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Elisabete Cristina Bastos Pinto FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY: RESULTS OF PORTO BIRTH COHORT Dissertação de candidatura ao grau de Doutor apresentada à Faculdade de Medicina da Universidade do Porto Porto, Março de 2010

FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

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Page 1: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

Elisabete Cristina Bastos Pinto

FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY:

RESULTS OF PORTO BIRTH COHORT

Dissertação de candidatura ao grau de Doutor apresentada à

Faculdade de Medicina da Universidade do Porto

Porto, Março de 2010

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II

Art.º 48º, § 3º

“A Faculdade não responde pelas doutrinas expendidas na dissertação.”

(Regulamento da Faculdade de Medicina da Universidade do Porto – Decreto-Lei nº 19337 de 29

de Janeiro de 1931)

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III

Corpo Catedrático da Faculdade de Medicina do Porto

Professores Catedráticos Efectivos

Doutor Manuel Maria Paula Barbosa

Doutor Manuel Alberto Coimbra Sobrinho Simões

Doutor Jorge Manuel Mergulhão Castro Tavares

Doutora Maria Amélia Duarte Ferreira

Doutor José Agostinho Marques Lopes

Doutor Patrício Manuel Vieira Araújo Soares da Silva

Doutor Daniel Filipe Lima Moura

Doutor Alberto Manuel Barros da Silva

Doutor José Manuel Lopes Teixeira Amarante

Doutor José Henrique Dias Pinto de Barros

Doutora Maria de Fátima Machado Henriques Carneiro

Doutora Isabel Maria Amorim Pereira Ramos

Doutora Deolinda Maria Valente Alves Lima Teixeira

Doutora Maria Dulce Cordeiro Madeira

Doutor Altamiro Manuel Rodrigues Costa Pereira

Doutor Rui Manuel Almeida Mota Cardoso

Doutor António Carlos Freitas Ribeiro Saraiva

Doutor Álvaro Jerónimo Leal Machado de Aguiar

Doutor José Luís Medina Vieira

Doutor José Carlos Neves da Cunha Areias

Doutor Manuel Jesus Falcão Pestana Vasconcelos

Doutor João Francisco Montenegro Andrade Lima Bernardes

Doutora Maria Leonor Martins Soares David

Doutor Rui Manuel Lopes Nunes

Doutor Amadeu Pinto de Araújo Pimenta

Doutor António Albino Coelho Marques Abrantes Teixeira

Doutor José Eduardo Torres Eckenroth Guimarães

Doutor Francisco Fernando Rocha Gonçalves

Doutor José Manuel Pereira Dias de Castro Lopes

Doutor Manuel António Caldeira Pais Clemente

Doutor Abel Vitorino Trigo Cabral

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IV

Professores Jubilados ou Aposentados

Doutor Abel José Sampaio Da Costa Tavares

Doutor Alexandre Alberto Guerra Sousa Pinto

Doutor Amândio Gomes Sampaio Tavares

Doutor António Augusto Lopes Vaz

Doutor António Carvalho Almeida Coimbra

Doutor António Fernandes da Fonseca

Doutor António Fernandes Oliveira Barbosa Ribeiro Braga

Doutor António Germano Pina Silva Leal

Doutor António José Pacheco Palha

Doutor António Luís Tomé da Rocha Ribeiro

Doutor António Manuel Sampaio de Araújo Teixeira

Doutor Artur Manuel Giesteira de Almeida

Doutor Belmiro dos Santos Patrício

Doutor Cândido Alves Hipólito Reis

Doutor Carlos Rodrigo Magalhães Ramalhão

Doutor Cassiano Pena de Abreu e Lima

Doutor Daniel Santos Pinto Serrão

Doutor Eduardo Jorge Cunha Rodrigues Pereira

Doutor Fernando de Carvalho Cerqueira Magro Ferreira

Doutor Fernando Tavarela Veloso

Doutor Francisco de Sousa Lé

Doutor Henrique José Ferreira Gonçalves Lecour de Menezes

Doutor João Silva Carvalho

Doutor Joaquim Germano Pinto Machado Correia da Silva

Doutor José Augusto Fleming Torrinha

Doutor José Carvalho de Oliveira

Doutor José Fernando Barros Castro Correia

Doutor José Manuel Costa Mesquita Guimarães

Doutor Levi Eugénio Ribeiro Guerra

Doutor Luís Alberto Martins Gomes de Almeida

Doutor Manuel Augusto Cardoso de Oliveira

Doutor Manuel Machado Rodrigues Gomes

Doutor Manuel Teixeira Amarante Júnior

Doutora Maria da Conceição Fernandes Marques Magalhães

Doutora Maria Isabel Amorim de Azevedo

Doutor Mário José Cerqueira Gomes Braga

Doutor Serafim Correia Pinto Guimarães

Doutor Valdemar Miguel Botelho dos Santos Cardoso

Doutor Walter Friedrich Alfred Osswald

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V

Ao abrigo do Art.º 8º do Decreto-Lei n.º 388/70 fazem parte desta dissertação as seguintes

publicações:

Pinto E, Severo M, Correia S, Santos-Silva I, Lopes C, Barros H. Validity and reproducibility of a

semi-quantitative food frequency questionnaire for use among Portuguese pregnant women.

Maternal and Child Nutrition 2010; 6: 105-19.

Pinto E, Barros H, Santos-Silva I. Dietary intake and nutritional adequacy prior to conception and

during pregnancy: a follow-up study in the north of Portugal. Public Health Nutrition 2009

Jul;12(7):922-31.

Pinto E, Ramos E, Severo M, Casal S, Santos-Silva I, Lopes C, Barros H. Measurement of dietary

intake of fatty acids in pregnant women: comparison of self-reported intakes with adipose tissue

levels. Submitted

Pinto E, Severo M, De Stavola B, Cunha A, Rodrigues T, Santos-Silva I, Barros H. Prenatal exposure

to fatty acids and fetal growth trajectories. Submitted

Pinto E, Ramos E, Guimarães JT, Barros H. Maternal blood IGFs, cord blood IGFs and lipids, and size

at birth: implications for adult hypercholesterolemia. Submitted

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VI

Esta investigação foi realizada no Serviço de Higiene e Epidemiologia da Faculdade de Medicina da

Universidade do Porto, sob a orientação do Senhor Professor Doutor Henrique Barros e co-

orientação da Senhora Professora Doutora Isabel dos Santos Silva.

Este projecto de investigação de base populacional – estudo de coorte, foi financiado pelo

Programa Operacional de Saúde – Saúde XXI, Quadro Comunitário de Apoio III e pela

Administração Regional de Saúde Norte.

No âmbito deste projecto de investigação, foi concedida a bolsa de Doutoramento pela Fundação

para a Ciência e a Tecnologia (SFRH / BD / 19803 / 2004).

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VII

Aos meus Pais

À Susana

Ao Professor Doutor Henrique Barros

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VIII

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IX

Agradecimentos

Ao Professor Doutor Henrique Barros agradeço tudo o que me ensinou, o incentivo e os desafios

ao longo destes anos. Agradeço-lhe o facto de me ter feito “crescer” pessoal e profissionalmente e

de tantas vezes me lembrar que o céu é o limite e o trabalho o único caminho nessa direcção.

À Professora Isabel dos Santos Silva agradeço tudo o que me ensinou, todo o apoio, incentivo e

paciência.

À Carla e à Elisabete agradeço o apoio, a colaboração, os ensinamentos e acima de tudo a

amizade.

Ao Nuno, à Ana, à Raquel e à Sofia agradeço o companheirismo, a amizade, a boa disposição e as

muitas conversas informais que muito contribuíram para a consecução desta tese.

À Andreia agradeço a amizade de muitos anos, o apoio e a disponibilidade permanentes.

Ao Milton agradeço toda a ajuda que me deu na análise estatística deste trabalho e a quem

reconheço uma paciência sem limite.

A todos os colegas do Serviço de Higiene e Epidemiologia, particularmente aos que estiveram

ligados à Geração XXI, agradeço a amizade, a compreensão e o incentivo constantes ao longo

deste meu percurso.

Aos meus pais e à minha irmã agradeço toda a dedicação, apoio incondicional e confiança,

agradeço-lhes por serem sempre o meu porto de abrigo.

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X

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Contents

Abstract 1

Resumo 7

Introduction 13

Aims of the study 25

Methods 29

Main results and discussion 47

Conclusions 65

References

69

Papers

I. Validity and reproducibility of a semi-quantitative food frequency

questionnaire for use among Portuguese pregnant women

II. Dietary intake and nutritional adequacy prior to conception and

during pregnancy: a follow-up study in the north of Portugal

III. Measurement of dietary intake of fatty acids in pregnant women:

comparison of self-reported intakes with adipose tissue levels

IV. Prenatal exposure to fatty acids and fetal growth trajectories

V. Maternal blood IGFs, cord blood IGFs and lipids, and size at birth:

implications for adult hypercholesterolemia

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XII

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PAPER I

Validity and reproducibility of a semi-quantitative food frequency

questionnaire for use among Portuguese pregnant women

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Page 110: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY
Page 111: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

PAPER II

Dietary intake and nutritional adequacy prior to conception and during

pregnancy: a follow-up study in the north of Portugal

Page 112: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY
Page 113: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

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Page 123: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

PAPER III

Measurement of dietary intake of fatty acids in pregnant women: comparison

of self-reported intakes with adipose tissue levels

Page 124: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY
Page 125: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

Measurement of dietary intake of fatty acids in pregnant women: comparison of self-

reported intakes with adipose tissue levels

Elisabete Pinto; Elisabete Ramos; Milton Severo; Susana Casal; Isabel dos Santos Silva; Carla

Lopes, Henrique Barros

ABSTRACT

Purpose: Dietary fatty acids affect several pregnancy outcomes, including foetal growth and

development. We compared self-reported intakes with concentrations of fatty acids in

adipose tissue in pregnant women.

Methods: The study was nested within Geração XXI, a birth cohort assembled in Portugal.

Intake was assessed by nine food diaries (FDs) completed throughout pregnancy and an FFQ

administered in the immediate postpartum period. A gluteal adipose tissue sample was

obtained from 23 women.

Results: FDs and FFQ estimated similar percentages of saturated (SFA), monounsaturated

(MUFA) and polyunsaturated fatty acids (PUFA), but the adipose tissue yielded a lower

percentage of SFA and higher percentages of MUFA and PUFA. Correlations between FDs

and adipose tissue ranged from r=0.50 for trans fatty acids to r=-0.19 for linolenic acid. The

proportion of women categorized in opposite tertiles by these two methods ranged from

4.3% to 30.4%. Correlations between FFQ and adipose tissue were even weaker and levels of

misclassification higher.

Conclusion: The correlations observed in this study between self-reported intakes and

tissue concentrations are weaker than those observed in a similar study conducted among

non-pregnant women, suggesting that adipose tissue levels of fatty acids may be a poor

biomarker of dietary intake in pregnancy.

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INTRODUCTION

Essential fatty acids and their long-chain unsaturated derivatives are crucial for fetal growth

and development and their requirements increasing during pregnancy (1, 2), particularly in

the last ten weeks (3). In contrast, trans fatty acids (TFA) have adverse effects on fetal

growth and development (4-6). Some studies have suggested that fatty acids may also affect

pregnancy length (7) and risk of pre-eclampsia (8), but the evidence from systematic reviews

is less consistent (9, 10).

Dietary intake can be assessed using several tools. Some attempt to estimate an

individual’s food intake (e.g. food frequency questionnaires (FFQ), food diaries (FDs)) and

others rely on assays to estimate the concentration of nutrients, or their metabolites, in

biological samples. Biomarkers are often considered to be the “gold standard” for dietary

evaluation because they are independent of an individual’s ability, or willingness, to

accurately report intake (11) and because they avoid interviewer bias (12). However,

biomarkers reflect not only an individual’s dietary intake but also his/her non-dietary

lifestyles, genetic background and metabolic profile. Biomarkers may also be affected by the

method of collection, sampling site and analytical technique used, and the inherent errors of

these procedures (13). Additionally, the value of a biomarker as a proxy for dietary intake

may be affected by specific physiological and biochemical adaptations, such as those

experienced during pregnancy (3, 14).

