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Original Research Communications |
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Objective: The objective was to determine the relative contributions of genetic background and energy intake and expenditure as determinants of body weight at 1 y of age.
Design: Forty infants of obese and 38 infants of lean mothers, half boys and half girls, were assessed at 3 mo of age for 10 risk factors for obesity: sex, risk group (obese or nonobese mothers), maternal and paternal body mass index, body weight, feeding mode (breast, bottle, or both), 3-d energy intake, nutritive sucking behavior during a test meal, total energy expenditure, sleeping energy expenditure, and interactions among them.
Results: The only difference between risk groups at baseline was that the high-risk group sucked more vigorously during the test meal. Four measures accounted for 62% of the variability in weight at 12 mo: 3-mo weight (41%, P = 0.0001), nutritive sucking behavior (9%, P = 0.0002), 3-d food intake (8%, P = 0.0002), and male sex (3%, P = 0.05). Food intake and sucking behavior at 3 mo accounted for similar amounts of variability in weight-for-length, body fat, fat-free mass, and skinfold thickness at 12 mo. Contrary to expectations, neither total nor sleeping energy expenditure at 3 mo nor maternal obesity contributed to measures of body size at 12 mo.
Conclusions: Energy intake contributes significantly to measures of body weight and composition at 1 y of age; parental obesity and energy expenditure do not.
Key Words: Obesity • body size • infants • risk factors • genetic influence • energy intake • energy expenditure • nutritive sucking behavior
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The present study was designed to resolve the conflict concerning the role of energy expenditure and energy intake in the prediction of body size in the first year of life. We determined TEEs, sleeping energy expenditures, energy intakes, and nutritive sucking behavior at 3 mo of age in 40 infants born to obese mothers and 38 infants born to lean mothers and determined measures of infant body composition at 3 and 12 mo of age.
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SUBJECTS AND METHODS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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18 y of age. In addition, the families had to express a high degree of commitment to the study, which had been described as being long. Exclusion criteria for the infants were as follows: a gestational age <36 or >42 wk and a low or high weight-for-gestational-age. Data were not available at 12 mo for 1 infant from the high-risk group and for 3 infants from the low-risk group; therefore, this report is based on data for 40 high-risk and 38 low-risk infants. Information about paternal height and weight was reported by the father or mother. Informed consent was obtained from the parents and the protocol was approved by the Institutional Review Boards of the University of Pennsylvania and of the Children's Hospital of Philadelphia. The study was conducted in the Nutrition and Growth Laboratory of the Children's Hospital of Philadelphia.
Body size and composition
Infant birth weight was obtained from hospital records. At 3 and 12 mo of age, weight was measured in triplicate with a digital scale (model 4800; Scaletronix, Carol Stream, IL); length with a Holtain Infant Length Board (Crymych, United Kingdom) (12); skinfold thicknesses with a Holtain Skinfold Caliper (Crymych) at the biceps, triceps, subscapular, and suprailiac sites; and body fat with total body electrical conductivity (HP2-TOBEC; EM-SCAN Incorporated, Springfield, IL) (13).
Energy intake
Three feeding modes of the 3-mo-old infants were assessed and categorized: 1) breast-feeding—all nourishment from breast milk; 2) formula feeding—all nourishment from infant formula, delivered by a bottle; and 3) combined breast-feeding and bottle-feeding. Energy intake was assessed in 2 ways: from food intake and from nutritive sucking behavior.
Food intake was determined from weighed food records (14) kept by the parents for 3 d during the week after the body-composition assessment. Parents were carefully instructed in the technique of weighing and recording all food intake. Bottles of formula were weighed before and after each feeding with a digital scale (model 6025; Sunbeam, Hattiesburg, MS) accurate to 1 g. Breast-fed infants were weighed unclothed before and after feeding with an integrating scale (model IP65, type I-15; Sartorius, Edgewood, NY) adapted with infant bassinets and accurate to 1 g. Food records were analyzed by a registered research dietitian, who was blinded to risk group, using the FOOD PROCESSOR II PROGRAM (ESHA Research, Salem, OR).
Nutritive sucking behavior was measured in the laboratory while the 3-mo-old infants were fed a midday test meal from an automated nutritive sucking apparatus (15). To maximize acceptance, nipples were constructed from standard, commercially available baby bottle nipples (Evenflo Products Co, Canton, GA; Gerber Products Co, Fremont, MI; and Playtex Products Inc, Westport, CT) adapted to deliver identical flow rates (16). Infants were fed either expressed breast milk or their customary formula by their mothers (or usual caregivers) with their customary nipple type. Five sucking variables were assessed during the test meal: total intake (in g) of formula or milk, total number of sucks, overall sucking rate (in sucks/s), suck rate within sucking bursts (in sucks/s), and maximum sucking pressure (in mm Hg). Because these variables were highly correlated, one representative value (total number of sucks) was used in the analyses.
