WEBVTT 00:00:10.786 --> 00:00:19.479 - Hey, we're going to get started. We'll reward those people that actually got here on time. My name's 00:00:19.479 --> 00:00:28.172 - Buff Brown, and I'm a member of BTOP. That stands for Bloomington Transportation Options for People. 00:00:28.172 --> 00:00:36.864 - We've had a livable cities speaker series going on now for about, we're on our sixth year, and today 00:00:36.864 --> 00:00:39.102 - we have our 18th speaker. 00:00:39.202 --> 00:00:49.487 - Our VTOP is an organization that promotes walking, biking, and transit and promoting those. We actually 00:00:49.487 --> 00:00:58.684 - work a lot with the city trying to encourage them to set policies that encourage those modes 00:00:58.684 --> 00:01:03.134 - of transportation. This is also sponsored by 00:01:03.426 --> 00:01:11.363 - A couple other groups, Health by Design is a group I want everybody to know about. It's how Gail and 00:01:11.363 --> 00:01:19.221 - I met, an organization out of Indianapolis that also promotes health by focusing on the form of the 00:01:19.221 --> 00:01:27.393 - city, urban form, and how that affects public health. And they're kind of, they're a local organization 00:01:27.393 --> 00:01:32.894 - in Indianapolis, but yet I think they have a statewide reach as well. 00:01:33.826 --> 00:01:42.358 - I hope that partners from all over Indiana join Health by Design and so they can collaborate. Also, 00:01:42.358 --> 00:01:51.060 - I'd like to introduce Hannah Laughlin to tell you a little bit about a local group called GOAL, which 00:01:51.060 --> 00:01:54.302 - stands for Get Onboard Active Living. 00:01:58.018 --> 00:02:03.501 - Our speaker today is going to touch a little bit on childhood obesity. So I just wanted those of you 00:02:03.501 --> 00:02:09.038 - who are in the audience who maybe don't know about our local efforts around childhood obesity to just 00:02:09.038 --> 00:02:14.521 - hear a little bit more about that before we start. So the goal program, as Buff said, stands for Get 00:02:14.521 --> 00:02:20.221 - On Board Active Living. And it's a free community-based childhood obesity program for not only children, 00:02:20.221 --> 00:02:26.030 - but also their parents. And it's made possible by seven local community partners who give in-kind donation 00:02:26.030 --> 00:02:27.984 - and staff time to be able to let us 00:02:27.984 --> 00:02:34.824 - including IU Health Bloomington, the City of Bloomington Parks and Recreation, the Monroe County YMCA, 00:02:34.824 --> 00:02:41.599 - Southern Indiana Pediatrics, MCCSE, RBB, and IU, both the Department of Kinesiology and the Office of 00:02:41.599 --> 00:02:48.638 - Community Health Engagement. So our program is for children from the ages of six to 18 who are overweight 00:02:48.638 --> 00:02:55.412 - or obese, and it's free, it's family-oriented, and it's community-focused. We try to get our kids out 00:02:55.412 --> 00:02:57.936 - in the community to use the resources 00:02:57.936 --> 00:03:05.551 - that we have here in Bloomington that can help them lose weight. And if anybody's interested in more 00:03:05.551 --> 00:03:13.165 - information, my program team is here. Raise your hands so they can help answer questions if you have 00:03:13.165 --> 00:03:21.006 - any at the end. Thank you. All right. Dr. Liu is a research scientist at the Children's Health Services 00:03:21.006 --> 00:03:25.982 - Research Program in Indianapolis. He is an associate professor of 00:03:26.114 --> 00:03:35.521 - clinical pediatrics at the IU School of Medicine. And so let me introduce Dr. Gil Lu. Thank you. Bye. 00:03:35.521 --> 00:03:44.836 - So it's a real pleasure to be here talking with you today. And if you want to interrupt at any time, 00:03:44.836 --> 00:03:55.166 - just do so. Yell out, hey, Gil, I have a question or a comment. I'd be delighted to make this a little bit more 00:03:55.266 --> 00:04:02.572 - of a dialogue than just me lecturing to you. And let me see if I can get this to go. Okay, so I just 00:04:02.572 --> 00:04:09.807 - wanted to start out by reviewing where the country stands in terms of rates of obesity. In actually 00:04:09.807 --> 00:04:17.041 - the late 80s, the US Centers for Disease Control and Prevention, the CDC, decided they wanted to do 00:04:17.041 --> 00:04:24.926 - nationwide surveillance of obesity rates and they thought a good way to do that was to get on the phone call 00:04:25.314 --> 00:04:32.006 - randomly dial people in a representative sample and ask them many questions, two of which are how tall 00:04:32.006 --> 00:04:38.763 - are you and how much do you weigh? So we know that there are biases in that type of question. If you're 00:04:38.763 --> 00:04:45.325 - a woman and somebody asks you how much do you weigh, what do you typically do? You under report. And 00:04:45.325 --> 00:04:52.146 - if you're a guy and somebody asks you how tall you are, what do guys typically do? They say that they're 00:04:52.146 --> 00:04:55.070 - a little bit taller than they might measure. 00:04:55.234 --> 00:05:02.684 - So anything that the CDC got they knew from the start that it was probably a very conservative and likely 00:05:02.684 --> 00:05:10.133 - modest estimate. The first kind of complete data across the nation rolled in in 1995 and the color scheme 00:05:10.133 --> 00:05:17.232 - is that if you are light blue then 5 to 10 percent or less of your adults had a BMI greater than 30. 00:05:17.232 --> 00:05:23.838 - Are all of you familiar with body mass index, how that's calculated? Okay, so just to review. 00:05:23.938 --> 00:05:30.936 - That's a way of adjusting your weight for your height, and it is a rough screen for whether you're carrying 00:05:30.936 --> 00:05:37.416 - excess fat tissue on your body. So we know some people like, you know, who's Sylvester Stallone is, 00:05:37.416 --> 00:05:43.895 - he's kind of built like a square, right? He's very, very muscular. He's kind of, you know, he's not 00:05:43.895 --> 00:05:50.569 - the tallest guy. He's got a big BMI, but clearly he doesn't have obesity or overweight. So BMI has its 00:05:50.569 --> 00:05:52.254 - limitations, but overall, 00:05:53.058 --> 00:06:01.065 - It's a pretty good estimate for whether you are normal weight, overweight, or underweight, 1995. And 00:06:01.065 --> 00:06:09.152 - this is the most current data from 2009. And you can see that essentially we've had to erase the blue 00:06:09.152 --> 00:06:16.446 - color scheme and completely revise and change how we're looking at the rates of overweight. 00:06:16.546 --> 00:06:23.644 - And in fact, most of the states in the US now have a rate of obesity greater than 30%, more than one 00:06:23.644 --> 00:06:30.953 - out of every three adults has a BMI greater than 30. And actually, the one lone blue state is no longer 00:06:30.953 --> 00:06:38.262 - blue. So Colorado used to have a rate of overweight that was less than 15%. But now, they join the rest 00:06:38.262 --> 00:06:44.798 - of the country in having at least one out of every four adults having a BMI greater than 30. 