Abstract
Type 2 diabetes is a highly prevalent but preventable disorder. We assessed the association between an a priori Mediterranean diet score (MeDiet) and fasting glucose and insulin at baseline and incident type 2 diabetes after 6-year follow-up in MESA. Dietary intake was measured at baseline by a 127-item food frequency questionnaire in 5,390 men and women aged 45-84 years free of prevalent diabetes and clinical CVD. A MeDiet score was created based on intake of 10 food components: vegetables, whole grains, nuts, legumes, fruits, ratio of monounsaturated to saturated fat, red and processed meat, dairy, fish and alcohol. Multivariable linear and proportional hazard models were used to estimate the association of MeDiet, categorized in quintiles, with baseline insulin and glucose, and incident diabetes, respectively. Models adjusted for demographic, physiologic and behavioral characteristics. After multivariable adjustment, individuals with a higher MeDiet score had lower baseline mean (95% CI) insulin levels [mean Q1: = 5.8 (5.6-6.0) umol/l; mean Q5: = 4.8 (4.6-5.0) umol/l; p-trend= <0.0001]. A higher MeDiet score was also associated with significantly lower glucose levels after basic adjustment, but was attenuated after adjustment for waist circumference. During follow-up, 412 incident diabetes events accrued. MeDiet was not significantly related to risk of incident diabetes (p-trend=0.64). In summary, greater consistency with a Mediterranean-style diet, reflected by a higher a priori Mediterranean diet score, was cross-sectionally associated with lower insulin levels among non-diabetics, and lower blood glucose prior to adjustment for obesity, but not with lower incidence of diabetes.
INTRODUCTION
Diabetes affects approximately 24 million people in the United States, 8% of the population, and is currently the seventh leading cause of death. It is projected that prevalence of diabetes will reach 26% by 2050(1). Accounting for about 95% of all diagnosed cases in the United States, type 2 diabetes (T2D) results in complications such as kidney failure, amputations and blindness affecting the quality of life(2). Management of the disease also poses a huge medical burden and economic impact making it a current public health priority. T2D can however, be prevented through healthy diets, other lifestyle modifications like weight loss and use of medication(3).
The Mediterranean diet (MeDiet) is the traditional diet of people living in olive-growing regions bordering the Mediterranean Sea. It is of public health interest due to the observation that adults living in these areas have historically had one of the lowest incidences of chronic diseases in the world and one of the highest life expectancies(4). This diet is characterized by a high consumption of whole grains, olive oil, legumes, vegetables, fruits, cereals, moderate to high consumption of fish and moderate to low consumption of meat and meat products, milk and dairy products, and alcohol in the form of wine is often consumed at meals(5). Extensive research has demonstrated a beneficial effect of specific dietary components of the MeDiet on weight loss, normalizing insulin resistance, and risk of developing T2D and cardiovascular disease(5-7). The MeDiet is widely viewed as ‘health promoting’, both among the scientific community and among the general public. Possible mechanisms by which intake of the Mediterranean diet may be associated with lower diabetes risk include fiber increasing satiety through prolonged mastication and antioxidants reducing the stress of beta cell dysfunction and insulin resistance(8) Relations of the MeDiet to disease risk may also be mediated through the anti-inflammatory effects of vitamins, minerals, antioxidants and unsaturated fat—particularly olive oil—present in high levels in the MeDiet(5, 7, 9, 10).
There is limited evidence of the association between insulin resistance - as a precursor of diabetes - and the MeDiet in non-diabetic individuals. Additionally, little research has investigated whether racial/ethnic heterogeneity exists in the relationship between intake of a Mediterranean-style diet and the incidence of diabetes and onset of insulin resistance. We hypothesized that in a community-based sample free of diabetes and cardiovascular disease, a high conformity to the Mediterranean-style diet would be associated cross-sectionally with lower insulin resistance and prospectively with a reduced risk for T2D incidence. Our MeDiet index was created a priori, and focused on those food groups commonly attributed to the Mediterranean cuisine, i.e., vegetables, whole grains, nuts, legumes, fruits, MUFA/SFA ratio, fish.
METHODS
Study Population
The Multi-Ethnic Study of Atherosclerosis (MESA) is a prospective population-based cohort study of 6,814 persons aged 45-84 years who self-identified as Hispanic, non-Hispanic Caucasian, African American and Asian Chinese(11). The study was initiated in July 2000 to determine characteristics associated with the prevalence and progression of subclinical cardiovascular disease (CVD) to clinically overt CVD as well as to investigate demographic differences and identify risk factors for CVD incidence. Baseline information was collected from enrollees, all of whom were free from clinical cardiovascular disease, at six U.S. field centers: Chicago, Illinois; Los Angeles County, California; New York, New York; Forsyth County, North Carolina; St. Paul, Minnesota; and Baltimore, Maryland. Detailed study protocol and inclusion criteria can be found at www.mesa-nhlbi.org. This study was conducted according to the guidelines laid down in the Declaration of Helsinki, and all procedures involving human subjects were approved by the Institutional Review Boards from each study center, All participants gave written informed consent.
