Nutritional risk and the metabolic syndrome in women: opportunities for preventive intervention from the Framingham Nutrition Study 1 3

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1 Nutritional risk and the metabolic syndrome in women: opportunities for preventive intervention from the Framingham Nutrition Study Barbara E Millen, Michael J Pencina, Ruth W Kimokoti, Lei Zhu, James B Meigs, Jose M Ordovas, and Ralph B D Agostino ABSTRACT Background: Diet is recognized as a key factor in the cause and management of the metabolic syndrome (MetS). However, policies to guide preventive clinical nutrition interventions of the condition are limited. Objectives: We examined the relation between dietary quality and incident MetS in adult women and identified foci for preventive nutrition interventions. Design: This was a prospective study of 00 healthy women (aged 0 69 y) in the Framingham Offspring-Spouse study who were free of MetS risk factors at baseline. The development of individual MetS traits and overall MetS status during y of follow-up were compared in women by tertile of nutritional risk, based on intake of 9 nutrients. Multivariate logistic regression models considered age, smoking, physical activity, and menopausal status. Results: Baseline age-adjusted mean nutrient intake and ischemic heart disease risk profiles differed by tertile of nutritional risk. Women with higher nutritional risk profiles consumed more dietary lipids (total, saturated, and monounsaturated fats) and alcohol and less fiber and micronutrients; they had higher cigarette use and waist circumferences. Compared with women with the lowest nutritional risk, those in the highest tertile had a - to -fold risk of the development of abdominal obesity and overall MetS during y of follow-up [odds ratio:. (95% CI:., 4.) and.0 (95% CI:., 7.6), respectively]. Conclusions: Higher composite nutritional risk predicts the development of abdominal obesity and MetS during long-term follow-up in healthy women, independent of lifestyle and ischemic heart disease risk factors. Preventive nutrition interventions for obesity and MetS risk reduction should focus on the overall nutritional quality of women s dietary profiles. Am J Clin Nutr 006;84:44 4. KEY WORDS Composite nutritional risk, dietary quality, ischemic heart disease risk, metabolic syndrome, abdominal obesity INTRODUCTION The metabolic syndrome (MetS), a clustering of metabolic risk factors including impaired fasting glucose, elevated blood pressure, low HDL cholesterol, elevated triacylglycerol, and abdominal obesity, affects 9% of American women ( 5). Diabetes risk increases 0-fold in women with MetS, and the development of ischemic heart disease (IHD) in women aged 65 y occurs primarily in those with MetS or multiple IHD risk factors (4, 6). An 8-y prospective study of women and men participating in the Framingham Offspring Study (6) showed that MetS accounted for one-fifth of IHD events and more than half of newly diagnosed type diabetes cases. MetS is thought to have a genetic basis, but environmental factors particularly obesity, physical inactivity, and diet are largely implicated in the cause of the syndrome (, 7, 8). The emergence of the current obesity epidemic (9) is likely to increase rates of MetS in the United States and cause higher rates of morbidity and mortality in women due to heart disease and diabetes (4, 5). MetS is identified as a target for secondary prevention in the National Cholesterol Education Program s Adult Treatment Panel III (NCEP ATP III; 4) in which emphasis is placed on improved nutrition, increased physical activity, and smoking cessation as central tenets of treatment. To date, however, epidemiologic research has provided only limited information to guide the development of targeted interventions, particularly preventive nutrition. This study examines the relation between dietary quality, by using a validated measure of composite nutritional risk, and the risk of development of MetS in healthy women aged 0 69 y during y of follow-up. Prospective multivariate analyses considered key diet and lifestyle factors, including physical activity and cigarette use, as well as biological and genetic covariates. SUBJECTS AND METHODS Participants For 50 y, the Framingham Study has investigated the natural progression of IHD and, more recently, other health problems From the Department of Family Medicine (BEM and RWK) and the Graduate Medical Sciences Division (BEM and RWK), Boston University School of