Skip to main content
  • More from ADA
    • Diabetes
    • Clinical Diabetes
    • Diabetes Spectrum
    • ADA Standards of Medical Care
    • ADA Scientific Sessions Abstracts
    • BMJ Open Diabetes Research & Care
  • Subscribe
  • Log in
  • My Cart
  • Follow ada on Twitter
  • RSS
  • Visit ada on Facebook
Diabetes Care

Advanced Search

Main menu

  • Home
  • Current
    • Current Issue
    • Online Ahead of Print
    • Special Article Collections
    • ADA Standards of Medical Care
  • Browse
    • By Topic
    • Issue Archive
    • Saved Searches
    • Special Article Collections
    • ADA Standards of Medical Care
  • Info
    • About the Journal
    • About the Editors
    • ADA Journal Policies
    • Instructions for Authors
    • Guidance for Reviewers
  • Reprints/Reuse
  • Advertising
  • Subscriptions
    • Individual Subscriptions
    • Institutional Subscriptions and Site Licenses
    • Access Institutional Usage Reports
    • Purchase Single Issues
  • Alerts
    • E­mail Alerts
    • RSS Feeds
  • Podcasts
    • Diabetes Core Update
    • Special Podcast Series: Therapeutic Inertia
    • Special Podcast Series: Influenza Podcasts
    • Special Podcast Series: SGLT2 Inhibitors
    • Special Podcast Series: COVID-19
  • Submit
    • Submit a Manuscript
    • Journal Policies
    • Instructions for Authors
    • ADA Peer Review
  • More from ADA
    • Diabetes
    • Clinical Diabetes
    • Diabetes Spectrum
    • ADA Standards of Medical Care
    • ADA Scientific Sessions Abstracts
    • BMJ Open Diabetes Research & Care

User menu

  • Subscribe
  • Log in
  • My Cart

Search

  • Advanced search
Diabetes Care
  • Home
  • Current
    • Current Issue
    • Online Ahead of Print
    • Special Article Collections
    • ADA Standards of Medical Care
  • Browse
    • By Topic
    • Issue Archive
    • Saved Searches
    • Special Article Collections
    • ADA Standards of Medical Care
  • Info
    • About the Journal
    • About the Editors
    • ADA Journal Policies
    • Instructions for Authors
    • Guidance for Reviewers
  • Reprints/Reuse
  • Advertising
  • Subscriptions
    • Individual Subscriptions
    • Institutional Subscriptions and Site Licenses
    • Access Institutional Usage Reports
    • Purchase Single Issues
  • Alerts
    • E­mail Alerts
    • RSS Feeds
  • Podcasts
    • Diabetes Core Update
    • Special Podcast Series: Therapeutic Inertia
    • Special Podcast Series: Influenza Podcasts
    • Special Podcast Series: SGLT2 Inhibitors
    • Special Podcast Series: COVID-19
  • Submit
    • Submit a Manuscript
    • Journal Policies
    • Instructions for Authors
    • ADA Peer Review
Metabolic Syndrome/Insulin Resistance Syndrome/Pre-Diabetes

Is the Diagnosis of Metabolic Syndrome Useful for Predicting Cardiovascular Disease in Asian Diabetic Patients?

Analysis from the Japan Diabetes Complications Study

  1. Hirohito Sone, MD, PHD, FACP1,
  2. Sachiko Mizuno, PHD2,
  3. Hitomi Fujii, MD2,
  4. Yukio Yoshimura, PHD, RD3,
  5. Yoshimitsu Yamasaki, MD, PHD4,
  6. Shun Ishibashi, MD, PHD5,
  7. Shigehiro Katayama, MD, PHD6,
  8. Yasushi Saito, MD, PHD7,
  9. Hideki Ito, MD, PHD8,
  10. Yasuo Ohashi, PHD2,
  11. Yasuo Akanuma, MD, PHD9,
  12. Nobuhiro Yamada, MD, PHD1 and
  13. the Japan Diabetes Complications Study Group*
  1. 1Department of Internal Medicine, University of Tsukuba Institute of Clinical Medicine, Tsukuba, Japan
  2. 2Department of Biostatistics, Epidemiology and Preventive Health Sciences, University of Tokyo, Tokyo, Japan
  3. 3Training Department of Administrative Dietician, Shikoku University, Tokushima, Japan
  4. 4Department of Internal Medicine and Therapeutics, Osaka University Graduate School of Medicine, Osaka, Japan
  5. 5Department of Endocrinology and Metabolism, Jichi Medical College, Tochigi, Japan
  6. 6Fourth Department of Medicine, Saitama Medical School, Saitama, Japan
  7. 7Department of Internal Medicine, Chiba University Graduate School of Medicine, Chiba, Japan
  8. 8Tama-Hokubu Medical Center, Tokyo, Japan
  9. 9Institute for Adult Diseases Asahi Life Foundation, Tokyo, Japan
  1. Address correspondence and reprint requests to Nobuhiro Yamada, MD, PhD, Professor, Department of Internal Medicine, University of Tsukuba Institute of Clinical Medicine, 1-1-1 Tennodai, Tsukuba, Ibaraki, Japan 305-8575. E-mail: jdcstudy{at}md.tsukuba.ac.jp
Diabetes Care 2005 Jun; 28(6): 1463-1471. https://doi.org/10.2337/diacare.28.6.1463
PreviousNext
  • Article
  • Figures & Tables
  • Info & Metrics
  • PDF
Loading

Analysis from the Japan Diabetes Complications Study

Abstract

OBJECTIVE—The metabolic syndrome (MetS) is believed to be associated with an increased risk of cardiovascular disease (CVD). Although its prevalence is extremely high among diabetic patients, its prevalence in those with no history of CVD has not been determined. Moreover, prospective studies published on the association between MetS and cardiovascular events in diabetic populations have used only the World Health Organization (WHO) definition of MetS and included only white European subjects. The aim of this study was to determine the prevalence of MetS, as defined by both the WHO and the National Cholesterol Education Program (NCEP), and its predictive value for CVD in Asian diabetic patients in a long-term, prospective setting.

RESEARCH DESIGN AND METHODS—The baseline characteristics and incidence/hazard ratio of cardiovascular events (coronary heart disease and stroke) were determined in 1,424 Japanese type 2 diabetic patients with and without MetS, as defined by WHO (WHO-MetS) or the NCEP.

RESULTS—A high prevalence (38–53%, depending on sex and definition) of MetS was found among diabetic patients, even those with no history of CVD. During the 8-year study period, only WHO-MetS was a predictor for CVD in female patients. In male patients, although both definitions of MetS were significant predictors for CVD, individual components of MetS, such as hyperlipidemia or hypertension, were equivalent or better predictors.

CONCLUSIONS—We found that MetS is relatively common in diabetic patients with no history of CVD. We suggest that the commonly used definitions of MetS, at least in their present forms, have limited clinical usefulness for Asian diabetic patients and may need some ethnic group−specific modifications for global use.

  • CHD, coronary heart disease
  • CVD, cardiovascular disease
  • ECG, electrocardiogram
  • HOMA-IR, homeostasis model assessment of insulin resistance
  • JDCS, Japan Diabetes Complications Study
  • MetS, metabolic syndrome
  • NCEP, National Cholesterol Education Program
  • UKPDS, U.K. Prospective Diabetes Study
  • WHO, World Health Organization
  • WHR, waist-to-hip ratio

The metabolic syndrome (MetS) is an important cluster of metabolic abnormalities linked with insulin resistance and cardiovascular disease (CVD) (1). The diagnostic criteria of MetS proposed by the World Health Organization (WHO-MetS) (2) and the National Cholesterol Education Program (NCEP-MetS) (3) are currently the most widely used. Although the prevalence of MetS in the general population reportedly differs widely among ethnic groups (4–8) and according to the definition of MetS used (7,9–11), the prevalence among patients with known diabetes is consistently high (70–90%) regardless of ethnicity or definition (12–20). Considering the high prevalence of CVD in the diabetic population (21) and the fact that subjects with a history of CVD often have multiple cardiovascular risk factors, it has been speculated that the extremely high prevalence of MetS among diabetic patients (12–20) may be due to the large number of patients who already have a history of CVD. However, the prevalence of MetS in diabetic patients without CVD has not been widely investigated to date. It is rational to examine this because diabetic patients with MetS have a higher incidence of CVD than those without MetS (15,16) and MetS is a stronger risk factor for CVD in patients with type 2 diabetes than in nondiabetic subjects (12).

Most prospective studies have shown that subjects with MetS are at increased risk of incident CVD (22,23) and mortality due to CVD (9,24–27). However, many of these studies excluded diabetic patients from their study populations (9,22–24). Diabetic patients are known to be at greater risk for CVD than nondiabetic subjects (21), and it has been suggested that MetS is responsible for the increased prevalence of coronary heart disease (CHD) seen in diabetic patients (20). Therefore, it is important to evaluate the predictive value of MetS on incident CVD in diabetic patients in long-term, prospective studies. To the best of our knowledge, there have been four cohort studies specifically targeting diabetic patients to determine the relative risk of MetS on the incidence of CVD (12,15,16) and mortality due to CVD (17). Although these studies involved only white European subjects and used only the WHO definition of MetS, most of them (12,15,16) demonstrated, as expected, that the presence of MetS is associated with at least a severalfold increase in the risk of CVD. The above findings notwithstanding, it remains unclear 1) whether such predictive values of MetS are also applicable to diabetic patients of other ethnicities, 2) which features of MetS are the best predictors of CVD and should become the critical therapeutic targets for the optimal management of CVD risk in diabetic patients (28), and 3) whether the commonly used NCEP definition of MetS (3) possesses the same predictive value for CVD as the WHO definition in diabetic patients.

The incidence of CVD in Asian subjects is known to be much less than in white subjects in general (29) and in diabetic populations in particular (30). In addition, the degree of obesity is very different between white and Asian diabetic patients (31,32), and the impact of obesity on CHD risk is known to be entirely different between whites and Asians (33,34). These differences could affect the apparent clinical significance of MetS (35,36), so that it is questionable whether the overall concept of MetS itself and the diagnosis of MetS under the present definitions based on data from mostly European and American patients are applicable to the evaluation of CVD risk in Asian diabetic patients. Therefore, in this long-term, prospective study of Japanese diabetic patients with no history of CVD, we determined the prevalence of MetS and analyzed its individual features and predictive value for incident CVD using the two most widely used definitions of MetS (2,3). Such comparisons are helpful in possibly establishing a global definition of MetS (10,37) and are also warranted to determine if there is heterogeneity in the power of individual MetS components to predict CVD (28).

RESEARCH DESIGN AND METHODS

The Japan Diabetes Complications Study (JDCS) is a nationwide, multicenter, prospective study of type 2 diabetic patients (38). In 1996, 2,205 patients aged 40–70 years with previously diagnosed type 2 diabetes and HbA1c levels >6.5% were recruited and registered. The eligibility criteria for participating patients has been previously described (38). The duration of the study was 8 years. Of the 2,205 patients, the present study focused on 1,424 patients (771 men and 653 women) who had a complete set of data, including those parameters necessary to satisfy the WHO (2) and NCEP (3) criteria for the definition of MetS at baseline. The JDCS protocol, which is in accordance with the Declaration of Helsinki, received ethical approval from the institutional review boards of all of the participating institutes and was undertaken in accordance with the Ethical Guidelines for Clinical Studies of the Japanese Ministry of Health, Labor, and Welfare. All of the study participants gave written informed consent.

Both the WHO (2) and the NCEP (3) definitions were used to diagnose MetS in this study. However, because the original cut-off for abdominal obesity in the NCEP definition (waist circumference ≥102 cm for men and ≥89 cm for women) has previously been shown to be inappropriate for Asian populations (35,37) and the number of subjects who met these criteria was extremely low, the cut-off limit was adjusted according to the criteria proposed by the Japan Society for the Study of Obesity (≥85 cm for men or ≥90 cm for women), which were based on the risk of obesity-related disorders in a Japanese population (39). The WHO criteria for obesity were adopted because the waist-to-hip ratio (WHR) was used rather than waist circumference. The criteria used for analysis in this study are shown in Table 3. Because all of the study subjects were diabetic, those who fulfilled two or more of criteria 1a, 2a, 5, or 6 were classified as having WHO-MetS and those who fulfilled two or more of criteria 1b, 2b, 3, or 4 were diagnosed as having NCEP-MetS, using a modified NCEP definition (Table 3). For comparisons with other traditional risk factors for CVD, we also evaluated high LDL cholesterol levels, cigarette smoking, and excessive alcohol intake (40). Medication use, including agents for hypertension and hyperlipidemia, were not considered when diagnosing MetS in this study.

Waist and hip circumferences were measured at the umbilicus and trochanter level, respectively. A baseline dietary survey, comprised of food records and a food frequency questionnaire that included alcohol consumption, was undertaken. Information regarding cigarette smoking was collected using a standardized questionnaire. All laboratory tests were undertaken using the standard methods of each of the participating institutes, apart from the HbA1c assays, which used a common standard, with 5.8% as the upper normal limit. Plasma LDL cholesterol was calculated using Friedewald’s equation, except for triglyceride levels >400 mg/dl, in which case the LDL cholesterol data were treated as “missing.” To estimate insulin resistance, the homeostasis model assessment of insulin resistance (HOMA-IR) was used (41). Plasma insulin levels and the HOMA-IR were not evaluated in patients treated with insulin.

Patients were assessed for CHD and stroke at baseline and yearly thereafter. In all subjects, a 12-lead electrocardiogram (ECG) was recorded at each assessment. Fatal and nonfatal CHD and stroke events identified during follow-up were certified by at least two members of the experts’ committee who were masked as to risk factor status and the other member’s diagnosis. With regard to CHD, myocardial infarction was defined according to the WHO Monitoring of Trends and Determinants in Cardiovascular Disease criteria (42) and angina pectoris was defined as typical effort-dependent chest pain or oppression relieved at rest or by using nitroglycerine, as validated by exercise-positive ECG and/or angiography. Stroke events were defined as a constellation of focal or global neurological deficits of sudden or rapid onset and for which there was no apparent cause other than a vascular accident, as determined by a detailed history, a neurological examination, and ancillary diagnostic procedures such as computed tomography, magnetic resonance imaging, cerebral angiography, and lumbar puncture. Stroke events were classified as cerebral infarction (including embolus), intracranial hemorrhage (including subarachnoid hemorrhage), transient ischemic attack, or stroke of undetermined type in accordance with WHO criteria (43). No cases of asymptomatic lesions detected by brain imaging (i.e., silent infarction) were included. Only “first-ever” CHD or stroke events during the study period were counted for the analysis; if a patient had both CHD and stroke events, each event was counted separately.

Data are presented as means ± SD or as a proportion, unless otherwise specified. To compare the distributions of baseline characteristics between groups, Wilcoxon’s rank-sum test or Fisher’s exact test was used. Incidence rates in the two groups were assessed by a score test under the Poisson assumption. Cox regression analysis was used to calculate the adjusted hazard ratio (HR) and 95% confidence interval (CI) of MetS risk factors with CHD, stroke, or both. Statistical analyses were performed separately by sex. The SAS software package (Version 8.0, Cary, NC) was used for all analyses. P < 0.05 was considered to be significant.

RESULTS

Baseline characteristics and prevalence of the metabolic syndrome

The baseline characteristics of the study subjects are shown in Table 1. In all, 51% of male and 53% of female subjects met WHO criteria for MetS, whereas 45% of male and 38% of female subjects met NCEP criteria for MetS. Plasma insulin levels and HOMA-IR were significantly higher in patients with MetS (both definitions) than in those without MetS; however, there were no significant differences in HbA1c or the frequency of oral hypoglycemic agent use. Insulin usage was significantly lower in women with MetS by either definition and in men with NCEP-MetS. Blood pressure and serum triglycerides were significantly higher and HDL cholesterol was significantly lower in MetS patients, despite the fact that the use of medications for both hypertension and hyperlipidemia was much more common than in patients without MetS. Daily energy intake did not differ between patients with and without MetS (data not shown).

Incidence of cardiovascular disease during follow-up

During the 8-year study period, the total number of CVD events was 117, comprised of 62 CHD and 59 stroke events. The combined incidence (per 1,000 patient-years) of CHD and/or stroke was significantly greater in patients with MetS (except in female patients with NCEP-MetS) than in those without MetS (Table 2).

Hazard ratios of the metabolic syndrome and its individual components for coronary heart disease and stroke

HRs were calculated to determine which definition of MetS was the better predictor of CVD and which of the individual MetS components (or other classic risk factors) could most efficiently predict CVD events in our subjects (Table 3). In male patients, WHO-MetS was not significantly associated with an increased risk for either CHD or stroke separately, but was associated with the combination of both (HR = 1.6). Triglyceride, LDL cholesterol (both for CHD), and blood pressure (≥140/90 mmHg) levels (for stroke) showed higher HRs. NCEP-MetS was a significant predictor of CHD in male patients, although its HR (1.9) was lower than that for triglycerides (2.9) or LDL cholesterol (2.1). Thus, neither definition of MetS was a substantially better predictor of CVD than the component parts in male patients. In contrast, in the female patients, WHO-MetS was a significant and strong predictor of CHD (HR = 2.8), stroke (HR = 3.7), and both CHD and stroke (HR = 3.2). In female patients, none of the individual elements nor the other classic risk factors showed significant increases in HRs, with the exception of hypertension (≥140/90 mmHg) for stroke, although its HR (2.4) was still lower than that for WHO-MetS. NCEP-MetS was not a significant risk factor for CHD or stroke in female patients (Table 3).

To examine the clustering effects of the individual components of MetS, the association between CVD risk and the number of MetS components fulfilled (other than diabetes) was analyzed (Table 3). Increasing the cut-off component number for the diagnosis of NCEP-MetS from ≥2 to ≥3 in male subjects did not dramatically improve the HR but did greatly reduce the number of patients diagnosed as having MetS, from 45 to 14.5% (Table 3). In female patients, changing the diagnostic cut-off component numbers was not particularly beneficial in improving the prognostic value of WHO-MetS (Table 3).

CONCLUSIONS

The prevalence of MetS in our diabetic patients who were free from CVD was not as high as that reported in previous studies that included patients with previous CVD (12–20) but was nevertheless relatively high (38–53%). Although we did not have age-matched nondiabetic control subjects, the prevalence of MetS was much higher than that reported in Japanese general population workers, namely 19.5% in men and 7.9% in women (33). Hypertension and dyslipidemia are much more common in diabetic patients than in nondiabetic subjects (21), and it has been speculated that the features of MetS more easily aggregate, even in the absence of current or previous CVD, leading to the observed increase in the prevalence of MetS. On the other hand, the prevalence of NCEP-MetS in the U.S. general population age 50 years and older is 44% (20), which is relatively close to that in our Japanese diabetic patients. However, even in the U.S. (excluding Asian Americans), the prevalence of MetS in those who have a BMI range equivalent to that of Japanese subjects is not >10% (44). This implies that in the U.S., obesity has a potent impact on the prevalence of MetS, as has also been shown in a recent study (45). This is in contrast to findings in Japan, where diabetes rather than obesity may have the greater influence on the prevalence of MetS, as Japanese diabetic patients are not obese by comparison with white diabetic patients or nondiabetic Japanese subjects (31,32).

The clinical importance of MetS is related to its putative impact on CVD morbidity and mortality. Among Italian patients with type 2 diabetes, the risk for CVD was 4.9 (CI 1.2–20.7) times higher in patients with WHO-MetS than in those without it (16), which was a higher rate than that seen in our male (1.6 [CI 1.0–2.6] times) and female (3.2 [CI 1.6–6.5] times) patients. These results suggest that the clinical impact of MetS on diabetic patients varies by ethnic group. Comparing cardiovascular risk factors in our Japanese patients to those in patients in the U.K. Prospective Diabetes Study (UKPDS) (46,47), hypertension is a common and potent risk factor for stroke (Table 3) (46). By contrast, HDL cholesterol levels, hypertension, and smoking, all of which were identified as significant risk factors for CHD in UKPDS patients (47), were not associated with a significant elevation of HRs in our Japanese patients (Table 3). Instead, triglyceride levels, which were not significant in UKPDS patients (47), were a strong predictor for CHD in male Japanese patients. These findings imply that the critical therapeutic targets among the components of MetS for preventing cardiovascular complications (28) may need to be modified according to a patient’s ethnic group.

Most of the previous studies evaluating the predictive power of MetS for CVD calculated the HRs by including sex as one of the independent variables for statistical adjustment, and very few studies have analyzed CVD risk separately by sex (24). Sex is reportedly an independent predictor for CVD, with an odds ratio of 2.6, which is larger than that of age, HbA1c, and even of MetS itself in type 2 diabetic patients (16). Our results revealed drastic differences in the HRs between sexes. In our female patients, WHO-MetS presented an increased risk for CVD events to a greater degree than could be predicted by the sum of the individual components (Table 3), whereas, in contrast, in our male patients, WHO-MetS was not even a significant risk factor for CVD. At baseline, obvious sex differences were observable in the proportion of subjects who smoked or consumed excessive alcohol, both of which were much higher in male patients. Of particular interest, the proportion of male subjects with excessive alcohol intake was at least twice as high in male patients with MetS than in those without MetS, whereas the proportion of current smokers did not differ in patients with and without MetS (Table 1). It can be speculated that excessive alcohol intake could be closely associated with MetS in male Japanese diabetic patients. Moreover, moderate alcohol intake, which has been shown to be beneficial for preventing CHD in U.S. and European diabetic patients, is not beneficial for Japanese patients (40).

Few studies have applied both the WHO and NCEP definitions of MetS to the same subjects to compare the prevalence of MetS or its predictive value for CVD. It has been reported that the prevalence of WHO-MetS is generally higher than that of NCEP-MetS in both sexes (7,12). This was confirmed in our Japanese diabetic subjects, although the difference in prevalence was not great. Regarding the predictive value of MetS, in subjects without diabetes or other cardiovascular risks, Hunt et al. (27) reported that the NCEP-MetS tended to be more predictive for cardiovascular mortality than the WHO-MetS, whereas Lakka et al. (9) reported a contrary result. In our diabetic patients, the NCEP guidelines, even modified for optimal use by Japanese subjects, were not more predictive than the WHO guidelines in female patients nor did they show excellent clinical usefulness in male patients. One possible explanation for this difference in our patients could be the hypertension cut-off used, with 140/90 mmHg in the WHO definition being a significant predictor for stroke, whereas 130/85 mmHg in the NCEP definition is not.

The strengths of our study were that 1) it is the first prospective study to determine the predictive value of MetS on CVD in Asian subjects, 2) the two most widely used definitions of MetS were applied to the same cohort for the evaluation of their clinical usefulness, and 3) the follow-up was mainly carried out in university or large general hospitals, which facilitated the reliable assessment of follow-up data and event diagnosis/records. Nevertheless, we acknowledge that the study had certain limitations: 1) Our study subjects were hospital-based patients with diabetes of a relatively long duration; therefore, we cannot make inferences beyond a similar group. 2) We analyzed both intervention (lifestyle modification through diabetes self-management care) and control (continuance of conventional care) groups of the JDCS together, although mild intervention produced only limited differences in glycemic control (0.1–0.2% in HbA1c) as well as a lack of significant differences in known classical cardiovascular risk factors, as previously reported (38). 3) We did not consider medication use in the diagnosis of MetS in this study. 4) Mortality was not analyzed because we did not have sufficient occurrences at this stage of the study.

In conclusion, we found a high prevalence of MetS among diabetic patients with no history of CVD. For Japanese female patients with type 2 diabetes, WHO-MetS but not NCEP-MetS was predictive for CVD. In male patients, although both WHO-MetS and NCEP-MetS were somewhat predictive for CVD, hyperlipidemia or hypertension had equivalent or higher HRs for CVD and seemed to be sufficient for the prediction of CVD. We suggest that the commonly used definitions of MetS, at least in their present forms, have limited clinical usefulness for Asian diabetic patients and may need some ethnic group−specific modifications for global use.

