Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts

Priyanka Parmar; Estelle Lowry; Florianne Vehmeijer; Hanan El Marroun; Alex Lewin; Mimmi Tolvanen; Evangelia Tzala; Leena Ala-Mursula; Karl-Heinz Herzig; Jouko Miettunen; Inga Prokopenko; Nina Rautio; Vincent Wv Jaddoe; Marjo-Riitta Järvelin; Janine Felix; Sylvain Sebert

doi:10.1136/jech-2019-213154

Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts

J Epidemiol Community Health. 2020 Nov;74(11):933-941. doi: 10.1136/jech-2019-213154. Epub 2020 Jun 24.

Authors

Priyanka Parmar¹, Estelle Lowry², Florianne Vehmeijer^{3

4

5}, Hanan El Marroun^{5

6

7}, Alex Lewin⁸, Mimmi Tolvanen¹, Evangelia Tzala⁹, Leena Ala-Mursula¹, Karl-Heinz Herzig^{10

11}, Jouko Miettunen^{1

10}, Inga Prokopenko^{12

13}, Nina Rautio^{1

14}, Vincent Wv Jaddoe^{3

4

5}, Marjo-Riitta Järvelin^{15

9

16

17}, Janine Felix^{3

4

5}, Sylvain Sebert^{15

9}

Affiliations

¹ Center for Life Course Health Research, University of Oulu, Oulu, Finland.
² School of Natural and Built Environment, Queen's University Belfast, Belfast, UK.
³ Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands.
⁴ The Generation R Study Group, Erasmus Medical Centre, Rotterdam, The Netherlands.
⁵ Department of Pediatrics, Erasmus Medical Centre, Rotterdam, The Netherlands.
⁶ Department of Child and Adolescent Psychiatry, Erasmus MC - Sophia Children's Hospital, Rotterdam, The Netherlands.
⁷ Department of Psychology, Education and Child Studies, Erasmus School of Social and Behavioral Sciences, Erasmus University Rotterdam, Rotterdam, The Netherlands.
⁸ Department of Medical Statistics, London School of Hygiene and Tropical Medicine, Faculty of Epidemiology and Population Health, London, UK.
⁹ Department of Epidemiology and Bio-statistics, School of Public Health, Imperial College London, London, UK.
¹⁰ Medical Research Center (MRC) Oulu, University of Oulu, Oulu, Finland.
¹¹ Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland.
¹² Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Guildford, UK.
¹³ Department of Metabolism, Digestion and Reproduction, Genomic Medicine, Faculty of Medicine, Imperial College London, London, UK.
¹⁴ Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland.
¹⁵ Center for Life Course Health Research, University of Oulu, Oulu, Finland sylvain.sebert@oulu.fi m.jarvelin@imperial.ac.uk.
¹⁶ MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.
¹⁷ Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK.

Abstract

Background: There are various maternal prenatal biopsychosocial (BPS) predictors of birth weight, making it difficult to quantify their cumulative relationship.

Methods: We studied two birth cohorts: Northern Finland Birth Cohort 1986 (NFBC1986) born in 1985-1986 and the Generation R Study (from the Netherlands) born in 2002-2006. In NFBC1986, we selected variables depicting BPS exposure in association with birth weight and performed factor analysis to derive latent constructs representing the relationship between these variables. In Generation R, the same factors were generated weighted by loadings of NFBC1986. Factor scores from each factor were then allocated into tertiles and added together to calculate a cumulative BPS score. In all cases, we used regression analyses to explore the relationship with birth weight corrected for sex and gestational age and additionally adjusted for other factors.

Results: Factor analysis supported a four-factor structure, labelled closely to represent their characteristics as 'Factor1-BMI' (body mass index), 'Factor2-DBP' (diastolic blood pressure), 'Factor3-Socioeconomic-Obstetric-Profile' and 'Factor4-Parental-Lifestyle'. In both cohorts, 'Factor1-BMI' was positively associated with birth weight, whereas other factors showed negative association. 'Factor3-Socioeconomic-Obstetric-Profile' and 'Factor4-Parental-Lifestyle' had the greatest effect size, explaining 30% of the variation in birth weight. Associations of the factors with birth weight were largely driven by 'Factor1-BMI'. Graded decrease in birth weight was observed with increasing cumulative BPS score, jointly evaluating four factors in both cohorts.

Conclusion: Our study is a proof of concept for maternal prenatal BPS hypothesis, highlighting the components snowball effect on birth weight in two different European birth cohorts.

Keywords: Ageing; Biostatistics; Birth defects; Birth weight; Cardiovascular disease; Child health; Cohort studies; Diabetes; Disability; Epidemiology of chronic non communicable diseases; Life course epidemiology; Maternal health.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Birth Weight*
Body Mass Index
Female
Finland
Gestational Age
Humans
Male
Netherlands
Pregnancy
Risk Factors
Socioeconomic Factors*

Abstract

Publication types

MeSH terms

Grants and funding