Annals
Established in 1927 by the American College of Physicians
:
Advanced search
box Article
 arrow  Table of Contents                
space
 arrow  Abstract of this article Free
space
 arrow  PDF of this article
space
 arrow  Summary for Patients
space
 arrow  Summary for Patients (PDF)
space
 arrow  Figures/Tables List
space
 arrow  Related articles in Annals
space
 arrow  Articles citing this article
space
box Services
 arrow  Send comment/rapid response letter
space
 arrow  Published comments/rapid response letters
space
 arrow  Notify a friend about this article
space
 arrow  Alert me when this article is cited
space
 arrow  Add to Personal Archive
space
 arrow  Download to Citation Manager
space
 arrow  ACP Search
space
 arrow  Get Permissions
space
box Google Scholar
 arrow  Search for Related Content
space
box Social Bookmarking
 Add to CiteULike Add to Complore Add to Connotea Add to Del.icio.us Add to Digg Add to Facebook Add to Reddit Add to Technorati Add to Twitter
What's this?
box PubMed
Articles in PubMed by Author:
 arrow  Orchard, T. J.
space
 arrow  Related Articles in PubMed
space
 arrow  PubMed Citation
space
 arrow  PubMed
space

ARTICLE

The Effect of Metformin and Intensive Lifestyle Intervention on the Metabolic Syndrome: The Diabetes Prevention Program Randomized Trial

right arrow Trevor J. Orchard, MD; Marinella Temprosa, MS; Ronald Goldberg, MD; Steven Haffner, MD; Robert Ratner, MD; Santica Marcovina, PhD, DSc; Sarah Fowler, PhD, for the Diabetes Prevention Program Research Group

19 April 2005 | Volume 142 Issue 8 | Pages 611-619

Background: The metabolic syndrome is a high-risk state for diabetes and cardiovascular disease. Little is known about its prevalence and prevention in those with impaired glucose tolerance.

Objective: To determine the prevalence of the metabolic syndrome at baseline in the Diabetes Prevention Program and the effect of intensive lifestyle intervention and metformin therapy on the syndrome's incidence and resolution.

Design: Randomized, controlled clinical trial.

Setting: Research and community-based centers.

Participants: Participants had impaired glucose tolerance (World Health Organization criteria plus fasting plasma glucose level ≥5.3 mmol/L [≥95 mg/dL]) and were followed for a mean of 3.2 years after random assignment to intensive lifestyle intervention, metformin therapy, or placebo.

Interventions: Metformin, 850 mg twice daily, or intensive lifestyle intervention designed to achieve and maintain a 7% weight loss and 150 minutes of exercise per week.

Measurements: The metabolic syndrome was defined as having 3 or more characteristics (waist circumference; blood pressure; and levels of high-density lipoprotein cholesterol, triglycerides, and fasting plasma glucose) that met criteria from the National Cholesterol Education Program Adult Treatment Panel III.

Results: Fifty-three percent of participants (n = 1711) had the metabolic syndrome at baseline; incidence did not vary substantially by age. However, low levels of high-density lipoprotein cholesterol predominated in younger participants (age 25 to 44 years), and high blood pressure predominated in older participants (age 60 to 82 years). In life-table analyses (log-rank test), incidence of the metabolic syndrome was reduced by 41% in the lifestyle group (P < 0.001) and by 17% in the metformin group (P = 0.03) compared with placebo. Three-year cumulative incidences were 51%, 45%, and 34% in the placebo, metformin, and lifestyle groups, respectively. There was no significant heterogeneity by ethnic group.

Limitations: The study involved a volunteer group with impaired glucose tolerance, which limits generalizability.

Conclusions: The metabolic syndrome affected approximately half of the participants in the Diabetes Prevention Program at baseline. Both lifestyle intervention and metformin therapy reduced the development of the syndrome in the remaining participants.



Editors' Notes
space
up arrowTop
dotEditors' Notes
down arrowMethods
down arrowResults
down arrowDiscussion
down arrowAuthor & Article Info
down arrowReferences

Context

  • Intensive diet and exercise or metformin can prevent the development of diabetes in individuals with impaired fasting glucose, but the effects of these interventions on development of the metabolic syndrome are unknown.

Contribution

  • This secondary analysis of Diabetes Prevention Program data showed that lifestyle intervention and metformin each reduced the development of the metabolic syndrome among the 45% of participants who did not have it at baseline. The impact of lifestyle intervention was much more marked than that of metformin.

Implications

  • Interventions that prevent diabetes will also reduce the development of the metabolic syndrome.

–The Editors

 

Considerable attention has recently been paid to the metabolic syndrome, a constellation of risk factors associated with insulin resistance and increased cardiovascular and diabetes risk. The third report of the National Cholesterol Education Program's Adult Treatment Panel now calls for the identification and treatment of this high-risk state and provides a simple set of criteria for diagnosis (1). The World Health Organization (WHO) and the American College of Endocrinology have also provided definitions (2). Although recent studies have provided estimates of the prevalence of the metabolic syndrome in the United States (3, 4), its interrelationship with impaired glucose tolerance is unclear. In particular, it is largely unknown what proportion of participants with impaired glucose tolerance have the metabolic syndrome and whether this varies by ethnicity, age, and sex. Clearly, because an elevated blood glucose level is a common criterion for all definitions, a close association is to be expected. This association may be even stronger in the subgroup of persons with both impaired glucose tolerance and impaired fasting glucose (that is, a fasting plasma glucose level 6.1 to 6.9 mmol/L [110 to 125 mg/dL]). The extent to which we may be able to reduce cardiovascular risk in patients with impaired glucose tolerance by preventing the metabolic syndrome through lifestyle or medication interventions is also unknown.

The Diabetes Prevention Program (5, 6) provides a unique opportunity to begin to address these issues. It involves a large sample of more than 3000 participants with impaired glucose tolerance who were carefully followed and randomly allocated to treatment with an intensive lifestyle intervention, metformin, or placebo. In this report, we address 2 questions: the prevalence of the metabolic syndrome at baseline in the trial population (and how this varies by age and sex) and whether the 2 interventions reduced the incidence of new cases of the metabolic syndrome or increased resolution of existing cases compared with placebo.


Methods
space
up arrowTop
up arrowEditors' Notes
dotMethods
down arrowResults
down arrowDiscussion
down arrowAuthor & Article Info
down arrowReferences

Participants and Procedures

Full details of the protocol have been published elsewhere (5, 6). The current report includes 3234 participants seen at baseline. This number includes participants from the 3 treatment arms investigated (that is, standard lifestyle or placebo, intensive lifestyle, and metformin), but not participants from the troglitazone arm, which was discontinued. Individuals were recruited between June 1996 and May 1999 from a variety of sources, including community screenings and household mailings, on the basis of perceived risk for diabetes. Written informed consent was obtained from all participants before screening, consistent with the Declaration of Helsinki and the guidelines of each center's institutional review board.

The initial screening step consisted of a fasting glucose measurement. If the participant was eligible, this was followed by a 75-g oral glucose tolerance test. Inclusion criteria were as follows: a fasting plasma glucose level of 5.3 to 7.0 mmol/L (95 to 125 mg/dL) (≥7.0 mmol/L [≥125 mg/dL] for Native Americans); a 2-hour plasma glucose level of 7.8 to 11.1 mmol/L (140 to 199 mg/dL) following the glucose load; age of at least 25 years; and body mass index of at least 24 kg/m2 (≥22 kg/m2 for Asian Americans because of differences in body size in this group). Main exclusion criteria were recent myocardial infarction, symptoms of coronary heart disease, major illness, previous diagnosis of diabetes, use of medications known to impair glucose tolerance, or triglyceride level of at least 6.8 mmol/L (≥600 mg/dL), as previously detailed (5). Standardized interviewer-administered questionnaires were used to obtain self-reported data on personal medical history, medications, and diet. Self-reported race or ethnicity was classified according to the question used in the 1990 U.S. Census questionnaire (7). Overall, adiposity was assessed by body mass index. Waist circumference was assessed in the standing position midway between the highest point of the iliac crest and the lowest point of the costal margin in the mid-axillary line. All anthropometric measures reflected the average of 2 measurements. Blood pressure was measured twice at 30-second intervals by using a standard mercury manometer. The participant was seated in a chair for 5 minutes before the first measurement was taken, and the mean of the 2 readings was used in the analyses.

