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Summary

  1. Top of page
  2. Summary
  3. What’s known
  4. What’s new
  5. Introduction
  6. Methods and procedures
  7. Results
  8. Discussion
  9. Author contributions
  10. References

Objectives:  We investigated the association between metabolic syndrome (MS) and health-related quality of life (HRQOL) assessed using generalised and obesity-specific QOL instruments.

Methods:  We recruited 456 outpatients [age: 19–81 years, body mass index (BMI): 16.3–36.7 kg/m2] in the primary care division from 12 general hospitals in Korea. HRQOL was measured using EuroQol comprising the health states descriptive system (EQ-5D) and visual analogue scale (EQ-VAS) as a general instrument. The Korean Obesity-related QOL scale (KOQOL) composed of six domains was used as a disease-specific QOL instrument. MS was defined on the basis of International Diabetes Federation (IDF) criteria with Korean-specific waist circumference cutoffs (men: 90 cm, women: 85 cm).

Results:  Subjects with MS displayed significantly higher impairment of EQ-5D and KOQOL. Binary logistic regression analysis of MS patients with controls for age, gender, smoking, alcohol, exercise, education, income, marital status and medication history disclosed odds ratio (OR) values of 2.13 (1.33–3.41) for impaired total KOQOL, 2.07 (1.31–3.27) for impaired physical health, 1.63 (1.03–2.60) for impaired work-related health, 2.42 (1.45–4.04) for impaired routine life, 2.08 (1.27–3.40) for impaired sexual life and 2.56 (1.59–4.11) for diet distress. Among the EQ-5D dimensions, only pain/discomfort displayed a significantly increased OR of 1.60 (1.01–2.56) in MS group.

Conclusions:  Subjects with MS displayed a significantly impaired HRQOL compared with those without MS. MS and HRQOL were more strongly associated in obesity-specific QOL than in generalised QOL.


What’s known

  1. Top of page
  2. Summary
  3. What’s known
  4. What’s new
  5. Introduction
  6. Methods and procedures
  7. Results
  8. Discussion
  9. Author contributions
  10. References
  • • 
    Metabolic syndrome is a chronic, progressive and multi-complex health problem that can trigger physical, emotional and psychosocial problems.
  • • 
    The impact of MS on health-related quality of life is yet to be clearly established, although obesity, diabetes and hypertension have obvious consequences of health-related quality of life.
  • • 
    Asians generally tend to have a higher risk of metabolic syndrome at a lower body mass index; however, limited data are currently available on the relationship between MS and health-related quality of life among Asians.

What’s new

  1. Top of page
  2. Summary
  3. What’s known
  4. What’s new
  5. Introduction
  6. Methods and procedures
  7. Results
  8. Discussion
  9. Author contributions
  10. References
  • • 
    Our study demonstrated that subjects with metabolic syndrome have significantly more impaired health-related quality of life than those without metabolic syndrome.
  • • 
    Subjects with metabolic syndrome were more likely to have problems with physical health, work-related health, routine life, sexual life, diet distress and pain/discomfort.
  • • 
    These findings strongly suggest that health-related quality of life should be considered in the management of subjects with metabolic syndrome.

Introduction

  1. Top of page
  2. Summary
  3. What’s known
  4. What’s new
  5. Introduction
  6. Methods and procedures
  7. Results
  8. Discussion
  9. Author contributions
  10. References

Metabolic syndrome (MS), a combination of metabolic risk factors, is associated with increased risk for cardiovascular disease (1). MS is a chronic, progressive and multi-complex health problem that can trigger physical, emotional and psychosocial problems.

The impact of MS on health-related quality of life (HRQOL) is yet to be clearly established, although obesity, diabetes and hypertension have obvious consequences of HRQOL (2–5). In postmenopausal Ecuadorian women, components of MS, such as abdominal obesity, hypertension and hyperglycaemia, impair HRQOL (6). Insulin resistance is associated with poor HRQOL in the domains of physical functioning and general health, but not mental functioning in an elderly population from the UK (7). Moreover, MS is associated with functional dependence and low HRQOL in elderly community-dwelling Brazilian people (8). In Italian obese outpatients, MS mainly affects the physical rather than the psychological domain of HRQOL (9).