00:06:45.762 --> 00:06:53.209 - So my health times have changed. We've seen this literal epidemic and explosion in rates of obesity 00:06:53.209 --> 00:07:00.657 - across our country. And this is sort of that same data but showing you the trend over time. So this 00:07:00.657 --> 00:07:08.104 - is a line graph starting in the late 80s going up to, you know, close to current day. And there are 00:07:08.104 --> 00:07:11.902 - some things to notice about this. One is that for, 00:07:12.546 --> 00:07:20.136 - Overweight, which we define as a BMI between 25 and 30, that rate has stayed about the same. But we've 00:07:20.136 --> 00:07:27.947 - seen most of the increases in people with BMI greater than 30 and in BMI greater than 40, which we define 00:07:27.947 --> 00:07:35.684 - as morbidly obese and has very, very serious implications for health. So not only have we seen it happen 00:07:35.684 --> 00:07:41.726 - across the country, but the severity of the rates seems to be increasing as well. 00:07:41.826 --> 00:07:48.588 - So for kids, you can't very well call up a kid and ask them how tall they are and how much they weigh. 00:07:48.588 --> 00:07:55.350 - It's just oftentimes they won't give you anywhere near a precise report. So what have we done instead? 00:07:55.350 --> 00:08:01.981 - They've actually paid for vans to go out across the US and measure children and do other health data 00:08:01.981 --> 00:08:05.854 - collection. And this shows that data for childhood obesity 00:08:06.914 --> 00:08:13.586 - And in general, the message is that we've seen similar rapid rises in number of kids who are obese, 00:08:13.586 --> 00:08:20.259 - a very clear trend of rise over time. And the perhaps most worrisome thing about this is do you see 00:08:20.259 --> 00:08:26.931 - the orange line at the bottom? That not only are we seeing children become overweight, but toddlers 00:08:26.931 --> 00:08:33.470 - and preschoolers are also seeming to become overweight more quickly. So Hannah, you've got to get 00:08:33.602 --> 00:08:42.803 - programs for kids younger than six. Because if you wait that long, you're going to miss a very important 00:08:42.803 --> 00:08:51.654 - window. OK, a little bit of trivia. Anybody know who started the National School Lunch Program? What 00:08:51.654 --> 00:09:00.856 - president? Truman in 1946. And he said that it was important for schools to deliver lunches to safeguard 00:09:00.856 --> 00:09:03.134 - the health and well-being 00:09:03.618 --> 00:09:10.473 - of the nation's children, and also a measure of national security. So what had we been dealing with 00:09:10.473 --> 00:09:17.533 - immediately before 1946? A war across the world. And interestingly, back in the 40s, the issue was not 00:09:17.533 --> 00:09:24.867 - obesity, which is a concern for how well our soldiers are able to defend us now, but actually underweight, 00:09:24.867 --> 00:09:27.198 - and particularly from Midwestern. 00:09:27.522 --> 00:09:34.684 - recruits, they were showing up so malnourished that they were unfit to serve as soldiers for this country. 00:09:34.684 --> 00:09:41.444 - So that was one of the main reasons why we started the school lunch program. And it might have times 00:09:41.444 --> 00:09:48.272 - of change. It used to be that the witches had to worry about fattening the kids up first. But we live 00:09:48.272 --> 00:09:55.166 - in an entirely different world now. So why do we worry about a BMI of 30? How did we pick this number? 00:09:55.266 --> 00:10:02.265 - of 30 for body mass index. Well, it happens that we've been following people now long enough to where 00:10:02.265 --> 00:10:09.401 - we can statistically determine that if your BMI exceeds 30 as a population, you are at much higher risk 00:10:09.401 --> 00:10:16.537 - for terrible health outcomes. And I'll just highlight two of them for you, or a few. But one for adults 00:10:16.537 --> 00:10:23.947 - came out in this paper in the Lancet just last year. And they looked at a million adults across 57 studies, 00:10:23.947 --> 00:10:25.182 - a worldwide view. 00:10:25.410 --> 00:10:31.868 - If you look, this paragraph I'm going to blow up for you, but moderate obesity, a BMI of 30 to 35 was 00:10:31.868 --> 00:10:38.200 - associated with approximately three year loss of life compared to normal weight individuals. And if 00:10:38.200 --> 00:10:44.658 - your BMI is greater than 40 in that morbid obese category, then you lose 10 years of life. And that's 00:10:44.658 --> 00:10:50.989 - equivalent to smoking your whole life. So I don't know if, you know, how you feel about tobacco use 00:10:50.989 --> 00:10:52.382 - or weight, but to me, 00:10:53.026 --> 00:11:01.577 - the proposition of one-third of our population in this country looking potentially at a very significant 00:11:01.577 --> 00:11:09.885 - shortening of their lifespan is something's got to change, right? And this is secondary stuff but I'm 00:11:09.885 --> 00:11:18.355 - sure many of you have heard about the Affordable Health Care Act and the need to reform our health care 00:11:18.355 --> 00:11:20.798 - expenditures, how much of our 00:11:20.962 --> 00:11:29.499 - gross domestic product is using to support healthcare, clearly we know that in overweight individuals 00:11:29.499 --> 00:11:37.869 - compared to normal weight that we spend much more on their care. So 41% more, $1.4 to every one for 00:11:37.869 --> 00:11:44.062 - a normal weight individual. So it's also a heavy economic burden as well. 00:11:47.170 --> 00:11:53.827 - For children, we don't know as much about the consequences of early overweight as far as how that's 00:11:53.827 --> 00:12:00.551 - going to translate into lifelong health impact, but it's not a big stretch to say that it's probably 00:12:00.551 --> 00:12:07.209 - just going to accrue more and more morbidity and mortality. But interestingly, we have seen that at 00:12:07.209 --> 00:12:14.332 - younger and younger ages, we're seeing clinical conditions that used to be only associated with overweight 00:12:14.332 --> 00:12:16.862 - in adults showing up in our children. 00:12:17.186 --> 00:12:24.619 - So there is a study in the southern U.S. that looked at how many 5 to 10-year-olds who are overweight 00:12:24.619 --> 00:12:31.978 - have elevated blood pressure, elevated cholesterol, are beginning to become resistant to insulin and 00:12:31.978 --> 00:12:39.703 - have pre-diabetes. And half of those kids had one of these factors, a quarter had two or more. And that's 00:12:39.703 --> 00:12:45.022 - something that we just really have no idea how that's going to play out. 00:12:45.314 --> 00:12:54.390 - early and shocking and dangerous for kids to have. Findings like hypertension, hyperlipidemia, and insulin 00:12:54.390 --> 00:13:03.127 - resistance at pre-adolescent ages. And then when you ask about health risk behaviors, children who are 00:13:03.127 --> 00:13:12.542 - overweight report increased use of alcohol and tobacco, less exercise, lower school performance, more sadness, 00:13:12.834 --> 00:13:22.870 - and lower quality relationships with their peers. So there's not just this clinical finding but also 00:13:22.870 --> 00:13:33.005 - heavy psychosocial burden as well. So what might have changed over the past 30 years to lead to these 00:13:33.005 --> 00:13:35.390 - rapid rises in obesity? 