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Pregnancy

Energy cost of pregnancy: increased tissue mass

Weight gain during pregnancy comprises the products of conception (fetus, placenta, amniotic fluid), and hypertrophy of several maternal tissues (uterus, breasts, blood, fat stores, extracellular extravascular fluid). An extensive review of the associated energy costs has been presented by Hytten (1991) and is summarised in Table 3. Protein is laid down predominantly in the fetus (44%), but also in the uterus (17%), blood (14%), placenta (10%) and breasts (8%). In contrast, fat deposition takes place predominantly in maternal adipose tissue (85%), with the fetus the only other major site of importance (14%). The gain in fat stores is by far the largest component of the energy cost of tissue deposition (72%). The fetus accounts for 19% and the placenta, uterus, blood volume and breasts 2%, 3%, 3% and 2%, respectively.

Hytten's review did not include a substantial number of relatively new longitudinal studies of changes in fat mass during pregnancy in which estimates of total fat gain, or the gain in maternal fat stores, represented 83% and 72% respectively of the energy costs associated with weight gain. Those new longitudinal studies which include both baseline values before pregnancy or in the first 12 weeks of gestation and values near term or during the first two months post partum are reviewed below. The 'whole-body' measurements of total body water (TBW, from isotope dilution) or estimates of body density (BD, from underwater weighing), were considered to give the best estimates of fat mass in late pregnancy. For estimates of fat gain derived from the sum of four skinfold thicknesses, post-partum rather than late-pregnancy values were used, because changes other than fat accumulation might influence skinfold thicknesses in late pregnancy.

Fat gain during pregnancy in developed countries. The results of 15 longitudinal studies are summarised in Table 4. The average gain in fat mass by late pregnancy estimated from TBW was 3.3 kg (Forsum et al, 1988; Goldberg et al, 1993; Hytten et al, 1966; Pipe et al, 1979; Taggart et al, 1967). In the two studies which measured BD the average increase in fat mass was 2.44 kg (Spaaij, 1993; van Raaij et al, 1988). Fat gain estimated from skinfolds was substantially lower and averaged only 1.2 kg. Part of this difference is attributable to the timing of the second measurement: TBW and BD measurements were made in late pregnancy, whereas the skinfold measurements were made post partum after the fat that was not deposited in maternal stores had been lost. The fat gains estimated from TBW and BD measurements need to be reduced by about 0.4 kg (representing the fat in the fetus), in order to estimate fat deposited in maternal stores (Table 3). The fat deposition estimated from TBW measurements is then 2.9 kg, and from BD 2.0 kg. The average gain in fat stores estimated from skinfolds (1.2 kg) is thus still substantially lower. Several authors have shown that some skinfolds increase more than others during pregnancy, indicating that fat deposition is not equally distributed over all adipose tissue sites. This applies particularly to the gluteal and upper thigh regions which are not included in the traditional four site measurements. As a consequence, the validity of fat gain estimated with the skinfold technique is questionable.

Table 3 Site-specific protein and fat deposition during pregnancy, and energy costs involved^a in a reference woman with a pregnancy weight gain of 12.4 kg delivering a baby of 3.3 kg^b

^a The energy needed for synthesis and deposition was assumed to be 29 kJ/g for protein and 46 kJ/g for fat (Durnin 1987). We later reduce the assumption for fat to 39 kJ/g.
^b Values obtained from Hytten (1991).
^c Blood-free uterus.
^d Extracellular extravascular water, assuming that there is no generalised edema.
^e The only adaptation we made to Hytten's value, was in the amount of fat laid down in maternal fat stores. The gain in adipose tissue is the difference between body weight gain and the sum of weight gains of fetus, placenta, amniotic fluid, uterus, breasts, blood and extracellular extravascular fluid. Hytten assumed this gain to be 100% fat, whereas in the table, the gain in adipose tissue is assumed to consist of 80% fat, 18% water and 2% protein (Garrow, 1978)

We also accept that the two whole-body methods give the best estimate of fat gain during pregnancy. Combining the methods results in an average total fat gain of 3.0 kg by late pregnancy and a gain in maternal fat stores of 2.6 kg. Note that this is very similar to Hytten's (modified) estimate (Table 3). The gain in maternal fat stores estimated by factorial analysis of weight gain was 3.0 kg (Table 4).

Fat gain during pregnancy in developing countries. In the only study from a developing country (The Gambia), in which TBW was measured, average fat gain was only 0.9 kg (Lawrence et al, 1987a), and the gain in maternal stores was estimated to be 0.4 kg.

