Changes in basal metabolic rate during pregnancy in relation to changes in body weight and composition, cardiac output, insulin-like growth factor I, and thyr

¹ From the Division of Nutrition, Department of Biomedicine and Surgery (ML, HO, AS, and EF), and the Division of Clinical Physiology, Department of Medicine and Care (BJ-S), University of Linkoping, Linkoping, Sweden, and the Lust och Hälsa (Pleasure and Health) Clinic, Linkoping, Sweden (KB).

² Supported by the Swedish Research Council (project no. 12172 and to BJS), the Swedish Nutrition Foundation, the County Council of Ostergotland, the Knut and Alice Wallenberg Foundation, the Dr P Hakansson Foundation, the Magnus Bergvall Foundation, the General Maternity Hospital Foundation, and the Lions Research Foundation.

³ Reprints not available. Address correspondence to E Forsum, Division of Nutrition, Department of Biomedicine and Surgery, University of Linkoping, SE-58185 Linkoping, Sweden. E-mail: elifo{at}ibk.liu.se.

ABSTRACT  
Background: The total energy cost of pregnancy is largely due to an elevated basal metabolic rate (BMR). Large variations in the BMR response to pregnancy have been reported, but the factors associated with this variability are incompletely known.

Objective: The objective was to identify factors associated with variability in the BMR response to pregnancy.

Design: In 22 healthy women, BMR, body weight (BW), total body fat (TBF), fat-free mass (FFM), circulatory variables, serum concentrations of insulin-like growth factor I (IGF-I), and thyroid hormones were measured before pregnancy and in gestational weeks 14 and 32. BMR and BW were also measured in gestational weeks 8, 20, and 35. Fetal weight was estimated in gestational week 31.

Results: In gestational week 14, the increase in BMR correlated significantly with the corresponding increase in BW and with the prepregnancy percentage of TBF. Together these variables explained 40% of the variability in the BMR response. In gestational week 32, the increase in BMR correlated significantly with the corresponding changes in BW, TBF, FFM, IGF-I, cardiac output, and free triiodothyronine. The increase in BW in combination with fetal weight or with the elevated concentration of IGF-I in serum explained 60% of the variability in the increase in BMR.

Conclusions: Weight gain and the prepregnancy percentage of TBF—ie, factors related to the maternal nutritional situation—are important factors with regard to the variability in the BMR response to pregnancy. Thus, it is important to consider the nutritional situation before and during gestation when assessing pregnancy energy requirements.

Key Words: Basal metabolic rate • cardiac output • body composition • free triiodothyronine • insulin-like growth factor I • pregnancy

INTRODUCTION  
Human pregnancy is associated with increased requirements for dietary energy (1, 2), including the energy cost resulting from an elevated basal metabolic rate (BMR). This elevation in BMR is considered to be a result of increased oxygen consumption because of enhanced work with respect to maternal circulation, respiration, and renal function and to the increased tissue mass (3). The magnitude of the increase in BMR during pregnancy varies considerably between women, but the factors responsible for the variation are incompletely known. Population data from 9 countries show that, when expressed as the average for all women studied in each country, cumulative BMR for the entire pregnancy was significantly correlated with gestational weight gain and with average prepregnancy body fatness (1). The nutritional situation of the woman thus seems to be important, although a large variation in the increase in BMR has been found among women within the same population who apparently are living under similar dietary conditions (1, 4). A relation between prepregnancy body fatness and increases in BMR during pregnancy has been found for women within a population in some studies (5, 6) but not in others (7, 8).

Several additional factors may be responsible for variability in the BMR response to pregnancy, eg, the variation in the magnitude of the increase in cardiac work. This increase is considered to account for 40% of the increase in oxygen consumption at the end of the first trimester and 25% of that at the end of the second trimester (9). However, Spaanderman et al (10) found no relation between the magnitude of the BMR response to pregnancy and the increase in cardiac output during the first trimester. Corresponding data for women in the second half of pregnancy are not available. It is also conceivable that, because thyroid hormones are known to control the rate of energy metabolism in humans, the BMR response to pregnancy is related to serum concentrations of these hormones. During pregnancy, the metabolically active hormones free triiodothyronine and free tetraiodothyronine decline slightly (11). However, no study has investigated their role in relation to the magnitude of the BMR response to pregnancy. Furthermore, it is conceivable that increases in serum concentrations of insulin-like growth factor I (IGF-I) during pregnancy are related to the increase in BMR because such concentrations are known to be correlated with body weight (BW) during pregnancy (12) and to vary in response to food intake (13) and thus to reflect the maternal nutritional situation. However, no reports are available of studies that investigated relations between increases in serum concentrations of IGF-I and increases in BMR during pregnancy. Forsum et al (8) found that birth weight correlated with the cumulative increase in BMR during the second half of pregnancy but not during the first half. Thus, fetal size is another factor that may influence variations among women with respect to the BMR response to pregnancy. The current study investigated fetal weight, maternal BW, and maternal body composition before and during pregnancy; serum concentrations of IGF-I and thyroid hormones; and circulatory variables in relation to the variability in the BMR response to pregnancy.