00:13:35.618 --> 00:13:43.312 - Many people think that it's a combination of our genetic predisposition and a rapidly changing environment 00:13:43.312 --> 00:13:50.718 - that's causing us to become more and more overweight. So just a diagram that in the past, well we know 00:13:50.718 --> 00:13:57.980 - that you put fat on your body if your energy quotient Q exceeds your work quotient W. So just simply 00:13:57.980 --> 00:14:02.366 - if you're eating more calories then you're burning in a day. 00:14:02.626 --> 00:14:09.285 - Many people will convert that into fat tissue and just store it. That's how our genes were made. And 00:14:09.285 --> 00:14:15.945 - that served us very, very well in the past when we were hunter-gatherers. So food was scarce. We had 00:14:15.945 --> 00:14:22.736 - to work hard to get it. And we needed to store energy. And there's been hundreds and hundreds of years 00:14:22.736 --> 00:14:29.527 - of environmental pressure to make us very thrifty in terms of our calories. And the thinking is in the 00:14:29.527 --> 00:14:30.846 - past three decades, 00:14:31.554 --> 00:14:39.169 - our environment has radically changed to where now we have a very, very easy time of getting lots of 00:14:39.169 --> 00:14:47.237 - Q and we essentially have to do no W. So our world is such that we can consume calories very, very readily 00:14:47.237 --> 00:14:54.174 - without hardly any work to get those. And you see that before our genotype, which was lean, 00:14:54.594 --> 00:15:01.411 - and we had to conserve our energy is now showing up as the overweight phenotype, same genotype. So clearly 00:15:01.411 --> 00:15:08.165 - our genes haven't changed in 30 years. It's unlikely that across the whole population something's mutated 00:15:08.165 --> 00:15:14.664 - in our DNA, but much more likely that we're seeing the effects of a very different environment that's 00:15:14.664 --> 00:15:21.227 - changed just over the past 30 or 40 years. So these are just, again, some lighthearted slides, but the 00:15:21.227 --> 00:15:24.094 - biggest hamburger in the world is 11 pounds. 00:15:24.514 --> 00:15:31.412 - And several people have taken it on. Eric didn't finish it. Kate did, unbelievably. And then I think 00:15:31.412 --> 00:15:38.446 - one of the most worrisome things we see is how foods marketed to kids. So even though they call cereal 00:15:38.446 --> 00:15:45.412 - mud and bugs, you can't see it because it's like brighted out. Kids buy the stuff. They love it. They 00:15:45.412 --> 00:15:52.446 - demand it from their children. So there are all of these kind of dangerous social phenomenon going on. 00:15:52.706 --> 00:15:59.487 - And we really have compartmentalized physical activity in our lives. So even the gems, we see escalators 00:15:59.487 --> 00:16:06.462 - and people choosing the easier route to get there. And I love this timeline. It showed up in the Washington 00:16:06.462 --> 00:16:13.113 - Post. And it started on my birthday, 1970. How many of you here are younger than 30? I'm just curious. 00:16:13.113 --> 00:16:19.572 - Raise your hand. A large majority of you. And that's really cool. I'm really glad to be speaking to 00:16:19.572 --> 00:16:20.734 - a young audience. 00:16:21.026 --> 00:16:30.503 - In 1970, again, sorry that you can't see this, but the prevalence of child obesity was 4%, one-third 00:16:30.503 --> 00:16:40.262 - to one-quarter of what it was now. And since I was born, there's been all of these amazing changes like 00:16:40.262 --> 00:16:50.302 - HBO and the first VCR and personal computer. The Happy Meal came in at 1978, the 7-11 big gulp in the 80s. 00:16:51.682 --> 00:16:59.104 - in where are some other like really neat things. I was trying to find somewhere on here like more and 00:16:59.104 --> 00:17:06.525 - more women are working so more and more kids are having prepared food or less time eating together as 00:17:06.525 --> 00:17:14.019 - a family. By the start of the 2000s, potatoes and white iceberg lettuce made up half of the vegetables 00:17:14.019 --> 00:17:21.150 - that we eat. So we had a very, very narrowing of the diversity of our fruit and vegetable intake. 00:17:22.082 --> 00:17:29.522 - And then at the beginning of this decade, we had to have things like Husky car seats. And Cookie Monster 00:17:29.522 --> 00:17:37.175 - could only talk about cookies as a sometimes food. And then now, you know, we're really trying to backpedal 00:17:37.175 --> 00:17:44.402 - and make up for all of these things that, you know, we thought were great. And they are great in some 00:17:44.402 --> 00:17:49.150 - ways, but they're also affecting our health in a very adverse way. 00:17:50.114 --> 00:17:55.927 - People have said it very eloquently. I'll read the middle and the last one. The current US environment 00:17:55.927 --> 00:18:01.797 - is characterized by an essentially unlimited supply of convenient, inexpensive, palatable, energy-dense 00:18:01.797 --> 00:18:07.724 - foods coupled with a lifestyle requiring negligible amounts of physical activity for subsistence. That's 00:18:07.724 --> 00:18:13.593 - the world we live in today. And because of that, genes have loaded the gun. Hundreds of years have made 00:18:13.593 --> 00:18:19.294 - us very, very thrifty in terms of hanging on to our calories and environment has pulled the trigger. 00:18:19.714 --> 00:18:26.724 - And now we see one out of every three US adults overweight, one out of every five or six kids overweight, 00:18:26.724 --> 00:18:33.469 - and children as young as two to five becoming overweight. The other thing, and I'll talk a little bit 00:18:33.469 --> 00:18:40.082 - more, so diet is clearly a major piece of this. And I'm not going to talk as much about diet today. 00:18:40.082 --> 00:18:46.695 - I'm going to lean more towards physical activity because that's my research interest. So forgive me 00:18:46.695 --> 00:18:48.414 - for kind of setting aside 00:18:48.610 --> 00:18:56.351 - but I'm going to focus more on physical activity and what we can do to design communities to promote 00:18:56.351 --> 00:19:04.400 - physical activity. But if you look at what happens from late childhood to adolescence, physical activity 00:19:04.400 --> 00:19:12.218 - basically steeply declines. And while physical activity is steadily decreasing from early adolescence 00:19:12.218 --> 00:19:16.510 - to late adolescence, which is the x-axis of this chart, 00:19:17.442 --> 00:19:24.344 - And girls, this is hours per week on the Y axis. We're seeing more and more computer use. And interestingly, 00:19:24.344 --> 00:19:30.992 - TV is kind of leveled off in our generation. So we're still getting a lot of screen time, but it's moved 00:19:30.992 --> 00:19:37.324 - from television to other electronics. And the same for boys, except even more so. Our young men are 00:19:37.324 --> 00:19:41.630 - just really glued to some sort of electronic screen that is not TV. 00:19:46.050 --> 00:19:53.472 - So this is for Hannah and the goal team. What do we know about weight loss programs? It's a big challenge. 00:19:53.472 --> 00:20:00.755 - So if you really, really give people good counseling about aggressive lifestyle modifications, so really 00:20:00.755 --> 00:20:07.692 - increasing their physical activity, teaching them how to eat a nutritious diet, we know that pretty 00:20:07.692 --> 00:20:12.894 - reliably we can get people to lose 10 to 20% of their current body weight. 