called snips. And snips are points of your DNA that differ across human beings. And there's roughly 1 million of them. And so what we do, basically also other people have done is sort of aggregating these tiny effect sizes into an index. And this is called the polygenic index. And this is telling us something about your genetic predisposition towards a certain outcome. And this is quite interesting, because this data, this new variable, essentially can be added to existing datasets. And so we have a wealth of information that has been collected in the past on surveys on existing data. And then we simply add one indicator, one new variable. This is telling us something about people's genetic predisposition. And just to be clear, this is not like a deterministic variable. It also exhibits quite a b
In Episode 2 of Series 4 of the DIAL Podcast, we are in discussion with Professor Hans van Kippersluis from the Erasmus University in Rotterdam. Hans, a professor of applied economics, is the Principal Investigator on the DIAL project, Gene Environment Interplay in the Generation of Health and Education Inequalities, which has used innovative methods and data to explore the interplay between nature and nurture in generating health and education inequalities.
Transcript
Christine Garrington 0:00
Welcome to DIAL, a podcast where we tune in to evidence on inequality over the life course. In series four, we're looking at what's been learned from some of the DIAL projects about how and when inequality manifests in our lives, and what its longer term consequences might be. For this second episode of the series, we're delighted to be joined by Hans van Kippersluis, Professor of Applied Economics at the Erasmus University in Rotterdam. And Principal Investigator of the DIAL project, Gene Environment Interplay in the Generation of Health and Education Inequalities - put more simply nature versus nurture. So Hans, welcome to the podcast. And I wonder if you can start by talking us through what researchers working on this project have actually been looking into.
Hans van Kippersluis 0:42
What we've been doing in this project is essentially incorporating the recent availability of genetic data into social science and most prominently economic analysis. And so most of our work has focused on the interplay between genes and the environment. So in the introduction, you mentioned nature versus nurture, but actually more accurately, what we're doing is nature and nurture jointly into how they shape essentially education and health outcomes. And I think this is also the main innovation of our project, because biologists have studied nature before; social scientists have of course, extensively studied nurture, but not many have studied the interplay, the interaction between the two. And I think this was sort of the main innovation for why we got the funding some five years ago. And so what we have done is mostly studying this interplay. But along the way, we have also made some methodological contributions to a field which is very new. Then we've also used genetic data to test all their theories, and also, I think, enrich the framework of equality of opportunity.
Christine Garrington 1:35
Yeah, fantastic project. And as you've just said, you've made unprecedented use of genomic as well as survey data in the research, tell us a bit more about the information that you've been able to access? And how you've been able to use it?
Hans van Kippersluis 1:47
Yeah, sure. So the interesting thing is that more and more social science datasets, so data sets that have been traditionally used by social scientists, and these are mostly extensive surveys, are now collecting DNA information from their respondents. And this is often from blood or saliva. And what they did is basically, so more than 99% of DNA is the same across human beings. And so what we are using is only this remaining less than 1% of the variation. And these are called snips. And snips are points of your DNA that differ across human beings. And there's roughly 1 million of them. And so what we do, basically also other people have done is sort of aggregating these tiny effect sizes into an index. And this is called the polygenic index. And this is telling us something about your genetic predisposition towards a certain outcome. And this is quite interesting, because this data, this new variable, essentially can be added to existing datasets. And so we have a wealth of information that has been collected in the past on surveys on existing data. And then we simply add one indicator, one new variable. This is telling us something about people's genetic predisposition. And just to be clear, this is not like a deterministic variable. It also exhibits quite a b
12 min