SUBJECTS AND METHODS  
Subjects
Thirty-nine healthy, nonsmoking women who were planning pregnancy and living in the Linkoping area were recruited by means of advertisements in the local press and through the health care system. All women underwent evaluation in the nonpregnant state, and 22 of the women became pregnant between 8 and 524 d (± SD: 137 ± 136 d) later. With the exception of 1 subject, whose BW was recorded and found to be unchanged 1 y after this investigation, these women became pregnant within 1 y. Gestational age was assessed on the basis of an ultrasound scanning measurement, which was generally taken in gestational week 12 ( Protocol
The women were examined before conception and during gestational weeks 8, 14, 20, 32, and 35. Before pregnancy and during gestational weeks 14 and 32, the following procedure was conducted. After an overnight fast, the woman arrived at the hospital by car, and a venous blood sample was drawn. She then rested for 45 min, after which her BMR was measured, and a transthoracic echocardiographic examination was immediately conducted to measure heart rate (HR), stroke volume, cardiac output, mean arterial pressure (MAP), and total peripheral vascular resistance (TPVR). The BW of the woman was then recorded, and she was given an oral dose of deuterium. During the next 14 d, the woman collected 5 urine samples to estimate total body water as a basis for body-composition assessment. In gestational weeks 8, 20, and 35, only BMR and BW were measured. In addition, fetal weight was estimated on the basis of an ultrasound scanning examination during gestational week 31. The BW of the woman was also measured in the delivery room before childbirth. The birth weight of the infants was obtained from hospital records.

Basal metabolic rate
We used a ventilated hood system (Deltatrac Metabolic Monitor; Datex Instrumentarium Corp, Helsinki) to measure carbon dioxide production and oxygen consumption during a 20-min period. BMR was calculated according to de Weir (15). For each subject, BMR obtained at each measurement occasion was plotted against the stage of gestation. The cumulative increase in BMR was calculated as the area under the curve from the start of pregnancy until delivery. In this calculation, BMR at the time of delivery was assumed to be equal to BMR during gestational week 35, and all women were assumed to have delivered their infants after 280 d of gestation. The cumulative increase in BMR was also calculated for the first half (before gestational week 20) and the second half (after gestational week 20) of pregnancy.

Deuterium dilution
Each subject was given an accurately weighed dose of ²H₂O (0.05 g/kg BW) after collection of background urine samples. Five additional urine samples were collected 1, 4, 8, 11, and 15 d after the day of dosing. Deuterium enrichment of dose and urine samples was analyzed with the use of an isotopic ratio mass spectrometer fitted with a CO₂/H₂/H₂O equilibrium device (Deltaplus XL; Thermoquest, Bremen, Germany). Deuterium dilution space was calculated from zero-time enrichment obtained from the exponential isotope disappearance curve, and total body water was calculated as deuterium dilution space divided by 1.04. Further details of analyses and calculations were published previously (16).