Dietary pattern assessment
At baseline, a 127-item food frequency questionnaire (FFQ) was used to assess usual dietary intake of participants over the past year. For each questionnaire item, participants were asked to report their frequency of consumption of various foods from among nine categories, ranging from rarely or never to two or more servings/day (six or more servings/day for beverages) and also their serving size as either small, medium or large. Servings per day were calculated from these categories. The questionnaire was patterned after the FFQ used in the Insulin Resistance Atherosclerosis Study, which has been validated in non-Hispanic white, African American, and Hispanic persons(12).
To ascertain conformity to a Mediterranean-style diet, a 10-point a priori Alternate Mediterranean Diet (MeDiet) score was created. The MeDiet score was adapted to the US population from a scoring system modeled for Greek populations and focuses on higher consumption of plant foods, monounsaturated fat, fish and lower intake of animal product and saturated fat(6, 13). As detailed in Table 1, the score included 10 food components: vegetables (excluding potatoes), whole grains, nuts, legumes, fruits, ratio of monounsaturated to saturated fat, red and processed meat, whole fat dairy, fish and alcohol(14). Participants with intakes above the median intake of traditional foods in the Mediterranean diet (i.e. vegetables, whole grains, nuts, legumes, fruits, MUFA/SFA ratio, fish) received 1 point, while those below the median received 0 points. For potentially detrimental foods inversely associated with the Mediterranean diet (i.e. red/processed meats, whole fat dairy), those with intakes below the median received 1 point; otherwise, they received 0 points. For example, red or processed meat below the median intake received 1 point. Alcohol intake received 1 point if consumed in moderate amounts (5-15g/d) and 0 otherwise (<5, >15 g/d). Points were then summed. The final MeDiet score ranged from 0 to 10 with a higher score indicating a closer resemblance to the Mediterranean diet.
Table 1.
Food group components of the 10-point Mediterranean Diet Score: The MESA Study (2000-2002)
| Food group | Foods included | Criteria for 1 point1 |
|---|---|---|
| Vegetables | All vegetables (Cruciferous vegetables, dark yellow vegetables, green leafy vegetables, other vegetables) except potatoes |
Greater than median intake |
| Legumes | Legumes, soy | Greater than median intake |
| Fruit | Fruits, fruit juice, avocado, tomato | Greater than median intake |
| Nuts | Seeds, nuts | Greater than median intake |
| Whole grains | All whole grain products | Greater than median intake |
| Fish | All fish | Greater than median intake |
| Red meat | Red and processed meats | Less than median intake |
| Ratio of monounsaturated to saturated fat |
— | Greater than median intake |
| Alcohol | Total alcohol (beer, liquor, wine) | Greater than median intake |
| Dairy | Whole milk, high fat cheeses and sauces |
Less than median intake |
0 points if these criteria are not met.
Outcome ascertainment
Insulin resistance was cross-sectionally characterized using mean baseline fasting glucose and fasting serum insulin levels among non-diabetics. Fasting serum glucose was measured at each exam using the thin film adaptation of the glucose oxidase method on the Vitros analyzer (Johnson & Johnson Clinical Diagnostics, Inc., Rochester, NY). To ensure consistency of the fasting serum glucose assay over the examinations, 200 samples from each of the four examinations were reanalyzed over a short time period to recalibrate the original observations. Fasting serum insulin levels were determined by a radioimmunoassay method using the Linco Human Insulin-Specific RIA Kit (Linco Research, Inc., St. Charles, MO). These assays were conducted at the Collaborative Studies Clinical Laboratory at Fairview University Medical Center (Minneapolis, MN)(15-17).
To determine incident diabetes, we excluded from the analyses individuals with diabetes at baseline, defined as fasting blood glucose ≥7.0mmol/l (126 mg/dl), self reported diabetes or using hypoglycemic drugs. During follow-up exams 2 (2002-2003), 3 (2004-2005) and 4 (2005-2007), participants without diabetes at baseline who met any of the above three criteria were considered to have incident type 2 diabetes. Person-years accrued from baseline until the date of the exam at which incident diabetes was identified, loss to follow-up, or the date of exam 4.
Covariate assessment
Demographic data was obtained during the baseline exam (2000-2002) with a standardized questionnaire and calibrated devices. Participants self-reported their racial/ethnic groups and were characterized as Caucasian, Chinese, African American and Hispanic. Annual gross family income was categorized as <$20,000, $20,000-<$50,000 and >$50,000 and the level of formal education was classified as <high school diploma, high school or some college and college diploma. Height was measured with a stadiometer with a level bubble (Accu-Hite Measuring device; Seca GmbH & Company KG, Hamburg, Germany) and weight with a Detecto platform balance scale (Titus Home Health Care, Alhambra, California). Body Mass Index (BMI) was calculated as weight in kilograms divided by the square of height in meters (kg/m2). Waist circumference in centimeters was measured at the level of the umbilicus. Resting seated blood pressure was measured three times using a Dinamap model Pro 100 automated oscillometric sphygmomanometer (Critikon, Tampla, FL) and the average of the last two measurements were used in analysis.
Additional variables such as use of hypertensive medication, use of statins (HMG-CoA reductase inhibitors), cigarette smoking status and time spent in moderate to vigorous exercise (MET-min/wk M-Su) were obtained from a combination of self-administered and interviewer-administered questionnaires. Pack years of smoking defined as number of years smoking times packs per day (cigarettes per day divided by 20) was then calculated(15, 18-20).
