Glycemic Index, Glycemic Load, and Prevalence of the Metabolic Syndrome in the Cooper Center Longitudinal Study

Glycemic Index, Glycemic Load, and Prevalence of the Metabolic Syndrome in the Cooper Center Longitudinal Study

RESEARCH Original Research Meets Learning Need Codes 3000, 4000, 5000, 5160, and 5190. To take the Continuing Professional Education quiz for this ar...

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RESEARCH Original Research

Meets Learning Need Codes 3000, 4000, 5000, 5160, and 5190. To take the Continuing Professional Education quiz for this article, log in to ADA’s Online Business Center at www.eatright.org/obc, click the “Journal Article Quiz” button, click “Additional Journal CPE Articles,” and select this article’s title from a list of available quizzes.

Glycemic Index, Glycemic Load, and Prevalence of the Metabolic Syndrome in the Cooper Center Longitudinal Study CARRIE E. FINLEY, MS; CAROLYN E. BARLOW, MS; THOMAS L. HALTON, PhD; WILLIAM L. HASKELL, PhD

ABSTRACT Objective Previous research examining the relationships among glycemic index, glycemic load, and the metabolic syndrome has resulted in inconsistent findings. The objective of this study was to examine whether glycemic index and glycemic load are associated with prevalent metabolic syndrome and its components after adjustment for cardiorespiratory fitness, an objective measure of physical activity habitus. Design Cross-sectional study. Subjects/setting Women (n⫽1,775) and men (n⫽9,137) who completed a comprehensive medical examination between October 1987 and March 1999, including maximal treadmill exercise test and 3-day dietary records at the Cooper Clinic, Dallas, TX. Main outcome measures Metabolic syndrome and its components, defined by the revised Adult Treatment Panel III criteria. Statistical analysis Multiple logistic regression models were used to estimate sex-specific odds ratios and 95% confidence intervals to evaluate the associations among glycemic index, glycemic load, and prevalent metabolic syndrome and its components, while adjusting for potential confounding variables.

C. E. Finley is a data analyst/statistician and C. E. Barlow is director, The Cooper Institute, Dallas, TX. T. L. Halton is the owner, Fitness Plus, Boston, MA. W. L. Haskell is a professor, Stanford Prevention Research Center, Stanford University School of Medicine, Palo Alto, CA and a scientific consultant, The Cooper Institute, Dallas, TX. Address correspondence to: Carrie E. Finley, MS, The Cooper Institute, 12330 Preston Rd, Dallas, TX 75230. E-mail: [email protected] Manuscript accepted: May 6, 2010. Copyright © 2010 by the American Dietetic Association. 0002-8223/$36.00 doi: 10.1016/j.jada.2010.09.016

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Results Prevalence of metabolic syndrome was 24% in men and 9% in women. A positive association across quintiles of glycemic index and metabolic syndrome, elevated triglycerides, and low high-density lipoprotein cholesterol (HDL-C) in men was observed in the fully adjusted model (P for trend⬍0.05). In women, glycemic index was positively associated with large waist girth, low HDL-C, and elevated triglycerides (P for trend⬍0.05 for all) after multivariate adjustment including cardiorespiratory fitness. Glycemic load was positively associated with elevated triglycerides and low HDL-C (P for trend⬍0.0001) and inversely associated with prevalence of large waist girth and elevated glucose (P for trend⬍0.0001) in men. Among women, glycemic load was positively associated with elevated triglycerides (P for trend⫽0.04) and low HDL-C (P for trend⬍0.0001) in the multivariate model including cardiorespiratory fitness. Conclusions A lifestyle that includes a low glycemic diet can improve metabolic risk profiles in men and women. Prospective studies examining glycemic index, glycemic load, and metabolic syndrome that control for cardiorespiratory fitness are needed. J Am Diet Assoc. 2010;110:1820-1829.

T

he metabolic syndrome is a clustering of metabolic risk factors that have been associated with increased risk of atherosclerotic cardiovascular disease and type 2 diabetes (1). The metabolic syndrome affects an estimated 64 million US adults based on estimates from the National Health and Nutrition Examination Survey (NHANES) (2). The metabolic syndrome is characterized by abdominal obesity and insulin resistance along with elevated blood pressure, dyslipidemia, and elevated plasma glucose (1,3). Clinical approaches to the prevention and management of metabolic risk include weight reduction by increasing physical activity and decreasing caloric intake through a low saturated and total fat diet (3). Low-fat, high-carbohydrate diets can result in hyperglycemia and increased insulin demand, depending on the quality and quantity of the carbohydrate (4); there-

© 2010 by the American Dietetic Association

fore, it is important to consider the glycemic response induced by increases in carbohydrate intake. The glycemic index was developed as a measure of carbohydrate quality (5). Glycemic load is the product of dietary glycemic index and carbohydrate per serving of food (6) and is, therefore, a measure of the quality and quantity of carbohydrate in the diet. Research on the effect of glycemic index and/or glycemic load on metabolic syndrome and its components has been inconsistent. Several observational and experimental studies have reported an inverse association between glycemic index and/or glycemic load and high-density lipoprotein cholesterol (HDL-C) (7-14) and a positive association with triglycerides (9,10,13), but did not examine metabolic syndrome as an outcome. Culberson and colleagues found no association between metabolic syndrome and glycemic load, but reported an inverse association between glycemic load and HDL-C (15), while Esposito and colleagues reported a reduction in the prevalence of metabolic syndrome in participants on a Mediterranean-type diet, but did not study glycemic index or glycemic load specifically (16). In addition to conflicting results, previous studies failed to account for objectively measured cardiorespiratory fitness, which has been shown to have an inverse association with the prevalence of metabolic syndrome (17-23). Therefore, to address the hypothesis that higher levels of glycemic index and glycemic load are directly associated with prevalence of the metabolic syndrome and its components, this study examines the cross-sectional associations between glycemic index, glycemic load, and the metabolic syndrome and its components with adjustment for cardiorespiratory fitness, an objective and reliable measure of recent physical activity habits, and other potential confounding factors in women and men enrolled in the Cooper Center Longitudinal Study. METHODS Participants The Cooper Center Longitudinal Study is a prospective cohort study of men and women who received a comprehensive medical examination at the Cooper Clinic, a preventive health clinic in Dallas, TX. The cohort consists of predominantly non-Hispanic whites (⬎95%) who are well-educated and employed or formerly employed in professional occupations and are generally self-referred to the clinic. Included in the current analysis were patients ages 20 to 79 years who visited the clinic from October 1987 to March 1999 and completed a 3-day dietary record as part of their medical examination. Participants were excluded from the study if they reported a personal history of diabetes or undiagnosed diabetes based on fasting blood glucose level ⬎125 mg/dL (6.9 mmol/L) (n⫽487); cardiovascular disease (n⫽196); cancer (n⫽659); were missing data on the metabolic syndrome variables (n⫽1,735); did not achieve 85% of their age-predicted maximal heart rate during treadmill exercise testing, an indication of an underlying disease process (n⫽399); reported excessively high (⬎6,000 kcal for men; ⬎5,000 kcal for women) or low (⬍600 kcal for men; ⬍500 kcal for women) energy intake (n⫽24) (21); or implausible glycemic load values (⬍5) after energy adjustment (n⫽16). This resulted in 9,137 men and 1,775 women for the

