We divided these 9,881 girls and 12,768 boys into 26 groups based on their race year and investigated the secular trends in height, weight, and BMI over the 26-year study period. BMI was calculated using the formula [weight (kg)]/[height (m)]
2. We then calculated the means of these indices for runners by high school grade for each year. The BMIs of the runners were compared to those in the general population. We calculated the mean BMI by using the mean values of height and weight of the 1st, 2nd, and 3rd grades of high school boys and girls reported in the Annual Report of School Health Statistics Research (
14) as representative of the general population. These data were compiled from students attending thousands of schools chosen through multi-stage sampling. The significance of the secular trends in weight, height, and BMI by race year (regarded as a continuous variable) was assessed separately by the grade using linear regression analyses. When unstandardized regression coefficients differed significantly from 0, corresponding 95% confidence intervals (CIs) were calculated and values less or greater than 0 for the upper or lower bounds of 95% CIs indicated statistically significant linear trends of decrease or increase by year, respectively. When unstandardized regression coefficients were significantly negative, we calculated the differences in the mean BMIs between 1989 and 2014 to determine the magnitudes of the decrease in BMI during the 26-year study period.
The directory yielded the grades of runners but not their ages. The ages of high school students in the 1st, 2nd, and 3rd grades are supposed to be 15 - 16, 16 - 17, and 17 - 18 years, respectively. Therefore, we assumed that the mean ages of the runners for the 3 grades were 15.5, 16.5, and 17.5 years, respectively. To evaluate the prevalence of thinness, we divided the participants for each grade into 4 groups according to a sex-specific and age-adjusted classification for adolescents proposed by Cole et al. (
15) as follows: for girls, 1) not thin: BMI ≥ 17.69, 18.09, and 18.38 kg/m
2 for age 15.5, 16.5, and 17.5, respectively; 2) mild thinness: 16.22 ≤ BMI < 17.69 kg/m
2, 16.62 ≤ BMI < 18.09 kg/m
2, and 16.89 ≤ BMI < 18.38 kg/m
2 for age 15.5, 16.5, and 17.5, respectively; 3) moderate thinness: 15.25 ≤ BMI < 16.22 kg/m
2, 15.63 ≤ BMI < 16.62 kg/m
2, and 15.90 ≤ BMI < 16.89 kg/m
2 for age 15.5, 16.5, and 17.5, respectively; and 4) severe thinness: BMI < 15.25, 15.63, and 15.90 kg/m
2 for age 15.5, 16.5, and 17.5, respectively; for boys, 1) not thin: BMI ≥ 17.26, 17.80, and 18.28 kg/m
2 for age 15.5, 16.5, and 17.5, respectively; 2) mild thinness: 15.82 ≤ BMI < 17.26 kg/m
2, 16.34 ≤ BMI < 17.80 kg/m
2, and 16.80 ≤ BMI < 18.28 kg/m
2 for age 15.5, 16.5, and 17.5, respectively; 3) moderate thinness: 14.86 ≤ BMI < 15.82 kg/m
2, 15.36 ≤ BMI < 16.34 kg/m
2, and 15.81 ≤ BMI < 16.80 kg/m
2 for age 15.5, 16.5, and 17.5, respectively; and 4) severe thinness: BMI < 14.86, 15.36, and 15.81 kg/m
2 for age 15.5, 16.5, and 17.5, respectively. These values in the criteria were from an international survey that included nationally representative data from large growth studies conducted in 6 countries, including Singapore, Hong Kong, Brazil, the Netherlands, Great Britain, and the U.S. We then calculated the percentages of participants in each thinness category among the total participants in each year. Logistic regression analysis was used to assess the secular trends in the prevalence of each thinness category (treated as the binary outcome) by grade, with the race year being treated as a continuous variable. Odds ratios (ORs) with corresponding 95% CIs were calculated, and a value greater than 1.0 for the lower bound of a 95% CI indicated a statistically significant increase of the prevalence by year.
We had a set of height and weight data measured among 45 female race participants within a few months before or after the Championships held between 2001 and 2011. Paired t-tests were performed to examine the difference between the self-reported data in the magazines and the measured. A correlation analysis was also conducted to measure the relationship between them.
All statistical analyses were performed using SPSS® 15.0J for Windows (IBM, Japan). P < 0.05 was considered statistically significant. The study was approved by the ethical committee of the Faculty of Sports and Health Studies, Hosei University (No. 201302-1).