Surprisingly, metabolic syndrome was not associated with impaired quality of life, despite a robust analysis that included two generic measures and an obesity-specific instrument (four outcomes in total). Participants in both groups reported slightly lower than average health status on the PCS-12 and relatively average health status on the MCS-12. [A summary score of 50 on both the physical and mental components of the SF-12 is indicative of average HRQoL (29
)]. In contrast, both groups reported relatively high quality of life on the second generic measure, the EQ-5D. Although specific cutoffs for quality of life have not been reported for the IWQoL-Lite (42
), the scores for participants with and without metabolic syndrome were intermediate between those reported in similar populations of obese individuals (range of 54.6 to 77.6) (35
). Mean IWQoL-Lite scores of 91.8 were reported in the nonobese general population (42
Secondary analyses showed no evidence of an interaction between metabolic syndrome and obesity class or between metabolic syndrome and diabetes. This is notable given that participants with metabolic syndrome were more likely to be female, older, of lower socioeconomic status, and to have a higher BMI and greater medication use, compared to those without metabolic syndrome. Participants with metabolic syndrome were also more likely to have hypertension and hyperlipidemia, although LDL-cholesterol levels were lower in this group. (The latter finding is likely explained by the fact that more participants in the metabolic syndrome group were taking lipid-lowering medications, compared to those without the condition.) Finally, the number of criteria for metabolic syndrome did not influence the null relationship between metabolic syndrome and HRQoL. Because all study participants had to have at least two criteria for metabolic syndrome to be eligible for enrollment, individuals with and without metabolic syndrome had similar baseline characteristics from a clinical perspective. Thus, it was more difficult to detect small differences between groups, and the association between metabolic syndrome and HRQoL was likely attenuated.
Consistent with previous studies, we found that BMI was associated with lower scores on the PCS-12 and IWQoL-Lite, but not on the mental health measures (13
). As the impact of obesity on physical functioning is well established (11
), the lack of association between HRQoL and metabolic syndrome in more obese subgroups was unexpected. A threshold BMI may exist for which obesity modifies the relationship between metabolic syndrome and HRQoL. Study participants were required to have a BMI between 30 kg/m2
and 50 kg/m2
. Significant differences in quality of life may have been detected if individuals with extreme obesity (BMI ≥ 50 kg/m2
) and metabolic syndrome had been included.
Mean scores on the PCS-12, MCS-12, and the IWQoL-Lite, for participants with and without metabolic syndrome, were remarkably similar to scores reported in previous studies that evaluated the impact of obesity on quality of life using the same instruments (22
). IWQoL-Lite scores in the present study were also very similar to those reported in a study that used this measure to compare weight-related quality of life in 1197 obese participants with and without diabetes (35
Findings from this study raise questions about a conceptual model relating obesity, the number of comorbid conditions, depression, and quality of life. Depression was associated with decreased quality of life across measures, while obesity and number of comorbidities were not. One possible explanation is that impaired quality of life is an intermediary which relates these conditions. In one study, for example, increasing BMI was associated with greater reports of physical pain (a component of QOL) which, in turn, were associated with greater symptoms of depression (46
). BMI alone was not associated with increased depression scores. Impaired quality of life may also act as a link between comorbidity and depression (47
). This framework would explain why we found depression to be associated with quality of life on all four measures, while the associations between comorbid conditions, obesity, and HRQoL were more inconsistent. However, the causality and time course of these relationships remain largely unknown. Therefore, prospective longitudinal studies, which include estimates of these factors and quality of life, are needed to elucidate their interrelations.
The present investigation had several strengths. We performed a robust analysis that included important factors that may affect quality of life, including depression and estimates of disease burden. Previous studies have failed to adjust for many of these confounding variables (16
). Ford and colleagues reported that metabolic syndrome was significantly associated with reduced quality of life in a population of 1,859 U.S. adults. However, only age, sex, ethnicity, educational status and smoking status were considered as covariates in their regression model (16
). Similarly, Miettola and colleagues examined the relationship between metabolic syndrome and HRQoL in a Finnish population, but only adjusted for age, gender, marital status, education, employment status, smoking, and physical activity (17
). The FCI in the present study indicated that participants had few comorbidities and were in relatively good health. Thus a volunteerism effect may have influenced our findings, in which individuals who elected to participate in the POWER Trial may have had better HRQoL than those who did not volunteer.
An additional strength of the present study was the use of several measures of HRQoL. Although the SF-36 (and the SF-12) and the EQ-5D have been widely used in weight loss studies, few studies have also included a disease-specific measure (50
). Obesity-specific instruments may complement generic measures in capturing more subtle differences in health among participants with milder obesity and reductions in aspects of mental or physical health unique to obesity (20
). Although metabolic syndrome was not associated with decreased quality of life on the IWQoL-Lite, this measure did detect differences in HRQoL that were not observed using the generic instruments.
This study also had several limitations. The particular version of the SF-12 that was used in this study only allowed the calculation of the summary scales but did not allow calculation of the individual subscales. Thus, differences between groups may have been present in the subscales that we were not able to detect. As previously noted, there were few clinically significant differences between participants with and without metabolic syndrome, making it difficult to detect small differences between groups.
In summary, metabolic syndrome was not associated with impaired HRQoL using two generic measures and an obesity-specific instrument. Diabetes and increasing obesity did not modify this relationship. These findings suggest that metabolic syndrome in itself is not associated with a decreased quality of life, but other factors such as obesity, depression, and greater disease burden may have significant effects on quality of life in this population. Larger studies that utilize multiple measures of quality of life and include the important covariates described previously are needed to confirm these findings.