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a Department of Paediatrics, University of Cambridge, Addenbrookes Hospital, Cambridge, United Kingdom
b Liggins Institute
c Epidemiology and Biostatistics Section, School of Population, University of Auckland, Auckland, New Zealand
| ABSTRACT |
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32 weeks gestation.
METHODS. A total of 56 healthy, developmentally normal, prepubertal children, aged 4 to 10 years were recruited. Thirty-seven were born
32 weeks gestation, and 19 were control subjects born at term with a birth weight >10th percentile. Insulin sensitivity (10–4 min–1 µU/mL) was calculated from a 90-minute frequently sampled intravenous glucose tolerance test. Perinatal, nutritional, and growth data were obtained retrospectively from both neonatal and early infancy records in the premature cohort.
RESULTS. Children born prematurely had decreased insulin sensitivity when compared with those born at term (13.8 vs 30.6). Neonatal nutrition was not correlated with insulin sensitivity; however, all of the infants had inadequate protein in the first month followed by excessive fat intake thereafter. Premature children with greater weight gain had lower insulin sensitivity. Higher carbohydrate intake in the first month of life was associated with greater weight gain from birth. No relationship was seen between weight gain and either protein or lipid intake.
CONCLUSIONS. Prematurely born children are insulin resistant and have suboptimal neonatal nutrition. Greater childhood weight gain magnifies this reduction in insulin sensitivity and seems to be associated with early nutrition. We speculate that a high carbohydrate neonatal diet may lead to greater weight gain and a greater reduction in insulin sensitivity in this group.
Key Words: prematurity insulin sensitivity neonatal nutrition carbohydrate intake
Abbreviations: SGA—small for gestational age SI—insulin sensitivity AIR—acute insulin response SDS—standard deviation score ASNS—American Society for Nutritional Sciences ChREBP—carbohydrate response element binding protein
There is now general consensus that many adult diseases, such as type 2 diabetes mellitus and hypertension, are in part determined by early life events. Initial epidemiologic observations from Barker and colleagues1–7 20 years ago linked lower birth weight to an increased risk of adult metabolic diseases. This association has subsequently been shown in other epidemiologic studies worldwide.8–12 Insulin resistance is observed early in the pathogenesis of these adult diseases, and an isolated reduction in insulin sensitivity has been reported in low birth-weight neonates and children.13,14 Thus, an explanation for this association between low birth-weight infants and later metabolic disease in adults is early impairment in insulin sensitivity, which worsens with increasing obesity, sedentary lifestyle, and puberty and manifests in adulthood as clinically relevant insulin resistance.
To date, the majority of published studies have focused on small for gestational age (SGA) term subjects, a group that usually has had in utero restriction, generally as a consequence of uteroplacental insufficiency. However, premature children (defined as a gestation <37 weeks) are also born at low birth weight and comprise 11.6% of births in the United States.15 This group, especially those born very premature (
32 weeks gestation), are exposed to nutritional restriction ex utero but at a similar developmental age to term SGA children. We have found recently that this group of premature children also have an isolated reduction in insulin sensitivity of similar magnitude to term SGA children.16
If an adverse perinatal environment induces a permanent resetting of insulin sensitivity, then identification of etiologic factors may enable modifications of neonatal and/or obstetric practices to decrease the risk of long-term metabolic sequelae. We have reported previously that a range of perinatal factors, including gestational age, birth weight, neonatal chronic illness, exposure to exogenous glucocorticoids, and maternal preeclampsia, were not associated with insulin sensitivity.16 This study incorporates the glucose metabolic data in a subset of these children and assesses the impact of neonatal nutrition and postnatal growth on glucose metabolic parameters and later growth.
| METHODS |
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32 weeks gestation. Subjects were prepubertal, with puberty defined as a testicular volume of >3 mL in boys and Tanner stage 2 breast development in girls. Children with evidence of adrenarche (Tanner stage 2 pubic hair or a dehydroepiandrosterone sulfate level outside the normal midchildhood range) were excluded. Gestation had been determined on all of the subjects by an early ultrasound scan (<14 weeks gestation). Subjects were recruited from past admission lists archived in the NICUs at National Womens and Middlemore Hospitals in Auckland. Exclusion criteria included multiple birth, chronic illness, identified syndromes, current medication known to influence insulin sensitivity (SI), a first-degree relative with diabetes mellitus, or presence of pretype 1 diabetes mellitus antibodies. The families of 103 eligible children who had been born prematurely were contacted, and the parents of 50 children consented to enroll their child. Complete neonatal records were available on 37 of these children, and these comprised our premature cohort. We have included previously reported SI data on a group of 19 healthy, control children for comparison.16 All were born at term with a birth weight greater than the 10th percentile.17 These children fulfilled the same criteria as described above for the premature cohort and were also aged 4 to 10 years. They included both normal height children recruited from the community and normal variant short stature children recruited from growth clinics.
