Characterizing extreme values of body mass index-for-age by using the 2000 Centers for Disease Control and Prevention growth charts

National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD 20782, USA.
American Journal of Clinical Nutrition (Impact Factor: 6.77). 09/2009; 90(5):1314-20. DOI: 10.3945/ajcn.2009.28335
Source: PubMed


The 2000 Centers for Disease Control and Prevention (CDC) growth charts included lambda-mu-sigma (LMS) parameters intended to calculate smoothed percentiles from only the 3rd to the 97th percentile.
The objective was to evaluate different approaches to describing more extreme values of body mass index (BMI)-for-age by using simple functions of the CDC growth charts.
Empirical data for the 99th and the 1st percentiles of BMI-for-age were calculated from the data set used to construct the growth charts and were compared with estimates extrapolated from the CDC-supplied LMS parameters and to various functions of other smoothed percentiles. A set of reestimated LMS parameters that incorporated a smoothed 99th percentile were also evaluated.
Extreme percentiles extrapolated from the CDC-supplied LMS parameters did not match well to the empirical data for the 99th percentile. A better fit to the empirical data was obtained by using 120% of the smoothed 95th percentile. The empirical first percentile was reasonably well approximated by extrapolations from the LMS values. The reestimated LMS parameters had several drawbacks and no clear advantages.
Several approximations can be used to describe extreme high values of BMI-for-age with the use of the CDC growth charts. Extrapolation from the CDC-supplied LMS parameters does not provide a good fit to the empirical 99th percentile values. Simple approximations to high values as percentages of the existing smoothed percentiles have some practical advantages over imputation of very high percentiles. The expression of high BMI values as a percentage of the 95th percentile can provide a flexible approach to describing and tracking heavier children.

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    • "There are also racial/ethnic disparities in the prevalence of extreme obesity among children [9,21e23]; these disparities are evident as young as preschool and observed within limited socioeconomic strata such as low-income samples [24] [25]. Most prior studies have examined differences in the proportion of children falling above various body mass index (BMI) cutoffs (e.g., 97th or 99th percentile [9] [22] [23], 1.2 times the 95th percentile [21] [26]). National estimates for the United States suggest that non-Hispanic black children are nearly twice as likely to fall above the 97th BMI percentile for age and sex compared with non-Hispanic white children (18.6% vs. 9.8%, respectively), and rates are also high among Hispanic children (15.6% [9]). "
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