title: Formulas predicting the percentile of serum cholesterol levels by age in adults.
abstract: The data of the National Health and Nutrition Examination Survey comprehensively have shown that distributions of serum cholesterol levels in the US adult population are age and sex dependent. General formulas have been constructed on the basis of the data of the National Health and Nutrition Examination Survey to predict the adult percentile in the population for serum cholesterol levels by age. A mathematical model and a computer program previously published by the author were employed in this study. Analysis of the computer-assisted predicted and the National Health and Nutrition Examination Survey-reported percentiles indicated that the designed program for calculating the formula was accurate and reliable. The formulas can determine the relationship among adult age, serum cholesterol level, and population percentile. It has been reported that adult individuals tend to have persistently the same percentiles of their serum cholesterol levels in the population with increasing ages in the absence of cholesterol-altering intervention. The percentiles predicted by the formula may reflect the relative degrees of risk for coronary heart disease. This information on the percentile may have a preventive diagnostic value for the detection, evaluation, and treatment of patients with high cholesterol levels. The percentile may be used as a parameter of risk assessment for coronary heart disease for all adult ages and sexes. However, clarification of a probable relationship between high percentiles (like high cholesterol levels) and coronary heart disease, and justification of the use of percentiles as a risk parameter, must await further clinical investigation.
authors.affiliation: Department of Pathology, Morristown-Hamblen Hospital, TN 37814.
authors.forename: S J
authors.initials: SJ
authors.lastname: Chung
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D002784:Cholesterol / Q000097:blood*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D012984:Software
chemical_list: D002784:Cholesterol