Prevalence, Incidence, and Reversal Pattern of Childhood Stunting From Birth to Age 2 Years in Ethiopia.

Importance: Although there has been a reduction in stunting (low-height-for-age and low-length-for-age), a proxy of malnutrition, the prevalence of malnutrition in Ethiopia is still high. Child growth patterns and estimates of stunting are needed to increase awareness and resources to improve the potential for recovery. Objective: To estimate the prevalence, incidence, and reversal of stunting among children aged 0 to 24 months. Design, Setting, and Participants: This population-based cohort study of the Birhan Maternal and Child Health cohort in North Shewa Zone, Amhara, Ethiopia, was conducted between December 2018 and November 2020. Eligible participants included children aged 0 to 24 months who were enrolled during the study period and had their length measured at least once. Data analysis occurred from Month Year to Month Year. Main Outcomes and Measures: The primary outcome of this study was stunting, defined as length-for-age z score (LAZ) at least 2 SDs below the mean. Z scores were also used to determine the prevalence, incidence, and reversal of stunting at each key time point. Growth velocity was determined in centimeters per month between key time points and compared with global World Health Organization (WHO) standards for the same time periods. Heterogeneity was addressed by excluding outliers in sensitivity analyses using modeled growth trajectories for each child. Results: A total of 4354 children were enrolled, out of which 3674 (84.4%; 1786 [48.7%] female) had their length measured at least once and were included in this study. The median population-level length was consistently below WHO growth standards from birth to 2 years of age. The observed prevalence of stunting was highest by 2 years of age at 57.4% (95% CI, 54.8%-9 60.0%). Incidence of stunting increased over time and reached 51.0% (95% CI, 45.3%-56.6%) between ages 12 and 24 months. Reversal was 63.5% (95% CI, 54.8%-71.4%) by age 6 months and 45.2% (95% CI, 36.0%-54.8%) by age 2 years. Growth velocity point estimate differences were slowest compared with WHO standards during the neonatal period (-1.4 cm/month for girls and -1.6 cm/month for boys). There was substantial heterogeneity in anthropometric measurements. Conclusions and Relevance: The evidence from this cohort study highlights a chronically malnourished population with much of the burden associated with growth faltering during the neonatal periods as well as after 6 months of age. To end all forms of malnutrition, growth faltering in populations such as that in young children in Amhara, Ethiopia, needs to be addressed.

Antenatal care coverage in a low-resource setting: Estimations from the Birhan Cohort.

Antenatal care (ANC) coverage estimates commonly rely on self-reported data, which may carry biases. Leveraging prospectively collected longitudinal data from the Birhan field site and its pregnancy and birth cohort, the Birhan Cohort, this study aimed to estimate the coverage of ANC, minimizing assumptions and biases due to self-reported information and describing retention patterns in ANC in rural Amhara, Ethiopia. The study population were women enrolled and followed during pregnancy between December 2018 and April 2020. ANC visits were measured by prospective facility chart abstraction and self-report at enrollment. The primary study outcomes were the total number of ANC visits attended during pregnancy and the coverage of at least one, four, or eight ANC visits. Additionally, we estimated ANC retention patterns. We included 2069 women, of which 150 (7.2%) women enrolled <13 weeks of gestation with complete prospective facility reporting. Among these 150 women, ANC coverage of at least one visit was 97.3%, whereas coverage of four visits or more was 34.0%. Among all women, coverage of one ANC visit was 92.3%, while coverage of four or more visits was 28.8%. No women were found to have attended eight or more ANC visits. On retention in care, 70.3% of participants who had an ANC visit between weeks 28 and <36 of gestation did not return for a subsequent visit. Despite the high proportion of pregnant women who accessed ANC at least once in our study area, the coverage of four visits remains low. Further efforts are needed to enhance access to more ANC visits, retain women in care, and adhere to the most recent Ethiopian National ANC guideline of at least eight ANC visits. It is essential to identify the factors that lead a large proportion of women to discontinue ANC follow-up.

Development of Prediction Models for Antenatal Care Attendance in Amhara Region, Ethiopia.