Various validated tools have been applied to quantify the influence of disease on HRQOL. EuroQol, a general HRQOL instrument, is a brief, standardised, generic measure that provides a profile of patient function and global health state rating (10). The Korean Obesity-related QOL scale (KOQOL) is a self-questionnaire specifically for obesity outlined by the Korea Obesity-QOL Research Group. KOQOL was developed to measure obesity-related QOL after sufficient testing for reliability and validity (11).

The prevalence of MS has increased gradually, with important health implications. Asians generally tend to have a higher risk of metabolic abnormalities at a lower body mass index (BMI) compared with Caucasians (12). The actual prevalence of metabolic syndrome is relatively high in Koreans, despite the low occurrence of obesity (13). However, limited data are currently available on the relationship between MS and HRQOL among Asians. Here, we investigate the association between MS and HRQOL using generalised (EuroQoL) and obesity-specific QOL (KOQOL) scales among Koreans.

Methods and procedures

  1. Top of page
  2. Summary
  3. What’s known
  4. What’s new
  5. Introduction
  6. Methods and procedures
  7. Results
  8. Discussion
  9. Author contributions
  10. References

Subjects

We recruited study participants who visited the Departments of Family Medicine of 12 general hospitals in Korea from March to August 2007 and who agreed to participate in this study after introduction. The written informed consents were obtained from the study participants upon their enrolment. This study protocol and informed consents were approved by the Institutional Review Board of Asan Medical Center. All individuals underwent a medical evaluation by physicians, including assessment of medical history and physical examination. A total of 488 study subjects were enrolled in this study. Pregnant and lactating women and patients with secondary causes of obesity, malignancy, thyroid disorders, severe hepatic or renal diseases were excluded from the study. The final study sample was limited to 456 subjects aged 19–81 years. Demographic data were collected by means of structured, self-reported questionnaires. Data included information on smoking, alcohol, exercise, education, income, marital status, past medical history and medication history.

Clinical measurements

Anthropometric measurements were performed on subjects in light clothing and no shoes. Heights and weights were measured using an automatic height–weight scale to the nearest 0.1 cm and 0.1 kg respectively. Waist circumference (WC) was evaluated at the midpoint between the lower border of the rib cage and iliac crest. Blood pressure was obtained with a standardised sphygmomanometer after a 10 min rest in the sitting position. Following a 12 h fast, blood was obtained in the morning from an antecubital vein into Vacutainer tubes and subsequently analysed at a central, certified laboratory. Fasting glucose was measured using the glucose oxidase method and triglycerides and high density lipoprotein (HDL)-cholesterol levels were assessed with the aid of enzymatic colorimetric procedures using an autoanalyzer (Hitachi-747; Hitachi, Tokyo, Japan).

Definition of metabolic syndrome

According to the International Diabetes Federation (IDF) (1), MS is defined as central obesity plus any two of the following four metabolic risk factors: (i) raised triglyceride level, ≥ 1.7 mmol/l (150 mg/dl); (ii) reduced HDL-cholesterol: < 1.03 mmol/l (40 mg/dl) in men and < 1.29 mmol/l (50 mg/dl) in women or specific treatment for these lipid abnormalities; (iii) raised blood pressure (systolic blood pressure ≥ 130 mmHg or diastolic blood pressure ≥ 85 mmHg) or treatment of previously diagnosed hypertension; (iv) raised fasting plasma glucose ≥ 5.6 mmol/l (100 mg/dl) or previously diagnosed type 2 diabetes. Central obesity was defined as the Korean-specific cutoffs for abdominal obesity, specifically, waist circumference ≥ 90 cm in men and ≥ 85 cm in women (14).

