Original Communication | Published:

High intakes of skimmed milk, but not meat, increase serum IGF-I and IGFBP-3 in eight-year-old boys

European Journal of Clinical Nutrition volume 58, pages 12111216 (2004) | Download Citation

Subjects

Abstract

Objective: To examine whether a high protein intake (PI) from either milk or meat, at a level often seen in late infancy, could increase s-IGF-I and s-IGF-I/s-IGFBP-3 in healthy, prepubertal children. IGF-I levels are positively associated with growth velocity in children and some studies suggest that a high animal PI can stimulate growth. During protein deprivation IGF-I decrease, but it is unknown whether a high PI can increase s-IGF-I in well-nourished children.

Design: In all, 24 8-y-old boys were asked to take either 1.5 l of skimmed milk (n=12) or the same amount of protein as 250 g low fat meat (n=12) daily for 7 days. The remaining diet they could choose freely. At baseline and after 7 days, anthropometrical variables were measured, diet was registered (3-day weighed records), and s-IGF-I and s-IGFBP-3 (RIA) were determined after fast.

Results: PI increased by 61% in the milk group to 4.0 g/kg/day (P<0.0001) and by 54% in the meat group to 3.8 g/kg/day (P=0.001). The high milk intake increased s-IGF-I by 19% (P=0.001) and s-IGF-I/s-IGFBP-3 by 13% (P<0.0001). There were no increases in the meat group.

Conclusions: High intake of milk and not meat, increased concentrations of s-IGF-I and s-IGF-I/s-IGFBP-3 significantly. Compounds in milk and not a high PI as such seem to stimulate IGF-I. This might explain the positive effect of milk intake on growth seen in some studies.

Introduction

The protein intake (PI) in children is considerably higher than in adults, when expressed per kg body weight, and infants and children receive typically two to three times as much as their physiological need (Rolland-Cachera et al, 1999). A PI below the physiological needs results in reduced growth. However, it is unknown to what degree PI and quality have a regulatory effect on growth in well-nourished children with a PI far above their physiological requirements.

IGF-I has a central role in the regulation of growth, which is supported by many studies showing a strong association between IGF-I and body size during infancy and childhood (Rolland-Cachera, 1995). The association between PI and growth is possibly mediated through IGF-I. Dietary depletion has a marked negative effect on IGF-I concentrations (Isley et al, 1983, 1984; Clemmons et al, 1985) in adults, and in malnourished children who have low concentrations of IGF-I, there is a quick and marked increase in IGF-I during rehabilitation (Smith et al, 1989). There is some evidence suggesting that protein restriction will result in decreased IGF-I concentrations in healthy children (Smith et al, 1995). Animal studies suggest that an excessive PI could result in increased IGF-I concentrations (Dardevet et al, 1991; Nap et al, 1993), and in well-nourished adults, there is a positive association between PI and circulating IGF-I (Holmes et al, 2002), but data on children and infants are lacking.

There is a need to understand the regulatory effect of nutrition on IGF-I and thereby growth. A reduced growth velocity is associated with adverse health and development outcomes (Barker, 1992). However, some, but not all, studies have shown a negative effect of a high growth velocity during early life on the risk of some non-communicable diseases later in life (Fall et al, 1995), but the role of early diet in these associations is not known.

Aim

The aim of this intervention study was to examine whether an increase in animal PI could increase concentrations of IGF-I and the molar ratio of IGF-I/IGFBP-3 in healthy, prepubertal children. To explore the role of animal protein quality, we performed two similar intervention studies with milk and meat, respectively.

Subjects and methods

In two separate studies, 24 8-y-old boys were asked to take about 53 g protein daily, 12 boys as 1.5 l of skimmed milk, and 12 other boys as 250 g low fat meat. In addition, they were asked to eat their normal diet ad libitum.

