A cross-sectional study of the association of age, race and ethnicity, and body mass index with sex steroid hormone marker profiles among men in the National Health and Nutrition Examination Survey (NHANES III). Issue 5 (6th October 2012)

• Record Type: Journal Article
• Authors: Ritchey, Jamie; Karmaus, Wilfried; Sabo-Attwood, Tara; Steck, Susan E; Zhang, Hongmei
• Is Part Of: BMJ open. Volume 2:Issue 5(2012)
• Publication Date: 2012-10-06
• Subjects: Epidemiology; Medicine -- Research -- Periodicals; 610.72
• DOI: 10.1136/bmjopen-2012-001315
• Languages: English
• ISSNs: 2044-6055

Abstract

Abstract : Objectives: Since sex hormone markers are metabolically linked, examining sex steroid hormones singly may account for inconsistent findings by age, race/ethnicity and body mass index (BMI) across studies. First, these markers were statistically combined into profiles to account for the metabolic relationship between markers. Then, the relationships between sex steroid hormone profiles and age, race/ethnicity and BMI were explored in multinomial logistic regression models. Design: Cross-sectional survey. Setting: The US Third National Health and Nutrition Examination Survey (NHANES III). Participants: 1538 Men, >17 years. Primary outcome measure: Sex hormone profiles. Results: Cluster analysis was used to identify four statistically determined profiles with Blom-transformed T, E, sex hormone binding globulin (SHBG), and 3-α diol G. We used these four profiles with multinomial logistic regression models to examine differences by race/ethnicity, age and BMI. Mexican American men >50 years were associated with the profile that had lowest T, E and 3-α diol G levels compared to other profiles (p<0.05). Non-Hispanic Black, overweight (25–29.9 kg/m 2 ) and obese (>30 kg/m 2 ) men were most likely to be associated with the cluster with the lowest SHBG (p<0.05). Conclusion: The associations of sex steroid hormone profiles by race/ethnicity are novel, while the findings by age and BMI groups are largely consistent with observations from single hormone studies. Future studies should validate these hormone profile groups and investigate these profiles in relation to chronic diseases and certain cancers.