The metabolic syndrome (MetS) is conceptualized as a constellation of multiple, closely-related metabolic disorders. It is a major global public health problem in both developed and developing countries . The commonly encompassed features of MetS are insulin resistance, hypertension, abdominal obesity, and dyslipidemia [1–4]. Those seemingly unrelated biological processes have been proved to occur at a frequency higher than by mere chance. In 1988, Reaven proposed an underlying pathophysiological causation and named it as Syndrome X. And the syndrome appears to increase the risk of developing cardiovascular disease and type 2 diabetes mellitus [6–9]. Although, it has been known for at least eighty years , the definition for MetS has been developing with time – World Health Organization (WHO) in 1999 , International Diabetes Federation (IDF) in 2004 , US National Cholesterol Education Program (NCEP) Adult Treatment Panel III (ATP III) in 2001  and a modified edition in 2005 . In China, Chinese Diabetes Society (CDS)  and Joint Committee for Developing Chinese Guidelines on Prevention and Treatment of Dyslipidemia in Adults (JCDCG)  also released their diagnosing criteria specifically for the Chinese population in 2004 and 2007, respectively. In 2009, a joint interim statement by six major institutions was released . In the statement, raised waist circumference (WC), elevated triglycerides (TG), reduced high-density lipoprotein cholesterol (HDL-C), elevated systolic and/or diastolic blood pressure (SBP, DBP), and elevated fasting plasma glucose (FPG) were included in the diagnosis criteria. WC, the indicator for central obesity, is defined as population- or country-specific.
Though the definition has been agreed upon, the mechanism of MetS is still controversial , such as some declaring that insulin resistance might be the major cause [5, 18]. There is debate about the essence of the MetS pertaining to which components are included and what pathologic process is central to its occurrence. The commonly included components are hypertension, obesity, elevated blood glucose, and dyslipidemia. These factors tend to cluster as a risk factor for the morbidity of cardiovascular disease, type 2 diabetes mellitus, and overall mortality [1, 13].
In recent years, factor analysis has been applied to shed some light on finding the “common soil” for the syndrome . Exploratory factor analysis (EFA), a multi-factorial statistical procedure, is used to extract a relatively small set of latent variables from the extensively observed ones. Observed variables are directly measurable, while the latent are the underlying factors. Studies with EFA indicate differences in the number of factors extracted and the variable loadings on each factor. The inconsistence may be due to the nature of EFA and the methods applied in the extraction of variables. The variables shared in common are assumed to be the underlying latent variables .
Confirmatory factor analysis (CFA) is another way to evaluate the factor structures of MetS based on the theoretical foundations set by EFA . It is used to analyze one or more latent causative factors underlying a concept, i.e. MetS in our study, by comparing the distribution and the established factor structure based on the known concept .
With a priori selected factor models from previous research, CFA can be used to compare competing models of MetS using the same dataset to determine which of the two or more hypothesized models fits best .
The aim of this study is to evaluate and compare two competing models of metabolic syndrome using CFA in a Chinese population. There are two single-factor models for candidate: Model 1 is by Pladevall et al. and Martinez-Vizcaino [24, 25], with WC, TG/HDL-C ratio, and mean arterial pressure (MAP) as factors, but HOMA-IR (homeostasis model of assessment for insulin resistance) or fasting insulin in the original models is substituted by fasting plasma glucose referred to the latest diagnosis criteria for MetS ; Model 2 is presented by Li and Ford  with WC, TG, and SBP, while fasting insulin is substituted by FPG.