APPENDIX

The Japan Diabetes Complications Study (JDCS) Group

Primary investigator:

Nobuhio Yamada (University of Tsukuba)

Chief of Assessment Committee:

Yasuo Akanuma (Institute for Adult Diseases Asahi Life Foundation)

Committee members:

Keita Ato, Masaaki Eto, Hiroshi Ito (Asahikawa Medical College); Azuma Kanatsuka, Naotake Hashimoto, Yasushi Saito, Kazuo Takahashi, Kazuo Yagi (Chiba University); Tadami Takekoshi, Takanobu Wakasugi (Fukui Prefectural Hospital); Shigetake Toyooka (Fukui Red Cross Hospital); Yukihiro Bando (Fukui Saiseikai Hospital); Tsugihiko Nakai, Koji Oida, Jinya Suzuki (Fukui University); Yasuaki Fukumoto, Seiichi Sumi (Garatia Hostiptal); Genshi Egusa, Rumi Fujikawa, Masamichi Okubo, Kiminori Yamane (Hiroshima University); Takao Koike, Narihito Yoshioka (Hokkaido University); Motonobu Anai, Ritsuko Honda, Masatoshi Kikuchi (Institute for Adult Diseases Asahi Life Foundation); Shun Ishibashi (Jichi Medical School); Masanobu Kawakami, Kazuyuki Namai (Jichi Medical School Omiya Medical Center); Takashi Sasaki, Masami Nemoto (Jikei University); Ryuzo Kawamori, Yasushi Tanaka (Juntendo University); Toshihiko Ishida (Kagawa University); Izumi Takei (Keio University); Yoshikuni Fujita, Keiji Tanaka, Yoshihiro Yajima (Kitazato University); Hideki Kishikawa, Tetsushi Toyonaga (Kumamoto University); Shingo Komichi, Zenji Makita, Kyohei Nonaka, Kentaro Yamada (Kurume University); Naoto Nakamura, Koji Nakano (Kyoto Prefectural University of Medicine); Toyoshi Iguchi, Hajime Nawata (Kyushu University); Yasuhisa Matsushima (Matsudo City Hospital); Hideo Takahashi (Minami Akatsuka Clinic); Hiroyuki Toyoshima (Minoh City Hospital); Shoichi Akazawa, Eiji Kawasaki, Shigenobu Nagataki (Nagasaki University); Nigishi Hotta, Jiro Nakamura (Nagoya University); Kentaro Doi, Yu Harano, Yasunao Yoshimasa (National Cardiovascular Center); Yoichi Hayashi (Nihon University); Shinichi Oikawa (Nippon Medical School); Ryuzo Abe, Hiroaki Seino, Daishiro Yamada (Ohta-Nishinouchi Hospital); Mitsuru Hoshi, Takao Watarai (Osaka Koseinenkin Hospital); Masatoshi Imaizumi, Ryohei Todo (Osaka National Hospital); Keisuke Kosugi, Yasuhisa Shimizu, Yutaka Umayahara (Osaka Police Hospital); Junichiro Miyagawa, Mitsuyoshi Namba, Kaoru Takemura, Yoshimitsu Yamasaki (Osaka University); Kazuhiro Hosokawa, Kempei Matsuoka (Saiseikai Central Hospital); Junko Nakano, Hirotaka Umezu (Saiseikai Fukushima General Hospital); Akihiko Hoshino, Toshihiko Nishiyama, Tetsushi Nogami (Saisekai Kumamoto Hospital); Hideo Nunome (Saiseikai Mito Hospital); Shigehiro Katayama, Atsuhito Togashi (Saitama Medical College); Kenichi Yamada (Sakura National Hospital); Atsunori Kashiwagi, Yoshihiko Nishio (Shiga University of Medical Science); Yukio Yoshimura (Shikoku University); Tatsuhide Inoue (Shizuoka General Hospital); Masafumi Kitaoka (Showa General Hospital); Toshio Kitada, Akio Shirai, Ryoichiro Watanabe (Takeda General Hospital); Takaichi Miyagawa (Tama Minami Clinic); Yoshikazu Sakamoto, Osamu Mokuta, Ryo Okazaki (Teikyo Universiy Ichihara Hospital); Kazuma Takahashi (Tohoku University); Koji Shirai, Hiroshi Miyashita (Toho University Sakura Hospital); Akira Tanaka (Tokyo Medical and Dental University); Yoshiaki Fujita (Tokyo Metropolitan Institute of Gerontology); Hideki Ito (Tama-Hokubu Medical Center) Reiko Kawahara, Yasue Omori, Asako Sato (Tokyo Women’s Medical University); Toshio Murase, Mitsuhiko Noda, Masato Odawara (Toranomon Hospital); Masashi Kobayashi, Masaharu Urakaze (Toyama Medical and Pharmaceutical University); Hitomi Fujii, Satoshi Iimuro, Takashi Kadowaki, Sachiko Mizuno, Yasuo Ohashi, Junichi Osuga, Yasuyoshi Ouchi, Akane Takahashi (University of Tokyo); Hirohito Sone, Kamejiro Yamashita (University of Tsukuba); Ryo Kawasaki, Hidetoshi Yamashita (Yamagata University); Hisahiko Sekihara, Yasumichi Mori (Yokohama City University); Tetsuo Nishikawa (Yokohama Rosai Hospital); Hiroto Furuta, Kishio Nanjo (Wakayama Medical University).

View this table:
  • View inline
  • View popup
Table 1—

Baseline characteristics of study subjects, grouped by metabolic syndrome status

View this table:
  • View inline
  • View popup
Table 2—

Incidence of coronary heart disease and/or stroke (per 1,000 patient-years) among study subjects grouped by metabolic syndrome status

View this table:
  • View inline
  • View popup
Table 3—

Patient prevalence at baseline and hazard ratios for coronary heart disease, stroke, or both in Japanese study subjects grouped by metabolic syndrome status

Acknowledgments

This study was financially supported by the Ministry of Health, Labor, and Welfare of Japan, the Japan Arteriosclerosis Prevention Fund, and the Japan Heart Foundation.

We gratefully acknowledge all the patients, physicians, and staff taking part in the JDCS.

