Diagnosis and Management of the Metabolic Syndrome

Grundy, Scott M.; Cleeman, James I.; Daniels, Stephen R.; Donato, Karen A.; Eckel, Robert H.; Franklin, Barry A.; Gordon, David; Krauss, Ronald M.; Savage, Peter J.; Smith, Sidney C.; Spertus, John A.; Costa, Fernando

doi:10.1161/circulationaha.105.169404

Cited by 9,874 publications

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“…The recent AHA/NHLBI Scientific Statement on Metabolic Syndrome [90,91] as well as the ATP III emphasize as the primary target, LDL, a marker that is not considered a feature of MetS and that may not even be high in many patients with MetS. Whereas nutritional recommendations are quite general (reduce weight, increase exercise), these reports emphasize a low fat diet (although limiting simple sugars).…”

Section: Discussionmentioning

confidence: 99%

“…In practical terms, a recommendation to reduce saturated fat on low CHO diets might be more helpful than blanket prohibition. In addition, the AHA/NHLBI report [90] presents the rationale for low CHO as the effect on appetite. Whereas this may be a component, it has been stated many times, and is part of basic biochemical education [16,93-96], that the rationale of CHO restriction is the control of metabolism by insulin regulation.…”

Section: Discussionmentioning

confidence: 99%

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Carbohydrate restriction improves the features of Metabolic Syndrome. Metabolic Syndrome may be defined by the response to carbohydrate restriction

2005

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Metabolic Syndrome (MetS) represents a constellation of markers that indicates a predisposition to diabetes, cardiovascular disease and other pathologic states. The definition and treatment are a matter of current debate and there is not general agreement on a precise definition or, to some extent, whether the designation provides more information than the individual components. We consider here five indicators that are central to most definitions and we provide evidence from the literature that these are precisely the symptoms that respond to reduction in dietary carbohydrate (CHO). Carbohydrate restriction is one of several strategies for reducing body mass but even in the absence of weight loss or in comparison with low fat alternatives, CHO restriction is effective at ameliorating high fasting glucose and insulin, high plasma triglycerides (TAG), low HDL and high blood pressure. In addition, low fat, high CHO diets have long been known to raise TAG, lower HDL and, in the absence of weight loss, may worsen glycemic control. Thus, whereas there are numerous strategies for weight loss, a patient with high BMI and high TAG is likely to benefit most from a regimen that reduces CHO intake. Reviewing the literature, benefits of CHO restriction are seen in normal or overweight individuals, in normal patients who meet the criteria for MetS or in patients with frank diabetes. Moreover, in low fat studies that ameliorate LDL and total cholesterol, controls may do better on the symptoms of MetS. On this basis, we feel that MetS is a meaningful, useful phenomenon and may, in fact, be operationally defined as the set of markers that responds to CHO restriction. Insofar as this is an accurate characterization it is likely the result of the effect of dietary CHO on insulin metabolism. Glucose is the major insulin secretagogue and insulin resistance has been tied to the hyperinsulinemic state or the effect of such a state on lipid metabolism. The conclusion is probably not surprising but has not been explicitly stated before. The known effects of CHO-induced hypertriglyceridemia, the HDL-lowering effect of low fat, high CHO interventions and the obvious improvement in glucose and insulin from CHO restriction should have made this evident. In addition, recent studies suggest that a subset of MetS, the ratio of TAG/HDL, is a good marker for insulin resistance and risk of CVD, and this indicator is reliably reduced by CHO restriction and exacerbated by high CHO intake. Inability to make this connection in the past has probably been due to the fact that individual responses have been studied in isolation as well as to the emphasis of traditional therapeutic approaches on low fat rather than low CHO.We emphasize that MetS is not a disease but a collection of markers. Individual physicians must decide whether high LDL, or other risk factors are more important than the features of MetS in any individual case but if MetS is to be considered it should be recognized that reducing CHO will bring improvement. Response of symptoms to CHO ...

