Topic 5 - How do we know what is in our foods?

Question 1

Different classification methods

Answer 1

• Meal occasion – Breakfast food, side dish, dessert
• Timing – Occasional food, party food
• By nutrient – Commonly by energy and/or carbohydrate, fat, protein
content e.g. starchy vegetables – More recently by phytochemical/bioactive
* By food group
– Fruit, vegetables, breads and cereals etc
* By common physical elements
– Stone fruit, fruit juice
* Botanical origin
– Gourd family (watermelon, honey dew)
* Edible component
– Stem, leaf, fruit

Question 2

Sources of our data on foods

Answer 2

1. Food composition databases 
– Nutrient data
2 Food labels/NIP 
– Ingredients + select number of nutrients
3 Australian Guide to Healthy Eating 
– Food groups
 – Systematic literature reviews
4. Scientific studies 
– Consumer beliefs (conceptual similarities)

Question 3

1. Food composition databases (FSANZ) ‐ How we find out what is in a food?

Answer 3

A.NUTTAB 2010
– Reference database 
– 2190 food items, up to 195 nutrients 
– Primarily analysed data 
– Incomplete data set

Question 4

Discuss AUSNUT 2007

Answer 4

B. AUSNUT 2007 – Survey database from ACNPAS – 4225 food items, 37 nutrients – Derived from NUTTAB and FSANZ analytical program – Contains some borrowed and calculated data – Complete data set

Question 5

Creating database values: direct approach

Answer 5

• Laboratory analysis,quality
• Sampling process = important
– from sources that consider known variability of food ie. true representation E.g. supermarket vs. butcher store meats
• Equal amounts of the food(s) collected and combined = homogenous sample
laboratory analysis (in replicate)
• Number of samples dependent on the variability

Question 6

Considerations during sampling

Root vegetable analysis example

Answer 6

Food sample collection procedure: Replicate purchases of approximately 1 kg each were made
in the towns that were major distribution centres in a country. The places of purchase in the town were randomly chosen by
volume of sales from the various types of outlet (supermarket, greengrocer, farmgate stall, etc.)

Question 7

Considerations during sampling;

Meat analysis example

Answer 7

Food sample collection procedure: • Twenty meat cuts purchased, two from each of ten regions;
purchases distributed between butchers and supermarkets in the
ratio 7:3, evenly distributed throughout the regions. • One cut from each region remained to be analysed raw; one from
each region to be analysed grilled.
Cooked:
• Cuts were weighed before and after grilling, then treated in the same way as raw cuts, with lean and fat being analysed separately

Question 8

Variability in food composition data

Answer 8

• Food of biological origin
– seasonal differences, soil composition, climate, cultivar differences or natural variation
* Manufactured food
– storage conditions and duration, manufacturing processes, recipe formulations, processing of the food item and combining of food items
* Food is sampled as a recipe (composite dish)
– Increased variability from amount of ingredients added, cooking times/techniques applied

Question 9

Creating database values: indirect approach

Answer 9

• Decreased quality: lacks control when used alone
• Data taken from published or unpublished literature • Calculations
• Data imputed
– estimated from a similar food item e.g. values for boiled used for steamed

Question 10

Terminology used

Answer 10

• Presumed zero values – dietary fibre in animal foods
* Trace values
– documented as ‘tr’ or ‘T’
– if a nutrient is known to exist but is below the level of quantification
* Missing values
–Incomplete dataset (inappropriate to assign a zero value)

Question 11

2. How is it reflected in our food labels?

Answer 11

• Draws on food composition data
• Average values of nutrients required by standard 1.2.8
• Does not need to be from analysed foods
• Nutrition panel calculator

Question 12

Limitations of label data

Answer 12

• Foods exhibit variations in nutrient composition
– biological materials
– formulations of ingredients
• Limited nutrients included

Question 13

4. Scientific studies

Answer 13

1. Nutrient contribution
2. Cluster analysis
3. Conceptual similarities

Question 14

Utilising food data to construct diets (dietary modelling)

Answer 14

• Can food X be incorporated into a healthy diet?
• Can which food group should food Y fit in within a healthy diet?
• What portion size is most appropriate for food Z?
• How much of the different food groups should we recommend for achieving our aim?

Question 15

Utilising food data to examine diets

Answer 15

• Dietary assessments in clinical studies/individual consultations
– Diet history (usual) 
– Food record (actual) 
– DietAdvice (new innovation)
 – Other forms (FFQ, 24hr recall)
Assessment validation