Exploring the Effects of Tai Chi on Cardiometabolic Risk in Women

Cardiovascular disease (CVD) is the leading cause of death in the United States. Historically, CVD has been under diagnosed and inadequately treated in women related to issues of gender bias, lack of public and medical awareness of its prevalence, and its unique presenting symptomatology. Despite increasing awareness, as well as better diagnostics and treatment, women are still more likely than men to present with advanced disease and experience higher CVD-related morbidity and mortality. Given these facts, prevention of CVD is critical. Cardiometabolic risk (CMR) is a relatively new term for a set of risk factors that, when viewed together, are indicators of overall risk for developing CVD. CMR is useful for assessing, modifying, and ultimately preventing the development of CVD. Prevention of CVD in women may best be achieved by early identification and treatment of evolving CMR. Central or abdominal obesity, reflecting the presence of visceral adipose tissue and evidenced by increased waist circumference, has been shown to be a significant predictor of CVD. In this PNI-based model of CMR and fatigue, abdominal adiposity and fatigue are products of allostatic load. Resulting from cumulative wear and tear, fatigue gives rise to dysregulation of metabolic processes, ultimately resulting in subjective symptomatology and disease risk. Additionally, fatigue often accompanies metabolic changes, potentiating a trajectory of CMR related to decreased physical activity and self-care. Tai chi may enhance relaxation and could potentially reduce CMR. The specific aims of this project are to refine a tai chi intervention using a wait-list pretest-posttest design with repeated measures. Feasibility and acceptability of the intervention and identification of potential indicators of effectiveness also will be assessed. Additionally, a PNI-based model of fatigue and CMR will be further refined. The first aim will be analyzed using a mixed effects model. The second specific aim, to refine a PNI-based model of fatigue and CMR, will be examined using descriptive statistics, graphical methods and pairwise correlations and, as a second step, variable reduction methods including factor analysis, principle component analysis and canonical correlation analysis. The project is based on a theoretically and scientifically sound framework to investigate a more comprehensive, sensitive, and innovative model for understanding, measuring, and potentially reducing CMR in women. With further studies, the goal of this line of research is to reduce CMR and perhaps reduce morbidity and mortality related to CVD.