Monday, March 14, 2016

Understanding Applied Regression Statistics in Physical Activity and Health Research: Columbia University EPIC Program, June 15-19, 2015



Adelphi’s CHI Summer Scholar Paul Rukavina, PhD, Associate Professor  & Coordinator of Physical Education Non-Certification Programs in the Department of Exercise Science, Health Studies, Physical Education, and Sport Management in the Ruth S. Ammon School of Education, Adelphi University.

This course was an introduction to the basics of regression analysis commonly used in the areas of physical activity and health promotion research. Sheila Vaidya, the instructor, systematically covered correlation, simple and multiple regression models, omnibus and partial F-Test, interpretation of interaction terms and using dummy coding for categorical variables. Last, we explored regression diagnostics and model type selection. The coursed described the theory and underlying assumptions of linear regression models. All of the classes were lecture-based and occurred at the Mailman School of Public Health at Columbia University.

I used the knowledge that I gained from the applied regression analysis class in a recent research project with colleagues Drs. Christy Greenleaf, University of Wisconsin-Milwaukee, and Jody Langdon, Georgia Southern University. We investigated the psychosocial predictors of obesity bias in pre-allied health and exercise science professionals, which includes the internationalization of general and athletic body ideals, perceived media pressure and information, and achievement goal orientations. 

We theorized pre-allied health and exercise science students had internalized attitudes from socialization in sport and exercise, and that these attitudes might predict attitudes toward overweight and obese individuals. The results indicated that the pre-allied health professionals were explicitly biased toward overweight and obese people, had internalized an athletic ideal (ideal body is toned for women, and athletically muscular for men), and had a high task orientation (improving oneself in sports) and ego orientation (comparison of oneself to others in sports).

Regression analyses produced some results as well. Internalization of the athletic body type predicted several aspects of obesity bias. In other words, those who held athletic body ideals were likely to be explicitly biased toward overweight and obese individuals. Also, task orientation negatively predicted character disparagement of overweight and obese. Those who had a tendency toward viewing one’s success as improving (using oneself as referent for success) tended not to hold stereotypes that disparaged the character of overweight and obese.

The results are important for those that prepare pre-allied health and exercise science professionals. If students’ attitudes go unchecked, these attitudes may negatively manifest when working with clients who lack athletic bodies or are overweight, such as overly blaming them for their condition and not providing the same attention or treatment as others who have more athletic body shapes and sizes.

It is important for professors to situate knowledge of overweight and obesity in a social ecological framework. Professors should emphasize that the determinants of body shape and size go beyond personal lifestyle choices and behavior; body shape and size are influenced by biology and genetics, social and physical environment, opportunities for health care, and policy making. Instead of assuming a client is lazy or lack will power, a client may be larger partly because of their genetics or lack of access to health foods, physical activity facilities, or health care.

The results of this study will be published in an upcoming issue of Advances of Physiology Education.