Sleeping energy expenditure
Sleeping energy expenditure was measured with open-circuit indirect calorimetry by using a computerized metabolic cart (model 2900Z; SensorMedics, Yorba Linda, CA) with a clear, ventilated hood placed over the head of the infant to sample gases. Infants entered the Growth and Nutrition Laboratory in the late morning and measurements were taken 1 h after the midday feeding while the infant was in natural sleep. The first 10 min of the 60-min assessment were considered a period of acclimation by the child; therefore, measurements during this time were not used in the calculations. Sleeping energy expenditures were reviewed and any interval associated with documented movement and waking or with changes in sleeping energy expenditures was removed from the analysis.
The TEE of the 3-mo-old infants was measured over 7 d with the doubly labeled water method. Isotopes were analyzed in the laboratories of the University of Chicago. Doubly labeled water is a nonintrusive, indirect calorimetric method that uses stable isotopes and is accurate and precise in infants (17–19). On the same day that sleeping energy expenditures were measured, a baseline urine specimen was collected and 0.25 g H218O and 0.15 g 2H2O/kg body wt were given orally. Any spillage of the dose was collected on absorbent paper and weighed. Two urine samples were collected 4–6 h after administration and 2 more were collected in the morning before feeding, 6–8 d after the dose. Urine specimens were collected in dry paper diapers and frozen in zip-locked plastic bags. Samples not collected in the Growth and Nutrition Laboratory were picked up by research assistants. Urine was expressed from the diaper by pressure and frozen.
The isotope abundances in the urine samples were analyzed by mass spectrometry (20). Triplicate 2-µL aliquots of urine were vacuum distilled into quartz tubes and reduced to hydrogen over zinc at 500°C. Aliquots (1.5 mL) of urine were equilibrated with carbon dioxide at a constant temperature and the resulting carbon dioxide was isolated. Gravimetric dilutions of the isotope-labeled water were analyzed by using the same methods. Isotopic enrichments were calculated relative to baseline, and the isotope-dilution spaces and elimination rates were calculated by using the slope-intercept method (16). Carbon dioxide production was calculated as follows:
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Statistical analysis
We first compared, with two-sample t tests, all variables related to weight and the possible influences on weight between high- and low-risk infants at 3 and 12 mo. Second, we estimated the relation among the variables measured at 3 and 12 mo by using Pearson correlation coefficients. Third, we evaluated by hierarchical linear regression analyses the independent contributions of the following unmodifiable variables: risk group, maternal and paternal BMI, sex, 3-mo weight, and sleeping energy expenditures on our predicted 12-mo outcomes (weight, weight-for-length, fat mass, fat-free mass, and sum of 4 skinfold-thickness measures). The modifiable variables feeding mode, 3-d food intake, and a representative measure of sucking behavior (total number of sucks during the laboratory meal) were then incrementally entered into the regression. A variable was kept in the model if the P value on entry was <0.10. A variable was removed from the regression if the P value was >0.10. The incremental variance (R2) for each variable added to the model was computed. Model building proceeded in this manner until all significant predictors had been entered one at a time.
TEE measurements were available for only 42 subjects. Variables for these 42 subjects did not differ significantly from those for the 36 subjects for whom TEE measurements were not available. Data for these 42 subjects were entered into a separate regression. The presence of obese fathers in the sample made possible comparisons of alternative risk groups in addition to the original comparisons based solely on maternal obesity. First, we compared the characteristics of 20 infants with 2 obese parents with those of 30 infants with no obese parents. Second, we also compared a risk group of 28 infants with 1 obese parent. Analyses were conducted by using SAS (SAS/STAT User's Guide, 1989; SAS Institute, Inc, Cary, NC).
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RESULTS |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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. Although selection was based only on the BMIs of the mothers, the BMIs of the fathers of the high-risk infants were significantly higher than those of the low-risk infants. There was no significant difference between the birth weights of the high- and low-risk infants.
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). The striking similarities in the changes in weight-for-length and the sum of 4 skinfold-thickness measurements during the year are illustrated in Figures 1 and 2, respectively. There was also no significant difference between the high-risk (3 of 39, or 8%) and low-risk (5 of 38, or 13%) groups in the proportion of subjects who were at or above the 90th percentile of weight-for-length at 12 mo.