The subjects were recruited in the following manner: Caucasian boys born in October–December 1992 were drawn at random from the Central Personal Register, and were invited to participate in the study. Children with a habitual milk intake of 500 ml/day, who were willing to increase their intake of milk or meat considerably during a week, were eligible for the study. Children with chronic illnesses, and children who suffered from any condition likely to affect their protein metabolism or growth were excluded from the study. From a total of 313 invited subjects, 30 agreed to participate, and 28 were eligible for the study. Of the 15 boys who were the first to agree to participate in the study, 14 were eligible and 12 completed the intervention with milk, and of the remaining 15 boys, 14 were eligible and 12 completed the intervention with meat. Subjects and their parents received oral and written information about the study and the parents gave their written consent. The children were examined at baseline and after 7 days of intervention.

Height was determined to nearest 1 mm using a wall-mounted stadiometer. Weight was measured to the nearest 0.1 kg using an electronic digital scale. Subjects wore only underpants when weighed.

Blood samples were drawn from a venipuncture after an overnight fast. Serum urea nitrogen (SUN) was determined colorimetrically (Vitros 950, Rocheste, New York, USA). Serum IGF-I was determined by radio immunoassay as previously described (Bang et al, 1991). Briefly, serum was extracted by acid–ethanol and cryoprecipitated prior to analysis in order to remove interfering IGF binding proteins. Inter- and intra-assay variations were less than 9 and 6%, respectively. Details regarding determination of IGF-I have been presented previously (Juul et al, 1994). IGFBP-3 was determined by a radio immunoassay as previously described (Blum et al, 1990). Reagents for the assay were obtained from Mediagnost GmbH (Tübingen, Germany). Sensitivity was 0.29 ng/ml (defined as 3 s.d. from the mean of the zero standard). Inter- and intra-assay coefficients of variation were 10.7 and 2.4% (at bound to free ratios of 0.4–0.5), respectively. Details regarding determination of IGFBP-3 have been presented previously (Juul et al, 1995). We used the following equivalents for conversion: 1 ng/ml IGF-I=0.133 nM IGF-I and 1 ng/ml IGFBP-3=0.033 nM IGFBP-3.

The participants (with their parents) kept a 3-day (2 week days and 1 weekend day) weighed food record prior to the intervention (day −3 to 0) and during the last 3 days of the intervention (day 5–7). The importance of maintaining usual dietary intake during the first 3-day period was emphasized to the children and parents. The average daily intakes of energy and nutrients were calculated for each subject by using a national food-composition database (DANKOST 2000, Dansk Catering Center, Herlev, Denmark).

The Ethics Committee of Copenhagen and Frederiksberg approved the study (J. No. KF 01-097/00).

Statistical methods

Statistical analyses were performed with SPSS (version 11.0; SPSS Inc., Chicago, IL, USA). All descriptive results are expressed as means±s.d. Differences in the variables between the milk group and the meat group were determined by two-tailed unpaired Student's t-tests. Differences in the variables between baseline and after 7 days were determined by two-tailed paired Student's t-tests. In order to examine the bivariate relations between the parameters, Pearson's correlation coefficients were calculated. The level of significance was set to 0.05 in all statistical procedures.

Results

Table 1 presents anthropometrical variables at baseline. There were no significant differences between the two groups at baseline, except for age. The children in the milk group gained an average 550 g of weight during the intervention, and this caused a significant increase in the BMI from 17.2 to 17.5 kg/m2 (P=0.015), while there were no changes in the meat group (29.0 and 29.0 kg, respectively).

Table 1: Description of the anthropometrical variables of the milk group and the meat group at baselinea

There were differences in the composition of the habitual diet (baseline values) in the two groups (Table 2). The meat group had a higher proportion of their energy from carbohydrate and a lower proportion from fat than the milk group. The protein energy percentage (PE%) increased significantly in both groups. In the milk group, the increase was 61%, and in the meat group 54%. However, in the milk group, the increased PE% was accompanied by a decrease in fat energy percentage (FE%), whereas in the meat group, the increase in PE% was accompanied by a decrease in carbohydrate energy percentage (CE%). Furthermore, the energy intake increased after 7 days of intervention by 13% in the milk group, but remained at the same level in the meat group.