Measurement of quality of life (QOL)

We mainly evaluated HRQOL using EuroQol and the KOQOL questionnaire. EuroQol consists of two parts, the health states descriptive system (EQ-5D) and visual analogue scale (EQ-VAS). EQ-5D records the level of self-reported problems according to five dimensions (mobility, self-care, usual activities, pain/discomfort and anxiety/depression) (10). Each of the dimensions is assessed based on a single question with three response levels [no problem (1), some problems (2) and extreme problems (3)]. The EQ-5D utility grades range from a full health score of 1 (where the respondent has no problems on any dimension) to the lowest score of −0.59 (where the respondent is at the bottom level of each dimension) (10). Next, respondents describe their own health status using VAS anchored at 100 (best imaginable health) and 0 (worst imaginable health) (15). The Korean version of those tools has been adapted culturally and translated (16). The KOQOL instrument comprised 15 items measuring six domains: psychosocial health, physical health, work-related health, routine life, sexual life and diet distress (11). Each item is rated on a 4-point Likert-type scale (always: 4, most: 3, occasionally: 2, never: 1). Higher scores represent more impaired QOL. The total KOQOL score ranges from 4 to 60, achieved by summing the raw scores for each of the 15 items.

Statistical analysis

Descriptive statistics were used to evaluate the distribution of socio-demographic and clinical variables and QOL measurements. EQ-5D, EQ-VAS and KOQOL scores were separately considered. Measurements were compared between subjects with and without MS, using independent t-tests and Chi-square tests. Separate regression analyses were performed with EQ-5D, EQ-VAS and KOQOL as dependent variables after controlling for age, gender, smoking, alcohol, exercise, education, income, marital status and medication history. To determine the impact of MS on QOL and its dimensions, binary logistic regression analyses were performed after subjects were categorised into two groups based on the medians of EQ-5D, EQ-VAS and KOQOL scores or the presence of problems in each EQ-5D dimensions. We estimated the odds ratios (OR) for more impaired QOL using logistic regression models with MS as the independent variable, and age, gender, smoking, alcohol, exercise, education, income, marital status and medication history as covariates. The reference group was set on less impaired QOL. Adjusted ORs are presented together with their 95% confidence intervals (CI). All statistical analyses were conducted using sas 9.1 (SAS Institute Inc., Cary, NC, USA). p-values < 0.05 were considered statistically significant.

Results

  1. Top of page
  2. Summary
  3. What’s known
  4. What’s new
  5. Introduction
  6. Methods and procedures
  7. Results
  8. Discussion
  9. Author contributions
  10. References

The basic characteristics of study participants are summarised in Table 1. The mean age of the subjects was 47.4 ± 11.3 (range, 19–81) years and 39.0% were women. Mean BMI was 25.0 ± 3.2 (range, 16.3–36.7) kg/m2, with 30.5% of subjects displaying MS. Mean EQ-5D, EQ-VAS and KOQOL scores were 0.8728 ± 0.1608, 71.6 ± 15.4 and 25.7 ± 5.9 respectively.

Table 1.   General characteristics of study subjects
Variablesn (%) or Mean ± SDRange
Total456100.0
Women17839.0
Smoking12126.6
Alcohol drinking28362.1
Regular exercise (≥ 2 times/week)22249.0
Education (> 12 years)20946.0
Income (> 3000 dollars/month)32071.1
Married38284.0
Medication for hypertension12527.4
Medication for diabetes5812.8
Medication for hyperlipidaemia5512.1
Metabolic syndrome13930.5
Age (years)47.4 ± 11.319–81
BMI (kg/m2)25.0 ± 3.216.3–36.7
Waist circumference (cm)85.6 ± 9.163.0–109.3
Systolic blood pressure (mmHg)124.3 ± 16.685–240
Diastolic blood pressure (mmHg)77.8 ± 11.550–120
Fasting Glucose (mg/dl)100.4 ± 25.362–276
Triglyceride (mg/dl)157.3 ± 101.927–944
HDL-Cholesterol (mg/dl)48.9 ± 12.122–90
EQ-5D0.8728 ± 0.16080.121–1.000
Dimensions of EQ-5DSome problemsExtreme problems
Mobility47 (10.4)1 (0.2)
Self-care8 (1.8)1 (0.2)
Usual activity33 (7.3)1 (0.2)
Pain/discomfort146 (32.3)5 (1.1)
Anxiety/depression155 (34.1)2 (0.4)
EQ-VAS71.6 ± 15.4(10–100)
  1. EQ-5D, EuroQol comprising five dimensions; EQ-VAS, EuroQol-visual analogue scale; KOQOL, Korean Obesity-related quality of life (QOL) scale; HDL, high density lipoprotein.