Statistical analyses
All analyses were performed using SAS software (version 9.2; SAS Institute, Cary, NC). Of the 6,814 MESA participants, we excluded those with prevalent diabetes (n=859), missing values (n=24) and people with unrealistic dietary intake (n=541). Unrealistic dietary intake was defined as caloric intake of <500 or >5,000 kcal/day. Our final analytic sample included 5,390 individuals
Cross-sectional demographic, behavioral and physiologic characteristics across quintiles of the MeDiet score were quantified using means and proportions. We used multivariable linear regression to assess the association of MeDiet with insulin resistance. Separate analyses were conducted for fasting glucose and insulin at baseline across MeDiet quintiles. After checking for normality of these outcomes, serum insulin was found to be skewed and was therefore log transformed for multivariate analyses. The adjusted mean values were then back-transformed to obtain the geometric means. Adjusted means at each MeDiet quintile were obtained by entering the MeDiet quintiles into the models as indicator variables. To test the linear trend across the quintiles of MeDiet, quintiles were entered into the models as continuous variables.
We used three multivariable models in our analyses. The first model (model 1) adjusted for age, gender, race/ethnicity, and study site. Model 2 adjusted for model 1 variables plus educational level, family income, physical activity, smoking status and total caloric intake. Further, to assess the effect of body adiposity and how this might mediate the association of the MeDiet and the outcomes, waist circumference was included in the final model (model 3). In sensitivity analyses, we explored substituting BMI for waist circumference.
Cox proportional hazards regression models were used to estimate the hazard ratios of developing type 2 diabetes by MeDiet quintiles. The adjustment approach was similar to the cross-sectional analysis, with quintile 1 as the reference for the Cox regression model. We further tested whether there were interactions by sex and race/ethnicity in the relation between MeDiet and outcomes by including cross-product terms in our models. In sensitivity analyses we evaluated the risk of incident IFG or diabetes in a subset free of IFG and diabetes at baseline.
RESULTS
The 5,390 participants in our analytic sample were on average 62 ±10.3 years old and 54% were female. The racial/ethnic distribution was as follows: 43% Caucasian, 13% Chinese, 24% African American and 20% Hispanic. The average MeDiet score was 5.0 ±1.9 on a 0-10 point scale within the study population. Participants who had higher MeDiet scores indicating a high conformity to the Mediterranean diet were more likely to be female, more educated, have higher incomes, a smaller waist circumference and be non-smokers (Table 2). In this population of non-diabetics, the mean glucose level was 89.5 mg/dL, and the geometric mean insulin level was 5.25 umol/l. Furthermore, 15.7% (n = 841) of the analytic sample had impaired fasting glucose (IFG), as defined by fasting glucose levels of 100 to 125 mg/dL.
Table 2.
Baseline characteristicsa by quintiles of the Mediterranean dietary score: The MESA Study (2000-2002)
| Quintileb | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|
|
| |||||
| MeDiet Score Range | (0-3) | (4) | (5) | (6) | (7-10) |
|
| |||||
| N | 1240 | 967 | 1051 | 932 | 1200 |
| Demographics | |||||
| Age, years ± SD | 60 ± 10.3 | 62 ± 10.2 | 62 ± 10.3 | 63 ± 10.2 | 63 ± 10.3 |
| Women, n (%) | 676 (54.5) | 522 (54.0) | 552 (52.5) | 505 (54.2) | 629 (52.4) |
| Racial/ethnic group, n (%) | |||||