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). The intraclass correlation of food intake among the 3 d was 0.67 (P < 0.001). Seventy-six infants accepted the laboratory test meal and, in contrast with the other measures, sucking behavior of the high-risk group was more vigorous than that in the low-risk group. The TEEs and sleeping energy expenditures of the 2 risk groups were almost identical at 3 mo of age, as was the measure of physical activity calculated from TEE minus sleeping energy expenditure (Table 4).
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Prediction of body size
Because body weight, weight-for-length, and changes in these variables were not significantly different between the high- and low-risk groups (Table 2
), we pooled the data from the 2 risk groups and calculated correlation coefficients among the variables measured at 3 and 12 mo. The significant intercorrelations among the risk factors at 3 mo of age, particularly between weight and TEE (r = 0.71, P < 0.001) and between weight and sleeping energy expenditure (r = 0.47, P < 0.001), are shown in Figure 3. Risk factors at 3 mo were also significantly correlated with weight at 12 mo, notably the well-recognized correlation between 3-mo and 12-mo weights (r = 0.59, P < 0.0001). Similar correlations were found for weight-for-length (Figure 4). The independent contributions of these highly intercorrelated risk factors were assessed by the regression analyses described above. Of the 10 risk factors, only 4 entered the regression that predicted 62% of the variability in weight and 54% of the variability in weight-for-length at 12 mo.
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and Figure 3). Male sex accounted for a small amount of variability (3%; P = 0.05). Weight-for-length values were comparable (Table 5 and Figure 4). Notable among the predictors that did not enter the regression were risk group, maternal and paternal BMI, feeding mode, sleeping energy expenditure, and interactions among them. The separate regression for TEE showed that it did not predict weight, weight-for-length, fat, fat-free mass, or skinfold thickness at 12 mo.
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Regression analyses also assessed the prediction of fat mass, fat-free mass, and the sum of 4 skinfold thicknesses at 12 mo of age. Initial (3 mo) fat mass accounted for 24% (P = 0.0001) of the variability in fat mass and food intake accounted for an additional 8% (P = 0.003). Initial (3 mo) fat-free mass accounted for 49% (P = 0.0001) of the variability in fat-free mass at 12 mo (P = 0.0001), whereas total sucks and food intake accounted for an additional 5% (P = 0.008) and 3% (P = 0.02), respectively. Neither TEE nor sleeping energy expenditure entered the regression.
Initial skinfold thickness accounted for 16% (P = 0.003) of the variance in skinfold thickness at 12 mo, whereas food intake and total sucks accounted for an additional 8% (P = 0.007) and 7% (P = 0.01), respectively. Again, neither TEE nor sleeping energy expenditure entered the regression.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The positive findings of this study are noteworthy. Four measures predicted a full 62% of the variance in body weight at 12 mo of age: the unmodifiable variables male sex and body weight at 3 mo and the modifiable variables energy intake and sucking behavior at 3 mo. Similar results were found for the other 4 indexes of body size and composition. The strength of these behavioral predictors is evident from the fact that they were derived from very limited information 9 mo earlier—no more than 3 d of food intake records and one test meal.
These findings go a long way to resolving the conflict among the results of the previous longitudinal studies of growth and development during the first year of life. They support the finding by Roberts (5) that the food intake of the 6 infants who became overweight was 42% greater than that of those who remained lean at 6 mo, the age at which these 6 infants first became overweight. Further support is provided by the finding of Dewey et al (6) that the greater fatness of 41 formula-fed infants than of 46 breast-fed infants was due to their greater energy intake.
Our finding that neither TEE nor sleeping energy expenditure predicted measures of body size or composition supports the results of Davies et al (2) and of Wells et al (3), who found no relation between TEE at 3 mo and measures of body fatness at 12 mo. Our findings do not support the finding of Roberts et al (1) that a low TEE at 3 mo predicted measures of body size at 12 mo. In contrast, we found that TEE at 3 mo was highly positively correlated with body weight at 12 mo (r = 0.71, P = 0.001).
