In this analysis, several diet-quality scores were associated with similar reductions in type 2 diabetes risk, which points to a common underlying dietary pattern. High-quality diets were associated with greater reductions in the number of type 2 diabetes cases among individuals with a high BMI.
The effects of high-quality diets on type 2 diabetes may be mediated by many factors. A low glycemic load minimizes postprandial glucose spiking, whereas fiber from whole grains, legumes, and nuts reduces glucose absorption (14
). Both may improve insulin demand and β-cell function. Magnesium from nuts and whole grains is also a cofactor for cellular glucose uptake and oxidation (16
). Polyunsaturated fats from vegetable oils and nuts reduce postprandial triglycerides and increase skeletal muscle cell membrane fluidity and glucose uptake compared with saturated fats (17
). Low-fat dairy is included in high-quality diets to reduce the intake of saturated fat but may provide additional benefits because dairy proteins stimulate the secretion of insulinotropic peptides (18
). Mediterranean-type diets include alcohol, which, in moderation, increases insulin sensitivity by an unknown mechanism (19
). Most high-quality diets restrict the intake of red and processed meat because they are major sources of saturated fat and other potentially harmful components. For example, heme iron can accumulate in tissues and potentially damage β-cells through oxidative stress (20
). Nitrates in processed meats are converted into nitrosamines in the intestines and promote insulin resistance in rodents (20
). Moreover, advanced glycation end products are formed when meat is cooked at high temperatures and induce insulin resistance in mice (20
In support of these mechanisms, whole grains (14
), alcohol (19
), low-fat dairy (18
), polyunsaturated fat (17
), and magnesium (16
) are associated with lower risk of type 2 diabetes, whereas glycemic load (15
), red and processed meat (20
), sugar-sweetened beverages (21
), and trans
) are associated with higher risk in meta-analyses of prospective cohort studies. In a meta-analysis of controlled trials, legumes improved glycemic control in people with or without type 2 diabetes (22
), whereas fish oil had no impact on glycemic control among patients with diabetes (23
). Interestingly, fruits and vegetables were not associated with type 2 diabetes in a meta-analysis (24
), which may be because potatoes, sometimes classified as a vegetable, have a high glycemic index and would bias associations toward the null (15
). These findings are consistent with publications from the Health Professionals Follow-Up Study and the Nurses’ Health Study.
Taken together, high-quality diets should have the greatest impact on type 2 diabetes if they include whole grains, nuts, legumes, moderate amounts of alcohol, and low-fat dairy, at the expense of glycemic load, red and processed meat, sugar-sweetened beverages, and trans
fat. Fruits and vegetables also should be included because they can replace harmful foods but may not be as important as other components for diabetes prevention. Fish should be included for the same reason and because of its inverse association with CVD mortality (3
). Finally, sodium should be minimized because of its positive association with hypertension and CVD (7
Among the scores tested, the DASH and aHEI reflected this evidence most strongly, whereas the HEI-2005 and RFS reflect this evidence most weakly. Not surprisingly, the HEI-2005 and RFS were not significantly associated with type 2 diabetes after multivariate adjustment. In the Health Professionals Follow-Up Study, participants in the top quintile of the original HEI or RFS had a 28% (6
) and a 23% (10
) lower CVD risk compared with participants in the bottom quintile. A high HEI (top vs. bottom quintile) also was significantly associated with a 14% lower CVD risk in the Nurses’ Health Study (5
). This suggests that these scores are associated with blood lipids and blood pressure but not insulin resistance.
To improve the predictive power of the original HEI on CVD outcomes, the aHEI was developed. In this study, a high aHEI was associated with 23% lower risk of type 2 diabetes and in the Nurses’ Health Study was associated with 36% lower risk (25
). A high aHEI also was associated with 39% lower risk of CVD in the Health Professionals Follow-Up Study and 29% lower risk in the Nurses’ Health Study (10
). In the Nurses’ Health Study, the aMED and DASH scores had similar associations with CVD (7
). Combined with their high correlations (r
> 0.71), this points to a common underlying dietary pattern. However, the DASH score provided better fit to the data and captured unique dietary variation related to diabetes risk. This could be because it includes sugar-sweetened beverages, which are associated with an increased risk of type 2 diabetes (21
However, despite these differences, the aHEI, aMED, and DASH scores were associated with nearly identical risk reductions. This is because even though some scores were not optimal, they awarded points to a sufficient number of beneficial components. This suggests that public health messages need not be overly strict, as adequate risk reductions can be achieved even if not all dietary recommendations are followed. But because these scores were associated with greater reductions in absolute risk of type 2 diabetes among the overweight and obese, public health messages should focus on improving diet quality in these groups to prevent the greatest number of cases.
Our study has several strengths. First, it is prospective, which minimizes reverse causality. Second, participants were relatively similar, which reduces residual confounding common to studies of diverse populations. Third, cumulative averages of diet scores were used, which accounts for previous dietary information and controls measurement error. Fourth, recall bias was reduced by not updating dietary data after the diagnosis of a chronic disease. Fifth, time-dependent confounding was adjusted for by using updated covariates. Sixth, a large sample size allowed for modest but potentially meaningful changes in risk to be detected.
Our study also has limitations. The first is that because of its ethnic homogeneity (most were white males), its findings may not be generalizable to other populations. The second limitation is the potential for confounding. Dietary patterns could simply be markers for factors such as health awareness. However, we controlled for many possible confounders of the relationship between diet and type 2 diabetes and used continuous diet scores and covariates to assess residual confounding.
In conclusion, several diet-quality scores were inversely associated with type 2 diabetes. These scores reflect a common dietary pattern characterized by high intake of fruits, vegetables, whole grains, nuts, legumes, and unsaturated fats; moderate intake of alcohol; and lowintake of red and processed meat, sodium, sugar-sweetened beverages, and trans fat. High-quality diets may yield the greatest reduction in diabetes cases when followed by those with a high BMI.