| White | 547 (44.1) | 396 (41.0) | 425 (40.4) | 377 (40.5) | 558 (46.5) |
| Chinese | 68 (5.5) | 99 (10.2) | 163 (15.5) | 165 (17.7) | 180 (15.0) |
| African American | 293 (23.6) | 243 (25.1) | 244 (23.2) | 230 (24.7) | 305 (25.4) |
| Hispanic | 332 (26.8) | 229 (23.7) | 219 (20.8) | 160 (17.2) | 157 (13.1) |
| Formal Education, n (%) | |||||
| <High school diploma | 249 (20.2) | 193 (20.0) | 182 (17.3) | 132 (14.2) | 122 (10.2) |
| High school or some college | 628 (50.8) | 484 (50.1) | 464 (44.2) | 132 (44.7) | 471 (39.3) |
| College diploma | 359 (29.0) | 289 (29.9) | 405 (38.5) | 132 (41.1) | 606 (50.5) |
| Gross family income, n (%) | |||||
| <$20,000 | 277 (23.0) | 222 (24.1) | 249 (24.5) | 194 (21.4) | 213 (18.3) |
| $20,000 - <$50,000 | 460 (38.2) | 379 (41.1) | 338 (33.2) | 324 (35.8) | 360 (30.9) |
| ≥$50,000 | 466 (38.8) | 322 (34.9) | 431 (42.3) | 388 (42.8) | 592 (50.8) |
| BMI, kg/m2 ± SD | 28.9 ± 5.7 | 28.0 ± 5.2 | 27.9 ± 5.3 | 27.5 ± 5.2 | 27.1 ± 4.8 |
| Waist circumference, cm ± SD | 99.2 ± 14.8 | 97.2 ± 13.8 | 97.0 ± 13.8 | 95.9 ± 13.9 | 94.9 ± 13.2 |
| Behavioral | |||||
| Current smoke, n (%) | 236 (19.1) | 136 (14.1) | 122 (11.6) | 83 (8.8) | 90 (7.5) |
| Pack years of cigarette smoking, years ± SD |
14.6 ± 30.1 | 11.6 ± 20.5 | 10.7 ± 21.6 | 8.2 ± 15.1 | 9.7 ± 18.5 |
| Physical activity, MET-min/wk ± SD |
3495 ± 4114 | 2921 ± 3702 | 2987 ± 3888 | 2934 ± 3889 | 2806 ± 3646 |
| Physiologic | |||||
| Systolic BP, mmHg ± SD | 124 ± 22 | 127 ± 21 | 125 ± 21 | 126 ± 21 | 126 ± 21 |
| Diastolic BP, mmHg ± SD | 72 ± 10 | 73 ± 10 | 72 ± 10 | 72 ± 10 | 72 ± 10 |
| Triglycerides, mg/dl ± SD | 131 ± 75 | 129 ± 76 | 132 ± 80 | 123 ± 65 | 118 ± 66 |
| LDL cholesterol, mg/dl ± SD | 120 ± 31 | 118 ± 32 | 116 ± 30 | 118 ± 30 | 117 ± 31 |
| HDL cholesterol, mg/dl ± SD | 50.9 ± 14.8 | 51.3 ± 14.6 | 51.2 ± 14.8 | 52.3 ± 15.8 | 53.0 ± 15.3 |
| Hypertensive med. use, n (%) | 318 (25.6) | 293 (30.3) | 324 (30.8) | 292 (31.3) | 365 (30.4) |
| Statins use, n (%) | 139 (11.2) | 133 (13.7) | 142 (13.5) | 122 (13.1) | 179 (14.9) |
Abbreviations: n, column totals; SD, standard deviation; BMI, body mass index; LDL, low density lipoprotein; HDL, high density lipoprotein.
Participants with prevalent diabetes were excluded.
Higher quintile represents closer conformity to the Mediterranean diet.
People with a higher MeDiet score had lower insulin levels after model 2 adjustments [mean Q1 (95% CI) = 5.8 (5.6-6.0) umol/l; mean Q5 = 4.8 (4.6-5.0) umol/l; p-trend = <0.0001] (Table 3). The results were similar to model 1, and this relation remained significant in model 3 which further adjusted for waist circumference (p-trend = <0.0001). Upon stratification by sex, the association in men remained significant across all models, while among women the association was attenuated after adjustment for waist circumference (model 3, p-trend = 0.11). After model 2 adjustments, mean fasting glucose was also lower for individuals in MeDiet quintile 5 [89.0 (88.4-89.6) mg/dl] relative to those in MedDiet quintile 1 [90.3 (89.7-90.9) mg/dl] (p-trend = 0.009). The relation, however, disappeared after adjusting for waist circumference (model 3, p-trend = 0.45).
Table 3.
Adjusted mean (95% CI) glucose and insulin levels by the Mediterranean dietary score quintiles: MESA (2000-2002)
| Quintilea | 1 | 2 | 3 | 4 | 5 | Beta for 1 Quintile Increase |
p-trend |
|---|---|---|---|---|---|---|---|
| Total Population | |||||||
| Glucose, mg/dl | |||||||
| Model 1 | 90.3 (89.8, 90.9) | 89.1 (88.5, 89.7) | 89.6 (89.0, 90.2) | 89.2 (88.6, 89.9) | 89.0 (88.4, 89.6) | −0.27 | 0.005 |