Importance: Antenatal care prevents maternal and neonatal deaths and improves birth outcomes. There is a lack of predictive models to identify pregnant women who are at high risk of failing to attend antenatal care in low-resource settings. Objective: To develop a series of predictive models to identify women who are at high risk of failing to attend antenatal care in a rural setting in Ethiopia. Design, Setting, and Participants: This prognostic study used data from the Birhan Health and Demographic Surveillance System and its associated pregnancy and child cohort. The study was conducted at the Birhan field site, North Shewa zone, Ethiopia, a platform for community- and facility-based research and training, with a focus on maternal and child health. Participants included women enrolled during pregnancy in the pregnancy and child cohort between December 2018 and March 2020, who were followed-up in home and facility visits. Data were analyzed from April to December 2022. Exposures: A wide range of sociodemographic, economic, medical, environmental, and pregnancy-related factors were considered as potential predictors. The selection of potential predictors was guided by literature review and expert knowledge. Main Outcomes and Measures: The outcome of interest was failing to attend at least 1 antenatal care visit during pregnancy. Prediction models were developed using logistic regression with regularization via the least absolute shrinkage and selection operator and ensemble decision trees and assessed using the area under the receiving operator characteristic curve (AUC). Results: The study sample included 2195 participants (mean [SD] age, 26.8 [6.1] years; mean [SD] gestational age at enrolment, 25.5 [8.8] weeks). A total of 582 women (26.5%) failed to attend antenatal care during cohort follow-up. The AUC was 0.61 (95% CI, 0.58-0.64) for the regularized logistic regression model at conception, with higher values for models predicting at weeks 13 (AUC, 0.68; 95% CI, 0.66-0.71) and 24 (AUC, 0.66; 95% CI, 0.64-0.69). AUC values were similar with slightly higher performance for the ensembles of decision trees (conception: AUC, 0.62; 95% CI, 0.59-0.65; 13 weeks: AUC, 0.70; 95% CI, 0.67-0.72; 24 weeks: AUC, 0.67; 95% CI, 0.64-0.69). Conclusions and Relevance: This prognostic study presents a series of prediction models for antenatal care attendance with modest performance. The developed models may be useful to identify women at high risk of missing their antenatal care visits to target interventions to improve attendance rates. This study opens the possibility to develop and validate easy-to-use tools to project health-related behaviors in settings with scarce resources.

Development of risk prediction models for preterm delivery in a rural setting in Ethiopia.

Background: Preterm birth complications are the leading causes of death among children under five years. However, the inability to accurately identify pregnancies at high risk of preterm delivery is a key practical challenge, especially in resource-constrained settings with limited availability of biomarkers assessment. Methods: We evaluated whether risk of preterm delivery can be predicted using available data from a pregnancy and birth cohort in Amhara region, Ethiopia. All participants were enrolled in the cohort between December 2018 and March 2020. The study outcome was preterm delivery, defined as any delivery occurring before week 37 of gestation regardless of vital status of the foetus or neonate. A range of sociodemographic, clinical, environmental, and pregnancy-related factors were considered as potential inputs. We used Cox and accelerated failure time models, alongside decision tree ensembles to predict risk of preterm delivery. We estimated model discrimination using the area-under-the-curve (AUC) and simulated the conditional distributions of cervical length (CL) and foetal fibronectin (FFN) to ascertain whether they could improve model performance. Results: We included 2493 pregnancies; among them, 138 women were censored due to loss-to-follow-up before delivery. Overall, predictive performance of models was poor. The AUC was highest for the tree ensemble classifier (0.60, 95% confidence interval = 0.57-0.63). When models were calibrated so that 90% of women who experienced a preterm delivery were classified as high risk, at least 75% of those classified as high risk did not experience the outcome. The simulation of CL and FFN distributions did not significantly improve models' performance. Conclusions: Prediction of preterm delivery remains a major challenge. In resource-limited settings, predicting high-risk deliveries would not only save lives, but also inform resource allocation. It may not be possible to accurately predict risk of preterm delivery without investing in novel technologies to identify genetic factors, immunological biomarkers, or the expression of specific proteins.

Impact of the COVID-19 pandemic on utilisation of facility-based essential maternal and child health services from March to August 2020 compared with pre-pandemic March-August 2019: a mixed-methods study in North Shewa Zone, Ethiopia.

INTRODUCTION: Health systems are often weakened by public health emergencies that make it harder to access health services. We aimed to assess maternal, newborn and child health (MNCH) service utilisation during the first 6 months of the COVID-19 pandemic compared with prior to the pandemic. METHODS: We conducted a mixed study design in eight health facilities that are part of the Birhan field site in Amhara, Ethiopia and compared the trend of service utilisation in the first 6 months of COVID-19 with the corresponding time and data points of the preceding year. RESULT: New family planning visits (43.2 to 28.5/month, p=0.014) and sick under 5 child visits (225.0 to 139.8/month, p=0.007) declined over the first 6 months of the pandemic compared with the same period in the preceding year. Antenatal (208.9 to 181.7/month, p=0.433) and postnatal care (26.6 to 19.8/month, p=0.155) visits, facility delivery rates (90.7 to 84.2/month, p=0.776), and family planning visits (313.3 to 273.4/month, p=0.415) declined, although this did not reach statistical significance. Routine immunisation visits (37.0 to 36.8/month, p=0.982) for children were maintained. Interviews with healthcare providers and clients highlighted several barriers to service utilisation during COVID-19, including fear of disease transmission, economic hardship, and transport service disruptions and restrictions. Enablers of service utilisation included communities' decreased fear of COVID-19 and awareness-raising activities. CONCLUSION: We observed a decline in essential MNCH services particularly in sick children and new family planning visits. To improve the resiliency of fragile health systems, resources are needed to continuously monitor service utilisation and clients' evolving concerns during public health emergencies.

