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

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Study Justification:
– Maternal physical and mental health during pregnancy are important factors that influence birth outcomes.
– There is a lack of prospective data on the integration of physical and mental health measures with birth outcomes in low- and middle-income country settings.
– The study aimed to investigate maternal health during pregnancy and its impact on birth outcomes in a South African birth cohort.
Study Highlights:
– The study enrolled 1137 pregnant women from two public health clinics in a poor peri-urban area of South Africa.
– Most pregnancies were uncomplicated, but a minority of women experienced gestational diabetes, anaemia, or pre-eclampsia.
– The majority of households had a monthly income of less than USD 350, and food insecurity was common.
– Most babies were born by vaginal delivery at full term, but 17% were preterm.
– Modifiable risk factors such as food insecurity, smoking, and alcohol consumption during pregnancy were associated with negative birth outcomes.
Study Recommendations:
– Public health interventions should be implemented to address modifiable risk factors identified in the study, such as food insecurity, smoking, and alcohol consumption during pregnancy.
– Interventions should focus on improving maternal and child health in low- and middle-income country settings.
Key Role Players:
– Researchers and scientists involved in maternal and child health studies.
– Public health officials and policymakers responsible for implementing interventions.
– Healthcare providers and clinics offering antenatal care and support.
– Community organizations and NGOs working in maternal and child health.
Cost Items for Planning Recommendations:
– Funding for research and data collection.
– Resources for implementing public health interventions.
– Training and capacity building for healthcare providers.
– Monitoring and evaluation of intervention programs.
– Community engagement and awareness campaigns.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong, as it is based on a prospective birth cohort study with a large sample size. The study collected comprehensive data on maternal health measures and birth outcomes. The abstract also highlights several modifiable risk factors associated with negative birth outcomes. To improve the evidence, it would be helpful to provide more specific information on the statistical analyses conducted and the effect sizes of the associations found.

Background Maternal physical and mental health during pregnancy are key determinants of birth outcomes. There are relatively few prospective data that integrate physical and mental maternal health measures with birth outcomes in low- and middle-income country settings. We aimed to investigate maternal health during pregnancy and the impact on birth outcomes in an African birth cohort study, the Drakenstein Child Health Study. Methods Pregnant women attending 2 public health clinics, Mbekweni (serving a predominantly black African population) and TC Newman (predominantly mixed ancestry) in a poor peri-urban area of South Africa were enrolled in their second trimester and followed through childbirth. All births occurred at a single public hospital. Maternal sociodemographic, physical and psychosocial characteristics were comprehensively assessed. Multivariable linear regression models were used to explore associations between maternal health and birth outcomes. Results Over 3 years, 1137 women (median age 25.8 years; 21% HIV-infected) gave birth to 1143 live babies. Most pregnancies were uncomplicated but gestational diabetes (1%), anaemia (22%) or pre-eclampsia (2%) occurred in a minority. Most households (87%) had a monthly income of less than USD 350; only 27% of moms were employed and food insecurity was common (37%). Most babies (80%) were born by vaginal delivery at full term; 17% were preterm, predominantly late preterm. Only 74 (7%) of babies required hospitalisation immediately after birth and only 2 babies were HIV-infected. Food insecurity, socioeconomic status, pregnancy-associated hypertension, pre-eclampsia, gestational diabetes and mixed ancestry were associated with lower infant gestational age while maternal BMI at enrolment was associated with higher infant gestational age. Primigravida or alcohol use during pregnancy were negatively associated with infant birth weight and head circumference. Maternal BMI at enrolment was positively associated with birth weight and gestational diabetes was positively associated with birth weight and head circumference for gestational age. Smoking during pregnancy was associated with lower infant birth weight. Conclusion Several modifiable risk factors including food insecurity, smoking, and alcohol consumption during pregnancy were identified as associated with negative birth outcomes, all of which are amenable to public health interventions. Interventions to address key exposures influencing birth outcomes are needed to improve maternal and child health in low-middle income country settings.

