I'm wondering if anyone knows of a Stata command that can do the same thing (i.e., use child BMI, age, and gender to produce a variable containing BMI relative to the 95th percentile, or even just produce the specific 95th percentile for any age, gender combination ). The limitations of expressing extremely high BMIs as z-scores apply to both cross-sectional and longitudinal studies, including those that evaluate obesity interventions. ![]() If a large proportion of children in an analysis have severe obesity (bmipct95 ≥ 120), you should consider expressing all BMIs relative to the 95 th percentile and using bmipct95 or bmidif95 in analyses. In addition to these 2 variables, the SAS program also outputs the CDC 50th ( bmi50) and 95 th ( bmi95) percentiles for the child's sex and age. ![]() A negative value for bmidif95 (or a bmipct95 < 100) would indicate that the child does not have obesity. For example, the CDC 95 th percentile for a 20-month-old boy is 18.0 kg/m 2 if this boy had a BMI of 21.3kg/m 2, his bmidif95 would be 3.3 kg/m 2 (21.3 - 18.0) and his bmipct95 would be 118% (100 × 21.3/18.0). Bmidif95 is the difference (in kg/m 2) between the child's BMI and the CDC 95 th percentile for that sex/age. Bmipct95 can range from below 50 to over 220, and a child with a bmipct95 of 140 would have a BMI that is equal to 1.4 times the 95th percentile. These 2 variables are likely to be better measures of adiposity among children who have very high BMIs than are z-scores and percentiles. The SAS code creates 2 variables, bmipct95 and bmidif95, that express a child's BMI relative to the 95 th percentile either as a percentage (bmipct95) or as a difference (bmidif95). The drawbacks of expressing very high BMIs as z-scores (or percentiles) have been emphasized by several investigators.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |