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B1.4 MJ from protein in men, did not differ significantly
from the other meals, which had similar energy density and
‘dietary fibre’ content (although they differed in their
sensory attributes, such as taste and after taste). There was
also no difference in intake among the 10 women who
consumed B0.7 MJ of protein from the high-protein meal.
This study did not covertly manipulate the meals to conceal
taste. Nevertheless, all the above observations taken together
raise questions about the predictive value of macronutrient-specific
models of feeding behaviour, at least under
laboratory conditions, which may not necessarily apply to
free-living conditions, for reasons that will emerge later.
Inevitably, attention is focused on the weight and energy
density of foods, including ready-to-eat foods, which have
recently flooded the market in developed countries.
Before considering these issues further, it is worth briefly
reflecting on the likely limitations of physiological processes
controlling feeding behaviour that place disproportionate
importance on a single nutrient (for example, carbohydrate).
Such a system would regulate energy balance poorly because
it would be unable to adapt adequately to situations
associated with changes in the proportions of different
macronutrients in the food supply. Therefore, it is not
surprising that specific macronutrient models of feeding
behaviour were not found to be robust in some circumstances,
particularly those involving covert manipulation of
diets with the same energy density but different macronutrient
composition (see above). In addition, pharmacological
inhibition of both fat and glucose oxidation in animals were
found to elicit a massive increase in food intake, compared to
inhibition of either fat or carbohydrate oxidative pathways
(Friedman and Tordoff, 1986). This suggests that the
regulatory system is responsive to oxidation of both fat
and carbohydrate, and that oxidation of each substrate
compensates for the other, when the availability of one of
them is reduced. Therefore, eating behaviour does not
unconditionally depend on the oxidation of one nutrient,
and indeed it would be surprising if it did. Furthermore, the
satiating effect of the Eskimo diet (fat and protein) (Mowat,
1981) would argue against the operation of a simple
carbohydrate oxidation or storage model of feeding behaviour
to the exclusion of other macronutrients.
Energy density, weight of food and carbohydrates
Several reports suggest that under ad libitum feeding conditions
(mainly under laboratory conditions), people tend to
consume a fixed weight or volume of food (Duncan et al.,
1983; Lissner et al., 1987; Tremblay et al., 1991; Tremblay,
1992; Poppitt, 1995; Rolls and Bell, 1999; Bell and Rolls,
2001). This implies that when foods or diets differ in energy
density, energy intake will be affected. Indeed, it has been
suggested that this is a major mechanism for determining
energy intake at different stages of the life cycle (for example,
compared to young adults, older adults reduce energy intake
by largely decreasing the energy density of the food eaten). If
Physiological aspects of energy metabolism
M Elia and JH Cummings
satiety was mainly determined by the weight of food eaten,
then those who consume high-energy density foods would
be expected to feel satiated only after increased energy
intake, whereas those consuming low-energy density foods
would feel satiated despite lower energy intake. This
argument has been promoted by several workers (Poppitt,
1995; Poppitt and Prentice, 1996; Prentice and Poppitt, 1996;
Rolls and Bell, 1999). It is argued that in real-life energy
dense foods tend to be more palatable and less satiating than
foods with low-energy density. Typically, palatable snacks are
energy dense, and those rich in both fat and available
carbohydrates, which are rapidly digested and absorbed, are
said to be particularly palatable (Drewnowski, 1998). Interestingly,
available carbohydrate and fat also provide more
NME per unit ME than does the diet as a whole or either
protein or NSP or other carbohydrates fermented in the large
bowel. Therefore, when using the ME system, high-fat, highavailable
carbohydrate foods (or diets) are more fattening
than isoenergetic high-protein, high-fibre foods. In addition,
foods of low-energy density (often rich in NSP and water)
were less palatable in these studies.
An examination of 1032 foods revealed that the strongest
predictors of energy density are water, which is negatively
related to energy density, and fat (g per 100 g food), which is
positively related to energy density (Stubbs et al., 2000). The
carbohydrate and protein content of foods (g per 100 g food)
are both positively related to energy density, but the
association is much weaker than those obtained with fat or
water (Figure 4). This weak relationship with carbohydrate is
understandable because it is possible for foods containing a
large proportion of energy from carbohydrate to have either
a low-energy density (for example, vegetables) or highenergy
density (some sweet snacks). Diet surveys do not
generally report the energy density of the food eaten, and
this precludes extensive analyses and interpretation of data
Energy density (kJ/100g)
4000
3500
3000
2500
2000
1500
1000
500
0
0 25 50
Weight (g/100g)
75 100
Fat (r 2 =75)
Protein (r 2 =13.9)
Carbohydrate (r 2 =1.9)
Water (r 2 =66.7)
Figure 4 Relationship between energy density (outcome variable)
and % weight of dietary macronutrients and water of 1032 readyto-eat
foods (Stubbs et al., 2000). The prediction equations
are as follows: Energy density (ED) ¼ 462.6 þ (35.5 fat); ED ¼
781.4 þ (12.2 protein); ED ¼ 654.5 þ (12.5 carbohydrate); and
ED ¼ 2034–(21.2 water). The values in parentheses, derived from
regression are r 2 100.
S55
European Journal of Clinical Nutrition