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Original Contribution |

Timing and Tempo of First-Year Rapid Growth in Relation to Cardiovascular and Metabolic Risk Profile in Early Adulthood FREE

Ralph W. J. Leunissen, MD; Gerthe F. Kerkhof, MSc; Theo Stijnen, MSc, PhD; Anita Hokken-Koelega, MD, PhD
[+] Author Affiliations

Author Affiliations: Department of Pediatrics, Subdivision of Endocrinology, Erasmus Medical Center/Sophia Children's Hospital, Rotterdam, the Netherlands (Drs Leunissen and Hokken-Koelega and Ms Kerkhof); and Department of Epidemiology and Biostatistics, Leids University Medical Centre, Leiden, the Netherlands (Dr Stijnen).


JAMA. 2009;301(21):2234-2242. doi:10.1001/jama.2009.761.
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Published online

Context Growth during infancy appears to be an important determinant of cardiovascular disease and type 2 diabetes later in life.

Objectives To specify which period in the first year of life is related to determinants of cardiovascular disease and type 2 diabetes in early adulthood and to investigate the association between tempo of first-year weight gain (>0.67 SDs) and these determinants.

Design, Setting, and Participants Observational study using longitudinal data collected in the Programming Factors for Growth and Metabolism (PROGRAM) study of 217 healthy participants, aged 18 to 24 years, including a relatively large sample of participants born small for gestational age and participants with short stature, performed at a medical center in the Netherlands between August 2004 and September 2007. The association of cardiovascular disease and type 2 diabetes with tempo of weight gain was assessed in a subgroup of 87 participants.

Main Outcome Measures Associations between periods of first-year growth and tempo of weight gain and determinants of cardiovascular disease and type 2 diabetes in early adulthood.

Results Weight gain in the first 3 months of life was inversely associated with insulin sensitivity (β, −0.223; 95% confidence interval [CI], −0.386 to −0.060) and serum high-density lipoprotein cholesterol level (β, −0.053; 95% CI, −0.090 to −0.016) and positively associated with waist circumference (β, 1.437; 95% CI, 0.066 to 2.808), acute insulin response (β, 0.210; 95% CI, 0.024 to 0.395), ratio of total cholesterol to high-density lipoprotein cholesterol (β, 0.052; 95% CI, 0.010 to 0.094), and level of triglycerides (β, 0.066; 95% CI, 0.003 to 0.129) in early adulthood. Rapid weight gain during the first 3 months of life resulted in a higher percentage of body fat, more central adiposity, and reduced insulin sensitivity in early adulthood than when slower weight gain occurred during the entire first year.

Conclusion Rapid weight gain in the first 3 months of life is associated with several determinants of cardiovascular disease and type 2 diabetes in early adulthood.

Figures in this Article

Low birth weight has been associated with cardiovascular disease and type 2 diabetes later in life,1 but other studies showed that growth patterns in infancy and childhood might have more effect.2,3 Catch-up growth in the first year of life is associated with determinants of cardiovascular disease and type 2 diabetes,46 while other studies showed that poor growth in early life and catch-up growth after age 2 years is related to an increased risk to develop cardiovascular events later in life.3,7 Data on the relationship between growth in early life and a broad cardiovascular and type 2 diabetes risk profile are scarce. In addition, the relationship between the tempo of early life growth and cardiovascular and metabolic risk in early adulthood is hardly investigated.

We conducted an observational study using longitudinal data collected in the Programming Factors for Growth and Metabolism (PROGRAM) study of 217 healthy participants, aged 18 to 24 years, to investigate which period in the first year of life is associated with determinants for cardiovascular disease and type 2 diabetes in early adulthood. The first year of life was divided into 4 periods of 3 months and changes in growth during these periods were related to the outcome measures of percentage of body fat, body mass index (calculated as weight in kilograms divided by height in meters squared), fat distribution, insulin sensitivity, lipid levels, and systolic blood pressure, which were measured between August 2004 and September 2007 at Erasmus Medical Center (Rotterdam, the Netherlands). In a subgroup of 87 young adults who experienced rapid weight gain during the first year of life (SD >0.67), we additionally investigated whether tempo of weight gain was associated with these determinants of metabolic and cardiovascular diseases later in life.

Study Participants

The total study population consisted of 323 healthy young adults. Participants, who were registered in several hospitals because of their small size at birth (birth length <−2 SDs)8 and normal stature as young adults (n = 92) or normal size at birth and short stature as young adults (adult height <−2 SDs)9 (n = 60), were randomly selected for this study. In addition, 34 young adults who were small at birth and had short stature were included. Healthy young adults (neither small at birth nor having short adult stature) from schools with different educational levels also were randomly asked to participate (n = 137). This design was purposely chosen because it increased the contrast in growth patterns and thus increased the statistical power to find a relationship between early growth patterns and determinants of cardiovascular disease and type 2 diabetes.

Figure 1 shows how many young adults were invited and how many were included in the study. The participation rate was 84.1%. Only whites born singleton at 36 weeks of gestation or longer were invited to participate to exclude a potential influence of ethnicity, parity, and prematurity. All included young adults had an uncomplicated neonatal period without severe asphyxia (defined as an Apgar score <3 after 5 minutes) and did not have sepsis or long-term complications of respiratory ventilation, such as bronchopulmonary dysplasia.