current analysis. The Cooper Center Longitudinal Study was reviewed and approved annually by The Cooper Institute Institutional Review Board. Clinical Examination Clinical examinations were completed after a 12-hour fast and were conducted by trained clinical personnel according to the Cooper Clinic’s standardized manual of operations. The details of the examination have been described in detail elsewhere (24). Briefly, a standardized medical history questionnaire was used to obtain information pertaining to personal and family health histories, personal health habits, and demographic information. Height and weight were measured in light clothing and without shoes using a standard clinical scale and stadiometer. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Waist girth was measured at the level of the umbilicus with a plastic anthropometric tape. Seated resting blood pressure was obtained with a mercury sphygmomanometer using the American Heart Association protocol (25). Fasting venous blood was assayed for serum cholesterol and triglycerides, HDL-C, and glucose using automated techniques at the Cooper Clinic Laboratory following the standards of the US Centers for Disease Control and Prevention Lipid Standardization Program (24-26). During their medical examination, participants completed a symptom-limited maximal treadmill exercise test using a modified-Balke protocol. Cardiorespiratory fitness was quantified as the total duration (minutes) of exercise. Details about specific speed and grade of each exercise stage have been described previously (24). Treadmill test duration is strongly correlated with measured maximal oxygen uptake in men (r⫽0.92) (27) and women (r⫽0.94) (28). Age- and sex-specific distributions of treadmill duration were computed for the following age groups: 20 to 39, 40 to 49, 50 to 59, and 60 to 79 years. Each sex- and age-specific distribution was divided into thirds of cardiorespiratory fitness to provide tertiles of fitness. Dietary Assessment As part of their medical examination, participants had the option to complete a 3-day diet record and have their diets analyzed and evaluated by a registered dietitian. The 3-day diet recording methods used in the Cooper Center Longitudinal Study have been described previously (29). Briefly, before their clinic visit, participants were mailed forms to record their food intake on 2 weekdays and 1 weekend day. The registered dietitians provided written detailed instructions and two-dimensional food models to help participants accurately record food intake and portion sizes. Participants were asked to bring the completed forms to their scheduled visit with the clinic registered dietitian. Nutrient analysis of the 3-day diet record data collected between 1987 and 1999 was performed using the Food Intake Analysis System (versions 3.0 and 3.9, 1996, 2000, University of Texas-Houston School of Public Health). The Food Intake Analysis System uses the US Department of Agriculture Survey Nutrient Database and pro-

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vides nutrient intake information for more than 50 nutrients. To account for missing data during analysis of the diet record data, adjusted standard portion sizes were used in place of missing portion sizes (30). To ascertain information on specific foods eaten, the diet record data was linked to the US Department of Agriculture Pyramid Servings database (31). This provided complete nutrient intakes and US Department of Agriculture Food Pyramid servings data for the 3-day diet records. For each participant, average dietary glycemic index was calculated. The glycemic index is a quantitative measure of a food based on the incremental blood glucose response and insulin demand for a given amount of carbohydrate. For these calculations, the 3-day diet record food list of 1,354 foods was linked to available glycemic index tables (32-34). Dietary glycemic index was calculated for each participant using the following formula: Glycemic indexday ⫽ 兺 (carbohydrate content of food ⫻ glycemic index of food)/共total amount of carbohydrate) Average dietary glycemic index for each participant was calculated as the mean of the 3 days of glycemic index. Dietary glycemic load was calculated for each participant using the following formula: Glycemic loadday ⫽ 兺 (Carbohydrate content of food ⫻ glycemic index of food)/100 The mean of the 3 days of glycemic load was calculated and represents the average dietary glycemic load for each participant. Each unit of glycemic load represents the equivalent blood glucose raising effect of 1 g pure glucose. To adequately control for total energy intake, the residuals method was used to adjust for all nutrients along with glycemic index and glycemic load (35). Metabolic Syndrome Prevalent metabolic syndrome and its components as defined by the revised Adult Treatment Panel III criteria were the primary outcome measures examined in the current study. In 2004, a revision of the glucose criterion of the metabolic syndrome was announced, lowering the cut-point from ⱖ110 mg/dL (6.1 mmol/L) to ⱖ100 mg/dL (5.6 mmol/L) (36). Participants were considered to have prevalent metabolic syndrome if they met three or more of the following criteria for metabolic syndrome (37): elevated waist circumference (waist girth: ⱖ102 cm [40 inches] for men or ⱖ88 cm [35 inches] for women), elevated triglycerides (ⱖ150 mg/dL [1.7 mmol/L]); reduced HDL-C (⬍40 mg/dL [1.03 mmol/L] for men, ⬍50 mg/dL [1.3 mmol/L] for women); elevated blood pressure (ⱖ130 mm Hg systolic or ⱖ85 mm Hg diastolic, or self-reported hypertension); and elevated fasting glucose (ⱖ100 mg/dL [5.6 mmol/L]). Statistical Methods Baseline characteristics for the participants stratified by metabolic syndrome status and sex were calculated. Analysis of variance was used to examine differences in continuous data. Mantel Hanzel ␹2 tests and Fisher exact

