Metabolic syndrome is a disease that simultaneously causes hyperglycemia, hypertension, hyperlipidemia, and abdominal obesity, which are major risk factors for cardiovascular diseases. Statistics Korea reported the ranking of diseases resulting in death in South Korea over the past 10 years, and it indicated that endocrine and metabolic diseases were the 4th major cause of death after cancer, heart disease, and respiratory diseases. Therefore, it is a serious health problem. The occurrence of metabolic syndrome is increasing worldwide, and it has been reported that it is increasing remarkably in Asia including South Korea.

Metabolic syndrome has different characteristics depending on race, region, gender, age, and family history, and various study results have been reported accordingly. Moreover, it has been revealed that lifestyle factors affect the components of metabolic syndrome and that intervening lifestyle can delay or prevent the onset of metabolic syndrome. Therefore, it can be said that metabolic syndrome requires medical treatment as well as correction of wrong living habits.

The 'Alameda County' study is a large-scale epidemiological study conducted in California, USA, in 1965 and is a representative study that identified the relationship between an individual's lifestyle with health status and disease susceptibility. This study suggested seven health behaviors (known as Alameda 7 model) related to health level, which were smoking, drinking, obesity, exercise, breakfast and snacks, and sleep. It was found that these health behaviors were highly associated with disease and death through follow-up studies. Nevertheless, prior studies based on the Alameda7 model just focus on identifying individual risk factors for diseases, and only a few studies considered multiple risk factors. In particular, since patient-centered (medical institution-centered) studies have low external validity, there is a limitation in generalizing and applying the results to the general population.

Consequently, it is necessary to analyze epidemiological data that can represent adults living in the community in order to understand and prevent metabolic syndrome. This study analyzed the relationship between health risk behaviors and metabolic syndrome in the Alameda7 model using an epidemiological survey representing Koreans. Moreover, this study developed a nomogram that allows clinicians to easily predict the group posing a high risk for metabolic syndrome in the primary health care setting.

This study analyzed 12,871 adults (≥19 years) who participated in the 6th Korean National Health and Nutrition Examination Survey. Metabolic syndrome was defined based on the Third Report of the National Cholesterol Education Program (NCEP)Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults(Adult Treatment Panel III)published by the National Institutes of Health. According to the criteria of the Adult Treatment Panel III, metabolic syndrome is diagnosed when a subject satisfies three conditions out of the following five conditions: waist circumference (≥102 cm for men and ≥88cm for women), triglyceride (≥150 mg/dl), HDL-cholesterol (<40mg/dl for men and <50mg/dl for women), blood pressure (systolic blood pressure ≥130 mmHg or more, or diastolic blood pressure ≥85 mmHg), and fasting blood sugar (100 mg/dl or more). Health risk behavior was defined as non-compliance with the guidelines of the Alameda7 model (smoking, excessive drinking, physical inactivity, inadequate weight control, inadequate sleep, skipping breakfast, and snacking). This study built a model for predicting metabolic syndrome using logistic regression to determine the relationship (influence) of each of the seven health risk behaviors with metabolic syndrome. The forward selection method was used to select variables in the logistic regression model, and the results were presented in the form of an unadjusted model and an adjusted multivariate model in which all seven variables were adjusted. The prediction accuracy of the developed metabolic syndrome prediction model was presented by AUC, balanced accuracy, general accuracy, and F1 score using 10-fold cross-validation.

The results of the analysis showed that the prevalence of metabolic syndrome among adults was 21.5%. Even after adjusting all variables in the multivariate model, smoking, skipping breakfast, and physical inactivity were independent risk factors for metabolic syndrome. It is necessary to promote and strengthen smoking cessation, regular breakfast, and regular physical activity for high-risk groups to prevent metabolic syndrome in Korean adults based on the results of this study. Furthermore, it is also needed to identify metabolic syndrome high-risk groups early based on multiple risk factors and establish a differentiated, personalized health policy that continuously manages them.