DIETARY FACTORS OR DIETARY PATTERNS? HOW TO EFFECTIVELY PREVENT CARDIOVASCULAR DISEASE THROUGH NUTRITION

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1 DIETARY FACTORS OR DIETARY PATTERNS? HOW TO EFFECTIVELY PREVENT CARDIOVASCULAR DISEASE THROUGH NUTRITION Demosthenes B. Panagiotakos, PhD, FRSPH, FACE Associate Professor of Biostatistics & Epidemiology of Nutrition Department of Nutrition and Dietetics Harokopio University of Athens Greece

2 Diet and Cardiovascular disease WHO reports that the 3 most important CVD risk factors are: smoking sedentary lifestyle unhealthy dietary habits because they can be modified!!!

3 The Mediterranean Dietary pattern Several epidemiological studies and clinical trials have shown the beneficial relationship between the Mediterranean dietary pattern and human health.

4 The first evidence Mediterranean Diet & CHD The very first study that indicated the beneficial role of the Mediterranean diet for human health, and for cardiovascular diseases in particular «The strongest correlation was between IHD incidence and average SFA intake or serum cholesterol levels», Ancel Keys ( )

5 DIETARY FACTORS OR DIETARY PATTERNS? Several investigators in the nutritional epidemiology field have suggested using a holistic dietary approach on disease prevention, instead of the food- or nutrient -based approach. Dietary patterns analysis has received much attention during the past few years, adding a new direction in nutritional epidemiology. Jacques PF, Tucker KL. Are dietary patterns useful for understanding the role of diet in chronic disease? Am J Clin Nutr. 2001

6 Why dietary pattern analysis? Traditional analyses that examine the association between diseases incidence and single or a few nutrients or foods, have been found valuable in understanding the role of foods on developing a disease they have also several limitations, both in concept and analysis.

7 Why dietary pattern analysis? Statistical Methodological

8 Why dietary pattern analysis?... it is known that people s nutritional choices include a variety of foods and other nutritional habits that may act synergistically or interactively on the risk of developing CVD. e.g., increased fruits & veggies intake is correlated with decreased animal fat consumption in most populations; people who usually tend to eat healthy have also other healthy behaviours, e.g., physical activity, non-smoking, etc Thus, even epidemiological models may account for residual confounding, a doubt would always exists.

9 Why dietary pattern analysis? In addition nutrient or food intakes are commonly associated with certain dietary patterns, E.g., fruits, veggies, cereals, olive oil Mediterranean diet Thus... single nutrient or food analysis may be confounded by the effect of dietary patterns.

10 Why dietary pattern analysis? there are extreme dietary behaviors e.g., increased intake of specific foods or food groups by a sub-group within the studied sample that may alter the true estimates of the effect size measures in the classical statistical models.

11 Why dietary pattern analysis?... the high level of inter-correlation (stats... colinearity) between food choices makes the estimation of the effect size measures (i.e., odds ratios, hazard ratios) of single foods or nutrients in regression models problematic. The traditional analyses cannot capture these problems and, therefore, diet pattern analysis seems more accurate.

12 Why dietary pattern analysis? the effect of single nutrients or foods may be too small to detect, but the cumulative effects of multiple nutrients or foods included in a dietary pattern may be sufficiently large to be detectable. E.g., in clinical trials interventions altering dietary patterns appeared to be more effective at lowering blood pressure than single nutrient supplementation.

13 Why dietary pattern analysis? analyses based on a large number of nutrients or foods may produce statistically significant associations by chance, because of the inflation of type I error.

14 Types of dietary pattern analysis

15 Dietary pattern analysis Two basic methodologies have been proposed for assessing dietary patterns an a-posterior analysis, using multivariate statistical techniques, e.g., cluster, principal components analysis (PCA) and factor analysis, and an α-priori analysis, based on dietary recommendations or food-consumption models e.g., Mediterranean type of diet, prudent diet, American Heart Association Step I diet, etc

16 a-posterior VS. a-priori analysis a-posterior analysis identifies sets of dietary habits that are strongly correlated together and have not been defined before. Uses all the nutritional information provided for each extracted component. α-priori defined dietary patterns are based on the existed scientific knowledge about the relationships between food and disease (like the food pyramids). Several diet scores (like the MedDietScore), based on the recommended consumption of various foods or nutrients, have been proposed to assess the level of adherence to a specific pattern

17 a-posterior VS. a-priori analysis In other words... α-priori analysis seems to be a method that is based on experts opinion. The previous approach is not necessarily wrong (on the contrary in most of the cases reflects accurate information from series of valid studies), but shares the limitations of static evaluation that cannot incorporate actual particularities of individuals choices in relation to the development of a disease.

18 a-posterior VS. a-priori analysis In a recent work it was tested the accuracy of α-posterior vs. α-priori dietary pattern analysis, in predicting 5-year CVD risk of the ATTICA study participants. α-priori dietary pattern analysis was based on the calculation of the MedDietScore α-posterior dietary pattern analysis was based on PCA Panagiotakos DB et al. J. Food Sci. 2009

19 a-posterior VS. a-priori analysis Receiver Operating Characteristics curves for the multi-adjusted models that evaluated dietary habits and incidence of CVD, using α-priori and α-posterior diet assessment methods. Α-priori and α-posterior dietary assessment showed similar estimating and discriminating ability in predicting 5-year CVD risk, in the ATTICA study participants (n=3042) Panagiotakos DB et al. J. Food Sci. 2009

20 Dietary patterns and CVD risk prediction

21 Dietary patterns and CVD risk prediction The main goal of risk-prediction models is to identify individuals at high risk for CVD and, therefore, identify people who are likely to benefit from aggressive preventive treatment, it is essential to increase models' accuracy. Panagiotakos DB, Pitsavos C & Stefanadis C. Risk Analysis 2009

22 Dietary patterns and CVD risk prediction Inclusion of dietary patterns scores in CVD risk models increases accuracy and reduces bias of the prediction. Panagiotakos DB, Pitsavos C & Stefanadis C. Risk Analysis 2009

23 Stability of dietary patterns

24 Stability of dietary patterns The short-term stability (repeatability) of a- priori and a-posterior derived dietary patterns, as well as its relation to food items or food groups used, was evaluated. Bountziouka V & Panagiotakos DB. Maturitas 2011

25 Stability of dietary patterns 500 participants (37±15 years, 38% male) filled a 76- item and a 36-item FFQ, twice within 15-days interval. The MedDietScore was indirectly calculated through the 76-item FFQ and the 36-item FFQ, and the stability (repeatability) of the a-priori defined patterns was tested. Furthermore, PCA was used to a-posterior assess dietary patterns and was applied to the 76-item FFQ, using as independent variables: (a) the food items and (b) the food groups of the FFQ.

26 Stability of dietary patterns The short-term stability of dietary patterns was revealed for both a-priori and a-posterior methods. For the a-posterior approach the use of food groups, instead of food items, seems to explain more variation in dietary intake.

27 Conclusions Dietary patterns seems to be an appropriate method to assess diet-disease associations than the use of single food or nutrients, and a promising area of research... because, they lead to more robust estimates of effect size measures, they capture the extremes of dietary habits, pre-empts nutritional confounding, and possible effect modification among nutritional variables, and they do not tend to be biased.

28 THANK YOU! Conflict of interest: None to declare