Abstract
BACKGROUND
This study provides the first reported estimates of the prevalence of the metabolic syndrome in a normal-weight Iranian population.
SUBJECTS AND METHODS
In this population-based cross-sectional study, the study population consisted of a representative sample of 1737 males and 1707 females aged ≥20 years with normal body mass index (BMI) (18.5–24.9 kg/m2 for both genders). The metabolic syndrome was defined according to the Adult Treatment Panel III guidelines. We present means and proportions, and multivariate odds ratios that quantify the association between metabolic syndrome and normal BMI quartiles, controlling for age, physical activity, smoking and education.
RESULTS
The overall prevalence of the metabolic syndrome in normal-weight men and women were 9.9% and 11.0% (P=0.2) respectively. Men had a lower BMI than women, while their waist circumference (WC) was higher. The prevalence of high WC and low high-density lipoprotein cholesterol (HDL-C) was higher in women, while high blood pressure, high triglyceride levels and having at least one metabolic risk factor were more prevalent in men. Individuals in the highest category of normal BMI had significantly higher odds for being at risk for metabolic syndrome compared to those in the first category (OR: 5.21 for men and 2.15 for women). There was an increasing trend in odds for having all the metabolic syndrome components except for high fasting blood sugar (FBS) and high WC in men. Women showed a similar increasing trend except for high FBS across normal BMI quartiles.
CONCLUSION
The prevalence of the metabolic syndrome in normal-weight Iranian adults is relatively high. Therefore, interventions for prevention of cardiovascular disease could be considered in this population.
The concept of the metabolically obese, normal-weight (MNOW) individual was originally developed over 20 years ago; however, a formal definition has not been developed.1,2 When it was originally introduced, MNOW was defined as an individual with a normal BMI who had three or more of the following risk factors: high waist circumference (WC), a high triglyceride level, a low HDL cholesterol (HDL-C) level, high blood pressure, and high fasting plasma glucose concentration.1 The Third Report of the National Cholesterol Education Program Expert Panel (Adult Treatment Panel III or ATP III) not only draws attention to the importance of the metabolic syndrome, but also provides the first practical definition of this syndrome.3
It has been reported that 30.1% of the Iranian population have metabolic syndrome, but there are no reports on the prevalence of this syndrome among individuals within the various BMI categories.4 The present study estimates the prevalence of metabolic syndrome in the adult population with normal BMI. According to WHO recommendations, the BMI threshold for increasing disease risk among the Caucasian population is 25 kg/m2 for men and women.5 Therefore, ethnic differences in body composition and susceptibility to cardiovascular disease should be taken into account when considering metabolic syndrome and its risk factors in normal-weight adults.6 In our previous investigation in Iran, we showed that lower cut points of BMI are appropriate for Iranians to detect obesity-related risk factors.7
In the present study, we hypothesized that the risk of metabolic syndrome is high in Iranian adults within the normal limits of BMI, as defined for universal application by the WHO. So we investigated normal-weight participants of the Tehran Lipid and Glucose Study to examine the prevalence of the metabolic syndrome and each of its components.
SUBJECTS AND METHODS
This study was conducted within the framework of the Tehran Lipid and Glucose Study (TLGS), a prospective study performed on representative sample of residents of district 13 of Tehran with the aim of determining the prevalence of non-communicable disease risk factors and developing a healthy lifestyle to improve these risk factors. In the TLGS, 15 005 people aged 3 years and older, living in district 13 of Tehran, were selected by multistage cluster random sampling method. There were 10 368 people aged 20 years or older. In the present population-based cross-sectional study, after excluding pregnant women and subjects taking medications that would affect their serum lipoproteins, blood pressure and carbohydrate metabolism, 3444 subjects (1737 men and 1707 women) with a normal body mass index and full relevant data were included.
Details of the TLGS protocol and all laboratory procedures are published elsewhere.8 Subjects were interviewed privately, face-to-face. Interviews were conducted by trained interviewers using pretested questionnaires. Initially, information on age, smoking habits, physical activity, education level, family history of diabetes and medication use was collected. Individuals who had sports or hard physical activity regularly at least once a week were considered as the positive physical activity group and those who did not as the negative group. Current or past smokers were considered as in the positive smoking group and those who did not smoke in the present and past were called nonsmokers. Education level was categorized to three levels of <8 years, 8–12 years and >12 years. Weight was then measured, while subjects were minimally clothed without shoes using digital scales and recorded to the nearest 100 g. Height was measured in a standing position, without shoes, using a tape meter, while the shoulders were in a normal position. BMI was calculated as weight in kilograms divided by height in meters squared. WC was measured at the narrowest level and that of the hip at the maximal level over light clothing, using an unstretched tape meter, without any pressure on the body surface, and was recorded to the nearest 0.1 cm. To reduce subjective error all measurements were taken by the same male technician for all males and the same female technician for all females. To measure blood pressure, subjects were first made to rest for 15 minutes. Then, a qualified physician measured blood pressure twice during physical examinations in a seated position after one initial measurement for determining the peak inflation level using a standard mercury sphygmomanometer.
A blood sample was taken after a 12 to 14 hour overnight fasting. Blood samples were taken in a sitting position according to the standard protocol and centrifuged within 30 to 45 minutes of collection. All blood analyses were done at the TLGS research laboratory on the day of blood collection. The analysis of samples was performed using a Selectra 2 auto-analyzer (Vital Scientific, Spankeren, Netherlands). Fasting blood sugar (FBS) was measured on the day of blood collection by an enzymatic colorimetric method using glucose oxidase. For lipid measurements, total cholesterol and triglyceride kits (Pars Azmoon Inc., Iran) were used. TC and TG were assayed using enzymatic colorimetric tests with cholesterol esterase and cholesterol oxidase, and glycerol phosphate oxidase, respectively. HDL-C was measured after precipitation of the apolipoprotein B containing lipoproteins with phosphotungstic acid. Lipid standard (C.f.a.s., Boehringer Mannheim, Germany; cat. no. 759350) was used to calibrate the Selectra 2 auto-analyzer for each day of laboratory analyses. All samples were analyzed when internal quality control met the acceptable criteria. Inter- and intra-assay coefficients of variation were 2% and 0.5% for TC and 1.6% and 0.6% for TG, respectively.
Normal-weight BMI was defined a range of 18.5–24.9 kg/m2 according to NIH criteria.9 The metabolic syndrome was defined according to the ATP III guidelines as the presence of three or more of the following:3 (1) abdominal obesity (WC ≥ 102 cm in men and ≥88 cm in women); (2) a high triglyceride level (≥150mg/dL); (3) a low HDL cholesterol level (<40mg/dL for men and <50mg/dL for women); (4) high blood pressure (systolic ≥130 mm Hg or diastolic ≥85 mm Hg); and (5) a high fasting plasma glucose concentration (≥110 mg/dL).
All means are presented as mean ± SD. Significant differences in general characteristics were examined using the chi-square and Student t tests. The prevalence of the metabolic syndrome and its individual components were compared according to sex category using the chi-square test. BMI ranging from 18.5–24.9 kg/m2 was stratified into four equal categories. Logistic regression analysis was used to examine the association between normal BMI quartiles and the metabolic syndrome with each metabolic component having at least one component and at least two components in the multivariate model. The odds ratios were adjusted for age, physical activity, smoking status and education level. The first category of BMI was considered as a reference in our logistic analyses. BMI quartiles were considered as independent variables with each of the metabolic variables as the dependent variable. All statistical analyses were performed separately by gender. Statistical Package for Social Science (SPSS Inc., Chicago IL. Version 9.05) was used for all statistical analyses.
RESULTS
Mean (±SD) age of men and women were 41.8(±16.4) and 35.9(±14.3) years, respectively (P<0.001) (Table 1). Men had a slightly lower BMI but a higher WC than women (P<0.001). A higher FBS, triglyceride levels, systolic and diastolic blood pressure and lower HDL-C was found in men compared to women. There was no difference between men and women in physical activity status, while the prevalence of smoking status and the education level less than 8 years and higher than 12 years were more common in men.
Table 1.
General characteristics of the study participants by gender.
| Men (n=1737) | Women (n=1707) | P value (men vs. women) | |
|---|---|---|---|
| Age (y) | 41.8±16.4 | 35.9±14.3 | <0.001 |
| Waist (cm) | 79.8±6.6 | 76.3±7.7 | <0.001 |
| Body mass index (kg/m2) | 22.4±1.8 | 22.5±1.7 | <0.001 |
| Fasting blood sugar (mg/dl) | 94.8±28.3 | 92.4±31.7 | <0.001 |
| Triglyceride (mg/dl) | 146.1 ±98.0 | 118.7±77.3 | <0.001 |
| Systolic blood pressure (mm Hg) | 116.6±17.0 | 111.8±16.8 | <0.001 |
| Diastolic (mm Hg) | 74.5±10.7 | 73.3±9.4 | 0.001 |
| HDL-cholesterol (mg/dL) | 40.0±9.8 | 47.1 ±11.2 | <0.001 |
| Physical activity* | |||
| Yes | 647(37.6)† | 685(40.4) | 0.053 |
| No | 1073(62.4) | 1012(59.6) | |
| Smoking‡ | |||
| Yes | 512(29.7) | 53(3.1) | <0.001 |
| No | 1210(70.3) | 1645(96.9) | |
| Education level | |||
| <8 years | 367(22.2) | 305(19.6) | 0.001 |
| 8–12 years | 981(59.3) | 1020(65.4) | |
| >12 years | 306(18.5) | 235(15.1) |
Data are mean±SD
Sports activity or hard work regularly at least once a week
Numbers in parenthesis represents percent
Yes= Smoking in the past or now; No= No smoking in the past or now
The overall prevalence of the metabolic syndrome in 1737 men and 1707 women with normal weight was 9.9% (CI 95%: 8.47–11.33) and 11.0% (CI 95%: 9.49–12.50), P=0.2, respectively (Table 2). The prevalence of high blood pressure, high triglyceride levels and at least two metabolic risk factors was more in men compared to women, while the prevalence of high WC and low HDL-C was higher in women.
Table 2.
Prevalence of metabolic syndrome and its risk factors by gender.
| Men | Women | P value (men vs women) | |
|---|---|---|---|
| High waist circumference | - | 7.2 (6.0–8.4) | <0.0001 |
| Low HDL-cholesterol | 56.3 (54.0–59.2) | 66.4 (65.7–97.1) | <0.0001 |
| High blood pressure | 24.8 (22.7–26.8) | 16.4(14.6–18.2) | <0.0001 |
| High triglycerides | 35.7 (33.4–38.0) | 22.0(20.0–24.0) | <0.0001 |
| High fasting blood sugar | 7.8 (6.5–9.1) | 6.6 (5.4–7.8) | 0.1 |
| At least one risk factor‡ | 75.4 (73.3–77.5) | 75.7 (73.6–77.8) | 0.8 |
| At least two risk factors‡ | 37.8 (35.5–40.1) | 28.8 (26.6–31.0) | <0.0001 |
| Metabolic Syndrome | 9.9 (8.5–11.3) | 11.0 (9.5–12.5) | 0.2 |
Numbers represent percentage of individuals who have the risk factor (s) and those in parentheses indicate 95% CI
High WC: WC ≥ 102 cm for men and WC ≥ 88 cm for women; low HDL: HDL <40 mg/dL for men and HDL <50 mg/dL for women; high blood pressure: systolic blood pressure ≥130 mm Hg and/or diastolic blood pressure ≥85 mm Hg; high triglycerides: Triglycerides level ≥150mg/dL; high FBS: FBS ≥ 110 mg/dL No men had high WC.
Multivariate-adjusted odds ratios for metabolic syndrome risk factors across normal-weight BMI quartiles in men are shown in Table 3. An increasing trend was observed for the odds of having high triglycerides (TG), high blood pressure, low HDL-C, at least one and two risk factors across BMI quartiles. Men in the third and fourth quartiles of BMI had significantly higher odds of having low HDL-C compared to the first quartile. The odds of high FBS for BMI quartiles were not statistically significant compared to the first quartile.
Table 3.
Multivariate adjusted odds ratios (95% confidence intervals) for metabolic risk factors according to quartiles of BMI in men.
| Men | BMI (kg/m2) | P for trend | |||
|---|---|---|---|---|---|
| 18.5–21.1* | 21.2–22.7 | 22.8–23.9 | 24.0–24.9 | ||
| Low HDL-cholesterol | 1.0 | 1.05 (0.79–1.40) | 1.59 (1.19–2.12)† | 1.79 (1.34–2.39)† | <0.001 |
| High blood pressure | 1.0 | 1.88 (1.27–2.78)† | 1.61 (1.08–2.40)† | 2.59 (1.77–3.79)‡ | <0.001 |
| High triglycerides | 1.0 | 2.22 (1.59–3.10)‡ | 2.96 (2.12–4.12)‡ | 4.66 (3.35–6.47)‡ | <0.001 |
| High fasting blood sugar | 1.0 | 1.57 (0.85–2.88) | 1.04 (0.55–1.98) | 1.80 (0.99–3.27) | 0.1 |
| At least one risk factor‡ | 1.0 | 1.68 (1.23–2.29)† | 2.09 (1.51–2.89)‡ | 3.37 (2.36–4.81)‡ | <0.001 |
| At least two risk factors‡ | 1.0 | 1.75 (1.26–2.43)† | 2.39 (1.73–3.30)‡ | 3.47 (2.52–4.77)‡ | <0.001 |
Odds ratios were adjusted for age, physical activity, smoking and education level.
High WC: WC ≥102 cm for men and WC ≥88 for women; low HDL: HDL <40 mg/dL for men and HDL <50 mg/dl for women; high blood pressure: systolic blood pressure ≥130 mm Hg and/or diastolic blood pressure ≥85 mm Hg; high TG: triglycerides level ≥150 mg/dL; high FBS: FBS ≥110 mg/dL
Reference group
P<0.05 compared to first quartile
P<0.0001 compared to first quartile
A similar analysis in women showed an increasing trend for the odds of having high WC, low HDL-C, high blood pressure, high TG, at least one and two risk factors across BMI quartiles (Table 4). Women in the third and fourth quartiles of BMI had a significantly higher odds of having high WC, high blood pressure, high TG and at least two risk factors compared to the first quartile. Also, those in the second and third quartile of BMI had significantly higher odds of having low HDL-C compared to the first. The odds of high FBS for BMI quartiles was not statistically significant compared to the first quartile.
Table 4.
Odds ratios (95% confidence intervals) for metabolic risk factors according to quartiles of BMI in women.
| Women | BMI (kg/m2) | P for trend | |||
|---|---|---|---|---|---|
| 18.5–21.2* | 21.3–22.8 | 22.9–24.0 | 24.1–24.99 | ||
| High waist circumference | 1.0 | 1.38 (0.48–3.96) | 2.94 (1.15–7.52)† | 7.49 (3.14–17.85)‡ | <0.001 |
| Low HDL-cholesterol | 1.0 | 1.37 (1.01–1.85)† | 1.42 (1.04–1.93)† | 1.02 (0.76–1.37) | 0.03 |
| High blood pressure | 1.0 | 1.57 (0.88–2.79) | 2.25 (1.31–3.88)† | 1.89 (1.10–3.23)† | 0.02 |
| High triglycerides | 1.0 | 1.41 (0.90–2.22) | 2.22 (1.45–3.41)‡ | 2.59 (1.71–3.93)‡ | <0.001 |
| High fasting blood sugar | 1.0 | 0.95 (0.40–2.22) | 1.14 (0.51–2.54) | 1.01 (0.46–2.19) | 0.9 |
| At least one risk factor§ | 1.0 | 1.45 (1.05–2.00)† | 1.60 (1.14–2.25)† | 1.16 (0.84–1.61) | 0.02 |
| At least two risk factors§ | 1.0 | 1.51 (0.98–2.30) | 2.07 (1.37–3.11)‡ | 2.88 (1.94–4.28)‡ | <0.001 |
Odds ratios were adjusted for age, physical activity, smoking and education level.
High WC: WC ≥102 cm for men and WC ≥ 88 cm for women; low HDL: HDL <40 mg/dl for men and HDL <50 mg/dL for women; High blood pressure: systolic blood pressure ≥130 mm Hg and/or diastolic blood pressure ≥85 mm Hg; high TG: triglycerides level ≥150 mg/dL; high FBS: FBS ≥110 mg/dL
Reference group
P<0.05 compared to first quartile
P<0.0001 compared to first quartile
Risk factors include having high WC, Low HDL, High BP, high TG and high FBS
Multivariate-adjusted odds ratios for metabolic syndrome across quartiles of normal-weight BMI in both genders are shown in Figure 1. The likelihood of the metabolic syndrome increased significantly (P<0.01) with increasing BMI category in both sexes, except in the women in second BMI quartile compared to the first (P=0.4). An increasing trend in odds for metabolic syndrome across BMI quartiles was found in both sexes (data not shown). Women in the third and fourth quartile of BMI showed a significantly higher odds of having metabolic syndrome compared to the first.
Figure 1.
Multivariate adjusted odds ratios and 95% confidence intervals (CI) for the metabolic syndrome according to body mass index (BMI). Odds ratios are adjusted for age, physical activity, smoking and education level. The first quartile was used as the referent group (OR 1.00), and the error bars for the remaining groups represent the 95% CI.
DISCUSSION
This study provides the first reported estimates of the prevalence of the metabolic syndrome in a normal-weight Iranian population. We showed that the overall prevalence of metabolic syndrome in 3444 normal-weight individuals was 10.5%, which is higher than the prevalence reported in some countries regardless of their BMI level and also than in normal-weight participants in the Park study (4.6% in men, 6.2% in women).10,11
Although it has been established that a high BMI value increases the risk of hypertension and dyslipidemia, these pathological states are also observed among those with a normal BMI.12–15 Participants with a BMI less than 25 kg/m2 meeting the metabolic syndrome criteria may be the “metabolically obese, normal-weight” individuals referred by Ruderman et al1,16 who potentially have insulin resistance as the central feature of their metabolic abnormalities. In the present study, men and women in the upper end of the normal BMI range were more likely to have the metabolic syndrome compared with those at the lower category of normal-weight BMI. We also found that 75% of our population had at least one risk factor for metabolic syndrome, which was the same as Singaporean and Asian Indian populations.17,18 Because of the high prevalence of metabolic syndrome in normal-weight Iranian adults, we suggest the use of weight loss programs in subjects with a BMI <25 kg/m2. Current weight-loss recommendations do not advise patients with BMI<25 kg/m2 to lose weight.19,20
In the present study, the highest prevalence of metabolic risk factors in normal-weight individuals was shown for low HDL-C, which is the same as in previous reports in normal-weight Asian Indians16 and in an Iranian population of all BMI categories.4 Also, in a cross-sectional study on normal-weight Caucasian adults, low HDL-C showed the highest prevalence of metabolic risks in both sexes.6 The high prevalence of hypertriglyceridemia in non-obese men of the present study (35.7%) was comparable to that in the Naval et al and Deurenberg-Yap et al studies.16,21 Also, in line with our findings, Ito et al found dyslipidemia in nearly 40% of normal-weight Japanese men and women.22 The prevalence of high WC was 7.2% (95% CI: 6.0–8.4) in women in our study and in the fourth quartile of BMI the odds ratio of high WC for metabolic syndrome was highest compared with other metabolic risk factors, while there were no men having high WC across normal-weight BMI categories. Although BMI serves as a useful marker of obesity and related insulin resistance,23 stronger correlations are observed between abdominal obesity and metabolic risk factors.24–26 Rexode et al showed that in women with a BMI <25 kg/m2 WC was strongly associated with increased coronary heart disease risk.27 The ATP III included WC as a surrogate marker of abdominal obesity, and WC is closely correlated with adipose tissue and is a better anthropometric predictor of metabolic risk factor than BMI.3 However, since the correlation between BMI and central obesity can vary considerably from one individual to another,28,29 it has been suggested that what causes normal-weight individuals to have metabolic syndrome is having a greater body fat or abdominal obesity at a normal BMI range.