The metabolic syndrome was defined according to criteria from the National Cholesterol Education Program's Adult Treatment Panel III (1), namely 3 or more of the following conditions: waist circumference greater than 102 cm in men and greater than 88 cm in women; serum triglyceride level of at least 1.7 mmol/L (≥150 mg/dL); high-density lipoprotein (HDL) cholesterol level less than 1.03 mmol/L (<40 mg/dL) in men and less than 1.3 mmol/L (<50 mg/dL) in women; blood pressure of 130/85 mm Hg or greater; and fasting plasma glucose level of 6.2 mmol/L (110 mg/dL).

Participants who were being treated with blood pressure–lowering or triglyceride-lowering medications (niacin or fibric acid derivatives) were classified as positive for the respective criterion. We chose the Adult Treatment Panel III (1) criteria because they are commonly used in the United States and are simpler to apply in clinical practice than, for example, the WHO criteria (2).

Participants were randomly assigned to receive 1 of 3 interventions: standard lifestyle recommendations plus metformin, 850 mg twice per day; standard lifestyle recommendations plus placebo; or an intensive program of lifestyle intervention. The randomization was done centrally by computer; assignments to the lifestyle group were blinded until randomization, while assignments to the medication groups were blinded until the end of the study. The goals of the lifestyle program were to achieve and maintain a weight reduction of at least 7% of clinical body weight through a healthy low-calorie, low-fat diet and to engage in physical activity of moderate intensity, such as brisk walking, for at least 150 minutes per week. Participants were seen quarterly, when blood pressure was assessed. Fasting glucose levels were determined at the 6-month visits, and fasting lipid levels and waist circumference were measured annually. Further details have been published elsewhere (5, 6). Figure 1 shows the number of participants observed at each annual examination by treatment group.



View larger version (40K):
[in this window]
[in a new window]
 
Figure 1. Randomly assigned participants by treatment group and annual visit.

 

Laboratory Methods

All of the analytic measurements were performed at the central biochemistry laboratory (Northwest Lipid Research Laboratories, University of Washington, Seattle, Washington). Fasting plasma glucose level was measured on a chemistry autoanalyzer by the glucokinase method. Insulin measurements were performed by using a polyethylene glycol–accelerated double antibody radioimmunoassay method developed in the Diabetes Endocrinology Research Center Immunoassay Core Laboratory (University of Washington, Seattle, Washington). This method is based on the use of an anti–human insulin guinea pig antibody and measures total immunoreactive insulin. The homeostasis model assessment for insulin resistance was calculated as follows (8):



{9MM1}

(1)

Measurements of total plasma cholesterol and triglycerides were performed enzymatically on a chemistry autoanalyzer by using methods standardized to the Centers for Disease Control and Prevention reference methods (9). We obtained HDL fractions for cholesterol analysis by treating whole plasma with dextran sulfate magnesium chloride to precipitate all of the apolipoprotein B–containing lipoproteins (10). We calculated low-density lipoprotein cholesterol by using the Friedewald equation (11). In participants with triglyceride levels higher than 4.5 mmol/L (>400 mg/dL), the lipoprotein fractions were separated by using preparative ultracentrifugation of plasma by beta quantification (12).

Statistical Analyses

Participants were followed for an average of 3.2 years (range, 0.04 to 5.0 years) from the start of the study in June 1996 through 31 July 2001, a period 4 months longer than that reported previously (5). This period was chosen to maximize the available data that were collected during the masked phase of the Diabetes Prevention Program, since unmasking occurred in early August 2001.

Random treatment assignments were stratified according to clinical center and were generated by the coordinating center through computer linkup to the field center at time of randomization. Therefore, assignment was unknown until randomization. Assignments to metformin and placebo were double-blinded. The study design and analysis followed the intention-to-treat principle. Nominal (unadjusted) P values and confidence intervals are reported. Logistic regression was used to compare the prevalence of the metabolic syndrome and its components at baseline among the demographic variables. The time to the outcome was assessed by using life-table methods (13). Modified product-limit curves for the cumulative incidence of the metabolic syndrome and for its resolution were compared by using the log-rank test. The estimated cumulative incidence, or resolution, at 3 years and the risk reduction, heterogeneity among strata, and interactions between treatment assignments and covariates were assessed by using proportional-hazards regression. Fixed-effects models with the assumption of normally distributed errors (14) were used to assess differences over time in body weight and in plasma glucose and glycosylated hemoglobin values among the 3 groups.

Role of the Funding Sources

The Diabetes Prevention Program was principally supported by the National Institute for Diabetes and Digestive and Kidney Diseases and other components of the National Institutes of Health and the Centers for Disease Control and Prevention. Representatives of the National Institutes of Health and the Centers for Disease Control and Prevention participated in the design of the study and in the reporting of the results. Although additional funding was provided by a variety of other sources, as listed in the acknowledgments, these sources had no role in the design or conduct of the study or in the reporting of results.


Results
space
up arrowTop
up arrowEditors' Notes
up arrowMethods
dotResults
down arrowDiscussion
down arrowAuthor & Article Info
down arrowReferences

Baseline Prevalence

Table 1 shows the prevalence of the metabolic syndrome and each of its components in the 3234 participants examined at baseline. Fifty-three percent of the participants (n = 1711) fulfilled the criteria for the metabolic syndrome; this proportion was relatively constant by age group. However, significant differences by age group (<45 years, 45 to 59 years, and ≥60 years) emerged for the separate components of the syndrome. Prevalence of low HDL cholesterol level ranged from 70% in those 25 to 44 years of age to only 40% in those age 60 years or older. Increased waist circumference, the most common component in all age groups, was present in 82% of those younger than 45 years of age, 78% of those 45 to 59 years of age, and 73% of those at least 60 years of age. High triglyceride levels (present in 46% of all participants) varied little by age, while high fasting plasma glucose level, whose prevalence ranged from 31% to 35%, was more common in the older age groups. High blood pressure was also more prevalent in older participants, doubling from 31% in those younger than age 45 years to more than 60% in those 60 to 82 years of age. Prevalence of the components also varied by sex: Women more frequently had increased waist circumference and low HDL cholesterol levels, while men more frequently had high triglyceride levels, high fasting blood glucose levels, and hypertension. (It should be noted that the National Cholesterol Education Program has different criteria for waist circumference and HDL level for each sex.) Although significant ethnic variation was also seen, it could not be clearly separated from the differing entry criteria used for different ethnic groups. For example, the metabolic syndrome was least prevalent in Asian Americans (41%) and in Native Americans (46%), groups who had lower thresholds for BMI and fasting glucose level, respectively, at study entry. Finally, if the criterion of more than 5.6 mmol/L (>100 mg/dL) were used for fasting glucose level instead of 6.2 mmol/L (110 mg/dL), the overall prevalence at baseline would have been 69% (2223 of 3234) rather than the 53% noted earlier. The interrelationship of the components of the metabolic syndrome is shown in the Appendix Figure.