Footnotes

  • H.S. and S.M. contributed equally to the study.

  • *

    ↵* A complete list of members of the Japan Diabetes Complications Study Group can be found in the appendix.

  • A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

    • Accepted February 17, 2005.
    • Received December 3, 2004.
  • DIABETES CARE

References

  1. ↵
    Reaven GM: Banting Lecture 1988: Role of insulin resistance in human disease. Diabetes 37: 1595–1607, 1988
    OpenUrlAbstract/FREE Full Text
  2. ↵
    World Health Organization: Definition, Diagnosis and Classification of Diabetes Mellitus and Its Complications. Part 1: Diagnosis and Classification of Diabetes Mellitus. Geneva, World Health Organization, 1999
  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 285:2486–2497, 2001
    OpenUrlCrossRefPubMedWeb of Science
  4. ↵
    Balkau B, Charles MA, Drivsholm T, Borch-Johnsen K, Wareham N, Yudkin JS, Morris R, Zavaroni I, van Dam R, Feskins E, Gabriel R, Diet M, Nilsson P, Hedblad B, European Group for the Study of Insulin Resistance: Frequency of the WHO metabolic syndrome in European cohorts, and an alternative definition of an insulin resistance syndrome. Diabete Metab 28:364–376, 2002
    OpenUrlPubMedWeb of Science
  5. 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 163:427–436, 2003
    OpenUrlCrossRefPubMedWeb of Science
  6. Meigs JB, Wilson PW, Nathan DM, D’Agostino RB Sr, Williams K, Haffner SM: Prevalence and characteristics of the metabolic syndrome in the San Antonio Heart and Framingham Offspring Studies. Diabetes 52:2160–2167, 2003
    OpenUrlAbstract/FREE Full Text
  7. ↵
    Cameron AJ, Shaw JE, Zimmet PZ: The metabolic syndrome: prevalence in worldwide populations. Endocrinol Metab Clin North Am 33:351–375, 2004
    OpenUrlCrossRefPubMedWeb of Science
  8. ↵
    Simmons D, Thompson CF: Prevalence of the metabolic syndrome among adult New Zealanders of Polynesian and European descent. Diabetes Care 27:3002–3004, 2004
    OpenUrlFREE Full Text
  9. ↵
    Lakka HM, Laaksonen DE, Lakka TA, Niskanen LK, Kumpusalo E, Tuomilehto J, Salonen JT: The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA 288:2709–2716, 2002
    OpenUrlCrossRefPubMedWeb of Science
  10. ↵
    Ford ES, Giles WH: A comparison of the prevalence of the metabolic syndrome using two proposed definitions. Diabetes Care 26:575–581, 2003
    OpenUrlAbstract/FREE Full Text
  11. ↵
    Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Bonadonna RC, Muggeo M: Carotid atherosclerosis and coronary heart disease in the metabolic syndrome: prospective data from the Bruneck study. Diabetes Care 26:1251–1257, 2003
    OpenUrlAbstract/FREE Full Text
  12. ↵
    Isomaa B, Almgren P, Tuomi T, Forsen B, Lahti K, Nissen M, Taskinen MR, Groop L: Cardiovascular morbidity and mortality associated with the metabolic syndrome. Diabetes Care 24:683–689, 2001
    OpenUrlAbstract/FREE Full Text
  13. Ilanne-Parikka P, Eriksson JG, Lindstrom J, Hamalainen H, Keinanen-Kiukaanniemi S, Laakso M, Louheranta A, Mannelin M, Rastas M, Salminen V, Aunola S, Sundvall J, Valle T, Lahtela J, Uusitupa M, Tuomilehto J, Finnish Diabetes Prevention Study Group: Prevalence of the metabolic syndrome and its components: findings from a Finnish general population sample and the Diabetes Prevention Study cohort. Diabetes Care 27:2135–2140, 2004
    OpenUrlAbstract/FREE Full Text
  14. Relimpio F, Martinez-Brocca MA, Leal-Cerro A, Losada F, Mangas MA, Pumar A, Astorga R: Variability in the presence of the metabolic syndrome in type 2 diabetic patients attending a diabetes clinic: influences of age and gender. Diabetes Res Clin Pract 65:135–142, 2004
    OpenUrlPubMed
  15. ↵
    Gimeno Orna JA, Lou Arnal LM, Molinero Herguedas E, Boned Julian B, Portilla Cordoba DP: Metabolic syndrome as a cardiovascular risk factor in patients with type 2 diabetes. Rev Esp Cardiol 57:507–513, 2004 (in Spanish)
    OpenUrlCrossRefPubMedWeb of Science
  16. ↵
    Bonora E, Targher G, Formentini G, Calcaterra F, Lombardi S, Marini F, Zenari L, Saggiani F, Poli M, Perbellini S, Raffaelli A, Gemma L, Santi L, Bonadonna RC, Muggeo M: Metabolic syndrome is an independent predictor of cardiovascular disease in type 2 diabetic subjects: prospective data from the Verona Diabetes Complications Study. Diabet Med 21:52–58, 2004
    OpenUrlCrossRefPubMedWeb of Science
  17. ↵
    Bruno G, Merletti F, Biggeri A, Bargero G, Ferrero S, Runzo C, Prina Cerai S, Pagano G, Cavallo-Perin P, Casale Monferrato Study: Metabolic syndrome as a predictor of all-cause and cardiovascular mortality in type 2 diabetes: the Casale Monferrato Study. Diabetes Care 27:2689–2694, 2004
    OpenUrlAbstract/FREE Full Text
  18. Costa LA, Canani LH, Lisboa HR, Tres GS, Gross JL: Aggregation of features of the metabolic syndrome is associated with increased prevalence of chronic complications in type 2 diabetes. Diabet Med 21:252–255, 2004
    OpenUrlCrossRefPubMedWeb of Science
  19. Lee YJ, Tsai JC: ACE gene insertion/deletion polymorphism associated with 1998 World Health Organization definition of metabolic syndrome in Chinese type 2 diabetic patients. Diabetes Care 25:1002–1008, 2002
    OpenUrlAbstract/FREE Full Text
  20. ↵
    Alexander CM, Landsman PB, Teutsch SM, Haffner SM, Third National Health and Nutrition Examination Survey (NHANES III), National Cholesterol Education Program (NCEP): NCEP-defined metabolic syndrome, diabetes, and prevalence of coronary heart disease among NHANES III participants age 50 years and older. Diabetes 52:1210–1214, 2003
    OpenUrlAbstract/FREE Full Text
  21. ↵
    Ekoe JM, Zimmet P, Williams R: The Epidemiology of Diabetes Mellitus. West Sussex, U.K., Wiley, 2001
  22. ↵
    Klein BE, Klein R, Lee KE: Components of the metabolic syndrome and risk of cardiovascular disease and diabetes in Beaver Dam. Diabetes Care 25:1790–1794, 2002
    OpenUrlAbstract/FREE Full Text
  23. ↵
    Girman CJ, Rhodes T, Mercuri M, Pyorala K, Kjekshus J, Pedersen TR, Beere PA, Gotto AM, Clearfield M, 4S Group, AFCAPS/TexCAPS Research Group: The metabolic syndrome and risk of major coronary events in the Scandinavian Simvastatin Survival Study (4S) and the Air Force/Texas Coronary Atherosclerosis Prevention Study (AFCAPS/TexCAPS). Am J Cardiol 93:136–141, 2004
    OpenUrlCrossRefPubMedWeb of Science
  24. ↵