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Figure 1. Derivation of Sample Into Subgroups
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Individuals were excluded if they (1) had any serious condition or disorder, (2) were receiving any treatment known to interfere with growth (eg, growth hormone deficiency, severe chronic illness, emotional deprivation, growth hormone treatment, treatment with glucocorticosteriods, radiotherapy), or (3) had endocrine or metabolic disorders, chromosomal defects, syndromes, or serious dysmorphic symptoms suggestive of a yet unknown syndrome. Birth data and childhood growth data were obtained from hospital records, primary health care center records, and general practitioner records.

The medical ethics committee of Erasmus Medical Center approved the study. Written informed consent was obtained from all participants.

Of the 323 study participants, data on first-year growth were available for 217 young adults. There were no significant differences in clinical characteristics with regard to birth length, birth weight, adult height, and adult weight between the young adults with first-year growth data and the ones without it. Of the 217 young adults with first-year growth data, 84 were small at birth (of whom 9 had short adult stature) and 129 had a normal size at birth (of whom 41 had short adult stature). Weight and height at the ages of 3, 6, 9, and 12 months had been prospectively measured at primary health care centers or hospitals. These data were collected during the study period (August 2004-September 2007) from the records of the health care centers and hospitals. Some centers and hospitals did not store records for 25 years, therefore data were missing for 106 young adults.

Measurements

Participants were invited to visit Erasmus Medical Center and were reimbursed for travel expenses. Prior to the taking of measurements, participants fasted for 12 hours and abstained from smoking and drinking alcohol for 16 hours. All anthropometric measurements were performed twice and the mean value was used for the analysis.

Lean body mass and fat mass were measured on 1 dual-energy x-ray absorptiometry machine (Lunar Prodigy, GE Healthcare, Chalfont St Giles, England). Insulin sensitivity index, acute insulin response to glucose, and the disposition index (the product of insulin sensitivity and acute insulin response indicating the degree of glucose homeostasis) were determined using the Bergman minimal model (MinMOD Millennium version 6.01, MinMOD Inc, Los Angeles, California), which calculated the paired glucose and insulin data obtained by frequent measurements during an intravenous glucose tolerance test1012 with tolbutamide.13 Blood pressure was measured after 10 minutes at rest, in the sitting position, using the nondominant arm with an automatic device (Accutorr Plus, Datascope Corp, Montvale, New Jersey) every 5 minutes for 1 hour and the mean value of these 13 measurements was taken to reflect resting blood pressure.

Laboratory Methods

Blood samples were drawn to determine serum lipid levels. The assays have been previously described in detail.14,15 Briefly, plasma glucose levels were determined on a VITROS analyzer 750 (Ortho-Clinical Diagnostics, Johnson & Johnson Company, Beerse, Belgium) and plasma insulin levels were measured using an immunoradiometric assay (Medgenix Diagnostics, Fleunes, Belgium). Total cholesterol level and total glucose level were measured using the CHOD-PAP and the GPO-PAP reagent kit (Roche Diagnostics, Mannheim, Germany). High-density lipoprotein (HDL) cholesterol level was measured using a homogeneous enzymatic colorimetric assay (Roche Diagnostics). Low-density lipoprotein (LDL) cholesterol level was calculated using the Friedewald formula: LDL cholesterol level in mmol/L = total cholesterol level − HDL cholesterol level − 0.45 × level of triglycerides. Apolipoprotein A-I and apolipoprotein B were determined by rate of nephelometry on the Image Immunochemistry System (Beckman Coulter, Mijdrecht, the Netherlands) according to the manufacturer's instructions.

Statistical Analysis

The SD scores for birth length, birth weight, and first-year growth were calculated to correct for gestational age and sex.8,9 The SD scores for adult height and adult weight also were calculated to correct for sex and age.9 All SD scores were calculated using the growth analyzer program (http://www.growthanalyser.org).

Multiple linear regression analyses were performed to investigate the association between weight gain per each 3 months in the first year of life and several determinants in the 217 young adults. The four 3-month periods were analyzed separately from each other. Adjustments were made for gestational age, sex, age, and socioeconomic status. To investigate the association between weight gain and the outcome variables independently of height, adjustments were made for height growth during the same 3-month period. A sample size of 217 study participants achieved 80% power to detect an R2 of 0.03 attributed to 1 independent variable using an F test with an α level of .05. The variables tested were adjusted for an additional 5 independent variables (gestational age, sex, age, socioeconomic status, and height growth in the same 3-month period). The goodness of fit of the models was assessed by studying the behavior of the residuals and by looking for outliers. When residuals deviated from homogeneity, outcome variables were log transformed. This applied to body mass index, insulin sensitivity, acute insulin response, disposition index, total cholesterol level, LDL cholesterol level, HDL cholesterol level, ratio of total cholesterol to HDL cholesterol, apolipoprotein B, ratio of apolipoprotein B to apolipoprotein A-I, and level of triglycerides.

