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Original Investigation |

Fish Intake in Pregnancy and Child Growth A Pooled Analysis of 15 European and US Birth Cohorts

Nikos Stratakis, MSc1,2; Theano Roumeliotaki, MPH1; Emily Oken, MD3; Henrique Barros, PhD4,5; Mikel Basterrechea6,7; Marie-Aline Charles, MD8,9; Merete Eggesbø, PhD10; Francesco Forastiere, PhD11; Romy Gaillard, PhD12; Ulrike Gehring, PhD13; Eva Govarts, MSc14; Wojciech Hanke, PhD15; Barbara Heude, PhD8,9; Nina Iszatt, PhD10; Vincent W. Jaddoe, PhD12; Cecily Kelleher, DMed16; Monique Mommers, PhD17; Mario Murcia, MSc7,18; Andreia Oliveira, PhD6,7; Costanza Pizzi, PhD19; Kinga Polańska, PhD17; Daniela Porta, MSc13; Lorenzo Richiardi, PhD19; Sheryl L. Rifas-Shiman, MPH3; Greet Schoeters, PhD20,21; Jordi Sunyer, PhD7,22,23; Carel Thijs, PhD17; Karien Viljoen, PhD16; Martine Vrijheid, PhD7,22,24; Tanja G. M. Vrijkotte, PhD25; Alet H. Wijga, PhD26; Maurice P. Zeegers, PhD2,27; Manolis Kogevinas, PhD7,28,29,30; Leda Chatzi, PhD1
[+] Author Affiliations
1Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Greece
2Section of Complex Genetics, Department of Genetics and Cell Biology, NUTRIM School of Nutrition and Translational Research in Metabolism, Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Centre+, Maastricht, Netherlands
3Obesity Prevention Program, Harvard Pilgrim Health Care Institute, Department of Population Medicine, Harvard Medical School, Boston, Massachusetts
4Department of Clinical Epidemiology, Predictive Medicine and Public Health, University of Porto Medical School, Porto, Portugal
5Epidemology Research Unit, Institute of Public Health, University of Porto, Porto, Portugal
6Public Health Division of Gipuzkoa, Basque Government; Health Research Institute, Biodonostia, San Sebastián, Spain
7Centros de Investigación Biomédica en Red Epidemiología y Salud Pública, Spain
8Centre for Research in Epidemiology and Biostatistics Paris Sorbonne Cité, Institut National de la Santé et de la Recherche Médicale, Early Origin of the Child Development and Health Team, Villejuif, France
9Université Paris Descartes, Villejuif, France
10Norwegian Institute of Public Health, Oslo, Norway
11Department of Epidemiology, Lazio Regional Health System, Rome, Italy
12Generation R Study Group, Department of Epidemiology, Erasmus University Medical Centre, Rotterdam, Netherlands
13Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
14Environmental Risk and Health, Flemish Institute for Technological Research, Mol, Belgium
15Department of Environmental Epidemiology, Nofer Institute of Occupational Medicine, Lodz, Poland
16School of Public Health, Physiotherapy, and Population Science, University College Dublin, Dublin, Ireland
17Department of Epidemiology, CAPHRI School for Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Centre+, Maastricht, Netherlands
18Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana–Universitat Jaume I, Universitat de València Joint Research Unit of Epidemiology and Environmental Health, Valencia, Spain
19Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin and Reference Centre for Epidemiology and Cancer Prevention in Piemonte, Turin, Italy
20Environmental Risk and Health, Flemish Institute for Technological Research, Mol, Belgium
21University of Antwerp, Antwerp, Belgium; University of Southern Denmark, Odense, Denmark
22Centre for Research in Environmental Epidemiology, Barcelona, Spain
23Pompeu Fabra University, Barcelona, Spain
24Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Spain
25Department of Public Health, Academic Medical Centre, University of Amsterdam, Amsterdam, Netherlands
26Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, Netherlands
27CAPHRI School for Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Centre+, Maastricht, Netherlands
28Centre for Research in Environmental Epidemiology, Barcelona, Spain
29Institut Hospital del Mar d'Investigacions Mèdiques, Barcelona, Spain
30National School of Public Health, Athens, Greece
JAMA Pediatr. 2016;170(4):381-390. doi:10.1001/jamapediatrics.2015.4430.
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Importance  Maternal fish intake in pregnancy has been shown to influence fetal growth. The extent to which fish intake affects childhood growth and obesity remains unclear.

Objective  To examine whether fish intake in pregnancy is associated with offspring growth and the risk of childhood overweight and obesity.

Design, Setting, and Participants  Multicenter, population-based birth cohort study of singleton deliveries from 1996 to 2011 in Belgium, France, Greece, Ireland, Italy, the Netherlands, Norway, Poland, Portugal, Spain, and Massachusetts. A total of 26 184 pregnant women and their children were followed up at 2-year intervals until the age of 6 years.

Exposures  Consumption of fish during pregnancy.