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Carbohydrate restriction improves the features of Metabolic Syndrome. Metabolic Syndrome may be defined by the response to carbohydrate restriction

2005

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“…MetS is traditionally classified on the basis of criteria such as those of the Adult Treatment Panel III 15. MetS can also be assessed using a MetS severity Z score, which was formulated according to how the 5 individual components correlate together on a sex and racial/ethnic basis 16, 17.…”

Section: Introductionmentioning

confidence: 99%

Assessing Baseline and Temporal Changes in Cardiometabolic Risk Using Metabolic Syndrome Severity and Common Risk Scores

Gurka

Filipp

Pearson

et al. 2018

JAHA

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BackgroundType 2 diabetes mellitus (T2DM) is considered a cardiovascular disease (CVD) risk equivalent, thereby linking assessment of cardiometabolic risk with that of CVD risk over time. Our goal was to determine how commonly used CVD risk scores and metabolic syndrome (MetS) severity performed in predicting T2DM with and without ultimate CVD.Methods and ResultsWe assessed data from 8273 participants of the ARIC (Atherosclerosis Risk in Communities) Study, using the pooled cohort atherosclerotic CVD risk score, the Framingham Risk Score, and a MetS severity Z score to assess their association with future risk for CVD alone, T2DM alone, or both over 20 years of follow‐up. Baseline levels of all scores were significantly associated with isolated incident T2DM (odds ratios [ORs] for each 1‐SD increase: atherosclerotic CVD=1.7, Framingham risk score=1.7, MetS Z score=5.1). All 3 baseline scores were also significantly associated with isolated incident CVD (atherosclerotic CVD OR=2.4, Framingham risk score OR=2.3, MetS Z‐score OR=1.8), with the 2 CVD scores remaining significant independent of MetS severity. MetS severity was strongly associated with future T2DM leading to CVD (MetS Z‐score OR=7.0, atherosclerotic CVD OR=3.9, Framingham risk score OR=3.5). Furthermore, changes in MetS severity were independently associated with future T2DM‐CVD progression.Conclusions CVD risk scores are associated with risk for future isolated T2DM in addition to isolated CVD. However, MetS severity (both baseline and changes over time) was more strongly associated with T2DM, including T2DM ultimately leading to CVD. Following MetS severity within patients over time may identify those at greatest risk of combined cardiometabolic disease.

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“…Consequently, it remains unclear as to whether, over time, psychopathology impairs components of the metabolic syndrome, or vice versa. Each direction is biologically plausible, since the development and progression of both psychopathology and metabolic dysregulation are associated with a range of detrimental biological processes, including altered autonomic and neuroendocrine stress functioning, low grade inflammation, cellular aging, and oxidative and nitrosative damage 16, 17, 18. Thus, the pathophysiology of psychopathology may increase the risk of metabolic dysregulation, and vice versa.…”

Section: Introductionmentioning

confidence: 99%

Bidirectional Prospective Associations of Metabolic Syndrome Components With Depression, Anxiety, and Antidepressant Use

et al. 2016

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BackgroundMetabolic syndrome components—waist circumference, high‐density lipoprotein cholesterol (HDL‐C), triglycerides, systolic blood pressure and fasting glucose—are cross‐sectionally associated with depression and anxiety with differing strength. Few studies examine the relationships over time or whether antidepressants have independent effects.MethodsParticipants were from the Netherlands Study of Depression and Anxiety (NESDA; N = 2,776; 18–65 years; 66% female). At baseline, 2‐ and 6‐year follow‐up, participants completed diagnostic interviews, depression and anxiety symptom inventories, antidepressant use assessment, and measurements of the five metabolic syndrome components. Data were analyzed for the consistency of associations between psychopathology indicators and metabolic syndrome components across the three assessment waves, and whether psychopathology or antidepressant use at one assessment predicts metabolic dysregulation at the next and vice versa.ResultsConsistently across waves, psychopathology was associated with generally poorer values of metabolic syndrome components, particularly waist circumference and triglycerides. Stronger associations were observed for psychopathology symptom severity than diagnosis. Antidepressant use was independently associated with higher waist circumference, triglycerides and number of metabolic syndrome abnormalities, and lower HDL‐C. Symptom severity and antidepressant use were associated with subsequently increased number of abnormalities, waist circumference, and glucose after 2 but not 4 years. Conversely, there was little evidence that metabolic syndrome components were associated with subsequent psychopathology outcomes.ConclusionsSymptom severity and antidepressant use were independently associated with metabolic dysregulation consistently over time and also had negative consequences for short‐term metabolic health. This is of concern given the chronicity of depression and anxiety and prevalence of antidepressant treatment.

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Diagnosis and Management of the Metabolic Syndrome

Cited by 9,874 publications

References 173 publications

Carbohydrate restriction improves the features of Metabolic Syndrome. Metabolic Syndrome may be defined by the response to carbohydrate restriction

Carbohydrate restriction improves the features of Metabolic Syndrome. Metabolic Syndrome may be defined by the response to carbohydrate restriction

Assessing Baseline and Temporal Changes in Cardiometabolic Risk Using Metabolic Syndrome Severity and Common Risk Scores

Bidirectional Prospective Associations of Metabolic Syndrome Components With Depression, Anxiety, and Antidepressant Use

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