The increased risk of the metabolic syndrome among normal-weight individuals in our study may be genetic in origin30 or consequent to abnormalities in body composition. Since it has been suggested that what causes metabolic syndrome in normal-weight individuals is having greater total, abdominal, subcutaneous and visceral fat at a normal BMI range,31–33 the BMI correspondence to the percent of body fat for Iranian subjects can be another explanation for the high prevalence of metabolic syndrome in the subjects of our study.
There are several points that should be considered when examining the results of this study. The principle limitation of this study was its cross-sectional nature, which prevented casual inferences to be made about the relationship between BMI and the metabolic syndrome. Another limitation was the site of waist measurement, which was the point of noticeable waist narrowing in this study, and might have resulted in lower WC values than those obtained using other common sites of measurement. In addition, besides age, physical activity, smoking and education, other interrelated factors associated with metabolic disorders like diet34 must be considered. Despite these limitations the outstanding strength of this study was using a large population-representative sample of Tehran, which enhances the validity of our findings.
Given the aforementioned limitations, we conclude that there was a relatively high prevalence of metabolic syndrome in normal-weight Iranian men and women. This warrants further investigation on the impact of weight loss and physical activity in this normal-weight population. Also, this study concluded that the cut points of BMI should be lowered in the Iranian population. Determining the actual level to which this should
REFERENCES
- 1.Ruderman NB, Schneider SH, Berchtold P. The “metabolically-obese,” normal-weight individual. Am J Clin Nutr. 1981;34:1617–21. doi: 10.1093/ajcn/34.8.1617. [DOI] [PubMed] [Google Scholar]
- 2.Ruderman NB, Berchtold P, Schneider S. Obesity-associated disorders in normal-weight individuals: some speculations. Int J Obes. 1982;6(Suppl):151–7. Review. [PubMed] [Google Scholar]
- 3.Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults: Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III) JAMA. 2001;285:2486–97. doi: 10.1001/jama.285.19.2486. [DOI] [PubMed] [Google Scholar]
- 4.Azizi F, Salehi P, Etemadi A, Zahedi-Asl S. Prevalence of metabolic syndrome in an urban population: Tehran Lipid and Glucose Study. Diabetes Res Clin Pract. 2003;61:29–37. doi: 10.1016/s0168-8227(03)00066-4. [DOI] [PubMed] [Google Scholar]
- 5.World Health Organization. WHO/NUT/NCD/98.1. Geneva: WHO; 1997b. Obesity. Preventing and managing the global epidemic, Report of WHO consultation on obesity. [PubMed] [Google Scholar]
- 6.Tanaka S, Togashi K, Rankinen T, Perusse L, Leon AS, Rao DC, et al. Is adiposity at normal body weight relevant for cardiovascular disease risk? Int J Obes Relat Metab Disord. 2002;26:176–83. doi: 10.1038/sj.ijo.0801880. [DOI] [PubMed] [Google Scholar]
- 7.Mirmiran P, Esmaillzadeh A, Azizi F. Detection of cardiovascular risk factors by anthropometric measures in Tehranian adults: receiver operating characteristic (ROC) curve analysis. Eur J Clin Nutr. 2004;58:1110–8. doi: 10.1038/sj.ejcn.1601936. [DOI] [PubMed] [Google Scholar]
