33
REVIEW / SYNTHE`SE
Metabolic syndrome and its association with morbidity and mortality Chris I. Ardern and Ian Janssen
Abstract: The metabolic syndrome (MetS) is a cluster of cardiovascular risk factors that are associated with increased risk of diabetes, cardiovascular disease (CVD), and all-cause mortality; however, it is clear that considerable variation exists in these relationships. Given that the prevalence of MetS increases with age, is higher in men than in women, and varies with race and ethnicity, a number of questions about the clinical application of MetS in predicting morbidity and mortality in diverse populations remain unanswered. Thus, in this review, we compare the ability of MetS to predict health risk across age, sex, race, and ethnicity, and in primary versus secondary prevention subgroups to explore these relationships. Furthermore, as there is currently no universal MetS criteria, we also discuss differences in the prediction of morbidity and mortality in studies that used different criteria to define MetS. At present, further research is necessary to examine the health risks associated with (i) different combinations of MetS components in diverse populations, (ii) the relative importance of each MetS component in predicting different health outcomes, and (iii) the independent contribution of MetS in predicting risk of morbidity and mortality beyond that incurred by other risk factors. Key words: cardiovascular disease, diabetes, death, epidemiology, population health. Re´sume´ : Le syndrome me´tabolique (MetS) constitue un ensemble de risques cardiovasculaires associe´s a` un plus haut risque de diabe`te, de maladie cardiovasculaire (CVD) et de mortalite´ de toute cause. Ces interrelations pre´sentent ne´anmoins une importante variation. Comme la pre´valence du MetS augmente avec l’aˆge, est plus e´leve´ chez les hommes et varie d’une race et d’un groupe ethnique a` l’autre, on n’a pas encore re´pondu a` certaines questions relatives aux applications cliniques du MetS en termes de pre´diction de la morbidite´ et de la mortalite´ dans diverses populations. Dans cet article-synthe`se, nous comparons le potentiel du MetS a` pre´dire le risque de maladie en fonction de l’aˆge, du sexe et de la race ou du groupe ethnique ; de plus, nous analysons les interrelations dans les sous-groupes de pre´vention primaire et de pre´vention secondaire. Comme il n’y a pas encore de crite`res universels du MetS, nous analysons aussi les diffe´rences de ` ce pre´diction de la morbidite´ et de la mortalite´ rapporte´es dans les e´tudes qui utilisent diffe´rentes de´finitions du MetS. A jour, il faut faire d’autres e´tudes pour analyser les risques de maladie associe´s a` (i) diffe´rentes combinaisons des constituants du Mets dans diverses populations, (ii) l’importance relative de chacun des constituants du Mets comme pre´dicteur de risque distinct et (iii) la contribution isole´e du MetS a` pre´dire la morbidite´ et la mortalite´ au-dela` du risque associe´ aux autres facteurs. Mots cle´s : maladie cardiovasculaire, diabe`te, mort, e´pide´miologie, sante´ de la population. [Traduit par la Re´daction]
Introduction Both the National Cholesterol Education Program (NCEP) third Adult Treatment Panel (ATP III) (Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults 2001) and the American Heart Association (Pearson et al. 2002) recommend aggressively targeting individuals with multiple cardiovascular risk factors such as the metabolic syndrome (MetS), owing to their increased risk of
type 2 diabetes (T2DM), cardiovascular disease (CVD), and premature mortality. The primary aim of this review was to summarize the evidence for an association between MetS and morbidity and mortality, and discuss differences by sex, race and ethnicity, age, and disease status. Second, this review compared different MetS criteria (see Lamarche and Desroches 2006 and Table 1 for a summary) as predictors of morbidity and mortality. Finally, to provide a context for future research into the association between MetS and mor-
Received 22 June 2006. Accepted 3 September 2006. Published on the NRC Research Press Web site at http://apnm.nrc.ca on 30 January 2007. C.I. Ardern.1 School of Kinesiology and Health Science, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada. I. Janssen. School of Kinesiology and Health Studies, Queen’s University, Kingston, ON K7L 3N6, Canada; Department of Community Health and Epidemiology, Queen’s University, Kingston, ON K7L 3N6, Canada. 1Corresponding
author (e-mail:
[email protected]).
Appl. Physiol. Nutr. Metab. 32: 33–45 (2007)
doi:10.1139/H06-099
#
2007 NRC Canada
34
Appl. Physiol. Nutr. Metab. Vol. 32, 2007 Table 1. NCEP, IDF, and WHO operational criteria for identifying individuals suspected of having the metabolic syndrome. Organization
Definition and criteria
WHO
Present if glucose intolerance, impaired glucose tolerance, insulin resistance, or diabetes and 2 or more of the following are identified: Abdominal obesity: (M, WHR>0.90; F, WHR>0.85) TG>1.7 mmol/L HDL-C (M, 88 cm) TG‡1.7 mmol/L HDL-C (M, 50th percentile of carotid IMT) on odds of CAD is further modified by the presence of diabetes. Thus, the results of the above studies are suggestive of greater absolute and relative risk of morbidity and mortality overall, but that this effect may be attenuated when the referent groups are individuals without MetS but with the same overt disease (e.g., CAD etc.).