The Auckland Ethics Committee provided approval for the study, and signed informed consent was obtained by subjects and their parents.
Study Protocol
Glucose metabolic data were obtained using a modified intravenous glucose tolerance test with tolbutamide and Bergmans Minimal Model as described previously.18 Measurements of SI and acute insulin response ([AIR] insulin release during the first 10 minutes of the intravenous glucose tolerance test with tolbutamide) were obtained. All of the subjects had height measured using a Harpenden stadiometer and weight measured on electronic scales.
The neonatal hospital records of the study group were retrospectively reviewed to obtain the following information: parenteral and enteral nutritional regimen until 12 weeks of age, weights at birth, corrected term (40 weeks gestation), and at corrected 1 year of age (12 months plus the number of weeks born prematurely). The neonatal records were completed daily, and all contained detailed data on the type and amount of nutrition that infants were receiving. Detailed information was available on the intravenous nutrition used, nutritional supplements, and preterm formula. Estimations used to calculate the nutrition in breast milk were made from data published previously.19 None of the premature infants received substantial breast milk until 4 weeks postnatally, although all received small amounts from early in the first week. Protein, lipid, carbohydrate, and energy intake (kilocalories per kilogram of body weight) were calculated for the periods 0 to 4 weeks, 4 to 8 weeks, and 8 to 12 weeks of age. Height and weight data were converted to SD scores (SDSs) using appropriate normative growth data to allow comparison between different ages and gender.20,21 SDSs were calculated from the standard formula: (growth measurement – mean growth measurement for age and gender)/growth measurement SD.
Nutritional data were compared with Canadian and American Society for Nutritional Sciences (ASNS) recommended daily nutritional requirements for premature infants.22,23 These recommendations were based on conservative estimations of nutrient and calorie requirements needed to maintain growth at a similar level to that in utero, taking into account skin heat and fluid loss, basal metabolic rate, energy of activity, and loss of energy and nutrients through excretion. These calculations are similar to but more exhaustive than those published previously.24,25
Other perinatal data were collected, including cause of prematurity (eg, induced delivery or premature labor, preeclampsia, and evidence of chorioamnionitis), neonatal illness (eg, days on oxygen, days of ventilation, and days of antibiotics), and medication (eg, prenatal and postnatal glucocorticoid exposure). This information has been described previously.16 When these variables were incorporated into mixed linear regression models, they were shown not to affect the metabolic and growth outcome parameters that we were assessing. We have not described them further in this study.
Assays
Plasma glucose was measured by Hitachi 911 automated random access analyzer (Tokyo, Japan) with an interassay coefficient of variation of 1.2%.26 Insulin was determined by an IMX microparticle enzyme immunoassay (Abbot, Abbott Park, IL) with an interassay coefficient of variation of <5%. This has minimal cross-reactivity with proinsulin. IA2 and glutamic acid decarboxylase antibodies were measured using a radioimmunoassay.27
Statistical Analysis
Differences in demographics and clinical measures between control and premature groups were investigated using t tests for continuous variables and
2 tests for proportions. General linear regression models were used to investigate the effect of maternal hypertension, maternal steroids, and postnatal steroids on SI in children who were born premature. General linear regression models were also used to establish whether neonatal nutrition affected either SI or later growth in the premature subjects. Variables included in the models were age, gender, weight SDS, height SDS, birth weight, and the nutritional parameters: carbohydrate, protein, lipid, and total energy intake in the first, second, and third months after birth. Perinatal variables examined to establish whether they had an effect on glucose parameters or growth included the number of days of ventilation and number of days on oxygen, days of glucocorticoid therapy, cause of prematurity, delivery method, and number of days on antibiotics. To demonstrate relevant univariate associations (which enable r2 to be assessed), simple linear regression was also used, examining growth variables against SI. The SI and AIR data were log transformed to meet the assumptions of normality. Growth was assessed at 4 time points: birth, at 40 weeks after the last menstrual period (term gestation), at 1 year corrected (ie, 1 year plus 8–14 weeks depending on the degree of prematurity), and current age. A significant P value was defined as <0.05. All of the values are mean ± SEM.