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tests were used to examine differences in categorical variables. Logistic regression models were used to estimate sex-specific odds ratios (OR) and 95% confidence intervals (CI) to evaluate the association between glycemic index, glycemic load, and prevalent metabolic syndrome and its components while adjusting for potential confounding variables. In the first model, age (years) and examination year were included as covariates. The second multivariate model included age, examination year, smoking history (never, past, current), alcohol intake (nondrinker, 1 to 7 drinks/week, 8 to 14 drinks/week, ⬎14 drinks/week), energy intake (continuous), percentage of calories from total fat in glycemic index models only (continuous), percentage of calories from protein in glycemic index models only (continuous), and energy-adjusted fiber (continuous) as covariates. In the analysis of elevated triglycerides, low HDL-C, high blood pressure, and elevated glucose, BMI is also included in the multivariate model due to its strong association with the exposure and outcome variables. The final multivariate model included all variables from the previous model and tertiles of cardiorespiratory fitness to examine the effect of fitness on the association between metabolic syndrome and glycemic index and glycemic load. Effect modification across tertiles of fitness was tested using the cross products of glycemic index or glycemic load variables and fitness as the interaction variable in the model. All P values presented are twosided, and P⬍0.05 was considered statistically significant. All analyses were performed using SAS (version 9.1, 2002, SAS Institute, Cary, NC). RESULTS The prevalence of metabolic syndrome in men was 24% (n⫽2,211) compared to 9% (n⫽153) in women (Table 1). Energy-adjusted glycemic index was higher in men with metabolic syndrome compared to men without metabolic syndrome (P⬍0.0001), whereas the opposite was observed for glycemic load with lower values (P⬍0.0001) reported in men with metabolic syndrome compared to men without metabolic syndrome. There was no observed difference in glycemic index or glycemic load for women. In general, men and women with metabolic syndrome were older, had higher values for BMI, waist girth, systolic and diastolic blood pressure, low-density lipoprotein cholesterol, triglycerides, and glucose, and lower values for HDL-C and cardiorespiratory fitness. Multivariate logistic regression was used to quantify the strength of association between energy-adjusted glycemic index and metabolic syndrome and its components by sex (Table 2). After adjustment for age and examination year, men in the highest quintile of glycemic index had increased odds of prevalent metabolic syndrome (OR⫽1.32; 95% CI⫽1.13 to 1.54) compared to men in the lowest quintile of glycemic index. This association was also observed for the components of the metabolic syndrome with the exception of high blood pressure and elevated glucose. A substantial inverse association was observed between glycemic index and elevated glucose. After multivariate adjustment, men in the upper quintiles of glycemic index had increased odds of metabolic syndrome, large waist girth, elevated triglycerides, and low HDL-C, with a significant trend seen across quintiles (P⬍0.05 for all). Adding cardiorespiratory fitness to the

Table 1. Baseline characteristics by metabolic syndrome status for 9,137 men and 1,775 women in the Cooper Center Longitudinal Study, 1987-1999 Men (nⴝ9,137) Metabolic syndrome

Energy-adjusted glycemic index Energy-adjusted glycemic load Age (y) BMIb Waist girth (cm) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Total cholesterol (mg/dL)c LDL-Cd (mg/dL)c HDL-Ce (mg/dL)c Triglycerides (mg/dL)f Glucose (mg/dL)g Central obesityh High blood pressurei Low HDL-Cj High triglyceridesk High fasting glucosel Smoking Never Past Current Alcohol intake Nondrinker 1-7 drinks/week 8-14 drinks/week ⬎14 drinks/week Time on treadmill (min) Energy intake (kcal/day) Carbohydrate (% of energy) Total fat (% of energy) Protein (% of energy) Energy-adjusted fiber (g/day)

Women (nⴝ1,775)

No metabolic syndrome

P value

4™™™™™™™™™ n (%) ™™™™™™™™™3 2,211 (24.2) 6,926 (75.8) 4™™™™™™™ mean⫾SDa ™™™™™™™3 54.9⫾4.6 54.2⫾4.8 140.5⫾33.2 145.2⫾34.2 47.5⫾9.4 46.6⫾10.2 29.5⫾4.1 25.4⫾2.9 103.1⫾11.5 90.7⫾8.5 128.3⫾13.4 119.8⫾12.6 87.1⫾9.3 79.7⫾8.7 220.7⫾40.5 205.1⫾39.0 140.1⫾38.0 133.7⫾35.4 38.1⫾9.4 50.8⫾12.7 212.8⫾116.7 102.7⫾59.0 103.9⫾8.0 96.9⫾8.0 4™™™™™™™™™ n (%) ™™™™™™™™™3 1,274 (57.6) 561 (8.1) 1,665 (75.3) 2,186 (31.6) 1,491 (67.4) 1,112 (16.1) 1,661 (75.1) 901 (13.0) 1,645 (74.4) 2,234 (32.3) 1,059 (47.9) 823 (37.2) 329 (14.9)

3,794 (54.8) 2,320 (33.5) 812 (11.7)

1,035 (46.8) 3,133 (45.2) 874 (39.5) 2,908 (42.0) 175 (7.9) 601 (8.7) 127 (5.7) 284 (4.1) 4™™™™™™™™ mean⫾SD ™™™™™™™™3 15.8⫾4.1 20.2⫾4.6 2,275.4⫾655.7 2,270.9⫾643.9 45.0⫾9.4 47.0⫾9.8 34.5⫾7.5 33.2⫾7.6 18.6⫾3.9 18.2⫾3.9 21.2⫾8.0 24.1⫾10.1

Metabolic syndrome

No metabolic syndrome

⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001

4™™™™™™™™™ n (%) ™™™™™™™™™3 153 (8.6) 1,622 (91.4) 4™™™™™™™ mean⫾SD ™™™™™™™3 53.4⫾6.3 53.1⫾5.9 114.6⫾25.5 115.1⫾26.6 50.6⫾9.5 45.4⫾10.4 30.8⫾6.0 23.0⫾4.0 92.3⫾12.9 72.9⫾19.5 128.4⫾14.3 112.6⫾13.8 84.7⫾9.8 75.2⫾9.2 221.4⫾41.9 197.8⫾37.8 137.4⫾38.5 114.8⫾33.6 46.9⫾11.2 65.5⫾15.9 185.6⫾93.9 87.3⫾49.3 103.6⫾7.7 93.5⫾7.6 4™™™™™™™™™ n (%) ™™™™™™™™™3 104 (68.0) 96 (5.9) 106 (69.3) 299 (18.4) 107 (69.9) 239 (14.7) 103 (67.3) 139 (8.6) 116 (75.8) 328 (20.2)

⬍0.0001

109 (71.2) 38 (24.8) 6 (3.9)

⬍0.0001 ⬍0.0001 0.0004 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001

0.63 ⬍0.0001 0.78 ⬍0.0001 ⬍0.0001 0.0009 ⬍0.0001

1,052 (64.9) 472 (29.1) 98 (6.0)