Comparison of MetS criteria as predictors of morbidity and mortality NCEP vs. WHO The majority of studies to date that have compared the NCEP and WHO MetS tools have not found important dif-
Appl. Physiol. Nutr. Metab. Vol. 32, 2007
ferences in the magnitude of their relative risks for morbidity and mortality, and are consistent with results of the meta-analysis by Ford (2005). One such study that compared NCEP and WHO for risk of incident T2DM was that of Hanley et al. (2005). In this study, 822 healthy middle-aged adults (40–69 y) from the Insulin Resistance Atherosclerosis Study were followed over 5.2 y for the development of T2DM, the results of which suggest that the MetS definitions were not materially different (NCEP: OR = 4.14, 2.79–6.16; WHO: OR = 3.68, 2.48–5.45). A second prospective study from the San Antonio Heart Study (25–64 y; n = 2 815) (Hunt et al. 2004) reinforce the findings of Hanley et al. (2005); in this study, the relative risk of all-cause mortality over 12.7 y of follow-up did not differ by MetS definition (NCEP: 1.47, 1.13–1.92; WHO: 1.27, 0.97–1.66), although NCEP-defined MetS yielded stronger estimates for CVD than WHO MetS (NCEP: 2.53, 1.74–3.67; WHO: 1.63, 1.13–2.36), with the difference being particularly pronounced in men. By contrast, it seems that the results from studies limited to older adults (‡65 y; Hillier et al. 2005) and Asian ethnic groups (Ko et al. 2005; Sone et al. 2006; Takamiya et al. 2004) more consistently yield stronger relative risk estimates for WHO than NCEP MetS criteria for CVD and all-cause mortality. Alternatively, other studies have compared the NCEP and WHO definitions by examining their sensitivity and specificity in identification of future health risk. Using an ROC curve approach, Hanson et al. (2002) found that prediction of incident T2DM in 1918 Pima Indians was more sensitive and specific for the WHO than the NCEP MetS definition. In recent cross-sectional analysis, results from Takamiya et al. (2004) also indicate differences by MetS definition for high coronary calcium scores (NCEP: OR = 3.02, 0.72–12.6; WHO: OR = 4.17, 1.15–15.2); however, results from the British Women’s Heart and Health Study (60–79 years) comparing definitions for the association between MetS and CAD do not (modified WHO: 1.53, 1.19–1.75; NCEP: 1.53, 1.27– 1.85) (Lawlor et al. 2004). Thus, although there is not a consensus, the majority of studies do not support the finding of large differences between WHO and NCEP MetS for the prediction of morbidity and mortality, and any such differences may be specific to the disease and population group studied. NCEP vs. NHLBI–AHA To date, only one prospective study (Katzmarzyk et al. 2006) has compared the ability of the original NCEP and the modified version adopted by the National Heart, Lung, and Blood Institute and American Heart Association (NHLBI–AHA; Grundy et al. 2004) to predict morbidity and mortality. Using data from the Aerobics Center Longitudinal Study (20 789 primarily white men), Katzmarzyk et al. (2006) report no important difference in the magnitude of prediction of all-cause (NCEP: 1.36, 1.14–1.62; NHLBI– AHA: 1.31, 1.11–1.54) or CVD mortality (NCEP: 1.79, 1.35–2.37; NHLBI–AHA: 1.67, 1.27–2.20) between definitions. By contrast, in cross-sectional analyses Skilton et al. (2006) found sex-specific associations between MetS and carotid IMT; however, overall, in both men and women, MetS as defined by the original NCEP criteria was a modestly stronger predictor of carotid atherosclerosis than NHLBIa˜ AHA MetS. #
2007 NRC Canada
Ardern and Janssen
NCEP vs. IDF To date there have been 3 notable studies (Katzmarzyk et al. 2006; Sone et al. 2006; Hanley et al. 2005) that have compared the NCEP and International Diabetes Federation (IDF; Alberti et al. 2005) MetS definitions in prospective analyses. In the first, results from Aerobics Centre Longitudinal Study men (Katzmarzyk et al. 2006) indicate no substantive differences in prediction of all-cause (NCEP: 1.36, 1.14–1.62; IDF: 1.26, 1.07–1.49) or CVD mortality (NCEP: 1.79, 1.35–2.37; IDF: 1.67, 1.27–2.20), according to MetS criteria. In the second, Sone et al. (2006) also reported similar relative risk estimates for NCEP and IDF MetS for incident CVD in diabetics from the Japan Diabetes Complications Study. In the third, using data from 822 participants in the Insulin Resistance Atherosclerosis Study (40–69 y), Hanley et al. (2005) reported that the adjusted odds ratios for incident T2DM over an average of 5.2 y of follow-up were only slightly higher using the NCEP (4.14, 2.79–6.16) than using the IDF (3.40, 2.28–5.06) MetS definition. Finally, the above results are consistent with a crosssectional analysis of 6780 participants in the Multi-Ethnic Study of Atherosclerosis (45–84 y) wherein the adjusted relative risks for the presence of aortic valve calcium and diabetes showed no significant difference between IDF- and NCEP-defined MetS (Katz et al. 2006). Thus, based on the available evidence, it appears that there are few differences in the magnitude of prediction of morbidity and mortality associated with NCEP- and IDF-defined MetS, and that the greatest prognostic differences between NCEP and IDF are likely to be in ethnic groups in which the suggested WC threshold varies considerably from that of the US NCEP (M: 102 cm; F: 88 cm) (Lorenzo et al. 2006).
