Jeroen Lakerveld started as a physiotherapist in the hospital in Utrecht. He ended up in the vascular department. “Almost all those people had type 2 diabetes and all those people smoked. When I picked them up from the smokehouse I thought: we are too late!” Then he started doing PhD research into lifestyle interventions. The frustrating thing was: what worked in controlled conditions did not work in real life. “I saw no effect at all, the health risks did not decrease. You can try to change someone's behavior, but it won't work if the environment doesn't change.”
And now Lakerveld has been focusing on that environment for thirteen years. In November, the Amsterdam UMC received 10.5 million euros to work with other European researchers to collect and analyze data for five years and to better identify the causes of obesity. OBCT calls the project: Obesity: Biological, socioCultural and environmental risk Trajectories. Simply put, the researchers look at groups of people with different backgrounds in different places. Why does one person become overweight and another not?
Isn't this an open-door investigation?
“At first glance it is simple, yes. It all has to do with lifestyle, exercise and nutrition, more energy goes in than goes out. But there are causes behind this behavior and there are various risk factors. In this project we identify genetic predisposition to becoming overweight. We also look at the socio-cultural environment: what is the norm for the people you interact with? Is it normal to eat on the couch in front of the TV? And we analyze the physical environment. For example, what is the density of fast food in a neighborhood, or what about the drivability?”
Drivability?
“In some areas, including in the Netherlands, you are practically pushed into the car. In East Groningen more than in Amsterdam, because the supermarket is far away, shops in the area are closed, everything is too far away to cycle and because you can easily park anywhere. In neighborhoods with high drivability diabetes is more common.
“Sometimes you find counterintuitive results or unhealthy factors go hand in hand with healthy ones. Take Utrecht Central Station. There is an overwhelming selection of unhealthy food, but it also has the largest bicycle shed in the world.”
What can you do with that data?
“It is important to show that this is really the case, so that policymakers can intervene. Differences between neighborhoods are relevant because everyone has been exposed and those factors are part of a system that contributes to health problems and inequalities. For example, you can create a map with a kind of dipstick and see which areas light up so that you know where intervention is most needed. At the same time, you also have to look for good comparison material and see over time whether an adjustment in the environment actually produces different behavior, or whether obesity subsequently decreases and ultimately less diabetes and cardiovascular disease occur.”
Are you also looking at 'blue zones', where people grow old healthily, such as in parts of Italy?
“We mainly focus on obesity, health risks and inequality. At the same time, you discover a lot about areas where things are going well. By the way, there is something interesting going on with those blue zones. Those things that made people live very long were often born out of necessity. Those healthy elderly people once had to start a vegetable garden out of poverty. Now it is cheaper to go to the supermarket and eat ultra-processed food.”
How do you map 28 countries?
“That is an enormous challenge. The Netherlands is a kind of living laboratory. There is a lot of data available on a small surface. Not only geographically, also from cohort studies and, for example, from the Central Bureau of Statistics. With the help of our geographers, we can enrich this with environmental data to conduct epidemiological research. The Netherlands also has many differences: city and countryside, socio-cultural… you also need those differences to explain the distribution in datasets.
“If you want to compare countries, high-resolution local data is not of much use, you have to look for data that measures in the same way. It is very complicated to get datasets for something like socio-economic status of a neighborhood or fast food exposure to be uniform.”
What do you do with genetic data?
“You not only want to know to what extent there is a genetic predisposition to obesity, but also how the interaction between genes and the environment works. We translate that data into a screener: a version for healthcare providers and one for ordinary people. Suppose we have your zip code, then we can see how strong the exposure to unhealthy factors is in your area. It is also useful to know where else you go often, such as where you work. And we'll take some cheek swab to see your genetic makeup. This gives you a holistic view of your risks and what you can do to reduce them.”
How far can you zoom in on the map?
“Up to about a hundred by a hundred meters. This scale provides sufficient opportunities to study relevant exposure areas around residential addresses. A good size is difficult to determine. Some people stay close to home, others have a long range. Another point is: people don't live where they live by chance. Anyone who has a dog and enjoys running will choose a neighborhood that suits that. So if you link the physical activity friendliness of the neighborhood to the behavior of residents, you may encounter reverse causality. These are all challenges for my field.”
You call yourself an upstreamist. What is that?
“A story. Three men are sitting by a river when they hear a child screaming in the water. They jump into the river and save the child. Then another one comes, and soon they are in the water saving all those children. One makes a raft with which he rescues a few at a time, the other throws a rope to children out of his reach. The third walks away. Upstream he sees children falling into the water near a broken bridge. He repairs the bridge so that no more children fall into the water.
“Translate that to chronic conditions of today. We are pulling people out of the water with chronic diseases caused by high blood pressure and cholesterol caused by unhealthy lifestyles. This is due to a lack of knowledge, perseverance and skills. This is in turn influenced by the environment. You can give a child with asthma a puffer, but you also need to know whether there is moisture in the house, what the housing association does and whether the house is next to a highway. You have to tackle the causes of the causes.”
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