Table 2: Description of the diet of the milk group and the meat group at baseline and after 7 days of interventiona

In both groups, the increased PI resulted in similar increases in SUN (Table 3), which is considered a valuable indicator of recent PI (Fomon, 1993). In the milk group, IGF-I concentrations increased significantly by 19%, and IGFBP-3 by 8%. However, there was no increase in IGF-I or IGFBP-3 in the meat group (P=0.98 and 0.20, respectively). Also, in the milk group, the molar ratio of IGF-I/IGFBP-3 increased significantly by 13%, whereas the molar ratio of IGF-I/IGFBP-3 did not increase in the meat group (P=0.51).

Table 3: Description of the blood parameters of the milk group and the meat group at baseline and after 7 days of interventiona

Discussion

This is the first intervention study exploring the hypothesis that a high intake of animal protein would increase the concentrations of IGF-I in well-nourished, prepubertal children. As expected, we managed to increase the intake of animal protein considerably, but our results showed that only increased intake of milk and not meat increased circulating IGF-I. Thus, it is more likely that it is constituents of milk rather than animal protein as such that stimulate IGF-I secretion.

We also found a significant increase in IGFBP-3 and the molar ratio of IGF-I/IGFBP-3 in the milk group, whereas there was no increase in the meat group. The stimulatory effect of milk on IGF-I as well as on IGFBP-3 may suggest a direct hepatic effect of certain compounds in milk on their production as IGF-I is produced in hepatocytes, and IGFBP-3 in hepatic Kuppfer cells. Both IGF-I and IGFBP-3 are highly dependent on growth hormone secretion. Therefore, we cannot exclude a direct stimulatory effect of milk on pituitary growth hormone secretion that subsequently could stimulate hepatic release of IGF-I and IGFBP-3 to the circulation.

The biological activity of IGF-I is strongly influenced by specific IGF-binding proteins (IGFBP-1 to -6), of which the major IGFBP-3 carries >90% of circulating IGF-I. The circulating pool of IGF-I, which is primary complexed to the high-molecular-weight IGFBP-3, is inhibited from trans-endothelial transport (Thissen et al, 1994). Thus, our data suggest that the free, biologically active IGF-I is also increased.

Our study was different from other studies addressing the same topic in a number of ways. We used a very high amount of animal protein, because over a short period we wanted to see if there was an effect or not. However, even if the PI during the intervention was quite high, about 4 g/kg body weight, many infants and young children have a PI at this level or higher (Rolland-Cachera et al, 1999). Furthermore, the high milk intake in the milk group, about 2 l/day, equals an intake of 700 ml in a 10 kg infant, when calculated per kg body weight. Many infants have an intake at this level. We used the same amount of animal protein for the intervention in the two groups, which gives us more strength to evaluate the effect of protein quality. Thus, we believe that our study can give information that is helpful in understanding the interaction between diet and IGFs.

The study has some limitations. There were significant differences in fat and carbohydrate content of the diet at baseline between the two groups. However, intakes of protein, meat, and milk were not different at baseline. Also, except for the intervention with meat and milk, the diet was not controlled. This resulted in some minor but significant differences in dietary intake between the two groups. Most important was that the energy intake in the milk group increased by 13% during the intervention, whereas there was only a 3% nonsignificant increase in the meat group. This is possibly due to the fact that satiety is better regulated in relation to solid than to liquid energy providers (DiMeglio & Mattes, 2000). It cannot be excluded that the increased IGF-I concentrations in the milk group were caused by an increased energy intake. However, we do not find it likely that our results are caused by the higher energy intake. In observational studies of adults, IGF-I concentrations are either not associated with energy intake, but strongly with animal PI (Allen et al, 2002), or positively associated with energy, but much weaker than with animal PI (Holmes et al, 2002).