Estimates of Stillbirths, Neonatal Mortality, and Medically Vulnerable Live Births in Amhara, Ethiopia.

Importance: Data on birth outcomes and early mortality are scarce, especially in settings with limited resources. Total births, both stillbirths and live births, are often not counted, yet such data are critical to allocate resources and target interventions to improve survival. Objective: To estimate the prevalence of stillbirths, neonatal deaths, and medically vulnerable phenotypes, such as preterm births, small-for-gestational-age (SGA), large-for-gestational-age (LGA), and low-birth-weight (LBW) births, in a setting where these key indicators remain largely unknown. Design, Setting, and Participants: This prospective pregnancy cohort study of women and their newborns was conducted between December 12, 2018, and November 5, 2020. The study was conducted in North Shewa Zone, Amhara, Ethiopia. Data were analyzed from July 2021 to May 2022. Main Outcomes and Measures: Pregnancy status, gestational age, birth weight, and vital status were measured to estimate the prevalence of stillbirths, live births, and medically vulnerable live births (ie, preterm, SGA, LGA, and LBW births). For mortality outcomes, the prevalence of neonatal (overall, early, and late) and perinatal mortality were estimated. Results: Among the 2801 enrolled women, the median (IQR) age at conception was 26.5 (22.2-31.0) years, and the median (IQR) gestational age at enrollment was 24 (17-31) weeks. Of the 2628 women (93.8%) with outcome data, 101 pregnancies (3.8%) resulted in an early loss (<28 gestational weeks). Among the 2527 remaining pregnant women, there were 2518 births between 28 and less than 46 weeks' gestation; 2459 (97.7%; 95% CI, 97.0%-98.2%) were live births and 59 (2.3%; 95% CI, 1.8%-3.0%) were stillbirths. Many newborns (41.7%) were born preterm, SGA, LGA, or LBW. The estimated prevalence was 15.1% (95% CI, 13.7%-16.6%) for preterm births, 23.1% (95% CI, 21.3%-25.1%) for SGA births, 10.6% (95% CI, 9.3%-12.1%) for LGA births, and 9.4% (95% CI, 8.2%-10.8%) for LBW births. Among live births, the overall prevalence of neonatal mortality was 3.1% (95% CI, 2.5%-3.9%); mortality was higher among preterm births (7.2%; 95% CI, 4.9%-10.4%), LBW births (12.2%; 95% CI, 8.2%-17.7%), and SGA births (4.1%; 95% CI, 2.6%-6.5%). The prevalence of early neonatal mortality was almost twice as high as the prevalence of late neonatal mortality. The perinatal mortality prevalence was 4.3% (95% CI, 3.6%-5.2%), with a 1.2:1 ratio of stillbirths to first-week deaths. Conclusions and Relevance: These findings have important implications for newborn health and survival. For policy makers and programmers, accurate data on key indicators of neonatal health provide information for resource allocation and to evaluate progress. For researchers, the findings underlie the importance for further research to develop and deliver interventions that improve health outcomes.

Birhan maternal and child health cohort: a study protocol.

INTRODUCTION: Reliable estimates on maternal and child morbidity and mortality are essential for health programmes and policies. Data are needed in populations, which have the highest burden of disease but also have the least evidence and research, to design and evaluate health interventions to prevent illnesses and deaths that occur worldwide each year. METHODS AND ANALYSIS: The Birhan Maternal and Child Health cohort is an open prospective pregnancy and birth cohort nested within the Birhan Health and Demographic Surveillance System. An estimated 2500 pregnant women are enrolled each year and followed through pregnancy, birth and the postpartum period. Newborns are followed through 2 years of life to assess growth and development. Baseline medical data, signs and symptoms, laboratory test results, anthropometrics and pregnancy and birth outcomes (stillbirth, preterm birth, low birth weight) are collected from both home and health facility visits. We will calculate the period prevalence and incidence of primary morbidity and mortality outcomes. ETHICS AND DISSEMINATION: The cohort has received ethical approval. Findings will be disseminated at scientific conferences, peer-reviewed journals and to relevant stakeholders including the Ministry of Health.