KOQOL25.7 ± 5.9 (15–57)
 Psychosocial health 6.3 ± 1.8 (4–16)
 Physical health 5.6 ± 1.6 (3–11)
 Work-related Health 5.6 ± 1.8 (3–12)
 Routine life 3.2 ± 1.3 (2–8)
 Sexual life 3.2 ± 1.2 (1–8)
 Diet distress 1.7 ± 0.8 (1–4)

Table 2 presents the EQ-5D, EQ-VAS and KOQOL scores depending on MS. The MS patients displayed considerably impaired EQ-5D and pain/discomfort dimensions. Subjects with MS showed significantly impaired KOQOL, physical health, routine life, sexual life and diet distress domains in relation to those without MS.

Table 2.   Health-related quality of life (HRQOL) scores evaluated according to the presence of metabolic syndrome (MS)
 Without MSWith MS
 n%n%P
  1. EQ-5D, EuroQol comprising five dimensions; EQ-VAS, EuroQol-visual analogue scale; KOQOL, Korean Obesity-related quality of life (QOL) scale; MR, metabolic syndrome. Independent t-test and Chi-square test.

Dimension of EQ-5D (Patients with any problem)
 Mobility278.52115.20.050
 Self-care51.642.90.464
 Usual activity196.01510.80.111
 Pain/discomfort9329.65842.00.014
 Anxiety/depression10633.55137.00.551
  Mean ± SD Mean ± SD 
EQ-5D3140.8826 ± 0.16011360.8501 ± 0.16070.049
EQ-VAS30072.6 ± 15.113569.6 ± 15.90.062
KOQOL30525.2 ± 5.413526.8 ± 6.70.013
 Psychosocial health3056.5 ± 1.81355.9 ± 1.80.006
 Physical health3055.4 ± 1.51356.0 ± 1.80.001
 Work-related health3055.5 ± 1.71355.8 ± 1.90.176
 Routine life3053.0 ± 1.11353.8 ± 1.6< 0.001
 Sexual life3053.1 ± 1.11353.4 ± 1.30.048
 Diet distress3051.6 ± 0.71351.9 ± 0.9< 0.001

Table 3 shows the multiple linear regression analyses to evaluate the associations between MS and EQ-5D, EQ-VAS and KOQOL and its domains. MS is significantly associated with more impaired KOQOL, particularly physical health, work-related health, routine life, sexual life and diet distress domains, after controlling for other factors.

Table 3.   Multiple linear regression analyses undertaken to explain variations of metabolic syndrome in EQ-5D, EQ-VAS and KOQOL and its domains
 Parameter estimatesSEp
  1. EQ-5D, EuroQol comprising five dimensions; EQ-VAS, EuroQol-visual analogue scale; KOQOL, Korean Obesity-related quality of life (QOL) scale. Multiple linear regression analyses were performed after controlling for the effects of age, gender, smoking, alcohol, exercise, education, income, marital status and medication history.

EQ-5D−0.0170.0170.310
 Mobility0.0230.0330.486
 Self-care0.0010.0180.940
 Usual activity0.0550.0290.059
 Pain/discomfort0.0810.0540.136
 Anxiety/depression0.0370.0520.483
EQ-VAS−2.8111.6310.086
KOQOL2.2090.622< 0.001
 Psychosocial Health−0.2660.1960.176
 Physical health0.6510.173< 0.001
 Work-related health0.4450.1920.021
 Routine life0.7830.136< 0.001
 Sexual life0.2690.1240.030
 Diet distress0.3280.086< 0.001

Binary logistic regression analyses of HRQOL with control for other factors, dependent on the presence of MS, are described in Table 4. MS patients displayed ORs of 2.13 (1.33–3.41) for impaired total KOQOL, 2.07 (1.31–3.27) for impaired physical health, 1.63 (1.03–2.60) for impaired work-related health, 2.42 (1.45–4.04) for impaired routine life, 2.08 (1.27–3.40) for impaired sexual life and 2.56 (1.59–4.11) for diet distress. Among the EQ-5D dimensions, only pain/discomfort was associated with a significantly increased OR of 1.60 (1.01–2.56) in MS group.