View this table:
[in this window]
[in a new window]
 
Table 1. Prevalence of the Metabolic Syndrome and Its Components by Age and Sex in the Diabetes Prevention Program

 


View larger version (37K):
[in this window]
[in a new window]
 
Appendix Figure. Venn diagram of the components of the metabolic syndrome.{webonly} Numbers are numbers of participants at baseline. The shaded sections represent participants meeting the metabolic syndrome criteria as defined by the National Cholesterol Education Program Adult Panel II. BP = blood pressure; HDL-C = high-density lipoprotein cholesterol; TG = triglyceride.

 

The severity of the metabolic syndrome, in terms of the number of positive criteria (mean, 2.6), did not differ by treatment group, sex, or age. No differences were seen among the treatment groups in the prevalence of the metabolic syndrome or of its components at baseline, except for low HDL cholesterol level (P = 0.01), which was more prevalent in the placebo group than in the metformin and lifestyle groups (60.4%, 54.3%, and 55.8%, respectively). The prevalence of high triglyceride levels was also marginally higher (P = 0.06) in the placebo group than in the metformin and lifestyle groups (48.6%, 44.0%, and 44.2%, respectively).

Baseline Correlations

Table 2 shows the correlations (Spearman rank) among the different components of the metabolic syndrome at baseline after adjustment for age, sex, and ethnicity. Also shown are the correlations with the homeostasis model assessment score for insulin resistance. Apart from the anticipated high correlation between systolic and diastolic blood pressure (r = 0.60) and between triglyceride level and HDL cholesterol level (r = –0.39), other major correlations were those between homeostasis model assessment for insulin resistance and 1) waist circumference (r = 0.44), 2) HDL cholesterol level (r = –0.31), and 3) fasting plasma glucose level (r = 0.31).


View this table:
[in this window]
[in a new window]
 
Table 2. Baseline Spearman Partial Correlations of Metabolic Syndrome Risk Factors and Homeostasis Model Assessment Score for Insulin Resistance Adjusted for Age, Sex, and Ethnicity

 

Incidence of the Metabolic Syndrome among Participants without the Syndrome at Baseline

Figure 2 separately shows the cumulative incidence of the metabolic syndrome by time since randomization for the 3 intervention groups after exclusion of baseline cases. The incidence is highest in the placebo group. By 3 years, 53% of the participants in the placebo group (260 of 490) had acquired the metabolic syndrome compared with 47% (236 of 503) in the metformin group and 38% (201 of 530) in the lifestyle group. The cumulative incidence overall (per 100 person-years) was 61% for the placebo group, 50% for the metformin group, and 38% for the lifestyle group. In a proportional hazards analysis, lifestyle intervention yielded a reduction of 41% (95% CI, 28% to 52%) in incidence of the metabolic syndrome compared with placebo (P < 0.001) and a significant 29% (CI, 13% to 42%) reduction compared with metformin (P < 0.001), which itself yielded a 17% (CI, 0% to 31%) lower incidence than placebo (P = 0.03). Redefining the metabolic syndrome by using the criterion of a glucose level greater than 110 mg/dL (>6.2 mmol/L) yielded very similar results. Three-year incidences were 40%, 33%, and 27% for the placebo, metformin, and lifestyle groups, respectively. No major adverse events were noted, but musculoskeletal problems were more common in the lifestyle group and gastrointestinal symptoms were more common in the metformin group and less common in the lifestyle group than in the group receiving placebo.



View larger version (15K):
[in this window]
[in a new window]
 
Figure 2. Development of the metabolic syndrome by intervention group in the Diabetes Prevention Program.

 

We also examined whether the efficacy of the 2 interventions differed by age, sex, ethnicity, or baseline fasting insulin level. Lifestyle intervention was least effective in those 25 to 44 years of age. Lifestyle intervention was effective compared with placebo in both men and women (P < 0.001), but more so in men (64% vs. 37%) (P = 0.02 for heterogeneity). Metformin was not effective compared with placebo in women (P > 0.2) but was effective in men (P = 0.002), again demonstrating significant heterogeneity (P = 0.02). Although numbers became too small for definitive results when divided according to ethnicity, it appears that risk reduction compared with placebo was greater for the lifestyle group than for the metformin group in both white persons (50% vs. 12%, respectively) and Hispanic persons (57% vs. 2%, respectively). In African Americans (42% vs. 29%) and Native Americans (43% vs. 42%), efficacy for the lifestyle group and the metformin group appeared more similar, while for Asian Americans, metformin showed a nonsignificantly greater reduction than intensive lifestyle intervention (62% vs. 30%). The efficacy of neither lifestyle nor metformin showed significant heterogeneity across the 5 ethnic groups. Finally, although lifestyle was effective compared with placebo regardless of baseline fasting insulin level, metformin showed significant heterogeneity (P = 0.03). Metformin was most effective in participants with a fasting insulin level of 136 pmol/L or less and had no effect in those with fasting insulin levels of 144 to 215 pmol/L or greater than 125 pmol/L compared with placebo.

Incidence of Metabolic Syndrome Components among Participants Not Meeting Criteria at Baseline

To examine the effect of the interventions on individual components, life-table analyses were performed for those who did not met the criteria at baseline. The incidence of specific components over time compared with placebo suggests that lifestyle reduces the incidence of all components except HDL cholesterol level, while metformin is effective only in reducing the incidence of waist circumference and fasting glucose level (Table 3).


View this table:
[in this window]
[in a new window]
 
Table 3. Three-Year Incidence and Prevalence of Metabolic Syndrome Components among Diabetes Prevention Program Participants by Treatment Group

 

Resolution of the Metabolic Syndrome among Participants Who Had the Syndrome at Baseline

Figure 3 shows the cumulative incidence of resolution of the metabolic syndrome (that is, no longer meeting the criteria) by treatment group. Although the pattern is somewhat similar to that seen for incidence of the metabolic syndrome, with the best result at 3 years occurring in the lifestyle group and an intermediary effect noted for metformin, the differences are less striking. By the log-rank test, only lifestyle showed a significant effect compared with placebo (P = 0.002). Nevertheless, prevalence at 3 years did vary significantly by treatment group (P < 0.001): Eighteen percent of the placebo group, 23% of the metformin group, and 38% of the lifestyle group no longer had the syndrome.



View larger version (15K):
[in this window]
[in a new window]
 
Figure 3. Resolution of the metabolic syndrome by intervention group in the Diabetes Prevention Program.

 

Prevalence of Metabolic Syndrome Components among Participants Meeting Criteria at Baseline

Also shown in Table 3 is the effect of the interventions on each component among participants who met the specific component criterion at baseline. A slightly different pattern emerges, that is, both interventions decreased the prevalence of low levels of HDL cholesterol, increased waist circumference, and fasting glucose level, while intensive lifestyle intervention also lowered the prevalence of increased blood pressure and triglyceride levels.

Prevalence of the Metabolic Syndrome in All Participants at 3 Years

The prevalence of the metabolic syndrome in all participants increased from 55% at baseline to 61% after 3 years in the placebo group (P = 0.003) and from 54% to 55% in the metformin group (P > 0.2). In the lifestyle group, overall prevalence decreased from 51% to 43% (P < 0.001).