We have previously developed a specific FFQ for the Portuguese adult (non-

pregnant) population (available at: http://higiene.med.up.pt/freq.php). This FFQ was

validated against FDs and adipose tissue fatty acid concentrations, with the level of

agreement between the FFQ fatty acid estimates and adipose tissue concentrations being

within the usual ranges observed for these tools (15, 16). Recently, we assessed the validity

of this FFQ relative to FDs to measure usual intake of macro- and micro-nutrients other than

fatty acids among Portuguese pregnant women using a similar methodology (17). For a

subsample of the participants we also obtained a gluteal subcutaneous adipose tissue

sample to measure fatty acid concentrations. In this paper we compare dietary intake of

fatty acids during pregnancy, as estimated by the FFQ and multiple FDs, with levels of these

acids in the gluteal adipose tissue.

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METHODS

Subjects and study design

Participants were pregnant women enrolled in the “Geração XXI”, a birth cohort

assembled in Porto, Portugal, during the years 2004-2005. Most participants (n=8,334) were

recruited during the immediate post-partum period but a “pregnancy” sub-sample (n=320)

was identified and followed regularly from the first trimester of pregnancy (gestational age

below 13 weeks). Of these, 101 participated in the FFQ validation study (17).

Women were interviewed in each trimester of pregnancy by trained interviewers

using structured questionnaires to obtain information on demographic and lifestyle

variables, past medical history and health status during pregnancy. They were also asked to

complete a 3-day FD (in non-consecutive days) in each trimester. Twenty-four women also

gave permission for the researchers to collect a sample of gluteal subcutaneous adipose

tissue in late pregnancy. The participants were re-interviewed in the immediate postpartum

period and the FFQ administered to estimate dietary intakes during the whole pregnancy.

Ethical approval was obtained from all relevant institutional ethics committees. Each

participant provided written informed consent, including specific consent for collection of a

sample of adipose tissue.

Food frequency questionnaire (FFQ) and food diaries (FDs)

Participants were given detailed instructions on how to complete the FDs. These

were checked for completeness and accuracy with the participants and coded by a trained

nutritionist. The semi-quantitative FFQ comprised 86 food items. Frequency of consumption

was recorded in nine pre-specified categories from “never or less than once per month” to

“six or more times per day”. Each food item was allocated a pre-specified portion size. Usual

intake of any given food was estimated by multiplying its frequency of intake by its portion

size (in grams) and, if appropriate, by a seasonal variation factor (16, 17). The Food

Processor software, version SQL 9.3.0 (ESHA Research, Salem, Oregon, 2004),

supplemented with nutritional composition data of Portuguese foods and recipes (17, 18),

was used to convert FFQ and FD food intakes into nutrient intakes. Further details on the

development of the FFQ, and on its validation for nutrients other than fatty acids, can be

found elsewhere (16, 17).

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Gluteal subcutaneous adipose tissue sample

The biopsy was scheduled for 37-39 weeks of gestation and performed as

recommended by Beyen and Katan (19). The tissue samples were obtained from the upper

half of the buttock and stored at -80ºC until analysis (storage time: <6 months for all

samples). Each sample was divided in two portions, washed with 0.9% NaCl if blood

contamination was visible, and transferred to the reaction vials. The total fatty acids were

analyzed as methyl esters, prepared by direct transterification of the sample tissue with

sodium methoxide (0.5M, 30 min, 50ºC). After extraction with heptanes, the solution was

analyzed in a gas chromatograph Chrompack CP 9001 (Middelburg, the Netherlands),

equipped with a split/splitless injector and a flame ionization detector. Separation was

achieved in a capillary column CP-Sil 88 (50m x 0.22mm, 0.2µm, Varian) with helium as

carried gas. Quantification was based on the relative percentages of the fatty acid methyl

esters, corrected for the detector response obtained with standard mixtures (Supelco,

Spain). A total of 33 fatty acids methyl esters were quantified in all samples. The

methodology was validated by previous analysis of a certified reference material (CRM163,

BCR, European Commission).

Statistical methods

Mann-Whitney and chi-square tests were used to compare the characteristics of

women who provided an adipose tissue sample to the characteristics of other women in the

pregnancy sub-cohort. Cook’s distance was estimated for several fatty acids and a cut-off of

0.18 was used to define outliers (4/n-k-1, where n is the number of women and k is the

number of independent variables) (20). Spearman correlation coefficients were calculated to

measure the degree of association between the fatty acids intakes estimates by the two

dietary tools and the concentrations in adipose tissue, with a bootstrap method (21) used to

estimate their 95% confidence intervals.

The level of agreement between the FFQ, FD and adipose tissue estimates was

assessed by calculating the percentage of women who were classified into the same (perfect

agreement) and opposite tertiles (extreme disagreement) of the intake/concentration

distributions.

Statistical analyses were performed using SPSS (version 14.0) and R computer

packages (version 2.6.0).

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RESULTS

Valid tissue concentrations of fatty acids were obtained for 23 women (one was excluded

because she was an outlier). These 23 participants were similar to the remaining women in

the pregnancy sub-cohort who provided complete dietary information (n=100) in terms of

their age [median (25th percentile; 75th percentile): 30.4 (27.0; 32.8) vs. 30.4 (27.9; 33.8)

years, respectively; p=0.59], educational level [9.0 (7.5; 12.0) vs. 9.0 (6.0; 12.0) completed

schooling years; p=0.35], pre-pregnancy body mass index (BMI) [23.0 (20.9; 26.7) vs. 23.8

(21.4; 26.0) kg/m2; p=0.45], and total energy and fat FFQ intakes [mean (SD): 2,444 (735) vs.

2,531 (642) kcal, p=0.58; 85.4 (29.6) vs. 89.6 (24.2) g fat; p=0.49].

The FFQ and the FDs yielded, on average, similar fatty acid percent distributions

(median: 33.1% vs. 33.6% for saturated (SFA), 40.4% vs. 43.2% for monounsaturated (MUFA)

and 16.9% vs. 15.0% for polyunsaturated (PUFA) fatty acids, respectively) (Table 1).

However, the adipose tissue profile generated a lower percentage of SFA (24.2%) and,

hence, higher percentages of MUFA (52.3%) and PUFA (20.5%) (Table 1).

Overall, adipose tissue levels were more strongly correlated with the FD than the FFQ

intake estimates (Table 1). The strongest associations between FDs and adipose tissue were

observed for TFA (r=0.50), SFA (r=0.45) and docosapentaenoic acid (DPA) (r=0.44).

Correlations between fatty acids measured by the FFQ and the adipose tissue

determinations were strongest for linoleic acid (r=0.26) and PUFA (r=0.23).

The proportion of women classified into the same tertile (perfect agreement) by both

the FDs and the adipose tissue determinations was highest for SFA (60.9%), TFA (56.5%) and

DPA (52.2%) and lowest for arachidonic acid (AA) (21.7%). Classification in opposite tertiles

(extreme disagreement) ranged from 4.3% for TFA and DPA to 30.4% for linolenic acid (Table

2). Perfect agreement between FFQ and adipose tissue levels was highest for TFA (47.8%)

and SFA (43.5%) and lowest for DPA (21.7%), with extreme disagreement ranging from 8.7%

for linoleic acid to 30.4% for DPA (Table 2).

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DISCUSSION

To our knowledge this is the first study to compare two self-reported methods (FDs and FFQ)

of estimating fatty acids intake to adipose tissue concentrations, in pregnant women.

Although fatty acid levels in the adipose tissue were slightly better correlated with the FDs

than the FFQ estimates, the correlations were very weak for many fatty acids in both

comparisons. Fair correlations between FDs estimates and adipose tissue levels were

obtained only for TFA, SFA and DPA.

Fat intake is difficult to assess using self-reported dietary tools as participants may

misreport fat intake (e.g. due to its social undesirability) (11, 22) and fat used for cooking is

often disregarded. For FFQs, the advantages of using an interviewer to maximise

completeness and accuracy need to be balanced against the possibility of introducing

interviewer bias even when, as in the present study, the interviewers are trained and

procedures standardized.

It is often assumed that biomarkers provide a more accurate estimate of intake (13).

The fatty acids composition of white adipose tissue in pregnant women reflects maternal

lipids metabolism over of the last 6-12 months (2) and, consequently, a sample taken late in

pregnancy will reflect intake as well as the fast metabolic turnover characteristic of

pregnancy (3, 22). The only published study to have assessed the fatty acid composition of

adipose tissue in pregnant women (2), although it did not collect information on dietary

intake, reported higher percentages of linoleic acid, AA, eicosapentaenoic acid (EPA), DPA ,

and DHA, but a lower proportion of linolenic acid (approximately half), than those observed

in the present study.

The initial validation study of our FFQ, conducted among healthy males and non-

pregnant female adults (16) using the same methodology to that of the present study,

reported a similar overall adipose tissue profile in non-pregnant women to that observed

among pregnant women in the present study except for a lower percentage of oleic acid and

higher percentages of linolenic acid and TFA (Table 3). The associations between FD

estimates and adipose tissue levels among non-pregnant women were, however, stronger

than those observed among pregnant women in the present study (Table 3), particularly for

SFA (r=0.70 vs. r=0.45, respectively) and MUFA (r=0.67 vs. r=0.31, respectively) (Table 3).

Similarly, a fair agreement between FD estimates and adipose tissue levels was observed for

EPA and DHA, two important fatty acids for fetal growth, among non-pregnant women in the

Page 131: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

previous validation study, but these associations were rather weak among pregnant women

in the present study (Table 3). As both studies used the same methodology, including the

same FFQ, FD methodology and adipose tissue analytical technique, the discrepancies found

may reflect specific effects of pregnancy. Greater within-subject variability in dietary intake

during pregnancy (e.g. due to nausea, vomits and appetite fluctuations) could account for

the poorer correlations among pregnant than non-pregnant women, but the main reason for

the poorer correlation between FD and adipose tissue fatty acid estimates in pregnant than

in non-pregnant women is probably the specific metabolic adjustments that occur during

pregnancy (3). Studies have reported lower DHA concentrations in maternal adipose tissue

relative to DHA concentration in fetal brain and fetal adipose tissue, suggesting differential

mechanisms in the placenta and/or fetus in the uptake and retention of n-3 and n-6 fatty

acids (3, 23, 24). We also observed a lower concentration of DHA, but not EPA, in adipose

tissue of pregnant than non-pregnant women (Table 3), but the sample sizes were too small

to be conclusive.

Our findings suggest that levels of fatty acids in adipose tissue collected in late

pregnancy may not be a good biomarker of dietary fat intake during the whole pregnancy as

they are likely to reflect the balance between maternal intake and fetal utilisation. Further

larger studies are needed to corroborate these findings.

Page 132: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

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12. Baylin A, Kabagambe EK, Siles X, Campos H. Adipose tissue biomarkers of fatty acid

intake. Am J Clin Nutr 2002; 76(4): 750-7.

13. Moore VM, Davies MJ, Willson KJ, Worsley A, Robinson JS. Dietary composition of

pregnant women is related to size of the baby at birth. J Nutr 2004; 134(7): 1820-6.

14. Arab L. Biomarkers of fat and fatty acid intake. J Nutr 2003; 133 Suppl 3: 925S-32S.

15. Lopes C, Ramos E, Santos A, Casal S, Pereira J, Martinez C, et al. Quantificação da

ingestão de ácidos gordos. Arq Med 2002; 16(Supl. 6): 7-11.

16. Lopes C, Aro A, Azevedo A, Ramos E, Barros H. Intake and adipose tissue composition of

fatty acids and risk of myocardial infarction in a male Portuguese community sample. J Am

Diet Assoc 2007; 107(2): 276-86.

17. Pinto E, Severo M, Correia S, Santos-Silva I, Lopes C, Barros H. Validity and

reproducibility of a semi-quantitative food frequency questionnaire for use among

Portuguese pregnant women. Maternal Child Nutr 2010; 6: 105-19.

18. Pinto E, Barros H, Dos Santos Silva I. Dietary intake and nutritional adequacy prior to

conception and during pregnancy: a follow-up study in the north of Portugal. Public Health

Nutr 2008: 1-10.

19. Beynen AC, Katan MB. Rapid sampling and long-term storage of subcutaneous adipose-

tissue biopsies for determination of fatty acid composition. Am J Clin Nutr 1985; 42(2): 317-

22.

20. de Vaus D. Analyzing social science data: 50 key problems in data analysis. 2002: 92-8.

21. Wood M. Bootstrapped confidence intervals as an approach to statistical inference.

Organizational Research Methods 2005; 8: 454-70.

22. Arab L, Akbar J. Biomarkers and the measurement of fatty acids. Public Health Nutr

2002; 5(6A): 865-71.