Medicine, Boston, MA; the Department of Mathematics, Boston University, Boston, MA (MJP, LZ, and RBD); the General Internal Medicine Division, Department of Medicine, Massachusetts Hospital and Harvard Medical School, Boston, MA (JBM); and the Lipid Metabolism Laboratory, US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University School of Medicine, Boston, MA (JMO). Supported by grants R0-HL and R0-HL from the National Heart, Lung, and Blood Institute (NHLBI); N0-HC-595 from NHLBI, National Institutes of Health (to The Framingham Study); and by a Career Development Award from the American Diabetes Association (to JBM). Reprints not available. Address correspondence to BE Millen, Department of Family Medicine, Boston University School of Medicine, One Boston Medical Center Plaza, Dowling 5, Boston, MA bmillen@bu.edu. Received January, 006. Accepted for publication March 0, Am J Clin Nutr 006;84:44 4. Printed in USA. 006 American Society for Nutrition

2 NUTRITIONAL RISK AND THE METABOLIC SYNDROME 45 among residents of Framingham, MA (0; RB D Agostino, WB Kannel, unpublished observations, ). In 97, a second-generation cohort was recruited, and 54 Framingham Study offspring and their spouses (48 men and 64 women) were invited to participate in the Framingham Offspring-Spouse (FOS) study (). Members of the FOS study cohort participate approximately every 4 y in standardized clinical assessments, including a complete physical examination, laboratory tests, noninvasive diagnostic testing, and updating of medical histories and other pertinent information. At FOS study exam, in , we fully characterized the nutrient intake of the Framingham Offspring. At exam 4, , risk factor profiles of women in the FOS study were evaluated in a manner that allowed the full evaluation of MetS risk according to the most recent NCEP expert criteria. Women aged 8 76 y (n 005) participated at exam (8% of the original offspring cohort women), and 967 (48%) of these women provided complete data on baseline diet (exam ) and IHD risk factors (exam 4) during y of follow-up (through exam 7, ). Approximately one-third of these women (n 00) were completely free of any MetS characteristics at baseline. Baseline IHD and MetS risk factor profiles of subjects included in these analyses (n 00) did not differ from those of subjects who were not followed because of missing nutrition or covariate data (n 0), except that our sample was slightly older (48.6 compared with 46.5 y) and had lower smoking rates (4% compared with 8.6%). As shown in Table, women without MetS risk factors at baseline had age and physical activity profiles similar to those of women in the FOS study who had MetS risk factors. Dietary intakes did not differ for most nutrients; observed differences were generally 6% except alcohol consumption, which was low in both groups (.5% and.7%, respectively). However, the remaining IHD risk profiles of women without MetS risk were lower than those for women with MetS risk, which is consistent with our intent to examine MetS development in healthy women free of endpoint characteristics. All participants provided written informed consent. The Boston University Medical Center s Human Subjects Institutional Review Board approved all protocols. Nutrient intake and composite nutrition risk score Nutrient intake was estimated from -d dietary records by using a validated, published method (, ). Participants were instructed by a registered dietitian in the clinic to record their intake during weekdays and weekend day, while adhering to their usual eating practices. Subjects were trained to estimate portion sizes by using a validated -dimensional food portion visual (). Dietary records were processed by trained coders who adhered to standardized protocols. Nutrient calculations were performed by using MINNESOTA NUTRITION DATA SYSTEM software (version.6; Food Database 6A; Nutrient Database ; Nutrition Coordinating Center, University of Minnesota, Minneapolis, MN; 4). The nutritional risk score is a validated 9-nutrient index for assessing diet quality (5, 6). Nutrient intakes in all women in the FOS study (n 65) with -d dietary records were ranked from to 65. Ranks were assigned so that a person with a somewhat more desirable intake (eg, lower fat or higher vitamin or mineral intake) received a lower rank, whereas a person with a less desirable intake (eg, higher fat or lower micronutrient intake) received a higher rank. An overall composite nutritional risk rank was computed by using the