Intervention studies with adults show conflicting results. In two intervention studies with either milk (Heaney et al, 1999) or a protein supplement, composed of 90% milk proteins (Schürch et al, 1998), circulating IGF-I levels were higher in the intervention groups than in the placebo groups. However, supplementation with either four glasses of milk per day or placebo did not change IGF-I in women (Storm et al, 1998). In 12-y-old girls, Cadogan et al found that supplementation with one pint of milk for 18 months tended to increase concentrations of IGF-I in comparison with a control group. The effect was significant after adjustment for pubertal status (Cadogan et al, 1997). Interestingly, the effect on circulating IGF-I increased slowly, reaching significance only after 18 months.

The increased concentrations of IGF-I in the milk group in our study could be caused by substances in milk, such as minerals (Devine et al, 1998). Recently, Giovannucci et al (2003) found that circulating IGF-I and the molar ratio of IGF-I/IGFBP-3 tended to increase with higher intake of several minerals. Since both meat and milk contain large amounts of zinc, it does not seem likely that this could explain our findings. There was no difference between the two groups with respect to the zinc intake at baseline (milk group: 9.5 mg/day, meat group: 9.1 mg/day, P=0.58) nor did the increase in zinc intake differ between the two groups (milk group: 59%, P<0.0001; meat group: 55%, P=0.002). The effect of milk could be caused by calcium. The effect of calcium from milk on IGF-I may differ from the effect of other calcium supplements. Wastney et al (2000) found no differences in IGF-I concentrations in adolescent girls after controlled diets with high (47 mmol/day) and low (21 mmol/day) intakes of calcium as calcium citrate malate, respectively, in a cross-over design.

Even though cow's milk contains IGF-I that is structurally identical to human IGF-I (Juskevich & Guyer, 1990; Daxenberger et al, 1998), and rat studies suggest intact absorption (Xian et al, 1995), it is the general belief that IGF-I will not retain bioactivity when delivered orally because of rapid proteolysis in the upper gut (Juskevich & Guyer, 1990; Daxenberger et al, 1998). Milk is rich in other trophic factors, such as hormones and cytokines, growth factors, and many bioactive peptides (Playford et al, 2000), which could also play a role.

The effect of milk on IGFs as seen in this short-term study is likely to result in an increased growth velocity if continued. Several studies have shown associations between milk intake and growth. Milk has led to a marked catch-up growth of Bundi children (Lampl et al, 1978), American teenagers (Dreizen et al, 1950, 1954), and Scottish school children (Orr, 1928). Also, in a recent study with children aged 3–10 y, milk-avoiders were significantly shorter than the control children (Black et al, 2002).

It is not known if dietary-induced changes in IGF-I levels in children have any long-term effects on health. In adults, low concentrations of IGF-I may be associated with increased rates of cardiovascular disease (Juul et al, 2002), whereas high concentrations of IGF-I are associated with an increased risk of hormonal cancers (Chan et al, 1998; Hankinson et al, 1998; Ma et al, 1999; Giovannucci et al, 2000). The association between milk intake and cancer is not simple, as some studies show a protective effect of milk (Ma et al, 2001).

In summary, high intake of milk and not meat increased concentrations of IGF-I and IGF-I/IGFBP-3 significantly. The biological purpose of milk is to support the newborn during a period of high growth velocity, which is not the case with meat. Therefore, it seems plausible that milk and not meat can stimulate the IGFs.

References

  1. , , , , & (2002): The associations of diet with serum insulin-like growth factor I and its main binding proteins in 292 women meat-eaters, vegetarians, and vegans. Cancer Epidemiol. Biomarkers Prev. 11, 1441–1448.

  2. , , , & (1991): Comparison of acid ethanol extraction and acid gel filtration prior to IGF-I and IGF-II radioimmunoassays: improvement of determinations in acid ethanol extracts by the use of truncated IGF-I as radioligand. Acta Endocrinol. (Copenh.) 124, 620–629.

  3. (1992): Fetal and Infant Origin of Adult Disease. London: British Medical Association.

  4. , , & (2002): Children who avoid drinking cow milk have low dietary calcium intakes and poor bone health. Am. J. Clin. Nutr. 76, 675–680.

