Co-causation of reduced newborn size by maternal undernutrition, infections, and inflammation.

Per Ashorn; Lotta Hallamaa; Lindsay H Allen; Ulla Ashorn; Upeksha Chandrasiri; Megan Deitchler; Ronan Doyle ORCID logo; Ulla Harjunmaa; Josh M Jorgensen; Steve Kamiza; +9 more... Nigel Klein; Kenneth Maleta; Minyanga Nkhoma; Brietta M Oaks ORCID logo; Basho Poelman ORCID logo; Stephen J Rogerson; Christine P Stewart; Mamane Zeilani; Kathryn G Dewey; (2018) Co-causation of reduced newborn size by maternal undernutrition, infections, and inflammation. MATERNAL AND CHILD NUTRITION, 14 (3). e12585-. ISSN 1740-8695 DOI: 10.1111/mcn.12585
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More than 20 million babies are born with low birthweight annually. Small newborns have an increased risk for mortality, growth failure, and other adverse outcomes. Numerous antenatal risk factors for small newborn size have been identified, but individual interventions addressing them have not markedly improved the health outcomes of interest. We tested a hypothesis that in low-income settings, newborn size is influenced jointly by multiple maternal exposures and characterized pathways associating these exposures with newborn size. This was a prospective cohort study of pregnant women and their offspring nested in an intervention trial in rural Malawi. We collected information on maternal and placental characteristics and used regression analyses, structural equation modelling, and random forest models to build pathway maps for direct and indirect associations between these characteristics and newborn weight-for-age Z-score and length-for-age Z-score. We used multiple imputation to infer values for any missing data. Among 1,179 pregnant women and their babies, newborn weight-for-age Z-score was directly predicted by maternal primiparity, body mass index, and plasma alpha-1-acid glycoprotein concentration before 20 weeks of gestation, gestational weight gain, duration of pregnancy, placental weight, and newborn length-for-age Z-score (p < .05). The latter 5 variables were interconnected and were predicted by several more distal determinants. In low-income conditions like rural Malawi, maternal infections, inflammation, nutrition, and certain constitutional factors jointly influence newborn size. Because of this complex network, comprehensive interventions that concurrently address multiple adverse exposures are more likely to increase mean newborn size than focused interventions targeting only maternal nutrition or specific infections.


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