23. Al MD, Badart-Smook A, von Houwelingen AC, Hasaart TH, Hornstra G. Fat intake of

women during normal pregnancy: relationship with maternal and neonatal essential fatty

acid status. J Am Coll Nutr 1996; 15(1): 49-55.

24. Al MD, van Houwelingen AC, Kester AD, Hasaart TH, de Jong AE, Hornstra G. Maternal

essential fatty acid patterns during normal pregnancy and their relationship to the neonatal

essential fatty acid status. Br J Nutr 1995; 74(1): 55-68.

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Table 1. Percent distributions of dietary and tissue fatty acids and their correlations (n=23)

FDs – food diaries (average of three trimester-specific 3-day FDs); FFQ – food frequency questionnaire; AT – adipose tissue; P25; P75 – percentiles 25th and 75th; r (95% CI)

- Spearman correlation coefficient (95% confidence interval); SFA – saturated fatty acids; MUFA – monounsaturated fatty acids; PUFA – polyunsaturated fatty acids; C18:1 -

oleic acid; C18:2 - linoleic acid; C18:3 – linolenic acid; C20:4 – arachidonic acid (AA); C20:5 – eicosapentaenoic acid (EPA); C22:5 – docosapentaenoic acid (DPA); C22:6 –

docosahexaenoic acid (DHA); TFA – trans fatty acids

Fatty acid

Adipose tissue (%)

Median (P25; P75)

FDs (%)

Median (P25; P75)

FFQ

Median (P25; P75)

AT - FDs

r (95% CI)

AT - FFQ

r (95% CI)

SFA 24.2 (21.5; 26.7) 33.1 (31.4; 35.4) 33.6 (28.4; 36.3) 0.45 (-0.07; 0.75) -0.11 (-0.57; 0.37)

MUFA 52.3 (49.7; 54.6) 40.4 (38.9; 43.7) 43.2 (41.3; 45.7) 0.31 (-0.15; 0.65) -0.04 (-0.50; 0.38)

PUFA 20.5 (19.5; 21.6) 16.9 (15.1; 18.3) 15.0 (13.4; 16.5) -0.05 (-0.46; 0.41) 0.23 (-0.17; 0.60)

C18:1 43.2 (41.4; 44.9) 36.3 (34.9; 40.5) 36.9 (33.0; 39.5) 0.21 (-0.24; 0.60) 0.02 (-0.47; 0.49)

C18:2 17.7 (16.8; 19.1) 13.7 (11.4; 14.5) 10.2 (8.50; 11.7) -0.07 (-0.48; 0.40) 0.26 (-0.11; 0.60)

C18:3 0.61 (0.49; 0.66) 1.77 (1.44; 2.39) 1.80 (1.38; 2.12) -0.19 (-0.58; 0.28) 0.07 (-0.35; 0.46)

C20:4 0.47 (0.38; 0.57) 0.15 (0.13; 0.19) 0.16 (0.13; 0.21) 0.06 (-0.31; 0.42) 0.08 (-0.29; 0.44)

C20:5 0.04 (0.03; 0.06) 0.11 (0.08; 0.17) 0.14 (0.10; 0.18) -0.04 (-0.52; 0.45) -0.02 (-0.42; 0.41)

C22:5 0.11 (0.09; 0.15) 0.03 (0.02; 0.03) 0.26 (0.04; 0.40) 0.44 (0.03; 0.72) -0.05 (-0.49; 0.40)

C22:6 0.15 (0.11; 0.18) 0.28 (0.25; 0.36) 0.29 (0.22; 0.37) 0.09 (-0.35; 0.51) -0.01 (-0.40; 0.43)

TFA 1.33 (1.20; 1.44) 0.97 (0.70; 1.24) 1.56 (1.30; 1.95) 0.50 (0.03; 0.75) 0.12 (-0.41; 0.75)

Omega 3 FA 0.83 (0.74; 1.01) 1.50 (1.36; 1.77) 1.68 (1.61; 1.94) -0.15 (-0.56; 0.38) 0.09 (-0.43; 0.49)

Omega 6 FA 1.23 (1.05; 1.46) 14.6 (12.7; 15.4) 10.9 (9.26; 12.3) 0.23 (-0.22; 0.59) -0.09 (-0.55; 0.33)

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Table 2. Level of agreement between self-reported fatty acid intakes and adipose tissue

concentrations (n=23)

Fatty acid

(%)

AT and FDs AT and FFQ

Agreement in the

same tertile

Extreme

disagreement

Agreement in

the same tertile

Extreme

disagreement

SFA 60.9 13.0 43.5 21.7

MUFA 47.8 17.4 39.1 17.4

PUFA 34.8 26.1 30.4 17.4

C18:1 39.1 17.4 30.4 17.4

C18:2 30.4 26.1 39.1 8.7

C18:3 26.1 30.4 26.1 21.7

C20:4 21.7 13.0 39.1 17.4

C20:5 39.1 26.1 39.1 26.1

C22:5 52.2 4.3 21.7 30.4

C22:6 26.1 17.4 30.4 21.7

TFA 56.5 4.3 47.8 17.4

Omega 3 FA 30.4 26.1 30.4 17.4

Omega 6 FA 30.4 17.4 26.1 21.7

AT – adipose tissue; FDs – food diaries (average of three trimester-specific 3-day FDs); FFQ – food frequency

questionnaire; SFA – saturated fatty acids; MUFA – monounsaturated fatty acids; PUFA – polyunsaturated fatty

acids; C18:1 - oleic acid; C18:2 - linoleic acid; C18:3 – linolenic acid; C20:4 – arachidonic acid (AA); C20:5 –

eicosapentaenoic acid (EPA); C22:5 – docosapentaenoic acid (DPA); C22:6 – docosahexaenoic acid (DHA); TFA –

trans fatty acids

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Table 3. Relative concentrations of individual fatty acids in adipose tissue in pregnant and

non-pregnant* women, and their correlations with intake as estimated by multiple food

diaries

Fatty

acids

AT

Median (P25; P75)

FDs vs. AT

r (95%CI)

Pregnant

women

(n=23)

Non-pregnant

women

(n=35) *

Pregnant women

(n=23)

Non-pregnant

women *

(n=35)

SFA 24.2 (21.5; 26.7) 22.8 (21.0; 28.1) 0.45 (-0.07; 0.75) 0.70 (0.51; 0.84)

MUFA 52.3 (49.7; 54.6) 55.6 (52.7; 60.2) 0.31 (-0.15; 0.65) 0.67 (0.45; 0.80)

PUFA 20.5 (19.5; 21.6) 19.3 (16.6; 22.8) -0.05 (-0.46; 0.41) 0.21 (-0.12; 0.50)

C18:1 43.2 (41.4; 44.9) 50.0 (46.6; 53.8) 0.21 (-0.24; 0.60) 0.52 (0.20; 0.73)

C18:2 17.7 (16.8; 19.1) 18.4 (15.9; 21.9) -0.07 (-0.48; 0.40) 0.27 (-0.09; 0.61)

C18:3 0.61 (0.49; 0.66) 0.33 (0.29; 0.38) -0.19 (-0.58; 0.28) -0.12 (-0.47; 0.26)

C20:4 0.47 (0.38; 0.57) 0.42 (0.32; 0.50) 0.06 (-0.31; 0.42) 0.31 (-0.04; 0.62)

C20:5 0.04 (0.03; 0.06) 0.05 (0.04; 0.07) -0.04 (-0.52; 0.45) 0.50 (0.20; 0.69)

C22:6 0.15 (0.11; 0.18) 0.21 (0.17; 0.31) 0.09 (-0.35; 0.51) 0.37 (-0.02; 0.63)

TFA 1.33 (1.20; 1.44) 0.88 (0.73; 0.98) 0.50 (0.03; 0.75) 0.02 (-0.30; 0.37)

AT – adipose tissue; FDs – food diaries (average of three trimester-specific 3-day FDs for pregnant women;

average of four 7-days FDs for non-pregnant women); P25; P75 – percentiles 25 and 75; FDs – food diaries; r -

Spearman correlation coefficient; SFA – saturated fatty acids; MUFA – monounsaturated fatty acids; PUFA –

polyunsaturated fatty acids; C18:1 - oleic acid; C18:2 - linoleic acid; C18:3 – linolenic acid; C20:4 – arachidonic

acid (AA); C20:5 – eicosapentaenoic acid (EPA); C22:6 – docosahexaenoic acid (DHA); TFA – trans fatty acids

* Adapted from Lopes et al. (15, 16) to include only data from adult non-pregnant women who completed the

FDs and also provided a gluteal adipose tissue sample. These women also completed a FFQ reporting diet

during preceding year. The same FFQ, FD collection methods and adipose tissue collection and analytic

procedures were used in the two studies.

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PAPER IV

Prenatal exposure to fatty acids and fetal growth trajectories

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Prenatal exposure to fatty acids and fetal growth trajectories

Elisabete Pinto, Milton Severo, Bianca De Stavola, Ana Cunha, Teresa Rodrigues, Isabel dos

Santos Silva, Henrique Barros

ABSTRACT

Background: In well-nourished populations maternal diet has little impact on size at birth,

but but little is known about its impact on fetal growth trajectories.

Aims: To investigate the effect of maternal diet, particularly intakes of energy,

macronutrients and specific fatty acids, on fetal growth trajectories.

Study design: A sample of women enrolled in “Geração XXI”, a Portuguese birth cohort, was

followed throughout pregnancy and their diet ascertained using a food frequency

questionnaire. Linear mixed models were fitted to assess the association of diet with fetal

growth trajectories and term birth size.

Subjects: 222 mother-infant pairs.

Outcome measures: Fetal growth estimated from ultrasonographic fetal measures (weight,

head and abdominal circumferences, femur length) taken from mid-pregnancy onwards

(mean number of scans/woman: 2; range 2-6).

Results: Energy, protein and carbohydrate intakes were not associated with any measure of

fetal growth. The effect of gestational age on fetal growth was modified by maternal fat

intake, with fetus of women in the top intake fifths of total fat, saturated-, trans- and n-6

fatty acids having a similar weight as those of women in the other fifths at 18th gestational

week, but an increasing lower weight after that (6-8g less weekly). Similar effect

modifications were observed for abdominal circumference, but not for head circumference

or femur length.

Conclusions: Maternal energy, protein and carbohydrate intakes had no effect on fetal

growth. Highest intakes of total fat, and certain of its components, were associated with a

slowdown in the rate of fetal growth in the last half of pregnancy.

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INTRODUCTION

Food deprivation is a major determinant of intrauterine growth restriction, in developing

countries (1), both as the result of macro (2) and micronutrients deficiencies (3). However, in

developed countries associations between maternal diet during pregnancy and size at birth

of their offspring are rarely observed and, when found, they tend to be weak (4, 5).

Fetal growth is a dynamic process and similar birth weights may be achieved through

different growth trajectories leading to variations in body composition and organ

development and maturation (6, 7). Animal experiments have suggested that fetal under-

nutrition in early pregnancy results in small but normally proportioned offspring, whereas

nutritional restrictions in late pregnancy may have several effects on body proportions but

little effect on birth weight (8). Data from children exposed in utero to the Dutch Hunger

Winter showed that birth weight and body proportions were only affected when exposure

occurred late in pregnancy (2). Maternal diet during pregnancy influences the balance

between the fetal demand for nutrients and the materno-placental capacity to supply

sufficient nutrients for the fetus to maintain its own innate growth trajectory (8). Failure to

support fetal nutrient requirements results in a range of fetal adaptations and

developmental changes and, although these adaptations may be beneficial for short-term

survival, they may lead to permanent alterations in the body’s structure and metabolism and

thereby to cardiovascular and metabolic disease in adult life (9).

Total fat and/or specific fatty acids are the only maternal nutrients for which there is

some, although inconsistent, evidence that they may affect fetal growth in well-nourished

populations. Some studies reported positive associations between maternal high intakes of

fish, or marine n-3 fatty acids, during pregnancy and newborn birth weight due to increases

in both pregnancy length and fetal growth rate (10, 11). However, other studies, including

randomized controlled trials, did not find any associations between maternal intake of total

fat, or of any of its components – i.e. proportions of saturated fatty acids (SFA),

monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), n-3 fatty acids or

n-6 fatty acids - and gestational length or newborn birth size (12-14). But, to our knowledge,

no study has so far investigated the role of these nutrients on fetal growth trajectories.

In this study, we investigated the effect of maternal diet, particularly energy,

macronutrients and specific fatty acids, on fetal growth trajectories in a group of well-

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nourished pregnant women. We also examined possible associations between maternal diet

and birth size of their offspring.

