Katherine L. Tucker, Ph.D Northeastern University, Boston, MA

Transcription

1 * Katherine L. Tucker, Ph.D Northeastern University, Boston, MA

2 * AFFILIATION/FINANCIAL INTERESTS Grants/Research Support: CORPORATE ORGANIZATION Kraft Foods Scientific Advisory Board/Consultant: Speakers Bureau: ILSI North America none Stock Shareholder: none Other Financial or Material Support/Honorarium: ILSI North America

3 *Usual intake *Valid and reliable nutrient intake *Diverse populations *Minimize burden *Minimize cost *

4 * *Essential, changing and complex *Need accurate assessment to identify true associations with health outcomes *Current methods subject to error and bias *Challenge especially for certain populations Improvements in dietary assessment methods are urgently needed in order to understand the effects of genetic factors on disease risk Penn et al. Genes Nutr 2010;5:205-13; Tucker KL. Nutr Metab Cardiovasc Dis 2007;17:74-81

5 *Diet records *Require literacy, cooperation, poor return *24 hour recalls *Valid but short term measure *Multiple measures have high burden *Food frequency *Long term measure of usual intake *Use of different forms may bias group comparisons *

6 *Effect of Random Within-Person Variation *Misclassification of individual s usual intake *Bias toward increased estimates of prevalence of high or low intake *Attenuation of correlations, regression coefficients and risk estimates

7 * *If random variation is assumed, can use a formula with at least 2 recalls or records to adjust for day to day variability with straightforward correlation or regression measures. *Not widely used outside of validation studies

8 *Adds a propensity questionnaire to two 24 hour recalls to adjust for infrequently consumed foods. *Statistical modeling is used to adjust for day to day variability with selected propensity intakes as covariates *Results and approach depend on specific foods or nutrients and the population being studied Subar, A. F. et al, J. Am. Diet. Assoc. 2006;106:

9 * *The day to day variation can no longer be assumed to be random *The propensity questionnaire is not adequately specific for diverse groups *This is a major problem for understanding gene diet interactions where detailed nutrient intake is needed

10 *Based on variance measurement and assumptions from the average population *Do not consider major dietary pattern subsets by *Ethnicity *Vegetarianism * *Can lead to systematic bias by subgroup and with changes over time *

11 *Designed to rank usual intake *Considered semi-quantitative *Recently challenged due to a few large studies showing better associations between multiple diet records and health outcomes than from FFQs *Fat and breast cancer (NCI, EPIC) *

12 * *Existing FFQs are designed to capture diet for the majority *Compromises by grouping foods and assuming relative exposures *Eg other fruits (other than apples and pears, banana, citrus, melon or berries) * Weighted average of grapes, plums, peaches, pineapple,mango, kiwi *This removes important variation! * Amplified with diverse cultural diets leading to confounding! *Assume standard recipes *Eg soup * Weighted averaged of canned chicken soup, beef noodle soup. vegetable soup * Ethnic differences are tremendous, can lead to bias! *Assume standard portions *Again, can remove variation and lead to bias!

13 * Energy Fat Carbohydrate Vit C Vit E Urban non-hispanic White Oakland, CA Urban African-American Oakland, CA Rural non-hispanic White Colorado Rural Hispanic Colorado Mayer-Davis et al. Ann Epidemiol 1999;9:

14 * Men Energy Protein Fat Fiber Vit C Calcium African Americans Japanese Americans Latinos Whites Stram et. al. Am J Epidemiol :358-70

15 * Women Energy Protein Tot Fat Fiber Vit C Calcium African Americans Japanese Americans Latinos Whites Stram et. al. Am J Epidemiol :358-70

16 Block Harvard * Energy Protein Vit A Vit C Iron Calcium African American Hispanic Non-Hispanic white African American Hispanic Non-Hispanic white WIC Dietary Assessment Validation Study Final Report -- September 22, 1994

17 Use of FFQs for multi-ethnic populations are currently inadequate and may lead to bias, particularly in comparing across groups and in combining groups in relation to outcomes.

18 *Original *Beans *Kidney 0.28 *Pinto 0.26 *Baked beans 0.26 *Lima 0.15 *Lentils 0.05 *Puerto Ricans *Beans *Kidney 0.60 *Pinto 0.05 *Pink 0.28 *White 0.07 *

19 * Mango Fruit nectar Avocado Cassava Green plantain Ripe plantain Meat pie, fritter Homemade soup Custard Rice with chicken Rice with pigeon peas Rice with beans Rice with meat

20 *

21 * Mean ± SE 24-hr recall Block FFQ Revised FFQ Revised FFQ open portions Energy (kcal) 1464 ± ± 45**** Protein (g) 60.0 ± ± 2.4**** 1202 ± 44**** 1409 ± ± 2.5*** 62.0 ± 3.4* Fat (g) 52.5 ± ± ± 2.1**** 51.4 ± 2.9 Carbohydrate (g) 191 ± ± 5.6**** 151 ± 5.6**** 176 ± 8.2** Vitamin A (µg RAE) 732 ± ± 44**** 454 ± 75**** 487 ± 76* Calcium * p < 0.05; (mg) ** p < 0.01; *** p < ; ± **** 31 p < , 454 by ± paired 32**** f-test statistics 431 ± for 26**** Ho: mean from food 549 ± 31** frequency = mean from 24-hour recall. For differences with non-normal distributions, significance levels were determined with the non-parametric sign test. Tucker et al. AM J Epidemiol (5)