mean of the ranks of 9 individual nutrients, including energy; protein; total fat; monounsaturated and saturated fats; alcohol; cholesterol; sodium; carbohydrate; polyunsaturated fat; fiber; calcium; selenium; vitamins C, B-6, B-, and E; folate; and -carotene. Among Framingham study participants, a higher intake of monounsaturated fats received a higher rating because it is derived from animal sources (eg, beef fat) rather than from vegetable sources (eg, olive oil). Risk factor measurements and interpretation Risk factors are routinely measured at Framingham study examinations (7) according to extensively published methods, including fasting lipid (7 0) and plasma glucose () concentrations; APOE genotypes ( ); duplicate blood pressure measurements (4); weight and height (5); abdominal obesity (6); self-reported age, smoking, and physical activity; and confirmed menopausal status (7). NCEP ATP III cutoffs (4) were used to evaluate study subjects IHD risk factor characteristics and to diagnose incident MetS by baseline nutritional risk status. Statistical analysis The primary research aim was to examine associations between the dietary quality assessed by our validated composite nutritional risk measure and the development of individual MetS risk factors and overall MetS risk. Multivariable analyses were adjusted for age, smoking, physical activity, and menopausal status. Analyses were restricted to women in the FOS study who were free of IHD, diabetes, MetS, and any MetS risk factors at exam 4. For MetS as an outcome and its individual risk factors in their categorical form [eg, elevated glucose ( 0 mg/dl), elevated blood pressure ( 0/ 85 mm Hg), elevated triacylglycerol ( 50 mg/dl), low HDL cholesterol ( 50 mg/dl), and abdominal obesity (waist circumference 88 cm)], we calculated the covariate-adjusted odds ratios (ORs) for each nutritional risk tertile and used the lowest tertile as the referent group. The tests were conducted in a -stage approach: first, we ascertained the significance of the risk rank tertile at the 0.0 level and then compared tertiles and of risk rank with tertile that served as reference at the 0.05 level. Because logistic regression and chi-square testing were used, Tukey s test was not available. However, we also ascertained that our findings remain significant even after Bonferroni s adjustment within each model. The covariates included continuous age and physical activity, and smoking (yes or no) and menopausal status (yes or no) were treated as categorical variables. SAS procedure LOGISTIC was used (8). Secondary analyses that adjusted for energy and APOE genotype did not alter our findings. Analyses were performed by using SAS software (version 8.; SAS Institute, Cary, NC). RESULTS At baseline, the nutrient intakes of these healthy women varied by dietary quality (Table ). Women with the highest nutritional risk profiles, based on the composite 9-nutrient measure of dietary quality, had lower energy intakes, higher percentages of energy from dietary lipids (total, saturated, and monounsaturated fats) and alcohol, and lower total carbohydrate intakes and fiber density, as well as lower amounts of all micronutrients (excluding vitamin B-). Relative to women with the lowest nutritional

3 46 MILLEN ET AL TABLE Dietary and risk factor profile of women in the Framingham Offspring-Spouse Study, (n 967) Baseline characteristic Women with MetS and any MetS risk factors (n 667) Women without MetS or any MetS risk factors (n 00) Nutrient Energy (kcal) Protein (%) Monounsaturated fat (%) Polyunsaturated fat (%) Total fat (%) Saturated fat (%) Alcohol (%) Cholesterol (mg/000 kcal) Sodium (mg/000 kcal) Carbohydrate (%) Dietary fiber (g/000 kcal) Calcium (mg/000 kcal) Selenium ( g/000 kcal) Vitamin C (g/000 kcal) Vitamin B-6 (g/000 kcal) Vitamin B- ( g/000 kcal) Folate ( g/000 kcal) Vitamin E (g/000 kcal) carotene ( g/000 kcal) Nutritional risk rank Risk factor Age (y) Systolic blood pressure (mm Hg) Diastolic blood pressure (mm Hg) Cigarette smoking (yes) (%). 4.0 Total cholesterol (mg/dl) 8, HDL cholesterol (mg/dl) 8, LDL cholesterol (mg/dl) 8, Triacylglycerol (mg/dl) 8, Glucose (mg/dl) 8, Waist circumference (cm) BMI (kg/m ) Physical activity index Postmenopausal (yes) (%) The sample is restricted to women who attended exams 4 and 7 and had complete nutrient intake data at exam and risk factor data at exam 4. x SD (all such values). The t test was used to obtain the age-adjusted means for continuous variables and to identify significant differences. The chi-square test was used to obtain the age-adjusted proportions and to identify significant differences between the subgroups. MetS, metabolic syndrome. P P P Hypertension is based on National Cholesterol Education Program criteria: blood pressure 40/90 mm Hg or taking antihypertensive medication. 