Circulatory variables
Cardiac output was determined by means of transthoracic echocardiography with the use of a 3.25-MHz transducer for two-dimensional images and a 2-MHz single probe for a Doppler scanning examination (CFM 750; GE Medical, Vingmed, Horten, Norway) as described and evaluated by Sjöberg and Wranne (17). First, with the subject lying in a left lateral recumbent position, the systolic aortic annulus diameter was measured on a two-dimensional image taken from a parasternal long-axis view. The aortic valve area was assumed to be circular and was calculated as (aortic annulus diameter/2)²x . Second, with the subject lying in a supine position with the head bent slightly backward, aortic blood flow velocity was measured with the single probe placed in the jugulum by means of a pulsed-wave Doppler scan. Stroke volume was calculated by using the average area under the aortic velocity curve (velocity integral) of 3 consecutive ejections and multiplied by the aortic valve area. HR was assessed from the electrocardiogram obtained during the Doppler scanning examination. Cardiac output (in mL/min) was calculated as stroke volume x HR. Blood pressure was measured noninvasively in the right arm with the use of a sphygmomanometer and the auscultatory method immediately after the echocardiography and while the subject was still lying in a supine position. MAP was estimated as diastolic pressure + (systolic pressure – diastolic pressure)/3, and TPVR was calculated as MAP/cardiac output. All examinations were performed by 1 of 3 experienced echocardiographers at the Division of Clinical Physiology, Linkoping University Hospital. The 3 echocardiographers measured the aortic annulus dimension and the systolic velocity integral with accuracy and precision in accordance with an earlier report (17). In 1 subject, the measurement of stroke volume in gestational week 14 failed as a result of technical problems.

Biochemical variables
Venous blood samples were collected in vacuum tubes. The samples were stored at 4 °C for 4 h, after which the blood was centrifuged at 1500 x g for 10 min at room temperature (20 °C) to obtain serum. Serum samples were stored at –70 °C until they were analyzed. Serum IGF-I was measured by means of a radioimmunoassay after acid-ethanol extraction as described previously (18). Serum concentrations of free triiodothyronine, free tetraiodothyronine, and thyroid-stimulating hormone (TSH) were analyzed by using a time-resolved fluoroimmunoassay with AutoDELFIA FT₃, AutoDELFIA FT₄, and AUTODELFIA hTSH Ultra kits (Wallac Oy, Turku, Finland), respectively, and with the use of the 1235 AutoDELFIA automatic immunoassay system (Perkin Elmer Life and Analytic Sciences, Boston) at Laboratory Medicine Ostergotland, Linkoping University Hospital. For 1 subject, no estimate of free tetraiodothyronine in serum was obtained in gestational week 32 because of a technical failure during the analysis.

Fetal weight and birth weight
Fetal weight was calculated from estimates of femur length, biparietal diameter, and abdominal circumference obtained by using the ultrasound scanning technique (14). The measurements were performed by an experienced midwife at the Clinic of Obstetrics and Gynaecology, University Hospital, Linkoping. The midwife recorded birth weight on an electronic scale (Tanita, Tokyo).

Body weight, height, and body composition
The BW of the women was recorded on a high-precision scale (KCC 150; Mettler-Toledo, Giessen, Germany). In the delivery room, BW was recorded on an electronic column scale (SECA; Vogel & Halke GmbH, Hamburg, Germany). Height was measured by using a wall stadiometer (Hultafors AB, Hultafors, Sweden). Total body fat (TBF) was calculated as BW – fat-free mass (FFM). FFM was calculated as total body water divided by 0.718 before pregnancy, by 0.723 at gestational week 14, and by 0.747 at gestational week 32 (16).

Statistical analysis
Values given are means ± SDs. Significant differences between group averages were identified by repeated-measures analysis of variance and subsequent post hoc analysis with the use of Tukey's multiple comparison test (19). Linear regression, correlation analyses, and multiple regression were performed as described by Hassard (19). Significance was set at P < 0.05. All statistical analyses were done with the use of STATISTICA software (version 6.0; StatSoft, Scandinavia AB, Uppsala, Sweden).

RESULTS  
Women
The women varied considerably with respect to BW, body mass index (BMI; in kg/m²), and percentage of TBF before conception. They also varied considerably with respect to weight gain during pregnancy (Table 1).

View this table:
TABLE 1. Characteristics of the women in the study and their infants¹

 
Basal metabolic rate
The average BMR did not differ significantly in gestational weeks 8, 14, and 20 from that before conception, but it did increase significantly from the prepregnancy value in gestational week 32 (1430 kJ/24 h) and gestational week 35 (1750 kJ/24 h) (Table 2). The increases in BMR during pregnancy varied considerably among women at all measurement occasions (Figure 1). In fact, until approximately gestational week 20, the BMR of some women even decreased. The cumulative increase in BMR (n = 22) was 16 ± 52 MJ (range: –69 to 122 MJ) for the first half of pregnancy, 177 ± 110 MJ (range: 9–437 MJ) for the second half of pregnancy, and 193 ± 156 MJ (range: –60 to 525 MJ) for the entire pregnancy.