101 (66.0) 962 (59.3) 44 (28.8) 541 (33.4) 6 (3.9) 86 (5.3) 2 (1.3) 33 (2.0) 4™™™™™™™™ mean⫾SD ™™™™™™™™3 10.4⫾3.9 14.7⫾4.5 1,743.6⫾497.6 1,700.8⫾468.1 49.4⫾9.7 49.9⫾10.2 32.7⫾7.8 31.6⫾8.0 18.3⫾4.0 18.0⫾4.1 19.1⫾8.4 20.0⫾8.6

P value

0.45 0.84 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001

0.09

0.49 ⬍0.0001 0.28 0.60 0.08 0.26 0.18

a

SD⫽standard deviation. BMI⫽body mass index; calculated as kg/m2. c To convert mg/dL cholesterol to mmol/L, multiply mg/dL by 0.026. To convert mmol/L cholesterol to mg/dL, multiply mmol/L by 38.7. Cholesterol of 193 mg/dL⫽5.00 mmol/L. d LDL-C⫽low-density lipoprotein cholesterol. e HDL-C⫽high-density lipoprotein cholesterol. f To convert mg/dL triglycerides to mmol/L, multiply mg/dL by 0.0113. To convert mmol/L triglycerides to mg/dL, multiply mmol/L by 88.6. Triglycerides of 159 mg/dL⫽1.80 mmol/L. g To convert mg/dL glucose to mmol/L, multiply mg/dL by 0.0555. To convert mmol/L glucose to mg/dL, multiply mmol/L by 18.0. Glucose of 108 mg/dL⫽6.0 mmol/L. h Central obesity: waist girthⱖ102 cm (40 inches) for men or ⱖ88 cm (35 inches) for women. i High blood pressure: ⱖ130 mm Hg systolic or ⱖ85 mm Hg diastolic, or self-reported hypertension. j Low HDL-C: ⬍40 mg/dL (1.04 mmol/L) for men, 50 mg/dL (⬍1.3 mmol/L) for women. k High triglycerides: ⱖ150 mg/dL (1.7 mmol/L). l High fasting glucose: ⱖ100 mg/dL (5.6 mmol/L). b

multivariate model slightly attenuated the associations observed in the previous model, but a notable trend remained across quintiles of glycemic index for metabolic syndrome, elevated triglycerides, and low HDL-C. The addition of fitness to the model did eliminate the trend

observed between glycemic index and the waist girth component of the metabolic syndrome in men (P for trend⫽0.31). A significant interaction was observed between glycemic index and fitness with the blood pressure component as the outcome variable (P⫽0.03). After fur-

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Table 2. Odds ratios and 95% confidence intervals for the association between metabolic syndrome and its individual components and energy-adjusted glycemic index in 9,137 men and 1,775 women in the Cooper Center Longitudinal Study, 1987-1999 Energy-Adjusted Glycemic Index Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

P value for trenda

4™™™™™™™™™™™™™™™™™™™™™™™™™™™™™ n (mean⫾standard deviation) ™™™™™™™™™™™™™™™™™™™™™™™™™™™™3 1,827 (47.7⫾4.4) 1,828 (52.5⫾0.7) 1,828 (54.7⫾0.6) 1,827 (56.8⫾0.7) 1,827 (60.3⫾2.0) 4™™™™™™™™™™™™™™™™™™™™™™™™™™™ odds ratio (95% confidence interval) ™™™™™™™™™™™™™™™™™™™™™™™™™3

Men Metabolic syndromeb Age, examination-year adjusted Multivariate adjustedc Multivariate⫹cardiorespiratory fitnessd Large waist girth Age, examination-year adjusted Multivariate adjustedc Multivariate⫹cardiorespiratory fitnessd Elevated triglycerides Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd Low HDL-Cf Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd High blood pressure Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd Elevated fasting glucose Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd Women Metabolic syndromeb Age, examination-year adjusted Multivariate adjustedc Multivariate⫹cardiorespiratory fitnessd Large waist girth Age, examination-year adjusted Multivariate adjustedc Multivariate⫹cardiorespiratory fitnessd Elevated triglycerides Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd Low HDL-C Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd High blood pressure Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd Elevated fasting glucose Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd

1.0 1.0 1.0

1.11 (0.94-1.30) 1.12 (0.95-1.32) 1.08 (0.91-1.29)

1.22 (1.05-1.44) 1.22 (1.04-1.44) 1.16 (0.98-1.38)

1.38 (1.18-1.62) 1.36 (1.16-1.60) 1.27 (1.07-1.50)

1.32 (1.13-1.54) 1.27 (1.08-1.50) 1.13 (0.95-1.35)

⬍0.0001 0.0005 0.05

1.0 1.0 1.0

0.98 (0.83-1.17) 1.03 (0.87-1.23) 0.98 (0.81-1.18)

1.12 (0.95-1.33) 1.18 (0.99-1.40) 1.10 (0.92-1.33)

1.12 (0.95-1.32) 1.15 (0.97-1.36) 1.02 (0.85-1.23)

1.23 (1.04-1.45) 1.27 (1.07-1.51) 1.09 (0.91-1.31)

0.005 0.003 0.31

1.0 1.0 1.0

1.21 (1.04-1.41) 1.23 (1.05-1.44) 1.21 (1.03-1.42)

1.28 (1.10-1.48) 1.26 (1.08-1.48) 1.23 (1.04-1.44)

1.38 (1.19-1.61) 1.37 (1.17-1.61) 1.31 (1.11-1.54)

1.47 (1.27-1.71) 1.38 (1.18-1.62) 1.30 (1.11-1.53)

⬍0.0001 ⬍0.0001 0.001

1.0 1.0 1.0

1.45 (1.24-1.68) 1.41 (1.21-1.66) 1.40 (1.19-1.65)

1.45 (1.25-1.69) 1.38 (1.18-1.62) 1.34 (1.14-1.58)

1.64 (1.41-1.91) 1.57 (1.35-1.84) 1.52 (1.30-1.78)

1.65 (1.42-1.92) 1.54 (1.31-1.81) 1.47 (1.25-1.73)

⬍0.0001 ⬍0.0001 ⬍0.0001

1.0 1.0 1.0

0.88 (0.77-1.01) 0.89 (0.77-1.02) 0.88 (0.77-1.01)

0.93 (0.82-1.06) 0.93 (0.81-1.07) 0.92 (0.80-1.05)

1.00 (0.87-1.14) 0.99 (0.87-1.14) 0.98 (0.85-1.12)