7 P From fasting blood samples. 9 To convert cholesterol to SI units, multiply by To convert triacylglycerols to SI units, multiply by 0.0. To convert glucose to SI units, multiply by risk, fewer women in the middle and highest tertiles complied with the NCEP ATP III dietary criteria for intakes of total fat, cholesterol, carbohydrate, and fiber (Table ). Compliance for saturated fat and fiber was particularly poor regardless of risk score. IHD risk profiles of women at baseline (Table 4) differed by selected characteristics in that those with the highest nutritional risk had a slightly higher waist circumference (74 cm compared with 7 cm) than did the women with a lower nutritional risk. Women with the highest nutritional risk had smoking rates -fold those of women with the lowest nutritional risk. Tables 5 and 6, respectively, examine the ORs for MetS risk factors and overall MetS and the rates of development of these characteristics by tertile of nutritional risk. The OR for developing abdominal obesity during y of follow-up in women in the highest tertile of nutritional risk was twice (OR:.; 95% CI:., 4.) that in women in the middle (OR:.; 95% CI: 0.6,.9) or the lowest (referent) tertile. Development of MetS in women in the highest tertile of nutritional risk was times that in women in the lowest tertile (OR:.0, 95% CI:., 7.6). The OR for developing hypertension and elevated glucose, low HDLcholesterol, and elevated triacylglycerol concentrations did not vary by baseline nutritional risk during follow-up in these healthy

4 NUTRITIONAL RISK AND THE METABOLIC SYNDROME 47 TABLE Age-adjusted mean nutrient intake by risk score tertiles of women in the Framingham Offspring-Spouse Study, (n 00) Nutrient (n 9) (n 09) (n 00) Selected macronutrients Energy (kcal) 849. (754., 944.4) a 66.8 (550., 7.) b (94.5, 574.8) c Protein (%) 6.4 (5.7, 7.) 6.7 (6., 7.4) 6.8 (6., 7.5) Monounsaturated fat (%). (.6,.6) a.7 (., 4.) b 5.0 (4.5, 5.4) c Polyunsaturated fat (%) 8. (7.6, 8.9) 7.9 (7., 8.5) 7.9 (7., 8.5) Risk nutrients Total fat (%) 4. (.9, 5.4) a 7.8 (6.7, 8.9) b 4. (40., 4.4) c Saturated fat (%). (0.6,.7) a. (.9,.8) b 5. (4.8, 5.8) c Alcohol (%).5 (.4,.6) a.8 (.9,.8) a 5. (4.0, 6.) b Cholesterol (mg/000 kcal) 5.4 (0.7, 47.) 45. (5.4, 64.9) 47. (6.5, 67.6) Sodium (mg/000 kcal) 79.6 (554., 95.) (78.8, 76.) 506. (0.4, 68.8) Protective nutrients Carbohydrate (%) 49. (47.8, 50.6) a 44. (4.9, 45.4) b 7.8 (6.6, 9.) c Dietary fiber (g/000 kcal) 8.4 (7.5, 9.) a.8 (.0,.6) b 9.0 (8., 9.9) c Calcium (mg/000 kcal) (77., 8.6) a 67.7 (589., 686.) b 56.0 (475.6, 576.4) c Selenium ( g/000 kcal) 0.5 (0.8, 7.) a 98.6 (9.5, 04.7) b 87.5 (8., 9.8) c Vitamin C (g/000 kcal) 7.8 (9., 6.4) a 9. (84.4, 00.) b 54.6 (46.4, 6.7) c Vitamin B-6 (g/000 kcal).9 (.8,.0) a. (.,.4) b. (.0,.) c Vitamin B- ( g/000 kcal) 5.8 (4., 7.4) 6. (4.7, 7.7) 4.8 (., 6.) Folate ( g/000 kcal).0 (95., 0.7) a 6.7 (00.7,.8) b 50.0 (., 66.8) c Vitamin E (g/000 kcal) 0. (9.5, 0.9) a 8. (7.4, 8.7) b 6.6 (6.0, 7.) c -Carotene ( g/000 kcal) (9.0, 550.6) a (864.6, 407.) b 89.5 (660., 98.9) c All values are x ; 95% CI in parentheses. The sample was restricted to women without ischemic heart disease, diabetes, metabolic syndrome (MetS) risk factors, or MetS who attended exams 4 and 7 and had complete nutrient intake data at exam and risk factor data at exam 4. Analysis of covariance (SAS PROC GLM) was used to obtain the age-adjusted means for the continuous variables and to identify subgroups that differed significantly. Means in a row with different superscript letters are significantly different, P women. More women developed abdominal obesity than developed any other MetS risk factor, and the rate of abdominal obesity development varied by tertile of nutritional risk (44.