We identified a dietary pattern, characterized by high consumption of white bread, fried potatoes, sugar in tea and coffee, burgers & sausages, soft drinks, and lower consumption of French dressing/vinaigrette and other vegetables that was associated with higher total cholesterol, lower HDL cholesterol and higher triglycerides and was predictive of increased risk of CHD. A second dietary pattern characterised by higher consumption of red meat, cabbage, brussels sprouts and cauliflower, and lower consumption of wholemeal bread, jam, marmalade and honey, tofu & soy, buns, cakes, pastries, fruit pies and polyunsaturated margarine also remained associated with increased risk of CHD after adjustment for non-dietary health behaviors and socioeconomic status.
We selected serum lipids to serve as intermediate biomarkers of risk in the dietary pattern-CHD analysis. There is strong evidence from observational studies 28
, cholesterol-lowering trials 29
and genetic association studies 30, 31
that blood lipids are causal factors for disease. We found mean differences in total cholesterol, HDL cholesterol and triglycerides of 0.15, 0.18 and 0.37 mmol/L across quartiles of dietary pattern score 1, corresponding to two-fold higher disease rate in the base model. The impact of diet appeared little confounded by associated health behaviors. Adjustments for employment grade, a powerful indicator of adult socioeconomic status, as well as smoking, alcohol and physical activity reduced the observed effect by 15%.
Dietary pattern 1 was strongly associated with lower HDL cholesterol and higher triglyceride levels. The relationship between dietary pattern 1 and CHD risk was attenuated by inclusion of BMI in the model. This suggests that this dietary pattern is a determinant of the metabolic syndrome risk profile. Additional attenuation by the inclusion of blood pressure supports this interpretation. Further work is required to directly investigate the impact of this dietary pattern on risk of metabolic syndrome.
Previous RRR studies of diet and CHD have used a range of intermediate markers including HDL cholesterol, LDL cholesterol, lipoprotein(a), C-peptide, C-reactive protein 7
, plasma homocysteine, folate, vitamin B12 8
and fat, carbohydrate and fibre density 10
. Despite differences in the intermediate markers, there are some similarities in the foods identified which were associated with increased risk of CVD such as potatoes and fried potatoes 8, 9
and processed meat 9
and in the foods that were shown to be associated with decreased risk of CVD, namely, wholegrains 10
and vegetables 7-10
. Similarly, using cluster analysis to identify dietary patterns in the Whitehall II study, Brunner et al. identified a healthy dietary cluster that was charcterised by higher intakes of wholemeal bread, fruits, vegetables and polyunsaturated margarine and lower intakes of red meat which was associated with lower risk of CHD. Previous RRR studies have not identified soft drinks in their dietary patterns although recent research has identified associations between soft drink consumption and risk factors for cardiovascular disease such as obesity, high blood pressure, abnormal glucose and low HDL cholesterol which is consistent with our findings 33
Strengths of our study include the large sample size, its prospective nature, and the rigorous methods of outcome ascertainment. While Hoffman et al. 7
also incorporated HDL and LDL cholesterol as dependent variables, as well as a range of intermediate markers, the study was based on a case-control design which has potential for recall bias and the biomarker measurements used as the intermediate markers were measured after the diagnosis of disease. In addition, their study only included women. Nettleton et al. 9
conducted a cross-sectional study investigating carotid intima media thickness rather than coronary events.
Foods identified in the dietary pattern may be indicators of other foods with which they are consumed. For example, salad dressing is not consumed alone and was correlated with salad vegetables in our study (data not shown); its presence in the dietary pattern is likely to reflect consumption with salad vegetables. When investigated separately, salad dressing was not associated with CHD risk, however as the effects of a total dietary pattern may be additive, a causal role for salad dressing cannot be ruled out. Similarly, a dietary pattern containing cruciferous vegetables (such as brussels sprouts and cauliflower) was associated with increased risk of CHD in this analysis. Importantly, when the individual foods were investigated separately none of the foods showed significant associations with risk of CHD (data not shown).
Research into dietary patterns aims to characterize the whole diet in combination, providing a summary measure of dietary exposure and capture complex behaviors and potentially interactive and antagonistic effects among nutrients that might impact upon health outcomes. Reduced rank regression analysis is a new statistical method which has been applied to dietary pattern research. It combines data-driven methods with use of a priori
knowledge of diet-disease relationships. RRR determines dietary patterns that explain the greatest variation in the intermediate markers/responses rather than explaining variation in food intakes and therefore, is particularly suited to identifying and confirming pathways through which dietary factors influence disease development in studies where intermediate biomarkers of exposure or disease are available 12
Additional work with the RRR techniques is required to determine the importance of dietary patterns extracted subsequent to the first pattern, which by definition explain the greatest variation in biomarkers. In our study, the third dietary pattern explained very little additional variation in any of the response variables, and was not predictive of coronary heart disease. However, previous work by Hoffmann et al. 5
showed that only the fourth dietary pattern extracted was associated with risk of type diabetes, despite explaining a small proportion of the variation in comparison to the first three dietary patterns that were extracted. Further work is required is determine the importance of extracting and investigating these subsequent patterns. A potential weakness of the RRR approach is the cross-sectional nature of underlying RRR dietary pattern analysis, however in our analysis we excluded participants who had a previous history of coronary heart disease in order to reduce the impact of changes in dietary behaviour due to pre-existing disease. In addition, further work is also required to determine whether the optimal use of the RRR method involves using biomarkers that reflect one disease progression pathway, with individual pathways modelled separately or whether there is an advantage to using multiple biomarker pathways in the same regression modelling 11, 12
The dietary patterns explained 3.9% of the variation in total cholesterol, 7.1% of the variation in HDL cholesterol and 5.3% of the variation in triglycerides. These results are comparable to other studies using RRR methods where biomedical risk factors have been used as the response variable 7, 11
. Studies using intakes of nutrient have tended to explain higher variation in those responses 5, 6, 13
. However, this is unsurprising as bloods lipids are a more remote response variable than nutrient intakes.
A range of socio-demographic factors (age, sex, ethnicity, employment grade), health behaviours (smoking, physical activity, alcohol) and other risk factors (blood pressure and BMI) were investigated as confounders and shown to attenuate the relationship between the dietary pattern and coronary heart disease, although the relationship remained significant. However, residual confounding cannot be ruled out due to the potential for measurement error among the covariates. BMI and blood pressure were included in the final regression models and shown to attenuate the relationship between dietary patterns and risk of CHD. This finding is consistent with the mediating role of these risk factors. The fully adjusted models may therefore underestimate the effect of diet 34
, while model 3, adjusted for energy misreporting, socio-demographic factors and non-dietary health behaviors may reflect the role of diet in CHD causation operating through multiple pathways.
This research highlights that certain dietary patterns are strongly associated with blood lipids and risk of CHD, and adds to the evidence that influences on HDL cholesterol and triglyceride levels are important in the dietary prevention of CHD. While the dietary pattern we identified may in part act though obesity and increased blood pressure, it appeared to have independent effects on the risk of CHD. Our findings are consistent with the operation of multiple dietary pathways influencing CHD risk. The reduced rank regression method is an advance in methodology, able to identify and confirm mechanisms through which diet may influence disease risk.