Disordered eating in Japanese and Chinese female runners, rhythmic gymnasts and gymnasts.
Eating Attitude Test-26 (EAT-26) and self-administered questionnaires were used to survey eating attitudes and menstrual irregularity of Japanese (J) and Chinese (C) collegiate female runners (RUNs), rhythmic gymnasts (RGYMs), gymnasts (GYMs), and nonathletic controls (NAs). Athletes were recruited from several outstanding colleges for physical education and sport in each country. The prevalence of disordered eating (DE) was significantly higher in Japanese athletes (21% in JRUNs, 19% in JRGYMs, and 15% in JGYMs) than Chinese athletes (4% in CRUNs, 2% in CRGYMs, and none in CGYMs). Also, the prevalence of amenorrhea was very low in CRUNs (1%), CRGYMs (0%), and CGYMs (0%), as compared with their respective Japanese counterparts (JRUNs 22%, JRGYMs 10%, JGYMs 8%). There was no significant difference in the prevalence of DE and amenorrhea between Japanese and Chinese NAs. Multivariate logistic regression analysis using 10 independent variables regarding anthropometrics, athletics, weight and diet concern, and nationality indicated that high frequency of dieting during a lifetime, high athletic level and being Japanese were significant risks for the development of DE in athletes. It is concluded that the low prevalence of DE in the Chinese in this study is partly explained by the lack of socioculturally- and socioeconomically-imposed desire to be thin as well as by the low frequency of dieting during their lifetime.
Okano
G
G
Division of Exercise Science, Sapporo Medical University, Sapporo, Japan. okano@sapmed.ac.jp
Holmes
R A
RA
Mu
Z
Z
Yang
P
P
Lin
Z
Z
Nakai
Y
Y
D000568:Amenorrhea / Q000208:ethnology; D015992:Body Mass Index; D015984:Causality; D016009:Chi-Square Distribution; D002681:China / Q000453:epidemiology; D015897:Comorbidity; D001068:Feeding and Eating Disorders / Q000208:ethnology*; D005260:Female; D006173:Gymnastics / Q000706:statistics & numerical data*; D006801:Humans; D007564:Japan / Q000453:epidemiology; D016015:Logistic Models; D015995:Prevalence; D012307:Risk Factors; D012420:Running / Q000706:statistics & numerical data*