Main Outcomes and Measures  We estimated offspring body mass index percentile trajectories from 3 months after birth to 6 years of age. We defined rapid infant growth as a weight gain z score greater than 0.67 from birth to 2 years and childhood overweight/obesity at 4 and 6 years as body mass index in the 85th percentile or higher for age and sex. We calculated cohort-specific effect estimates and combined them by random-effects meta-analysis.

Results  This multicenter, population-based birth cohort study included the 26 184 pregnant women and their children. The median fish intake during pregnancy ranged from 0.5 times/week in Belgium to 4.45 times/week in Spain. Women who ate fish more than 3 times/week during pregnancy gave birth to offspring with higher body mass index values from infancy through middle childhood compared with women with lower fish intake (3 times/week or less). High fish intake during pregnancy (>3 times/week) was associated with increased risk of rapid infant growth, with an adjusted odds ratio (aOR) of 1.22 (95% CI, 1.05-1.42) and increased risk of offspring overweight/obesity at 4 years (aOR, 1.14 [95% CI, 0.99-1.32]) and 6 years (aOR, 1.22 [95% CI, 1.01-1.47]) compared with an intake of once per week or less. Interaction analysis showed that the effect of high fish intake during pregnancy on rapid infant growth was greater among girls (aOR, 1.31 [95% CI, 1.08-1.59]) than among boys (aOR, 1.11 [95% CI, 0.92-1.34]; P = .02 for interaction).

Conclusions and Relevance  High maternal fish intake during pregnancy was associated with increased risk of rapid growth in infancy and childhood obesity. Our findings are in line with the fish intake limit proposed by the US Food and Drug Administration and Environmental Protection Agency.

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Figure 1.
Frequency of Fish Intake in Pregnancy (Times/Week) in Participating Cohorts

The line within the box marks the median; the boundaries of the box indicate the 25th and 75th percentiles; horizontal bars denote the variability outside the upper and lower quartiles (ie, within 1.5 IQR of the lower and upper quartiles); and circles represent outliers. Cohort abbreviations: ABCD, Amsterdam Born Children and their Development; EDEN, Étude des Déterminants Pré et Postnatals du Développement et de la Santé de l’Enfant; FLEHS I, Flemish Center of Expertise on Environment and Health; GASPII, Genetics and Environment Prospective Study on Childhood in Italy; HUMIS, Human Milk Study; INMA, Infancia y Medio Ambiente; KOALA, Kind, Ouders, en Gezondheid: Aandacht voor Leefstijl en Aanleg Birth Cohort Study; NINFEA, Nascita e INFanzia: gli Effetti dell’Ambiente; PIAMA, Prevention and Incidence of Asthma and Mite Allergy; REPRO, Polish Mother and Child Cohort Study; RHEA, Mother Child Cohort in Crete.

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Figure 2.
Adjusted Associations of Fish Intake in Pregnancy With Rapid Growth in Infancy and Childhood Overweight/Obesity

Rapid growth was defined as a weight gain z score greater than 0.67 based on World Health Organization (WHO) growth curves. Overweight/obesity was defined as body mass index in the 85th percentile or higher for age and sex based on WHO growth curves. Odds ratios (95% CIs) by cohort were obtained by using logistic regression models adjusted for maternal age, maternal education, prepregnancy body mass index, smoking during pregnancy, and birth weight. Reference category was fish intake 1 or more times/week. Combined estimates were obtained by using a random-effects meta-analysis. The names of the cohorts and the cohort-specific ORs (95% CIs) are shown on the left, and weights of each study are shown on the right. The squares represent the point estimate of each study, whereas the size of the square is proportional to the weight assigned to each cohort based on both the within- and between-study variability; horizontal lines denote 95% CIs; and diamonds represent overall estimates. Cohort abbreviations: ABCD, Amsterdam Born Children and their Development; EDEN, Étude des Déterminants Pré et Postnatals du Développement et de la Santé de l’Enfant; FLEHS I, Flemish Center of Expertise on Environment and Health; GASPII, Genetics and Environment Prospective Study on Childhood in Italy; HUMIS, Human Milk Study; INMA, Infancia y Medio Ambiente; KOALA, Kind, Ouders, en Gezondheid: Aandacht voor Leefstijl en Aanleg Birth Cohort Study; NINFEA, Nascita e INFanzia: gli Effetti dell’Ambiente; PIAMA, Prevention and Incidence of Asthma and Mite Allergy; REPRO, Polish Mother and Child Cohort Study; RHEA, Mother Child Cohort in Crete.

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Figure 3.
Body Mass Index (BMI) Percentile Trajectories From 3 Months to 6 Years According to Different Levels of Fish Intake in Pregnancy

BMI percentile values indicate the place of children in the corresponding growth chart of the World Health Organization reference population (eMethods in the Supplement) and were derived by using mixed-effects linear regression models fitted with: fish intake, an interaction term for fish intake and child age, maternal age, maternal education, prepregnancy BMI, smoking during pregnancy, and birth weight as fixed-effects parameters; random cohort and child intercepts; and a random slope for child age.

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