Additionally, the total study group was divided into 2 groups, irrespective of birth length or birth weight, one with rapid weight gain during the first year of life and one without it (Figure 1). Rapid weight gain was defined as an SD score of more than 0.67 of weight gain in the first year of life because SD scores of 0.67 represent the width of each percentile band on standard growth charts (second to ninth percentile, ninth to 25th percentile, etc).16 Of the group with first-year rapid weight gain, 2 subgroups were formed based on rapid (SD ≥0.5) or slow (SD <0.5) weight gain during the first 3 months. A cutoff SD score of 0.5 was chosen because clinicians can easily detect an SD score change of 0.5 on a growth chart.

Differences in clinical characteristics between the 2 subgroups were determined by an independent t test. Differences in determinants of cardiovascular disease and type 2 diabetes between these 2 subgroups were determined by regression analyses, with corrections for first-year height growth to investigate the association between weight gain and the variables independently of height growth. Additional adjustments were made for gestational age, sex, age, and socioeconomic status. Eighty-seven young adults fulfilled the inclusion criteria for the subgroup analyses. According to a power analysis performed prior to the study (α level of .05 and a power level of 80%), at least 72 participants should be included in the regression analyses to enable detection of an R2 change of 0.10. The variables tested were adjusted for an additional 5 independent variables (gestational age, sex, age, socioeconomic status, and height growth in the first year of life). The SPSS statistical package version 15.0 (SPSS Inc, Chicago, Illinois) was used for the analyses. All statistical tests were performed 2-sided and results were regarded as statistically significant if the P value was less than .05.

The clinical characteristics of the study population are shown in Table 1. The mean (SD) age in early adulthood was 20.8 (1.67) years.

Table Graphic Jump LocationTable 1. Clinical Characteristics of the Study Populationa
Weight Gain in the First Year of Life and Determinants of Cardiovascular Disease and Type 2 Diabetes in Early Adulthood

Associations between first-year weight gain and several determinants of cardiovascular disease and type 2 diabetes in early adulthood are shown in Table 2. Adjustments were made for gestational age, sex, age, socioeconomic status, and SD score for height growth in the similar 3-month period. Height growth was adjusted for to investigate the association between weight gain and the outcome variables independently of height growth. Weight gain in the first 3 months of life had an inverse association with insulin sensitivity and HDL cholesterol levels in early adulthood. Positive associations were found between weight gain in the first 3 months of life and waist circumference, acute insulin response, ratio of total cholesterol to HDL cholesterol, and levels of triglycerides in early adulthood. Weight gain from 3 to 6 months was only positively related to acute insulin response. The other 3-month periods in the first year of life showed no significant associations. The proportion of explained variance of the models was 3.5% to 43%. The same analyses were performed without adjustment for height growth in the 3-month period, which showed similar results.

Table Graphic Jump LocationTable 2. Associations Between Standard Deviations in Weight Gain in the First Year of Life and Determinants of Cardiovascular Disease and Type 2 Diabetes in Early Adulthooda

To investigate whether the associations between weight gain in the first 3 months and determinants of cardiovascular disease and type 2 diabetes were explained by fat mass in early adulthood, an additional adjustment was performed for percentage of body fat. The associations between weight gain in the first 3 months and insulin sensitivity (β, −0.163; 95% confidence interval [CI], −0.312 to −0.014), HDL cholesterol level (β, −0.053; 95% CI, −0.091 to −0.014), and ratio of total cholesterol to HDL cholesterol (β, 0.054; 95% CI, 0.011 to 0.096) remained significant. The associations with waist circumference (β, 0.947; 95% CI, −0.015 to 1.909), acute insulin response (β, 0.154; 95% CI, −0.023 to 0.330), and level of triglycerides (β, 0.057; 95% CI, −0.006 to 0.119) became nonsignificant.

The study population consisted of a relatively large sample of young adults born small for gestational age and young adults with short adult stature. Therefore, birth length and adult height also were adjusted for to eliminate the effect of selection bias. Similar results were found because weight gain in the first 3 months also was inversely related to insulin sensitivity (β, −0.216; 95% CI, −0.381 to −0.051) and HDL cholesterol level (β, −0.056; 95% CI, −0.093 to −0.018), and positively associated with ratio of total cholesterol to HDL cholesterol (β, 0.053; 95% CI, 0.011 to 0.095), and acute insulin response (β, 0.185; 95% CI, 0.002 to 0.368).

Whether differences in body mass index per 3 months were associated with the determinants of cardiovascular disease and type 2 diabetes in early adulthood also was investigated. These associations were similar as the associations between first-year weight gain and several determinants in early adulthood.

Tempo of Weight Gain in the First Year of Life and Determinants of Cardiovascular Disease and Type 2 Diabetes in Early Adulthood

To assess if tempo of weight gain was associated with determinants of cardiovascular disease and type 2 diabetes in early adulthood, subgroups were formed based on rapid or slow weight gain in the first 3 months of life. Of all young adults with a clinically relevant weight gain of at least 0.67 SDs in the first year of life, some had a weight gain of more than 0.5 SDs in the first 3 months (rapid growth, n = 65), while others had a weight gain in the first 3 months of less than 0.5 SDs (slow growth, n = 22). The clinical characteristics of these 2 subgroups are shown in Table 3. The SD scores for birth length and birth weight were not significantly different between the subgroups. First-year growth patterns and the SD scores for adult height, weight, and weight minus height are shown in Figure 2. Both subgroups attained a similar adult height SD score. However, the rapid growth group attained a nonsignificantly higher adult weight SD score than the slow growth group (mean difference, 0.50; 95% CI, −0.05 to 1.06; Figure 3). When weight for height was expressed as weight SD minus height SD, the rapid growth group had more weight gain than height growth in the first 3 months, while the slow growth group had more height growth than weight gain (mean difference, 0.94; 95% CI, 0.38 to 1.50).