Table 4.   Adjusted odds ratio (OR) and 95% confidence interval (CI) for impaired QOL as dependent variables and metabolic syndrome as an independent variable
 Cutoff score for impaired QOLAdjusted OR 95% CI
  1. EQ-5D, EuroQol comprising five dimensions; EQ-VAS, EuroQol-visual analogue scale; KOQOL, Korean Obesity-related quality of life (QOL) scale; odds ratios (ORs) were adjusted for age, gender, smoking, alcohol, exercise, education, income, marital status and medication history.

EQ-5D< 0.9421.470.92–2.34
Mobilitysome/extreme1.350.64–2.82
Self-caresome/extreme1.350.30–6.14
Usual activitysome/extreme1.890.82–4.34
Pain/discomfortsome/extreme1.601.01–2.56
Anxiety/depressionsome/extreme1.200.74–1.93
EQ-VAS< 751.540.97–2.46
KOQOL≥ 252.131.33–3.41
Psychosocial health≥ 70.680.43–1.10
Physical health≥ 62.071.31–3.27
Work-related health≥ 61.631.03–2.60
Routine life≥ 32.421.45–4.04
Sexual life≥ 32.081.27–3.40
Diet distress≥ 22.561.59–4.11

Discussion

  1. Top of page
  2. Summary
  3. What’s known
  4. What’s new
  5. Introduction
  6. Methods and procedures
  7. Results
  8. Discussion
  9. Author contributions
  10. References

Our KOQOL and EQ-5D scores demonstrate that subjects with MS have significantly more impaired HRQOL than those without MS. Subjects with MS were more likely to have problems with physical health, work-related health, routine life, sexual life and diet distress according to KOQOL and pain/discomfort as indicated by the EQ-5D. Our results are consistent with the previous findings (6–9). Insulin resistance was associated with poor HRQOL in the domains of physical functioning and general health but not in mental functioning (7). In a recent study, waist–hip ratio, fasting insulin, triglycerides and HDL-cholesterol were associated with a subsequent decline in physical functioning in both men and women (17). Additionally, metabolic abnormalities related to insulin resistance are associated with reduced muscle strength and impaired HRQOL in the domain of physical functioning (18).

Obesity is associated with a profound decrease in HRQOL and the most significant impairment tends to be associated with physical domains of functioning (19–21). The mean BMI of subjects in this study was overweight (25.0 kg/m2) and we used the IDF definition for MS, which includes abdominal obesity as an essential component. In this regard, impairment of physical health was observed on the obesity-specific QOL scale, particularly in MS subjects. Increasing BMI mainly affected the domains of physical activity and bodily pain (19,22,23) and obesity had a significant negative impact on physical well-being (20). This particular clustering of physical abilities with increasing BMI and poor HRQOL in the physical domain may have important implications in obesity (24). Consistent with those findings, pain/discomfort was significantly associated with MS in our study.

We found no significant association between MS and psychosocial health. This finding is consistent with the lack of association of insulin resistance or MS with emotional problems in QOL measurements (7,9,17). A recent study reported that obese subjects showed a weakest association with emotional health and a strong association with physical components (21). One of the reasons for the lack of significance in the association between MS and psychosocial health is that middle-aged participants in our study possibly recognise abdominal obesity as a health problem, rather than concern for body shape. In addition, MS is a constellation of generally mild conditions and not serious problems. Consequently, the psychosocial burden may be slight.