00:20:13.858 --> 00:20:20.475 - But what we don't know is how to help them keep that weight off. So 80% of people who have been enrolled 00:20:20.475 --> 00:20:27.280 - in good clinical trials of weight loss programs at the five-year mark have actually exceeded their starting 00:20:27.280 --> 00:20:33.771 - weight. So we can get weight off in the short term. About 20% of your weight is a good goal and proven 00:20:33.771 --> 00:20:40.072 - success in weight management programs. But very, very few programs know how to sustain weight loss. 00:20:40.072 --> 00:20:42.782 - At five years, virtually all of them fail. 00:20:45.442 --> 00:20:51.636 - And this is a complicated chart, but it's a way to represent a meta-analysis, which means to take all 00:20:51.636 --> 00:20:57.890 - of the literature that exists that is strong evidence and represent it on a page or several pages. And 00:20:57.890 --> 00:21:03.963 - this just shows the current state of child weight management programs. So the first thing I want to 00:21:03.963 --> 00:21:10.217 - point out is that you can fit all of the evidence on one page. That's kind of sad. So we've got a long 00:21:10.217 --> 00:21:13.982 - way to go to figure out how to help kids manage their weight. 00:21:14.914 --> 00:21:21.474 - And this line right here, if you touch this line, your trial is no different experimental group versus 00:21:21.474 --> 00:21:28.161 - control. So anything touching this line showed no significant effect. So you can see most of the studies 00:21:28.161 --> 00:21:34.529 - are touching the line. Only a few are showing statistically significant weight management and there 00:21:34.529 --> 00:21:41.662 - are one, two, three, four, five trials right now out of all of the published literature that shows that we can, 00:21:41.986 --> 00:21:49.636 - effectively get kids to lose weight in weight management programs. And they have very, very modest effects. 00:21:49.636 --> 00:21:56.933 - So in general, the kids drop between four and eight pounds in the program after six to 12 months. None 00:21:56.933 --> 00:22:04.158 - of them enroll kids that are preschool age. So that's a wide open frontier for research. And we don't 00:22:04.158 --> 00:22:11.454 - know whether it benefits like their lipid status or their blood pressure or their insulin sensitivity. 00:22:12.386 --> 00:22:18.260 - And there is some evidence for older kids that some of the weight loss medications work, but again not 00:22:18.260 --> 00:22:24.020 - for long term and actually many of these have bad side effects. So we have no idea once a child or a 00:22:24.020 --> 00:22:30.007 - person becomes overweight how to help them in the long term. That's kind of the overall summary of this. 00:22:30.007 --> 00:22:35.710 - So I'm really like giving you such depressing news. The world is becoming more and more overweight. 00:22:35.710 --> 00:22:41.470 - That overweight has horrible health consequences and once a person is overweight there's very little 00:22:41.698 --> 00:22:48.620 - return to normal weight for those people who have been enrolled in good trials that have collected data 00:22:48.620 --> 00:22:55.408 - in the long term. So what does that hold for us as far as priorities? I would suggest that instead of 00:22:55.408 --> 00:23:02.330 - focusing on treatment, while it's important and should receive continued research, especially for kids, 00:23:02.330 --> 00:23:09.384 - we need to look at prevention. Because it seems like treatment is not the answer, at least at the current 00:23:09.384 --> 00:23:10.782 - state of things. OK. 00:23:10.978 --> 00:23:17.849 - More trivial pursuit, which of these household appliances is least used by immigrant families in the 00:23:17.849 --> 00:23:25.128 - US? Anybody want to take a stab at it? It actually is the dishwasher. Anybody here grow up in an immigrant 00:23:25.128 --> 00:23:31.454 - family? I can't really tell people's race, ethnicity. I did, my parents moved here from the, 00:23:31.906 --> 00:23:37.444 - from China and Taiwan in the late 60s and they sure enough use their dishwasher as a drying rack. They 00:23:37.444 --> 00:23:42.981 - just don't believe it gets dishes as clean as they can and they think it's a total waste of like water 00:23:42.981 --> 00:23:48.465 - and electricity. Why do I ask you that? Well, the person who invented the front loading dishwasher is 00:23:48.465 --> 00:23:50.078 - from Indiana, his name is Sam 00:23:50.178 --> 00:23:56.307 - Regenstrief and any house that has a front loading dishwasher pays a little bit on Sam's patent. So 00:23:56.307 --> 00:24:02.681 - you can imagine the Regenstrief family has just accumulated a fair amount of wealth and he's done very, 00:24:02.681 --> 00:24:09.117 - very good things with that money. One is that he's given it to the Boys and Girls Clubs of America which 00:24:09.117 --> 00:24:15.246 - is a great youth community organization. But the other is that he established where I work which is 00:24:15.246 --> 00:24:19.230 - the Regenstrief Institute at Indiana University in Indianapolis. 00:24:19.458 --> 00:24:26.027 - And another thing that Sam had great foresight to do is he said, why don't we go ahead and start working 00:24:26.027 --> 00:24:32.407 - on electronic medical records at the Regan Street Institute. That's one of the things I want for this 00:24:32.407 --> 00:24:38.913 - place to be a leader in. So Indiana has one of the longest standing, largest electronic medical records 00:24:38.913 --> 00:24:44.606 - in the world, which I think is really, really cool because it's a great tool for research. 00:24:44.738 --> 00:24:52.051 - So we have data on over 6 million patients. They've generated almost, you know, 900 plus million observations 00:24:52.051 --> 00:24:59.097 - and it's widespread. It's the nation's only city-wide medical record and it's rapidly becoming state-wide 00:24:59.097 --> 00:25:05.812 - in terms of getting disparate hospital systems to share data and store it so that people can look at 00:25:05.812 --> 00:25:06.942 - it and study it. 00:25:09.186 --> 00:25:15.968 - So I want to show you some analyses that we've done. We went into the record and asked for all heights 00:25:15.968 --> 00:25:22.619 - and weights on kids from 4 to 16, from 96 to present. And then we looked at whether or not they were 00:25:22.619 --> 00:25:29.335 - seen for well child visits versus sick visits. And then we categorized them in terms of their weight. 00:25:29.335 --> 00:25:35.920 - So we take care of about 10,000 patients a year. Many of them come for multiple visits, but many of 00:25:35.920 --> 00:25:37.566 - them only come one time. 00:25:37.666 --> 00:25:46.192 - We have a mostly publicly insured population, so they're fairly transient. And this just shows you that 00:25:46.192 --> 00:25:54.554 - they're normally distributed. So it's half boy, half girl, mostly younger, which is when kids come to 00:25:54.554 --> 00:26:03.326 - the pediatrician more. But you can see that half of our population is African-American, and over half have 00:26:03.458 --> 00:26:10.199 - either Medicaid or Medicare. So it's a low income, high minority population living in Indianapolis, 00:26:10.199 --> 00:26:17.007 - basically who I'm talking about. So one of the limitations of this work is I don't have a lot to say 00:26:17.007 --> 00:26:24.152 - about wealthy, non-minority subjects at present. We're trying to get that data in so as the record grows, 00:26:24.152 --> 00:26:31.364 - we'll have more of that population. And just like the national data, we've seen our obesity rates steadily 00:26:31.364 --> 00:26:32.510 - climb over time. 00:26:33.538 --> 00:26:39.919 - And this is interesting to me. So one thing that you can see is that our Latino subjects have the highest 00:26:39.919 --> 00:26:46.118 - rates of overweight. They're the collection of bars in the middle and that they're becoming overweight 00:26:46.118 --> 00:26:52.559 - at much younger ages. So we know that, you know, toddlers and preschoolers are rapidly becoming overweight 00:26:52.559 --> 00:26:58.699 - and especially among Hispanics and especially among Hispanic males. They seem to be at really, really 00:26:58.699 --> 00:27:00.926 - high risk for developing overweight. 