Feasibility of adolescents to conduct community-based participatory research on obesity and diabetes in rural Appalachia.

Community-Based Participatory Research (CBPR) has been advocated to translate advances in health care sciences to the community. We describe a novel approach applied to obesity management and diabetes prevention. This takes advantage of a network of science clubs organized by the Health Sciences and Technology Academy (HSTA) for extracurricular activity of disadvantaged high school students in rural Appalachia. Physician scientists and educators provided an intensive summer course on CBPR, ethics, and study design on obesity management and diabetes prevention. Ethical certification for CBPR investigation was obtained for 210 students and 18 mentors for a study on the prevalence of obesity and Type II diabetes within their community. Over a 6-month period, 989 had a collection of complete analyzable data, of which 103 had diabetes. The proportion with obesity (BMI > or = 30) was over 50%. The frequency of diabetes was related to increasing BMI. When BMI > or = 40, the frequency approached 50%, and exhibited a clear familial distribution. We conclude that trained adolescents can effectively conduct CBPR, and obesity and diabetes are more prevalent than previously reported in this community. This experience provides encouragement to conduct future studies to infl uence weight management from high-risk populations in this medically disadvantaged community.

Family networks of obesity and type 2 diabetes in rural Appalachia.

The prevalence of obesity and diabetes has been studied in adolescent and adult populations in poor, medically underserved rural Appalachia of West Virginia. A web-based questionnaire about obesity and diabetes was obtained in 989 family members of 210 Community Based Clinical Research (CBPR) trained adolescent members of a network of 18 science clubs, incorporating 142 families. After age-correction in < 20 years old, 50% of both adolescents and adults were obese. The frequency distribution of obesity was trimodal. In the overall population 10.4% had type 2 diabetes, while 24% of adult, obese subjects had type 2 diabetes. A new metric, the family diabetes risk potential, identified a trimodal distribution of risk potential. In the lowest most common distribution 43% of families had a diabetic family member. In the intermediate distribution, 69% had a diabetic family member, and in the distribution with highest scores all the families had a diabetic member. In conclusion, the poorest counties of rural Appalachia are at crisis level with the prevalence of obesity and diabetes. The distribution of age-corrected obesity and family diabetes risk potential are not normally distributed. We suggest that targeting individual family units at greatest risk offers the most efficient strategy for ameliorating this epidemic.

Team building: electronic management-clinical translational research (eM-CTR) systems.

Classical drug exposure: response studies in clinical pharmacology represent the quintessential prototype for Bench to Bedside-Clinical Translational Research. A fundamental premise of this approach is for a multidisciplinary team of researchers to design and execute complex, in-depth mechanistic studies conducted in relatively small groups of subjects. The infrastructure support for this genre of clinical research is not well-handled by scaling down of infrastructure used for large Phase III clinical trials. We describe a novel, integrated strategy, whose focus is to support and manage a study using an Information Hub, Communication Hub, and Data Hub design. This design is illustrated by an application to a series of varied projects sponsored by Special Clinical Centers of Research in chronic obstructive pulmonary disease at the University of Pittsburgh. In contrast to classical informatics support, it is readily scalable to large studies. Our experience suggests the culture consequences of research group self-empowerment is not only economically efficient but transformative to the research process.