Table Graphic Jump LocationTable 3. Clinical Characteristics and Determinants of Cardiovascular Disease and Type 2 Diabetes of Young Adults With Rapid vs Slow First-Year Growtha
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Figure 2. Height and Weight During Early Adulthood Relative to Height and Weight in the First Year of Life
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The comparison is between young adults with slow weight gain vs young adults with rapid weight gain during the first 3 months of life. Values are expressed as mean (SEM).

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Figure 3. Height, Weight, and Weight Minus Height at 21 Years
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Values are expressed as mean (SEM).

The rapid growth group had a significantly higher percentage of body fat (β, 6.00; 95% CI, 1.77 to 10.24), a greater waist circumference (β, 6.19; 95% CI, 0.67 to 11.71), a higher ratio of trunk fat to total fat (β, 0.029; 95% CI, 0.001 to 0.056), and a reduced insulin sensitivity (β, −0.69; 95% CI, −0.02 to 1.38) in early adulthood than the slow growth group after adjustment for gestational age, sex, age, socioeconomic status, and height growth in the first year of life (Table 3). After adjustment for adult percentage of body fat, the difference in waist circumference (β, 0.96; 95% CI, −3.27 to 5.19), fat distribution (β, 0.014; 95% CI, −0.013 to 0.041), and insulin sensitivity (β, −0.297; 95% CI, −0.954 to 0.360) between the 2 subgroups disappeared. This indicates that percentage of body fat explained the differences in these variables between the 2 subgroups. Adjustment for birth weight SD and birth length SD did not change the results.

Our study shows that increased weight gain relative to height growth in the first 3 months of life is associated with reduced insulin sensitivity and serum HDL cholesterol level, and an increased waist circumference, acute insulin response, ratio of total cholesterol to HDL cholesterol, and serum level of triglycerides in early adulthood. These are all important determinants of cardiovascular disease and type 2 diabetes later in life. Even after adjustment for adult percentage of body fat, the associations with insulin sensitivity, HDL cholesterol level, and ratio of total cholesterol to HDL cholesterol remained significant. A subgroup analysis showed that of all young adults with first-year rapid weight gain (>0.67 SDs), those with rapid weight gain in the first 3 months of life had a higher percentage of body fat, more central adiposity, and reduced insulin sensitivity in early adulthood than those with slower growth. Percentage of body fat explained the differences in central adiposity and insulin sensitivity in early adulthood between the 2 subgroups.

Low birth weight has previously been associated with an increased risk of cardiovascular disease and type 2 diabetes later in life.1719 Although this was initially thought to be due to an unfavorable fetal environment,1 other studies reported that postnatal catch-up growth influenced the risk as well.46,2022 Our study shows that increased weight gain in the first 3 months of life is significantly associated with several determinants for cardiovascular disease and type 2 diabetes in early adulthood. Of all young adults born small for gestational age, 90% experience catch-up growth in the first 2 years of life.23 We previously showed that young adults with catch-up growth between birth and adulthood had a higher risk for cardiovascular disease or type 2 diabetes, while young adults born small for gestational age without catch-up growth did not have an increased risk.14,15,24 This indicates that having a low birth weight for gestational age is not directly related with an unfavorable cardiovascular and metabolic profile, but increased weight gain during early childhood is.

To investigate whether tempo of weight gain is associated with cardiovascular or metabolic determinants, we performed a subgroup analysis based on rapid or slow weight gain in the first 3 months of life for all young adults with first-year rapid weight gain. Of the participants who showed postnatal weight gain in the first year of life, those with rapid weight gain during the first 3 months had a higher percentage of body fat, more central adiposity, and reduced insulin sensitivity in early adulthood, while both subgroups reached a similar adult height. The rapid weight gain group was fatter in early adulthood and this explained the difference in central adiposity and insulin sensitivity. Therefore, it is important to investigate which factors determine weight gain in early life because this might lead to intervention strategies to prevent cardiovascular events later in life.

Currently it is unclear whether epigenetic factors are involved. Early nutrition might be a major factor. Generally, nutrient-enriched diets lead to rapid weight gain in early life, and subsequently have adverse effects on cardiovascular risk factors later in life.4,25,26 Also, formula-fed infants grow at a faster rate than breast-fed infants and have a higher risk of being overweight later in life.27,28 Unfortunately, our study did not have nutritional data to investigate the relationship between early nutrition, growth in infancy, and cardiovascular determinants later in life. Nevertheless, our findings suggest that the use of nutrient-enriched formulas, which induce rapid weight gain in early life, might increase the risk for cardiovascular disease and type 2 diabetes later in life.25 Nutritional intervention, like initiating breastfeeding during the first 3 months of life, might decrease the prevalence of cardiovascular disease and type 2 diabetes.

