3.8 Article

Mucosal IgA and URTI in American college football players: A year longitudinal study

Journal

MEDICINE AND SCIENCE IN SPORTS AND EXERCISE
Volume 37, Issue 3, Pages 374-380

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1249/01.MSS.0000155432.67020.88

Keywords

immunefunction; athletes; illness; infection

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Purpose: The purpose of this study was: (a) to evaluate secretory immunoglobulin A (s-IgA) over a 12-month time period in college football players, and (b) to assess which of the commonly used standard methods of reporting s-IgA, either alone or in combination, serves as the best predictor of incidence of upper respiratory tract infection (URTI). Methods: One hundred college-aged males (75 varsity college football athletes, 25 nonfootball controls) were studied at eight points over a 12-month period. Resting mucosal IgA, protein and osmolality levels were determined from saliva using established procedures. In addition, incidence of URTI over the 12-month study duration was calculated from completed standard research logs. Repeated-measures ANOVA were conducted on the dependent variables and eight separate stepwise multiple regression analyses were conducted to predict the dependent variable number of colds by the independent variables, s-IgA, saliva flow rate, secretion rate of s-IgA, protein, s-IgA:protein, osmolality and s-IgA:osmolality at each data collection point. Results: There was a significant main effect for group, time, and the group X time interaction for s-IgA, the secretion rate of s-IgA, and the number of colds. In the regression model, the only variable that made a significant contribution to the variance at all time points was the secretion rate of s-IgA. Conclusion: These findings suggest that a season of training in American football results in a significant decrease in both s-IgA and the secretion rate of s-IgA as well as an increase in the incidence of URTI. Among the various methods commonly employed to express s-IgA levels, the secretion rate of s-IgA may be the most useful clinical biomarker to predict the incidence of URTI.

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