  5. , , , , & (1990): A specific radioimmunoassay for the growth hormone (GH)-dependent somatomedin-binding protein: its use for diagnosis of GH deficiency. J. Clin. Endocrinol. Metab. 70, 1292–1298.

  6. , , & (1997): Milk intake and bone mineral acquisition in adolescent girls: randomised, controlled intervention trial. Br. Med. J. 315, 1255–1260.

  7. , , , , , , & (1998): Plasma insulin-like growth factor-I and prostate cancer risk: a prospective study. Science 279, 563–566.

  8. , & (1985): Supplemental essential amino acids augment the somatomedin-C/insulin- like growth factor I response to refeeding after fasting. Metabolism 34, 391–395.

  9. , , , & (1991): Influence of low- and high-protein diets on insulin and insulin-like growth factor-1 binding to skeletal muscle and liver in the growing rat. Br. J. Nutr. 65, 47–60.

  10. , & (1998): Increased milk levels of insulin-like growth factor 1 (IGF-1) for the identification of bovine somatotropin (bST) treated cows. Analyst 123, 2429–2435.

  11. , , , & (1998): Effects of zinc and other nutritional factors on insulin-like growth factor I and insulin-like growth factor binding proteins in postmenopausal women. Am. J. Clin. Nutr. 68, 200–206.

  12. & (2000): Liquid versus solid carbohydrate: effects on food intake and body weight. Int. J. Obes. Relat. Metab. Disord. 24, 794–800.

  13. , , & (1950): The effect of milk supplements on the growth of children with nutritive failure. 2. Height and weight changes. Growth 14, 189–211.

  14. , , , & (1954): Maturation of bone centers in hand and wrist of children with chronic nutritive failure. Effect of dietary supplements of reconstituted milk solids. Am. J. Dis. Child. 87, 429–439.

  15. , , , & (1995): Weight in infancy and prevalence of coronary heart disease in adult life. BMJ 310, 17–19.

  16. (1993): Protein, In Nutrition of Normal Infants. ed. SJ Fomon, pp 121–146. St. Louis: Mosby.

  17. , , , , , , , & (2000): A prospective study of plasma insulin-like growth factor-1 and binding protein-3 and risk of colorectal neoplasia in women. Cancer Epidemiol. Biomarkers Prev. 9, 345–349.

  18. , , , , , & (2003): Nutritional predictors of insulin-like growth factor I and their relationships to cancer in men. Cancer Epidemiol. Biomarkers Prev. 12, 84–89.

  19. , , , , , , , & (1998): Circulating concentrations of insulin-like growth factor-I and risk of breast cancer. Lancet 351, 1393–1396.

  20. , , , , , , & (1999): Dietary changes favorably affect bone remodeling in older adults. J. Am. Diet. Assoc. 99, 1228–1233.

  21. , , & (2002): Dietary correlates of plasma insulin-like growth factor I and insulin-like growth factor binding protein 3 concentrations. Cancer Epidemiol. Biomarkers Prev. 11, 852–861.

  22. , & (1983): Dietary components that regulate serum somatomedin-C concentrations in humans. J. Clin. Invest. 71, 175–182.

  23. , & (1984): Changes in plasma somatomedin-C in response to ingestion of diets with variable protein and energy content. J. Parenter. Enteral. Nutr. 8, 407–411.

  24. & (1990): Bovine growth hormone: human food safety evaluation. Science 249, 875–884.

  25. , , , , , , , & (1994): Serum insulin-like growth factor-I in 1030 healthy children, adolescents, and adults: relation to age, sex, stage of puberty, testicular size, and body mass index. J. Clin. Endocrinol. Metab. 78, 744–752.

  26. , , , , , , & (1995): Serum levels of insulin-like growth factor (IGF)-binding protein-3 (IGFBP-3) in healthy infants, children, and adolescents: the relation to IGF-I, IGF-II, IGFBP-1, IGFBP-2, age, sex, body mass index, and pubertal maturation. J. Clin. Endocrinol. Metab. 80, 2534–2542.

  27. , , , & (2002): Low serum insulin-like growth factor I is associated with increased risk of ischemic heart disease: a population-based case–control study. Circulation 106, 939–944.