HRQOL is assessed using generic or disease-specific measurements. Generic measures assess multiple domains of functioning and may be applied to any health problems. We applied EuroQol on the basis of evidence that valuations for a standard set of EuroQol health states are broadly similar between countries, suggestive of cross-national and cross-cultural applicability (25). In contrast to generic measures, disease-specific instruments are designed to identify HRQOL associated with specific health problems. Disease-specific measurements tend to be more sensitive than generic measurements (5).

We evaluated the correlation between KOQOL and EuroQol instruments before applying these tools in our study to analyse the degree of consistency between the questionnaires. The QOL scores evaluated using both instruments displayed significant correlations with each other (data not shown). However, the relationship between MS and HRQOL was more significant in KOQOL than EuroQol analyses. Our results suggest that KOQOL is a sensitive and valid instrument for measuring health status and physical functioning in Korean MS subjects. We employed median values of each QOL score as cutoffs for impaired QOL on the basis of previous analyses (6).

Several expert groups have proposed different diagnostic criteria to define MS (26–28). The prevalence of MS in study subjects based on IDF criteria was 30.5%, which was much higher than that of the general Korean population (16.2%). However, when we applied the modified National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III) using the same criteria for central obesity as 90 cm for men and 85 cm for women, the prevalence of MS in this study subjects was 41.9%. The prevalence of MS using NCEP ATP III criteria depends on the cutoff value of waist circumference for central obesity. In the general Korean population, the prevalence of MS using NCEP ATP III (27) or modified NCEP ATP III criteria (28) was 17.6% (29) or 30.9% (30), respectively. In the US adult population, the prevalence of MS using NCEP ATP III or IDF definition was 34.5% or 39.0% respectively (31). Similar results were discovered in the European population. The use of the IDF criteria of MS has provided a higher prevalence estimate of MS than the estimate based on the NCEP criteria in the European population (32,33).

Previous studies evaluated the association between MS and HRQOL using the NCEP ATP III (6,8,9). The results obtained by applying NCEP ATP III criteria in our study were similar to the findings using IDF criteria. However, the recent consensus strongly recommends ethnic-specific cutoffs even for the definition of obesity (1). It is reasonable to observe an association between MS defined by IDF criteria using ethnic-specific cutoffs for WC for Korean (14) and HRQOL using the Korean Obesity-specific QOL scale.

Our study has several limitations. First, the data are cross-sectional and therefore we were unable to draw conclusions on the causal relationship between MS and HRQOL. Second, results were obtained in the outpatient population seeking medical treatment and their external validity in the general population and different settings requires determination. Third, we used the obesity-specific QOL instrument, as an MS-specific QOL instrument has not been developed yet. However, analyses using the obesity-related QOL instrument considering a central role for abdominal obesity in MS may not be a serious problem. Finally, we could not completely adjust each treatment regimen precisely, even after including any medication as a covariable.

To our knowledge, the association between MS and HRQOL has never been addressed among Asian populations. We conclude that Korean subjects with MS have significantly impaired HRQOL even after controlling for confounding variables. Our MS subjects presented lower QOL in terms of physical health, work-related health, routine life, sexual life and diet distress with KOQOL and pain/discomfort with EQ-5D. These findings strongly suggest that HRQOL should be considered in the management of subjects with MS.

Author contributions

  1. Top of page
  2. Summary
  3. What’s known
  4. What’s new
  5. Introduction
  6. Methods and procedures
  7. Results
  8. Discussion
  9. Author contributions
  10. References

J.H. Han, H.S. Park, K.E. Yun, S.H. Cho, E.Y. Choi, S.Y. Lee, J.H. Kim and H.N. Sung were involved in the post hoc design, data analysis, interpretation of results and preparation of article. J.H. Kim, S.I. Choi, Y.S. Yoon, E.S. Lee, H.R. Song, C.I. Shin, H.M. Chang and S.C. Bae were involved in the statistical analyses and the review of the article.

References

  1. Top of page
  2. Summary
  3. What’s known
  4. What’s new
  5. Introduction
  6. Methods and procedures
  7. Results
  8. Discussion
  9. Author contributions
  10. References