Rossie M, Turati F, Lagiou P, Trichopoilos D, Augustin LS, La Veechia C, Trichopoilos A. Mediterranean diet and glycaemic load in relation to incidence of type 2 diabetes: Results from the Greek cohort of the population-based European Prospective Investigation into Cancer and Nutrition (EPIC). Diabetologia. 2013 Nov; 56(11): 2,405-2,413.
PubMed ID: 23975324
To investigate two different dietary aspects, i.e., adherence to the Mediterranean diet and glycemic load (GL), in relation to diabetes occurrence.
- Could be contacted and responded during follow-up
- Did not have diabetes, cancer, cardiovascular disease or stoke
- Dietary data that did not contain any missing values.
From the original 28,572 EPIC participants, exclusions include the following:
- 1,027 because they could not be traced or did not respond during follow-up
- 2,302 due to prevalent diabetes at enrollment
- 694 due to prevalent cancer
- 1880 due to cardiovascular diseases
- 902 due to stroke
- 344 due to missing values of dietary variables.
The participants for this cohort study were selected from the 28,572 Greek participants of the EPIC study.
Prospective cohort study.
Dietary Intake/Dietary Assessment Methodology
- A semi-quantitative food frequency questionnaire was used to detect usual intake of 150 foods and beverages
- Nutrient, ethanol and energy intakes were calculated using a food composition database modified to accommodate the particularities of the Greek diet
- A Mediterranean diet score was assessed through nine dietary components that capture the essence of the traditional Mediterranean diet. A value of zero or one was assigned to each component of the score as follows:
- For components frequently consumed in the traditional Mediterranean diet (i.e., vegetables, legumes, fruit and nuts, cereals, fish and seafood, as well a high ratio of monounsaturated to saturated lipids), participants whose consumption was above the sex–specific median were assigned a value of one; otherwise, zero.
- For components less frequently consumed in the traditional Mediterranean diet (dairy, as well as meat and meat products), participants whose consumption was at or below the sex–specific median were assigned a value of one; otherwise, zero
- A value of one was also given to men consuming 10g to less than 50g of ethanol per day and to women consuming 5g to less than 25g of ethanol per day; otherwise, a value of zero was assigned
- Thus, the total MDS ranged from zero (minimal adherence to the traditional Mediterranean diet) to nine (maximal adherence to the traditional Mediterranean diet)
- The average daily GL was calculated for each study participant by adding up the products of the carbohydrate content per serving for each food, multiplied by the average number of servings of that food per day, multiplied by the food’s GI
- Average daily GI as calculated by dividing GL by the total amount of available carbohydrate.
- Frequency distribution was estimated for categorical variables and quartile values for continuous variables
- Cox proportional hazards regression models were used to assess the relationships of diabetes with MDS (in categories zero to three, four, five, six to nine, as well as per two-point increase), GL (in sex-specific quartiles, as well as per ten-point increase) or with a combination of GL and MDS (GL less than or equal to or more than sex-specific median and MDS less than or equal to or more than median, four)
- Models were adjusted for age, sex, level of education, BMI, physical activity expressed in MET hours per day and waist-to-hip ratio
- Models for MDS and for the combination of GL and MDS were also adjusted for total energy intake (sex-specific quintiles, categorically); those for GL, for non-carbohydrate energy intake (sex-specific quintiles, categorically), in order to avoid possible over-adjustment due to the high correlation between GL and carbohydrates (since carbohydrate intake contributes to the GL computation)
- Hazard ratios (HR) were estimated for diabetes according to GI through the model used for GL adjusting for total energy intake
- If the value of the adjustment variable was missing, it was replaced using the central category
- Analyses were performed for the overall study population and in strata of age, sex, BMI and physical activity.
Timing of Measurements
- Food frequency questionnaire: Administered at enrollment to gather dietary information for the year preceeding enrollment
- Diagnosis of diabetes: Date of diagnosis or date of death.
Diagnosis of diabetes was ascertained via medical records (discharge diagnosis or death certificates).