0.93 (0.82-1.07) 0.90 (0.78-1.03) 0.87 (0.76-1.01)

0.72 0.38 0.21

1.0 0.82 (0.72-0.94) 0.74 (0.65-0.85) 0.88 (0.77-1.00) 0.80 (0.70-0.91) 1.0 0.86 (0.75-0.98) 0.77 (0.67-0.88) 0.90 (0.78-1.04) 0.78 (0.68-0.90) 1.0 0.85 (0.74-0.98) 0.76 (0.66-0.88) 0.89 (0.78-1.03) 0.77 (0.67-0.89) 4™™™™™™™™™™™™™™™™™™™™™™™™™™™™™ n (mean⫾standard deviation) ™™™™™™™™™™™™™™™™™™™™™™™™™™™™3 355 (44.4⫾5.5) 355 (51.1⫾1.0) 355 (53.8⫾0.7) 355 (56.2⫾0.7) 355 (60.1⫾2.1) 4™™™™™™™™™™™™™™™™™™™™™™™™™™™ odds ratio (95% confidence interval) ™™™™™™™™™™™™™™™™™™™™™™™™™3

0.004 0.003 0.002

1.0 1.0 1.0

0.94 (0.54-1.63) 0.93 (0.52-1.63) 0.92 (0.52-1.65)

0.94 (0.54-1.63) 1.01 (0.57-1.78) 0.95 (0.53-1.70)

1.13 (0.67-1.93) 1.20 (0.68-2.13) 1.15 (0.64-2.05)

1.33 (0.79-2.25) 1.43 (0.80-2.56) 1.28 (0.71-2.31)

0.24 0.17 0.35

1.0 1.0 1.0

0.89 (0.54-1.46) 0.83 (0.49-1.39) 0.82 (0.48-1.40)

1.02 (0.63-1.66) 1.06 (0.64-1.76) 0.99 (0.59-1.67)

1.21 (0.75-1.94) 1.26 (0.76-2.10) 1.22 (0.72-2.05)

1.59 (1.00-2.52) 1.74 (1.04-2.89) 1.58 (0.93-2.67)

0.03 0.02 0.05

1.0 1.0 1.0

0.74 (0.46-1.20) 0.71 (0.43-1.18) 0.72 (0.43-1.20)

1.23 (0.79-1.91) 1.25 (0.78-2.03) 1.25 (0.78-2.00)

1.40 (0.91-2.18) 1.38 (0.86-2.22) 1.38 (0.86-2.22)

1.49 (0.96-2.31) 1.40 (0.86-2.28) 1.37 (0.84-2.23)

0.01 0.04 0.05

1.0 1.0 1.0

1.10 (0.71-1.69) 1.04 (0.66-1.65) 1.05 (0.66-1.66)

1.46 (0.96-2.20) 1.35 (0.87-2.11) 1.35 (0.86-2.10)

1.99 (1.34-2.96) 1.71 (1.10-2.64) 1.70 (1.10-2.63)

2.56 (1.73-3.78) 2.13 (1.37-3.31) 2.09 (1.35-3.25)

⬍0.0001 ⬍0.0001 0.0001

1.0 1.0 1.0

1.18 (0.82-1.71) 1.25 (0.82-1.83) 1.24 (0.85-1.82)

1.10 (0.76-1.60) 1.13 (0.77-1.67) 1.12 (0.76-1.66)

1.28 (0.89-1.86) 1.25 (0.84-1.86) 1.25 (0.84-1.86)

1.07 (0.73-1.57) 0.99 (0.65-1.50) 0.98 (0.64-1.49)

0.56 0.94 0.99

1.0 1.0 1.0

1.04 (0.73-1.49) 1.05 (0.72-1.51) 1.05 (0.72-1.52)

1.27 (0.90-1.80) 1.25 (0.87-1.80) 1.25 (0.87-1.80)

1.17 (0.83-1.67) 1.10 (0.75-1.61) 1.10 (0.75-1.61)

1.16 (0.81-1.66) 1.05 (0.71-1.54) 1.05 (0.71-1.55)

0.30 0.71 0.71

a

Tests for linear trend using the median value for each quintile. Metabolic syndrome defined as meeting three or more of the following criteria: elevated waist circumference (waist girth: ⱖ102 cm [40 inches] for men or ⱖ88cm [35 inches] for women), elevated triglycerides (ⱖ150 mg/dL [1.7 mmol/L]); reduced HDL-C (⬍40 mg/dL [1.03 mmol/L] for men, ⬍50 mg/dL [1.3 mmol/L] for women); elevated blood pressure (ⱖ130 mm Hg systolic or ⱖ85 mm Hg diastolic, or self-reported hypertension); and elevated fasting glucose (ⱖ100 mg/dL [5.6 mmol/L]). c Multivariate adjusted model includes age (continuous), examination year, smoking (never, past, current), alcohol intake (nondrinker, 1-7 drinks/week; 8-14 drinks/week; ⬎14 drinks/week), protein (% of kcal, continuous), total fat (% of kcal, continuous), energy adjusted fiber (continuous), energy intake (continuous). d Multivariate⫹cardiorespiratory fitness model contains all variables in the multivariate adjusted model and tertiles of cardiorespiratory fitness using time on treadmill. e Multivariate adjusted model includes all variables from footnote c and body mass index (⬍25; 25-29.9, ⬎30). f HDL-C⫽high-density lipoprotein cholesterol. b