Other studies from developing countries have used the skinfold technique (Barba, 1995; Thongprasert et al, 1987; Tuazon et al. 1987) and the average fat gain observed was 1.47 kg. The data are subject to the same drawbacks outlined above. The gain in maternal fat stores estimated by factorial analysis of weight gain was 1.3 kg.

In summary we recommend continued use of Hytten's estimates of the energy deposited as new tissue as set out in Table 3, but with a reduction in the assumption for maternal fat. The costs of deposition can be presented as 30 MJ (7200 kcal) for the fetus and 112 MJ (26 700 kcal) for the mother, or as 29 MJ (6900 kcal) for protein and 113 MJ (27000 kcal) for fat (mother and fetus combined).

Assuming a desirable fat gain of 2.5 kg in the maternal compartment and 0.4 kg in the fetus represents a reduction of about 0.5 kg from the 1985 value. Assuming the cost of deposition to be 39 kJ/g (9.3 kcal/ g), the total costs of fat gain are therefore 98 MJ (24 400 kcal) for the mother and 16 MJ (3800 kcal) for the fetus. Energy deposition can be assumed to be 0.4, 0.7 and 0.5 MJ/day (95, 165 and 120 kcal/day) in the three trimesters.

Energy cost of pregnancy: change in basal metabolic rate As a result of the increased tissue mass, maintenance costs rise during pregnancy, and this increase in basal metabolic rate is one of the :major components of the energy costs of gestation. In this section, an overview is given of changes in basal or resting metabolic rate (BMR or RMR) measured in recent longitudinal studies conducted in various countries.

Description of studies reviewed. During the past 10 years, nine prospective, longitudinal studies have been published which included measurements of changes in BMR throughout pregnancy. Five studies were performed in affluent, developed countries namely Scotland (Durnin et al, 1987), England (Goldberg et al, 1993), Sweden (Forsum et al, 198,3) and The Netherlands (Spaaij, 1993; van Raaij et al, 1987). The remaining studies were conducted in the poorer, less developed countries of Thailand (Thongprasert et al, 1987), The Philippines (Tuazon et al, 1987) and The Gambia (Lawrence et al, 1987b; Poppitt et al, 1993). Data in the Gambian study conducted by Lawrence were collected from two separate groups, one of which was provided with a high energy supplement throughout pregnancy.

Table 4 Longitudinal estimates of fat gain in pregnancy

^a Body weight gain was extrapolated to the full 40 week period, assuming that the average weight gain during the first 10 weeks of pregnancy is 0.65 kg, and that body weight increases by 0.40 kg/week towards term (Hytten, 1991).
^b Estimated, from actual measurements.
^c Gain in adipose tissue was calculated by factorial analysis: subtracting birthweight (and placental weight), as well as Hytten's estimate for the increased weights of placenta, uterus, breasts, blood, extracellular extravascular and amniotic fluids (5.75 kg, or, excluding placental weight, 5.1 kg) from pregnancy weight gain.
^d Developing country.

All the studies reported changes in BMR during pregnancy relative to either a pre-pregnancy or an early pregnancy (10-18 weeks) baseline (Table 5). Measurements were made under standardised conditions (rest, post-absorption and thermoneutrality), and gaseous exchange was measured using a Douglas bag, ventilated hood or whole-body indirect calorimeter. The costs of maintaining the fetus and other products of conception were calculated as the cumulative change in BMR throughout pregnancy measured up to 35/36 weeks (Durnin et al, 1987; Lawrence et al, 1987a; Spaaij, 1993; Thongprasert et al, 1987; van Raaij et al, 1987) or up to 40 weeks or term (Forsum et al, 1988; Goldberg et al, 1993; Poppitt et al, 1993; Tuazon et al, 1987).

Variability of changes in BMR between populations. Figure 1 shows the mean changes in BMR measured longitudinally every 6 weeks. The data have been separated into two groups representing developed (left hand panel) and less developed (right-hand panel) countries. There is a clear divergence between the women from affluent and developing countries. In the former, BMR increased rapidly in response to pregnancy. In the latter the increase in BMR was delayed and, in the Gambian women, was preceded by a rapid fall early in gestation. The most striking feature of Table 5 is the wide variability in cumulative maintenance costs among populations. These costs range from an average of +210 MJ (+50 200 kcal) in the Swedish women to - 45 MJ ( - 10 750 kcal) in unsupplemented Gambian women. For the purpose of formulating energy requirements of pregnancy, changes observed in healthy populations with favourable pregnancy outcome should be the criteria. The average is 159 MJ (38000 kcal), which is remarkably close to the original estimate of 150 MJ based on literature values of changes in oxygen consumption of individual organs and processes (Hytten & Chamberlain, 1980). Average increases over the first, second and third trimester of pregnancy were +0.2, + 0.4 and + 1.1 MJ/day ( + 48, + 96 and + 263 kcal/ day), respectively; average percentage increases above non-pregnant non-lactating (NPNL) BMR were +4%, + 7% and + 19%.

