Analysis of Dietary Data Collected from Childcare Settings Beth Dixon, PhD, MPH Associate Professor Department of Nutrition, Food Studies and Public Health New York University
Big Picture Questions What do you want to measure? E.g., foods served vs consumed How much detail do you want to measure? generic types of foods vs specific types and amounts of foods More details (espamounts) allow comparison to quantitative dietary recommendations for assessing overall quality of foods served or consumed
Sources of Dietary Data What is purchased Receipts What is served Menus What is served or consumed Staff reports Direct observation
Types Amounts Data Collection Generic Specific Methods "Milk" "1% Milk" 1/2 cup Receipts X X Menus X Possibly Possibly Staff Reports X Possibly Likely Direct Observations X Likely X
Cross-center Variability in Data from Menus, Staff Reports, Direct Obs For example, Information on Information on 1st center menu 2 nd center menu Generic Milk 1/2 cup of 1% milk Peaches 4 oz of canned peaches in litesyrup
Data Collection Methods for Direct Obs Paper / pencil using form(s) Data entered later into dietary assessment software system Electronic (handheld, laptop) Data (from list) entered later or data entered real-time into dietary assessment software system Difficult to collect data electronically from >1 child
Example of Paper / Pencil: Meal Observation Form ID#/Location: / Date/Observer Initials: / Meal (circle): Brkfst Snack Lunch Served: a.m. / p.m. Child #1 Foods & Beverages (Note details, e.g. brand, packaged, fresh, canned, On Menu? Amount Served Amount Eaten frozen, low fat)
Issues with Use of Form Types of Foods How much detail? How consistent? (generic) Milk vs 1 % milk Amounts of Foods How accurate? Visual guess-timates from observations or staff report
After form completed Enter data into dietary assessment software program Right away Delayed time frame Longer time elapsed from observations to data entry, more difficult to confirm types and amounts of foods with accuracy
Dietary Assessment Software Public NCI Automated Self-administered 24-h Dietary Recall (ASA24) USDA Automated Multiple Pass Method (AMPM) Private University of Minnesota NDS-R ESHA Food Processor SQL Others
NCI ASA24 Respondent Web site (Version 1) released in September 2011. Version 1 incorporates: updates to the underlying probes and pathways using the current version of USDA s Automated Multiple-Pass Method (AMPM); update from version 1.0 to version 4.1 of USDA s Food and Nutrient Database for Dietary Surveys (FNDDS); update of MyPyramidEquivalents using version 2.0 of the USDA's MyPyramidEquivalents Database (MPED) and the USDA's CNPP's MPED Addendum;
MPED 2.0 Grains Group Vegetables Group Fruits group Milk Group 1. Total grain 2. Whole grain 3. Non-whole / Refined grain 4. Total vegetables 5. Dark-green vegetables 6. Orange vegetables 7. White potatoes 8. Other starchy vegetables 9. Tomatoes 10. Other vegetables 11. Total fruits 12. Citrus fruits, melons, and berries 13. Other fruits 14. Total Milk (milk, yogurt and cheese) 15. Milk 16. Yogurt 17. Cheese Meat and Beans Group 18. Meat, poultry, and fish 19. Meat (beef, pork, veal, lamb, and game) 20. Organ meats (meat and poultry) 21. Frankfurters, sausage, and luncheon meats(made from meat or poultry) 22. Poultry (chicken, turkey, and other) 23. Fish and shellfish high in n-3 fatty acids 24. Fish and shellfish low in n-3 fatty acids 25. Eggs 26. Cooked dry beans and peas 27. Soybean products (tofu and meat analogs) 28. Nuts and seeds Oils Extras (SoFAS) 29. Discretionary oil 30. Discretionary solid fat 31. Added sugars 32. Alcoholic beverages
Comparisons to Recommendations Energy and nutrient intakes Dietary Reference Intakes (RDA, AI) Servings of food groups USDA Food Intake Plan in the Dietary Guidelines for Americans 2010 CACFP Meal Patterns