Discussion
space
up arrowTop
up arrowEditors' Notes
up arrowMethods
up arrowResults
dotDiscussion
down arrowAuthor & Article Info
down arrowReferences

These data provide further evidence of the potential benefit of the Diabetes Prevention Program interventions beyond diabetes prevention alone and raise the additional possibility of cardiovascular prevention. Although we are unaware of any publications specifically examining the prevalence of the metabolic syndrome in patients with impaired glucose tolerance, a recent analysis of the data set from the Third National Health and Nutrition Examination Survey (NHANES III) suggests that 33% of U.S. adults who are 50 years of age or older and have impaired glucose tolerance also have the metabolic syndrome (4). Our overall prevalence of 53% is probably higher, even allowing for our additional requirement of a fasting plasma glucose level of at least 5.3 mmol/L (≥95 mg/dL). Several reports have also documented the general prevalence of this syndrome by using either the Adult Treatment Panel III criteria (1) used in the current report or the WHO definitions (2). Ford and colleagues (3) recently estimated from NHANES III that the metabolic syndrome was present in approximately 22% of all U.S. adults age 20 years and older. Of interest, unlike our data, which showed a relatively constant prevalence by age group, the age-specific prevalence of the metabolic syndrome in the general population increased dramatically, from just over 12% among individuals in their thirties to 20% among those in their forties, 35% among those in their fifties, and 45% thereafter. Again, it would seem that our population, as expected, has a higher prevalence of the metabolic syndrome and presumably higher cardiovascular and diabetes risk than the general population. However, it should be noted that our population is highly selected for having impaired glucose tolerance but not diabetes. One might thus anticipate a less marked prevalence relationship with age in the Diabetes Prevention Program, since we would be increasingly eliminating participants with the metabolic syndrome who have also developed diabetes as they age. The NHANES data from Ford and colleagues (3) also examined prevalence by sex and, as in our population, showed little difference overall. The American Diabetes Association recently redefined prediabetes by using a fasting plasma glucose criterion (15) of greater than 5.6 mmol/L (>100 mg/dL). As anticipated, this increased the prevalence of the condition but had little effect on the relative impact of the interventions on incidence.

Prevalence studies that have examined the association of the metabolic syndrome with cardiovascular disease generally support the syndrome's identification and prevention. The Bruneck study (16), for example, reported that participants with the WHO definition of the metabolic syndrome had an increased risk for both carotid and coronary disease after 5 years of follow-up. Alexander and associates' analysis of the NHANES III data (4) also suggests that participants with the metabolic syndrome (with or without diabetes) have an increased prevalence of coronary artery disease, thus further underscoring the potential benefit of preventing or delaying the syndrome. However, these findings should be interpreted in the context of other related states, for example, impaired glucose tolerance itself. The Diabetes Epidemiology: Collaborative analysis Of Diagnostic criteria in Europe (DECODE) study (17, 18) recently firmly established a strong predictive role for all-cause and cardiovascular mortality. Nonetheless, these interventions, especially the lifestyle intervention, should yield cardiovascular benefit by improving glucose tolerance and the metabolic syndrome, no matter how the risk is attributed between the two.

Our data, although derived from a volunteer population with impaired glucose tolerance but not diabetes, provide potentially important clinical information concerning the metabolic syndrome and its prevention. Although the population studied had moderately severe impaired glucose tolerance (fasting plasma glucose level ≥5.3 mmol/L [≥95 mg/dL]), only 53% overall had the metabolic syndrome, suggesting that this high-risk state is far from omnipresent even in impaired glucose tolerance. Of particular note is the variation by age group of the components contributing to the diagnosis. Waist circumference and low HDL cholesterol level appear to be particular features of the younger participants with the metabolic syndrome, while blood pressure is particularly important for the older participants. Triglyceride levels, on the other hand, appear fairly constant for all ages. It is interesting to speculate whether this age difference relates to the increasing conversion to diabetes (and thus study ineligibility) with age or differences in perceived diabetes risk leading to Diabetes Prevention Program screening. Similarly, the difference between the sexes is interesting: Waist circumference and low HDL cholesterol level predominate in women and high fasting glucose level and high blood pressure are more noticeable in men. Because the criteria for entry varied by ethnic group to some degree, meaningful interpretation of ethnicity-specific data is limited, although it is important to note that no heterogeneity was seen for treatment effects by ethnic group.

Because the metabolic syndrome is not consistent over age groups, these findings could be interpreted as an argument for treating the individual risk factors themselves and not limiting intervention to the syndrome. These findings also raise the issue recently addressed by Stern and colleagues (19) that cardiovascular risk prediction is probably better addressed by multivariable models than by categorizing participants by glucose tolerance status. Of interest, waist circumference and low HDL cholesterol levels were the best predictors in the San Antonio Heart Study (12).

Particularly encouraging is the dramatic effect of lifestyle on both the incidence of new metabolic syndrome (and its components) and on participants who had the syndrome at baseline. The beneficial effect of lifestyle intervention on components other than glucose level is particularly encouraging and provides important evidence of the value of this approach to those with blood pressure, weight, and lipid disturbances in general. The intermediary effect of metformin, which closely mirrors the pattern of results for the overall trial in terms of diabetes prevention or delay, further underscores the preferential value of lifestyle as the initial approach to prevention of the metabolic syndrome and its cardiovascular complications.

The complete lack of effect of metformin in women is surprising, given its overall effect on diabetes prevention. This finding can be only partly related to the smaller sample available for prevention of the metabolic syndrome. Sex differences in the prediction of the metabolic syndrome have, however, been noted before. For example, Han and colleagues (20) reported that C-reactive protein level predicted the metabolic syndrome in women but not men. It has also been observed that metformin decreases basal testosterone levels in men (21) but not women (22). In addition, the sex-specific criteria for the syndrome may play a role. These criteria are somewhat arbitrary and may not effectively represent underlying metabolic differences between the sexes. The reduced efficacy of metformin in participants with higher baseline insulin levels also deserves further investigation, although it probably reflects a relatively weaker effect of metformin on insulin resistance than that seen for lifestyle.

The dramatic effect of lifestyle on both the prevention of incident metabolic syndrome and reduction of its overall prevalence appears to be most strongly related to a reduction in waist circumference and in blood pressure and not, as might have been anticipated, through a correction of the lipid abnormalities of triglycerides and HDL cholesterol. The incidence of abnormal HDL cholesterol level was virtually identical by treatment group, while waist circumference and frequency of hypertension were both significantly reduced by intensive lifestyle intervention. It is interesting to speculate why lifestyle should have relatively little effect on HDL cholesterol level but such a marked effect on blood pressure. Similar results have been reported by the Finnish Diabetes Prevention Study (23). One possibility may be that although total calories were reduced in the lifestyle group, the relatively greater focus on fat content may have altered the ratio of polyunsaturated to saturated fats, which is related to HDL cholesterol levels (24).

Although we were not able to determine the best way to define the metabolic syndrome as an intervention target, or even whether to define it at all, future follow-up of the cohort will enable us to determine whether this particular combination of risk factors or some other variation better predicts cardiovascular outcomes. Naturally, our intervention results apply primarily to persons with impaired glucose tolerance and cannot be immediately translated to other groups.

These data provide an extensive and detailed description of the metabolic syndrome in a high-risk population and reveal important differences in composition of the syndrome by age and sex. They also demonstrate the value of lifestyle intervention, in particular, in both the prevention and treatment of this condition, above and beyond improvement in glycemia alone. Lifestyle intervention may reduce cardiovascular risk in persons with impaired glucose tolerance.


Author and Article Information
space
up arrowTop
up arrowEditors' Notes
up arrowMethods
up arrowResults
up arrowDiscussion
dotAuthor & Article Info
down arrowReferences

From the Diabetes Prevention Program Coordinating Center, The Biostatistics Center, George Washington University, Rockville, Maryland.

Grant Support: Funding was provided by the National Institutes of Health (5U01DK048489) through the National Institute of Diabetes and Digestive and Kidney Diseases, the National Center on Minority Health and Health Disparities, the National Institute of Child Health and Human Development, the Office of Women's Health, and the National Institute on Aging. In addition, the Indian Health Service, the Centers for Disease Control and Prevention, the American Diabetes Association, and 2 pharmaceutical companies—Bristol-Myers Squibb and Parke-Davis—contributed support. The General Clinical Research Center Program, National Center for Research Resources, supported many of the clinical centers. Support to the clinical centers and the Coordinating Center was provided by the National Institute of Diabetes and Digestive and Kidney Diseases through a cooperative agreement, except for the Southwestern American Indian Centers, which were supported directly by the National Institute of Diabetes and Digestive and Kidney Diseases and the Indian Health Service.