Our findings also do not support the finding of Roberts et al (1) that maternal obesity (in combination with a low TEE at 3 mo) predicted overweight in 6 infants at 12 mo. The mean BMI of our obese mothers (32.1) was almost identical to the mean BMI (32.2) of the obese mothers in the study by Roberts et al. Nevertheless, our 40 infants of obese mothers did not differ in any measure of body size or composition from the 38 infants of our nonobese mothers. We had not expected to find this lack of influence of maternal BMI on infants' weight, but a review of the literature revealed that it is not uncommon. Six studies reported no such relation during the first year of life (23–28) whereas only 2 found such a relation (29, 30).
These findings, and findings from similar studies, strongly support the view that energy intake, not energy output, is the major determinant of body size during the first year of life. Even the one exception, the findings for 6 overweight infants by Roberts et al (1), may be only apparent. Roberts et al (1) initially reported no significant difference in energy intake between low- and high-risk groups at 3 mo. However, as noted above, Roberts (5) later reported that the infants who became overweight consumed 42% more energy at 6 mo than did the infants who did not become overweight. Their having become overweight at 6 and 12 mo may have been due to their high energy intake rather than to their low TEE at 3 mo, an explanation compatible with the results of the prospective study by Ravussin et al (31) of already-obese adult Pima Indians. In this study, a reduced rate of energy expenditure predicted weight gain but less than half of the increase in body energy stores was accounted for by this reduced energy expenditure; energy intake may have accounted for the rest.
Because our results are limited to the first year of life, effects of the risk factors that we examined may differ at later ages. In fact, studies of preadolescent children have yielded conflicting results regarding the relative importance of energy intake and energy expenditure. For example, in prospective longitudinal studies, Goran et al (32) found that energy expenditure did not predict later fatness, whereas Delany et al (33) reported that reduced energy expenditure did predict increased body fat in boys. Although parental obesity has begun to exert an effect on fatness in childhood (24), it is not clear that the effect is exerted via energy expenditure. Neither Goran et al (34 ) nor Salbe et al (35 ) found a relation between parental BMI and the TEE in the children they studied, implying that a parental effect may be exerted by increased energy intake. The only prospective study of energy intake of children did not, however, support this implication: Griffiths et al (36) reported that a low energy intake at 4 y of age predicted adiposity in girls at age 15 y.
Clearly, there is a need for further studies to elucidate the respective roles of energy intake and energy expenditure in the genesis of human obesity. However, even the most careful studies face daunting obstacles. The periods of energy surplus that lead to obesity—from a high energy intake, a low energy expenditure, or both—may be transient. Accordingly, studies conducted during periods of energy balance may not detect critical relations. Furthermore, as the weights of children diverge, it becomes increasingly difficult to appropriately normalize energy intake and expenditure.
Skepticism has surrounded the accuracy of self reports of energy intake, and studies with doubly labeled water indicate that there is significant underreporting of food intake by adolescents (37) and adults (38), particularly if they are obese. The method we used to measure food intake in the present study (ie, 3-d weighed food records) involved careful weighing of the baby bottle or infant before and after each feeding over a period of 3 d; therefore, we feel that the method was reliable. Furthermore, we found no evidence of obesity-related bias: reports of infants' energy intakes by obese and nonobese mothers did not differ significantly.
Note that the 3-d food intake records were not correlated with the total number of sucks in the laboratory test meal (r = 0.12, P = 0.28). The 2 measures assess different aspects of energy intake and together provide a more comprehensive assessment than does either method alone. Furthermore, sucking behavior was the only variable that differentiated the high- and low-risk groups and, in another study, nutritive sucking behavior in infancy independently predicted adiposity in children as old as 3 y (39).
The findings of the present study suggest an alternative to a popular theory of the origin of obesity. The origin of obesity may be excessive energy intakes and not deficits in energy expenditure. This theory has implications for both research and practice, suggesting that genetic research pay particular attention to factors that control food intake. Its implications for practice and for the control of obesity are favorable: instead of being derived from largely unmodifiable metabolic determinants, obesity may result from the potentially modifiable voluntary behavior of excessive food intake.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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2 Supported in part by grants 31050 and 01183 from the National Institute of Mental Health, grant 38633 from the National Heart, Lung, and Blood Institute, grant RR00240 from the National Institutes of Health, and grant DK30031 from the Clinical Nutrition Research Unit of the University of Chicago.
3 Address reprint requests to AJ Stunkard, Department of Psychiatry, University of Pennsylvania, 3600 Market Street, Room 734, Philadelphia, PA 19104-2648. E-mail: stunkard{at}mail.med.upenn.edu.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONSUBJECTS AND METHODSRESULTSDISCUSSIONREFERENCES |
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0.01. SEE, sleeping energy expenditure; TEE, total energy expenditure.