In this study, the association between early weight gain and several determinants was investigated, but other periods in life might be important as well. As shown in reports of the Helsinki Birth Cohort Study, young adults with slow weight gain from birth to 2 years followed by catch-up in weight during childhood also had an increased risk for the development of cardiovascular disease and type 2 diabetes.3,29,30 Similar results have been found in a cohort study in India.31 These study participants experienced growth retardation in weight in early life before they showed catch-up growth in weight during childhood. This might indicate that excessive weight gain after a period of growth retardation, either intrauterine or in early life, increases the risk for the development of cardiovascular disease and type 2 diabetes later in life. Our study suggests that the tempo of weight gain might be more relevant than the timing. This merits further study of factors influencing tempo of growth.

Our study population consisted of a relatively large sample of young adults born small for gestational age. We have deliberately chosen this design because the wider range of birth size created greater contrast in the study population, which contributed to a better statistical model in which relationships between various factors (first-year growth and determinants of cardiovascular disease and type 2 diabetes) could be detected with more statistical power. To eliminate potential selection bias, adjustments were made for the selection criteria of birth length and adult height but these results were similar to the unadjusted findings.

Nevertheless, the findings in this study need to be confirmed in population-based cohort studies with standardized early life measurements. Such studies also should investigate associations with parental factors, such as inheritance of cardiovascular disease, and maternal health factors during pregnancy, because these factors were not available in this study and might provide further insight into which factors are associated with birth size, first-year growth, and the increased risk for developing cardiovascular disease and type 2 diabetes later in life. This study assessed an extensive set of determinants of cardiovascular disease and type 2 diabetes later in life, but this also led to a relatively high number of comparisons. Therefore, in 5% of the comparisons, false-positive associations might be found (type I error). However, significant associations were found in more than 5% of the comparisons.

In conclusion, rapid weight gain in the first 3 months of life is associated with an unfavorable cardiovascular and metabolic profile in early adulthood. Furthermore, rapid weight gain in the first 3 months of life is more detrimental than slow weight gain. More studies are required to investigate which factors determine rapid weight gain in early infancy because those results might lead to interventions that could decrease the risk for development of cardiovascular disease and type 2 diabetes later in life.

Corresponding Author: Ralph W. J. Leunissen, MD, Erasmus Medical Center/Sophia Children's Hospital, Room Sb 2670, 60 Molewaterplein Dr, 3015 GJ Rotterdam, the Netherlands (r.leunissen@erasmusmc.nl).

Author Contributions: Dr Hokken-Koelega had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Leunissen, Stijnen, Hokken-Koelega.

Acquisition of data: Leunissen, Kerkhof, Stijnen.

Analysis and interpretation of data: Leunissen, Kerkhof, Stijnen, Hokken-Koelega.

Drafting of the manuscript: Leunissen, Stijnen.

Critical revision of the manuscript for important intellectual content: Leunissen, Kerkhof, Stijnen, Hokken-Koelega.

Statistical analysis: Leunissen, Kerkhof, Stijnen, Hokken-Koelega.

Obtained funding: Stijnen, Hokken-Koelega.

Administrative, technical, or material support: Stijnen, Hokken-Koelega.

Study supervision: Stijnen, Hokken-Koelega.

Financial Disclosures: None reported.

Funding/Support: The Programming Factors for Growth and Metabolism (PROGRAM) study was financially supported by Netherlands Organization for Scientific Research grant 015 000 088, by grants from Revolving Fund 2001 and Vereniging Trustfonds awarded to Erasmus University, Rotterdam, the Netherlands, and by a grant from the Jan Dekkerstichting/Dr Ludgardine Bouwmanstiching and the Stichting De Drie Lichten, the Netherlands.

Role of the Sponsors: The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; and in the preparation, review, and approval of the manuscript.

Additional Contributions: We thank J. Dunk, I. Andriga, and I. van Slobbe (Department of Pediatric Endocrinology, Erasmus Medical Center/Sophia Children's Hospital, Rotterdam, the Netherlands), for their technical assistance and support with data collection and J. Sluimer (Department of Nuclear Medicine, Erasmus Medical Center/Sophia Children's Hospital) for checking the dual-energy x-ray absorptiometry results. We also thank Y. B. de Rijke, PhD, and A. W. van Toorenenbergen, PhD (Department of Clinical Chemistry, Erasmus Medical Center/Sophia Children's Hospital), for analyzing the lipid levels. None of the persons mentioned here received any compensation.