MATERIAL AND METHODS

Subjects

This study was based on data from pregnant women enrolled in Geração XXI, a

population-based prospective birth cohort assembled in Porto, Portugal (15). A sub-sample

of mothers in this cohort, recruited through two of the five participating maternity hospitals

– Júlio Dinis Maternity and S. João Hospital - between 1st December of 2004 and 31st

December of 2005, were consecutively invited to participate if they reported a gestational

age below 13 weeks. Those who agreed to participate were interviewed in each trimester of

pregnancy and in the immediate postpartum period. In accordance with Portuguese

antenatal care guidelines, each woman was scheduled to have three routine obstetric scans

in one of these hospitals - in early (gestational age <14 weeks), mid (gestational age between

18 and 25 weeks) and late pregnancy (gestational age ≥25 weeks).

A total of 430 pregnant women were enrolled (recruitment rate 96.2%): 300 at Júlio

Dinis Maternity and 130 at S. João Hospital. Of these, 21 were excluded immediately after

enrolment because the self-reported gestational age was not confirmed by the ultrasound

exam. Further women were excluded at a later stage because of miscarriage (n=24), medical

abortion (n=2), fetal death (n=4), severe intra-uterine growth restriction with major

malformations (n=1), twin pregnancies (n=9) and refusal to be further evaluated (n=59) or

inability to complete the food frequency questionnaire (FFQ) in the immediate post-partum

(n=35). An additional 52 women were excluded because only one ultrasound scan was

performed after the 17th gestational week due to very preterm deliveries, missed

appointments or scans having been performed somewhere else. In the analysis, a further

woman was excluded because the two available ultrasound evaluations were both

performed in mid-pregnancy (in weeks 18 and 22). This analysis is therefore based on data

from the 222 remaining participants.

Approval for the study was obtained from institutional ethics committees. Each

participant provided written informed consent.

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Data collection

Trained interviewers administered structured questionnaires in each trimester of

pregnancy and in the post-partum to obtain information on demographic and lifestyle

variables, past medical history and health status during pregnancy. Education was recorded

as number of completed schooling years and categorized as ≤6, 7–9, 10–12 and >12 years.

Pre-pregnancy body mass index (BMI) was estimated from self-reported pre-pregnancy

weight or, if this was not known (for 13.2% of women), the weight measured at the first

ante-natal visit. BMI was analysed according to the follow categories: <25.0kg.m-2, 25.0–

29.9kg.m-2 and ≥30.0kg.m-2. Maternal smoking habits were categorised as having ever/never

smoked throughout pregnancy. Newborns’ anthropometric data were collected from

hospital records. Birth weight was measured in digital scales and reported to the nearest 2g

in S. João Hospital and to the nearest 5g in Júlio Dinis Maternity; length and head

circumference were reported to the nearest 0.1cm. Birth weight was measured shortly after

birth and length and head circumference were measured in the first 24h hours, by trained

paediatricians.

Maternal dietary intake during pregnancy

Dietary intake was ascertained by the application of a semi-quantitative FFQ. The FFQ

was administered four times. The first administration (FFQ1) occurred at the time of the first

ante-natal interview during the first trimester of pregnancy, and it aimed to estimate usual

dietary intake in the preceding year; the second (FFQ2) and third (FFQ3) administrations

took place in mid- and late pregnancy and sought to ascertain maternal diet during the first

and second pregnancy trimesters, respectively. The fourth administration (FFQ4) occurred a

few days after delivery and aimed to estimate usual dietary intake during the whole

pregnancy. In a previous study (16) we showed that the dietary intake in this group of

pregnant women varied little throughout pregnancy and that the FFQ applied in the

immediate post-partum is a valid tool to rank women in terms of their dietary intake. Thus,

we used the data provided by the FFQ4 in the present analysis.

Nutritional intake was estimated by multiplying the frequency of intake of each 86

FFQ food or food group items by its respective allocated portion size, in grams, and

subsequently converted into nutrients using Portuguese food composition tables (15). In this

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study, we examined possible associations between maternal dietary intakes of energy and

macronutrients, with particular emphasis on total fat and its components, and fetal growth

trajectories.

Fetal ultrasonography

Fetal ultrasound examinations were carried out at the obstetric ultrasonographic

units in the two hospitals, using Aloka ultrasound equipments (SSD 2000, abdominal probe

of 3.5 Mhz). Ultrasound data were recorded in Astraia® - an obstetric and gynaecological

database, version 1.18, Germany. Gestational age was estimated on the basis of the first day

of the last menstrual period, as reported by the women, and subsequently confirmed by the

early-pregnancy ultrasound (taken before the 14th gestational week). If the two methods

yielded different estimates, the latter one was chosen.

The fetal growth measures examined included head and abdominal circumferences,

femur length and biparietal diameter (the latter was only used by Astraia® to automatically

estimate fetal weight, as proposed by Hadlock et al. (17)). Fetal ultrasound measurements

were taken by trained obstetricians, to the nearest millimetre, using standardized

procedures.

In this analysis, we only considered ultrasounds taken at mid- and late pregnancy (i.e.

in the 18th gestational week or later). The number of ultrasound scans available per woman

within this period ranged from 2 to 6 (with 122 (55.0%) having two scans, 80 (36.0%) having

three, and 20 (9.0%) having at least four). The mean gestational age at the first ultrasound

within this period was 21.2 weeks (SD: 2.0).

Statistical Analysis

The individual fetal growth trajectories over gestational age (measured in days but

expressed in weeks) were examined to assess data quality. These checks were performed

separately for each fetal growth dimension: weight, head and abdominal circumferences,

and femur length.

The nutrients investigated were total energy, proteins, carbohydrates, total fat,

saturated fatty acids (SFA), trans fatty acids (TFA), and n-3 and n-6 fatty acids. The 1st and 4th

quintiles of their distributions in the whole study population were used to categorise women

into three groups, with the bottom category corresponding to values less than the 1st

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quintile, and the top category corresponding to values greater than the 4th quintile. The

bottom and top fifths were compared to the middle category (reference).

For each fetal growth dimension, mixed models were fitted, assuming a quadratic

relationship with gestational age, to estimate the effect of each categorized nutrient on

average fetal size at the 18th gestational week and the average weekly rate of growth from

then onwards. These models always included fetal gender and maternal smoking as a priori

predictors of average size and average rate of growth. Mixed models were fitted to estimate

the effect of categorized nutrients on newborn size as measured by weight, length and head

circumference at birth. Several potential confounders for the effect of the dietary variables

on fetal growth and birth size were also considered, including maternal age, education,

parity, height, and pre-pregnancy weight and BMI. Each of these variables was included in

the model and any changes in the effect of the nutrient assessed. Statistical analyses were

performed in SPSS (version 17.0) and R (version 2.6.0) computer packages.

RESULTS Participating women had a mean age of 28.8 years (standard deviation (SD) 5.9) at the time

of their enrolment into the study and a median number of completed schooling years of 9

(inter-quartile range (IR): 6, 12) (Table 1). About 90% of the women were married, and for

47% the current pregnancy was their first. Sixty percent of the participants had a pre-

pregnancy BMI<25.0kg.m-2, and 19% reported having ever smoked during pregnancy (Table

1).

Median daily energy intake during the whole pregnancy was 2423kcal (percentile 20;

percentile 80 (P20; P80): 1979; 3016), 18.3% as proteins, 51.4% as carbohydrates and 31.8%

as total fat (Table 1). SFA and TFA contributed to 10.9% and 0.54% of the total energy intake,

respectively.

The median gestational age at birth of their offspring was 39.1 weeks (P25, P75: 38.3,

40.0), similar for boys and girls. At birth girls were, on average, 240g lighter, 0.5cm shorter

and had a 0.5cm smaller head circumference than boys (Table 2).

At the 18th gestational week, there were no significant differences in fetal weight

according to the gender of the fetus or the smoking status of the mothers (Table 3). From

the 18th gestational week onwards fetal weight increased, on average, 85.7g per week. The

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weekly increments in head circumference, abdominal circumference and femur length were,

on average, 14.3mm, 12.8mm and 2.94mm, respectively. The weekly increment in fetal

weight was 8.3g lower in females, but no clear gender differences were observed in relation

to the other three fetal measures (Table 3). Relative to fetus of non-smokers those of

smokers had a significantly lower rate of growth, with smaller weekly increments in weight

(less 8.7g), femur length (0.12mm) and abdominal circumference (0.51mm) from the 18th

gestational week onwards (Table 3).

At the 18th gestational week there were no associations between maternal intakes

and fetal size (Table 4). Maternal intakes of energy, protein and carbohydrates had no effect

on the rate of fetal growth from then onwards, but a high maternal fat consumption slowed

down the rate of fetal growth. Fetus of mothers in the top intake fifths of total fat, SFA, TFA

and n-6 fatty acids gained weekly less 5.5, 7.2, 8.3 and 7.7g, respectively, in fetal weight

from the 18th gestational week onwards (Table 4) and about 0.4mm less weekly in

abdominal circumference (i.e., 0.37mm for total fat, 0.47mm for SFA, 0.39mm for TFA and

0.38mm for n-6 fatty acids; Table 4). Fetus of pregnant women in the top fifth of TFA intake

also had a lower weekly rate of increase in femur length (β=-0.09mm, 95 percent confidence

interval (CI): -0.16, -0.03). In contrast, none of the maternal nutrients examined had an

effect on the rate of growth of head circumference (data not shown).

After controlling for gestational age, fetus gender, smoking and other potential

confounders there was no evidence of any association between maternal diet throughout

pregnancy and newborn anthropometry at birth, except that newborns whose mothers were

in the bottom fifth for SFA were, on average, 0.66cm (CI: -1.25, -0.07) shorter at birth than

those whose mothers were in the reference category (data not shown).

DISCUSSION

To the best of our knowledge, no previous study has examined the effect of maternal diet

during pregnancy on fetal growth trajectories. A recent study used a similar approach, but to

evaluate the effect of maternal smoking on fetal growth (7). We observed no associations

between maternal intake of energy or macronutrients and fetal size at the 18th gestational

week but, from then onwards, we found that average weekly increases in weight and

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abdominal circumference were lower among fetus of mothers who were in the highest

intake fifths of total fat, SFA, TFA and n-6 fatty acids. In contrast, maternal fat intake had no

effect on the rate of growth of head circumference or femur length (only a weak interaction

between TFA intake and gestational age on the rate of increase in femur length was

observed). These findings are consistent with animal experiments, particularly those

conducted in sheep whose organogenesis during fetal development is comparable to that in

humans, that identified the third trimester of pregnancy as the time window of higher

plasticity of adipose tissue and muscle (18). The lack of associations between maternal diet

and rate of increase in head circumference and femur length in mid-late pregnancy suggest

that the rate of linear (skeletal) growth may be determined at an earlier stage of pregnancy

and is not affected by maternal diet later on.

We examined the role of maternal diet on overall fetal weight as well as on body

proportions, as birth weight is likely to be a rather crude surrogate of fetal growth and

development. We found that the associations of maternal fat intake with the rate of fetal

growth observed in this study were mainly driven by similar associations with abdominal

circumference. Rates of increase in abdominal circumference are likely to reflect mainly

rates in liver growth because this organ grows rapidly in late gestation to become the most

important abdominal organ at birth (19). Interestingly, Barker et al. found that subjects with

a reduced abdominal circumference at birth had hypercholesterolemia in adulthood (19),

suggesting that the mechanisms controlling cholesterol metabolism in later life may be

programmed in utero.

Our observation of a lower rate of fetal growth in fetus whose mothers consumed

the highest quantities of TFA is also largely supported by the literature (20-22). Placenta

allows the transport of TFA to the fetus (21) and both experimental data, from in vitro and

animal studies, and human data, from studies of preterm infants and children, indicate that

trans fatty acids may impair growth (21). Albeit some studies reported an association

between maternal intake of n-3 fatty acids and birth weight no association was found with

rate of fetal growth in mid- and late pregnancy in this study. One previous study showed

that birth weight was positively associated with maternal serum levels of n-3 fatty acids in

early pregnancy (as a proxy for dietary intake), but negatively associated with serum levels

of n-6 fatty acids and TFA (20). However, no such associations were reported by another

study which ascertained dietary intake in the last trimester of pregnancy (12).