The DCHS is a multidisciplinary population-based birth cohort study situated in the Drakenstein area in Paarl, a peri-urban area, 60km outside Cape Town, South Africa.[18] The population comprise approximately 200 000 people with little immigration or emigration. The public health system includes well-established primary health clinics providing antenatal care and HIV treatment and prevention programs including prevention of mother to child transmission (PMTCT). All births occur at a single hospital, Paarl Hospital. More than 90% of the population access health care in the public sector including antenatal services. Maternal physical and mental health was investigated through longitudinal measurements through pregnancy and birth, as were socio-demographic factors and psychosocial risk factors.[18–20] Consenting pregnant women were enrolled from March 2012 to March 2015 and followed through childbirth. Women were enrolled in their second trimester (20–28 weeks gestation) at 2 public sector primary health care clinics, one serving a predominantly mixed ancestry population (TC Newman) and the other serving a predominantly Black African population (Mbekweni). As per the national health program, antenatal and obstetric care was provided free to women in these health care facilities. Women were eligible to participate if they attended one of the two study clinics, were at least 18 years of age and intended to remain resident in the study area for at least 1 year. All assessments were available in English, isiXhosa, and Afrikaans and participants chose their preferred language. Sociodemographic variables including age, marital status, employment, and income were measured through questionnaires and antenatal visits. Socioeconomic status (SES) was 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).[13] Perceived household food insecurity was assessed using an adapted version of the short form of the USDA Household Food Security Scale[21] (detailed in Pellowski et al.).[22] Maternal physical health was assessed at enrolment, at a follow-up antenatal visit and at birth through questionnaires and physical examination conducted by trained study staff on study-specific equipment. Maternal blood pressure (single arm, single measurement using an electronic blood pressure cuff) and weight were monitored antenatally. All pregnancy complications were collected prospectively (at enrolment and a second antenatal visit) as well as from chart review. High blood pressure was defined as having a BP ≥140/90 mmHg. Pre-eclampsia was defined as new onset of hypertension after 20 weeks gestation with proteinuria or other organ dysfunction. Eclampsia was defined as the presence of seizures due to pre-eclampsia. Haemoglobin measurement was done in the antenatal period as part of routine care. Anaemia was calculated conservatively as any haemoglobin measurement <10 g/dl. WHO guidelines define moderate or severe anaemia as <10 g/dl. Gestational diabetes was assessed through urine dipstick and fasting blood glucose if urine glucose was positive. No formal glucose tolerance tests were conducted. Routine antenatal care included HIV rapid testing on enrolment if a mother’s HIV status was unknown.[23] Syphilis serology, hemoglobin measurement and urine dipstick analysis for proteinuria or white cells were performed; urine analysis was repeated through pregnancy. Maternal mental health was measured using validated questionnaires administered by trained study staff at an antenatal visit at 28 to 32 weeks’ gestation. The Edinburgh Postnatal Depression Scale (EPDS) was used to assess symptoms of depression and has been validated for use in both postpartum and pregnant women. The EPDS comprises 10 items, each scored on a severity scale ranging from 0 to 3. A total score of 13 or greater indicates probable depression. The SRQ-20 is a WHO-endorsed measure of psychological distress; a cut-off score of ≥8 was used to dichotomize participants into high and low risk categories.[24] [25]The Intimate Partner Violence (IPV) Questionnaire used in this study was adapted from the WHO multi-country study and the Women’s Health Study in Zimbabwe.[26] Participants were dichotomized into exposed or unexposed for having experienced emotional, physical or sexual IPV in the past 12 months. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST)[27] was used to assess self-report of tobacco, alcohol, and other substance use (during the past three months). Maternal smoking or passive smoke exposure was measured by urine cotinine antenatally and at birth using the IMMULITER 1000 Nicotine Metabolite Kit (Siemens Medical Solutions DiagnosticsR, Glyn Rhonwy, United Kingdom) to distinguish categories of smoke exposure i.e. levels <10 ng/ml (non-smoker), 10–499 ng/ml (passive smoke exposure) or ≥500 ng/ml (active smoker). Pregnancy data were collected from mothers at two antenatal visits. Study staff attended all deliveries, and recorded mode of delivery, development of any complications and infant birth outcomes. Mothers and infants were followed until discharge from Paarl hospital. Birth weight, length and head circumference were measured at birth by trained staff. Gestational age at birth was estimated based on an antenatal ultrasound done in the second trimester; if this was unavailable then symphysis-fundal height, recorded by trained clinical staff at enrolment, or maternal recall of last menstrual period was used. Ethical approval was obtained from the Faculty of Health Sciences Research Ethics Committee, University of Cape Town (401/2009) and the Provincial Research committee. Mothers gave written informed consent at enrolment. Data were analysed using Stata 12 (StataCorp Inc, College Station, Texas, USA). Demographics, physical and mental health, pregnancy- and birth-related data were described using median (interquartile range (IQR)) or number (%). Outliers were not deleted. Data were compared between black African and mixed ancestry participants using the Mann-Whitney U test and the χ2 test. Birth weight, length and head circumference were converted to Z-scores for gender and gestational age using the revised 2003 Fenton curves which harmonizes the preterm growth charts with the new WHO growth standards.[28] Predictors of poor birth outcomes (gestational age at delivery in weeks; birthweight and head circumference Z-scores) were identified using multivariable linear regression models. The basic multivariable model included maternal age, marital status, SES and food security. For additional covariates, univariable analyses were conducted. Significant univariable coefficients (p<0.15) were included in multivariable hierarchical regression models. In multivariable hierarchical regression analyses, a P-value<0.05 was considered statistically significant. Data will be made available on request.

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The study titled “Maternal health and birth outcomes in a South African birth cohort study” provides valuable insights into the factors influencing maternal health and birth outcomes in a low-middle income country setting. The study highlights several modifiable risk factors associated with negative birth outcomes, which can be targeted through public health interventions to improve maternal and child health. Some of the key recommendations based on the study findings include:

1. Implementing food security programs to address household food insecurity, as it was identified as a risk factor for lower infant gestational age.

