Using a novel statistical method, we derived a diet pattern score that was strongly associated with markers of inflammation and endothelial dysfunction. This pattern strongly predicted risk of type 2 diabetes in a nested case-control analysis, independent of BMI and other diabetes risk factors. This association was subsequently confirmed in 2 separate cohorts of women. These findings provide evidence that the association between dietary factors and risk of type 2 diabetes may be mediated in part by inflammation and endothelial dysfunction.
The pattern we identified was characterized by high intakes of sugar-sweetened soft drinks, refined grains, diet soft drinks, processed meat, and low intakes of wine, coffee, cruciferous vegetables, and yellow vegetables. Other vegetables (celery, mushrooms, green pepper, corn, mixed vegetables, eggplant, and summer squash) were not correlated with inflammation and were only moderately associated with the pattern; thus, the contribution of this food group to the overall pattern was negligible. Most of these food groups have been identified to be associated with diabetes risk in previous studies and some have also been found to be associated with inflammatory markers. Moderate alcohol consumption (1–3 drinks/d) has been consistently associated with lower incidence of diabetes (26
) and lower levels of pro-inflammatory markers (27
). An inverse association between coffee consumption and risk of type 2 diabetes was observed in several prospective cohort studies (33
). Sugar-sweetened beverages have been associated with risk of diabetes among women (37
); these beverages contribute importantly to glycemic load, which has been associated with inflammatory markers (38
). Several epidemiologic studies found that diets rich in whole grains compared with refined grains may protect against type 2 diabetes (39
). Refined grains may be associated with increased diabetes risk because these foods tend to be low in cereal fiber and have a high glycemic index, which both appear to be associated with increased diabetes risk (4
). Other components of whole grains may also have beneficial effects, with isoflavones being potentially associated with decreased inflammation (44
). Frequent consumption of meat, in particular processed meat, has been consistently shown to increase the risk of diabetes in prospective studies (6
). Advanced glycation end products, which are high in processed animal foods high in protein and fat, have been found to promote inflammatory mediators in humans (48
). Vegetable consumption was inversely associated with risk of diabetes in the National Health and Nutrition Examination Survey (49
) and in a Finnish cohort study (50
) but not among older women in the Iowa Women’s Health Study (41
). The effects of vegetable consumption on inflammatory processes are largely unknown. A cross-sectional study of the elderly observed lower concentrations of CRP with higher fruit and vegetable consumption, although this study did not provide estimates for vegetables alone or for specific subgroups of vegetables (51
). In a recent trial over a 2-y period among men and women with the metabolic syndrome, increased consumption of fruit, vegetables, walnuts, whole grains, and olive oil significantly reduced concentrations of CRP, IL-6, IL-7, and IL-18 and improved endothelial function compared with that in a control group that consumed an otherwise healthy diet (<30% fat, <10% saturated fat) (52
). These effects were attenuated but not eliminated by additional adjustment for weight change over the course of the study.
Recently, we reported the role of overall dietary patterns derived by using factor analysis in predicting the risk of diabetes in 2 cohort studies (5
). A prudent pattern (characterized by a high consumption of vegetables, fruit, fish, poultry, and whole grains) was associated with a modest nonsignificant risk reduction in both studies, whereas a Western pattern (characterized by a high consumption of red meat, processed meat, French fries, high-fat dairy products, refined grains, and sweets and desserts) was associated with an increased risk of type 2 diabetes. Here, the multivariate RR for extreme quintiles was 1.49 (95% CI: 1.26, 1.76) in the NHS (6
) and 1.59 (95% CI: 1.32, 1.93) in the Health Professionals Follow-up Study (5
). The prudent pattern was inversely associated with plasma concentrations of CRP and E-selectin, and the Western pattern showed a positive relation with CRP, E-selectin, sICAM-1, and sVCAM-1 after adjustment for age, BMI, physical activity, smoking status, and alcohol consumption in the NHS among control women of the same nested case-control study used in our analysis (10
). In addition, the Western pattern was significantly correlated with CRP in the Health Professionals Follow-up Study after adjustment for a variety of risk factors but not after adjustment for BMI (9
). In a recent study of 4304 Finnish men and women, a prudent pattern (characterized by higher consumption of fruit and vegetables) was significantly associated with a lower risk of type 2 diabetes, whereas a “conservative” pattern (characterized by consumption of butter, potatoes, and whole milk) was significantly associated with an increased risk (7
In contrast with our previous analyses and the Finnish study, which derived the dietary patterns by using factor analysis based on the observed covariance among food groups, the present study used the information on inflammatory biomarkers to derive the dietary pattern. The advantage of this approach as opposed to the factor analysis approach is that the derived dietary pattern incorporates information on biological pathways and thus is hypothesis-driven instead of being driven by patterns of eating behavior and could be more predictive of disease risk. Using the same technique, we previously identified a dietary pattern in the prospective EPIC-Potsdam cohort that was characterized by a high intake of fresh fruit and a low intake of sugar-sweetened beverages, beer, meat, poultry, processed meat, legumes, and bread, excluding whole-grain bread (8
). Subjects who scored high had high plasma concentrations of HDL cholesterol and adiponectin and low plasma concentrations of glycated hemoglobin. After multivariate adjustment, the RR for type 2 diabetes mellitus for extreme quintiles of the dietary pattern score was 0.27 (95% CI: 0.13, 0.64; P
for trend < 0.001). However, the pattern was not significantly associated with CRP concentrations, and we were not able to verify these results in independent study samples, as we did in the present study.