Barker DJ, Gluckman PD, Godfrey KM, Harding JE, Owens JA, Robinson JS. Fetal nutrition and cardiovascular disease in adult life.  Lancet. 1993;341(8850):938-941
PubMed   |  Link to Article
Baker JL, Olsen LW, Sorensen TI. Childhood body-mass index and the risk of coronary heart disease in adulthood.  N Engl J Med. 2007;357(23):2329-2337
PubMed   |  Link to Article
Barker DJ, Osmond C, Forsen TJ, Kajantie E, Eriksson JG. Trajectories of growth among children who have coronary events as adults.  N Engl J Med. 2005;353(17):1802-1809
PubMed   |  Link to Article
Singhal A, Cole TJ, Fewtrell M,  et al.  Promotion of faster weight gain in infants born small for gestational age: is there an adverse effect on later blood pressure?  Circulation. 2007;115(2):213-220
PubMed   |  Link to Article
Chomtho S, Wells JC, Williams JE, Davies PS, Lucas A, Fewtrell MS. Infant growth and later body composition: evidence from the 4-component model.  Am J Clin Nutr. 2008;87(6):1776-1784
PubMed
Ekelund U, Ong KK, Linne Y,  et al.  Association of weight gain in infancy and early childhood with metabolic risk in young adults.  J Clin Endocrinol Metab. 2007;92(1):98-103
PubMed   |  Link to Article
Eriksson JG, Forsen T, Tuomilehto J, Winter PD, Osmond C, Barker DJ. Catch-up growth in childhood and death from coronary heart disease: longitudinal study.  BMJ. 1999;318(7181):427-431
PubMed   |  Link to Article
Usher R, McLean F. Intrauterine growth of live-born Caucasian infants at sea level: standards obtained from measurements in 7 dimensions of infants born between 25 and 44 weeks of gestation.  J Pediatr. 1969;74(6):901-910
PubMed   |  Link to Article
Fredriks AM, van Buuren S, Burgmeijer RJ,  et al.  Continuing positive secular growth change in the Netherlands 1955-1997.  Pediatr Res. 2000;47(3):316-323
PubMed   |  Link to Article
Bergman RN, Phillips LS, Cobelli C. Physiologic evaluation of factors controlling glucose tolerance in man: measurement of insulin sensitivity and beta-cell glucose sensitivity from the response to intravenous glucose.  J Clin Invest. 1981;68(6):1456-1467
PubMed   |  Link to Article
Pacini G, Bergman RN. MINMOD: a computer program to calculate insulin sensitivity and pancreatic responsivity from the frequently sampled intravenous glucose tolerance test.  Comput Methods Programs Biomed. 1986;23(2):113-122
PubMed   |  Link to Article
Boston RC, Stefanovski D, Moate PJ, Sumner AE, Watanabe RM, Bergman RN. MINMOD Millennium: a computer program to calculate glucose effectiveness and insulin sensitivity from the frequently sampled intravenous glucose tolerance test.  Diabetes Technol Ther. 2003;5(6):1003-1015
PubMed   |  Link to Article
Bergman RN. Lilly lecture 1989: toward physiological understanding of glucose tolerance: minimal-model approach.  Diabetes. 1989;38(12):1512-1527
PubMed   |  Link to Article
Leunissen RW, Kerkhof GF, Stijnen T, Hokken-Koelega AC. Fat mass and apolipoprotein E genotype influence serum lipoprotein levels in early adulthood, whereas birth size does not.  J Clin Endocrinol Metab. 2008;93(11):4307-4314
PubMed   |  Link to Article
Leunissen RW, Oosterbeek P, Hol LK, Hellingman AA, Stijnen T, Hokken-Koelega AC. Fat mass accumulation during childhood determines insulin sensitivity in early adulthood.  J Clin Endocrinol Metab. 2008;93(2):445-451
PubMed   |  Link to Article
Ong KK, Ahmed ML, Emmett PM, Preece MA, Dunger DB. Association between postnatal catch-up growth and obesity in childhood: prospective cohort study.  BMJ. 2000;320(7240):967-971
PubMed   |  Link to Article
Barker DJ, Winter PD, Osmond C, Margetts B, Simmonds SJ. Weight in infancy and death from ischaemic heart disease.  Lancet. 1989;2(8663):577-580
PubMed   |  Link to Article
Frankel S, Elwood P, Sweetnam P, Yarnell J, Smith GD. Birthweight, body-mass index in middle age, and incident coronary heart disease.  Lancet. 1996;348(9040):1478-1480
PubMed   |  Link to Article
Eriksson JG, Forsen T, Tuomilehto J, Osmond C, Barker DJ. Early growth and coronary heart disease in later life: longitudinal study.  BMJ. 2001;322(7292):949-953
PubMed   |  Link to Article
Belfort MB, Rifas-Shiman SL, Rich-Edwards J, Kleinman KP, Gillman MW. Size at birth, infant growth, and blood pressure at three years of age.  J Pediatr. 2007;151(6):670-674
PubMed   |  Link to Article
Ekelund U, Ong K, Linne Y,  et al.  Upward weight percentile crossing in infancy and early childhood independently predicts fat mass in young adults: the Stockholm Weight Development Study (SWEDES).  Am J Clin Nutr. 2006;83(2):324-330
PubMed
Law CM, Shiell AW, Newsome CA,  et al.  Fetal, infant, and childhood growth and adult blood pressure: a longitudinal study from birth to 22 years of age.  Circulation. 2002;105(9):1088-1092
PubMed   |  Link to Article
Hokken-Koelega AC, De Ridder MA, Lemmen RJ, Den Hartog H, De Muinck Keizer-Schrama SM, Drop SL. Children born small for gestational age: do they catch up?  Pediatr Res. 1995;38(2):267-271
PubMed   |  Link to Article
Leunissen RW, Stijnen T, Hokken-Koelega AC. Influence of birth size on body composition in early adulthood: the PROGRAM study.  Clin Endocrinol (Oxf). 2009;70(2):245-251
PubMed   |  Link to Article
Singhal A, Cole TJ, Fewtrell M, Lucas A. Breastmilk feeding and lipoprotein profile in adolescents born preterm: follow-up of a prospective randomised study.  Lancet. 2004;363(9421):1571-1578
PubMed   |  Link to Article
Fewtrell MS, Morley R, Abbott RA,  et al.  Catch-up growth in small-for-gestational-age term infants: a randomized trial.  Am J Clin Nutr. 2001;74(4):516-523
PubMed
Armstrong J, Reilly JJ.Child Health Information Team.  Breastfeeding and lowering the risk of childhood obesity.  Lancet. 2002;359(9322):2003-2004
PubMed   |  Link to Article
Gillman MW, Rifas-Shiman SL, Camargo CA Jr,  et al.  Risk of overweight among adolescents who were breastfed as infants.  JAMA. 2001;285(19):2461-2467
PubMed   |  Link to Article
Kajantie E, Barker DJ, Osmond C, Forsen T, Eriksson JG. Growth before 2 years of age and serum lipids 60 years later: the Helsinki Birth Cohort study.  Int J Epidemiol. 2008;37(2):280-289
PubMed   |  Link to Article
Eriksson JG, Osmond C, Kajantie E, Forsen TJ, Barker DJ. Patterns of growth among children who later develop type 2 diabetes or its risk factors.  Diabetologia. 2006;49(12):2853-2858
PubMed   |  Link to Article
Bhargava SK, Sachdev HS, Fall CH,  et al.  Relation of serial changes in childhood body-mass index to impaired glucose tolerance in young adulthood.  N Engl J Med. 2004;350(9):865-875
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1. Derivation of Sample Into Subgroups
Graphic Jump Location
Place holder to copy figure label and caption
Figure 2. Height and Weight During Early Adulthood Relative to Height and Weight in the First Year of Life
Graphic Jump Location