Potential Financial Conflicts of Interest: Consultancies: T.J. Orchard (Metabolic Syndrome Alliance, Sanofi-Aventis); Grants received: R. Ratner (Bristol-Myers Squibb).

Requests for Single Reprints: Diabetes Prevention Program Coordinating Center, The Biostatistics Center, George Washington University, 6110 Executive Boulevard, Suite 750, Rockville, MD 20852.

Current Author Addresses: Dr. Orchard: Diabetes and Lipid Research Building, University of Pittsburgh, 3512 5th Avenue 203, Pittsburgh, PA 15213.

Ms. Temprosa and Dr. Fowler: George Washington University, Biostatistics Center, 6110 Executive Boulevard, Suite 750, Rockville, MD 20852.

Dr. Goldberg: Diabetes Research Institute, University of Miami School of Medicine, 1450 NW 10th Avenue R-77, Miami, FL 33136.

Dr. Haffner: Department of Medicine, Clinical Epidemiology, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, MSC 7873, San Antonio, TX 78229-3900.

Dr. Ratner: Medstar Research Institute, 6495 New Hampshire Avenue, Suite 201, Hyattsville, MD 20783.

Dr. Marcovina: Northwest Lipid Research Labs, 2121 North 35th Street, University of Washington, Seattle, WA 98103-9103.

Author Contributions: Conception and design: T.J. Orchard, M. Temprosa, R. Goldberg, S. Haffner, R. Ratner, S. Fowler.

Analysis and interpretation of the data: T.J. Orchard, M. Temprosa, R. Goldberg, R. Ratner, S. Fowler.

Drafting of the article: T.J. Orchard, M. Temprosa, R. Goldberg, S. Haffner, S. Fowler.

Critical revision of the article for important intellectual content: T.J. Orchard, M. Temprosa, R. Goldberg, S. Haffner, R. Ratner, S. Marcovina, S. Fowler.

Final approval of the article: T.J. Orchard, M. Temprosa, R. Goldberg, R. Ratner, S. Marcovina, S. Fowler.

Provision of study materials or patients: The DPP Research Group, T.J. Orchard, R. Goldberg, S. Haffner, R. Ratner, S. Marcovina.

Statistical expertise: M. Temprosa, S. Fowler.

Obtaining of funding: The DPP Research Group Principal Investigators.

Administrative, technical, or logistic support: T.J. Orchard, M. Temprosa, R. Goldberg, S. Marcovina, S. Fowler.

Collection and assembly of data: The DPP Research Group, T.J. Orchard, M. Temprosa, R. Goldberg.


References
space
up arrowTop
up arrowEditors' Notes
up arrowMethods
up arrowResults
up arrowDiscussion
up arrowAuthor & Article Info
dotReferences

1.  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. [PMID: 11368702].[Free Full Text]

2.  Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med. 1998;15:539-53. [PMID: 9686693].

3.  Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. JAMA. 2002;287:356-9. [PMID: 11790215].[Abstract/Free Full Text]

4.  Alexander CM, Landsman PB, Teutsch SM, Haffner SM. NCEP-defined metabolic syndrome, diabetes, and prevalence of coronary heart disease among NHANES III participants age 50 years and older. Diabetes. 2003;52:1210-4. [PMID: 12716754].[Abstract/Free Full Text]

5.  Knowler WC, Barrett-Connor E, Fowler SE, Hamman RF, Lachin JM, Walker EA, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346:393-403. [PMID: 11832527].

6.  The Diabetes Prevention Program. Design and methods for a clinical trial in the prevention of type 2 diabetes. Diabetes Care. 1999;22:623-34. [PMID: 10189543].[Abstract]

7.  Bureau of the Census. Census of the Population, 1990. Washington, DC: U.S. Government Printing Office; 1990.

8.  Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28:412-9. [PMID: 3899825].[Medline]

9.  Warnick GR. Enzymatic methods for quantification of lipoprotein lipids. Methods Enzymol. 1986;129:101-23. [PMID: 3724535].[Medline]

10.  Warnick GR, Benderson J, Albers JJ. Dextran sulfate-Mg2+ precipitation procedure for quantitation of high-density-lipoprotein cholesterol. Clin Chem. 1982;28:1379-88. [PMID: 7074948].[Free Full Text]

11.  Svejgaard A, Platz P, Ryder LP. HLA and disease 1982—a survey. Immunol Rev. 1983;70:193-218. [PMID: 6339368].[Medline]

12.  Hokanson JE, Austin MA, Brunzell JD. Measurement and clinical significance of low density lipoprotein subclasses. In: Rifai N, Warnick GR, Dominiczak MH, eds. Handbook of Lipoprotein Testing. Washington, DC: AACC Pr; 1997:267-82.

13.  Lachin JM. Biostatistical Methods: The Assessment of Relative Risks. New York: J Wiley; 2000.

14.  Diggle PJ, Liang KY, Zeger SL. Analysis of Longitudinal Data. New York: Oxford Univ Pr; 1994.

15.  Screening for type 2 diabetes. Diabetes Care. 2004;27(Suppl 1):S11-4. [PMID: 14693922].[Free Full Text]

16.  Bonora E, Kiechl S, Willeit J, Oberhollenzer F, Egger G, Bonadonna RC, et al. Carotid atherosclerosis and coronary heart disease in the metabolic syndrome: prospective data from the Bruneck study. Diabetes Care. 2003;26:1251-7. [PMID: 12663606].[Abstract/Free Full Text]

17.  Glucose tolerance and cardiovascular mortality: comparison of fasting and 2-hour diagnostic criteria. Arch Intern Med. 2001;161:397-405. [PMID: 11176766].[Abstract/Free Full Text]

18.  Glucose tolerance and mortality: comparison of WHO and American Diabetes Association diagnostic criteria. The DECODE study group. European Diabetes Epidemiology Group. Diabetes Epidemiology: Collaborative analysis Of Diagnostic criteria in Europe. Lancet. 1999;354:617-21. [PMID: 10466661].[Medline]

19.  Stern MP, Williams K, Haffner SM. Identification of persons at high risk for type 2 diabetes mellitus: do we need the oral glucose tolerance test? Ann Intern Med. 2002;136:575-81. [PMID: 11955025].[Abstract/Free Full Text]

20.  Han TS, Sattar N, Williams K, Gonzalez-Villalpando C, Lean ME, Haffner SM. Prospective study of C-reactive protein in relation to the development of diabetes and metabolic syndrome in the Mexico City Diabetes Study. Diabetes Care. 2002;25:2016-21. [PMID: 12401749].[Abstract/Free Full Text]

21.  Ozata M, Oktenli C, Bingol N, Ozdemir IC. The effects of metformin and diet on plasma testosterone and leptin levels in obese men. Obes Res. 2001;9:662-7. [PMID: 11707532].[Medline]

22.  Vrbikova J, Hill M, Starka L, Cibula D, Bendlova B, Vondra K, et al. The effects of long-term metformin treatment on adrenal and ovarian steroidogenesis in women with polycystic ovary syndrome. Eur J Endocrinol. 2001;144:619-28. [PMID: 11375796].[Abstract]

23.  Crouse JR 3rd. Gender, lipoproteins, diet, and cardiovascular risk. Sauce for the goose may not be sauce for the gander. Lancet. 1989;1:318-20. [PMID: 2563468].[Medline]

24.  Lindstrom J, Louheranta A, Mannelin M, Rastas M, Salminen V, Eriksson J, et al. The Finnish Diabetes Prevention Study (DPS): Lifestyle intervention and 3-year results on diet and physical activity. Diabetes Care. 2003;26:3230-6. [PMID: 14633807].[Abstract/Free Full Text]

 

Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Facebook Facebook   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?

