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Fung TT, McCullough M, van Dam RM, Hu FB. A prospective study of overall diet quality and risk of type 2 diabetes in women. Diabetes Care. 2007 Jul; 30(7): 1,753-1,757.

PubMed ID: 17429059
Study Design:
Prospective Cohort Study
B - Click here for explanation of classification scheme.
POSITIVE: See Research Design and Implementation Criteria Checklist below.
Research Purpose:

To assess the association between the Alternate Healthy Eating Index (AHEI) and risk of type 2 diabetes in women.

Inclusion Criteria:
  • Participants were part of the Nurses’ Health Study (NHS) that began in 1976 when 121,700 female nurses aged 30 to 55 years living in 11 U.S. states responded to a questionnaire regarding medical, lifestyle and other health-related information
  • This analysis included women who completed the 1984 FFQ with 70 missing items and total energy intake (as calculated from the FFQ) between 500 and 3,500kcal per day.
Exclusion Criteria:

A history of cancer, cardiovascular disease or diabetes at baseline.

Description of Study Protocol:

Study Description

A total of 80,029 women aged 38 to 63 years in the Nurses’ Health Study were followed from 1984 to 2002. The AHEI score was computed from dietary information collected from five repeated food frequency questionnaires administered between 1984 and 1998. Relative risks (RRs) for type 2 diabetes were calculated using Cox proportional hazards models and adjusted for known diabetes risk factors. Also examined was how changes in score in four, six to eight and 10 to 12 years are associated with diabetes risk.

Study Duration

Follow-up over 18 years.


United States

Data Collection Summary:

Dietary Assessment Method

Participants completed a 116-item food frequency questionnaire (FFQ).

Brief Description of Dietary Patterns

  • The AHEI score was computed from dietary information collected from five repeated food frequency questionnaires administered between 1984 and 1998
  • Scoring for the AHEI was based on intake levels of nine components:
    • Fruits
    • Vegetables
    • Ratio of white (seafood and poultry) to red meat
    • Trans fat
    • Ratio of polyunsaturated to saturated fat
    • Cereal fiber
    • Nuts and soy
    • Moderate alcohol consumption (0.5 to 1.5 servings per day)
    • Long-term multivitamin use (five years).
  • These components were chosen on the basis of their association with disease and mortality risk in observational and experimental studies
  • Each component contributed zero to 10 points, except for the multivitamin component, which was assigned either 2.5 or 7.5 to avoid over-weighting of this binary variable.
  • Summing up the scores for all components, the maximum possible AHEI score was 87.5.

Outcomes Measured

Outcome measured was incident type 2 diabetes that occurred between the return of the 1984 questionnaire and June 1, 2002.