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ther examination of the association between glycemic index and the blood pressure component stratified by tertiles of cardiorespiratory fitness, men in the high fitness category showed an inverse association between glycemic index and high blood pressure (P for trend⫽ 0.0009), while a nonsignificant trend was observed for a positive association in the low fitness category (P for trend⫽0.43). Although glycemic index was not significantly associated with prevalent metabolic syndrome (Q5: OR⫽1.33; 95% CI⫽0.79 to 2.25) in women, higher glycemic index levels were associated with increased odds of large waist girth, elevated triglycerides, and low HDL-C after adjustment by age and examination year (Table 2). After multivariate adjustment, the associations between elevated triglycerides and glycemic index approached significance in the upper quintiles, with a statistically significant trend across quintiles (P for trend⫽0.04). Women in the highest quintile of glycemic index had increased odds of having a large waist girth (Q5: OR⫽1.74; 95% CI⫽1.04 to 2.89) and low HDL-C (Q5: OR⫽2.13; 95% CI⫽1.37 to 3.31), even after multivariate adjustment. The addition of fitness to the multivariate model did not substantially change the pattern or strength of association observed between glycemic index and prevalence of the waist girth or HDL-C component of metabolic syndrome. Men in the highest quintile of glycemic load had decreased odds of prevalent metabolic syndrome, large waist girth, elevated triglycerides, high blood pressure, and elevated glucose, and increased odds for low HDL-C compared to men in the lowest quintile of glycemic load after adjustment for age and exam year (Table 3). After multivariate adjustment, the inverse association between metabolic syndrome, large waist girth, and elevated glucose and glycemic load remained significant (P for trend⬍0.05 for all). Glycemic load was positively associated with elevated triglycerides (P for trend⫽0.003) and low HDL-C (P for trend⬍0.0001) in the multivariate model. After cardiorespiratory fitness was added to the model, the positive associations with elevated triglycerides and low HDL-C and the inverse associations with elevated glucose remained significant (P for trend⬍0.0001 for all). Among women, there was no observed association between glycemic load and prevalent metabolic syndrome or its components with the exception of low HDL-C (Q5 OR⫽3.02; 95% CI⫽2.03 to 4.49) after age- and examination-year adjustment (Table 3). This pattern was also observed after multivariate adjustment and adjustment for cardiorespiratory fitness, although the positive trend between glycemic load and elevated triglycerides approached significance in the multivariate model (P⫽0.06) and was statistically significant in the cardiorespiratory fitness model (P⫽0.04). In the multivariate-adjusted model including cardiorespiratory fitness as a covariate, the odds ratio for the prevalence of the low HDL-C component was 3.91 (95% CI⫽2.47 to 6.18) for the highest quintile of glycemic load compared to the lowest quintile of glycemic load (P for trend⬍0.0001). DISCUSSION Results from this large epidemiological study of men and women showed that glycemic index was positively

associated with the prevalence of metabolic syndrome, elevated triglycerides, and low HDL-C and inversely associated with high glucose in men independent of cardiorespiratory fitness and other potential confounders. In women, glycemic index was also positively associated with elevated triglycerides, large waist girth, and low HDL-C after multivariate adjustment. In the study, glycemic load was not associated with prevalent metabolic syndrome, but there was a positive association between glycemic load and both elevated triglycerides and low HDL-C in men and women after adjustment for potential confounders including cardiorespiratory fitness. Although several studies have examined the relations between glycemic index, glycemic load, metabolic syndrome, and its components, this study was unique in that it included men and women to allow for sex-specific analyses, a 3-day dietary record of specific foods consumed, a maximal treadmill exercise test as an objective measure of cardiorespiratory fitness, a comprehensive medical examination, and a thorough medical history questionnaire.

An unexpected finding of the study was the inverse association between glycemic index, glycemic load, and glucose in men. In 2004, Ford and colleagues reported the prevalence of metabolic syndrome in the NHANES III population to be 25% in men and 23% in women using the revised Adult Treatment Panel III definition (2). The sample of men in this study had a similar prevalence of metabolic syndrome (24%) to the national sample using the same criteria for metabolic syndrome, but women in the Cooper Center Longitudinal Study had a 14% lower prevalence of metabolic syndrome than women in the NHANES III study (23% in NHANES III vs 9% in Cooper Center Longitudinal Study). Men and women in the present study showed similar patterns of association even with the much lower prevalence of metabolic syndrome in women from the Cooper Center Longitudinal Study. Previous studies of the Cooper Center Longitudinal Study cohort found these women to be relatively healthy with a lower incidence of hypertension (38), lower rates of cardiovascular disease (39), lower prevalence of overweight and obesity (40), and lower prevalence of metabolic syndrome (23) compared to other national samples (2,41-43). One strength of the present study was that both glycemic index and glycemic load were included as exposure variables and the metabolic syndrome and all components of the syndrome were included as outcomes in separate analyses that also included an objective measure of cardiorespiratory fitness as a potential confounder. McKeown and colleagues observed a positive association between glycemic index and metabolic syndrome (Q5: OR⫽1.41; 95% CI⫽1.04 to 1.91) in men and women in pooled analyses after multivariate adjustment including self-reported physical activity (44). A significant trend was observed across quintiles of glycemic index and metabolic syndrome among Cooper Center Longitudinal Study men in the present study, but the

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1825

Table 3. Odds ratio and 95% confidence intervals for the association between metabolic syndrome and its individual components and energy-adjusted glycemic load in 9,137 men and 1,775 women in the Cooper Center Longitudinal Study, 1987-1999 Energy-Adjusted Glycemic Load Quintile 1

Quintile 2

Quintile 3

Quintile 4

Quintile 5

P value for trenda

4™™™™™™™™™™™™™™™™™™™™™™™™™™™™™™ n (mean⫾standard deviation) ™™™™™™™™™™™™™™™™™™™™™™™™™™™™™™3 1,828 (99.0⫾18.3) 1,827 (127.1⫾5.1) 1,827 (143.1⫾4.4) 1,828 (159.2⫾5.3) 1,827 (191.8⫾23.3) 4™™™™™™™™™™™™™™™™™™™™™™™™™™™ odds ratio (95% confidence interval) ™™™™™™™™™™™™™™™™™™™™™™™™™™™3

Men Metabolic syndromeb Age, examination-year adjusted Multivariate adjustedc Multivariate⫹cardiorespiratory fitnessd Large waist girth Age, examination-year adjusted Multivariate adjustedc Multivariate⫹cardiorespiratory fitnessd Elevated triglycerides Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd Low HDL-Cf Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd High blood pressure Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd Elevated fasting glucose Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd Women Metabolic syndromeb Age, examination-year adjusted Multivariate adjustedc Multivariate⫹cardiorespiratory fitnessd Large waist girth Age, examination-year adjusted Multivariate adjustedc Multivariate⫹cardiorespiratory fitnessd Elevated triglycerides Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd Low HDL-C Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd High blood pressure Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd Elevated fasting glucose Age, examination-year adjusted Multivariate adjustede Multivariate⫹cardiorespiratory fitnessd

1.0 1.0 1.0

0.94 (0.81-1.09) 1.05 (0.91-1.23) 1.09 (0.93-1.28)

0.66 (0.57-0.77) 0.80 (0.68-0.94) 0.86 (0.73-1.02)

0.70 (0.60-0.81) 0.90 (0.76-1.05) 1.00 (0.84-1.19)

0.60 (0.51-0.70) 0.85 (0.71-1.02) 1.08 (0.90-1.30)

