Mobile Data and the 'Holy Grail' in Obesity Research

Mobile Data and the Search for the 'Holy Grail' in Obesity Research

; Donna Spruijt-Metz, PhD

Disclosures

January 26, 2016

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Editor's Note: In this One-on-One interview, Medscape Editor-in-Chief Eric J. Topol, MD, talks to Donna Spruijt-Metz, PhD, an expert in pediatric obesity, about how mobile data collection and wearable sensor technology can potentially reduce the epidemic of "diabesity" in the United States.

Searching for Better Data Collection

Eric J. Topol, MD: Hi. I'm Eric Topol, editor-in-chief of Medscape, and I'm very pleased to welcome Donna Spruijt-Metz from the University of Southern California. We're going to be talking about her program in mobile health and obesity. Donna, tell us a little bit about your background and how you got into working in mobile connected health.

Donna Spruijt-Metz, PhD: My background is in obesity research, predominantly childhood obesity. A long time ago, before the term "mobile health" existed, I was doing an in-lab study where I brought overweight Hispanic and African American kids into our lab, where they had 2 days of after-school exercise, nutrition classes, and motivational interviewing. We collected data like good researchers, pre- and post-intervention. As this intervention unrolled and I was on the ground, in the trenches with these kids, I realized that we have all of these data on them that we could be using, but we don't even look at them until the trial is over.

Not only that. I was talking to one of the kids for the motivational interview—and we're doing a randomized controlled trial, so everybody has to get the same treatment—and I knew that she was about to head into a full hour of talking about sugar-sweetened beverages and why they're bad. I had just spoken with her and knew that she doesn't drink them. She had other vices, but not sugar-sweetened beverages. I thought to myself, we're going to lose this kid and we're not using the data that we have. And there weren't any accelerometers in the first and last weeks. We could be having that data all the time. There's got to be a better way, and that's what got me started.

Dr Topol: So that was the impetus to bring in mobile data collection from the real world in these kids representing minorities?

Dr Spruijt-Metz: Right.

Real-Time Interventions

Dr Topol: What have you learned from this?

Dr Spruijt-Metz: The kids that I work with love the real-time attention. When we intervene using real-time new technologies, they are in communication with us. One of my real-time interventions is what we call Just-In-Time Adaptive Intervention. "Just in time" because it's in context, which is so important. It's when you need it. We are intervening in these kids' sedentary behaviors—not having them come in and telling them, "You must be less sedentary," but sensing that they've been sedentary for a certain amount of time and texting them to let them know that it's time to get moving.

Dr Topol: Do you have to give them a smartphone?

Dr Spruijt-Metz: It depends. For some of the research that we're doing now, we use our own phones, so they have to have an Android phone, for instance, to be in a particular study. For others, we give them phones. We also have deployable sensors in the home to try to understand their behavior in the context of the family.

The Holy Grail of Obesity Research

Dr Topol: Recently there was a study that you may have seen in Cell Metabolism,[1] where the Salk Institute in La Jolla made a smartphone app that helps to collect information on all of the food that one eats during the day. They found that people eat all day long, not just in three meals, and particularly in the evening. Wouldn't it be nice if we had a way to passively detect what people are ingesting?

Dr Spruijt-Metz: That is, in obesity research, the wicked question.

Dr Topol: It's the Holy Grail that's missing?

Dr Spruijt-Metz: It's the Holy Grail. There are a number of different efforts around that. There are two best measures that we have. There is doubly labeled water: You drink isotope-labeled water and then give me all of your pee for the next 10 days. That's fun and kids love it—no. Also, it gives us energy in and energy out, but we don't know what they're eating.

Right after that gold standard is 3-day dietary recall, which is unreliable at best. It's not so much that people lie, but they don't remember what they ate. They don't know what was in the food. Even if we call them with the best dietitian support for 3 days, they're not reliable. It's downhill from there.

In a couple of labs in Hawaii and Pittsburgh, they have been trying to do photo capture and then machine learning of recognition of the food on the plate. I think it's a rabbit hole.

Dr Topol: It's a tough one, isn't it? Well, let's hope that someday that technology will evolve. I've seen some things like trying to look at the conductance of tissues. People are definitely trying it, but as we say, this is a difficult feature.

Dr Spruijt-Metz: Well, the question is, I'm beginning to think, do we need to know? To understand the metabolism, it's important to know what people eat—exactly what they eat. Then you might want to do a controlled feeding study. But to understand and change behavior, we might not need to know that. I don't know. My jury is still out.

The Challenge of Changing Behavior

Dr Topol: I did want to get into that with you, Donna, about changing behavior, the ultimate challenge. The hope is that, through mobile connectivity, there would be feedback loops and a new way to intervene. Not just getting data on things like activity; you would also have the ability to gamify it, to have managed competitions with peers and neighbors, Facebook friends, whatever, and you would be able to incentivize it, whether it's with finances or other means. Do you think that we're going to be able to crack the case? Obviously, obesity is such a dominant problem and it's horrible to see the rate in children. Could this be a way, with these other tools that are on top of smartphone connectivity, to finally start to tackle the behavioral issue?

Dr Spruijt-Metz: I think that only a smartphone will never be enough. It's just a gadget.

It needs to be smart. It needs to have some good artificial and real intelligence behind it. I think that it'll always be a combination of smartphones and sensors, either wearable or deployable, so that we know what people are doing and can adapt in real-time to their personal needs. It's personalized. Precision behavioral medicine is what we're getting, what we can do now in real-time with these technologies. Do I think gamification will help? I don't know. I've developed some games. I've worked in that field.

Dr Topol: Especially with kids, you would think.

Dr Spruijt-Metz: Developing a good game is very difficult. It has to be darn slick before it's going to work. Even Angry Birds—at some point, people get tired of it. I think gamification has something else to offer that's very cool, though, which is that you can use it as a tool to teach things to kids without having to test them.

Dr Topol: Or feeling that they're having to go through educational maneuvers.

Dr Spruijt-Metz: You can just watch what they're doing from the back end, and once you sort that out from game mechanics and how well they play it, you can see where they're struggling and where they're not struggling.

Dr Topol: What about managed competition with other kids and their peers? Is that a strategy that you're using?

Dr Spruijt-Metz: I'm not sure that competition is always the way to go. I think it's good for some people some of the time. [Northwestern University professor of preventive medicine] Bonnie Spring has done some really great work with adults where it's anonymized. You have teams, but you don't really know who is on the team. I think it can work for kids. It has to be done really well.

Dr Topol: It hasn't been tested yet, right?

Dr Spruijt-Metz: Well, you can't test it. When you start talking about mobile health and embedding games and competitions, it's all in how you do it and what other things are surrounding it. If I make a terrible intervention and make competitions out of it, and then it doesn't seem to help, then is competition no good or the other elements? That's where some of [Pennsylvania State University researcher] Linda Collins's work, looking at fractional factorial designs of what works and what doesn't within the context of a larger intervention, is important. So I can't give you a good answer for that.

Capturing Environmental Factors

Dr Topol: What about the other factors that are not necessarily captured well today? We talked about the actual ingestion of food, but what about sleep and other environmental factors that we don't do so well at quantifying or even capturing at any level? What do you think about those?

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