- Mediterranean diet score
- Glycemic load.
- Level of education
- Physical activity
- Waist-to-hip ratio
- Total energy intake
- Non-carbohydrate energy intake.
- Initial N: 28,572
- Attrition (final N): 22,295
- Age: 39 to 63 years
- Other relevant demographics:
- Educational levels
- Total physical activity.
- Waist-to-hip ratio.
- Location: Greece.
- Better educated participants tended to be more compliant with the Mediterranean diet
- Younger participants reported a diet with a higher GL in comparison with older participants.
- GL correlated positively, but weakly, with MDS, with medians of 102.1, 111.4, 118.4 and 129.4 in successive MDS categories (Spearman's correlation coefficient 0.28)
- Overall, a significant inverse association of increased adherence to the Mediterranean diet with type 2 diabetes emerged, with a HR of 0.88 (95% CI: 0.78, 0.99) for MDS greater than or equal to six compared with MDS less than or equal to three. The corresponding HRs were 0.94 (95% CI: 0.63, 1.40) for BMI less than 25kg/m2 and 0.87 (95% CI: 0.77, 0.98) for BMI greater than or equal to 25kg/m2 (P for heterogeneity = 0.868). No heterogeneity was evident by age (P=0.560), sex (P=0.487) or physical activity level (P=0.495).
- The HRs for successive GL quartiles, compared with the lowest quartile of intake, were 1.11 (95% CI: 0.98, 1.25), 1.13 (95% CI: 0.99, 1.29) and 1.21 (95%CI: 1.05, 1.40), respectively, with a significant trend in risk (P=0.013)
- The HRs for the highest vs. the lowest GL quartiles were 1.21 (95% CI: 1.05, 1.41) after adjustment for fats, 1.21 (95% CI: 1.02, 1.44) after adjustment for fiber, 1.18 (95% CI: 1.02, 1.37) after adjustment for alcohol and 1.20 (95% CI: 1.04, 1.39) after adjustment for meat
- The HR for the highest quartile of GL was 0.77 (95% CI: 0.47, 1.25; P for trend = 0.308) among participants with BMI less than 25kg/m2 and 1.26 (95% CI: 1.08, 1.47; P for trend = 0.004) among those with BMI greater than or equal to 25kg/m2 (P for heterogeneity = 0.494)
- Results did not significantly differ by age (P=0.113), sex (P=0.951) or physical activity level (P=0.415)
- With reference to GI, compared with the lowest quartile, the HR was 1.14 (95% CI: 1.01, 1.29) for the second quartile, 1.13 (95% CI: 1.00, 1.28) for the third quartile and 1.14 (95% CI: 1.01, 1.30) for the highest quartile. There was no heterogeneity among strata of BMI (P=0.772).
- Compared with participants with a diet characterized by a high GL and a low MDS (i.e., GL higher than 129.0/105.5 for men and women and MDS less than or equal to four), the HRs were 0.89 (95% CI: 0.79, 1.00) for those with a high GL diet and a high MDS; 0.89 (95% CI: 0.78, 1.02) for those with a low GL diet and a low MDS; and 0.82 (95% CI: 0.71, 0.95) for those with a low GL diet and a high MDS. The test for interaction was not significant (P=0.722).
A low glycemic load diet that also adequately adheres to the principles of the traditional Mediterranean diet may reduce the incidence of type 2 diabetes.
This study evaluated the impact of following the Mediterranean diet and the glycemic load of foods with the incidence of diabetes in the Greek participants of the EPIC trial. Diet information was collected once only at the time of enrollment (1994 to 1999) and the participants were followed until December 2011. Although the researchers consider that the dietary habits recorded at baseline may not have been consistent throughout the follow-up period, they dismissed this, which is a significant limitation of the study. Similarly, anthopometric measures and physical activity were also taken once at baseline only. Participants were 39 to 63 years of age at the time of enrollment; it is unrealistic to expect diet and and activity patterns in this wide age range would not change over more than 15 years of follow-up.
