Maternal health and birth outcomes in a South African birth cohort study

Zar, Heather J.; Pellowski, Jennifer; Cohen, Sophie; Barnett, Whitney; Vanker, Aneesa; Koen, Nastassja; Stein, Dan J.

doi:10.1371/journal.pone.0222399

Cited by 49 publications

(70 citation statements)

References 35 publications

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“…18 Similarly, a cohort study in urban South Africa found an independent association between food insecurity and gestational age. 19 Another study in the USA found an association between food insecurity and preterm birth among parous women. 20 There are a number of plausible pathways by which food insecurity may increase risk of preterm birth.…”

Section: Resultsmentioning

confidence: 99%

Food insecurity as a risk factor for preterm birth: a prospective facility-based cohort study in rural Haiti

Richterman

Raymonville²,

Hossain

et al. 2020

BMJ Glob Health

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IntroductionHaiti has an estimated neonatal mortality rate of 32/1000 live births, the highest in the Western Hemisphere. Preterm birth and being born small for gestational age (SGA) are major causes of adverse neonatal outcomes worldwide. To reduce preterm birth and infants born SGA, it is important to understand which women are most at risk and how risk varies within countries. There are few studies estimating the prevalence and risk factors for these conditions in Haiti, particularly in rural regions.MethodsWe conducted a prospective cohort study of pregnant women at a rural tertiary care centre in Haiti from May to December 2017. We collected data during interviews and from the medical record. We built multivariable models to identify risk factors for preterm birth and being born SGA among women who had a facility-based delivery.Results1089 pregnant women delivered at the hospital and were included in this analysis. Median gestational age at delivery was 38 weeks (IQR 36–40). In multivariable analyses, risk factors for preterm birth included maternal age <20 years (adjusted OR (AOR) 1.76, 95% CI 1.14 to 2.72) and >34 years (AOR 1.46, 95% CI 1.01 to 2.11) and severe hunger in the household (AOR 1.57, 95% CI 1.09 to 2.26). Risk factors for SGA were age >34 years (AOR 1.76, 95% CI 1.18 to 2.59), twin pregnancy (AOR 3.28, 95% CI 1.20 to 8.95) and first pregnancy (AOR 1.57, 95% CI 1.12 to 2.23). Number of prior abortions was associated with reduced risk for SGA (AOR 0.41, 95% CI 0.17 to 0.97).ConclusionsFood insecurity as a risk factor for preterm birth stands out as an important addition to the understanding of the risk of neonatal morbidity and mortality. This association highlights a potentially important intervention target to improve birth outcomes and suggests that food support has an important role to play for pregnant women who are food insecure in low-income settings.

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Section: Resultsmentioning

confidence: 99%

Food insecurity as a risk factor for preterm birth: a prospective facility-based cohort study in rural Haiti

Richterman

Raymonville²,

Hossain

et al. 2020

BMJ Glob Health

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show abstract

“…It must be noted that owing to the history of apartheid in South Africa, these study sites are culturally different with respect to ancestry and language. Socioeconomic status is measured based on a composite score of asset ownership, household income, employment and education, adapted from items used in the South African Stress and Health Study (SASH) [ 19 ]. A score below the median are referred to as lower socioeconomic status, while scores above the median are referred to as a higher socioeconomic status.…”

Section: Methodsologymentioning

confidence: 99%

Flexible modelling of risk factors on the incidence of pneumonia in young children in South Africa using piece-wise exponential additive mixed modelling

Ramjith

Roes

Zar

et al. 2021

BMC Med Res Methodol

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Introduction Recurrent episodes of pneumonia are frequently modeled using extensions of the Cox proportional hazards model with the underlying assumption of time-constant relative risks measured by the hazard ratio. We aim to relax this assumption in a study on the effect of factors on the evolution of pneumonia incidence over time based on data from a South African birth cohort study, the Drakenstein child health study. Methods We describe and apply two models: a time-constant and a time-varying relative effects model in a piece-wise exponential additive mixed model’s framework for recurrent events. A more complex model that fits in the same framework is applied to study the continuously measured seasonal effects. Results We find that several risk factors (male sex, preterm birth, low birthweight, lower socioeconomic status, lower maternal education and maternal cigarette smoking) have strong relative effects that are persistent across time. When time-varying effects are allowed in the model, HIV exposure status (HIV exposed & uninfected versus HIV unexposed) shows a strong relative effect for younger children, but this effect weakens as children grow older, with a null effect reached from about 15 months. Weight-for-length at birth shows a time increasing relative effect. We also find that children born in the summer have a much higher risk of pneumonia in the 3-to-8-month age period compared with children born in winter. Conclusion This work highlights the usefulness of flexible modelling tools in recurrent events models. It avoids stringent assumptions and allows estimation and visualization of absolute and relative risks over time of key factors associated with incidence of pneumonia in young children, providing new perspectives on the role of risk factors such HIV exposure.

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“…The DCHS is an ongoing, multidisciplinary population-based birth cohort study in the Drakenstein area in Paarl (outside Cape Town, South Africa) (Stein et al, 2015;Zar et al, 2015Zar et al, , 2019 . After providing informed consent, pregnant women were enrolled during their second trimester (20-28 weeks gestation); maternal-child dyads were then followed through childbirth and longitudinally thereafter.…”

Section: Drakenstein Children's Health Study (Dchs) In South Africamentioning

confidence: 99%

Low generalizability of polygenic scores in African populations due to genetic and environmental diversity

Majara

Kalungi

Koen

et al. 2021

Preprint

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African populations are vastly underrepresented in genetic studies but have the most genetic variation and face wide-ranging environmental exposures globally. Because systematic evaluations of genetic prediction had not yet been conducted in ancestries that span African diversity, we calculated polygenic risk scores (PRS) in simulations across Africa and in empirical data from South Africa, Uganda, and the UK to better understand the generalizability of genetic studies. PRS accuracy improves with ancestry-matched discovery cohorts more than from ancestry-mismatched studies. Within ancestrally and ethnically diverse South Africans, we find that PRS accuracy is low for all traits but varies across groups. Differences in African ancestries contribute more to variability in PRS accuracy than other large cohort differences considered between individuals in the UK versus Uganda. We computed PRS in African ancestry populations using existing European-only versus ancestrally diverse genetic studies; the increased diversity produced the largest accuracy gains for hemoglobin concentration and white blood cell count, reflecting large-effect ancestry-enriched variants in genes known to influence sickle cell anemia and the allergic response, respectively. Differences in PRS accuracy across African ancestries originating from diverse regions are as large as across out-of-Africa continental ancestries, requiring commensurate nuance.

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Maternal health and birth outcomes in a South African birth cohort study

Cited by 49 publications

References 35 publications

Food insecurity as a risk factor for preterm birth: a prospective facility-based cohort study in rural Haiti

Food insecurity as a risk factor for preterm birth: a prospective facility-based cohort study in rural Haiti

Flexible modelling of risk factors on the incidence of pneumonia in young children in South Africa using piece-wise exponential additive mixed modelling

Low generalizability of polygenic scores in African populations due to genetic and environmental diversity

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