- 8.Azizi F, Rahmani M, Emami H, Mirmiran P, Hajipour R, Madjid M, et al. Cardiovascular risk factors in an Iranian urban population: Tehran lipid and glucose study (phase 1) Soz Praventivmed. 2002;47:408–26. doi: 10.1007/s000380200008. [DOI] [PubMed] [Google Scholar]
- 9.National Institutes if Health, National Heart Lung and Blood Institute. Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults- The Evidence Report National Institutes of Health. Obes Res. 1998;6(Suppl 2):51S–209S. [PubMed] [Google Scholar]
- 10.Reynolds K, He J. Epidemiology of the metabolic syndrome. Am J Med Sci. 2005;330:273–9. doi: 10.1097/00000441-200512000-00004. [DOI] [PubMed] [Google Scholar]
- 11.Park YW, Zhu S, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB. The metabolic syndrome: prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey, 1988–1994. Arch Intern Med. 2003;163:427–36. doi: 10.1001/archinte.163.4.427. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease burden associated with overweight and obesity. JAMA. 1999;282:1523–9. doi: 10.1001/jama.282.16.1523. [DOI] [PubMed] [Google Scholar]
- 13.Yamamoto A, Horibe H, Mabuchi H, Kita T, Matsuzawa Y, Saito Y, et al. Analysis of serum lipid levels in Japanese men and women according to body mass index. Increase in risk of atherosclerosis in postmenopausal women. Research Group on Serum Lipid Survey 1990 in Japan. Atherosclerosis. 1999;143:55–73. doi: 10.1016/s0021-9150(98)00275-5. [DOI] [PubMed] [Google Scholar]
- 14.Wilson PW, D’Agostino RB, Sullivan L, Parise H, Kannel WB. Overweight and obesity as determinants of cardiovascular risk: the Framingham experience. Arch Intern Med. 2002;162:1867–72. doi: 10.1001/archinte.162.16.1867. [DOI] [PubMed] [Google Scholar]
- 15.Zhou B, Wu Y, Yang J, Li Y, Zhang H, Zhao L. Overweight is an independent risk factor for cardiovascular disease in Chinese populations. Obes Rev. 2002;3:147–56. doi: 10.1046/j.1467-789x.2002.00068.x. [DOI] [PubMed] [Google Scholar]
- 16.Ruderman N, Chisholm D, Pi-Sunyer X, Schneider S. The metabolically obese, normal-weight individual revisited. Diabetes. 1998;47:699–713. doi: 10.2337/diabetes.47.5.699. [DOI] [PubMed] [Google Scholar]
- 17.Vikram NK, Pandey RM, Misra A, Sharma R, Devi JR, Khanna N. Non-obese (body mass index < 25 kg/m2) Asian Indians with normal waist circumference have high cardiovascular risk. Nutrition. 2003;19:503–9. doi: 10.1016/s0899-9007(02)01083-3. [DOI] [PubMed] [Google Scholar]
- 18.Deurenberg-Yap M, Schmidt G, van Staveren WA, Deurenberg P. The paradox of low body mass index and high body fat percentage among Chinese, Malays and Indians in Singapore. Int J Obes Relat Metab Disord. 2000;24:1011–7. doi: 10.1038/sj.ijo.0801353. [DOI] [PubMed] [Google Scholar]
- 19.Schurgin S, Siegel RD. Pharmacotherapy of obesity: an update. Nutr Clin Care. 2003;6:27–37. [PubMed] [Google Scholar]
- 20.Ruderman N, Chisholm D, Pi-Sunyer X, Schneider S. The metabolically obese, normal-weight individual revisited. Diabetes. 1998;47:699–713. doi: 10.2337/diabetes.47.5.699. [DOI] [PubMed] [Google Scholar]