| Model 2 | 90.3 (89.7, 90.9) | 88.9 (88.2, 89.5) | 89.6 (89.0, 90.2) | 89.2 (88.5, 89.8) | 89.0 (88.4, 89.6) | −0.26 | 0.009 |
| Model 3 | 89.9 (89.3, 90.4) | 88.9 (88.3, 89.5) | 89.5 (88.9, 90.1) | 89.3 (88.7, 90.0) | 89.4 (88.8, 89.9) | −0.07 | 0.45 |
| Insulin, umol/lb | |||||||
| Model 1 | 5.7 (5.5, 5.9) | 5.3 (5.1, 5.5) | 5.3 (5.1, 5.5) | 5.1 (4.9, 5.3) | 4.8 (4.7, 5.0) | −0.04 | <.0001 |
| Model 2 | 5.8 (5.6, 6.0) | 5.3 (5.1, 5.5) | 5.3 (5.1, 5.5) | 5.0 (4.8, 5.2) | 4.8 (4.6, 5.0) | −0.04 | <.0001 |
| Model 3 | 5.5 (5.4, 5.7) | 5.3 (5.1, 5.5) | 5.3 (5.1, 5.4) | 5.1 (4.9, 5.3) | 5.0 (4.9, 5.2) | −0.02 | <.0001 |
| Males | |||||||
| Glucose, mg/dl | |||||||
| Model 1 | 92.7 (91.8, 93.5) | 91.0 (90.0, 91.9) | 91.1 (90.2, 92.0) | 91.1 (90.1, 92.1) | 90.6 (89.7, 91.4) | −0.42 | 0.003 |
| Model 2 | 92.7 (91.8, 93.6) | 90.7 (89.8, 91.7) | 91.3 (90.4, 92.2) | 91.1 (90.1, 92.0) | 90.5 (89.6, 91.3) | −0.43 | 0.004 |
| Model 3 | 92.2 (91.4, 93.1) | 90.7 (89.8, 91.6) | 91.3 (90.4, 92.2) | 91.3 (90.3, 92.2) | 90.8 (89.9, 91.6) | −0.26 | 0.07 |
| Insulin, umol/lb | |||||||
| Model 1 | 6.1 (5.8, 6.4) | 5.3 (5.0, 5.6) | 5.2 (4.9, 5.5) | 4.9 (4.7, 5.2) | 5.0 (4.7, 5.2) | −0.05 | <.0001 |
| Model 2 | 6.2 (5.9, 6.5) | 5.3 (5.0, 5.7) | 5.3 (5.0, 5.6) | 4.9 (4.6, 5.2) | 4.9 (4.6, 5.1) | −0.06 | <.0001 |
| Model 3 | 5.8 (5.6, 6.1) | 5.3 (5.1, 5.6) | 5.3 (5.0, 5.5) | 5.0 (4.8, 5.3) | 5.1 (4.9, 5.3) | −0.03 | <.0001 |
| Females | |||||||
| Glucose, mg/dl | |||||||
| Model 1 | 88.4 (87.6, 89.1) | 87.5 (86.6, 88.3) | 88.3 (87.5, 89.2) | 87.6 (86.7, 88.5) | 87.7 (86.9, 88.5) | −0.13 | 0.32 |
| Model 2 | 88.3 (87.5, 89.1) | 87.2 (86.3, 88.1) | 88.1 (87.3, 89.0) | 87.5 (86.6, 88.4) | 87.7 (86.9, 88.5) | −0.10 | 0.48 |
| Model 3 | 87.8 (87.1, 88.6) | 87.3 (86.5, 88.2) | 88.0 (87.2, 88.8) | 87.6 (86.7, 88.5) | 88.1 (87.4, 88.9) | 0.09 | 0.50 |
| Insulin, umol/lb | |||||||
| Model 1 | 5.4 (5.2, 5.7) | 5.3 (5.0, 5.6) | 5.4 (5.1, 5.6) | 5.2 (4.9, 5.5) | 4.7 (4.5, 5.0) | −0.03 | 0.0002 |
| Model 2 | 5.4 (5.2, 5.7) | 5.2 (5.0, 5.5) | 5.3 (5.1, 5.6) | 5.2 (4.9, 5.4) | 4.8 (4.6, 5.0) | −0.03 | 0.0005 |
| Model 3 | 5.2 (5.0, 5.4) | 5.3 (5.1, 5.5) | 5.3 (5.0, 5.5) | 5.2 (5.0, 5.4) | 5.0 (4.8, 5.2) | −0.01 | 0.11 |
Abbreviations: CI, confidence interval
Higher quintile represents closer conformity to the Mediterranean diet.
Values for quintiles 1 through 5 are geometric means. Betas for 1 quintile increase in the Mediterranean diet score are presented on the log scale.
The log-scale betas multiplied by 100 gives the percent change per 1 quintile increase in the Mediterranean diet score. For example, using Model 1 and the total population, each 1 quintile higher Mediterranean diet score is associated with a 4% lower insulin level. Model 1 adjusted for age, gender, race/ethnicity, study site. Model 2 adjusted for Model 1 + educational level, family income, smoking status, physical activity, total caloric intake. Model 3 adjusted for Model 2 + waist circumference
Model 1 adjusted for age, gender, race/ethnicity, study site.
Model 2 adjusted for Model 1 + educational level, family income, smoking status, physical activity, total caloric intake.
Model 3 adjusted for Model 2 + waist circumference
After 6.6 years of follow-up, 412 participants (7.6%) developed T2D. In this study population, MeDiet was not significantly related to the risk of T2D incidence and this relation was consistent across sex (Table 4) and racial/ethnic groups (results not shown for racial/ethnic groups). The model 2 multivariable hazard ratio (95% confidence interval) of T2D among those in the highest quintile of MeDiet score vs. the lowest quintile was 0.91 (0.67-1.23), p-trend=0.64 (Table 4).
Table 4.