View this table:
TABLE 2. Study variables in the subjects before pregnancy and in gestational weeks 14 and 32¹

 

View larger version (26K):
FIGURE 1.. Basal metabolic rate of individual women (n = 22) in the study in gestational weeks 8, 14, 20, 32, and 35, expressed as a percentage of the prepregnancy value. Each symbol represents 1 subject.

 
Body weight and body composition
BW, FFM, and TBF before pregnancy and at 14 and 32 wk of gestation are shown in Table 2. For BW, results obtained during gestational weeks 8, 20, and 35 are also given. BW was higher in gestational weeks 8 (1.8 kg), 14 (2.4 kg), 20 (5.2 kg), 32 (12.1 kg), and 35 (14.1 kg) than it had been before pregnancy. When compared with the prepregnancy values, little change was observed in average FFM and TBF in gestational week 14, whereas these estimates had increased by 7.6 and 4.5 kg, respectively, in gestational week 32. As shown in Table 3, significant correlations were observed before pregnancy between BMR and BW and between BMR and FFM but not between BMR and TBF. However, in gestational weeks 14 and 32, BW, FFM, and TBF were all significantly correlated with BMR. As shown in Table 4, increases in BW were significantly correlated with increases in BMR at all measurement occasions during pregnancy. Note that the coefficient of correlation between increases in BMR and increases in BW in gestational week 32 was as high as 0.699, which explains almost 50% of the variability of the increase in BMR. Furthermore, during the entire pregnancy, weight gain (in kg) and cumulative BMR (in kJ) were significantly correlated (r = 0.570; P < 0.05). In addition, in gestational week 32, increases in FFM and TBF were significantly correlated with increases in BMR (Table 4). Finally, when expressed as a percentage of the prepregnancy BMR, the increase in BMR in gestational week 14 correlated significantly with the percentage of prepregnancy TBF (r = 0.457; P < 0.05).

View this table:
TABLE 3. Correlation coefficients for equations obtained when basal metabolic rate (BMR) was regressed on body weight (BW), total body fat (TBF), or fat-free mass (FFM) ¹

 

View this table:
TABLE 4. Correlation coefficients obtained when increases in basal metabolic rate during pregnancy (y) are regressed on a number of selected independent variables¹

 
Insulin-like growth factor I
IGF-I concentrations were significantly lower in gestational week 14 and significantly higher in gestational week 32 than the IFG-I values obtained before pregnancy (Table 2). As shown in Table 4, the change in the serum concentration of IGF-I was significantly correlated with the elevation in BMR in gestational week 32 but not with that in gestational week 14. The changes in the serum concentration of IGF-I in gestational week 32 from the values obtained before pregnancy were also correlated with fetal weight in gestational week 31 (r = 0.490; P = 0.021).

Circulatory variables
Stroke volume, HR, cardiac output, MAP, and TPVR before pregnancy and in gestational weeks 14 and 32 are shown in Table 2. Average stroke volume in gestational week 14 was 11 mL higher than that before pregnancy. In gestational week 32, no further increase was recorded because, at that time, stroke volume was 8 mL higher than it had been before pregnancy. Meanwhile, MAP was lower in gestational weeks 14 and 32 than it had been before conception; the decrease was significant in week 14 but not in week 32. Average HR in gestational week 14 was not significantly different from the prepregnancy value, whereas the value in gestational week 32 was significantly higher than that before pregnancy. Average cardiac output had increased 0.9 L by gestational week 14 and 1.6 L by gestational week 32. As also shown in Table 2, TPVR had decreased 23% and 29% by gestational weeks 14 and 32, respectively. As shown in Table 4, the correlation coefficient for the linear relation between increases in BMR (y) and increases in cardiac output (x) was significant in gestational week 32 but not in gestational week 14.

Thyroid hormones
As shown in Table 2, by gestational weeks 14 and 32, average serum concentrations of free triiodothyronine and free tetraiodothyronine had declined from prepregnancy values. Furthermore, by gestational week 14, average serum TSH concentrations had decreased significantly, from 2.3 mU/L before pregnancy to 1.8 mU/L. This decrease was followed by an increase in the average value to 2.1 mU/L at gestational week 32. As shown in Table 4, the change in free triiodothyronine was significantly correlated with the increase in BMR in gestational week 32. No other significant correlations were found between the changes in serum concentrations of free triiodothyronine or free tetraiodothyronine and the corresponding increases in BMR.