%, 45.8%, and 64.6% in tertiles, and, respectively). DISCUSSION Relatively poor dietary quality, characterized by higher composite nutritional risk profiles, was associated with the -y development of abdominal obesity and MetS in healthy Framingham study women aged 0 69 y, independent of age, smoking, physical activity, or menopausal status. Higher nutritional risk, attributed to a combination of higher dietary lipids (percentage of energy from total, saturated, and monounsaturated fats) and alcohol consumption and to lower intakes of total carbohydrates, fiber, and micronutrients, was associated with a - to -fold increase in the rates of abdominal obesity and MetS development. Although we found that poor dietary quality was not related to the development of other MetS risk factors during y of follow-up in these women, we note that it predicted MetS overall and abdominal obesity, the most prevalent emerging MetS risk factor in the United States (5) and these healthy Framingham women. Most research to date on the relations between indexes of dietary quality and MetS risk or its constituent risk factors is cross-sectional in nature but supports our findings. McKeown et al (9) examined the association between the dietary glycemic TABLE Age-adjusted proportions of women in the Framingham Offspring-Spouse Study who complied with the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP-III) dietary guidelines, (n 00) Nutrient (n 9) (n 09) (n 00) % % % Guidelines Saturated fat ( 7%) Polyunsaturated fat ( 0%) Monounsaturated fat ( 0%) Total fat (5 5%) Carbohydrate (50 60%) Fiber (0 0 g/d) Protein (5%) Cholesterol ( 00 mg/d) All values are x. The sample was restricted to women without ischemic heart disease, diabetes, metabolic syndrome (MetS) risk factors, or MetS who attended exams 4 and 7 and had complete nutrient intake data at exam and risk factor data at exam 4. Logistic regression (SAS PROC LOGISTIC) was used to obtain the age-adjusted proportions and to identify subgroups that differed significantly. 4 Tertiles and were contrasted against tertile as the reference after the use of Bonferroni s adjustment: P 0.00, P 0.0, 4 P 0.05.

5 48 MILLEN ET AL TABLE 4 Age-adjusted risk factor profile by risk score tertiles of women in the Framingham Offspring-Spouse Study, (n 00) Risk factor (n 9) (n 09) (n 00) Mean SD Age (y) Systolic blood pressure (mm Hg) 0.40 (08.6,.45) (09.06,.78).6 (09.68,.55) Diastolic blood pressure (mm Hg) (69.5, 7.5) 7.6 (70.04, 7.68) (69.47, 7.) Cigarette smoking (yes, %) Total cholesterol (mg/dl) 6, (84.7, 97.0) 96.9 (9., 0.09) 97.0 (90.7, 0.47) HDL cholesterol (mg/dl) 6,7 6. (6.9, 65.64) (64.48, 68.7) (6.7, 68.00) LDL cholesterol (mg/dl) 6,7. (06.95, 9.69) 6.60 (.0,.78) 6.99 (0.8,.78) Triacylglycerols (mg/dl) 6, (6.7, 74.4) 67.6 (6.8, 7.68) 7.45 (68.4, 77.88) Glucose (mg/dl) 6,9 85. (8.78, 86.49) (84.86, 87.) (85., 87.75) Waist circumference (cm) (70.5, 7.0) a 7.99 (70.85, 7.) a 7.7 (7.55, 74.9) b BMI (kg/m ).77 (.0,.).75 (.,.7).4 (.70,.58) Physical activity index 6.56 (5.7, 7.85) 7.6 (6.44, 8.78) 7.0 (5.79, 8.) Postmenopausal (no) (%) The sample was restricted to women without ischemic heart disease, diabetes, metabolic syndrome (MetS) risk factors, or MetS who attended exams 4 and 7 and had complete nutrient intake data at exam and risk factor data at exam 4. Analysis of covariance (SAS PROC GLM) was used to obtain the age-adjusted means for continuous variables and to identify significant differences. Logistic regression (SAS PROC LOGISTIC) was used to obtain the age-adjusted proportions and to identify subgroups that differed significantly. Both sets of analyses used Bonferroni s correction for each variable. x SD (all such values). Hypertension is based on National Cholesterol Education Program criteria: blood pressure 40/90 mm Hg or taking antihypertensive medication. 4 x ; 95% CI in parentheses (all such values). 5 Tertiles and were contrasted against tertile as the reference, P From fasting blood samples. 7 To convert cholesterol to SI units, multiply by To convert triacylglycerols to SI units, multiply by To convert glucose to SI units, multiply by Means in a row with different superscript letters are significantly different, P index, a ranking of carbohydrate-containing foods based on their effect on blood glucose (0), and MetS in the FOS study cohort. Compared with men and women in the lowest quintile of glycemic index, those in the highest quintile had a 4% greater risk of MetS (OR:.4; 95% CI:.04,.9). In analyses of the third National Health and Nutrition Examination Survey data set, Guo et al () used the US Department of Agriculture Healthy Eating Index (HEI), a 0-factor composite measure of dietary quality (), to examine the relation between compliance with the US Department of Agriculture s Dietary Guidelines for Americans () and the Food Guide Pyramid (4) and obesity risk. Subjects with a poor HEI score had a risk of obesity twice that in subjects TABLE 5 Odds ratio for metabolic syndrome (MetS) components and MetS in women in the Framingham Offspring-Spouse study (n 00) Outcome (n 9) (n 09) Age-adjusted (n 00) Ageadjusted Multivariateadjusted Multivariateadjusted Elevated glucose ( 0 mg/dl).0 (ref).5 (0., 9.5).6 (0., 0.4). (0.4,.8).0 (0.5, 7.9) Elevated blood pressure ( 0/ 85 mmhg).0 (ref). (0.6,.). (0.6,.).0 (0.6,.0). (0.6,.) Elevated triacylglycerol ( 50 mg/dl).0 (ref) 0.8 (0.4,.6) 0.8 (0.4,.7).7 (0.8,.4).7 (0.8,.6) Low HDL cholesterol ( 50 mg/dl) 4.0 (ref) 0.6 (0.,.) 