The researchers did not use or describe any blinding for the investigators who were reviewing the medical records for a diagnosis of diabetes.
Research Design and Implementation Criteria Checklist: Primary Research
|1.||Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies)|
|2.||Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about?|
|3.||Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to nutrition or dietetics practice?|
|4.||Is the intervention or procedure feasible? (NA for some epidemiological studies)|
|1.||Was the research question clearly stated?|
|1.1.||Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified?|
|1.2.||Was (were) the outcome(s) [dependent variable(s)] clearly indicated?|
|1.3.||Were the target population and setting specified?|
|2.||Was the selection of study subjects/patients free from bias?|
|2.1.||Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study?|
|2.2.||Were criteria applied equally to all study groups?|
|2.3.||Were health, demographics, and other characteristics of subjects described?|
|2.4.||Were the subjects/patients a representative sample of the relevant population?|
|3.||Were study groups comparable?|
|3.1.||Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT)|
|3.2.||Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline?|
|3.3.||Were concurrent controls used? (Concurrent preferred over historical controls.)|
|3.4.||If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis?|
|3.5.||If case control or cross-sectional study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable. Criterion may not be applicable in some cross-sectional studies.)|
|3.6.||If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")?|
|4.||Was method of handling withdrawals described?|
|4.1.||Were follow-up methods described and the same for all groups?|
|4.2.||Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.)|
|4.3.||Were all enrolled subjects/patients (in the original sample) accounted for?|
|4.4.||Were reasons for withdrawals similar across groups?|
|4.5.||If diagnostic test, was decision to perform reference test not dependent on results of test under study?|
|5.||Was blinding used to prevent introduction of bias?|
|5.1.||In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate?|
|5.2.||Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.)|
|5.3.||In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded?|
|5.4.||In case control study, was case definition explicit and case ascertainment not influenced by exposure status?|
|5.5.||In diagnostic study, were test results blinded to patient history and other test results?|
|6.||Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described?|
|6.1.||In RCT or other intervention trial, were protocols described for all regimens studied?|
|6.2.||In observational study, were interventions, study settings, and clinicians/provider described?|
|6.3.||Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect?|
|6.4.||Was the amount of exposure and, if relevant, subject/patient compliance measured?|
|6.5.||Were co-interventions (e.g., ancillary treatments, other therapies) described?|
|6.6.||Were extra or unplanned treatments described?|
|6.7.||Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups?|
|6.8.||In diagnostic study, were details of test administration and replication sufficient?|
|7.||Were outcomes clearly defined and the measurements valid and reliable?|
|7.1.||Were primary and secondary endpoints described and relevant to the question?|
|7.2.||Were nutrition measures appropriate to question and outcomes of concern?|
|7.3.||Was the period of follow-up long enough for important outcome(s) to occur?|
|7.4.||Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures?|
|7.5.||Was the measurement of effect at an appropriate level of precision?|
|7.6.||Were other factors accounted for (measured) that could affect outcomes?|
|7.7.||Were the measurements conducted consistently across groups?|
|8.||Was the statistical analysis appropriate for the study design and type of outcome indicators?|
|8.1.||Were statistical analyses adequately described and the results reported appropriately?|
|8.2.||Were correct statistical tests used and assumptions of test not violated?|
|8.3.||Were statistics reported with levels of significance and/or confidence intervals?|
|8.4.||Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)?|
|8.5.||Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)?|
|8.6.||Was clinical significance as well as statistical significance reported?|
|8.7.||If negative findings, was a power calculation reported to address type 2 error?|
|9.||Are conclusions supported by results with biases and limitations taken into consideration?|
|9.1.||Is there a discussion of findings?|
|9.2.||Are biases and study limitations identified and discussed?|
|10.||Is bias due to study’s funding or sponsorship unlikely?|
|10.1.||Were sources of funding and investigators’ affiliations described?|
|10.2.||Was the study free from apparent conflict of interest?|