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Title: Developing community friendly appropriate biomarkers

Author
item SIMPSON, PIPPA - ACHRI-DAC
item JO, CHAN-HEE - ACHRI-DAC
item GOSSETT, JEFF - ACHRI-DAC
item HUANG, B. EMMA - UNC
item VARGAS, PERLA - ACHRI-DAC
item Bogle, Margaret

Submitted to: International Society for Behavioral Nutrition and Physical Activity
Publication Type: Abstract Only
Publication Acceptance Date: 4/20/2007
Publication Date: 6/16/2007
Citation: Simpson, P., Jo, C., Gossett, J., Huang, B., Vargas, P., Bogle, M.L. 2007. Developing community friendly appropriate biomarkers [abstract]. Proceedings of the International Society for Behavioral Nutrition and Physical Activity. p. 214.

Interpretive Summary:

Technical Abstract: In this presentation we discuss the statistical methodology used in the development of biomarkers to track disease as an outcome for nutrition or exercise interventions in community settings. Obesity and co-morbidities are of growing concern. Nutrition and physical activity interventions have been developed to reduce these problems and associated diseases. However, biomarkers for tracking disease existence and progress, like blood pressure or HDL for heart disease, may be unreliable and of limited use for comparison of intervention groups even in clinical settings. Thus, the search for more reliable and sensitive biomarkers suitable for use in community settings continues. This presentation focuses on the statistical methodology needed to develop reliable biomarkers for use in community settings. It covers the evaluation of data collection processes and steps necessary to translate a clinical biomarker into a reliable biomarker suitable for non-clinical community environments. This includes choosing an appropriate and feasible sample to establish validity, and the assessment of reliability, and predictivity of the biomarker. Examples are given from the literature, and some results from the U.S. National Health and Nutrition Evaluation Survey (NHANES) data are presented. Community friendly biomarkers will be applicable to smaller samples and allow for quicker evaluation of the effectiveness of efforts to reduce obesity and its related morbidities.