Growth curves for cardio-metabolic risk factors in XXXX and adolescents.

@entity1 @entity854 @entity1674 @entity165
OBJECTIVE: This study developed percentile curves for anthropometric (waist circumference) and cardiovascular (lipid profile) risk factors for US @entity1 and adolescents. STUDY DESIGN: A representative sample of US @entity1 and adolescents from the National Health and Nutrition Examination Survey from 1988 to 1994 (NHANES III) and the current national series (NHANES 1999-2006) were combined. Percentile curves were constructed, nationally weighted, and smoothed using the Lambda, Mu, and Sigma method. The percentile curves included age- and sex-specific percentile values that correspond with and transition into the adult abnormal cut-off values for each of these anthropometric and cardiovascular components. To increase the sample size, a second series of percentile curves was also created from the combination of the 2 NHANES databases, along with cross-sectional data from the Bogalusa Heart Study, the Muscatine Study, the Fels Longitudinal Study and the Princeton Lipid Research Clinics Study. RESULTS: These analyses resulted in a series of growth curves for waist circumference, total @entity165 , LDL @entity165 , @entity1674 , and HDL @entity165 from a combination of pediatric data sets. The cut-off for abnormal waist circumference in adult males (102 cm) was equivalent to the 94(th) percentile line in 18-year-olds, and the cut-off in adult females (88 cm) was equivalent to the 84(th) percentile line in 18-year-olds. @entity1674 were found to have a bimodal pattern among females, with an initial peak at age 11 and a second at age 20; the curve for males increased steadily with age. The HDL curve for females was relatively flat, but the male curve declined starting at age 9 years. Similar curves for total and LDL @entity165 were constructed for both males and females. When data from the additional @entity1 studies were added to the national data, there was little difference in their patterns or rates of change from year to year. CONCLUSIONS: These curves represent waist and lipid percentiles for US @entity1 and adolescents, with identification of values that transition to @entity854 . They could be used conditionally for both epidemiological and possibly clinical applications, although they need to be validated against longitudinal data.
