Introduction to Human Nutrition

Food Composition 285

Data in food composition tables may be original
analytical values, imputed, calculated, or borrowed.
Original analytical values are those taken from pub-
lished literature or unpublished laboratory reports.
Unpublished reports may include original calculated
values, such as protein values derived by multiplying
the nitrogen content by the required factor, energy
values using energy conversion factors for some con-
stituents of food, and “logical” values, such as the
content of cholesterol in vegetable products, which
can be assumed to be zero. Imputed values are esti-
mates derived from analytical values for a similar
food or another form of the same food. This category
includes those data derived by difference, such as
moisture and, in some cases, carbohydrate and values
for chloride calculated from the sodium content. Cal-
culated values are those derived from recipes by cal-
culation from the nutrient content of the ingredients
corrected by the application of preparation factors.
Such factors take into account losses or gain in weight
of the food or of specifi c nutrients during preparation
of the food. Borrowed values are those derived from
other tables or databases without referring to the
original source. When a value for the content of a
specifi c nutrient in a food is not included, there is a
“–” or “0” value and, when a table has no values for a
particular nutrient, the value is regarded as being “not
included.” In some tables, e.g., the National Nutrient
Database for Standard Reference, SR, of the USDA,
“0” value is a true zero, meaning the particular nutri-
ent was not detected by the analytical method used;
“–” indicates a missing value.
The proportion of the various types of data differs
between tables and for different nutrients (Table
11.6). Details on food tables can be obtained from the
Food and Agriculture Organization (http://www.fao.

org/infoods). In other tables, such as those in the

Netherlands, where sources of the data are given in

the references, information on how the data have

been obtained can also be found. However, this is not

the case for all tables of food composition.

11.5 Overcoming the inadequacies of

food composition tables

Nutrient losses and gains during food

processing and preparation

In the absence of analytical data for all forms of foods

nutrient values can be estimated by calculation using

standard algorithms that have been experimentally

derived. Since the content of nutrients per unit mass

of food changes when foods are prepared, such losses

and gains can be classifi ed in two ways. The fi rst can

be described by a food yield factor, when the weight

of the primary ingredients at the precooking stage is

compared with the weight of the prepared food at the

cooking stage and also with the fi nal weight of

the food as consumed at the post-cooking stage. The

weight of the food can be increased due to the hydra-

tion of the dry form of a food (e.g., rice, macaroni)

with cooking liquid, (e.g., water or broth) or increased

due to the absorption of fat during frying of the food

(e.g., potato). Alternatively, the weight of the food can

decrease due to dehydration during cooking as a

result of evaporative and drip losses.

The second, the nutrient retention factor, is related

to changes in the amount of specifi c nutrients when

foods are prepared. Changes in the nutrient levels can

occur due to partial destruction of the nutrient as a

result of the application of heat, alkalization, etc. Also,

for some dietary components (e.g. β-carotene) the

amount of available component may increase due to

the breakdown of cell walls in the plant-based sample.

Although original analytical data would be the most

desirable type of data for foods at all stages of prepa-

ration, they are seldom available. Efforts are in prog-

ress in several regions to revise the nutrient losses and

gain factors, including nutrient retention and yield

factors, in order to compare and harmonize them and

thereby improve the quality of food composition data

calculated.

As food composition data are frequently lacking

for cooked foods, estimates based on the use of

these factors for calculating the nutrient content of

Table 11.6 Proportion of various types of data in food composition
tables

Types of data

McCance and

Widdowson tables, UK

(developed country)

South African food

composition table

(developing country)

Analyses 70% 41% in 1999 (improved
from 18% in 1991)
10% 49%
Calculated 15% 10%
Estimated 5% –