    Hu G, Qiao Q, Tuomilehto J, Balkau B, Borch-Johnsen K, Pyorala K, the DECODE Study Group: Prevalence of the metabolic syndrome and its relation to all-cause and cardiovascular mortality in non-diabetic European men and women. Arch Intern Med 164:1066–1076, 2004
    OpenUrlCrossRefPubMedWeb of Science
  25. Malik S, Wong ND, Franklin SS, Kamath TV, L’Italien GJ, Pio JR, Williams GR: Impact of the metabolic syndrome on mortality from coronary heart disease, cardiovascular disease, and all causes in United States adults. Circulation 110:1239–1244, 2004
    OpenUrl
  26. Ford ES: The metabolic syndrome and mortality from cardiovascular disease and all-causes: findings from the National Health and Nutrition Examination Survey II Mortality Study. Atherosclerosis 173:309–314, 2004
    OpenUrlCrossRefPubMedWeb of Science
  27. ↵
    Hunt KJ, Resendez RG, Williams K, Haffner SM, Stern MP, San Antonio Heart Study: National Cholesterol Education Program versus World Health Organization metabolic syndrome in relation to all-cause and cardiovascular mortality in the San Antonio Heart Study. Circulation 110:1251–1257, 2004
    OpenUrlAbstract/FREE Full Text
  28. ↵
    Golden SH, Chong R: Are there specific components of the insulin resistance syndrome that predict the increased atherosclerosis seen in type 2 diabetes mellitus? Curr Diab Rep 4:26–30, 2004
    OpenUrlPubMed
  29. ↵
    van den Hoogen PC, Feskens EJ, Nagelkerke NJ, Menotti A, Nissinen A, Kromhout D: The relation between blood pressure and mortality due to coronary heart disease among men in different parts of the world: Seven Countries Study Research Group. N Engl J Med 342:1–8, 2000
    OpenUrlCrossRefPubMedWeb of Science
  30. ↵
    Lee ET, Keen H, Bennett PH, Fuller JH, Lu M: Follow-up of the WHO Multinational Study of Vascular Disease in Diabetes: general description and morbidity. Diabetologia 44 (Suppl. 2):S3–S13, 2001
  31. ↵
    Sone H, Ito H, Ohashi Y, Akanuma Y, Yamada N, Japan Diabetes Complication Study Group: Obesity and type 2 diabetes in Japanese patients (Letter). Lancet 361:85, 2003
    OpenUrlPubMedWeb of Science
  32. ↵
    Sone H, Yoshimura Y, Ito H, Ohashi Y, Yamada N, Japan Diabetes Complications Study Group: Energy intake and obesity in Japanese patients with type 2 diabetes. Lancet 363:248–249, 2004
    OpenUrlPubMed
  33. ↵
    Anuurad E, Shiwaku K, Nogi A, Kitajima K, Enkhmaa B, Shimono K, Yamane Y: The new BMI criteria for Asians by the regional office for the Western Pacific region of WHO are suitable for screening of overweight to prevent metabolic syndrome in elder Japanese workers. J Occup Health 45:335–343, 2003
    OpenUrlCrossRefPubMedWeb of Science
  34. ↵
    WHO Expert Consultation: Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 363:157–163, 2004
    OpenUrlCrossRefPubMedWeb of Science
  35. ↵
    Tan CE, Ma S, Wai D, Chew SK, Tai ES: Can we apply the National Cholesterol Education Program Adult Treatment Panel definition of the metabolic syndrome to Asians? Diabetes Care 27:1182–1186, 2004
    OpenUrlAbstract/FREE Full Text
  36. ↵
    Ota T, Takamura T, Hirai N, Kobayashi K: Preobesity in World Health Organization classification involves the metabolic syndrome in Japanese. Diabetes Care 25:1252–1253, 2002
    OpenUrlFREE Full Text
  37. ↵
    Jorgensen ME, Borch-Johnsen K: The metabolic syndrome. Is one global definition possible? Diabet Med 21:1064–1065, 2004
    OpenUrlCrossRefPubMedWeb of Science
  38. ↵
    Sone H, Katagiri A, Ishibashi S, Abe R, Saito Y, Murase T, Yamashita H, Yajima Y, Ito H, Ohashi Y, Akanuma Y, Yamada N, the Japan Diabetes Complications Study Group: Effects of lifestyle modifications on patients with type 2 diabetes: the Japan Diabetes Complications Study (JDCS) study design, baseline analysis and three year-interim report. Horm Metab Res 34:509–515, 2002
    OpenUrlCrossRefPubMedWeb of Science
  39. ↵
    Examination Committee of Criteria for “Obesity Disease” in Japan, Japan Society for the Study of Obesity: New criteria for “obesity disease” in Japan. Circ J 66:987–992, 2002
    OpenUrlCrossRefPubMedWeb of Science
  40. ↵
    Sone H, Yamada N, Mizuno S, Aida R, Ohashi Y, the Japan Diabetes Complications Study (JDCS) Group: Alcohol use and diabetes mellitus. Ann Intern Med 141:408–409, 2004
    OpenUrlPubMed
  41. ↵
    Bonora E, Formentini G, Calcaterra F, Lombardi S, Marini F, Zenari L, Saggiani F, Poli M, Perbellini S, Raffaelli A, Cacciatori V, Santi L, Targher G, Bonadonna R, Muggeo M: HOMA-estimated insulin resistance is an independent predictor of cardiovascular disease in type 2 diabetic subjects: prospective data from the Verona Diabetes Complications Study. Diabetes Care 25:1135–1141, 2002
    OpenUrlAbstract/FREE Full Text
  42. ↵
    Tunstall-Pedoe H, Kuulasmaa K, Amouyel P, Arveiler D, Rajakangas AM, Pajak A: Myocardial infarction and coronary deaths in the World Health Organization MONICA Project: registration procedures, event rates, and case-fatality rates in 38 populations from 21 countries in four continents. Circulation 90:583–612, 1994
    OpenUrlAbstract/FREE Full Text
  43. ↵
    Aho K, Harmsen P, Hatano S: Marquardsen J, Smirnov VE, Strasser T, on behalf of the participants in the WHO Collaborative Study on the Control of Stroke in the Community: Cerebrovascular disease in the community: results of a WHO Collaborative Study. Bull World Health Organ 58:113–130, 1980
    OpenUrlPubMedWeb of Science
  44. ↵
    St-Onge MP, Janssen I, Heymsfield SB: Metabolic syndrome in normal-weight Americans: new definition of the metabolically obese, normal-weight individual. Diabetes Care 27:2222–2228, 2004
    OpenUrlAbstract/FREE Full Text
  45. ↵
    Huang TT, Kempf AM, Strother ML, Li C, Lee RE, Harris KJ, Kaur H: Overweight and components of the metabolic syndrome in college students. Diabetes Care 27:3000–3001, 2004
    OpenUrlFREE Full Text
  46. ↵
    Davis TM, Millns H, Stratton IM, Holman RR, Turner RC: Risk factors for stroke in type 2 diabetes mellitus: United Kingdom Prospective Diabetes Study (UKPDS) 29. Arch Intern Med 159:1097–1103, 1999
    OpenUrlCrossRefPubMedWeb of Science
  47. ↵
    Turner RC, Millns H, Neil HA, Stratton IM, Manley SE, Matthews DR, Holman RR: Risk factors for coronary artery disease in non-insulin dependent diabetes mellitus: United Kingdom Prospective Diabetes Study (UKPDS) 23. BMJ 316:823–828, 1998
    OpenUrlAbstract/FREE Full Text
PreviousNext
Back to top
Diabetes Care: 28 (6)

