Introduction to Human Nutrition

294 Introduction to Human Nutrition

employ the term “reference” and hence they can be
classifi ed as reference nutritional data. Such data were
historically developed to ensure the adequacy of the
human diet from the point of view of micronutrients.
However, as our knowledge of diet and chronic disease
has evolved, a second set of reference nutrition values
had to be developed, this time to minimize the risk of
chronic disease. Table 12.1 shows a non-exhaustive
list of these nutrients and the risk factor or chronic
disease they are associated with.
In addition to these data, recommendations are
made for ideal body weight and there are specifi c sets
of dietary guidelines for such life stages as lactation,
pregnancy, aging, etc. However, the regulatory envi-
ronment in nutrition is dominated by the above
nutrients and also the micronutrients.
The whole purpose of devising these two sets of
metrics – nutrient intakes and nutrient reference
values – is to fi rst measure where we are in relation to
our nutritional well-being and second to set targets
to move the population toward a healthier diet. There
is however, a very slight antagonism between the
establishment of an ideal pattern of nutrient intake
and developing public health nutrition programs to
achieve that goal. The reason is that the former does
so in isolation from the real world of everyday eating.
Its focus is on experimental studies that, for example,
help delineate the optimal balance of dietary fatty
acids to minimize plasma cholesterol. That optimal
may be very signifi cantly different from prevailing
dietary habits and to attempt to bridge the gap too
fast might produce a public health nutrition program
that is unrealistic. Thus nutritionists can look at pre-
vailing intakes against ideal intakes and then set out

interim attainable targets in realistic public health

nutrition programs that can be implemented over a

defi ned and reasonable period of time. In summary,

it is not possible to develop a meaningful nutrition

regulatory framework without access to both nutrient

intake data and dietary reference data.

12.3 Exploration of dietary patterns

With a given set of population nutrient intake data
and a given set of nutritional reference values, it is
possible to divide the population into those closest to
some nutritional ideal and those furthest from such
an achievement. These two contrasting groups can
now be laid against one another and a wide range of
data, listed in Box 12.1, can be examined.
Based on these comparisons and using appropriate
statistical techniques, it is possible to begin to discern
the reasons why one group are near achieving some
nutritional ideal and why another are set far off the
mark. These reasons now feed into policy advice and
begin to form the nucleus of a nutrition regulatory
structure that may help the population improve their
diet. Given that the focus of this text is nutrition, it
would be worthwhile to single out food patterns for
a more critical analysis. The following is a hypotheti-
cal fi nding in relation to three foods that appear to be
important in determining the nutritional adequacy of
“achievers” and “non-achievers” of some nutrient
goal.
Look at Table 12.2. At fi rst glance C seems unim-
portant and A and B seem to be important and going
in opposite directions. These are very typical data that
emerge from such analyses and they hide two very
important statistics that should always be sought in
studies of this nature. The fi rst missing statistic is
Table 12.1 Nutrients and associated risks “% consumers” and the second is the “intake among

Nutrient Effects

Saturated fatty acids Blood cholesterol
Monounsaturated fatty acids Blood cholesterol
n-6 polyunsaturated fatty acids Blood cholesterol
Trans unsaturated fats Blood cholesterol
n-3 polyunsaturated fatty acids Blood cholesterol
Total fat Obesity
Sodium Blood pressure
Sugar Dental caries
Fiber Digestive disorders
Folic acid Neural tube defects
Fruits and vegetables Certain cancers

Box 12.1

Nutrients

Foods

Eating habits

Anthropometry

Socioeconomic data

Physical activity

Education

Others