Empirical Evidence for Syndrome Z : A Hierarchical 5-Factor Model of the Metabolic Syndrome Incorporating Sleep Disturbance Measures

THE METABOLIC SYNDROME IS A CO-OCCURRENCE OR CLUSTERING OF METABOLIC DISTURBANCES THAT RESULTS IN A HIGHER RISK OF TYPE 2 DIABETES and cardiovascular disease1 and may contribute to the pathogenesis of other complex diseases, including colon and other cancers.2 The metabolic syndrome is becoming increasingly more prevalent worldwide3–5 with approximately 25% to 40% of adult Americans (at least 47 million people) reported to have the syndrome.6,7 Although the metabolic syndrome has been shown to increase with age, recent studies have also indicated a rise in the prevalence among younger subjects, particularly women aged 20 to 39 years, a rise that appears to mirror the increasing rates of obesity among women compared to men in the United States.1 In terms of ethnicity, Mexican Americans appear to have the highest prevalence of the syndrome (31.9%) followed by Caucasians (23.8%) and African Americans (21.6%).6 The metabolic syndrome has been defined formally by several agencies, including the World Health Organization,8 National Cholesterol Education Program Third Adult Treatment Panel,9,10 American Heart Association/National Heart, Lung and Blood Institute,11,12 and the International Diabetes Federation.13 Although there is some disparity among these definitions, differences predominantly occur in the cutpoint values applied, the number of individual attributes required, the emphasis on central obesity, and consideration of medication use. Nevertheless, all of the definitions encompass some criteria of 4 key elements: insulin resistance/glucose dysregulation, obesity, hypertension, and dyslipidemia. To help understand the underlying complex pathophysiology of the metabolic syndrome, researchers have utilized factor-analysis methods to determine the number of components (or factors) that best represent the syndrome statistically and to assess the strength of the relationships between each measurable attribute and the underlying latent factor, as well as relationships between factors, using factor loadings. Although some inconsistencies have been reported, most studies in adults using 8 to 10 metabolic measures (fasting insulin level, fasting glucose level, postchallenge insulin level, postchallenge glucose level, body mass index [BMI], waist circumference [waist], waist-to-hip ratio [WHR], high density lipoprotein-cholesterol level [HDL], triglyceride levels, systolic blood pressure [SBP], and diastolic blood pressure [DBP]) have shown that 4 factors— insulin resistance, obesity, blood pressure, and lipids—best describe the metabolic syndrome as a unifying, second-order construct.14–16 Recently, sleep disturbances, including obstructive sleep apnea (OSA), sleep deprivation, and sleep fragmentation, have been suggested to be involved in the development of the metabolic syndrome.17 OSA, a chronic illness characterized by repetitive episodes of partial or complete cessation of breathing during sleep, may affect up to 17% of middle-aged adults18 and has been associated with all 4 of the more established components of the metabolic syndrome,17 leading to the suggestion that a “syndrome Z” exists.19 Although the co-aggregation of OSA with the metabolic syndrome has been largely attributed to obesity, the exact mechanisms driving the association between OSA and the metabolic syndrome and its individual features remain to be elucidated. Tasali and Ip20 have suggested that OSA leads to chronic intermittent hypoxia and sleep fragmentation from arousals, which lead to a cascade of pathogenic mechanisms, such as oxidative stress and neurohumoral changes, that, in turn, lead to insulin resistance, hypertension, and dyslipidemia. Furthermore, both experimental and epidemiologic studies have implicated sleep deprivation and sleep fragmentation in the pathogenesis of impaired glucose tolerance21–23 and hypertension.24–26 In particular, suppression of deep or slow wave sleep (SWS), without any change in total sleep time, has recently been demonstrated to result in decreased insulin sensitivity and reduced glucose tolerance.27 Despite these suggested associations for the concept of syndrome Z, there is currently no evidence that sleep disturbance actually clusters with other traditionally recognized features of the metabolic syndrome to produce a unifying trait. Therefore, we used factor analysis to evaluate the fit of a second-order factor model for syndrome Z, whereby the second-order factor, syndrome Z, was defined by 5 first-order factors: insulin resistance, obesity, hypertension, dyslipidemia, and sleep disturbance. We defined the sleep-disturbance factor with 4 measures, the apnea-hypopnea index (AHI), the arousal index (ArI), the percentage of sleep time when oxygen saturation was less than 90%, and the percentage of sleep time in SWS. Because sleep disturbance and metabolic measures may vary by age, sex, and race,1,6,28,29 we also tested for generalizability of the model using simultaneous multiple group factor analysis methods.