Board certified in internal medicine a card carrying phd level epidemiologist. One of his many areas of expertise is obesity and weight loss. He teaches an undergraduate class and humbio titled obesity in America is currently close to completing a community based NIH r 1 level intervention targeting weight loss and more than 200 adults in a local underserved community hear more from him later today he's gonna help lead the discussion about the north coast. But for now he'll present some of his current thoughts on community based research. Thanks. Well, thanks very much.
I'm gonna follow terms of interventions and talk a little bit about vivomixx, which is a obesity reduction program in a low income Latino neighborhood. I came here in 2001. We randomize more than 400 individuals from county health, these county primary care centers. We follow them for 15 months and we used a intervention that relied on one in one case management by nurses and dietitians. We compared these intervention participants to usual care. And what we wanted to do was aggregate as well as we could all cardiovascular risk factors and one way of doing this was a Framingham risk. And what we essentially found in this was that if we looked at this Framingham risk probability, that is the likelihood of having a cardiac event over the next ten years again predicted risk. We saw that for usual care, there was an increase in that risk while the case manage group.
Case management to focus on individual cardiovascular risk factors. We saw reduction in that probability. But I think we also learned some other things. First of all, that risk factor management was really difficult. Those differences I just showed you are at best modest even though they are statistically significant. And this is especially true when they were CO comorbidities present. In fact, the participants and physicians that we were working with were really satisfied by this type of intervention. However, the nurses and dietitians were really expensive and we were thinking about sustainability and cost effectiveness. We needed to think about different ways that we might make the intervention more efficient. And then finally. And perhaps most importantly, we found that participants were really interested in weight loss, but the case managers couldn't focus on this issue largely because they were so occupied by risk factor management via medication's. And then finally.
We heard again and again and observed that participants in heart to heart really needed extra help putting the case manager or their primary care physician advice into action. So it's on the basis of these sort of insights that we designed our follow on study, which we call vivamus evos. And this is cited at one of the four health centers that. Studied initially. We have randomized the population of 207 obese. Low income Latino primary care patients. This is a population with low levels of education, most of which was obtained in Mexico. Each of these individuals has at least one inadequately controlled cardiovascular risk factor. We are in the process of following this population for 24 months. Using two separate interventions, the first is a case management approach very similar to heart to heart where we have both one on one meetings with participants to try to facilitate weight loss as well as group sessions that have an informational component as well as a behavioral change component.
The second intervention is essentially adding on to that case management intervention, a community health worker home visit where these various implementation barriers are addressed within the participants home. We also have a comparison group and you'll note that there's unequal randomization allocation between these three these three groups in part because the most important contrast is between the case management with or without the community health worker. But I gave it to another reason for the unequal allocation. Our primary outcome is change in BMI. But we're also looking at a whole host of secondary outcomes, including individual risk factors. Some of the mediators that we think may be involved in facilitating facilitating weight loss in these patients and then also very carefully looking at whether we can detect moderators that might predict who is going to lose more weight within this type of intervention. We are in the process of continuing the intervention. Our last participant was randomized a year ago, so we're following that last cohort of recruits for the next 12 months. In terms of the objectives we have with this study. A lot of this was really focused on using participatory methods to develop this intervention. Specifically tailoring it for not only a Latino community, but for the residents of a particular neighborhood. This is a neighborhood that's in unincorporated San Mateo County, sort of wedge between Atherton and redwood.
We certainly wanted to conduct a RCT evaluating these two weight loss strategies. But we also wanted to integrate this program into the primary care delivery system at this health. A very important part of this is to also estimate the cost effectiveness. Again, we've designed this to be more efficient both through using group sessions and using a health educator rather than a more highly trained dietitian or nurse and then using a community health worker who's a largely been trained simply to provide the sort of advice that will help his fellow neighbors lose way. On the basis of all the information that we're collecting, our hope is that we're going to transition this. Research program into an ongoing county program. Essentially using the clinical trial to obtain rigorous information that builds a business case for why the county should take over this program. Here's just a very quick summary of the design. Much of the intervention is front loaded into the first six and 12 months with a maintenance phase for the next 12 months and. And you'll see that we have assessments at 6, twelve eighteen and then a final endpoint at 24 months. Just to show you a little bit about the population that we've recruited. As I said. This is a low education group, much more so for women, 100 percent of this population was born outside of the United States. Here are some of the baseline values.
I don't wanna focus on anything other than the first line. Which suggests that we have a population that averages a BMI of around 35 to 36. In terms of strategies, we've incorporated into this clinical trial. I wanna talk about some specific elements that make this perhaps different from a clinical trial that is cited in a clinical research. A clinic located at Stanford. So we had to confront what I feel is valid community suspicion about experimentation, particularly the idea that we would have a population that would be randomized the usual care. To overcome this. We did a lot of consultation with community based organizations as well as our county sponsor who runs the delivery system. We felt it very important to integrate this into the healthcare setting both to show that this was a feasible strategy as well as to think about sustainability. We have provided incentives to the participants. But really only for the research aspects of this, we haven't incentives people for the interventional aspects. We sought to minimize the size of the control group, both because it made sense statistically, but also because we wanted to have most of the individuals receiving the active interventions. And finally, even those who are randomized to usual primary care will be crossed over into intervention once the 24 month period is up. So just to sort of talk a little bit about some of the challenges.
A lot of logistical obstacles to success in this type of research. We're working in settings that don't have the infrastructure that we have on campus. Including these community organizations adds extra complexity. The populations and the community based organizations are skeptical and we need to convince them about the value of research. And many of these organizations don't necessarily have the same commitment to scientific rigor that we might want them to do. And of course. Turf wars over funding and personnel are common in this setting. However, this is offset i believe by a large number of charms of working in this sort of, setting. We're really intervening in the real world. Not the optimized research clinic. In some sense. We're trying to re-envision health from the community's perspective and not necessarily impose only our viewpoint on what communities need to do. We're working with a population in great need. And working with organizations that at the end of the day are really grateful for the resources and expertise that we have contributed. And finally, we're contributing to reducing health disparities and i'll just end on the note that I believe that unless we consciously and explicitly take into account. Health disparities and work to reduce them. We may actually add to them if we use interventions and technologies that work best in middle class white populations. Thank you.
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