⬍0.0001 0.02 0.77

1.0 1.0 1.0

0.86 (0.74-1.00) 0.95 (0.81-1.11) 0.97 (0.82-1.15)

0.60 (0.51-0.70) 0.71 (0.60-0.84) 0.77 (0.64-0.92)

0.52 (0.44-0.61) 0.65 (0.55-0.78) 0.71 (0.59-0.86)

0.38 (0.32-0.46) 0.52 (0.43-0.63) 0.64 (0.52-0.79)

⬍0.0001 ⬍0.0001 ⬍0.0001

1.0 1.0 1.0

1.00 (0.87-1.15) 1.14 (0.98-1.33) 1.16 (0.99-1.35)

0.76 (0.66-0.88) 0.99 (0.85-1.16) 1.04 (0.88-1.22)

0.80 (0.69-0.92) 1.14 (0.97-1.34) 1.19 (1.01-1.41)

0.76 (0.66-0.88) 1.34 (1.13-1.59) 1.50 (1.25-1.79)

⬍0.0001 0.003 ⬍0.0001

1.0 1.0 1.0

1.23 (1.06-1.43) 1.23 (1.05-1.45) 1.25 (1.07-1.47)

1.29 (1.11-1.50) 1.43 (1.22-1.68) 1.50 (1.27-1.76)

1.54 (1.33-1.79) 1.77 (1.50-2.08) 1.86 (1.58-2.19)

1.60 (1.38-1.86) 2.02 (1.70-2.39) 2.27 (1.90-2.70)

⬍0.0001 ⬍0.0001 ⬍0.0001

1.0 1.0 1.0

0.84 (0.74-0.96) 0.91 (0.79-1.04) 0.91 (0.79-1.05)

0.65 (0.57-0.74) 0.75 (0.65-0.86) 0.76 (0.66-0.87)

0.76 (0.66-0.87) 0.92 (0.80-1.06) 0.93 (0.81-1.08)

0.67 (0.58-0.76) 0.91 (0.78-1.06) 0.93 (0.80-1.08)

⬍0.0001 0.28 0.45

1.0 0.72 (0.63-0.83) 0.61 (0.53-0.70) 0.62 (0.55-0.71) 0.50 (0.43-0.57) 1.0 0.78 (0.68-0.90) 0.69 (0.60-0.80) 0.76 (0.66-0.88) 0.69 (0.59-0.80) 1.0 0.78 (0.68-0.90) 0.70 (0.60-0.80) 0.76 (0.66-0.88) 0.69 (0.59-0.81) 4™™™™™™™™™™™™™™™™™™™™™™™™™™™™™™ n (mean⫾standard deviation) ™™™™™™™™™™™™™™™™™™™™™™™™™™™™™™3 355 (78.8⫾14.8) 355 (102.3⫾3.7) 355 (114.6⫾3.5) 355 (127.7⫾4.3) 355 (151.7⫾16.0) 4™™™™™™™™™™™™™™™™™™™™™™™™™™™ odds ratio (95% confidence interval) ™™™™™™™™™™™™™™™™™™™™™™™™™™™3

⬍0.0001 ⬍0.0001 ⬍0.0001

1.0 1.0 1.0

0.99 (0.59-1.69) 1.03 (0.60-1.77) 1.03 (0.59-1.80)

0.80 (0.47-1.38) 0.83 (0.47-1.47) 0.82 (0.46-1.47)

1.00 (0.59-1.68) 1.08 (0.61-1.89) 1.17 (0.66-2.08)

0.90 (0.53-1.54) 0.94 (0.52-1.69) 1.08 (0.59-1.97)

0.74 0.89 0.72

1.0 1.0 1.0

0.94 (0.61-1.47) 1.06 (0.67-1.67) 1.07 (0.67-1.71)

0.67 (0.42-1.07) 0.78 (0.48-1.27) 0.77 (0.46-1.28)

0.62 (0.38-1.00) 0.76 (0.45-1.26) 0.81 (0.47-1.37)

0.82 (0.52-1.28) 0.97 (0.59-1.61) 1.15 (0.68-1.95)

0.16 0.62 0.89

1.0 1.0 1.0

0.86 (0.53-1.37) 0.91 (0.55-1.49) 0.90 (0.55-1.48)

1.10 (0.71-1.72) 1.35 (0.84-2.17) 1.37 (0.85-2.21)

1.30 (0.84-2.01) 1.59 (0.98-2.57) 1.64 (1.01-2.66)

1.20 (0.77-1.86) 1.38 (0.84-2.28) 1.46 (0.88-2.41)

0.16 0.06 0.04

1.0 1.0 1.0

1.46 (0.95-2.24) 1.55 (0.98-2.45) 1.55 (0.98-2.45)

1.62 (1.06-2.47) 1.95 (1.23-3.08) 1.96 (1.24-3.10)

2.07 (1.37-3.12) 2.48 (1.57-3.92) 2.53 (1.60-4.01)

3.02 (2.03-4.49) 3.71 (2.35-5.85) 3.91 (2.47-6.18)

⬍0.0001 ⬍0.0001 ⬍0.0001

1.0 1.0 1.0

0.99 (0.69-1.43) 1.08 (0.74-1.58) 1.09 (0.74-1.59)

0.91 (0.63-1.30) 1.06 (0.72-1.55) 1.05 (0.72-1.55)

0.64 (0.44-0.93) 0.72 (0.48-1.09) 0.73 (0.48-1.10)

0.92 (0.64-1.32) 1.09 (0.72-1.64) 1.11 (0.74-1.68)

0.22 0.82 0.90

1.0 1.0 1.0

0.87 (0.62-1.24) 0.97 (0.67-1.39) 0.97 (0.67-1.39)

0.83 (0.59-1.18) 1.02 (0.71-1.48) 1.02 (0.71-1.48)

0.92 (0.65-1.30) 1.17 (0.80-1.70) 1.16 (0.80-1.69)

0.82 (0.58-1.16) 1.08 (0.73-1.59) 1.07 (0.72-1.59)

