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Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts
by
Parmar, Priyanka
, Prokopenko, Inga
, Järvelin, Marjo-Riitta
, Ala-Mursula, Leena
, Jaddoe, Vincent WV
, El Marroun, Hanan
, Vehmeijer, Florianne
, Miettunen, Jouko
, Tzala, Evangelia
, Lowry, Estelle
, Rautio, Nina
, Sebert, Sylvain
, Lewin, Alex
, Tolvanen, Mimmi
, Herzig, Karl-Heinz
, Felix, Janine
in
Adult
/ Ageing
/ Alcohol use
/ Biostatistics
/ Birth defects
/ Birth Weight
/ Births
/ Blood pressure
/ Body Mass Index
/ Cardiovascular disease
/ Child health
/ Cohort analysis
/ Cohort studies
/ Diabetes
/ Disability
/ Epidemiology of chronic non communicable diseases
/ Ethics
/ Ethnicity
/ Factor analysis
/ Female
/ Finland
/ Gestational Age
/ Humans
/ Life course epidemiology
/ Male
/ Maternal health
/ Mothers
/ Netherlands
/ Original Research
/ Population
/ Pregnancy
/ Questionnaires
/ Risk Factors
/ Socioeconomic Factors
/ Socioeconomics
/ Variables
2020
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Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts
by
Parmar, Priyanka
, Prokopenko, Inga
, Järvelin, Marjo-Riitta
, Ala-Mursula, Leena
, Jaddoe, Vincent WV
, El Marroun, Hanan
, Vehmeijer, Florianne
, Miettunen, Jouko
, Tzala, Evangelia
, Lowry, Estelle
, Rautio, Nina
, Sebert, Sylvain
, Lewin, Alex
, Tolvanen, Mimmi
, Herzig, Karl-Heinz
, Felix, Janine
in
Adult
/ Ageing
/ Alcohol use
/ Biostatistics
/ Birth defects
/ Birth Weight
/ Births
/ Blood pressure
/ Body Mass Index
/ Cardiovascular disease
/ Child health
/ Cohort analysis
/ Cohort studies
/ Diabetes
/ Disability
/ Epidemiology of chronic non communicable diseases
/ Ethics
/ Ethnicity
/ Factor analysis
/ Female
/ Finland
/ Gestational Age
/ Humans
/ Life course epidemiology
/ Male
/ Maternal health
/ Mothers
/ Netherlands
/ Original Research
/ Population
/ Pregnancy
/ Questionnaires
/ Risk Factors
/ Socioeconomic Factors
/ Socioeconomics
/ Variables
2020
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Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts
by
Parmar, Priyanka
, Prokopenko, Inga
, Järvelin, Marjo-Riitta
, Ala-Mursula, Leena
, Jaddoe, Vincent WV
, El Marroun, Hanan
, Vehmeijer, Florianne
, Miettunen, Jouko
, Tzala, Evangelia
, Lowry, Estelle
, Rautio, Nina
, Sebert, Sylvain
, Lewin, Alex
, Tolvanen, Mimmi
, Herzig, Karl-Heinz
, Felix, Janine
in
Adult
/ Ageing
/ Alcohol use
/ Biostatistics
/ Birth defects
/ Birth Weight
/ Births
/ Blood pressure
/ Body Mass Index
/ Cardiovascular disease
/ Child health
/ Cohort analysis
/ Cohort studies
/ Diabetes
/ Disability
/ Epidemiology of chronic non communicable diseases
/ Ethics
/ Ethnicity
/ Factor analysis
/ Female
/ Finland
/ Gestational Age
/ Humans
/ Life course epidemiology
/ Male
/ Maternal health
/ Mothers
/ Netherlands
/ Original Research
/ Population
/ Pregnancy
/ Questionnaires
/ Risk Factors
/ Socioeconomic Factors
/ Socioeconomics
/ Variables
2020
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Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts
Journal Article
Understanding the cumulative risk of maternal prenatal biopsychosocial factors on birth weight: a DynaHEALTH study on two birth cohorts
2020
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Overview
BackgroundThere are various maternal prenatal biopsychosocial (BPS) predictors of birth weight, making it difficult to quantify their cumulative relationship.MethodsWe 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.ResultsFactor 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.ConclusionOur 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.
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