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On the basis of the observed associations between maternal fat intake and the rate

of fetal growth, one would have predicted similar association with size at birth. However,

and similarly to others (14, 23, 24), we found no associations between maternal diet and any

of the birth size dimensions examined. The large majority of women had their last

ultrasonographic evaluation around the 30-34th gestational weeks; thus, it is possible that

further changes in the rate of fetal growth may have occurred between the time of the last

ultrasound scan and birth. Besides, as fetal weight was estimated indirectly from ultrasound

measurements and birth weight was measured directly, the two measures may not be

entirely comparable.

This study has strengths but also some weaknesses. It was nested within a

prospective population-based cohort study of pregnant women who were followed up

throughout pregnancy and for whom detailed data on dietary data and ultrasonographic

fetal measurements were collected. There were no differences in maternal or newborn

characteristics between the participants and those women who would have been eligible

but did not complete the required ultrasound evaluations or the FFQ, except that the

proportion of ever-smokers during pregnancy was lower among participants (18% vs. 32%;

P=0.009). A few women developed gestational diabetes (n=18) or gestational hypertensive

disorders (n=6), but their exclusion from the analysis did not affect the results. Reassuringly,

the major determinants of the fetal growth rate in the second half of pregnancy were, as

expected, gestational age, fetal gender and maternal smoking during pregnancy, despite the

fact that none of these variables was associated with fetal size at the 18th gestational week.

The observed effect of maternal smoking on fetal growth is consistent with data from a large

Dutch birth cohort (7), which reported severe growth fetal retardation for mothers who

smoked later in pregnancy relative to those who smoked only during mid pregnancy.

Because our sample size was much smaller we were unable to examine trimester-specific

smoking effects. Our analyses of the association between maternal diet and both fetal

growth and birth size adjusted for fetus gender and maternal smoking, as well as other

potential confounding variables, the possibility of residual confounding cannot be ruled out.

Our examination of growth trajectories was restricted to gestational age greater than

17th weeks because earlier ultrasounds evaluations did not provide estimates for all the fetal

size measures examined in this study. Data on usual diet during pregnancy was collected

retrospectively by administering a previously validated FFQ in the immediate post-partum

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period; this is unlikely to have introduced bias as both the interviewers and the women were

unaware of the specific study hypothesis. The present analysis was restricted to intake of

energy and macronutrients because micro-nutrient intakes were within recommended levels

for practically all study women and a large proportion took supplements (15). Our a priori

decision to focus on the role of specific fatty acids and their association with fetal growth

trajectories was informed by previously published work (20, 25). As our study population

comprised well nourished women we hypothesized that any dietary effects on fetal growth

were likely to be modest (4, 5). However, as the maturation of many organs – e.g. lungs,

kidneys, organs of the digestive tract – takes place during the last trimester (9), even small

variations within the normal range of growth and development in late fetal life may have

life-long health consequences.

In summary, our study showed that in well nourished women levels of intake of total

energy, protein and carbohydrate throughout pregnancy had no effects on fetal growth.

However, highest intakes of total fat, SFA, TFA and n-6 fatty acids, were associated with a

slowdown in the rate of fetal growth in the last half of pregnancy, reflecting mainly a

slowdown in the rate of increase in abdominal circumference. Although the observed effects

on fetal growth rate were small they may, nevertheless, be of relevance in the context of the

“fetal origins of adult diseases” hypothesis.

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pregnancy. Nestle Nutr Workshop Ser Pediatr Program. 2008; 61: 103-21.

2. Stein A, Zybert P, van de Bor M, Lumey L. Intrauterine famine exposure and body

proportions at birth: the Dutch Hunger Winter. Int J Epidemiol. 2004; 33(4): 831-6.

3. Roberfroid D, Huybregts L, Lanou H, Henry M, Meda N, Menten J, et al. Effects of

maternal multiple micronutrient supplementation on fetal growth: a double-blind

randomized controlled trial in rural Burkina Faso. Am J Clin Nutr. 2008; 88(5): 1330-40.

4. Gillman M. Epidemiological challenges in studying the fetal origins of adult chronic

disease. Int J Epidemiol. 2002; 31(2): 294-9.

5. Lagiou P, Mucci L, Tamimi R, Kuper H, Lagiou A, Hsieh C, et al. Micronutrient intake

during pregnancy in relation to birth size. Eur J Nutr. 2005; 44(1): 52-9.

6. Harding J. The nutritional basis of the fetal origins of adult disease. Int J Epidemiol. 2001;

30(1): 15-23.

7. Jaddoe V, Verburg B, de Ridder M, Hofman A, Mackenbach J, Moll H, et al. Maternal

smoking and fetal growth characteristics in different periods of pregnancy: the generation R

study. Am J Epidemiol. 2007; 165(10): 1207-15.

8. Godfrey K, Barker D. Fetal nutrition and adult disease. Am J Clin Nutr. 2000; 71(5 Suppl):

1344S-52S.

9. Barker D. Fetal and infant origins of adult disease. Plymouth: Latimer Trend & Company

Ltd, 1992.: 1-20.

10. Olsen S, Osterdal M, Salvig J, Kesmodel U, Henriksen T, Hedegaard M, et al. Duration of

pregnancy in relation to seafood intake during early and mid pregnancy: prospective cohort.

Eur J Epidemiol. 2006; 21(10): 749-58.

11. Olsen S. Consumption of marine n-3 fatty acids during pregnancy as a possible

determinant of birth weight. A review of the current epidemiologic evidence. Epidemiol Rev.

1993; 15(2): 399-413.

12. Drouillet P, Forhan A, De Lauzon-Guillain B, Thiebaugeorges O, Goua V, Magnin G, et al.

Maternal fatty acid intake and fetal growth: evidence for an association in overweight

women. The 'EDEN mother-child' cohort (study of pre- and early postnatal determinants of

the child's development and health). Br J Nutr. 2009; 101(4): 583-91.

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13. Helland I, Saugstad O, Smith L, Saarem K, Solvoll K, Ganes T, et al. Similar effects on

infants of n-3 and n-6 fatty acids supplementation to pregnant and lactating women.

Pediatrics. 2001; 108(5): E82.

14. Szajewska H, Horvath A, Koletzko B. Effect of n-3 long-chain polyunsaturated fatty acid

supplementation of women with low-risk pregnancies on pregnancy outcomes and growth

measures at birth: a meta-analysis of randomized controlled trials. Am J Clin Nutr. 2006;

83(6): 1337-44.

15. Pinto E, Barros H, dos Santos Silva I. Dietary intake and nutritional adequacy prior to

conception and during pregnancy: a follow-up study in the north of Portugal. Public Health

Nutr. 2009; 12(7): 922-31.

16. Pinto E, Severo M, Correia S, dos Santos Silva I, Lopes C, Barros H. Validity and

reproducibility of a semi-quantitative food frequency questionnaire for use among

Portuguese pregnant women. Maternal and Child Nutrition. 2010; 6: 105-19.

17. Hadlock F, Harrist R, Carpenter R, Deter R, Park S. Sonographic estimation of fetal

weight. The value of femur length in addition to head and abdomen measurements.

Radiology. 1984; 150(2): 535-40.

18. Symonds M, Stephenson T, Gardner D, Budge H. Long-term effects of nutritional

programming of the embryo and fetus: mechanisms and critical windows. Reprod Fertil.

2007; 19(1): 53-63.

19. Barker D, Martyn C, Osmond C, Hales C, Fall C. Growth in utero and serum cholesterol

concentrations in adult life. BMJ. 1993; 307(6918): 1524-7.

20. van Eijsden M, Hornstra G, van der Wal M, Vrijkotte T, Bonsel G. Maternal n-3, n-6, and

trans fatty acid profile early in pregnancy and term birth weight: a prospective cohort study.

Am J Clin Nutr. 2008; 87(4): 887-95.

21. Koletzko B, Muller J. Cis- and trans-isomeric fatty acids in plasma lipids of newborn

infants and their mothers. Biol Neonate.1990; 57(3-4): 172-8.

22. Hornstra G, van Eijsden M, Dirix C, Bonsel G. Trans fatty acids and birth outcome: some

first results of the MEFAB and ABCD cohorts. Atheroscler Suppl. 2006; 7(2): 21-3.

23. Lagiou P, Tamimi R, Mucci L, Adami H, Hsieh C, Trichopoulos D. Diet during pregnancy in

relation to maternal weight gain and birth size. Eur J Clin Nutr. 2004; 58(2): 231-7.

24. Susser M. Maternal weight gain, infant birth weight, and diet: causal sequences. Am J

Clin Nutr. 1991; 53(6): 1384-96.

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25. Dirix C, Kester A, Hornstra G. Associations between term birth dimensions and prenatal

exposure to essential and trans fatty acids. Early Hum Dev. 2009; 85(8): 525-30.

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Table 1. Characteristics of the Study Sample of Pregnant Women, Geração XXI, Porto, Portugal

n (%)

Maternal age at enrolment into the study

(years)

≤ 20

21 – 34

≥ 35

27 (12.2)

159 (71.6)

36 (16.2)

Education (completed schooling years)

≤ 6

7 – 9

10 – 12

≥ 13

67 (30.2)

68 (30.6)

59 (26.6)

28 (12.6)

Marital status at enrolment

Married/ Fact union

199 (89.6)

Gravidity

First pregnancy

105 (47.3)

Maternal BMI* before pregnancy (kg.m-2)

< 25.0

25.0 – 29.9

> 29.9

122 (59.8)

56 (27.5)

26 (12.7)

Smoking during pregnancy

Ever

41 (18.5)

Median (P20; P80)†

Energy (kcal) 2423 (1979; 3016)

Protein (g) 111.6 (91.0; 134.7)

Carbohydrates (g) 303.3 (245.8; 393.8)

Total fat (g) 82.5 (66.2; 112.7)

Saturated fatty acids (g) 28.2 (21.9; 39.2)

Trans fatty acids (g) 1.42 (1.05; 1.95)

n-3 fatty acids (g) 1.47 (1.08; 1.84)

n-6 fatty acids (g) 9.00 (6.80; 12.64) BMI – body mass index; * data available for 204; † Percentiles 20 and 80 are shown because they were used to define the three nutrient intake categories presented in Table 4.

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Table 2. Characteristics of the Study Sample of Newborns, Geração XXI, Porto, Portugal

Total sample

Median (P25; P75)¥

Boys §

Median (P25; P75)¥

Girls §

Median (P25; P75)¥

n (%) 222 (100.0) 104 (46.8) 118 (53.2)

Gestational age at birth (wks) 39.1 (38.3; 40.0)

(n=220)

39.1 (38.2; 40.0)

(n=102)

39 (38.6; 40.0)

(n=118)

Birth weight (g) 3216 (2868; 3483)

(n=222)

3320 (2961; 3590)

(n=104)

3080 (2842; 3349)

(n=118)

Birth length (cm) 49.0 (47.5; 50.0)

(n=221)

49.5 (48.0; 51.0)

(n=104)

49.0 (47.0; 50.0)

(n=117)

Birth head circumference (cm) 34.0 (33.5; 35.0)

(n=216)

34.5 (33.5; 35.5)

(n=102)

34.0 (33.0; 34.5)

(n=114)

§ The numbers of boys and girls may be smaller than the total number because of missing values.