Do all MetS components contribute equally to morbidity and mortality risk? The NCEP, WHO, and IDF definitions of the MetS all weight each risk factor component equally. However, the results from several studies indicate that some of the MetS components have a far greater impact on morbidity and mortality risk than others. For example, Hunt et al. (2004) found that the presence of high fasting glucose was a stronger predictor of all-cause and CVD mortality than the other MetS components among 2 815 participants of the San Antonio Heart Study. A second prospective cohort study of 2089 black and white middle-aged individuals found that only high blood pressure and low HDL cholesterol were significant predictors of CAD when all 5 of the NCEP MetS components were included in the same multivariate prediction model (McNeill et al. 2005). A third prospective cohort study of 2484 men and women aged 50–75 y reported that obesity and high blood pressure in men and high blood pressure and HDL cholesterol in women were far better predictors of CVD events than were other MetS components in multivariate models (Girman et al. 2005). Finally, in a prospective cohort study of 3 128 angiography patients, the ability of MetS to predict new CAD events was carried primarily through high fasting glucose and low HDL cholesterol (Anderson et al. 2004). There is also compelling evidence that the hypertriglyceridemic waist (HTW), a combination of high waist circumfer-
39
ence (‡90 cm) and elevated triglycerides (‡2.0 mmol/L) in men, may be used as a simple tool for the identification of an atherogenic metabolic triad (hyperapolipoprotein B, small dense LDL-C particles, and hyperinsulinemia) that is difficult to measure in clinical practice (Lemieux et al. 2000). To this end, the HTW phenotype is associated with elevated odds of CAD in men (Lemieux et al. 2000), and predictive of coronary risk factors in women (LaMonte et al. 2003). Moreover, in a study by St-Pierre and colleagues (2002) that compared normoglycemic men and those with impaired fasting glucose (IFG) also stratified their analysis by the presence or absence of HTW. The results of this study suggested that, compared with normoglycemic/no HTW (odds ratio = 1.00) men, the odds of having CAD by coronary angiography were no different in the IFG/no HTW men (1.6, 0.4–5.8), but significantly elevated in both normoglycemic/ HTW (5.4, 3.1–9.3) and IFG/HTW men (8.5, 3.5–2.04). Given that only a small number of men were classified into the IFG/no HTW group (n = 11) it is also clear that the HTW is associated with glucose dysregulation, as intended. Although we are not aware of any studies that allow the direct comparison of the added value of each additional component to the HTW phenotype, the results of Wilson et al. (2005) suggest similar relative risk of CAD if glucose, blood pressure, or HDL-C components are present with elevated triglycerides and waist circumference, by comparison to all other combinations of 3 MetS components defined by NCEP criteria. In a recent study Macchia et al. (2006) developed a diagnostic score for MetS, which was aimed at predicting T2DM by weighting each of the NCEP MetS components. Furthermore, each MetS component was broken down into 3 to 5 categories, as apposed to a binary ‘‘yes or no’’ outcome as considered in current MetS diagnostic criteria. The diagnostic score was developed using a sample of 7 468 patients with a history of myocardial infarction. The patients were followed for 3.5 years, during which time 940 developed T2DM. The statistical approach employed in this study was akin to that used to generate the global Framingham CAD Risk Score, in that points for each risk factor category were assigned and these points were weighted proportionately to the value of the coefficients of the multivariate analysis (Wilson et al. 1998). Similar to the Framingham approach, measures of age and sex were also included in the prediction model, and because measures of waist circumference were not available, BMI was used as a surrogate. The final diabetes prediction model is shown in Table 2 – the more risk factor points the greater the risk. There was a substantial difference in the weighting of the MetS components, which translated into differences in the risk factor points allocated. Given that this diagnostic score was developed to predict T2DM, it is not surprising that the risk factor points allocated for fasting glucose were far greater than the risk factor points allocated for the other MetS components. The results from these aforementioned studies raise the question as to why all components of the MetS are weighted equally. Additional research is required to determine if a weighting system should be used when diagnosing the MetS wherein some risk factor components are given more emphasis than others. With that being said, the appropriate weights for a weighted score will likely vary by outcome #
2007 NRC Canada
40
Appl. Physiol. Nutr. Metab. Vol. 32, 2007
Table 2. Diabetes diagnostic score derived using NCEP MetS components. Risk factor
Diabetes risk points
Gender Female Male
0 3
Age (y) £50 >50
0 4
Hypertension No Yes
0 2
Body mass index (kg/m2)