Related articles in Annals:

Summaries for Patients
The Effect of Diet and Exercise or Metformin on the Metabolic Syndrome
Annals 2005 142: I-46. [Full Text]  

Letters
The Diabetes Prevention Program and the Metabolic Syndrome
Priscilla S. Sarinas AND Daniel S. Dube
Annals 2005 143: 544-545. [Full Text]  

Letters
The Diabetes Prevention Program and the Metabolic Syndrome
Frank A. Anania, Samir Parekh, AND Aasma Shaukat
Annals 2005 143: 545. [Full Text]  

Letters
The Diabetes Prevention Program and the Metabolic Syndrome
Trevor J. Orchard, Marinella Temprosa, AND Robert Ratner
Annals 2005 143: 545-546. [Full Text]  



This article has been cited by other articles:


Home page
CirculationHome page
Z. Yu, X. Ye, J. Wang, Q. Qi, O. H. Franco, K. L. Rennie, A. Pan, H. Li, Y. Liu, F. B. Hu, et al.
Associations of Physical Activity With Inflammatory Factors, Adipocytokines, and Metabolic Syndrome in Middle-Aged and Older Chinese People
Circulation, June 16, 2009; 119(23): 2969 - 2977.
[Abstract] [Full Text] [PDF]


Home page
Arch Intern MedHome page
J. Salas-Salvado, E. Ros, R. Estruch, M.-I. Covas, and for the PREDIMED Study Investigators
Which Mediterranean Diet in the Management of Metabolic Syndrome?--Reply
Arch Intern Med, June 8, 2009; 169(11): 1077 - 1077.
[Full Text] [PDF]


Home page
Diabetes and Vascular Disease ResearchHome page
K. I. Cheang, J. M. Huszar, A. M. Best, S. Sharma, P. A. Essah, and J. E. Nestler
Long-term effect of metformin on metabolic parameters in the polycystic ovary syndrome
Diabetes and Vascular Disease Research, April 1, 2009; 6(2): 110 - 119.
[Abstract] [PDF]


Home page
Diabetes CareHome page
Diabetes Prevention Program Research Group
Changes in Albumin Excretion in the Diabetes Prevention Program
Diabetes Care, April 1, 2009; 32(4): 720 - 725.
[Abstract] [Full Text] [PDF]


Home page
CMAJHome page
S. H. Ley, S. B. Harris, M. Mamakeesick, T. Noon, E. Fiddler, J. Gittelsohn, T. M.S. Wolever, P. W. Connelly, R. A. Hegele, B. Zinman, et al.
Metabolic syndrome and its components as predictors of incident type 2 diabetes mellitus in an Aboriginal community
Can. Med. Assoc. J., March 17, 2009; 180(6): 617 - 624.
[Abstract] [Full Text] [PDF]


Home page
The Diabetes EducatorHome page
H. A. Amundson, M. K. Butcher, D. Gohdes, T. O. Hall, T. S. Harwell, S. D. Helgerson, K. K. Vanderwood, and for the Montana Cardiovascular Disease and Diabete
Translating the Diabetes Prevention Program Into Practice in the General Community: Findings From the Montana Cardiovascular Disease and Diabetes Prevention Program
The Diabetes Educator, March 1, 2009; 35(2): 209 - 223.
[Abstract] [Full Text] [PDF]


Home page
Diabetes and Vascular Disease ResearchHome page
J. B Lindsey, F. Cipollone, S. M Abdullah, and D. K Mcguire
Receptor for advanced glycation end-products (RAGE) and soluble RAGE (sRAGE): cardiovascular implications
Diabetes and Vascular Disease Research, January 1, 2009; 6(1): 7 - 14.
[Abstract] [PDF]


Home page
Diabetes and Vascular Disease ResearchHome page
M. Hanefeld, A. Karasik, C. Koehler, T. Westermeier, and J.-L. Chiasson
Metabolic syndrome and its single traits as risk factors for diabetes in people with impaired glucose tolerance: the STOP-NIDDM trial
Diabetes and Vascular Disease Research, January 1, 2009; 6(1): 32 - 37.
[Abstract] [PDF]


Home page
Arch Intern MedHome page
J. Salas-Salvado, J. Fernandez-Ballart, E. Ros, M.-A. Martinez-Gonzalez, M. Fito, R. Estruch, D. Corella, M. Fiol, E. Gomez-Gracia, F. Aros, et al.
Effect of a Mediterranean Diet Supplemented With Nuts on Metabolic Syndrome Status: One-Year Results of the PREDIMED Randomized Trial
Arch Intern Med, December 8, 2008; 168(22): 2449 - 2458.
[Abstract] [Full Text] [PDF]


Home page
Eur J EndocrinolHome page
S. Bo, G. Ciccone, S. Guidi, R. Gambino, M. Durazzo, L. Gentile, M. Cassader, P. Cavallo-Perin, and G. Pagano
Diet or exercise: what is more effective in preventing or reducing metabolic alterations?
Eur. J. Endocrinol., December 1, 2008; 159(6): 685 - 691.
[Abstract] [Full Text] [PDF]


Home page
Endocr. Rev.Home page
M.-A. Cornier, D. Dabelea, T. L. Hernandez, R. C. Lindstrom, A. J. Steig, N. R. Stob, R. E. Van Pelt, H. Wang, and R. H. Eckel
The Metabolic Syndrome
Endocr. Rev., December 1, 2008; 29(7): 777 - 822.
[Abstract] [Full Text] [PDF]


Home page
Diabetes CareHome page
Z. T. Bloomgarden
American College of Endocrinology Pre-Diabetes Consensus Conference: Part One
Diabetes Care, October 1, 2008; 31(10): 2062 - 2069.
[Full Text] [PDF]


Home page
J. Clin. Endocrinol. Metab.Home page
J. L. Rosenzweig, E. Ferrannini, S. M. Grundy, S. M. Haffner, R. J. Heine, E. S. Horton, and R. Kawamori
Primary Prevention of Cardiovascular Disease and Type 2 Diabetes in Patients at Metabolic Risk: An Endocrine Society Clinical Practice Guideline
J. Clin. Endocrinol. Metab., October 1, 2008; 93(10): 3671 - 3689.
[Abstract] [Full Text] [PDF]


Home page
NDT PlusHome page
P. K.-T. Li, B. C.-H. Kwan, C. C. Szeto, and G. T.-C. Ko
Metabolic syndrome in peritoneal dialysis patients
NDT Plus, August 1, 2008; 1(4): 206 - 214.
[Abstract] [Full Text] [PDF]


Home page
CirculationHome page
S. K. Kumanyika, E. Obarzanek, N. Stettler, R. Bell, A. E. Field, S. P. Fortmann, B. A. Franklin, M. W. Gillman, C. E. Lewis, W. C. Poston II, et al.
Population-Based Prevention of Obesity: The Need for Comprehensive Promotion of Healthful Eating, Physical Activity, and Energy Balance: A Scientific Statement From American Heart Association Council on Epidemiology and Prevention, Interdisciplinary Committee for Prevention (Formerly the Expert Panel on Population and Prevention Science)
Circulation, July 22, 2008; 118(4): 428 - 464.
[Abstract] [Full Text] [PDF]


Home page
The Annals of PharmacotherapyHome page
A. R Desilets, S. Dhakal-Karki, and K. C Dunican
Role of Metformin for Weight Management in Patients Without Type 2 Diabetes
Ann. Pharmacother., June 1, 2008; 42(6): 817 - 826.
[Abstract] [Full Text] [PDF]