Dietary Component RDA or AI a Age 1-3 yrs Age 4-8 yrs Macronutrients Energy (kcal) 1200 1400 Carbohydrate (g) 130 130 Protein (g) 13 19 Fat (g) 30-45 25-35 Vitamins Thiamin (mg) 0.5 0.6 Riboflavin (mg) 0.5 0.6 Niacin (mg) 6 8 Pyridoxine (mg) 0.5 0.6 Folate (μg) 150 200 Vitamin B-12 (mcg) 0.9 1.2 Vitamin A (RE) 300 400 Vitamin C (mg) 15 25 Vitamin E (mg α) 6 7 Vitamin D (mcg) 15 15 Vitamin K (mcg) 30 55 Minerals Calcium (mg) 700 1000 Iron (mg) 7 10 Magnesium (mg) 80 130 Zinc (mg) 3 5
Food groups and subgroups USDA Food Intake Plans in Dietary Guidelines for Americans 2010 1,200 kcal diet 1,400 kcal diet Grains, total 4.00oz 5.00oz All or some whole grain 2.00oz 2.50oz Vegetables, total 1.50c 1.50c Vegetables, dark green 0.14c 0.14c Vegetables, orange 0.43c 0.43c Vegetables, starchy vegetables 0.50c 0.50c Vegetables, other 0.37c 0.37c Beans and peas (legumes) 0.07c 0.07c Fruits and Fruit Juice, total 1.00c 1.50c Meats/alternatives, total 3.00oz 4.00oz Meat, high-fat/fried Meat, low-fat n/a n/a Meat alternative n/a n/a Dairy 2.50c 2.50c Milk, whole n/a n/a Milk, reduced-fat n/a n/a Milk, 1% or nonfat n/a n/a Cheese n/a n/a Yogurt n/a n/a Discretionary fat, oil (kcal) n/a n/a Maximum SoFAS limit, calories (% of calories) 121 (10%) 121 (9%) Solid fats (kcal) n/a n/a Added sugars (kcal) n/a n/a
CACFP Child Meal Pattern: Breakfast Select All Three Components for a Reimbursable Meal Food Components Ages 1-2 Ages 3-5 Ages 6-12 1 1 milk fluid milk 1/2 cup 3/4 cup 1 cup 1 fruit/vegetable juice, 2 fruit and/or vegetable 1/4 cup 1/2 cup 1/2 cup 1 grains/bread 3 breador 1/2 slice 1/2 slice 1 slice cornbread or biscuit or roll or muffin or 1/2 serving 1/2 serving 1 serving cold dry cereal or hot cooked cereal or 1/4 cup 1/4 cup 1/3 cup 1/4 cup 3/4 cup 1/2 cup pasta or noodles or grains 1/4 cup 1/4 cup 1/2 cup 1 Children age 12 and older may be served larger portions based on their greater food needs. They may not be served less than the minimum quantities listed in this column. 2 Fruit or vegetable juice must be full-strength. 3 Breads and grains must be made from whole-grain or enriched meal or flour. Cereal must be whole-grain or enriched or fortified.
To improve quality of data collection: Train research staff to Observe consistently Record consistently (e.g., cookie vschocolate chip cookie vs Chips Ahoy chocolate chip cookie) Estimate common portion sizes (e.g., ½ cup, 4 oz) Enter data into software program consistently
To improve quality of data collection: To improve identification of foods Confirm with teachers or food service staff about types (e.g., 1% milk) Check kitchen To improve estimation of amounts Provide visual aids of portion sizes Force proportions of portion sizes (e.g., ¼ cup, ½ cup, ¾ cup) on form
Final Comments Right now, direct observation is best method to collect details about types and amounts of foods (menus and staff report can help confirm) Accurate collection of both types and amounts of foods Accurate collection of both types and amounts of foods is needed to compare to national recommendations to assess diet quality as well as adherence to policy, standards, or regulations
Which Method(s)? Importance in study less less less less less Receipts Number of dietary factors Distribution of dietary factors Time Money Menus, Staff Reports more more more more more Direct Observation
Final Comments Collection of high quality detailed dietary information (served or consumed) takes TIME and MONEY Either study design needs to be small(er) in scope with detailed dietary data collection from all centers detailed dietary data collection from all centers OR Study design is large(r) in scope with sub-sample that includes detailed dietary data collection
Thank you