¥ Unless otherwise specified

Median (P25; P75) – median (percentile 25th; percentile 75th); wks - weeks

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Table 3. Fetal Growth Trajectories in Relation to Fetal Gender and Maternal Smoking Status, Geração XXI, Porto, Portugal

Fetal weight (g)

Head circumference (mm) Femur length (mm) Abdominal circumference

(mm)

Coef 95% CI Coef 95% CI Coef 95% CI Coef 95% CI Fixed effects

Intercept Reference 117.8 (28.7; 206.8) 148.2 (143.8; 152.6) 26.3 (25.2; 27.4) 126.3 (120.6; 131.9) (at 18th gestational wks) Female gender 6.5 (-46.0; 59.0) -3.1 (-5.7; -0.5) -0.32 (-0.98; 0.34) -3.1 (-6.4; 0.3)

Maternal smoking 31.5 (-36.3; 99.4) 0.38 (-3.0; 3.7) 0.22 (-0.63; 1.08) 2.7 (-1.7; 7.0)

Gestational age (wks) Reference 85.7 (74.9; 96.5) 14.3 (13.8; 14.8) 2.94 (2.81; 3.07) 12.8 (12.1; 13.4) Female gender -8.3 (-12.3; -3.0) -0.11 (-0.31; 0.08) 0.04 (-0.01; 0.09) -0.12 (-0.37; 0.12) Maternal smoking -8.7 (-14.3; -3.0) -0.21 (-0.47; 0.06) -0.12 (-0.18; -0.05) -0.51 (-0.85; -0.17)

Gestational age

2 (wks) Reference 3.7 (3.2; 4.1) -0.24 (-0.26; -0.22) -0.04 (-0.04; -0.03) -0.11 (-0.14; -0.08)

Random effects

Between babies SD 100.8 5.68 1.37 7.41 Within babies SD 140.5 6.55 1.70 8.38

Coef – beta coefficient; 95% CI – 95% confidence interval; wks – weeks; Gestational age 2

– quadratic term for gestational age; SD – standard deviation

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Table 4. Maternal Dietary Intake During Pregnancy and Fetal Growth Trajectories, Geração XXI, Porto, Portugal

Average size at the 18th

gestational week

(95% CI) §

in ref. category ¥

Change in average size at the 18th

gestational week §

from ref. category ¥

Average weekly fetal

growth rate (95% CI) §Ŧ

in ref. category¥

Change in average weekly fetal growth rate

(95% CI) §

from ref. category

Ŧ

Bottom fifth ¥ Top fifth

¥ Bottom fifth

¥ Top fifth

¥

Fetal weight (g)

Energy (kcal) 116.0 (25.4; 206.6) -6.7 (-74.5; 61.2) 15.4 (-51.9; 82.6) 85.9 (75.0; 96.8) 1.45 (-3.9; 6.8) -1.7 (-7.2; 3.7)

Proteins (g) 115.2 (23.5; 207.0) 11.3 (-55.7; 78.3) 7.7 (-59.8; 75.2) 86.1 (75.2; 97.1) -2.4 (-7.6; 2.8) -0.8 (-6.3; 4.6)

Carbohydrates (g) 119.6 (26.7; 212.4) -11.7 (-79.1; 55.7) 15.9 (-51.3; 83.0) 84.6 (73.7; 95.6) 4.6 (-0.7; 9.8) -0.9 (-6.1; 4.4)

Total fat (g) 109.5 (18.2; 200.8) 6.9 (-60.7; 74.4) 36.6 (-30.5; 103.7) 87.0 (76.1; 97.9) -1.4 (-6.7; 3.9) -5.5 (-10.9; -0.1)

SFA (g) 106.2 (14.7; 197.6) 6.6 (-61.3; 74.6) 35.6 (-31.2; 102.5) 87.8 (76.9; 98.7) -1.4 (-6.8; 3.9) -7.2 (-12.6; -1.8)

TFA (g) 115.1 (22.6; 207.5) -22.9(-89.8; 43.9) 22.6 (-44.3; 89.5) 88.1 (77.2; 99.0) -0.8 (-6.1; 4.5) -8.3 (-13.6; -3.0)

n-3 FA (g) 120.1 (28.6; 211.6) -9.8 (-76.8; 57.3) -4.5 (-72.7; 63.6) 85.4 (74.4; 96.3) 2.2 (-3.1; 7.5) -1.3 (-6.8; 4.1)

n-6 FA (g) 111.8 (20.4; 203.2) 0.6 (-66.6; 67.9) 32.5 (-33.5; 98.6) 86.7 (75.9; 97.6) 0.2 (-5.1; 5.5) -7.7 (-12.9; -2.5)

Abdominal circumference (mm)

Energy (kcal) 126.0 (120.2; 131.7) 0.59 (-3.73; 4.92) 1.66 (-2.62; 5.95) 12.8 (12.2; 13.5) -0.01 (-0.33; 0.31) -0.11 (-0.43; 0.22)

Proteins (g) 125.7 (119.9; 131.5) 2.22 (-2.05; 6.48) 1.35 (-2.94; 5.64) 12.8 (12.2; 13.5) -0.23 (-0.54; 0.08) -0.08 (-0.41; 0.25)

Carbohydrates (g) 126.2 (120.3; 132.1) -0.59 (-4.88; 3.71) 2.03 (-2.24; 6.31) 12.7 (12.1; 13.4) 0.28 (-0.03; 0.60) -0.08 (-0.39; 0.24)

Total fat (g) 125.3 (119.5; 131.0) 2.15 (-2.15; 6.45) 3.66 (-0.61; 7.93) 12.9 (12.2; 13.5) -0.26 (-0.58; 0.05) -0.37 (-0.70; -0.05)

SFA (g) 125.0 (119.2; 130.8) 1.56 (-2.77; 5.88) 3.76 (-0.51; 8.02) 12.9 (12.3; 13.6) -0.20 (-0.52; 0.12) -0.47 (-0.80; -0.15)

TFA (g) 126.2 (120.3; 132.1) -0.50 (-4.78; 3.77) 0.74 (-3.55; 5.02) 12.9 (12.3; 13.6) -0.17 (-0.49; 0.15) -0.39 (-0.71; -0.07)

n-3 FA (g) 126.3 (120.5; 132.1) 0.29 (-3.99; 4.56) -1.34 (-5.68; 3.00) 12.8 (12.1; 13.4) 0.06 (-0.26; 0.38) 0.03 (-0.29; 0.36)

n-6 FA (g) 125.7 (119.8; 131.5) 1.05 (-3.25; 5.35) 2.04 (-2.19; 6.28) 12.9 (12.2; 13.5) -0.06 (-0.38; 0.26) -0.38 (-0.69; -0.06)

§ Mixed models were fitted adjusting for fetus gender, maternal smoking status, gestational age (as linear and quadratic terms), interaction between gestational age and maternal smoking status, and interaction between gestational age and fetus gender. Further adjustment for maternal age, educational level, parity, height, and pre-pregnancy weight or BMI did not affect these findings.

Ŧ From the 18

th gestational week onwards;

¥ The cutoff points used to define these categories for each nutrient are shown in Table 1

95% CI – 95% confidence interval; Ref. – reference; SFA – saturated fatty acids; TFA – trans-fatty acids; FA – fatty acids

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PAPER V

Maternal blood IGFs, cord blood IGFs and lipids, and size at birth: implications

for adult hypercholesterolemia

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Maternal blood IGFs, cord blood IGFs and lipids, and size at birth: implications for adult

hypercholesterolemia

Elisabete Pinto, Elisabete Ramos, João Tiago Guimarães, Isabel dos Santos Silva, Henrique

Barros

ABSTRACT

Background: There is on-going interest in unraveling the pathways linking the intra-uterine

environment with adult conditions such as cardiovascular diseases.

Aims: To quantify the associations between cord and maternal insulin-like growth factors

(IGFs) and the birth size, and the association of these factors with cord lipids.

Study design: A sample of 196 mother-infant pairs enrolled in “Geração XXI”, a Portuguese

birth cohort. Maternal and umbilical blood samples were drawn at the time of delivery.

Serum IGF-1, IGF-2 and IGFBP-3 levels were determined in all maternal and cord samples,

and serum total cholesterol, HDL cholesterol (HDLc) and triglycerides (TG) measured in cord

samples. Linear regression models were used to examine association between IGFs, cord

lipids and several birth size measures.

Results: Both maternal and cord IGF-1 levels were positively associated with birth size, but in

mutually-adjusted analyses only the cord IGF-1 effect persisted (for each standard deviation

increment in log IGF-1 cord levels birth weight increased by 371g (95%CI: 287; 456). Similar

positive associations of cord IGF-1 were observed with length, head circumference and

ponderal index at birth. Neither maternal nor cord IGF-2 or IGFBP-3 were independently

associated with birth size. Cord IGF-1 levels were positively associated with cord HDLc and

negatively associated with cord TG. Birth size was also negatively associated with cord TG,

but the effect disappeared on adjustment for cord IGF-1.

Conclusions: Cord IGF-1 plays a more important role in fetal growth than maternal IGF-1.

Cord IGF-1 affects cord lipids raising, thus, the hypothesis that cord lipids might be a possible

link between the intrauterine environment and adult diseases.

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INTRODUCTION

There is an increasing interest in the life-course influence of the intrauterine environment on

cardiovascular and metabolic diseases. Adults who had experienced reduced rates of fetal

growth have increased risks of high blood pressure (1), impaired glucose tolerance (2),

abnormal blood coagulation (3), higher serum levels of total and low density lipoproteins

cholesterol (LDLc) (4), and higher mortality from coronary heart disease mortality (5, 6).

Birth weight (BW) is commonly used as a surrogate measure of intrauterine exposures,

because it reflects the role of both genetic and environmental factors, including parental

socio-economical status, maternal nutrition and endocrine regulation of fetal growth (7).

The importance of environmental factors on BW was highlighted by Brooks et al. (8) in their

study of pregnancies involving ovum donation. They found that BW was affected by the

weight of the recipient mother, but not by the weight of the donor mother. BW is the most

widely investigated measure of fetal growth, partly because it is routinely collected and

partly because it is less likely to be affected by measurement error than other newborn

anthropometric measures, such as length, arm circumference or abdominal circumference.

Retarded intrauterine growth affects body proportions at birth as well as birth size and,

hence, availability of data on anthropometric measures other than BW, as markers of

adiposity and body proportionality, may be of relevance as they have been linked to health

outcomes later in life in some studies (9).

Since the 1980s there is growing evidence that Insulin-like Growth Factors (IGFs) are

associated with fetal growth (10, 11). IGFs are produced by fetal, placental and maternal

tissues but it is unclear whether IGFs influence fetal growth regardless of their origin (7).

IGFs have mitogenic properties, inducing somatic cell growth and proliferation, and the

ability to influence the transport of glucose and amino acids across the placenta. Alterations

in the IGF axis are associated with fetal growth restriction in both animal models and human

studies (7). Cord blood IGF-1 and IGFBP-3 have been consistently associated with larger birth

anthropometric parameters (12-18), while IGF-2 has been shown to have either a positive

(14) or a null (12, 18, 19) association with BW. Cord IGF-1 levels have been shown to be

associated with cord blood concentration of high density lipoproteins cholesterol (HDLc) and

of triglycerides (TG) (20) and these, in turn, are known to be associated with lipid profiles in

adult life (21). Thus, one can hypothesise that IGFs may play an important role in the way the

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prenatal environment may permanently influence lipid metabolism and, possibly, other

health outcomes later in life.

This study aims to investigate associations between cord and maternal IGFs, cord

lipids and birth size, and their implications in terms of potential pathways linking in utero

exposures to adult diseases and, in particular, adult hypercholesterolemia.

SUBJECTS AND METHODS

Subjects

Participants in this study were selected from Geração XXI, a birth cohort assembled in Porto,

Portugal. All mothers resident in the metropolitan area of Porto who delivered a live-born

baby between 1st May 2005 and 31st August 2006 in five public level III maternity units were

invited to participate in Geração XXI. These hospitals are responsible for 91.6% of the

deliveries in the whole catchment population, with the remaining occurring in private

hospitals/clinics. A total of 8654 babies were enrolled into the study.

Maternal and cord blood samples were available for a sub-sample of 1581 Caucasian

mothers and babies. We excluded twin pregnancies (n=21), mothers with a diagnosis of

diabetes or hypertensive disorders before or during pregnancy (n=100), preterm deliveries

(gestational duration < 37 weeks) (n=78) and newborns for whom anthropometry data at

birth were not available (n=9). The eligible study population included 1373 mother-newborn

pairs, comprising 41 low birth BW (<2500g) and 55 macrossomic newborns (BW> 3999g).

The final sample size for this analysis included these 96 newborns (and their mothers) as well

as a random sample of 100 newborns with BW between 2500g to 3999g (inclusive).

Data collection

All mothers were invited and interviewed in the 24 to 72 hours after delivery by

trained interviewers, using a structured questionnaire to elicit information on demographic

and lifestyle variables, past medical history and health status during pregnancy. Education

was recorded as the number of completed years of schooling and categorized as <6, 7–9,

10–12 and >12. Maternal weight gain during pregnancy was estimated from self-reported

pre-pregnancy weight and the weight at the end of pregnancy. Pre-pregnancy body mass

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index (BMI) was estimated from self-reported pre-pregnancy weight and the height

measurement taken during the interview (if the latter was not possible, the measured height

recorded on the national identity card was used (n=17)) and it was analyzed according to

WHO categories (underweight: <18.5kg/m2; normal weight: 18.5–24.9kg/m2; overweight:

25.0–29.9kg/m2; obesity: ≥30.0kg/m2). Tobacco smoking was recorded as the daily number

of cigarettes smoked in each trimester of pregnancy and women subsequently dichotomized

as being either ever- or never-smokers.