0.6 (0.,.). (0.6,.6). (0.6,.6) Abdominal obesity (waist circumference 88 cm).0 (ref).0 (0.6,.8). (0.6,.9). (.,.9) 5. (., 4.) 6 MetS ( of the above).0 (ref) 0.9 (0.,.7) 0.8 (0.,.5). (., 7.6) 5.0 (., 7.6) 5 All values are relative risks; 95% CIs in parentheses. The sample was restricted to women without ischemic heart disease, diabetes, MetS risk factors, or MetS who attended exams 4 and 7 and had complete nutrient intake data at exam and risk factor data at exam 4. Multivariate logistic regression model (SAS PROC LOGISTIC) adjusted for age, smoking, physical activity, and menopausal status. To convert glucose to SI units, multiply by To convert triacylglycerols to SI units, multiply by To convert cholesterol to SI units, multiply by ,6 Tertiles and were contrasted against tertile as the reference: 5 P 0.05, 6 P 0.0.

6 NUTRITIONAL RISK AND THE METABOLIC SYNDROME 49 TABLE 6 Multivariate-adjusted rates (per 00 women) of development of metabolic syndrome (MetS) and MetS components in women in the Framingham Offspring-Spouse study (n 00) Risk factor (n 9) (n 09) (n 00) P value Elevated glucose ( 0 mg/dl) Elevated blood pressure ( 0/ 85 mmhg) Elevated triacylglycerol ( 50 mg/dl) Low HDL cholesterol ( 50 mg/dl) Abdominal obesity (waist circumference 88 cm) MetS ( of the above) The sample was restricted to women without ischemic heart disease, diabetes, MetS risk factors, or MetS who attended exams 4 and 7 and had complete nutrient intake data at exam and risk factor data at exam 4. Covariates included age, smoking, physical activity, and menopausal status. Multivariate logistic regression model (SAS PROC LOGISTIC) adjusted for age, smoking, physical activity, and menopausal status. Multivariate-adjusted P value for overall significance of the risk rank variable. To convert glucose to SI units, multiply by To convert triacylglycerol to SI units, multiply by To convert cholesterol to SI units, multiply by with a good HEI score; ORs for obesity in women and men were.7 (95% CI:.,.6) and.9 (95% CI:.,.), respectively. Ours is the first study to conduct longitudinal research on overall dietary quality and the development of MetS and its component traits. The individual nutrients we found to be associated with our composite index of dietary quality have also been examined in relation to MetS risk in previous research, and the findings are largely consistent with our research. Cross-sectional studies suggest that low and moderate intakes of carbohydrate (NCEP ATP III criteria; 5); higher intakes of fiber (9), fruit and vegetables (high in vitamin C and -carotene; 6), vitamin C, and -carotene (7); and light-to-moderate alcohol consumption (5, 8 4) confer a lower risk of MetS. Conversely, higher total dietary fat intake was found to increase MetS risk in prospective research (4). It is important to note that cross-sectional literature does not distinguish between simple and complex carbohydrates, even though they may differentially affect MetS risk. In terms of individual MetS risk factors, higher consumption of vitamins C and E, -carotene, and selenium has been shown to be associated with lower levels of abdominal obesity cross-sectionally (7), as have higher intakes of fiber (4, 44) and fruit and vegetables (45) in prospective analyses. Cross-sectional research also shows heavy alcohol consumption to be associated with higher risk of abdominal obesity (4, 46). We identified abdominal obesity as the most prevalent MetS risk factor to emerge during long-term follow-up in these healthy women in the FOS study, a finding confirmed in national prevalence data (5). Furthermore, NCEP ATP III recognizes abdominal obesity as a key underlying feature of MetS (47, 48). It is postulated that obesity is a proinflammatory state that contributes to insulin resistance, a condition that is suggested to cause dyslipidemia, glucose intolerance, and elevated blood pressure, in addition to exacerbating obesity. The factors produced by adipose tissue that are assumed