A Community‐Based Participatory Research/Translational Biomedical Research Strategy for Personalizing Nutrition, Medicine, and Healthcare

Abstract

AbstractPersonal and public health information is usually derived from studies of large population groups. Although reported as population attributable risk (PAR), these estimates are often applied to individuals. PARs for intake of nutrients, exposure to toxins, responses to drug, having certain genetic variants, and, more recently, nutrient{‐‐}gene interactions are statistical estimates of the percentage reduction in disease in the population if the risk were to be avoided or the gene variant were not present. Individuals differ in genetic makeup, life‐style, and dietary patterns and may not be represented by individuals in the study population. Although these risk factors are valuable guidelines, they may not apply to individuals. Intervention studies are likewise limited by small sample sizes, short time frames to assess physiological changes, and variable experimental designs that often preclude comparative or consensus analyses. A fundamental challenge for personalizing nutritional recommendations to optimize health and medicine for getting the right drug to the right person at the right time will be to develop a means to sort individuals into groups and, eventually, develop risk factors for individuals. The classic case{‐‐}control prospective design may need to be revised in order to develop individual risk factors. A promising approach for more complete analyses of the interaction of genetic makeups and environment relies on translational research strategies where the study participant is physiologically monitored over time. Community‐based participatory research (CBPR) methodology is a form of translational research whose central focus is developing a partnership among researchers and individuals in a community that allows for more in‐depth life‐style analyses but simultaneously helps improve the health of individuals and communities through application of research outcomes.