Rather than describing hypothesized healthy eating patterns or recommended patterns, the patterns we identified in this analysis were reflective of the patterns of consumption that actually existed within the AARP cohort population. A potential criticism of this approach is that, given the data driven nature of the factors, they are dependent on the study population for their validity. Following from this, in a different population, or even in the same population at a different time, we might have observed a different set of factors thus limiting the interpretive value of these dietary patterns. But analogous versions of two of the three patterns we observed, the fruit and vegetable pattern and the meat and potatoes pattern, have emerged repeatedly in studies using factor analysis to study dietary patterns in North America (12
), Europe (11
), and Asia(14
). It is frequently the case that these studies identified additional factors, often of unique relevance to the locality of the study, but the fruit and vegetable and the meat and starch patterns were ubiquitous. The common observation of these patterns occurred despite the obvious geographical and cultural differences, despite the use of different FFQs, and despite different decisions by investigators with respect to food groupings and number of factors to retain. Furthermore, in longitudinal analyses, these patterns have been shown to be highly stable over time (26
). Given the broad geographic and temporal consistency in factor analysis results, it is reasonable to conclude that the fruit and vegetable and the meat and starch patterns we observed are not likely to be the results of chance observations but rather reflect true underlying dietary patterns observed in many populations over time, and therefore do capture important dimensions of the dietary experience in the AARP cohort.
The seven previous prospective studies of diet patterns as identified by factor analysis and subsequent risk of colorectal cancer (11
) have found associations that were generally consistent with what we observed in the AARP cohort. The fruit and vegetable pattern has been associated with a reduced risk of colorectal cancer in most cohort studies (12
), but the associations have been modest and typically were not statistically significant. Conversely, the meat and starch pattern has been associated with increased risk of colorectal cancer in most (12
), but not all (11
), studies, and even in the studies that did find increased risk with high score on the meat and potatoes factor, the associations were not statistically significant.
The first factor had the appearance of a global fruit and vegetable score. In that way, using it as an exposure may not have been too different from simply using fruits and vegetables as an exposure and then controlling for all other dietary variables. The advantage of factor scores in this situation may have been the ability of the factors to account adequately for variation in all other dietary components (since all foods made weighted contributions to the factor score), whereas in a traditional single food (or food group) analysis, controlling for potential confounding by other dietary constituents may have been incomplete. If this is true, it may help explain why we were able to observe a fruit and vegetable effect in men when many cohorts looking only at fruit or at vegetables observed null results (27
). We still observed a null result for women on the fruit and vegetable factor, though, and this is consistent with most recent results from prospective studies of these food groups taken individually (27
The associations we observed for the meat and potatoes factor are consistent with results published in two recent meta-analyses of meat and risk of colorectal cancer (38
). While some have noted that almost all of the individual studies in those meta-analyses, and in subsequent publications (40
), found only modest and not statistically significant increases in risk, the association we observed between high score on the meat and potato factor and risk of subsequent disease provide support to the notion that diets characterized by high intake of meat, and particularly red meat, increase risk of colorectal cancer.
While, as expected, we did observe the two ubiquitous patterns (fruits and vegetables and meat and potatoes), the third pattern, the fat-reduced and diet food factor, was novel. The dieting-related features of this pattern caused us to wonder what other characteristics described people with high scores on this factor. For example, were they overweight people whose adoption of this pattern reflected a desire to address poor health and dissatisfaction with current weight? But on the contrary, high scores on this factor were associated with health-promoting behaviors and lower BMI. When we controlled for these, however, we still observed the inverse association giving us greater confidence that this dietary pattern was itself responsible for the decreased risk. Nonetheless, it is likely that we did not control for the “healthy” lifestyle factors completely, either through imperfect measurement of the exposures or through failure to control for other unknown or unmeasured confounding factors, and therefore we cannot rule out residual confounding as an explanation for the inverse association.
Interestingly, we found different associations between what appeared to be similar factors in men and women and subsequent risk of colorectal cancer. It is possible that women and men completed the FFQ differently resulting in different degrees of measurement error. If the reported diet in women had more random error, then associations would be attenuated compared to what we observed in the men. But the associations were not simply attenuated, as we actually observed stronger associations for the meat and potatoes factor in women. The use of MHT was more common among women with low scores on the meat and potatoes factor, and given previous studies showing a possible inverse association between MHT and colorectal cancer (41
), this could, in part, explain the stronger association in women than in men for this variable. We did control for MHT use in multivariate models, but it is possible that we did so imperfectly and thus we cannot rule out residual confounding. There was no association between MHT and the fruit and vegetable factor scores, however, and yet we still saw differences in risk estimates for men and women on this variable. An alternate possibility is that genuine differences exist in the diet-related pathology of colorectal cancers between men and women.
In summary, we observed that both for men and (especially) women, a dietary pattern characterized by frequent meat and potatoes consumption was associated with an increased risk of colorectal cancer, whereas a dietary pattern typified by frequent consumption of fat-reduced and diet foods was associated with a significant reduction in risk among men and the suggestion of a decreased risk among women. And while a vegetables and fruits pattern was associated with reduced risk among men, it was not associated with colorectal cancer outcomes in women. These differences in the associations among dietary patterns and risk of colorectal cancer do raise interesting questions with respect to a possible physiological role of gender in disease etiology, but in general, dietary patterns characterized by comparatively low frequency of meat and potato consumption, high frequency of fruit and vegetable intake, and high frequency of fat-reduced foods are consistent with a decreased risk of disease.