Hazard ratios (95% CI) of type 2 diabetes across quintiles of the Mediterranean Dietary Score: MESA (2000-2007)
| Quintilesa | 1 | 2 | 3 | 4 | 5 | HR for 1 Quintile Increase |
p -trend |
|---|---|---|---|---|---|---|---|
| Total Population | |||||||
| N events | 99 | 73 | 83 | 68 | 89 | ||
| Person-years | 4936 | 3886 | 4230 | 3702 | 5013 | ||
| Incidence rateb | 20.1 | 18.8 | 19.6 | 18.4 | 17.8 | ||
| HR (CI) | |||||||
| Model 1 | 1 (referent ) | 0.93 (0.69, 1.26) | 1.00 (0.75, 1.35) | 0.96 (0.70, 1.31) | 0.93 (0.69, 1.25) | 0.99 (0.92, 1.06) | 0.71 |
| Model 2 | 1 (referent ) | 0.88 (0.65, 1.20) | 0.97 (0.72, 1.31) | 0.93 (0.67, 1.28) | 0.91 (0.67, 1.23) | 0.98 (0.92, 1.06) | 0.64 |
| Model 3 | 1 (referent ) | 1.01 (0.74, 1.38) | 1.04 (0.77, 1.41) | 1.08 (0.78, 1.50) | 1.09 (0.80, 1.49) | 1.02 (0.95, 1.10) | 0.51 |
| Males | |||||||
| N events | 41 | 40 | 41 | 35 | 42 | ||
| Person-years | 2281 | 1799 | 2048 | 1691 | 2350 | ||
| Incidence rateb | 18.0 | 22.2 | 20.0 | 20.7 | 17.9 | ||
| HR (CI) | |||||||
| Model 1 | 1 (referent ) | 1.19 (0.77, 1.84) | 1.09 (0.70, 1.69) | 1.19 (0.75, 1.87) | 1.02 (0.65, 1.58) | 1.00 (0.91, 1.10) | 0.98 |
| Model 2 | 1 (referent ) | 1.12 (0.71, 1.75) | 1.07 (0.68, 1.66) | 1.08 (0.67, 1.73) | 0.95 (0.60, 1.50) | 0.99 (0.89, 1.09) | 0.79 |
| Model 3 | 1 (referent ) | 1.24 (0.79, 1.94) | 1.15 (0.74, 1.81) | 1.26 (0.78, 2.04) | 1.11 (0.70, 1.76) | 1.02 (0.92, 1.13) | 0.69 |
| Females | |||||||
| N events | 58 | 33 | 42 | 33 | 47 | ||
| Person-years | 2656 | 2087 | 2182 | 2011 | 2664 | ||
| Incidence rateb | 21.8 | 15.8 | 19.2 | 16.4 | 17.6 | ||
| Model 1 | 1 (referent ) | 0.73 (0.48, 1.12) | 0.93 (0.62, 1.39) | 0.77 (0.50, 1.18) | 0.86 (0.58, 1.27) | 0.97 (0.88, 1.06) | 0.51 |
| Model 2 | 1 (referent ) | 0.70 (0.45, 1.09) | 0.88 (0.58, 1.34) | 0.78 (0.50, 1.22) | 0.89 (0.59, 1.35) | 0.98 (0.89, 1.08) | 0.70 |
| Model 3 | 1 (referent ) | 0.82 (0.53, 1.29) | 0.95 (0.62, 1.45) | 0.92 (0.59, 1.45) | 1.12 (0.74, 1.71) | 1.03 (0.93, 1.14) | 0.55 |
Abbreviations: CI, confidence interval; HR, hazard ratio.
Higher quintile represents closer conformity to the Mediterranean diet.
Incidence per 1000 person-years.
Model 1 adjusted for age, gender, race/ethnicity, study site.
Model 2 adjusted for Model 1 + educational level, family income, smoking status, physical activity, total caloric intake.
Model 3 adjusted for Model 2 + waist circumference
In additional analyses, there were no significant interactions by race/ethnicity or gender in the relation between the Mediterranean diet and insulin levels, glucose levels, or incidence of diabetes. Results were similar when we adjusted for BMI instead of waist circumference (data not shown). Furthermore, we also evaluated risk of incident IFG or diabetes in a subset free of IFG and diabetes at baseline. There was no evidence that the MeDiet Score was associated with lower risk of incident IFG or diabetes. The HR for 1 quintile change in MeDiet Score was 0.98 (0.94. 1.02).
DISCUSSION
In this population-based multi-ethnic sample, higher consumption of the Mediterranean-style diet was associated cross-sectionally with lower blood glucose and insulin levels, prior to adjustment for adiposity. Adjustment for waist circumference attenuated the association between MeDiet and blood glucose, but the relation between MeDiet and insulin levels remained statistically significant. MeDiet was not related to the incidence of T2D.
Similar to our findings, an inverse cross-sectional association was found between indices of glucose homeostasis and adherence to the Mediterranean diet among non-diabetic subjects in Greece(21). A recent study in French households comparing computer-simulated personalized diets to a 7-day food records of adults from French households in meeting dietary recommendations also showed that foods typical of the Mediterranean diet such as unrefined grains, legumes, nuts, fruits, fish and vegetables were efficient ways to achieve overall nutrient adequacy(9). Additionally, current evidence indicates that adherence to a Mediterranean dietary pattern together with maintenance of ideal body weight appears to be an excellent strategy to reduce type 2 diabetes risk(10, 22).