| RESULTS |
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There was little variation in intake between the infants after 4 weeks of age. None of the macronutrient values, that is, total calorie intake, protein, lipid, and carbohydrate were correlated with SI. However all of the infants had inadequate protein intake in the first 4 weeks of life when compared with the values recommended for premature infants by the Canadian Paediatric Society, the European Society of Pediatric Gastroenterology, and ASNS.22–25 All of the infants had lipid intake over the recommended values in the 4- to 12-week period. The intake values are compared with the Canadian and the ASNS recommendations in Table 2.
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Premature Auxology
In the premature group, nutritional status at the time of SI testing was inversely correlated with SI as expressed as weight SDS (r2 = 0.40; P < .0001) or body mass index SDS (r2 = 0.38; P
.0001). Weight SDS at 1 year corrected for gestational age was inversely correlated with current SI (r2 = 0.22; P < .01); however, weight SDS at 40 weeks from the last menstrual period (the equivalent of term gestation) was not (r2 < 0.05).
Weight gain was assessed over 3 time frames, from birth to the equivalent of term gestation (40 weeks), from 40 weeks until 1 year corrected for gestational age, and from 40 weeks until current age. Weight gain was derived from the difference in weight SDS at the beginning and end of each time period. Weight gain from birth to 40 weeks gestation was not associated with SI. SI, however, was inversely correlated with weight gain from 40 weeks through childhood with greater weight gain associated with lower SI (r2 = 0.53; P < .0001) as shown in Fig 1. Similarly, weight gain from 40 weeks gestation to 1 year was inversely correlated with current SI (r2 = 0.21; P = .01).
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| DISCUSSION |
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Prematurity has similarities to in utero nutritional restriction. Most premature births occur in the equivalent of the third trimester of pregnancy, and postnatally these infants are poorly nourished, catabolic, and lose weight. Thus, animal models of in utero nutritional restriction and human epidemiologic data on SGA subjects may well be applicable to prematurity. It is interesting to note that metabolic abnormalities, at least with respect to reduced SI, are quantitatively very similar in both premature and term SGA subjects after controlling for age, fat mass, and pubertal status.16 Thus, it is possible that similar etiologic factors are present in both groups.
The diets that our premature cohort received are somewhat different to those given in animal models in that they contained relatively low protein over the first 2 to 3 months followed by elevated lipid after the first month and consistently high carbohydrate throughout. The consistency of diets between premature subjects makes the lack of any correlation with SI difficult to interpret. That all of the subjects had an abnormal diet may be more relevant, and dietary abnormalities may still be a major etiologic factor in the development of the reduced SI. Animal models strongly support a role for nutrition in the development of metabolic abnormalities. Low protein intake in the dams has been shown to lead to insulin resistance, glucose intolerance, and hypertension in the offspring.33 These animal studies have shown changes in pancreatic size, structure, and blood flow, as well as hepatic structure and size with altered hepatic enzyme activity and set points.34–38 Reduced late-pregnancy protein intake has also been implicated in lower birth weight and placental size in humans.39 Animal models that were protein deprived in utero followed by a high-fat diet after weaning fared the worst, having the most marked glucose intolerance.32,38
The 2 main factors influencing SI in healthy children are fat mass and pubertal status.18 Because all of our subjects were prepubertal, alteration in fat mass was the main variable influencing SI. When controlling for fat mass, prematurely born children were
50% less insulin sensitive compared with control children, indicating a specific isolated reduction in SI in premature children. However, as expected within the premature group, fat mass was inversely correlated with SI. Weight SDS and body mass index SDS were closely correlated in this study (r2 = 0.77), and both can be used as a reasonable proxy for adiposity. Not surprisingly, therefore, SI was lowest in those who were heaviest and who had gained the greatest weight. Interestingly, weight gain from birth until 40 weeks gestation (the first 8–14 weeks of life for this premature cohort) had no impact on later weight SDS, whereas weight gain thereafter was associated with current weight SDS, even between 40 weeks and 1 year of age.