Methods of outcome assessment

  • When a participant reported a new diagnosis of diabetes in the biennial questionnaires, she was mailed a supplementary questionnaire that assessed symptoms, diagnostic tests and treatment to confirm the diagnosis. Diabetes was confirmed when one or more of the following criteria were met:
    • Manifestation of classic symptoms (excessive thirst, polyuria, weight loss and hunger) plus an elevated fasting glucose level [140mg per dL (7.8mmol per L)] or elevated non-fasting level [200mg per dL (11.1mmol per L)]
    • Asymptomatic but elevated plasma glucose level on at least two different occasions (as defined above) or abnormal oral glucose tolerance test (200mg per dL two hours after glucose load)
    • Receipt of any hypoglycemic treatment for diabetes.
  • Review of medical records by an endocrinologist blinded to the questionnaire information confirmed 61 (98%) of the 62 reports.
Description of Actual Data Sample:
  • Sample size:
    • Initial N: The Nurses’ Health Study (NHS) began in 1976 with 121,700 female nurses
    • Current study N: 80,029 women with follow-up from 1984 to 2002.
  • Age: 38 to 63 years
  • Gender: 100% female
  • Race/ethnicity: US, mostly white
  • Baseline health status:
    • Free of history of cancer, cardiovascular disease and diabetes at baseline
    • BMI: 23.6 to 24.7
    • Hypertension rate: 20% to 21%
    • Hypercholesterolemia rate: 7% to 11%.
  • Baseline distribution of dietary patterns:
    • AHEI range: 24.2 to 53.5
    • Energy intake range: 1,516kcal to 1,958kcal per day
    • Glycemic load range: 97 to 102.
Summary of Results:
  • Using the cumulative AHEI score and adjusting for potential confounders, the authors found an inverse association between AHEI score and type 2 diabetes
  • Relative risk (RR) comparing top to bottom quintiles was 0.64 [(95% CI: 0.58 to 0.71) P<0.0001]. This association was slightly stronger among the symptomatic individuals [RR comparing fifth to first quintile 0.56 (0.49 to 0.64) P<0.0001].
  • Additional adjustment for waist-to-hip ratio somewhat attenuated the association, but it remained statistically significant, indicating that diet composition apart from adiposity influences diabetes risk
  • In stratified analysis, the AHEI was associated with diabetes only among non-smokers. RR comparing top to bottom quintiles among non-smokers was 0.74 [(0.66 to 0.83) P<0.0001, P interaction between smokers and non-smokers was 0.06]. No sign of any association was observed with smokers.
  • The inverse association remained strong among women with no hypertension [fifth vs. first quintile RR 0.60 (0.52 to 0.69), Ptrend<0.0001], but no association was observed among those with hypertension (P interaction=0.0001)
  • Women who reported normal blood cholesterol level had an RR of 0.66 [(0.58 to 0.76) P trend<0.0001] but association for those reporting hypercholesterolemia was weaker [fifth vs. first quintile RR 0.88 (0.74 to 1.04), P trend=0.07, P interaction=0.002]
  • Also examined were individual components in the AHEI for their contribution to the inverse association with type 2 diabetes risk, showing a substantial inverse association with nuts and soy, cereal fiber and the white-to-dark meat ratio
  • For every five-point increase in the score of these components (maximum score for each component is 10 points), the multivariate RR for diabetes was 0.56 [(95% CI: 0.50 to 0.63) Ptrend<0.0001] for cereal fiber, 0.86 [(0.81 to 0.91) Ptrend<0.0001] for nuts and soy, and 0.89 [(0.84 to 0.95) P trend=0.0002] for the white-to-red meat ratio
  • As alcohol has shown clear inverse association in epidemiological studies, the authors explored the importance of the alcohol component for diabetes risk by removing it from the AHEI score and adjusting for alcohol intake in the proportional hazards model. The AHEI remained inversely associated with diabetes, albeit weaker [RR comparing fifth with first quintile 0.81 (0.73 to 0.89), Ptrend<0.0001]. The RR for alcohol consumption of 15g per day (1 drink) compared with abstainers, after adjustment for the AHEI score (without the alcohol component) was 0.49 (0.43 to 0.55).
  • To explore the period during follow-up at which diet may have an influence on diabetes development, the investigators used the baseline and the most recent AHEI score to predict diabetes risk and found associations of a magnitude similar to that for the cumulative updated AHEI score in the main analysis (data not shown). Most women did not change their diet drastically during follow-up.
  • Women who consistently had a high AHEI score (fourth or fifth quintile) during the follow-up period had a substantially lower risk for diabetes than those who consistently had a low score (first or second quintile)
  • Also examined was the association between a change in the AHEI score according to different time intervals of dietary change. When women scored high in the beginning of a score change period but dropped to low scores at the end of that period, there was no significant reduction of risk. On the other hand, changes in score from low to high conferred a substantial risk reduction, even when changes occurred in the last 4 years [RR comparing low-to-high vs. low-to-low in four years 0.78 (95% CI: 0.66 to 0.92), Ptrend=0.003].
  • Model adjustments:
    • Model 1: Age and energy adjusted
    • Model 2 multivariate: Adjusted for:
      • Age
      • Energy intake
      • Smoking
      • BMI (continuous and quadratic term)
      • Physical activity
      • Family history
      • Menopausal status
      • Post-menopausal hormone use.
    • Model 3 multivariate: As Model 2 plus waist-to-hip ratio (WHR); analysis limited to those with waist and hip information in 1986. 


Total Energy Intake BMI Sex Age Smoking Alcohol Intake Physical Activity
x x   x x Part of AHEI x


Author Conclusion:

A higher AHEI score is associated with a lower risk of type 2 diabetes in women. Therefore, the AHEI score may be a useful clinical tool to assess diet quality and to recommend for the prevention of diabetes.

Strengths and Limitations


  • Long follow-up, multiple dietary measurements.
  • Statistical control for BMI, WHR
  • Repeated measurements of potential confounders.


  • Additional confounders may not have been accounted for
  • Possible misreporting of diabetes, although it should be less in this cohort than in general population
  • AHEI is not developed specifically for diabetes prevention.
Reviewer Comments:

No comment.

Research Design and Implementation Criteria Checklist: Primary Research
Relevance Questions
  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)
Validity Questions
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 intervening factors 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?