00:27:01.154 --> 00:27:08.932 - early and then staying overweight throughout their childhood. And that's just shown here. It's very, 00:27:08.932 --> 00:27:17.402 - very hard to see, but this is a model that's virtually invisible. Age is on the bottom and rate of overweight 00:27:17.402 --> 00:27:25.334 - is on the top. And this just shows numbers of kids becoming overweight by a certain age. And you can't 00:27:25.334 --> 00:27:30.878 - see it, but this is the Latino curve. It's earlier than everybody else. 00:27:31.266 --> 00:27:40.268 - So at age 4, we saw about 15 to 20% of our Latinos already crossing a BMI threshold that would define 00:27:40.268 --> 00:27:49.447 - them as obese. So that population in particular deserves some attention. So America's losing the battle 00:27:49.447 --> 00:27:57.566 - against obesity. Sustainable weight loss has not been demonstrated. In Indianapolis, we see 00:27:57.954 --> 00:28:04.811 - clear patterns by race, ethnicity, and sex. And based on these things, we probably need to start working 00:28:04.811 --> 00:28:11.472 - on obesity as early as we can, like even with pregnant mothers before the child pops out of the womb. 00:28:11.472 --> 00:28:18.394 - Any questions? You guys hanging in there? OK, I see a couple in the back. Why don't we take two questions 00:28:18.394 --> 00:28:20.222 - that I'm going to motor on. 00:29:07.394 --> 00:29:12.638 - I think that's a very good hypothesis. I don't know of any specific literature that talks about stay 00:29:12.638 --> 00:29:17.934 - at home moms versus working moms. I do know that there have been many studies that show the more that 00:29:17.934 --> 00:29:23.334 - children eat breakfast at home and dinner at home, the healthier their diet composition is and the less 00:29:23.334 --> 00:29:28.318 - risk they have for overweight. So I think that connects. And then there was one other question. 00:29:39.746 --> 00:29:47.557 - Very, very good question. So it turns out that African American females have the next highest risk. 00:29:47.557 --> 00:29:55.525 - So it actually goes Hispanic males, African American females, Hispanic females, and then the rest are 00:29:55.525 --> 00:30:03.493 - pretty close. And one piece of good news that I didn't mention is it looks like recently our rates of 00:30:03.493 --> 00:30:05.758 - overweight have leveled off. 00:30:07.138 --> 00:30:14.861 - You know, so cause for, you know, a little bit of celebration there. But for certain subgroups, 00:30:14.861 --> 00:30:23.308 - the Latinos, maybe it's still rapidly climbing. So that's a great question. Okay, this gets to my second 00:30:23.308 --> 00:30:32.158 - half of the talk. And so now in terms of prevention, there are many ways to go about that. Policy approaches. 00:30:33.058 --> 00:30:39.807 - But I'm going to focus on something called the built environment. And that just means anything that 00:30:39.807 --> 00:30:46.692 - man decides to install in their communities. And I'm really looking at kind of larger scale features. 00:30:46.692 --> 00:30:53.441 - So while it could be, you know, stairs and signs and buildings, we're going to talk about ways that 00:30:53.441 --> 00:31:00.798 - we decide how to allocate land use to residential versus commercial landscaping that we do in street design. 00:31:01.122 --> 00:31:08.461 - are the features of the built environment that I'm going to be talking more about. So it seems pretty 00:31:08.461 --> 00:31:15.655 - clear that if we look at how we do our transportation infrastructure, how we decide to allocate our 00:31:15.655 --> 00:31:22.922 - land use mix, and how densely we develop residential areas, those things have been proven to promote 00:31:22.922 --> 00:31:28.318 - walking and biking in adults. So if you take a street network that is more 00:31:28.770 --> 00:31:35.394 - a grid structure versus the cul-de-sacs and disconnected streets that we see in suburbs, then people 00:31:35.394 --> 00:31:41.952 - walk and bike more on a grid. Similarly, if you take residential commercial retail and you blend it 00:31:41.952 --> 00:31:48.511 - all together like you see in the middle of cities, so people living in apartments that are close to 00:31:48.511 --> 00:31:55.200 - stores and also close to where they work, adults walk and bike more. And then lastly, in places where 00:31:55.200 --> 00:31:57.758 - there are more and more adults living, 00:31:58.402 --> 00:32:07.033 - densely in an area, that is also promoting a physically active lifestyle. And that probably makes sense 00:32:07.033 --> 00:32:15.747 - to a lot of you. So we're looking for the best ways that we can modify the built environment to increase 00:32:15.747 --> 00:32:24.461 - physical activity, to enhance a person's nutrition in their diet, and to keep them from being sedentary. 00:32:24.461 --> 00:32:28.030 - And we don't know how to do that for kids. 00:32:28.226 --> 00:32:34.830 - quite yet. So how many of you grew up on a cul-de-sac or a separated street? Yeah, yeah, many of you 00:32:34.830 --> 00:32:41.629 - did. It's a great place for a kid to be, right? It's safe, it's away from traffic, the parents can more 00:32:41.629 --> 00:32:46.206 - easily supervise what's going on, maybe you knew your neighbors more. 00:32:46.946 --> 00:32:53.113 - But urban designers who are looking for smart designs for adults hate cul-de-sac. So you can see there's 00:32:53.113 --> 00:32:59.045 - this kind of battle already set up for what do we do in terms of good things for kids? What do we do 00:32:59.045 --> 00:33:05.094 - in terms of good things for adults when the two things are so separate and distinct? Hard to say. What 00:33:05.094 --> 00:33:10.498 - we do know is that the more that you get a kid outdoors, the more active they are, which is 00:33:10.498 --> 00:33:16.606 - a neat association. And that we need more research into this area is kind of the summary of this slide. 00:33:18.594 --> 00:33:24.928 - And I have a particular interest in greenness. So the way that we landscape cities with more and more 00:33:24.928 --> 00:33:31.387 - vegetation and seeing if that improves health. And that's based on lots of kind of interesting studies. 00:33:31.387 --> 00:33:37.659 - So let me just holly a couple for you. One was just looking at people who were hospitalized that had 00:33:37.659 --> 00:33:44.180 - the bed by the window or the bed that didn't have the view. And it turns out that the patients who could 00:33:44.180 --> 00:33:48.030 - look out onto a green setting requested pain medication less. 00:33:48.514 --> 00:33:54.158 - Their nurses thought that they recovered better and they actually had an earlier discharge from their 00:33:54.158 --> 00:33:59.746 - hospital. And that, you know, hard to say exactly what's going on there, but I thought, and it's one 00:33:59.746 --> 00:34:05.335 - of the earlier starts at looking at the effect of greenness on health. And now we're seeing more and 00:34:05.335 --> 00:34:11.255 - more in studies that communal green spaces build a lot of community cohesion and good social interactions. 