to contribute to the inflammatory state are cytokines (eg, tumor necrosis factor, interleukin 6, leptin, resistin, C-reactive protein, and plasminogen activator inhibitor ) and nonesterified fatty acids that induce insulin resistance by interfering with insulin signal transduction and hence glucose transport (47 49). Obesity per se also contributes to the development of hypertension and low HDL cholesterol (50), risk factors that appeared in 0 0% of these healthy women in the FOS study. Hyperglycemia, another risk factor that is influenced by obesity, was uncommon in our subjects. From the dietary perspective, macronutrients, including fat and simple carbohydrates, are thought to produce oxidative stress that also stimulates the inflammatory responses in obesity (49). Other macronutrients and micronutrients such as fiber, fruit, vegetables, alcohol, and vitamin E are anti-inflammatory, and they suppress oxidative stress (49). Women with the highest nutritional risk had higher smoking rates; had larger waist circumferences; had lower intakes of energy, carbohydrate, fiber, and most micronutrients; and consumed more dietary lipids and alcohol than did women with the lowest nutritional risk. The groups of women did not differ significantly in baseline BMI status. The poor overall quality of their diets contributed to the development of abdominal obesity. Our findings concur with other research, which observes that lifestyle behaviors are related and that persons with better dietary quality consume higher levels of energy and more nutrient-dense diets (5 5). Our findings provide a response to expert position statements that have urged research on overall dietary quality to improve the understanding of the numerous modifiable determinants of disease risk that may guide the development of innovative, focused, and individualized preventive intervention strategies (4, 54, 55). Risk of MetS was highest in women with a higher composite nutritional risk who consumed both a high dietary lipid density and smaller amounts of carbohydrate, fiber, and micronutrients. As is consistent with current expert preventive nutrition guidelines, each of these components of dietary quality could be targeted along with weight management, increased physical activity, and avoidance of smoking to lower MetS and obesity risk. Our previous research (5, 6) also showed a close association between dietary quality, assessed by composite nutritional risk scores, and 5 habitual dietary patterns of women that were characterized in the FOS study cohort. The unique food preferences of women in each dietary pattern subgroup provide a further framework and specific food behavior targets for preventive nutrition intervention planning at the individual and population

7 440 MILLEN ET AL levels. Recommendations for such strategies were published previously (5, 6, 7, 56 58). It is a strength of this research that disease-free women of a broad age range were followed during an extended time for the emergence of MetS risk. Among the limitations of these findings is the lack of follow-up assessment of subjects nutritional risk over time. Such changes could result in misclassification bias that would attenuate the estimated diet-disease relations. We suggest that the findings reported here may underestimate the true relations between nutritional risk and MetS. Future research should refine the nutritional risk score by incorporating both simple and complex carbohydrates and possibly other dietary factors such as nutrient density. Moreover, results may not be generalizable to minority women because the Framingham cohort is predominantly white. Nevertheless, the finding that poor diet predicted the development of abdominal obesity and MetS in healthy younger and middle-aged women during long-term follow-up underscores the importance of diet in the cause of MetS and should be considered in developing preventive nutrition interventions. Analysis of covariance (SAS PROC GLM) was used to obtain the age-adjusted means for the continuous variables and to identify subgroups that differed significantly. Analysis of covariance (SAS PROC GLM) was used to obtain the age-adjusted means for continuous variables and to identify significant differences. Logistic regression (SAS PROC LOGISTIC) was used to obtain the age-adjusted proportions and to identify subgroups that differed significantly. Both sets of analyses used Bonferroni s correction for each variable. 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