The comparison is between young adults with slow weight gain vs young adults with rapid weight gain during the first 3 months of life. Values are expressed as mean (SEM).

Place holder to copy figure label and caption
Figure 3. Height, Weight, and Weight Minus Height at 21 Years
Graphic Jump Location

Values are expressed as mean (SEM).

Tables

Table Graphic Jump LocationTable 1. Clinical Characteristics of the Study Populationa
Table Graphic Jump LocationTable 2. Associations Between Standard Deviations in Weight Gain in the First Year of Life and Determinants of Cardiovascular Disease and Type 2 Diabetes in Early Adulthooda
Table Graphic Jump LocationTable 3. Clinical Characteristics and Determinants of Cardiovascular Disease and Type 2 Diabetes of Young Adults With Rapid vs Slow First-Year Growtha

References

Barker DJ, Gluckman PD, Godfrey KM, Harding JE, Owens JA, Robinson JS. Fetal nutrition and cardiovascular disease in adult life.  Lancet. 1993;341(8850):938-941
PubMed   |  Link to Article
Baker JL, Olsen LW, Sorensen TI. Childhood body-mass index and the risk of coronary heart disease in adulthood.  N Engl J Med. 2007;357(23):2329-2337
PubMed   |  Link to Article
Barker DJ, Osmond C, Forsen TJ, Kajantie E, Eriksson JG. Trajectories of growth among children who have coronary events as adults.  N Engl J Med. 2005;353(17):1802-1809
PubMed   |  Link to Article
Singhal A, Cole TJ, Fewtrell M,  et al.  Promotion of faster weight gain in infants born small for gestational age: is there an adverse effect on later blood pressure?  Circulation. 2007;115(2):213-220
PubMed   |  Link to Article
Chomtho S, Wells JC, Williams JE, Davies PS, Lucas A, Fewtrell MS. Infant growth and later body composition: evidence from the 4-component model.  Am J Clin Nutr. 2008;87(6):1776-1784
PubMed
Ekelund U, Ong KK, Linne Y,  et al.  Association of weight gain in infancy and early childhood with metabolic risk in young adults.  J Clin Endocrinol Metab. 2007;92(1):98-103
PubMed   |  Link to Article
Eriksson JG, Forsen T, Tuomilehto J, Winter PD, Osmond C, Barker DJ. Catch-up growth in childhood and death from coronary heart disease: longitudinal study.  BMJ. 1999;318(7181):427-431
PubMed   |  Link to Article
Usher R, McLean F. Intrauterine growth of live-born Caucasian infants at sea level: standards obtained from measurements in 7 dimensions of infants born between 25 and 44 weeks of gestation.  J Pediatr. 1969;74(6):901-910
PubMed   |  Link to Article
Fredriks AM, van Buuren S, Burgmeijer RJ,  et al.  Continuing positive secular growth change in the Netherlands 1955-1997.  Pediatr Res. 2000;47(3):316-323
PubMed   |  Link to Article
Bergman RN, Phillips LS, Cobelli C. Physiologic evaluation of factors controlling glucose tolerance in man: measurement of insulin sensitivity and beta-cell glucose sensitivity from the response to intravenous glucose.  J Clin Invest. 1981;68(6):1456-1467
PubMed   |  Link to Article
Pacini G, Bergman RN. MINMOD: a computer program to calculate insulin sensitivity and pancreatic responsivity from the frequently sampled intravenous glucose tolerance test.  Comput Methods Programs Biomed. 1986;23(2):113-122
PubMed   |  Link to Article
Boston RC, Stefanovski D, Moate PJ, Sumner AE, Watanabe RM, Bergman RN. MINMOD Millennium: a computer program to calculate glucose effectiveness and insulin sensitivity from the frequently sampled intravenous glucose tolerance test.  Diabetes Technol Ther. 2003;5(6):1003-1015
PubMed   |  Link to Article
Bergman RN. Lilly lecture 1989: toward physiological understanding of glucose tolerance: minimal-model approach.  Diabetes. 1989;38(12):1512-1527
PubMed   |  Link to Article