  28. , & (1978): The effects of protein supplementation on the growth and skeletal maturation of New Guinean school children. Ann. Hum. Biol. 5, 219–227.

  29. , , , , , & (1999): Prospective study of colorectal cancer risk in men and plasma levels of insulin-like growth factor (IGF)-I and IGF-binding protein-3. J. Natl. Cancer Inst. 91, 620–625.

  30. , , , , , & (2001): Milk intake, circulating levels of insulin-like growth factor-I, and risk of colorectal cancer in men. J. Natl. Cancer Inst. 93, 1330–1336.

  31. , & (1993): Age-related plasma concentrations of growth hormone (GH) and insulin-like growth factor-I (IGF-I) in Great Dane pups fed different dietary levels of protein. Domest. Anim. Endocrinol. 10, 237–247.

  32. (1928): Milk consumption and the growth of school-children. Lancet i, 202–203.

  33. , & (2000): Colostrum and milk-derived peptide growth factors for the treatment of gastrointestinal disorders. Am. J. Clin. Nutr. 72, 5–14.

  34. (1995): Prediction of adult body composition from infant and child measurements, In Body Composition Techniques in Health and Disease. eds. PSW Davies & TJ Cole, pp 100–145. Cambridge: Cambridge University Press.

  35. , & (1999): Increasing prevalence of obesity among 18-year-old males in Sweden: evidence for early determinants. Acta Paediatr. 88, 365–367.

  36. , , , , & (1998): Protein supplements increase serum insulin-like growth factor-I levels and attenuate proximal femur bone loss in patients with recent hip fracture. A randomized, double-blind, placebo-controlled trial. Ann. Intern. Med. 128, 801–809.

  37. , & (1989): Plasma somatomedin-C in Nigerian malnourished children fed a vegetable protein rehabilitation diet. Eur. J. Clin. Nutr. 43, 705–713.

  38. , & (1995): Effects of caloric or protein restriction on insulin-like growth factor-I (IGF-I) and IGF-binding proteins in children and adults. J. Clin. Endocrinol. Metab. 80, 443–449.

  39. , , , , , , , , , & (1998): Calcium supplementation prevents seasonal bone loss and changes in biochemical markers of bone turnover in elderly New England women: a randomized placebo-controlled trial. J. Clin. Endocrinol. Metab. 83, 3817–3825.

  40. , & (1994): Nutritional regulation of the insulin-like growth factors. Endocr. Rev. 15, 80–101.

  41. , , , , , & (2000): Changes in calcium kinetics in adolescent girls induced by high calcium intake. J. Clin. Endocrinol. Metab. 85, 4470–4475.

  42. , & (1995): Degradation of IGF-I in the adult rat gastrointestinal tract is limited by a specific antiserum or the dietary protein casein. J. Endocrinol. 146, 215–225.

Download references

Acknowledgements

The idea for this study came from a discussion between the authors. No author had a financial or personal conflict of interest related to this research or its source of funding.

Author information

Affiliations

  1. Department of Human Nutrition and Centre for Advanced Food Studies, The Royal Veterinary and Agricultural University, Frederiksberg, Denmark

    • C Hoppe
    • , C Mølgaard
    •  & K F Michaelsen
  2. Department of Growth and Reproduction, Rigshospitalet, Copenhagen, Denmark

    • A Juul

Authors

  1. Search for C Hoppe in:

  2. Search for C Mølgaard in:

  3. Search for A Juul in:

  4. Search for K F Michaelsen in:

Contributions

Guarantor: C Hoppe.

Contributors: CH conducted the statistical analyses and prepared the first draft of the manuscript in collaboration with CM and KFM. AJ was responsible for all IGF-I and IGFBP-3 measurements. All contributors participated in interpreting the results and were involved in preparing the final draft of the manuscript.

Corresponding author

Correspondence to C Hoppe.

About this article

Publication history

Received

Revised

Accepted

Published

DOI

https://doi.org/10.1038/sj.ejcn.1601948

Further reading