Fetal weight and birth weight
Fetal weight and birth weight are shown in Table 1, and correlation coefficients for the linear relations between increases in BMR (y) and fetal weight in gestational week 31 and birth weight (x) are presented in Table 4 for results obtained in gestational weeks 8, 14, 20, 32, and 35. None of these correlations were significant, although the correlation between fetal weight in gestational week 31 and the increased BMR in gestational week 32 was as high as 0.417 (P = 0.054). The cumulative increase in BMR during the first half of pregnancy was not significantly correlated with fetal weight in gestational week 31 (r = 0.324) or with birth weight (r = 0.040). The cumulative increase in BMR during the second half of pregnancy was not correlated with birth weight (r = 0.198; NS), and the correlation coefficient for the linear relation between the cumulative increase in BMR during the second half of pregnancy and fetal weight in gestational week 31 was as high as 0.421 (P = 0.051).

Investigated factors in relation to variability in the BMR response to pregnancy
Gestational week 14
In gestational week 14, the multiple regression equation relating the increase in BMR (y) to the percentage of TBF before pregnancy (x₁) and to the increase in BW (x₂) was as follows:

DISCUSSION  
The women in this study were not randomly selected. They volunteered to participate in a study of diet and physical activity during pregnancy. Therefore, they may not necessarily be completely representative of Swedish women. However, before conception, 26% and 9% of the women in this study had a BMI >25 and >30, respectively. These figures agreed with recent estimates of BMIs in Swedish women of similar age (20) and with BMI estimates obtained in comparable women from several other Western countries (21). Moreover, the increases in TBF and BMR during pregnancy among the women in the current study were similar to those values reported in other studies of Western women (4, 22-24). The average weight gain during pregnancy for our subjects was somewhat greater than that recommended by the Institute of Medicine (25), and they gave birth to relatively heavy infants. Earlier studies suggest that Swedish women tend to gain slightly more weight during pregnancy than do other Western women (1, 26) and that Scandinavian newborns have become heavier during recent years (27). Thus, we believe that the women in our study are, in fact, quite representative of Swedish women and that they do not differ greatly from women in many other Western countries. When expressed per kilogram of FFM, our measurements of BMR before conception were in good agreement with data obtained in earlier studies of comparable women (8, 28).

In the current study, stroke volume, HR, and cardiac output increased during pregnancy, and MAP and TPVR decreased from the values obtained before conception. These changes agreed with earlier findings in pregnant women (10, 29). Our results suggest that the increase in cardiac output in gestational week 14 is an effect of an increased stroke volume and a decreased TPVR and that this increase in cardiac output is not correlated with the increase in BMR. However, the increase in cardiac output in gestational week 32 and compared with the prepregnancy value is also an effect of an increase in HR. At this stage of pregnancy, the increase in cardiac output is correlated with the increase in BMR. Such a significant relation between increases in BMR and cardiac output in late pregnancy has not been reported previously. It explained 35% of the variability in the BMR response to pregnancy in gestational week 32.

The changes during pregnancy in serum concentrations of free triiodothyronine, free tetraiodothyronine, and TSH in the women in our study were in good agreement with earlier findings (11, 30). Thus, we confirmed that serum concentrations of free triiodothyronine and free tetraiodothyronine decrease during pregnancy, and we observed for the first time a significant relation between changes in free triiodothyronine and increases in BMR in gestational week 32. The physiologic importance of the marginal decline in serum concentrations of free triiodothyronine and free tetraiodothyronine in the latter part of pregnancy is not known (11). It may be part of a regulation with the goal of maintaining an appropriate metabolic rate in the woman, perhaps by counteracting the stimulating effect on energy metabolism apparently associated with a high body fat content in pregnancy. However, it is important to point out that the observed relation between increases in BMR and changes in serum concentrations of free triiodothyronine was rather weak and that it explained only 20% of the variability in the BMR response to pregnancy in gestational week 32.

