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

Study Objective: Sleep disturbances have been associated with individual components of the metabolic syndrome (syndrome X), and, although the concept has been proposed, it is not known whether sleep disturbances actually cluster with features of the metabolic syndrome to produce a unifying trait, syndrome Z. Therefore, we evaluated a second-order factor model, whereby syndrome Z was described by 5 first-order factors - insulin resistance, obesity, hypertension, dyslipidemia, and sleep disturbance - with the sleep disturbance factor defined using the apnea-hypopnea index, arousal index, percentage of sleep time with oxygen saturation less than 90%, and percentage of slow wave sleep. Design: Observational, cross-sectional study. Setting: Clinical research center. Participants: Five hundred thirty-three adults from the Cleveland Family Sleep Study who underwent polysomnography and were not treated by continuous positive airway pressure. Measurements and Results: When modeling syndrome Z as a second-order factor unifying 5 first-order factors, we observed good overall model fit (X-2/df = 3.20; CFl = 0.96; RMSEA = 0.06; SRMR = 0.05) and found that obesity was the most important determining factor (standardized loading = 0.85 standard error = 0.02; P < 0.01) followed by sleep disturbance (0.82 +/- 0.03; P < 0.01), insulin resistance (0.67 +/- 0.03; P < 0.01), hypertension (0.64 +/- 0.04; P < 0.01), and dyslipidemia (0.60 +/- 0.05; P < 0.01). Simultaneous multiple group analyses revealed that this model was essentially generalizable across age, race, and sex subgroups. Conclusions: Our results demonstrate that sleep disturbance co-aggregates with other metabolic features to represent a single unifying trait, syndrome Z. Although our model awaits validation in other populations, it provides a tool for better understanding the synergistic risk of syndrome Z, compared with syndrome X, on type 2 diabetes and cardiovascular disease in future studies.