ArticleBMC pregnancy and childbirth2025
Non-linear association of low birthweight with risk factors including women's BMI: evidence from an international comparison.
Article in BMC pregnancy and childbirth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Machine learning based prediction of low birth weight and its associated risk factors: Insights from the Bangladesh Demographic and Health Survey 2022.PLOS global public health · 2025Article
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Abstract
backgroundIt is widely known that, in addition to physical characteristics such as parents' height and weight, social attributes such as parents' education, income level, and employment status have a significant impact on birthweight. However, these results were obtained using data from individual countries, and there were no country-level comparisons of the factors identified as influencing birthweight. A multi-country analysis is essential to determine whether these factors are consistently linked to low birthweight across different economic and healthcare systems.
methodsUsing panel data on low-birthweight fertility rates for 143 countries over the period of 2000-2015, we used five factors (women's body mass index [BMI], real gross domestic product [GDP] per capita, women's employment status, healthcare level, and adolescent childbearing) in relation to countries' low-birthweight rates to determine how these factors relate to each country's low-birthweight rate and estimate a fixed-effects model. Considering the possibility that these five factors are non-linear rather than linear, we estimated quadratic and cubic functions. We conducted a detailed analysis of women's BMI and real GDP per capita. Furthermore, we considered the 2008 global financial crisis as an exogenous natural experiment for the low-birthweight rate and conducted a difference-in-differences (DID) analysis to confirm the possibility that the correlation between women's employment rate and low-birthweight rate is a causal relationship.
resultsAll five factors were identified as important risk factors. Of the five, all but adolescent childbearing were found to have a non-linear rather than a monotonous linear relationship with low birthweight. The low-birthweight rate improved sharply with improvement in women's average BMI below 28. Furthermore, the results of the DID analysis suggest that women's employment plays an important role in the relationship between low-birthweight rates and GDP.
conclusionsThese results provide a useful policy tool for achieving the goal of the 65th World Health Assembly to "reduce the incidence of low birthweight." In particular, improvements in women's average BMI, real GDP per capita, and women's employment rates in low-income countries may be linked to reductions in the incidence of low birthweight.
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