0.34 0.52 0.54

a

Tests for linear trend using the median value for each quintile. Metabolic syndrome defined as meeting three or more of the following criteria: elevated waist circumference (waist girth: ⱖ102 cm [40 inches] for men or ⱖ88 cm [35 inches] for women), elevated triglycerides (ⱖ150 mg/dL [1.7 mmol/L]); reduced HDL-C (⬍40 mg/dL [1.03 mmol/L] for men, ⬍50 mg/dL [1.3 mmol/L] for women); elevated blood pressure (ⱖ130 mm Hg systolic or ⱖ85 mm Hg diastolic, or self-reported hypertension); and elevated fasting glucose (ⱖ100 mg/dL [5.6 mmol/L]). c Multivariate adjusted model includes age (continuous), examination year, smoking (never, past, current), alcohol intake (nondrinker, 1-7 drinks/week; 8-14 drinks/week; ⬎14 drinks/week), energy-adjusted fiber (continuous), energy intake (continuous). d Multivariate⫹cardiorespiratory fitness adjusted model contains all variables in the multivariate adjusted model and tertiles of cardiorespiratory fitness using time on treadmill. e Multivariate adjusted model includes all variables from footnote c and body mass index (⬍25; 25-29.9, ⬎30). f HDL-C⫽high-density lipoprotein cholesterol. b

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association was not statistically significant for women. Liu and colleagues found that glycemic index and glycemic load were inversely associated with HDL-C and positively associated with elevated triacylglycerols in postmenopausal women from the Nurses’ Health Study, but did not examine metabolic syndrome as an outcome (10). Although self-reported physical activity was included as a potential confounder in the analysis, these studies did not have an objective measure of cardiorespiratory fitness. The present analysis supports the HDL-C and triglycerides findings in men and women even after adjustment for cardiorespiratory fitness. Recent experimental studies of components of the metabolic syndrome support the inverse association between high glycemic diets and HDL-C (11,14,45) and the positive association with triglycerides observed in this study of the Cooper Center Longitudinal Study (13). Previous research shows that replacing dietary fat with dietary carbohydrate can result in substantial alterations in glucose and insulin metabolism. Over time, these substantial shifts in glucose and insulin responses from high-glycemic diets can contribute to insulin resistance, which is characterized by an increase in triglycerides and decrease in HDL-C (46-49). Diets with high glycemic index and glycemic load values are inherently high in carbohydrate, which may explain the associations observed between glycemic index, glycemic load, and the low HDL-C and elevated triglyceride component of the metabolic syndrome. An unexpected finding of the study was the inverse association between glycemic index, glycemic load, and glucose in men. Previous research from the Nurses’ Health Study and the Melbourne Collaborative Cohort Study has shown a positive association between glycemic index, glycemic load, and type 2 diabetes in men and women (6,50-52), although results from the Iowa Women’s Health Study and the Atherosclerosis Risk in Communities study showed no association between glycemic index and incidence of type 2 diabetes (53,54). In the present study, men and women with a history of diabetes and those who had elevated fasting blood glucose levels ⱖ125 mg/dL were excluded from the analysis, which makes it difficult to compare to previous research examining glycemic index, glycemic load, and type 2 diabetes. The findings from this study suggest that glycemic index and glycemic load are inversely associated with glucose levels in men with impaired fasting glucose, defined as fasting glucose levels from 100 mg/dL to 124 mg/dL (5.6 to 6.9 mmol/L), but more research is necessary to support these findings. A key finding from this study was that the positive associations observed between glycemic index and glycemic load and specific components of the metabolic syndrome in men and women were independent of cardiorespiratory fitness. Previous research in other study populations has shown that objectively measured cardiorespiratory fitness and self-reported physical activity are positively associated with metabolic syndrome (1820,22,55). Cardiorespiratory fitness was included as a potential confounding variable in the multivariate logistic regression model and a strong inverse association was observed between cardiorespiratory fitness and metabolic syndrome in men (metabolic syndrome: moderate fitness category: OR⫽0.38; 95% CI⫽0.34 to 0.42; high fitness

category: OR⫽0.11; 95% CI⫽0.09 to 0.13) and women (metabolic syndrome: moderate fitness category: OR⫽ 0.34; 95% CI⫽0.23 to 0.50; high fitness category: OR⫽0.24; 95% CI⫽0.15 to 0.37). These findings are consistent with previously published reports from the Cooper Center Longitudinal Study (17,21,23). The addition of cardiorespiratory fitness did attenuate the observed association between glycemic load and metabolic syndrome in men, suggesting that cardiorespiratory fitness is a strong confounding variable and should be included in analyses examining glycemic load and metabolic syndrome. Although cardiorespiratory fitness was inversely associated with prevalent metabolic syndrome in men and women, many of the associations between glycemic index, glycemic load, and several components of the metabolic syndrome remained significant after adjustment for cardiorespiratory fitness. This study does have several limitations to consider. In general, the sample from the Cooper Center Longitudinal Study is a homogeneous group of disease-free, upper middle-class white men and women who are self-referred to the Cooper Clinic. Although this does increase the internal validity of the study, it may limit the generalizability of the results to the general population. In addition, diet was measured from only 3 days of dietary records, which might not be sufficient to estimate usual intake and could result in an overestimation or underestimation of intake. Imputed values for glycemic index were used for a small percentage of foods (2%) because glycemic index values were not available for all foods in the database. Sufficient data on menopausal status and medication use was lacking, which inhibits the ability to examine their influence on the studied associations. The lack of data on the use of blood pressure⫺lowering medications in both men and women may explain the inconsistent findings between glycemic index, glycemic load, and the blood pressure component of the metabolic syndrome. Finally, the crosssectional study design allows for the report of associations between variables in the analysis, but does not allow for the determination of causality. CONCLUSIONS In this large epidemiologic study of 10,912 men and women, glycemic index was positively associated with prevalence of metabolic syndrome, elevated triglycerides, and low HDL-C and inversely associated with elevated glucose in men. Among women, glycemic index was also positively associated with elevated triglycerides and low HDL-C. A positive association between glycemic load and elevated triglycerides and low HDL-C was observed in men and women. Glycemic load was also inversely associated with large waist girth and elevated glucose in men. These associations were independent of cardiorespiratory fitness and other confounding variables. Although a cross-sectional study cannot prove a causal relation, findings from this study suggest that consuming a low glycemic index and glycemic load diet is associated with an improved metabolic risk profile. More prospective research studies are needed to further assess the association between glycemic index, glycemic load, and metabolic syndrome, while controlling for cardiorespiratory fitness.

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STATEMENT OF POTENTIAL CONFLICT OF INTEREST: No potential conflict of interest was reported by the authors. FUNDING/SUPPORT: The research presented in this manuscript was supported by private donations. ACKNOWLEDGEMENTS: The authors thank Dr Kenneth H. Cooper, MD, MPH, for establishing the Cooper Center Longitudinal Study; the Cooper Clinic registered dietitians for data collection; and Melba Morrow for editorial assistance.

18.

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