Contrary to our hypothesis, the Mediterranean dietary pattern was not related to a lower type 2 diabetes incidence in this population. This is in contrast to previous published findings, such as the PREDIMED study, a randomized trial in Spain, which indicated that consumption of the Mediterranean diet led to a 50% reduction in diabetes incidence over four years among non-diabetics at high cardiovascular disease risk, and the observational Nurses’ Health Study (NHS) which found that after a 20-year follow-up, consumption of a Mediterranean-style diet was associated with a significantly l risk of cardiovascular disease, coronary heart disease and stroke(6, 23). A recent large prospective study (European Prospective Investigation Into Cancer and Nutrition (EPIC) Study: The InterAct project) which used nine dietary characteristic components of the Mediterranean diet (score range; 0-18) also showed that adherence to the Mediterranean diet was associated with a small reduction in the risk of developing T2D(24).
There are several limitations of our study which may explain the lack of association in the MESA population between the MedDiet score and incident diabetes. First, the MeDiet score might be inadequate for a multi-ethnic population in the US, with dietary patterns very different from those traditionally observed in Mediterranean countries. As a second limitation, our study attempted to define a Mediterranean dietary pattern from usual diets of participants using a dietary assessment tool not specifically designed to measure conformity to the MeDiet. Not all of the distinct food components of the traditional MeDiet were included in the questionnaire (e.g. olive oil). Furthermore, many of the components were part of line items which included non-MeDiet foods in addition to the MeDiet food items. Our attempt to tease out specific food components from composite or mixed dishes might have possibly led to either overestimation or underestimation of some food categories. Third, measurement error associated with changes in diet over the duration of follow-up could cause misclassification of the exposure. Unlike the Nurses’ Health Study where there was updated dietary information, MESA had only one dietary measure. This might be a possible explanation for the differences in our findings(6). Lastly, if the association between the MeDiet and incident diabetes is small in magnitude, we may have been underpowered to detect a relation. Despite these limitations, our study also has several important strengths, including the diverse population, use of objectively-identified diabetes (not only self-report), and the highly standardized serum processing, anthropometric measurements, and covariate assessment across study centers.
Notably, a previous analysis of the MESA sample identified two empirically derived dietary patterns associated with the risk of diabetes(17). In contrast to the previous work, our MeDiet index focused a priori on only those food groups commonly attributed to the Mediterranean cuisine. However, the percent agreement of quintile ranks for the Mediterranean diet score and each of the previous dietary patterns were about 35%, indicating a fair to moderate agreement in how the dietary patterns were associated with the risk of type 2 diabetes.
In this study, we found that a high consumption of the MeDiet was associated with significantly lower serum insulin levels, but after adjustment for obesity was not related to glucose levels or the incidence of T2D. The new dietary guidelines for Americans, which are based on current epidemiological evidence, reiterate the need for a more plant based diet, less processed meat, and more low fat dairy and seafood, which are typical components of the Mediterranean dietary pattern. The synergistic effect of these individual components of the MeDiet may give this dietary pattern its numerous beneficial properties in mitigating chronic diseases, such as, type 2 diabetes. Overall, our research supports the existing evidence that consistent consumption of a Mediterranean-type diet may lead to reduced risk for type 2 diabetes. Given the beneficial effects of the traditional Mediterranean diet, further research should determine whether this pattern is applicable to and leads to similar health benefits in diverse ethnic groups with other culinary traditions.
ACKNOWLEDGMENTS
This research was supported by contracts N01-HC-95159 through N01-HC-95169 from the National Heart, Lung, and Blood Institute. Dr. Nettleton was supported by grant 5K01DK082729-02 from the National Institute of Diabetes and Digestive and Kidney Diseases.
EEA and AA developed the research question and operationalized the MeDiet Score. EEA and PLL conducted the data analysis and led in writing the manuscript. EEA, AA, JAN, LMS, AGB, and PLL made substantial conceptual contributions and revisions.
The authors thank the other investigators, the staff, and the participants of the MESA study for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org.
Footnotes
The authors do not have any conflict of interest.