Leunissen RW, Kerkhof GF, Stijnen T, Hokken-Koelega AC. Fat mass and apolipoprotein E genotype influence serum lipoprotein levels in early adulthood, whereas birth size does not.  J Clin Endocrinol Metab. 2008;93(11):4307-4314
PubMed   |  Link to Article
Leunissen RW, Oosterbeek P, Hol LK, Hellingman AA, Stijnen T, Hokken-Koelega AC. Fat mass accumulation during childhood determines insulin sensitivity in early adulthood.  J Clin Endocrinol Metab. 2008;93(2):445-451
PubMed   |  Link to Article
Ong KK, Ahmed ML, Emmett PM, Preece MA, Dunger DB. Association between postnatal catch-up growth and obesity in childhood: prospective cohort study.  BMJ. 2000;320(7240):967-971
PubMed   |  Link to Article
Barker DJ, Winter PD, Osmond C, Margetts B, Simmonds SJ. Weight in infancy and death from ischaemic heart disease.  Lancet. 1989;2(8663):577-580
PubMed   |  Link to Article
Frankel S, Elwood P, Sweetnam P, Yarnell J, Smith GD. Birthweight, body-mass index in middle age, and incident coronary heart disease.  Lancet. 1996;348(9040):1478-1480
PubMed   |  Link to Article
Eriksson JG, Forsen T, Tuomilehto J, Osmond C, Barker DJ. Early growth and coronary heart disease in later life: longitudinal study.  BMJ. 2001;322(7292):949-953
PubMed   |  Link to Article
Belfort MB, Rifas-Shiman SL, Rich-Edwards J, Kleinman KP, Gillman MW. Size at birth, infant growth, and blood pressure at three years of age.  J Pediatr. 2007;151(6):670-674
PubMed   |  Link to Article
Ekelund U, Ong K, Linne Y,  et al.  Upward weight percentile crossing in infancy and early childhood independently predicts fat mass in young adults: the Stockholm Weight Development Study (SWEDES).  Am J Clin Nutr. 2006;83(2):324-330
PubMed
Law CM, Shiell AW, Newsome CA,  et al.  Fetal, infant, and childhood growth and adult blood pressure: a longitudinal study from birth to 22 years of age.  Circulation. 2002;105(9):1088-1092
PubMed   |  Link to Article
Hokken-Koelega AC, De Ridder MA, Lemmen RJ, Den Hartog H, De Muinck Keizer-Schrama SM, Drop SL. Children born small for gestational age: do they catch up?  Pediatr Res. 1995;38(2):267-271
PubMed   |  Link to Article
Leunissen RW, Stijnen T, Hokken-Koelega AC. Influence of birth size on body composition in early adulthood: the PROGRAM study.  Clin Endocrinol (Oxf). 2009;70(2):245-251
PubMed   |  Link to Article
Singhal A, Cole TJ, Fewtrell M, Lucas A. Breastmilk feeding and lipoprotein profile in adolescents born preterm: follow-up of a prospective randomised study.  Lancet. 2004;363(9421):1571-1578
PubMed   |  Link to Article
Fewtrell MS, Morley R, Abbott RA,  et al.  Catch-up growth in small-for-gestational-age term infants: a randomized trial.  Am J Clin Nutr. 2001;74(4):516-523
PubMed
Armstrong J, Reilly JJ.Child Health Information Team.  Breastfeeding and lowering the risk of childhood obesity.  Lancet. 2002;359(9322):2003-2004
PubMed   |  Link to Article
Gillman MW, Rifas-Shiman SL, Camargo CA Jr,  et al.  Risk of overweight among adolescents who were breastfed as infants.  JAMA. 2001;285(19):2461-2467
PubMed   |  Link to Article
Kajantie E, Barker DJ, Osmond C, Forsen T, Eriksson JG. Growth before 2 years of age and serum lipids 60 years later: the Helsinki Birth Cohort study.  Int J Epidemiol. 2008;37(2):280-289
PubMed   |  Link to Article
Eriksson JG, Osmond C, Kajantie E, Forsen TJ, Barker DJ. Patterns of growth among children who later develop type 2 diabetes or its risk factors.  Diabetologia. 2006;49(12):2853-2858
PubMed   |  Link to Article
Bhargava SK, Sachdev HS, Fall CH,  et al.  Relation of serial changes in childhood body-mass index to impaired glucose tolerance in young adulthood.  N Engl J Med. 2004;350(9):865-875
PubMed   |  Link to Article

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