Information on gestational length (estimated from date of last menstrual period),

newborn gender, and neonate birth size (i.e. weight (in g), length (in cm), head

circumference (in cm) and ponderal index (PI) (weight (kg)/length (m)3)) were collected from

the clinical records. BW was measured shortly after birth, using digital scales. BL was

measured with infantometers and head circumference (HC) with tapes, with both sets of

measurements taken within the first 24 hours after birth.

Biochemical analysis

Mothers provided a venous blood sample during labour or in the first hours after

delivery (maximum 72h). In addition, a blood sample from the umbilical cord was also

collected during labour. Blood were collected in Vacutainer serum tubes (Becton-

Dickinson, USA). All specimens were separated and stored in aliquots at -80º until assayed.

The median storage time of the samples was 1004 days (range: 905 to 1245). Samples from

mother-newborn pairs were examined in the same batch, to reduce bias, and laboratory

staff was kept blind to the characteristics of the samples.

Serum total cholesterol and triglycerides were measured using conventional

colorimetric methods, while HDL Cholesterol was measured with a direct method. The

within- and between-batch variability for the serum concentrations of these variables were

all less than 5%. All this measurements were made using an Olympus AU5400 automated

clinical chemistry analyzer. (Beckman-Coulter, Izasa, Porto, Portugal).

IGF-I and IGFBP3 were both measured with a solid-phase, enzyme-labeled

chemiluminescent immunometric assay using a Siemens IMMULITE 2000 automated

analyzer (Siemens, Lisboa, Portugal). Analytical sensitivity is 20.0ng/dl for IGF-I and 0.1μg/ml

for IGFBP3. Within- and between-batch coefficients of variation were below 10% for both

IGF-1 and IGFBP-3. Samples for the determination of IGF-2 were measured in duplicate by an

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immunoradiometric assay (IRMA), from Diagnostics Systems Laboratories, Inc., that includes

an extraction step (DSL-9100 Active IGF-II IRMA kit, Arium, Lisboa, Portugal). The detection

limit for this method was 12.0ng/dl, with the within- and between-batch coefficients of

variation being less than 11%. Samples for the determination of IGF-2 were analyzed using

kits from the same production lot.

Statistical analysis

The Kolmogorov–Smirnoff test was used to assess the assumption of normality.

Logarithmic transformations were made on each of the IGFs and IGFBP-3 values to achieve

normality. Gender differences in mean levels of cord IGFs and lipids were examined using

the Mann-Whitney U test.

Correlations between hormone/lipid levels and newborn size measures were

quantified using Pearson correlation coefficients. Linear regression models were fitted to

examine the independent role of each IGF on birth size measures (BW, BL, HC and ponderal

index (PI, defined as length (m) / weight (kg)3) . The effect of each IGF on birth size was

examined for increments of one standard deviation (SD) of the log transformed IGF values to

facilitate interpretation. The potential confounding effect of several variables was assessed,

including storage time, laboratory batch, maternal age, education, gravidity, tobacco

smoking during pregnancy, pre-pregnancy BMI, weight gain during pregnancy, gestational

length and newborn gender. Models were fitted to provide three different estimates: (i)

firstly, estimates of the effect of maternal and newborn IGFs and IGFBP-3 on birth size

measures adjusted for other maternal and newborn characteristics (only the variables

shown to be confounders were included in the final model as indicated in the tables); (ii)

estimates of each cord (or maternal) IGF effects on birth size further adjusted for the other

two cord (or maternal) IGF levels; and, finally, (iii) estimates of the cord and maternal IGF-1

effects on birth size adjusted for all the variables in (i) and for each other. To assess whether

these associations were being driven by the extreme values at the birth size distribution we

conducted further analyses restricted to newborns (and their mothers) with BW between

2500g and 3999g (inclusive).

Linear regression models were also fitted to quantify the independent effect of cord

IGF-1 and birth size measures on cord lipid levels.

Statistical analyses were performed using SPSS, version 17.0.

Page 164: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

RESULTS

Mothers had a mean age of 28.5 (standard deviation (SD): 5.4) years, 54.1% were

primiparae and 25% reported having ever smoker during pregnancy. 35% of the women

were overweight or obese prior to becoming pregnant. The mean weight gain during

pregnancy was 13.7 (SD: 5.8) kg. Ninety-eight newborns were male. The mean gestational

duration was 39.4 (SD: 1.2) weeks. The median BW was 2395g among low BW newborns

(interquartile range (IQR): 2290; 2450), 3217g among babies with adequate BW (IQR: 310;

3486) and 4130g for the macrossomic newborns (IQR: 4080; 4260) (Table 1).

Medians and IQR of the levels of cord and maternal blood IGF-1, IGF-2, IGFBP-3, total

cholesterol, HDLc are also shown in Table 1. As expected, for all parameters, maternal

concentrations were much higher than the corresponding cord blood ones.

There were no statistically significant gender (female vs. male) differences in cord

blood concentrations of IGFs and IGFBP-3 (IGF-1 (ng/ml): 64.2 vs. 61.3, p=0.215; IGF-2

(ng/ml): 443.3 vs. 446.2, p= 0.707; IGFBP3 (mcg/ml): 1.4 vs. 1.4, p=0.101), or in cord TG

levels (0.36 vs. 0.33g/L, p=0.590), but the total cholesterol and HDLc concentrations were

significantly higher in females (total cholesterol (g/L): 0.67 vs. 0.60, p=0.026; HDLc (g/L): 0.27

vs. 0.25, p=0.026).

Correlations between cord and maternal levels of IGFs and IGFBP-3, cord lipids and

birth size measures are shown in Table 2. Each one of the IGFs measured in cord blood was

positively correlated with its counterpart measured in maternal blood; all cord IGFs were

positively correlated with BW, BL, HC and PI, whereas only maternal IGF-1 was correlated

significantly with birth size. The correlation coefficients between maternal and cord blood

specimens were: 0.32 (p<0.001) for IGF-1, 0.16 (p=0.009) for IGF-2 and 0.24 (p=0.010) for

IGFBP-3. IGFs and IGFBP3 levels in cord blood were positively correlated with cord levels of

HDLc, but negatively correlated with cord levels of TG. There were, however, no correlations

between cord lipid levels and birth size measures except for a weak inverse correlation

between cord TG and HC (Table 2).

After adjustment for maternal and newborn characteristics, cord IGF-1, IGF-2 and

IGFBP-3 were all positively associated with BW, BL and HC (Table 3, model 1), but only IGF-1

levels were associated with PI. The strongest effects were observed for IGF-1 – for each SD

increment in log IGF-1 cord concentration BW increased by 319.6g (95% CI: 237.3; 401.9), BL

by 1.24cm (95% CI: 0.96; 1.53), HC by 0.83cm (95% CI: 0.59; 1.07) and PI by 3.2kg/m3 (0.7;

Page 165: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

5.6) (Table 3). In contrast, maternal IGFs were not associated with birth size measures,

except for an association between maternal IGF-1 and BL. Cord IGF levels are highly

correlated (Table 2) and mutually-adjusted analyses showed that the effect of IGF-1 on birth

size persisted after adjustment for the other two cord IGFs, whereas the effects of IGF-2 and

IGFBP-3 disappeared (Table 3, model 2). The effect of maternal IGF-1 on birth size was

slightly strengthened after adjustment for the other two maternal IGFs, with IGF-1 being

positively and independently associated with both weight and length at birth. However, the

magnitude of the IGF-1 association was much stronger for cord levels (for each SD increment

in log IGF-1 cord and maternal levels BW increased by 342.2g (95% CI: 214.2; 476.3) and

147.8g (95% CI: 3.2; 292.3), respectively, and BL increased by 1.01cm (95% CI: 0.54; 1.48)

and 0.80cm (95% CI: 0.27; 1.34), respectively) (Table 3; model 2). Thus, when both maternal

and cord IGF-1 levels were included simultaneously in the same model (Table 3, model 3),

only the effect of cord IGF-1 on birth size persisted (for each SD increment of log IGF-1 cord

levels BW increased by 371.3g (95% CI: 286.9; 455.8), BL by 1.29cm (95% CI: 0.96; 1.62), HC

by 0.85cm (95% CI: 0.58; 1.12) and PI by 0.9kg/m3 (95% CI: 0.4; 1.4)) (Table 3). Restricting the

analyses to newborns (and their mothers) with BW between 2500g and 3999g (inclusive) did

not affect these findings.

After adjustment for relevant maternal and newborn characteristics, cord IGF-1 levels

were significantly associated with cord levels of HDLc and TG (Table 4). These associations

persisted after adjustment for birth size measures (HDLc increased by 0.01g/L and TG

decreased by 0.06g/L for each SD increment in the log IGF-1 cord levels) (Table 4). In

contrast, the effect of BW, BL, HC and PI on cord levels of HDLc and TG disappeared after

further adjustment for cord IGF-1 levels (Table 4).

DISCUSSION

Cord blood levels of IGF-1, IGF-2 and IGFBP-3 were all associated with newborn BW,

BL, HC and PI, but in mutually adjusted analyses only IGF-1 was found to be an independent

correlate of birth size. Maternal IGF-1 was also found to be associated with BW and BL, but

its effects disappeared on adjustment for cord IGF-1. Cord IGF-1 levels were also positively

associated with cord HDLc, and negatively associated with TG levels, with these associations

persisting after adjustment for birth size measures. In contrast, birth size measures were not

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associated with cord HDLc, but were negatively associated with cord TG; however, these

birth size effects on cord TG disappeared on adjustment for cord IGF-1 levels.

Serum concentrations of IGF-1 and IGF-2 are higher in pregnant women than non-

pregnant women (22) with concentrations increasing even further by the third trimester

(23), suggesting a possible role of maternal IGFs on fetal growth. In our study, only maternal

IGF-1 was found to be associated with BW, and its effect disappeared on adjustment for cord

IGF-1. Other previous studies have also shown no association between maternal IGFs and

BW (24, 25).

Our data favour a stronger independent role of cord, rather than maternal, IGFs on

fetal growth. The positive association between cord IGF-1 and BW is extensively

corroborated by the literature (12-18, 26, 27). The same is true for IGFBP-3 (12-14, 16). The

findings for IGF-2 are not so consistent. Two previous studies (10, 14, 16) reported a positive

correlation between IGF-2 and BW, but no correlations were found in others (12, 15, 18, 19,

27). The effect of IGF axis on the other newborns’ anthropometric measures has been less

studied but, similarly to our study, positive associations of cord IGF-1 with BL (16, 28, 29) and

PI (29, 30) have been described. In the present study, cord IGF-2 and IGFBP-3 were positively

associated with birth size but these associations disappeared on adjustment for cord IGF-1.

Maternal IGF-2 and IGFBP-3 were not associated with birth size, before or after adjustment

for maternal IGF-1.

We did not find differences in the IGF axis according to the gender of the fetus.

Previous studies reported higher IGF-2 concentrations in cord blood from male newborns

(11), or higher cord IGF-1 and IGFBP-3 in females (29). However, similarly to our study, a

recent one (20) found no gender differences in cord IGF levels.

One of the strengths of the present study is that it is based on a random sample of

mothers-newborn pairs, with the sampling procedure designed to oversample low BW and

macrossomic newborns so that the IGF associations could be examined across the full birth

size distribution. Most previous studies had had a case-control design, whereby newborns

from uncomplicated pregnancies were compared with newborns from mothers who

developed gestational diabetes or hypertensive disorders. These disorders, in addition with

twin pregnancies, are important causes of extreme birth size. We excluded such conditions

from our study, to allow examination of the role of the IGFs axis on birth size in the absence

of any obvious pathology.

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Badiee et al. (31) has revised data on cord lipid levels in several populations. Our

Portuguese sample of newborns had concentrations of total cholesterol, HDLc and TG similar

to those observed in Chile, Brazil and USA; in Poland, higher levels of TG and lower levels of

HDLc were reported, while in Japan the opposite was observed. Iranian data showed higher

concentrations of all measured parameters. A previous study in the Portuguese population

(32) showed a higher total cholesterol and HDLc concentrations in cord blood and similar TG

levels. We compared the two studies regarding the timing of the blood collection, average

BW, gestational age, maternal blood levels and methods of assay and we cannot find

differences, except in the sample size (other study figured out only 39 newborns of non pre-

eclamptic mothers). It is possible that the differences could be attributable to differences in

sample size. Furthermore, procedures in the collection and storage and of biological samples

can compromise the validity of the findings.