22 * Tucker et al. AM J Epidemiol (5)

23 *Widely used FFQs capture foods commonly consumed in the United States *Extensive misclassification possible for specific minorities or subgroups *Foods of Our Delta Study (FOODS 2000) *Dietary survey of residents of the Delta region *Commissioned by the USDA Delta Nutrition Intervention Research Initiative (Delta NIRI) * Source: Willett, 1984; Champagne, 2004; Tucker, 2005

24 24 Tucker, KL et.al. Public Health Nutr :87-96

25 * *Inclusion of four portion sizes to capture variation reported *Standard reference amounts used instead of small, medium, large etc. *Median portion (from FOODS 2000) considered the reference 1 st choice: half of reference 2 nd choice: reference 3 rd choice: 1.5 X reference 4 th choice: 2 X reference

26 *Started with the USDA Delta NIRI FFQ *Collected more local information *Limited to 20 minutes *Collapsed items to be inclusive *

27 * Nutrient Short FFQ Men Long FFQ Short FFQ Women Long FFQ Vitamin B12 Energy adjusted Energy adjusted & de-attenuated Calcium Iron Energy adjusted Energy adjusted & de-attenuated Energy adjusted Energy adjusted & de-attenuated Potassium Energy adjusted Energy adjusted & de-attenuated Source: Carithers, T JADA 2009

28 * *What are the effects on the use of data with multiple ethnic groups with large variation in validity across groups? *How can we ensure that diet disease relationships are not biased due to systematic differences in intake measurement?

29 *Ethnic variation in diet *Food choice *Recipe *Portion size lead to bias in assessment + Ethnic and population variation in prevalence of polymorphisms leads to inherent confounding that cannot be easily corrected *

30 SBP (mmhg) SBP (mmhg) Waist circumference (cm) P= APOA1-75 and total fat intake P-value for interaction= <31% 31% Total fat intake, % from energy P= CC CT+TT P=0.235 APOA4 N147S and total fat intake P-value for interaction= <31% 31% Total fat intake, % from energy P=0.010 AA AG+GG Waist Circumference and blood pressure by SNP and total fat intake category (below or above population median) in Puerto Rican adults P= APOA5 S19W and total fat intake P-value for interaction= <31% 31% Total fat intake, % from energy P= CC CG+GG *

31 *Unique genetic profile of Puerto Ricans Protective Minor Alleles Risk Minor Alleles Unique genetic profile of Puerto Ricans may increase predisposition to chronic diseases (less protection, more risk). Mattei et al. BMC Genetics

32 * *Recalls allow open ended capture of diverse diets *But NOT usual intake *Not clear that adjustment for day to day variation will be sufficient for complex interaction studies *Collecting multiple days is very expensive with high respondent burden *Currently available FFQ may lead to bias because they do not discriminate intakes well and do not equally represent diets of different groups

33 * The WG considered pros & cons of various protocols: The following protocols were selected to be included in PhenX Survey: *24 hour recall (Multiple Pass) for * Total Dietary Intake * Supplement Intake *Bioassay (NHANES laboratory protocol) for * Selenium * Vitamin D *Single and Multi-Factor screeners, including: * Fruits and Vegetables * Dairy * Added Sugars * Calcium * Fiber * Supplements * Caffeine Erin M. Ramos, PhD MPH, Office of Population Genomics, NHGRI

34 *Very difficult to get valid estimates for diverse populations *Requires much more detail than most FFQ currently include *Online, can skip to tailor questions to individual level much more quickly *

35 Can include many more foods, recipes, portions to assess diet as accurately as a 24 hour recall, using similar probes to obtain individual foods/recipes How often do you eat bread? What types of bread do you eat at least once per month? (select from list) How often do you eat each type?... How often do you eat Mexican food If yes to tacos, eg, Home made or restaurant/fast food Type (bean, beef, specific recipe) If never, skip; if frequently, can get detail continuing down to extent needed Use photographs to capture wider range of portion size *

36 *Improvements in dietary assessment methods are needed *Minimize measurement error *Quality and quantity of intake *Recalls allow open ended capture of diverse diets *But not usual intake *Not clear that adjustment for day to day variation will be sufficient for genetic interaction studies as intakes are usually dichotomized *Currently available FFQ may lead to bias as they do not equally represent diets of different groups *

37 *Need to convince funders, reviewers, scientists to value the importance of comprehensive dietary assessment that includes diverse populations *Need to convince the community that it can be done well *Need to use new technology to make instruments more comprehensive, faster, more user friendly and cost-effective *