References
- 1.Boyle JP, Thompson TJ, Gregg EW, et al. Projection of the year 2050 burden of diabetes in the US adult population: dynamic modeling of incidence, mortality, and prediabetes prevalence. Popul Health Metr. 2010;8:29. doi: 10.1186/1478-7954-8-29. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.American Diabetes Association Diagnosis and classification of diabetes mellitus. Diabetes Care. 2011;34:S62–S69. doi: 10.2337/dc11-S062. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Knowler WC, Barrett-Connor E, Fowler SE, et al. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med. 2002;346:393–403. doi: 10.1056/NEJMoa012512. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Keys A, Menotti A, Karvonen MJ, et al. The diet and 15-year death rate in the Seven Countries Study. American Journal of Epidemiology. 1986;124:903–915. doi: 10.1093/oxfordjournals.aje.a114480. [DOI] [PubMed] [Google Scholar]
- 5.Estruch R, Martínez-González MA, Corella D, et al. Effects of a Mediterranean-style diet on cardiovascular risk factors: a randomized trial. Ann Intern Med. 2006;145:1–11. doi: 10.7326/0003-4819-145-1-200607040-00004. [DOI] [PubMed] [Google Scholar]
- 6.Fung TT, Rexrode KM, Mantzoros CS, et al. Mediterranean diet and incidence of and mortality from coronary heart disease and stroke in women. Circulation. 2009;119:1093–1100. doi: 10.1161/CIRCULATIONAHA.108.816736. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Martínez-González MA, de la Fuente-Arrillaga C, Núñez-Córdoba JM, et al. Adherence to Mediterranean diet and risk of developing diabetes: prospective cohort study. BMJ. 2008;336:1348–1351. doi: 10.1136/bmj.39561.501007.BE. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Ben-Avraham S, Harman-Boehm I, Schwarzfuchs D, et al. Dietary strategies for patients with type 2 diabetes in the era of multi-approaches: review and results from the Deitary Intervention Randomized Controlled Trial (DIRECT) Diabetes Res Clin Pract. 2009;86:S41–S48. doi: 10.1016/S0168-8227(09)70008-7. [DOI] [PubMed] [Google Scholar]
- 9.Maillot M, Issa C, Vieux F, et al. The shortest way to reach nutritional goals is to adopt Mediterranean food choices: evidence from computer-generated personalized diets. Am J Clin Nutr. 2011;94:1127–1137. doi: 10.3945/ajcn.111.016501. [DOI] [PubMed] [Google Scholar]
- 10.Kastorini CM, Panagiotakos DB. Mediterranean diet and diabetes prevention: myth or fact? World J Diabetes. 2010;1:65–67. doi: 10.4239/wjd.v1.i3.65. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Bild DE, Bluemke DA, Burke GL, et al. Multi-Ethnic Study of Atherosclerosis: objectives and design. American Journal of Epidemiology. 2002;156:871–881. doi: 10.1093/aje/kwf113. [DOI] [PubMed] [Google Scholar]
- 12.Mayer-Davis EJ, Vitolins MZ, Carmichael SL, et al. Validity and reproducibility of a food frequency interview in a Multi-Cultural Epidemiology Study. Annals of Epidemiology. 1999;9:314–324. doi: 10.1016/s1047-2797(98)00070-2. [DOI] [PubMed] [Google Scholar]
- 13.Trichopoulou A, Costacou T, Barnia C, et al. Adherence to a Mediterranean diet and survival in a Greek population. New England Journal of Medicine. 2003;348:2599–2608. doi: 10.1056/NEJMoa025039. [DOI] [PubMed] [Google Scholar]
- 14.Nettleton JA, Steffen LM, Mayer-Davis EJ, et al. Dietary patterns are associated with biochemical markers of inflammation and endothelial activation in the Multi-Ethnic Study of Atherosclerosis (MESA) American Journal of Clinical Nutrition. 2006;83:1369–1379. doi: 10.1093/ajcn/83.6.1369. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Bertoni AG, Burke GL, Owusu JA, et al. Inflammation and the incidence of type 2 diabetes: the Multi-Ethnic Study of Atherosclerosis (MESA) Diabetes Care. 2010;33:804–810. doi: 10.2337/dc09-1679. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Lutsey PL, Jacobs DR, Jr., Kori S, et al. Whole grain intake and its cross-sectional association with obesity, insulin resistance, inflammation, diabetes and subclinical CVD: the MESA Study. Br J Nutr. 2007;98:397–405. doi: 10.1017/S0007114507700715. [DOI] [PubMed] [Google Scholar]
- 17.Nettleton JA, Steffen LM, Ni H, et al. Dietary patterns and risk of incident type 2 diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA) Diabetes Care. 2008;31:1777–1782. doi: 10.2337/dc08-0760. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Lutsey PL, Pereira MA, Bertoni AG, et al. Interactions between race/ethnicity and anthropometry in risk of incident diabetes: the Multi-Ethnic Study of Atherosclerosis. American Journal of Epidemiology. 2010;172:197–204. doi: 10.1093/aje/kwq100. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Nettleton JA, Lutsey PL, Wang Y, et al. Diet soda intake and risk of incident metabolic syndrome and type 2 diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA) Diabetes Care. 2009;32:688–694. doi: 10.2337/dc08-1799. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Kandula NR, Diez-Roux AV, Chan C, et al. Association of acculturation levels and prevalence of diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA) Diabetes Care. 2008;31:1621–1628. doi: 10.2337/dc07-2182. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Panagiotakos DB, Tzima N, Pitsavos C, et al. The association between adherence to the Mediterranean diet and fasting indices of glucose homeostasis: the ATTICA study. J Am Coll Nutr. 2007;26:32–38. doi: 10.1080/07315724.2007.10719583. [DOI] [PubMed] [Google Scholar]
- 22.Salas-Salvadó J, Martínez-González MA, Bulló M, et al. The role of diet in the prevention of type 2 diabetes. Nutr Metab Cardiovasc Dis. 2011;21:B32–B48. doi: 10.1016/j.numecd.2011.03.009. [DOI] [PubMed] [Google Scholar]
- 23.Salas-Salvadó J, Bulló M, Babio N, et al. Reduction in the incidence of type 2 diabetes with the Mediterranean diet: results of the PREDIMED-Reus nutrition intervention randomized trial. Diabetes Care. 2011;34:14–19. doi: 10.2337/dc10-1288. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.InterAct Consortium Mediterranean diet and type 2 diabetes risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) study: the InterAct project. Diabetes Care. 2011;34:1913–1918. doi: 10.2337/dc11-0891. [DOI] [PMC free article] [PubMed] [Google Scholar]