00:34:11.255 --> 00:34:16.788 - So gardens and parks are great places for neighbors to get to know each other. And I wanted to look 00:34:16.788 --> 00:34:17.950 - at how these spaces, 00:34:18.306 --> 00:34:28.116 - can get kids to be more active and to have less obesity. So, like I said before, we took all the patients 00:34:28.116 --> 00:34:37.556 - in our county out of our medical record system and we started mapping them as a start to look at what 00:34:37.556 --> 00:34:46.718 - their environments were like. And on this map, the purple dots is color coded by race and green is 00:34:47.042 --> 00:34:54.726 - Caucasian, purple is African-American, so what would you say about Indianapolis? Very segregated, right? 00:34:54.726 --> 00:35:02.264 - It's like oil and water along north-south boundaries. So that's the first thing that's just like, wow, 00:35:02.264 --> 00:35:09.655 - I didn't realize that blacks and whites are living so separately in our city, and they probably have 00:35:09.655 --> 00:35:14.046 - very distinct environments as a result of that. Next, we... 00:35:14.690 --> 00:35:21.204 - Anybody a geography major in here? Or doing any geographic information, spatial analysis stuff? I'm 00:35:21.204 --> 00:35:27.718 - not one of those people, but there's a way where you can look at observations in space and look and 00:35:27.718 --> 00:35:34.557 - see whether they're clustered. So we just wanted to know are overweight children clustering in our city? 00:35:34.557 --> 00:35:41.202 - And it turns out that they are. And especially when you look separately by race, the African American 00:35:41.202 --> 00:35:43.742 - children who are overweight are living 00:35:43.842 --> 00:35:49.920 - near other overweight kids. So again, another piece of evidence that suggests there's some 00:35:49.920 --> 00:35:56.598 - sort of environmental factor going on that's affecting kids' weight. OK. So we decided, well, let's 00:35:56.598 --> 00:36:03.410 - actually see if we can get at the greenness question. So we looked at the kids who are staying in our 00:36:03.410 --> 00:36:10.089 - hospital system so we can measure their weights over time. So it's better to have longitudinal data 00:36:10.089 --> 00:36:11.358 - versus a snapshot. 00:36:11.618 --> 00:36:20.553 - Let's look at the effect of greenness and residential density on their change of weight and BMI. And 00:36:20.553 --> 00:36:29.488 - this just says both greenness and residential density and individual level factors affect a person's 00:36:29.488 --> 00:36:38.600 - weight and that these two factors probably interact in some way. So that's our conceptual model. Let's 00:36:38.600 --> 00:36:39.838 - get into kind 00:36:41.762 --> 00:36:47.510 - detail, but anyway, we also included the age of the child, their race, whether they're boys or girls, 00:36:47.510 --> 00:36:53.314 - their starting weight, so whether they were overweight or normal weight at the beginning of the study, 00:36:53.314 --> 00:36:59.006 - how they were insured, the income level of their neighborhood based on the census, so sometimes poor 00:36:59.006 --> 00:37:04.641 - kids live in wealthier neighborhoods, sometimes poor kids live in poor neighborhoods, and the year, 00:37:04.641 --> 00:37:07.966 - because we know that obesity rates are climbing over time. 00:37:10.178 --> 00:37:16.832 - So how did we get at greenness? Well, it turns out that all the time satellites are flying over the 00:37:16.832 --> 00:37:23.885 - US and one of the things that they're collecting is information on vegetation. And so they take a picture 00:37:23.885 --> 00:37:30.871 - of the surface and by looking at two spectrums of light, the visible spectrum and the infrared spectrum, 00:37:30.871 --> 00:37:36.926 - you can actually determine how much plant matter there is and whether it's healthy or not. 00:37:37.730 --> 00:37:46.149 - It's just really useful for us. And that's called the Normalized Difference Vegetation Index, NDVI. 00:37:46.149 --> 00:37:54.737 - So we've got greenness in hand. And the scale goes from minus one to plus one. So if you're less than 00:37:54.737 --> 00:38:03.156 - 0.1, you're in a pretty non-vegetated place. And if you're from a half to one, you're in very, very 00:38:03.156 --> 00:38:05.598 - lush surroundings, a park or 00:38:05.762 --> 00:38:13.902 - Here it'd be like rainforest kind of. And then the city in Indianapolis collects data on every parcel 00:38:13.902 --> 00:38:22.601 - because they want to know how to tax. So for every little piece of land with a structure on it, Indianapolis 00:38:22.601 --> 00:38:30.742 - and I'm sure Bloomington too knows whether it's residential, commercial, industrial and then they use 00:38:30.742 --> 00:38:34.014 - that to collect funding, public funding. 00:38:34.626 --> 00:38:43.862 - land use as well. And then we took patients' homes and drew circles on them and said, tell me what the 00:38:43.862 --> 00:38:53.187 - NDVI is in the circle and what kinds of land use there are in the circle. And it turns out that there's 00:38:53.187 --> 00:38:55.518 - a bunch of good variation 00:38:55.618 --> 00:39:02.987 - in greenness across our city. So there were some places like parking garage or the core of our city 00:39:02.987 --> 00:39:10.799 - or industrial complexes where the NDVI was very, very low and there were people living near those places. 00:39:10.799 --> 00:39:18.316 - And then there were places like parks or cemeteries where it was super green and similarly there were 00:39:18.316 --> 00:39:25.022 - plenty of families and everything in between. In this study we had roughly 4,000 subjects. 00:39:25.282 --> 00:39:34.270 - We saw the same pattern as our general clinic population, so mostly younger than 10 years, a high rate 00:39:34.270 --> 00:39:43.258 - of publicly insured, a high rate of obesity, and many of them were living in low income neighborhoods. 00:39:43.258 --> 00:39:52.158 - So the average income of the neighborhood that a child lived in was 37,000, just to give you an idea. 00:39:53.666 --> 00:40:00.903 - Basically what we saw is that the higher the NDVI, the lower the rate of weight gain over time. So for 00:40:00.903 --> 00:40:08.281 - these thousands of kids in the urban location of Indianapolis, greenness was protective against obesity. 00:40:08.281 --> 00:40:15.377 - Now it's hard for us to say exactly, you know, does greenness cause lower weight over time? In order 00:40:15.377 --> 00:40:18.750 - to do that, we'd have to conduct an experiment. 