- 21.Deurenberg-Yap M, Chew SK, Lin VF, Tan BY, van Staveren WA, Deurenberg P. Relationships between indices of obesity and its co-morbidities in multi-ethnic Singapore. Int J Obes Relat Metab Disord. 2001;25:1554–62. doi: 10.1038/sj.ijo.0801739. [DOI] [PubMed] [Google Scholar]
- 22.Ito H, Nakasuga K, Ohshima A, Sakai Y, Maruyama T, Kaji Y, et al. Excess accumulation of body fat is related to dyslipidemia in normal-weight subjects. Int J Obes Relat Metab Disord. 2004;28:242–7. doi: 10.1038/sj.ijo.0802528. [DOI] [PubMed] [Google Scholar]
- 23.Stevens J, Cai J, Pamuk ER, Williamson DF, Thun MJ, Wood JL. The effect of age on the association between body-mass index and mortality. N Engl J Med. 1998;338:1–7. doi: 10.1056/NEJM199801013380101. [DOI] [PubMed] [Google Scholar]
- 24.Blair SN, Ludwig DA, Goodyear NN. A canonical analysis of central and peripheral subcutaneous fat distribution and coronary heart disease risk factors in men and women aged 18–65 years. Hum Biol. 1988;60:111–22. [PubMed] [Google Scholar]
- 25.Bjomtorp P. Abdominal fat distribution and disease: an overview of epidemiological data. Ann Med. 1992;24:15–8. doi: 10.3109/07853899209164140. [DOI] [PubMed] [Google Scholar]
- 26.Pi-Sunyer FX. Medical hazards of obesity. Ann Intern Med. 1993;119:655–60. doi: 10.7326/0003-4819-119-7_part_2-199310011-00006. [DOI] [PubMed] [Google Scholar]
- 27.Rexrode KM, Carey VJ, Hennekens CH, Walters EE, Colditz GA, Stampfer MJ, et al. Abdominal adiposity and coronary heart disease in women. JAMA. 1998;280:1843–8. doi: 10.1001/jama.280.21.1843. [DOI] [PubMed] [Google Scholar]
- 28.Stevens J, Cai J, Pamuk ER, Williamson DF, Thun MJ, Wood JL. The effect of age on the association between body mass index and mortality. N Engl J Med. 1998;338:1–7. doi: 10.1056/NEJM199801013380101. [DOI] [PubMed] [Google Scholar]
- 29.Folsom AR, Kaye SA, Sellers TA, Hong CP, Cerhan JR, Potter JD, et al. Body fat distribution and 5-year risk of death in older women. JAMA. 1993;269:483–7. Erratum in: JAMA 1993; 269: 1254. [PubMed] [Google Scholar]
- 30.St-Onge MP, Janssen I, Heymsfield SB. Metabolic syndrome in normal-weight Americans: new definition of the metabolically obese, normal-weight individual. Diabetes Care. 2004;27:2222–8. doi: 10.2337/diacare.27.9.2222. [DOI] [PubMed] [Google Scholar]
- 31.Dvorak RV, DeNino WF, Ades PA, Poehlman ET. Phenotypic characteristics associated with insulin resistance in metabolically obese but normal-weight young women. Diabetes. 1999;48:2210–4. doi: 10.2337/diabetes.48.11.2210. [DOI] [PubMed] [Google Scholar]
- 32.Heber D, Ingles S, Ashley JM, Maxwell MH, Lyons RF, Elashoff RM. Clinical detection of sarcopenic obesity by bioelectrical impedance analysis. Am J Clin Nutr. 1996;64:472S–477S. doi: 10.1093/ajcn/64.3.472S. [DOI] [PubMed] [Google Scholar]
- 33.Dvorak RV, DeNino WF, Ades PA, Poehlman ET. Phenotypic characteristics associated with insulin resistance in metabolically obese but normal-weight young women. Diabetes. 1999;48:2210–4. doi: 10.2337/diabetes.48.11.2210. [DOI] [PubMed] [Google Scholar]
- 34.Mensink RP, Zock PL, Kester AD, Katan MB. Effects of dietary fatty acids and carbohydrates on the ratio of serum total to HDL cholesterol and on serum lipids and apolipoproteins: a meta-analysis of 60 controlled trials. Am J Clin Nutr. 2003;77:1146–55. doi: 10.1093/ajcn/77.5.1146. [DOI] [PubMed] [Google Scholar]