Surprisingly, given the lack of an association with SI, macronutrient differences in intake during the first 3 months were associated with later weight gain. Greater carbohydrate intake in the first month was associated with current weight SDS, and higher carbohydrate intake was directly associated with increased later weight. This result would not have been predicted from animal models induced by manipulations of pregnancy nutrition. However, manipulation of carbohydrate postnatally has been associated with later adult obesity and insulin resistance. Srinivasan et al40 report a model of feeding neonatal rat pups on artificially high carbohydrate milk formula during their suckling period. These pups as adults develop obesity and hyperinsulinemia. It is, thus, feasible that high carbohydrate early in life could have permanent sequelae on growth and glucose regulation. Moreover, it is noteworthy that rodent protein-deficient diets have elevated carbohydrate to maintain isocaloric feeds and, therefore, the effect of a low-protein diet may indeed be to establish a high-carbohydrate diet.41
There is increasing evidence in term infants that early food intake is associated with later increases in weight gain. Early postnatal calorie intake and growth have been associated with an increased risk of later childhood obesity.42–44 The effect of early weight gain or catch-up growth may be even more marked in SGA-born children. This group is not only more likely to develop adult obesity but also more likely to develop the metabolic syndrome.45–47
Recently, a controversial publication by Singhal et al48 has suggested that relative early overnutrition in children born prematurely may result in a persistent reduction in SI. Premature subjects from several previous studies were analyzed between 13 and 16 years, where a preterm formula or breast milk enriched with protein and fat (but not carbohydrate) was compared against either a standard formula or banked breast milk for neonatal nutrition. Fasting elevations in 32/33 split proinsulin were detected in the preterm formula group and considered a marker of reduced SI. However, this study had normal fasting insulin levels between groups suggesting that SI was unchanged between groups and had variable pubertal status making SI difficult to interpret.
Our data suggest that, similar to SGA subjects, there is an underlying isolated, early defect in SI in all of those born prematurely. This defect probably only becomes symptomatic with amplification, and this most commonly occurs with increasing weight and fat mass. SGA subjects who manifest with later disease, such as hypertension or glucose intolerance, tend to be in the heaviest tertile and more insulin resistant.45,49 We observed a similar relationship between weight SDS and SI in our premature cohort. Although early life events, and, in particular, diet, may cause a change in the SI observed, our data suggest that early diet also influences later weight gain. Thus, whereas all of the premature subjects seem to have some reduction in SI, this is accentuated in those who have gained more weight, possibly a consequence of early high-carbohydrate exposure.
Glucose acting through the carbohydrate response element binding protein (ChREBP) has been shown to be a major regulator of hepatocyte triglyceride and glycolytic pathways.50 ChREBP is also present in both adipose tissue and hypothalamus. High-carbohydrate diets in rats cause activation of ChREBP, and persistent upregulation of ChREBP could result in increased fat mass.51 High-carbohydrate diets in rats also decrease uncoupling protein 2 and 3 gene transcription in muscle tissue predisposing to fat accumulation.52 Thus, mechanisms exist that increase fat mass with a high-carbohydrate diet, that if they became permanent, could result in the increased weight SDS observed in our premature subjects.
Caution, however, must be taken in overinterpreting our results. Although the diets of our premature cohort are consistently suboptimal, the macronutrient ratios are related and were regulated to a large degree by the infants health. Thus, a higher carbohydrate intake may reflect other neonatal problems. We have attempted to exclude potential confounders, such as chronic illness, cause for prematurity, and medication, but it is possible that others exist that we have not accounted for. Neonatal nutrition varies both internationally and between centers nationally. It has also changed over the past decade with a greater emphasis on increasing protein intake earlier. Therefore, if an effect of nutrition was the primary etiology for the metabolic and growth differences observed, this may now be different.
| CONCLUSIONS |
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| ACKNOWLEDGMENTS |
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| FOOTNOTES |
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Address correspondence to Paul L. Hofman, FRACP, Liggins Institute, University of Auckland, Private Bag 92019, Auckland, New Zealand. E-mail: p.hofman{at}auckland.ac.nz
The authors have indicated they have no financial relationships relevant to this article to disclose.
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