00:40:18.914 --> 00:40:26.250 - But this is pretty good preliminary evidence that landscaping may be an approach to get kids more active 00:40:26.250 --> 00:40:33.517 - and to protect them from gaining excess weight. So higher greenness was associated with either declines 00:40:33.517 --> 00:40:40.644 - or lower rates of change in BMI. Residential density was less important in this group than we've seen 00:40:40.644 --> 00:40:48.190 - for adults. And we also looked at things like the street networks and they weren't very important for kids. 00:40:48.514 --> 00:40:56.385 - So. And this is one of the largest studies of its kind. It has lots of racial representation of minority 00:40:56.385 --> 00:41:03.881 - groups, which is also rare. And I had the lecture of working with geographers and urban planners to 00:41:03.881 --> 00:41:11.377 - set up the study. So those are some of the strengths. Why might greenness be a good thing for kids? 00:41:11.377 --> 00:41:17.374 - Again, the more time kids spend outside, we know the more active that they are. 00:41:17.602 --> 00:41:24.086 - In cities, it turns out that the greener a neighborhood is, the more it seems like people are caring 00:41:24.086 --> 00:41:30.763 - for their neighborhood. So if you're putting in the time to landscape an area, then there's likely more 00:41:30.763 --> 00:41:37.247 - social investment in that neighborhood. And we've seen through other studies that greenness produces 00:41:37.247 --> 00:41:44.052 - beneficial effects in terms of reducing stress, people reporting higher quality mental health, and higher 00:41:44.052 --> 00:41:47.390 - self-esteem as well. So we're going forward to look 00:41:47.682 --> 00:41:54.492 - at this more, and let me tell you briefly about that. So I'm going to go by these real quick. The next 00:41:54.492 --> 00:42:01.302 - thing we want to do, so we have the measures from the clinical record, we have the observations of the 00:42:01.302 --> 00:42:08.111 - urban form, but what we didn't know is whether kids were using the greenness or not, right? So we have 00:42:08.111 --> 00:42:14.921 - these big kind of gaps in the study. So how are we going to figure that out? We are going to give kids 00:42:14.921 --> 00:42:16.574 - GPS enabled cell phones, 00:42:17.058 --> 00:42:23.622 - and strap these little pager-like devices on them called accelerometers which measure all of your activity 00:42:23.622 --> 00:42:30.248 - over time. And they hold charges for a month so you don't have to recharge them. So we're going to directly 00:42:30.248 --> 00:42:36.444 - observe where kids go, where they accrue physical activity, and then we're going to also ask them in 00:42:36.444 --> 00:42:42.701 - interviews, tell me about the exercise that you're getting over the week, how you're using the places 00:42:42.701 --> 00:42:45.278 - near your home. And with this technology, 00:42:45.570 --> 00:42:52.767 - This is an example of a path of a person wearing the cell phone over time. So time is from early in 00:42:52.767 --> 00:43:00.108 - the day to later in the day rising. And then you can see the places where they go. And if you connect 00:43:00.108 --> 00:43:07.305 - the path data with the accelerometer data, oh, this is a bunch of kids. And then you can see places 00:43:07.305 --> 00:43:14.142 - where activity is elevated, which would be the peaks on the map, and where it's low, which are 00:43:14.946 --> 00:43:22.572 - flat areas of the map. So hopefully we'll get more at the missing behavioral measures, which we can't 00:43:22.572 --> 00:43:30.123 - get just by like extracting things from the medical record. And forgive me, but I'm going to blow by 00:43:30.123 --> 00:43:37.824 - these. We're also working with the public schools in Indianapolis to improve their physical education. 00:43:37.824 --> 00:43:44.926 - That's how we're delivering the GPS units and accelerometers. So I'm just going to go by this. 00:43:45.762 --> 00:43:53.961 - Ultimately, the way that I would love for this research to be applied is by the policy makers who actually 00:43:53.961 --> 00:44:01.240 - are designing the neighborhoods and incentivizing development. So one great thing we're seeing 00:44:01.240 --> 00:44:09.209 - in Indianapolis is a rapid expansion of urban trails, which has had a lot of benefits. Raising property 00:44:09.209 --> 00:44:15.262 - values, bringing amenities to low-income neighborhoods versus the urban sprawl 00:44:15.522 --> 00:44:25.216 - that we've seen in many places. And a lot more urban gardens in our city. And we've got a lot of work 00:44:25.216 --> 00:44:35.100 - to do. So in Indianapolis, we have much less parks than similarly sized cities in the US. We have very, 00:44:35.100 --> 00:44:41.182 - very low rates of public transportation and walking and biking. 00:44:41.282 --> 00:44:48.314 - If you look at the public infrastructure, the built environment that we have to support physical activity, 00:44:48.314 --> 00:44:55.345 - especially in terms of sidewalks, very low. So many, many opportunities for intervening. And I'll conclude 00:44:55.345 --> 00:45:01.983 - by just saying, you know, this work was supported by the National Institutes of Health and had a lot 00:45:01.983 --> 00:45:08.686 - of great partnerships. Geography, School of Public and Environmental Affairs, the Polis Center, which 00:45:08.686 --> 00:45:10.526 - is an urban research group, 00:45:10.946 --> 00:45:22.955 - and the biostatisticians to run the analyses. So thank you very much. I'd love to hear questions or 00:45:22.955 --> 00:45:35.924 - talk more with you about your ideas for how to prevent obesity through communities. So that's it. Questions 00:45:35.924 --> 00:45:38.206 - anybody? Go ahead. 00:45:44.866 --> 00:45:55.980 - Yeah, we're just starting that right now. Okay, so the question was I think related to the last few 00:45:55.980 --> 00:46:07.649 - slides given that we have the path data and the direct measurement of physical activity have we included 00:46:07.649 --> 00:46:14.206 - greenness as a part of analyzing that data and we just got 00:46:14.338 --> 00:46:21.585 - those observations from the schools a few months ago. So we are. We're going to look at, you know, one 00:46:21.585 --> 00:46:28.620 - of the hard things is you have this path and the GPS device can update itself every five seconds is 00:46:28.620 --> 00:46:35.797 - what we've set it to. And then you have a minute by minute measure of their activity. So we're buried 00:46:35.797 --> 00:46:41.214 - in data. And we've got to boil it down to destinations versus the, you know, 00:46:41.858 --> 00:46:47.841 - commuting from destination to destination and then figuring out how important is it when you're moving 00:46:47.841 --> 00:46:53.823 - by car from one place to another or if you're in your house versus your friend's house. So we're still 00:46:53.823 --> 00:46:59.922 - struggling with how to take that path, boil it down into a variable and then look at greenness for that. 00:46:59.922 --> 00:47:05.730 - So we could take the greenness over the whole path but I think we should wait it by time spent in a 00:47:05.730 --> 00:47:09.854 - place and then even when you're spending time in a place what activity 00:47:09.954 --> 00:47:22.336 - you're doing. So there's still some steps we're taking to transform the data into something that we 00:47:22.336 --> 00:47:26.174 - can plug into a stats package. 00:47:37.410 --> 00:47:44.936 - Yeah, so I'm not 100% sure where the public transit. Yeah, thanks, thanks, thanks. The question was, 00:47:44.936 --> 00:47:52.387 - given that Indianapolis has either passed a new public transportation act, I actually think they're 00:47:52.387 --> 00:47:59.913 - still in the middle of passing it. How might improvements in public transit be relevant to this type 00:47:59.913 --> 00:48:05.502 - of research into preventing obesity? So I think that that's still unclear. 