Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts
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 N...
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Online Access: | http://dx.doi.org/10.1136/jech-2019-213154 https://syndication.highwire.org/content/doi/10.1136/jech-2019-213154 |
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crjcrbmj:10.1136/jech-2019-213154 2024-06-23T07:55:31+00:00 Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts 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 EU Horizon 2020 Academy of Finland 2020 http://dx.doi.org/10.1136/jech-2019-213154 https://syndication.highwire.org/content/doi/10.1136/jech-2019-213154 en eng BMJ http://creativecommons.org/licenses/by-nc/4.0/ Journal of Epidemiology and Community Health volume 74, issue 11, page 933-941 ISSN 0143-005X 1470-2738 journal-article 2020 crjcrbmj https://doi.org/10.1136/jech-2019-213154 2024-06-06T04:15:15Z 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. Article in Journal/Newspaper Northern Finland The BMJ Journal of Epidemiology and Community Health jech-2019-213154 |
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The BMJ |
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crjcrbmj |
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English |
description |
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. |
author2 |
EU Horizon 2020 Academy of Finland |
format |
Article in Journal/Newspaper |
author |
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 |
spellingShingle |
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 Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts |
author_facet |
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 |
author_sort |
Parmar, Priyanka |
title |
Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts |
title_short |
Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts |
title_full |
Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts |
title_fullStr |
Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts |
title_full_unstemmed |
Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts |
title_sort |
understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a dynahealth study on two birth cohorts |
publisher |
BMJ |
publishDate |
2020 |
url |
http://dx.doi.org/10.1136/jech-2019-213154 https://syndication.highwire.org/content/doi/10.1136/jech-2019-213154 |
genre |
Northern Finland |
genre_facet |
Northern Finland |
op_source |
Journal of Epidemiology and Community Health volume 74, issue 11, page 933-941 ISSN 0143-005X 1470-2738 |
op_rights |
http://creativecommons.org/licenses/by-nc/4.0/ |
op_doi |
https://doi.org/10.1136/jech-2019-213154 |
container_title |
Journal of Epidemiology and Community Health |
container_start_page |
jech-2019-213154 |
_version_ |
1802648159366676480 |