The Prevalence of Metabolic Syndrome in an NHANES Population.
Authors: Hollenbeak Christopher , Spackman Eldon , Page Matthew J. , Ben-Joseph3 Rami , Williamson3 Todd 
Published: October 2019

Abstract
Metabolic syndrome (MetS) is a constellation of metabolic risk factors that can lead to diabetes, cardiovascular events, and other complications. MetS is recognized by several standards-setting bodies, including the National Cholesterol Education Program - Adult Treatment Panel III (NCEP-ATP III) and the International Diabetes Federation (IDF). In this study, we used a nationally representative set of data to create a model to predict the prevalence of MetS in a population from demographic information. Data for this study were from the National Health and Nutrition Examination Survey (NHANES) data set, a nationwide probability sample survey designed to collect information on the health and nutritional status of the U.S. population through interviews and direct physical examinations. NHANES 2001–2002 includes data for 11,039 persons, of which 2,605 had information necessary for identification of metabolic syndrome. A weighted logistic regression model was used to determine the effects of gender, age, ethnicity, and smoking status on the prevalence of MetS based on IDF and NCEP-ATP III criteria. Estimated coefficients were then used to predict the prevalence of MetS conditional on the demographic characteristics of the population. In addition, the model predicts the one-year risk of acute myocardial infarction and stroke as well as the prevalence of coronary heart disease, congestive heart failure, and type 2 diabetes among those with MetS. Values were calculated based on the population age 18 and over as reported by the U.S. Census combined with the NHANES 2001–2002 means for the other demographic variables (gender, mean age, ethnicity, smoking status). The model was validated using an earlier NHANES cohort (1999–2000). Table 1 presents the prevalence of MetS based on the two definitions and the percentage of each population exceeding the risk thresholds for each of the five MetS components. The estimated rate of metabolic syndrome in the U.S. is 25.0% according to the NCEP-ATP III definition and 41.3% according to the IDF definition, a difference most likely attributable to the smaller waist circumference listed by the IDF definition. The complications are not consistently higher for either group as defined by NCEP-ATP III or IDF. The model validation shows how well the model predicts MetS prevalence in the NHANES 1999–2000 data. The predicted prevalence using demographics from NHANES 1999–2000 and following the NCEP-ATP III definition was 24.7% compared to an actual prevalence of 23.1%. Using the IDF definition the prevalence was predicted to be 40.9% and the actual prevalence was 39.2%. For both definitions predictions were within the 95% probability range suggested by the model. In a disease where actual clinical measures are required for diagnosis, it is possible to model and predict the prevalence of MetS using fundamental demographic data. Therefore, this model will be useful for healthcare providers and decision makers in estimating the prevalence of MetS when clinical measures are absent.
Table 1. Prevalence of Metabolic Syndrome and Its Components NCEP-ATP III IDF * Annual Risk, ** Prevalence Prevalence 25.0% 41.3% Components High Waist Circumference 88.5% 100% High Triglycerides 83.3% 65.5% Low HDL Cholesterol 82.0% 58.5% High Blood Pressure 62.7% 72.9% High Fasting Plasma Glucose 76.4% 66.0% Complications Acute Myocardial Infarction * 0.4% 0.8% Stroke * 0.8% 0.6% Coronary Heart Disease ** 4.8% 5.0% Congestive Heart Failure ** 4.0% 3.6% Diabetes ** 24.0% 20.6%