Variability of changes in BMR within populations (between subjects). Only three studies give information on the between-subject variability in maintenance costs. In Figure 2 the cumulative changes in BMR of women from England (Goldberg et al, 1993), The Netherlands (Spaaij, 1993) and The Gambia (Poppitt et al, 1993) illustrate a wide range between individuals in each population. Since the cumulative increase in BMR during pregnancy constitutes a large proportion of the total energy costs, this variability will have an important influence on extra daily requirements for individuals. Although this substantial between-subject variability has no impact on the formulation of recommended daily intakes (which are expressed for population groups), it emphasises the difficulty of making any prescriptive recommendations for individuals.

Determinants of changes in BMR. To identify the nutritional factors which influence pregnancy maintenance costs, a regression analysis on the mean values from the nine studies was performed. Correlations were calculated between the cumulative maintenance costs and each of the following variables: pre-pregnancy height, pre-pregnancy weight, pre-pregnancy fat-free mass, pre-pregnancy fat mass, pre-pregnancy percentage fat, weight gain during pregnancy, fat gain during pregnancy, and birthweight. The maintenance costs were most strongly correlated with the fatness of the women before they became pregnant (r = + 0.72, p < 0.001) and the amount of weight gained during pregnancy (r = +0.79, p < 0.001, Figure 3). These two variables were themselves highly correlated (r= +0.88, p < 0.001). From the regression line in Figure 3, it appears that for a favourable weight gain during pregnancy (approx 12.5 kg), the cumulative increase in BMR is about 160 MJ (38 000 kcal).

There is evidence from English (Goldberg et al, 1993) and Dutch studies (Spaaij, 1993) that the highly individual metabolic response to pregnancy may also be directed by pre-pregnancy fatness on an individual basis. However, three tertiles of Scottish women, grouped according to their initial percentage body fat, did not show different changes in BMR during pregnancy (Durnin, 1992). Unfortunately, no correlation coefficients between initial fatness and changes in BMR were given. Poppitt et al, (1993) also found no relationship between pre-pregnancy body fatness and cumulative maintenance costs. However, the range of pre-pregnancy fatness in the marginally nourished Gambian women was narrow.

The associations between maintenance needs, pregnancy weight gain and pre-pregnancy fatness are important in the development of energy recommendations. They indicate that achieving a target weight gain (approx 12.5 kg) will necessarily be associated with high maintenance costs (approx 160 MJ). They also indicate that many populations may be found to have lower maintenance requirements, but that these will probably be associated with inadequate weight gain and should not therefore be used for the formulation of energy recommendations.

Prediction of BMR during pregnancy. In non-pregnant women, BMR (MJ/day) can be predicted from body weight (kg), height (m) and age (y) with the Schofield equations (Schofield et al, 1985) which were used in the 1985 WHO/FAO/UNU report. No predictive equations are available for different stages of gestation. We compared three methods to predict BMR during pregnancy. In method 1 the Schofield equations were applied to data from pregnant women, using their body weight in pregnancy. In method 2 the equations were used to predict non-pregnant BMR from pre-pregnancy body weight. This estimate was then corrected by adding a factor specific for each trimester ( + 0.2, + 0.4 and + 1.1 MJ/day for the first, second and third trimesters, respectively). In method 3 the same estimates of pre-pregnancy BMR were corrected using a multiplication factor (1.04, 1.07 and 1.19 for the first, second and third trimesters, respectively). The three methods were compared using data from individual women from England (Goldberg et al, 1993) and The Gambia (Poppitt et al, 1993). Method 2 provided the best prediction. We therefore recommend that, if the BMR × PAL system is to be used for pregnancy, BMR should be calculated by adding increments of 0.2, 0.4 and 1.1 MJ in the three trimesters to NPNL BMR predicted from the Schofield equations.

Table 5 Population characteristics

^S Supplemented with energy-dense groundnut biscuits.
^U Unsupplemented.
^a PP = pre-pregnant; EP = early pregnancy.

Continued

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