Home page
British Journal of Diabetes & Vascular DiseaseHome page
A. S Wierzbicki, S. D Purdon, T. C Hardman, R. Kulasegaram, and B. S Peters
Review: Clinical aspects of the management of HIV lipodystrophy
The British Journal of Diabetes & Vascular Disease, May 1, 2008; 8(3): 113 - 119.
[Abstract] [PDF]


Home page
Diabetes CareHome page
D. Giugliano, A. Ceriello, and K. Esposito
Mediterranean Diet Inversely Associated With the Incidence of Metabolic Syndrome: the SUN Prospective Cohort: Response to Tortosa et al.
Diabetes Care, May 1, 2008; 31(5): e36 - e36.
[Full Text] [PDF]


Home page
Diabetes CareHome page
P. Ilanne-Parikka, J. G. Eriksson, J. Lindstrom, M. Peltonen, S. Aunola, H. Hamalainen, S. Keinanen-Kiukaanniemi, M. Laakso, T. T. Valle, J. Lahtela, et al.
Effect of Lifestyle Intervention on the Occurrence of Metabolic Syndrome and its Components in the Finnish Diabetes Prevention Study
Diabetes Care, April 1, 2008; 31(4): 805 - 807.
[Abstract] [Full Text] [PDF]


Home page
DiabetesHome page
K. J. Mather, T. Funahashi, Y. Matsuzawa, S. Edelstein, G. A. Bray, S. E. Kahn, J. Crandall, S. Marcovina, B. Goldstein, R. Goldberg, et al.
Adiponectin, Change in Adiponectin, and Progression to Diabetes in the Diabetes Prevention Program
Diabetes, April 1, 2008; 57(4): 980 - 986.
[Abstract] [Full Text] [PDF]


Home page
J. Clin. Endocrinol. Metab.Home page
G. Hu, J. Lindstrom, P. Jousilahti, M. Peltonen, L. Sjoberg, R. Kaaja, J. Sundvall, and J. Tuomilehto
The Increasing Prevalence of Metabolic Syndrome among Finnish Men and Women over a Decade
J. Clin. Endocrinol. Metab., March 1, 2008; 93(3): 832 - 836.
[Abstract] [Full Text] [PDF]


Home page
Eur Heart J SupplHome page
J.-P. Despres, P. Poirier, J. Bergeron, A. Tremblay, I. Lemieux, and N. Almeras
From individual risk factors and the metabolic syndrome to global cardiometabolic risk
Eur. Heart J. Suppl., March 1, 2008; 10(suppl_B): B24 - B33.
[Abstract] [Full Text] [PDF]


Home page
Diabetes CareHome page
C. Bianchi, R. Miccoli, G. Penno, and S. Del Prato
Primary Prevention of Cardiovascular Disease in People With Dysglycemia
Diabetes Care, February 1, 2008; 31(Supplement_2): S208 - S214.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Clin. Nutr.Home page
D. Giugliano, A. Ceriello, and K. Esposito
Are there specific treatments for the metabolic syndrome?
Am. J. Clinical Nutrition, January 1, 2008; 87(1): 8 - 11.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Clin. Nutr.Home page
D. Giugliano, A. Ceriello, and K. Esposito
Glucose metabolism and hyperglycemia
Am. J. Clinical Nutrition, January 1, 2008; 87(1): 217S - 222S.
[Abstract] [Full Text] [PDF]


Home page
Diabetes and Vascular Disease ResearchHome page
J. Mcgavock, E. Sellers, and H. Dean
Physical activity for the prevention and management of youth-onset type 2 diabetes mellitus: focus on cardiovascular complications
Diabetes and Vascular Disease Research, December 1, 2007; 4(4): 305 - 310.
[Abstract] [PDF]


Home page
J. Appl. Physiol.Home page
S. F. E. Praet and L. J. C. van Loon
Optimizing the therapeutic benefits of exercise in Type 2 diabetes
J Appl Physiol, October 1, 2007; 103(4): 1113 - 1120.
[Abstract] [Full Text] [PDF]


Home page
HypertensionHome page
L. F. Lien, A. J. Brown, J. D. Ard, C. Loria, T. P. Erlinger, A. C. Feldstein, P.-H. Lin, C. M. Champagne, A. C. King, H. L. McGuire, et al.
Effects of PREMIER Lifestyle Modifications on Participants With and Without the Metabolic Syndrome
Hypertension, October 1, 2007; 50(4): 609 - 616.
[Abstract] [Full Text] [PDF]


Home page
cfpHome page
A. Emili, H. Abushomar, and K. Nair
Treating metabolic syndrome: Lifestyle change or medication?
Can Fam Physician, July 1, 2007; 53(7): 1203 - 1205.
[Full Text] [PDF]


Home page
Eur Heart JHome page
Authors/Task Force Members:, G. Mancia, G. De Backer, A. Dominiczak, R. Cifkova, R. Fagard, G. Germano, G. Grassi, A. M. Heagerty, S. E. Kjeldsen, et al.
2007 Guidelines for the Management of Arterial Hypertension: The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC)
Eur. Heart J., June 11, 2007; (2007) ehm236v1.
[Full Text] [PDF]


Home page
Diabetes CareHome page
J. Waden, L. M. Thorn, C. Forsblom, T. Lakka, M. Saraheimo, M. Rosengard-Barlund, O. Heikkila, M. Wessman, J. A. Turunen, M. Parkkonen, et al.
Leisure-Time Physical Activity Is Associated With the Metabolic Syndrome in Type 1 Diabetes: Effect of the PPAR{gamma} Pro12Ala polymorphism: the FinnDiane Study
Diabetes Care, June 1, 2007; 30(6): 1618 - 1620.
[Full Text] [PDF]


Home page
British Journal of Diabetes & Vascular DiseaseHome page
R. E Pratley and G. Matfin
Review: Pre-diabetes: clinical relevance and therapeutic approach
The British Journal of Diabetes & Vascular Disease, May 1, 2007; 7(3): 120 - 129.
[Abstract] [PDF]


Home page
Diabetes CareHome page
C. Y. Jeon, R. P. Lokken, F. B. Hu, and R. M. van Dam
Physical Activity of Moderate Intensity and Risk of Type 2 Diabetes: A systematic review
Diabetes Care, March 1, 2007; 30(3): 744 - 752.
[Abstract] [Full Text] [PDF]


Home page
Diabetes CareHome page
M. Freemark
Pharmacotherapy of Childhood Obesity: An evidence-based, conceptual approach
Diabetes Care, February 1, 2007; 30(2): 395 - 402.
[Full Text] [PDF]


Home page
Diabetes CareHome page
M. A. Abdul-Ghani, M. Matsuda, B. Balas, and R. A. DeFronzo
Muscle and Liver Insulin Resistance Indexes Derived From the Oral Glucose Tolerance Test
Diabetes Care, January 1, 2007; 30(1): 89 - 94.
[Abstract] [Full Text] [PDF]


Home page
Arch Intern MedHome page
J. A. Tice, A. Kanaya, T. Hue, S. Rubin, D. S. M. Buist, A. LaCroix, J. V. Lacey Jr, J. A. Cauley, S. Litwack, L. A. Brinton, et al.
Risk Factors for Mortality in Middle-aged Women
Arch Intern Med, December 11, 2006; 166(22): 2469 - 2477.
[Abstract] [Full Text] [PDF]


Home page
Mayo Clin Proc.Home page
L. W. Johnson and R. S. Weinstock
The Metabolic Syndrome: Concepts and Controversy
Mayo Clin. Proc., December 1, 2006; 81(12): 1615 - 1620.
[Abstract] [Full Text] [PDF]