In the present study, cord IGF-1 was positively associated with cord HDLc and

negatively associated with cord TG. Similar results were reported in a previous study (20),

with the authors postulating a direct effect of IGF-1 on HDLc metabolism, as well as

alterations in the IGF-1 mediated fetal liver production of TG (20). Although little is known

about the control and function of circulating fetal lipoproteins in utero (33), in adults IGF-1

and IGFBP-3 levels are associated with several features of the metabolic syndrome (34),

namely with circulating levels of HDLc and TG (35).

There is evidence to suggest that the intrauterine environment may permanently

influence lipid metabolism (21, 36, 37). Some studies showed that BW correlates negatively

with serum TG levels (38, 39) and positively with serum HDLc (38, 40) in adult life. Barker (4)

advanced as a possible explanation for that the impairment of the liver growth in low BW

children which leads to permanent changes in LDLc metabolism. One study reported that

LDLc concentration was negatively associated with BW and HC in full-term neonates (40).

Most of the original studies linking birth size with disease outcomes later in life were

limited, due to their retrospective nature, by the unavailability of detailed newborn

anthropometric data. The present study benefited from the availability of such detailed

newborn anthropometric data, which were collected using standardised procedures, as well

as from the availability of cord and maternal samples.

Both cord lipid profile and birth size have been shown to be associated with

hypercholesterolemia later in life. We found that cord IGF-1, but not birth size, was

Page 168: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

independently associated with cord lipid levels and therefore hypothesized that cord lipids,

rather than birth size, could be the relevant marker of in utero programming of lipid

metabolism. IGF-1 levels affect both birth size and therefore it could simply be a surrogate of

IGF-1 and/or of the mechanism linking IGF-1 and cord lipid profile to adult

hypercholesterolemia (Figure 1). The fact that the association between birth size and cord

lipids was not independent of cord IGF-1, strengthens the hypothesis that birth size may be a

surrogate for cord IGF-1. Our results are based on cross-sectional data and further

prospective studies are needed to unravel the mechanisms underlying the associations

between birth size, cord IGFs and cord lipids, and hypercholesterolemia later in life.

Page 169: FETAL GROWTH AND DIETARY INTAKE DURING PREGNANCY

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Table 1. Mothers and newborns characteristics, including maternal and cord levels of IGFs

and lipids

Maternal characteristics

Age (years) Mean (SD) 28.5 (5.4)

Education (years) Median (IR) 10 (7; 12)

Ever smoking during pregnancy n (%) 47 (24.6)

Gravidity (=1) n (%) 106 (54.1)

Pre-pregnancy BMI (kg/m2) Median (IR) 23.7 (21.4; 26.3)

Pre-pregnancy weight (kg) Mean (SD) 63.4 (13.9)

Weight gain during pregnancy (kg) Mean (SD) 13.7 (5.8)

IGF-1 (ng/ml) Median (IR) 244.0 (150.0; 339.0)

IGF-2 (ng/ml) Median (IR) 998.0 (770.4; 1249.3)

IGFBP-3 (mcg/ml) Median (IR) 4.6 (3.6; 5.5)

Newborn characteristics

Gender (male) n (%) 98 (50.0)

Gestational age (weeks) Mean (SD) 39.4 (1.2)

Birth weight (g)

Low birth weight (<2500g)

Adequate birth weight (2500<BW<4000g)

Macrossomic (>3999g)

Median (IR)

2395 (2290; 2450)

3217 (3010; 3486)

4130 (4080; 4260)

IGF-1 (ng/ml) Median (IR) 63.4 (40.7; 79.3)

IGF-2 (ng/ml) Median (IR) 444.8 (355.7; 514.6)

IGFBP-3 (mcg/ml) Median (IR) 1.4 (1.2; 1.6)

Total cholesterol (g/L) Median (IR) 0.62 (0.50; 0.73)

HDL cholesterol (g/L) Median (IR) 0.25 (0.21; 0.30)

Triglycerides (g/L) Median (IR) 0.35 (0.27; 0.46)

BMI – body mass index, SD – standard deviation; IR – interquartile range, BW – birth weight

* Corresponding median (IQR) in each birth weight category were 45.5 (44.8; 47.0), 49.5 (48.0; 50.5) and 52.0

(51.0; 52.6) cm for birth length; 24.8 (23.5; 26.7), (26.5 (25.4; 28.4) and 29.7 (28.5; 31.3) kg/m3 for PI; and 32.5

(31.5; 33.4), 34.0 (34.0; 35.5) and 36.0 (35.4; 37.0) cm for head circumference.

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Table 2. Correlation coefficients between maternal and cord IGFs and lipids levels, and birth size measures

Newborn Mother

IGF-1 IGF-2 IGFBP-3 Total c HDLc TG IGF-1 IGF-2 IGFBP-3 BW BL HC PI

Ne

wb

orn

IGF-1 1 0.32** 0.81** 0.10 0.31** -0.45** 0.32** 0.08 0.20* 0.53** 0.44** 0.42** 0.39**

IGF-2 1 0.45** 0.05 0.22** -0.23** 0.28** 0.16* 0.19* 0.26** 0.26** 0.24** 0.14

IGFBP-3 1 0.12 0.21** -0.22** 0.38**

0.08 0.24* 0.48** 0.43** 0.39** 0.30**

Total c 1 0.68** 0.06 0.13 0.16* 0.21** -0.08 -0.11 -0.02 0.00

HDLc 1 -0.29** 0.13 0.07 0.11 0.01 -0.02 0.06 0.06

TG 1 -0.04 -0.05 0.01 0.01 -0.06 -0.17* -0.13

Mo

the

r

IGF-1 1 0.33** 0.73** 0.33** 0.31** 0.22** 0.20**

IGF-2 1 0.57** <0.01 0.06 -0.03 -0.10

IGFBP-3 1 0.10 0.11 0.08 0.03

Total c – total cholesterol; HDLc – HDL cholesterol; TG – triglycerides; BW – birth weight; BL – birth length; HC – head circumference; PI – ponderal index

** P<0.01; *P<0.05

Levels of IGFs and IGFBP-3 were log-transformed to achieve normality

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Table 3. Associations between cord and maternal blood levels of IGF-1, IGF-2 and IGFBP-3 on birth size

Birth weight

(cm)

Birth length

(cm)

Head circumference

(cm)

Ponderal index

(m/kg3)

Model I

β (95% CI)

Newborn IGF-1 (SD) 319.6 (237.3; 401.9) 1.24 (0.96; 1.53) 0.83 (0.59; 1.07) 0.32 (0.07; 0.56)

Newborn IGF-2 (SD) 110.1 (26.7; 193.5) 0.58 (0.26; 0.91) 0.30 (0.04; 0.56) 0.04 (-0.24; 0.31)

Newborn IGFBP-3 (SD) 241.0 (151.7; 330.1) 1.12 (0.82; 1.43) 0.70 (0.44; 0.95) 0.25 (-0.23; 0.73)

Maternal IGF-1 (SD) 75.4 (-13.8; 164.6) 0.49 (0.15; 0.84) 0.17 (-0.09; 0.43) 0.00 (-0.04; 0.04)

Maternal IGF-2 (SD) 19.6 (-69.1; 108.4) 0.25 (-0.09; 0.58) 0.03 (-0.23; 0.29) -0.02 (-0.06; 0.03)

Maternal IGFBP-3 (SD) 23.8 (-60.9; 108.6) 0.22 (-0.11; 0.55) 0.10 (-0.15; 0.35) -0.01 (-0.05; 0.04)

Model II

β (95% CI)

Newborn IGF-1 (SD) 342.2 (214.2; 476.3) 1.01 (0.54; 1.48) 0.76 (0.36; 1.16) 0.11 (0.03; 0.19)

Newborn IGF-2 (SD) 27.6 (-56.4; 111.6) 0.19 (-0.12; 0.50) 0.08 (-0.18; 0.34) -0.00 (-0.05; 0.05)

Newborn IGFBP-3 (SD) -39.0 (-177.5; 99.4) 0.23 (-0.27; 0.74) 0.05 (-0.37; 0.48) -0.56 (-1.36; 0.24)

Maternal IGF-1 (SD) 147.8 (3.2; 292.3) 0.80 (0.27; 1.34) 0.21 (-0.21; 0.63) 0.01 (-0.06; 0.08)

Maternal IGF-2 (SD) 0.7 (-118.4; 119.7) 0.21 (-0.24; 0.66) -0.09 (-0.44; 0.26) -0.03 (-0.09; 0.03)

Maternal IGFBP-3 (SD) -87.2 (-242.8; 68.3) -0.49 (-1.07; 0.009) 0.00 (-0.45; 0.45) 0.01 (-0.07; 0.08)

Model III

β (95% CI)

Newborn IGF-1 (SD) 371.3 (286.9; 455.8) 1.29 (0.96; 1.62) 0.85 (0.58; 1.12) 0.09 (0.04; 0.14)

Maternal IGF-1 (SD) -14.3 (-88.0; 59.3) 0.09 (-0.21; 0.40) -0.07 (-0.31; 0.18) -0.02 (-0.06; 0.03)

Levels of IGF-1, IGF-2 and IGFBP-3 were log-transformed

β (95% CI) – Change in BW, BL, HC and PI per one SD increment in log IGFs/IGFBP-3 cord levels (95% confidence interval); SD – standard deviation

Model 1: BW analyses: adjusted for maternal pre-pregnancy BMI, maternal weight gain, gestation length, and newborn gender; BL, HC, PI analyses: adjusted for

maternal pre-pregnancy BMI, gestation length, and newborn gender

Model 2: Cord (and maternal) effects adjusted for all variables considered in model 1 and for the other two cord (or maternal) IGFs in the same group

Model 3: Cord and maternal IGF-1 effects adjusted for all variables considered in model 1 and mutually for each other

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Table 4. Independent effects of cord IGF-1 levels and birth size on cord lipid levels

Total cholesterol

(g/L)

HDLc

(g/L)

TG

(g/L)

IGF-1 (SD)ϕ

β (95% CI)a -0.01 (-0.02; 0.02) 0.01 (0.00; 0.01) -0.06 (-0.08; -0.04)

β (95% CI)b -0.01 (-0.03; 0.02) 0.01 (0.00; 0.02) -0.06 (-0.09; -0.03)

β (95% CI)c -0.00 (-0.02; 0.02) 0.01 (0.00; 0.02) -0.06 (-0.09; -0.03)

β (95% CI)d -0.00 (-0.02; 0.02) 0.01 (0.00; 0.02) -0.05 (-0.08; -0.03)

β (95% CI)e -0.01 (-0.02; 0.01) 0.01 (0.00; 0.02) -0.06 (-0.08; -0.03)

Birth weight (SD)

β (95% CI)a 0.00 (-0.03; 0.02) 0.00 (-0.01; 0.01) -0.05 (-0.07; -0.02)

β (95% CI)f 0.01 (-0.02; 0.03) -0.01 (-0.02; 0.00) 0.01 (-0.04; 0.03)

Birth length (SD)

β (95% CI)a -0.01 (-0.03; 0.02) 0.01 (-0.01; 0.01) -0.04 (-0.07; -0.01)

β (95% CI)f 0.01 (-0.02; 0.02) -0.00 (-0.01; 0.01) 0.00 (-0.03; 0.03)

Head circumference (SD)

β (95% CI)a 0.01 (-0.01; 0.03) 0.00 (-0.01; 0.01) -0.05 (-0.07; -0.02)

β (95% CI)f 0.01 (-0.01; 0.03) -0.00 (-0.01; 0.01) -0.02 (-0.05; 0.01)

Ponderal index (SD)

β (95% CI)a 0.00 (-0.02; 0.02) 0.00 (-0.01; 0.01) -0.03 (-0.05; -0.00)

β (95% CI)f 0.01 (-0.01; 0.02) -0.00 (-0.01; 0.00) -0.01 (-0.03; 0.02)

ϕ Variable log-transformed; SD – standard deviation

β (95% CI) – Change in cord levels of total cholesterol, HDLc and TG associated with one SD increment in log

IGF-1 cord levels and with one SD increment in BW, BL, HC and PI aAdjusted for gestational length and newborn gender, and for the other two cord lipids

bAs (a) but further adjusted BW

cAs (a) but further adjusted for BL

dAs (a) but further adjusted for g HC

eAs (a) but further adjusted for PI

fAdjusted for gestational length, newborn gender, cord IGF-1 and the other two cord lipids

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Figure 1. Hypothetical mechanisms underlying the fetal origins of adult hypercholesterolemia

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