In this Issue

June 2005, 28(6)
  • Table of Contents
  • About the Cover
  • Index by Author
Sign up to receive current issue alerts
View Selected Citations (0)
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word about Diabetes Care.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Is the Diagnosis of Metabolic Syndrome Useful for Predicting Cardiovascular Disease in Asian Diabetic Patients?
(Your Name) has forwarded a page to you from Diabetes Care
(Your Name) thought you would like to see this page from the Diabetes Care web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Is the Diagnosis of Metabolic Syndrome Useful for Predicting Cardiovascular Disease in Asian Diabetic Patients?
Hirohito Sone, Sachiko Mizuno, Hitomi Fujii, Yukio Yoshimura, Yoshimitsu Yamasaki, Shun Ishibashi, Shigehiro Katayama, Yasushi Saito, Hideki Ito, Yasuo Ohashi, Yasuo Akanuma, Nobuhiro Yamada
Diabetes Care Jun 2005, 28 (6) 1463-1471; DOI: 10.2337/diacare.28.6.1463

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Add to Selected Citations
Share

Is the Diagnosis of Metabolic Syndrome Useful for Predicting Cardiovascular Disease in Asian Diabetic Patients?
Hirohito Sone, Sachiko Mizuno, Hitomi Fujii, Yukio Yoshimura, Yoshimitsu Yamasaki, Shun Ishibashi, Shigehiro Katayama, Yasushi Saito, Hideki Ito, Yasuo Ohashi, Yasuo Akanuma, Nobuhiro Yamada
Diabetes Care Jun 2005, 28 (6) 1463-1471; DOI: 10.2337/diacare.28.6.1463
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • RESEARCH DESIGN AND METHODS
    • RESULTS
    • CONCLUSIONS
    • APPENDIX
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Tables
  • Info & Metrics
  • PDF

Related Articles

Cited By...

More in this TOC Section

  • Hepatic Enzymes, the Metabolic Syndrome, and the Risk of Type 2 Diabetes in Older Men
  • Anthropometry, Glucose Tolerance, and Insulin Concentrations in Indian Children
  • Dietary Calcium, Vitamin D, and the Prevalence of Metabolic Syndrome in Middle-Aged and Older U.S. Women
Show more Metabolic Syndrome/Insulin Resistance Syndrome/Pre-Diabetes

Similar Articles

Navigate

  • Current Issue
  • Standards of Care Guidelines
  • Online Ahead of Print
  • Archives
  • Submit
  • Subscribe
  • Email Alerts
  • RSS Feeds

More Information

  • About the Journal
  • Instructions for Authors
  • Journal Policies
  • Reprints and Permissions
  • Advertising
  • Privacy Policy: ADA Journals
  • Copyright Notice/Public Access Policy
  • Contact Us

Other ADA Resources

  • Diabetes
  • Clinical Diabetes
  • Diabetes Spectrum
  • Scientific Sessions Abstracts
  • Standards of Medical Care in Diabetes
  • BMJ Open - Diabetes Research & Care
  • Professional Books
  • Diabetes Forecast

 

  • DiabetesJournals.org
  • Diabetes Core Update
  • ADA's DiabetesPro
  • ADA Member Directory
  • Diabetes.org

© 2021 by the American Diabetes Association. Diabetes Care Print ISSN: 0149-5992, Online ISSN: 1935-5548.