It is generally considered that BMR is significantly related to FFM in nonpregnant women, whereas TBF is not (31). The apparent explanation is that adipose tissue has a lower rate of oxygen consumption than do other tissues (32). Our results obtained before pregnancy are in agreement with these statements. However, when measured during pregnancy in the women in the current study, BMR was correlated not only with BW and FFM (in kg) but also with TBF (in kg). A significant relation between BMR and TBF (in kg) in gestational weeks 31–35 has been reported by Bronstein et al (33) in a cross-sectional study of pregnant women. However, the current study is the first to show such a relation in early pregnancy and also to present such findings based on measurements obtained in the same women before and during pregnancy. A possible explanation for these results is that the metabolic activity of adipose tissue increases during pregnancy. In this context, it is of interest to note that several studies have presented results indicating that the size of different adipose tissue compartments changes during reproduction (26, 34), that biochemical studies have indicated that pregnancy influences the activity of specific enzymes in adipose tissue (35), and that concentrations of plasma lipoprotein fractions are elevated during pregnancy, which indicates an increased metabolism of lipids (36). Furthermore, Okereke et al (37) reported that fat oxidation during human pregnancy is related to serum concentrations of leptin, an adipocyte-derived hormone, and of resistin, a novel hormone that is secreted by human adipocytes and the placenta, which has been suggested to play a role in regulating energy metabolism during pregnancy (38). This information supports the suggestion that adipose tissue becomes more metabolically active during pregnancy, and it could help to explain the significant relation between the percentage of TBF before gestation and the increase in BMR during pregnancy that was found in both the current study and in previous studies (1, 5, 6).

The results of the current study suggest that the factors responsible for the variability in the BMR response to pregnancy differ in early and late pregnancy. In early pregnancy, factors associated with the maternal nutritional situation—ie, the percentage of TBF before pregnancy and the gain in BW during pregnancy—explained 40% of this variability. The rest—ie, as much as 60%—cannot be explained by variations in circulatory changes or in serum concentrations of thyroid hormones or IGF-I, and thus it remains unknown. It is likely, however, that nutritional factors not taken into account in our study, such as the recent intake of dietary energy, may account for a part of the unexplained variability. This suggestion is based on the findings of Lawrence et al (39), who reported that supplementing poor women with dietary energy during pregnancy increased their BMR. We found that, in late pregnancy, >60% of the variability in the increase in BMR was explained by combining the increase in BW and fetal weight. At that stage of pregnancy, the metabolic rate of the fetus apparently contributes to the variability in the BMR response to pregnancy, and it is relevant to comment on the finding that 60% of variability in the increased BMR in gestational week 32 could be explained by increases in BW and elevations in serum concentrations of IGF-I. It is likely that this finding is due to the correlation between changes in serum concentrations of IGF-I in gestational week 32 and fetal weight, as observed in this study. However, as indicated earlier, because BW during pregnancy and the intake of macronutrients are both related to serum concentrations of IGF-I (12, 13), the observed relation may also be explained by variations in the nutritional situation of the women in our study.

Current recommendations for dietary energy intake during gestation assume that women gain 12 kg BW during the entire pregnancy, which is associated with optimal reproductive outcome (1, 40). This weight gain is associated with an increased BMR equivalent to 150 MJ for the entire pregnancy (1). However, optimal weight gain during pregnancy is > 12 kg for lean women and < 12 kg for overweight and obese women (25, 40). The data in the current study confirm that, during pregnancy, weight gain is correlated with the cumulative increase in BMR. Because this increase in BMR represents a chief component of the energy cost of pregnancy, our observation can be reconciled with the statement by Butte et al (5) that gestational weight gain is a principal determinant of the incremental energy needs during pregnancy. Many women in developing countries are lean; therefore, their optimal weight gain during pregnancy is >12 kg. In contrast, overweight and obesity among women of reproductive age are common in many countries, and for such women the optimal weight gain is <12 kg. Therefore, current recommendations for dietary energy requirements during pregnancy are inappropriate for lean, overweight, and obese women. Such recommendations should be extended to include guidelines for women who are lean, overweight, or obese before pregnancy.

ACKNOWLEDGMENTS  
We thank all the women who participated in this study. We also thank Inger Ekman and Margareta Nordvall for performing echocardiographic examinations and Ulf Hannestad for technical support during deuterium analyses.

EF designed the study, and ML had the responsibility for recruiting and investigating subjects and for analyzing samples and data. HO participated in investigating subjects and performing deuterium analyses and also analyzed IGF-I in serum under the supervision of AS. KB provided obstetrical care or medical advice and helped with subject recruitment. BJS was responsible for the echocardiographic examinations. ML and EF wrote the manuscript, which was subsequently reviewed by HO, AS, KB, and BJS. None of the authors had any conflict of interest.

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