Home page
J Am Coll CardiolHome page
C. Iribarren, A. S. Go, G. Husson, S. Sidney, J. M. Fair, T. Quertermous, M. A. Hlatky, and S. P. Fortmann
Metabolic Syndrome and Early-Onset Coronary Artery Disease: Is the Whole Greater Than Its Parts?
J. Am. Coll. Cardiol., November 7, 2006; 48(9): 1800 - 1807.
[Abstract] [Full Text] [PDF]


Home page
J. Clin. Endocrinol. Metab.Home page
S. T. Page, J. K. Amory, B. D. Anawalt, M. S. Irwig, A. T. Brockenbrough, A. M. Matsumoto, and W. J. Bremner
Testosterone Gel Combined with Depomedroxyprogesterone Acetate Is an Effective Male Hormonal Contraceptive Regimen and Is Not Enhanced by the Addition of a GnRH Antagonist
J. Clin. Endocrinol. Metab., November 1, 2006; 91(11): 4374 - 4380.
[Abstract] [Full Text] [PDF]


Home page
J. Clin. Endocrinol. Metab.Home page
K. A. Neville, R. J. Cohn, K. S. Steinbeck, K. Johnston, and J. L. Walker
Hyperinsulinemia, Impaired Glucose Tolerance, and Diabetes Mellitus in Survivors of Childhood Cancer: Prevalence and Risk Factors
J. Clin. Endocrinol. Metab., November 1, 2006; 91(11): 4401 - 4407.
[Abstract] [Full Text] [PDF]


Home page
Postgrad. Med. J.Home page
J O'Loughlin, E Dugas, K Maximova, and N Kishchuk
Reporting of ethnicity in research on chronic disease: update
Postgrad. Med. J., November 1, 2006; 82(973): 737 - 742.
[Abstract] [Full Text] [PDF]


Home page
Arterioscler. Thromb. Vasc. Bio.Home page
A. E. Griel, E. H. Ruder, and P. M. Kris-Etherton
The Changing Roles of Dietary Carbohydrates: From Simple to Complex
Arterioscler. Thromb. Vasc. Biol., September 1, 2006; 26(9): 1958 - 1965.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Clin. Nutr.Home page
L. J Moran, M. Noakes, P. M Clifton, G. A Wittert, G. Williams, and R. J Norman
Short-term meal replacements followed by dietary macronutrient restriction enhance weight loss in polycystic ovary syndrome
Am. J. Clinical Nutrition, July 1, 2006; 84(1): 77 - 87.
[Abstract] [Full Text] [PDF]


Home page
The Diabetes EducatorHome page
N. J. Davis, A. Emerenini, and J. Wylie-Rosett
Obesity management: physician practice patterns and patient preference.
The Diabetes Educator, July 1, 2006; 32(4): 557 - 561.
[Abstract] [Full Text] [PDF]


Home page
Am. J. Clin. Nutr.Home page
Y. A Carpentier, L. Portois, and W. J Malaisse
n-3 Fatty acids and the metabolic syndrome
Am. J. Clinical Nutrition, June 1, 2006; 83(6): S1499 - 1504S.
[Abstract] [Full Text] [PDF]


Home page
Diabetes CareHome page
K. Esposito, M. Ciotola, D. Carleo, B. Schisano, F. Saccomanno, F. C. Sasso, D. Cozzolino, R. Assaloni, D. Merante, A. Ceriello, et al.
Effect of Rosiglitazone on Endothelial Function and Inflammatory Markers in Patients With the Metabolic Syndrome
Diabetes Care, May 1, 2006; 29(5): 1071 - 1076.
[Abstract] [Full Text] [PDF]


Home page
Diabetes CareHome page
L. G. K. de Aguiar, L. R. Bahia, N. Villela, C. Laflor, F. Sicuro, N. Wiernsperger, D. Bottino, and E. Bouskela
Metformin Improves Endothelial Vascular Reactivity in First-Degree Relatives of Type 2 Diabetic Patients With Metabolic Syndrome and Normal Glucose Tolerance
Diabetes Care, May 1, 2006; 29(5): 1083 - 1089.
[Abstract] [Full Text] [PDF]


Home page
Arterioscler. Thromb. Vasc. Bio.Home page
D. Giugliano and K. Esposito
Optimal Treatments for the Metabolic Syndrome
Arterioscler. Thromb. Vasc. Biol., April 1, 2006; 26(4): e30 - e30.
[Full Text] [PDF]


Home page
Diabetes CareHome page
K. Esposito and D. Giugliano
Beneficial Effects of a Dietary Approaches to Stop Hypertension Eating Plan on Features of the Metabolic Syndrome: Response to Azdbakht et al.
Diabetes Care, April 1, 2006; 29(4): 954 - 955.
[Full Text] [PDF]


Home page
Diabetes CareHome page
D. Giugliano and K. Esposito
The Metabolic Syndrome: Time for a Critical Appraisal: Joint Statement From the American Diabetes Association and the European Association for the Study of Diabetes: Response to Kahn et al.
Diabetes Care, January 1, 2006; 29(1): 175 - 176.
[Full Text] [PDF]


Home page
Evid. Based Med.Home page
R. J Sigal
A lifestyle intervention or metformin prevented or delayed the onset of metabolic syndrome in persons at risk
Evid. Based Med., December 1, 2005; 10(6): 172 - 172.
[Full Text] [PDF]


Home page
Physiol. GenomicsHome page
J. M. Dhahbi, P. L. Mote, G. M. Fahy, and S. R. Spindler
Identification of potential caloric restriction mimetics by microarray profiling
Physiol Genomics, November 17, 2005; 23(3): 343 - 350.
[Abstract] [Full Text] [PDF]


Home page
ANN INTERN MEDHome page
F. A. Anania, S. Parekh, and A. Shaukat
The Diabetes Prevention Program and the Metabolic Syndrome
Ann Intern Med, October 4, 2005; 143(7): 545 - 545.
[Full Text] [PDF]


Home page
ANN INTERN MEDHome page
P. S. Sarinas and D. S. Dube
The Diabetes Prevention Program and the Metabolic Syndrome
Ann Intern Med, October 4, 2005; 143(7): 544 - 545.
[Full Text] [PDF]


Home page
Diabetes CareHome page
Z. T. Bloomgarden
2nd International Symposium on Triglycerides and HDL: Metabolic syndrome
Diabetes Care, October 1, 2005; 28(10): 2577 - 2584.
[Full Text] [PDF]


Home page
DOC NewsHome page
Preventing Metabolic Syndrome by Preventing Diabetes
DOC News, August 1, 2005; 2(8): 14 - 15.
[Full Text]


Home page
J. Clin. Endocrinol. Metab.Home page
Endocrinology & Metabolism News, June 2005
J. Clin. Endocrinol. Metab., June 1, 2005; 90(6): 16a - 16a.
[Full Text] [PDF]

Rapid Responses:

Read all Rapid Responses

Metabolic Syndrome and Fatty Liver
Frank A. Anania, et al.
Annals Online, 22 Apr 2005 [Full text]
Multitargeted treatment for metabolic syndrome
Vasilios G Athyros, et al.
Annals Online, 5 May 2005 [Full text]
Sleep Related Breathing Disorders and the Metabolic Syndrome
PRISCILLA S. SARINAS M.D. FACP, et al.
Annals Online, 20 May 2005 [Full text]
In Response
Trevor J Orchard, et al.
Annals Online, 16 Jun 2005 [Full text]



 Home | Current Issue | Past Issues | In the Clinic | ACP Journal Club | CME | Collections | Audio/Video | Mobile | Subscribe | Tools | Help | ACP Online 

Copyright © 2005 by the American College of Physicians.