Major dietary patterns are related to plasma concentrations of markers of inflammation and endothelial dysfunction
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1 Major dietary patterns are related to plasma concentrations of markers of inflammation and endothelial dysfunction Esther Lopez Garcia, Matthias B Schulze, Teresa T Fung, James B Meigs, Nader Rifai, JoAnn E Manson, and Frank B Hu
2 American Journal of Clinical Nutrition 80; Published in 2004 Conducted in Boston, USA Study protocol approved by Harvard School of Public Health Human Subjects Committee Review Board
3 Background Atherosclerosis = inflammatory disease dysfunction of the vascular endothelium enhanced endothelial activation reflected by plasma concentra ons of soluble endothelial adhesion molecules (ICAMs, VCAM 1, E selectin) in CVD Ross, R. (1999); Libby, P. (2000)
4 Background Major dietary patterns relation to plasma markers of CVD risk and metabolic syndrome Fung et al. (2001)
5 Aim To evaluate whether dietary patterns are associated with markers of inflammation and endothelial dysfunction, including C reactive protein (CRP), interleukin 6 (IL 6), E selectin, soluble intercellular adhesion molecule 1 (sicam 1), and soluble vascular cell adhesion molecule 1 (svcam 1).
6 Summary Nurses Health Study established in 1976, USA registered female nurses The present study included 732 healthy women Did NOT have CVD, cancer, or diabetes at the time of blood drawing Averageage56 years
7 Methods Andreas Schuster, Anja Horina; Biostatistik Dec Blood collection and assessment of biomarkers: Collected between 1989 and 1990 When possible a phlebotomy kit was sent with instructions 97% arrived within 26h of phlebotomy Centrifuged and frozen at 70 C until analysis Quality control samples CRP, IL 6, E selectin, sicam 1, svcam 1
8 Methods Assessment of dietary intake: Semi quantitative food frequency questionnaires (FFQ): Previously validated FFQ used Mailed to subjects 116 food items with specified serving sizes 9 frequency categories from almost never to 6 times/day Converted to a value in number of servings/ day Aggregated single food items into 37 predefined food groups To minimize within-person variation in consumption of individual foods Assessment of other variables: Smoking, Body weight, BMI, Physical activity (MET h/wk)
9 Statistical Analysis PRINCIPLE COMPONENTS ANALYSIS To derive dietary patterns based on food groups Each subject received a factor score for each dietary pattern MULTIPLE LINEAR REGRESSION find relationships between plasma concentration of endothelial markers and dietary patterns Log transformed data to achieve normal distribution Adjustment for age, physical activity, smoking status, alcohol consumption, and separately for BMI
10 Results Andreas Schuster, Anja Horina; Biostatistik Dec major dietary patterns Prudent pattern Higher intakes of vegetables, fruit, legumes, whole grain, fish and poultry Western pattern Higher intakes of red meat, processed meat, refined grains, sweets, desserts, French fires and high fat dietary products
11 Results For analysis and comparison each pattern was further seperated into Quintiles: Prudent pattern Western pattern Q 1 Q 2 Q 3 Q 4 Q 5 Q 1 Q 2 Q 3 Q 4 Q 5
12 Results Key Message: Dietary patterns are associated with biomarkers of inflammation and endothelial function The prudent pattern improves endothelial function and decreases CRP Western pattern shows positive correlation with all analysed markers of inflammation and endothelial function
13 Was the study design appropriate? Andreas Schuster, Anja Horina; Biostatistik Dec ASSOCIATION between laboratory markers and dietary habits??? Cross Sectional study PRIMARY RESEARCH
14 Statistical analysis appropriate? Andreas Schuster, Anja Horina; Biostatistik Dec PRINCIPAL COMPONENTS ANALYSIS: Transforming high dimensional data into a simpler, lower dimensional form, without loosing too much information using the dependencies between the variables dimensionality reduction identifying patterns in data MULTIPLE LINEAR REGRESSION: Adjusted for confounders in the analysis Still significant correlation The reported P values for regression coefficients were incorrectly cited»not reproducible
15 Validation of Results? Group size?? (Western pattern/ Prudent Pattern) Blood samples Analyses corrected for fasting status! Time of day when blood was drawn?? Haemolysis destruction of blood cells Physical activity before blood drawing? influence on expression of adhesion molecules?? Pregnancy? Hormonal changes? Medication? (anti inflammatory drugs, statins) Cross sectional study/dietary assessment Some dietary information was collected 4 years before drawing blood Average of both FFQs when administered twice (651 subjects) change of dietary habits Response rate from originally screened participants not known
16 Validation of Results? Error in the measurement of food consumption Self administered questionnaires Sent per mail response rate? Sometimes filled in twice combination with 24 h recall!!?? Factor analysis approach for dietary patterns very complex method, arbitrary decisions necessary Bias Originally control group for other diabetes study inclusion criteria?? Probably different dietary behavior because they knew they are monitored within a study
17 Conclusion Are the results valid?
18 Conclusion Are the results valid?
19 Conclusion No standarised methods Results only partly transferable onto average an population special population (highly educated, age, etc ) Looking at it from a clinical aspect, there might be a role of dietary habits in the modulation of inflammation and endothelial function
20 Improvement Suggestions: Combination of questionnaires and 24 h recall to assess dietary habits Shorter periods between administration of questionnaires and blood sampling Methods and study protocol more standardised!! Standardised blood sampling
21
22 Andreas Schuster, Anja Horina; Biostatistik Dec. 2013
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