2. Developing smoking cessation programs to support pregnant women in quitting smoking or reducing exposure to secondhand smoke, as smoking during pregnancy was associated with lower infant birth weight.

3. Raising awareness about the risks of alcohol consumption during pregnancy and providing support for pregnant women struggling with alcohol use, as alcohol use during pregnancy was negatively associated with infant birth weight and head circumference.

4. Strengthening antenatal care services, including regular screenings for gestational diabetes, hypertension, and other pregnancy complications, as early detection and management of these conditions can help improve birth outcomes.

5. Integrating mental health screening and support into routine antenatal care, as maternal mental health was found to be an important factor in birth outcomes.

6. Developing comprehensive health education programs targeting pregnant women and their families to increase awareness and knowledge about healthy pregnancy practices, prenatal care, and breastfeeding.

By implementing these targeted interventions, access to maternal health can be improved, leading to better birth outcomes and overall maternal and child health in low-middle income country settings.
AI Innovations Description
Based on the information provided, here is a recommendation that can be developed into an innovation to improve access to maternal health:

Implement targeted public health interventions to address modifiable risk factors associated with negative birth outcomes. This can include:

1. Food security programs: Develop initiatives to address household food insecurity, as it was identified as a risk factor for lower infant gestational age. This can involve providing nutritional support, education on healthy eating, and access to affordable and nutritious food options for pregnant women.

2. Smoking cessation programs: Implement interventions to support pregnant women in quitting smoking or reducing exposure to secondhand smoke. Smoking during pregnancy was associated with lower infant birth weight. This can involve counseling, nicotine replacement therapy, and educational campaigns on the risks of smoking during pregnancy.

3. Alcohol awareness and support: Develop programs to raise awareness about the risks of alcohol consumption during pregnancy and provide support for pregnant women struggling with alcohol use. Alcohol use during pregnancy was negatively associated with infant birth weight and head circumference.

4. Antenatal care and screening: Strengthen antenatal care services, including regular screenings for gestational diabetes, hypertension, and other pregnancy complications. Early detection and management of these conditions can help improve birth outcomes.

5. Mental health support: Integrate mental health screening and support into routine antenatal care. Maternal mental health was found to be an important factor in birth outcomes. Implementing screening tools like the Edinburgh Postnatal Depression Scale (EPDS) and providing access to counseling services can help identify and support women experiencing mental health challenges during pregnancy.

6. Health education and awareness: Develop comprehensive health education programs targeting pregnant women and their families. This can include information on healthy pregnancy practices, the importance of prenatal care, and the benefits of breastfeeding. Increasing awareness and knowledge can empower women to make informed decisions about their health and improve maternal and child health outcomes.

By implementing these targeted interventions, access to maternal health can be improved, leading to better birth outcomes and overall maternal and child health in low-middle income country settings.
AI Innovations Methodology
To simulate the impact of the main recommendations on improving access to maternal health, the following methodology can be used:

1. Identify the target population: Determine the specific population that will be the focus of the intervention. This could be pregnant women in low-middle income country settings, similar to the population in the South African birth cohort study.

2. Define the intervention: Clearly outline the targeted public health interventions based on the recommendations provided. This could include implementing food security programs, smoking cessation programs, alcohol awareness and support initiatives, strengthening antenatal care and screening, providing mental health support, and developing health education and awareness programs.

3. Collect baseline data: Gather data on the current state of maternal health and birth outcomes in the target population. This can include information on maternal sociodemographic characteristics, physical and mental health measures, pregnancy complications, birth outcomes, and other relevant factors.

4. Design the simulation model: Develop a simulation model that incorporates the key variables and relationships identified in the South African birth cohort study. This model should be able to simulate the impact of the recommended interventions on maternal health and birth outcomes.

5. Implement the interventions: Apply the targeted public health interventions to the simulation model. This can involve adjusting variables related to food security, smoking, alcohol consumption, antenatal care, mental health support, and health education based on the recommendations.

6. Run the simulation: Use the simulation model to simulate the impact of the interventions on maternal health and birth outcomes. This can involve running multiple iterations of the model to account for variability and uncertainty.

7. Analyze the results: Analyze the simulation results to determine the potential impact of the interventions on improving access to maternal health. This can include assessing changes in birth outcomes such as gestational age, birth weight, and head circumference, as well as other relevant indicators of maternal health.

8. Interpret the findings: Interpret the simulation results to understand the potential benefits and limitations of the recommended interventions. This can involve comparing the simulated outcomes to the baseline data and assessing the feasibility and scalability of the interventions in real-world settings.

9. Communicate the findings: Present the findings of the simulation study in a clear and concise manner. This can include preparing a report or presentation that highlights the potential impact of the interventions on improving access to maternal health and provides recommendations for implementation.

By following this methodology, researchers and policymakers can gain insights into the potential impact of targeted public health interventions on improving access to maternal health and birth outcomes in low-middle income country settings.

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