Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts. Issue 11 (24th June 2020)

• Record Type: Journal Article
• Authors: Parmar, Priyanka; Lowry, Estelle; Vehmeijer, Florianne; El Marroun, Hanan; Lewin, Alex; Tolvanen, Mimmi; Tzala, Evangelia; Ala-Mursula, Leena; Herzig, Karl-Heinz; Miettunen, Jouko; Prokopenko, Inga; Rautio, Nina; Jaddoe, Vincent WV; Järvelin, Marjo-Riitta; Felix, Janine; Sebert, Sylvain
• Is Part Of: Journal of epidemiology and community health. Volume 74:Issue 11(2020)
• Page Start: 933
• Page End: 941
• Publication Date: 2020-06-24
• Subjects: Ageing -- Diabetes -- Disability -- Child health -- Maternal health -- Birth defects -- Cardiovascular disease -- Birth weight -- Epidemiology of chronic non communicable diseases -- Life course epidemiology -- Cohort studies -- Biostatistics; Public health -- Periodicals; Epidemiology -- Periodicals; 614.4
• DOI: 10.1136/jech-2019-213154
• Languages: English
• ISSNs: 0143-005X

Abstract

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.