The current RRR approach requires response (biomarker) information. This information may not be available in many studies otherwise suitable for evaluating diet-disease associations. Also, the biomarker information available may not reflect the current state of knowledge. In our study, we selected inflammatory markers that previously predicted risk of diabetes in the same cohort (53
). However, pathways other than inflammation may also be relevant in the development of diabetes. For example, we observed significant associations between markers of body iron stores (55
) and β cell function (56
) and risk of diabetes in the NHS, but did not consider these markers in the present analysis for 2 reasons. First, measures of body iron stores were only weakly correlated with inflammatory markers, which limits the usefulness of their additional inclusion in the RRR analysis. Second, β cell function was not measured in a large proportion of the current sample. Although this narrows potential effects of diet on diabetes risk to a single pathway, previous RRR analyses suggest that one single dietary pattern is unlikely to explain several different and independent pathways (8
). It might be of interest to evaluate whether other biomarkers play a role in mediating effects of the dietary pattern on inflammatory markers, for example, lipoproteins. Unfortunately, we did not have lipoprotein markers available for our nested case-control study population.
Obesity induces a state of chronic low-grade inflammation (58
), and excess body fat may therefore also explain associations between those food groups identified to be components of the dietary pattern and inflammatory markers. For example, diet soft drinks were directly associated with BMI cross-sectionally in the NHS-II (37
), although this association most likely represents a reverse causation because the use of diet soft drinks instead of regular soft drinks is the most frequently reported diet intervention to lose weight in US adults (59
). Although diet soft drinks were identified as a component of the RRR pattern, associations between diet soft drinks and inflammatory markers may be confounded by BMI. With use of the BMI-adjusted biomarker levels as responses in RRR, the pattern remained similar with sugar-sweetened beverages and refined grains being positively associated with the pattern and wine, coffee, and cruciferous vegetables being negatively associated. However, diet soft drinks were no longer an important component of the pattern. Adjustment for BMI also partly attenuated the age-adjusted associations between the dietary pattern and risk of diabetes. However, it is also possible that weight gain is one potential pathway by which the dietary pattern is associated with inflammation and diabetes risk. Adjustment for BMI may therefore lead to an underestimation of the true effect of the diet. To determine whether BMI is a confounder or mediator is not possible with our study design, because associations between the dietary pattern, BMI, and inflammatory markers were analyzed cross-sectionally. Nevertheless, component foods such as sugar-sweetened soft drinks, refined grains, wine, coffee, and vegetables appear to relate to inflammatory markers independent of BMI, and the association between the dietary pattern and diabetes risk remained strong after adjustment for BMI and the waist-to-hip ratio. Our data also suggest that the diet pattern score may be more strongly associated with diabetes risk among obese women than among lean women.
The repeated dietary measurements used in this study were advantageous because they dampened measurement errors and took into account changes in eating behaviors over time (23
). Compared with the traditional approach of examining the effects of individual nutrients or foods, the dietary pattern approach has the advantage of representing the cumulative effects of overall diet.
The NHS and NHS-II cohorts are study populations of US female nurses and therefore are not representative of the general US female population. Thus, our results should be replicated in other populations. Another potential limitation of our study is the reliance on self-reported confounder information. For example, smoking has been related to inflammation (60
) and diabetes risk (4
), and smoking cessation has effects on body weight (61
). Because smoking and poor diet may also be part of an unhealthy lifestyle, residual confounding due to measurement error in assessing smoking history or due to insufficient control in statistical models might have biased our observations, but it is unlikely that such a bias would explain the strong relation between the dietary pattern and diabetes risk. Similarly, a history of hypertension may influence dietary behavior and is associated with inflammation (62
). Although adjustment for hypertension did not alter our observations, residual confounding might still be present.
In conclusion, our data suggest that a diet high in sugar-sweetened soft drinks, refined grains, diet soft drinks, and processed meat and low in wine, coffee, cruciferous vegetables, and yellow vegetables may increase the risk of developing type 2 diabetes, possibly by exacerbating inflammatory processes.