236723 A Comparison of Methods for Sex Steroid Hormone Adjustment, National Health and Nutrition Examination Survey (NHANES III)

Tuesday, November 1, 2011: 12:50 PM

Jamie Ritchey, MPH, PhD , US Army Public Health Command, Behavioral and Social Health Outcomes Program, Oak Ridge Institute for Science and Education (ORISE), Aberdeen Proving Ground, MD
Hongmei Zhang, PhD , Arnold School of Public Health, Epidemiology and Biostatistics, University of South Carolina, Columbia, SC
Wilfried Karmaus , Arnold School of Public Health, Epidemiology and Biostatistics, University of South Carolina, Columbia, SC
Susan E. Steck, PhD , Department of Epidemology and Biostatistics & Cancer Prevention and Control Program, University of South Carolina, Columbia, SC
Tara Sabo-Attwood, PhD , Department of Environmental Health Sciences, Norman J. Arnold School of Public Health, University of South Carolina, USA;, University of South Carolina, Columbia, SC
Introduction: Differences in testosterone (T), 17- estradiol (E) and sex hormone binding globulin (SHBG) have been hypothesized to explain racial disparities in chronic disease rates, yet epidemiologic results have been mixed. Since T and E are transported by SHBG, it is considered essential to estimate free T and E by adjusting total T and E levels by SHBG. Therefore, we compared standardization (E/SHBG or T/SHBG) and different statistical adjustment approaches of T and E for SHBG. Methods: We investigated data of 1,506 men, >=17 years from the Third National Health and Nutrition Examination Survey (NHANES III). To examine linearity between sex hormones and SHBG we used plots and regression models. We included age, body mass index (BMI), E, and race in models to determine if the statistical importance of these variables changed by the method of SHBG adjustment. Results: We found that T and E were moderate and weakly correlated with SHBG, respectively (r-squared, T 0.25, E 0.04). Based on model residual plots and r-squared, the categorical model performed better than the linear models. To address non-linearity by using SHBG in quintiles adjusting T, the associations of T with specific levels of age, race, BMI, and E changed by more than 10% compared to both linear models. Conclusion: Choosing an appropriate adjustment for model variables is important to prevent bias in analyses, and confusion across studies. Linearity between variables should not be assumed automatically when adjusting sex steroid hormones by SHBG, however, this needs to be determined in each study.

Learning Areas:
Epidemiology
Public health biology
Public health or related research

Learning Objectives:
1. Identify linear and non-linear methods in the literature used to model the relationship between sex steroid hormones (testosterone and 17- estradiol) and sex hormone binding globulin (SHBG). 2. Discuss the importance of evaluating linearity between variables when adjusting testosterone and 17- estradiol for sex hormone binding globulin in linear regression models for each analysis population, even when using national samples like NHANES III data.

Keywords: Biostatistics, Endocrine

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: This is part of my PhD dissertation.I have 10+ years of public health experience using SAS and SPSS to manage and analyze data examining disease etiology, health services research, and health policy hypotheses leading to public health reports and peer-reviewed publications. I completed my dissertation work off-site in a different state, while working full time in public health. Along with communicable disease investigations, I am the go to person for epidemiologic advice designing studies, creating databases, and/or conducting SAS/SPSS analysis for tobacco, syphilis, hepatitis, back to school immunization satisfaction survey, and disease outbreak studies.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.