00:48:06.082 --> 00:48:12.361 - that we don't know about Indiana is just how to get people on the public transit. And I don't know if 00:48:12.361 --> 00:48:18.578 - that's a question of there's so little good public transit that people just discount it as an option 00:48:18.578 --> 00:48:24.734 - or if we had a bunch of buses running all the time if people would get on them and use them. What I 00:48:24.734 --> 00:48:31.013 - do know is that for our patients, low income families who are race, ethnicity, minorities, they don't 00:48:31.013 --> 00:48:31.998 - have access to, 00:48:33.218 --> 00:48:40.954 - public places for fiscal activity. So often parks are removed from their neighborhoods and places to 00:48:40.954 --> 00:48:48.691 - buy fresh fruit and vegetables are removed. So they need some way of getting from where they live to 00:48:48.691 --> 00:48:56.427 - an amenity for health. And most of them rely on public transportation. So I think that it would help 00:48:56.427 --> 00:49:01.406 - but I don't know of any studies I can cite that would tell that. 00:49:02.242 --> 00:49:11.473 - Charlotte, and they studied the people that stopped driving and started riding the transit. And I think 00:49:11.473 --> 00:49:20.881 - there was an average loss of about seven pounds. But it's a study that's substantial. And also the amount 00:49:20.881 --> 00:49:29.935 - of walking that occurs from transit, for transit riders, people have found that to be around 20 to 30 00:49:29.935 --> 00:49:31.710 - minutes of walking. 00:49:32.258 --> 00:49:37.278 - per day, which wouldn't otherwise have existed. 00:50:14.850 --> 00:50:22.257 - Yeah, yeah. So the question is in Bloomington it seems like you have plenty of options but people are 00:50:22.257 --> 00:50:29.519 - either unaware of them or even if they're unaware they might have other barriers to accessing them. 00:50:29.519 --> 00:50:36.926 - So I think there's a lot of great research going on right now in terms of social media and marketing. 00:50:37.442 --> 00:50:45.058 - to help people because clearly what we've seen although it's probably becoming less is one, people were 00:50:45.058 --> 00:50:52.675 - unaware of the problem of overweight. So at an individual level many people at BMI of 25 to 30 actually 00:50:52.675 --> 00:50:59.998 - don't think that they're carrying too much weight when we can show that over a lifetime that weight 00:50:59.998 --> 00:51:07.102 - will cause their health to decline. So that's one is just perception of weight status and being, 00:51:07.362 --> 00:51:13.634 - activated to change your lifestyle. The second question of if you want to change your lifestyle but 00:51:13.634 --> 00:51:20.095 - you don't know how to use the things in your environment is a big challenge. So I can say there's many 00:51:20.095 --> 00:51:26.053 - instances of healthcare providers telling people that they need to lose weight, exercise more, 00:51:26.053 --> 00:51:32.451 - and eat better, but they are completely unaware of all of the environmental barriers that people face 00:51:32.451 --> 00:51:34.270 - when they do that and that's 00:51:34.722 --> 00:51:42.395 - True for everybody but especially so for families that have low income or come from a different cultural 00:51:42.395 --> 00:51:50.434 - background than their provider. So I think that there needs to be like a multi-pronged approach to addressing 00:51:50.434 --> 00:51:57.742 - this and people will hold up as an example what we've done with tobacco. So physicians have learned 00:51:57.742 --> 00:52:00.446 - to counsel better about tobacco use. 00:52:00.546 --> 00:52:07.613 - The policies about taxing tobacco, the availability of tobacco, and then the perception of tobacco in 00:52:07.613 --> 00:52:15.026 - media has been changed. And we've actually seen tobacco use decline by a lot over time. It's been actually 00:52:15.026 --> 00:52:22.301 - a very successful public health intervention. For obesity, the hard thing is it's not just one behavior, 00:52:22.301 --> 00:52:29.022 - not whether you're lighting up a cigarette or not, but it's what you eat, how you move, and then 00:52:29.314 --> 00:52:35.983 - Not only how you move, but how you keep from sitting still. So sedentary activity is separate from physical 00:52:35.983 --> 00:52:42.158 - activity, and both of them have to be addressed. So I think the tough thing is telling people where 00:52:42.158 --> 00:52:48.333 - their markets are, where they can exercise, what they should do at home, how they parent, all those 00:52:48.333 --> 00:52:54.817 - things. Really, really complicated interplay of behavior that produces this health condition of carrying 00:52:54.817 --> 00:52:57.534 - too much weight. Yeah, maybe a couple more. 00:53:10.658 --> 00:53:18.823 - Yeah, so the question is what is there about best practices or evidence for preventing obesity in toddlers 00:53:18.823 --> 00:53:26.607 - and preschool kids or managing obesity? And I'll just say right now it's an open question with active 00:53:26.607 --> 00:53:34.314 - studies underway and everything that's been reported is preliminary. So there are piloting programs, 00:53:34.314 --> 00:53:40.190 - one just to show that we can safely talk about like reducing caloric intake. 00:53:40.290 --> 00:53:46.487 - for a toddler and helping toddlers choose better foods to eat. We really don't know how to do that. 00:53:46.487 --> 00:53:52.685 - We know more about, you know, in terms of activity, if you want a toddler to be active, then it has 00:53:52.685 --> 00:53:58.944 - to be things like play instead of exercise. And you're right about the mothers are just as important 00:53:58.944 --> 00:54:05.762 - or perhaps more important than the child. So for toddlers, certainly, they're a product of their environment. 00:54:05.762 --> 00:54:09.790 - They're making very few or essentially no independent decisions. 00:54:10.530 --> 00:54:19.722 - intervene on the guardians that are providing their care. I think that's part of the problem. I would 00:54:19.722 --> 00:54:29.095 - actually argue again for families that have low income and live in very distressed cities, even if they 00:54:29.095 --> 00:54:38.558 - know the right things to do, often they have a hard time achieving those things. So one thing I hear all 00:54:38.658 --> 00:54:45.211 - the time is, I really would love for my kid to be active. I would love to be outside. That's the way 00:54:45.211 --> 00:54:51.893 - I grew up. But where I live, they have to stay in the house. And that's just what I have to do to keep 00:54:51.893 --> 00:54:58.381 - them safe. So I don't know. I think it's also creating supportive environments that currently don't 00:54:58.381 --> 00:55:04.350 - exist, as well as educating and enabling families and individuals to change their behavior. 00:55:05.154 --> 00:55:09.118 - Okay, I'll take one more and then maybe I'll talk with you individually. So go ahead. 00:56:25.474 --> 00:56:29.822 - we can do this, we really could, we just have to decide that we... 00:57:04.866 --> 00:57:14.589 - I think that's a great closing comment. So again, thank you so much for taking time out of your day 00:57:14.589 --> 00:57:24.506 - to come and attend this talk and I'll stick around and if anybody has any other questions I'd love to 00:57:24.506 --> 00:57:27.326 - speak with you individually.