The prediction model provides an easy-to-use obesity evaluation tool that should help awareness of underweight and obesity conditions. Results of a multivariate linear regression analysis, which included HWDI and age as variables in the model, predicted BF% to be 34.508 − 0.159 (HWDI) + 0.161 (age) for men and 53.35 − 0.265 (HWDI) + 0.132 (age) for women. HWDI and BF% were found to be inverse which related to a tendency toward a linear relationship. Multiple linear and nonlinear regression analysis were used to construct the BF% prediction model. Pearson’s correlation coefficient was used to assess the relationship between HWDI and BF%. HWDI was calculated as the difference between height and weight. Bioelectrical impedance analysis was used to measure BF% in 2,771 healthy adult Thais. Our objectives were to find the relationship between HWDI and BF% and to find a BF% prediction model from HWDI in relation to age and gender. While body-fat percentage (BF%) is considered to be the most accurate obesity evaluation tool, it is a more expensive method and more difficult to measure than the others. The height-weight difference index (HWDI) is a new indicator for evaluating obesity status.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |