Birthweight data completeness and quality in population-based surveys: EN-INDEPTH study

National, regional, and global estimates of low birthweight in 2020, with trends from 2000: a systematic analysis

BACKGROUND

Low birthweight (LBW; <2500 g) is an important predictor of health outcomes throughout the life course. We aimed to update country, regional, and global estimates of LBW prevalence for 2020, with trends from 2000, to assess progress towards global targets to reduce LBW by 30% by 2030.

METHODS

For this systematic analysis, we searched population-based, nationally representative data on LBW from Jan 1, 2000, to Dec 31, 2020. Using 2042 administrative and survey datapoints from 158 countries and areas, we developed a Bayesian hierarchical regression model incorporating country-specific intercepts, time-varying covariates, non-linear time trends, and bias adjustments based on data quality. We also provided novel estimates by birthweight subgroups.

FINDINGS

An estimated 19·8 million (95% credible interval 18·4-21·7 million) or 14·7% (13·7-16·1) of liveborn newborns were LBW worldwide in 2020, compared with 22·1 million (20·7-23·9 million) and 16·6% (15·5-17·9) in 2000-an absolute reduction of 1·9 percentage points between 2000 and 2020. Using 2012 as the baseline, as this is when the Global Nutrition Target began, the estimated average annual rate of reduction from 2012 to 2020 was 0·3% worldwide, 0·85% in southern Asia, and 0·59% in sub-Saharan Africa. Nearly three-quarters of LBW births in 2020 occurred in these two regions: of 19 833 900 estimated LBW births worldwide, 8 817 000 (44·5%) were in southern Asia and 5 381 300 (27·1%) were in sub-Saharan Africa. Of 945 300 estimated LBW births in northern America, Australia and New Zealand, central Asia, and Europe, approximately 35·0% (323 700) weighed less than 2000 g: 5·8% (95% CI 5·2-6·4; 54 800 [95% CI 49 400-60 800]) weighed less than 1000 g, 9·0% (8·7-9·4; 85 400 [82 000-88 900]) weighed between 1000 g and 1499 g, and 19·4% (19·0-19·8; 183 500 [180 000-187 000]) weighed between 1500 g and 1999 g.

INTERPRETATION

Insufficient progress has occurred over the past two decades to meet the Global Nutrition Target of a 30% reduction in LBW between 2012 and 2030. Accelerating progress requires investments throughout the lifecycle focused on primary prevention, especially for adolescent girls and women living in the most affected countries. With increasing numbers of births in facilities and advancing electronic information systems, improvements in the quality and availability of administrative LBW data are also achievable.

FUNDING

The Children's Investment Fund Foundation; the UNDP-UNFPA-UNICEF-WHO World Bank Special Programme of Research, Development and Research Training in Human Reproduction; and the Bill & Melinda Gates Foundation.

Accuracy of Syrain Refugee Mothers' Perceptions of Newborn's Birth Size: Insights from a National Survey in Turkey

This study aims to assess the accuracy of maternally perceived birth size and its associated factors among the Syrian refugees in Turkey, using the data from 2018 Turkey Demographic and Health Survey Syrian Migrant Sample (TDHS-SM-18). The study includes information on the last-born child, singleton pregnancies, births in healthcare facilities, children under 5 living with their mothers, with recorded birth weight (n = 969). The study categorizes the mother's perception of size into three groups : compatible, overestimated, and underestimated. Various factors, including sociodemographic characteristics, financial aspects, maternal characteristics, and child characteristics, are considered as explanatory variables. The analysis employs a complex sample multiple logistic regression model. The findings reveal that the majority of mothers accurately perceive the birth size, but 17.1% of them do not. Maternal factors such as region of residence, literacy, occupation, age at birth, and child factors such as birth order, birth interval, gender, and birth weight are identified as associated factors with maternal misperception. This study provides valuable insights into the accuracy of maternally perceived birth size and sheds light on the factors influencing this perception among Syrian refugee mothers in Turkey.

Quantitative Proteomics of Maternal Blood Plasma in Isolated Intrauterine Growth Restriction

Intrauterine growth restriction (IUGR) remains a significant concern in modern obstetrics, linked to high neonatal health problems and even death, as well as childhood disability, affecting adult quality of life. The role of maternal and fetus adaptation during adverse pregnancy is still not completely understood. This study aimed to investigate the disturbance in biological processes associated with isolated IUGR via blood plasma proteomics. The levels of 125 maternal plasma proteins were quantified by liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with corresponding stable isotope-labeled peptide standards (SIS). Thirteen potential markers of IUGR (Gelsolin, Alpha-2-macroglobulin, Apolipoprotein A-IV, Apolipoprotein B-100, Apolipoprotein(a), Adiponectin, Complement C5, Apolipoprotein D, Alpha-1B-glycoprotein, Serum albumin, Fibronectin, Glutathione peroxidase 3, Lipopolysaccharide-binding protein) were found to be inter-connected in a protein-protein network. These proteins are involved in plasma lipoprotein assembly, remodeling, and clearance; lipid metabolism, especially cholesterol and phospholipids; hemostasis, including platelet degranulation; and immune system regulation. Additionally, 18 proteins were specific to a particular type of IUGR (early or late). Distinct patterns in the coagulation and fibrinolysis systems were observed between isolated early- and late-onset IUGR. Our findings highlight the complex interplay of immune and coagulation factors in IUGR and the differences between early- and late-onset IUGR and other placenta-related conditions like PE. Understanding these mechanisms is crucial for developing targeted interventions and improving outcomes for pregnancies affected by IUGR.

National routine data for low birthweight and preterm births: Systematic data quality assessment for United Nations member states (2000-2020)

OBJECTIVE

Low birthweight (<2500 g) and preterm birth (<37 weeks) are markers of newborn vulnerability. To facilitate informed decisions about investments in prevention and care, it is imperative to enhance data quality and use. Hence, the objective of this study is to systematically assess the quality of data concerning low birthweight and preterm births within routine administrative data sources.

DESIGN

Systematic data quality assessment by adopting the WHO Data Quality Framework.

SETTING

National routine data system from UN member states.

POPULATION

Livebirths.

METHODS

National routine administrative data on low birthweight and preterm births for 195 countries from 2000 to 2020 were systematically collated, totalling >700 million live births. The WHO data quality framework was adapted to undertake standardised data quality assessments.

MAIN OUTCOME MEASURES

Availability, reporting quality, internal and external consistency of low birthweight and preterm data.

RESULTS

Most United States Member States (64%: 124/195) had national data on low birthweight and (40%: 82/195) had data on preterm birth. Routine data system reporting was highest in North America, Australasia and Europe, where more than 95% live births had data on low birthweight and over 75% had data preterm births. In contrast, data reporting was lowest in sub-Saharan Africa (13% for low birthweight, 8% for preterm births) and Southern Asia (16% for low birthweight, 5% for preterm births). Most countries collect individual-level data; but, aggregate data reporting from hospital-based systems remain common in sub-Saharan Africa and Southern Asia. While data quality was generally high in North America, Australasia and Europe, gaps remain in the availability of gestational age metadata. Consistency between low birthweight and preterm rates were poor in Southern Asia and sub-Saharan Africa regions across time. There was high external consistency between low birthweight rates obtained from routine administrative data compared with low birthweight rates obtained from survey data for countries with high data quality.

CONCLUSIONS

Sub-Saharan Africa and South Asia countries have data gaps but also opportunities for rapid progress. Most births occure in facilities, electronic health information systems already include low birthweight, and adding accurate gestational age including with ultrasound assessment is becoming increasingly attainable. Moving toward the collection of individual level data would enable monitoring of quality of care and longer-term outcomes. This is crucial for every child and family and essential for measuring progress towards relevant sustainable development goals. The assessment will inform countries' actions for data quality improvement at national level and use of data for impact.

Small babies, big risks: global estimates of prevalence and mortality for vulnerable newborns to accelerate change and improve counting

Small newborns are vulnerable to mortality and lifelong loss of human capital. Measures of vulnerability previously focused on liveborn low-birthweight (LBW) babies, yet LBW reduction targets are off-track. There are two pathways to LBW, preterm birth and fetal growth restriction (FGR), with the FGR pathway resulting in the baby being small for gestational age (SGA). Data on LBW babies are available from 158 (81%) of 194 WHO member states and the occupied Palestinian territory, including east Jerusalem, with 113 (58%) having national administrative data, whereas data on preterm births are available from 103 (53%) of 195 countries and areas, with only 64 (33%) providing national administrative data. National administrative data on SGA are available for only eight countries. Global estimates for 2020 suggest 13·4 million livebirths were preterm, with rates over the past decade remaining static, and 23·4 million were SGA. In this Series paper, we estimated prevalence in 2020 for three mutually exclusive types of small vulnerable newborns (SVNs; preterm non-SGA, term SGA, and preterm SGA) using individual-level data (2010-20) from 23 national datasets (∼110 million livebirths) and 31 studies in 18 countries (∼0·4 million livebirths). We found 11·9 million (50% credible interval [Crl] 9·1-12·2 million; 8·8%, 50% Crl 6·8-9·0%) of global livebirths were preterm non-SGA, 21·9 million (50% Crl 20·1-25·5 million; 16·3%, 14·9-18·9%) were term SGA, and 1·5 million (50% Crl 1·2-4·2 million; 1·1%, 50% Crl 0·9-3·1%) were preterm SGA. Over half (55·3%) of the 2·4 million neonatal deaths worldwide in 2020 were attributed to one of the SVN types, of which 73·4% were preterm and the remainder were term SGA. Analyses from 12 of the 23 countries with national data (0·6 million stillbirths at ≥22 weeks gestation) showed around 74% of stillbirths were preterm, including 16·0% preterm SGA and approximately one-fifth of term stillbirths were SGA. There are an estimated 1·9 million stillbirths per year associated with similar vulnerability pathways; hence integrating stillbirths to burden assessments and relevant indicators is crucial. Data can be improved by counting, weighing, and assessing the gestational age of every newborn, whether liveborn or stillborn, and classifying small newborns by the three vulnerability types. The use of these more specific types could accelerate prevention and help target care for the most vulnerable babies.

Improving birth weight measurement and recording practices in Kenya and Tanzania: a prospective intervention study with historical controls

BACKGROUND

Low birth weight (LBW) is a significant public health concern given its association with early-life mortality and other adverse health consequences that can impact the entire life cycle. In many countries, accurate estimates of LBW prevalence are lacking due to inaccuracies in collection and gaps in available data. Our study aimed to determine LBW prevalence among facility-born infants in selected areas of Kenya and Tanzania and to assess whether the introduction of an intervention to improve the accuracy of birth weight measurement would result in a meaningfully different estimate of LBW prevalence than current practice.

METHODS

We carried out a historically controlled intervention study in 22 health facilities in Kenya and three health facilities in Tanzania. The intervention included: provision of high-quality digital scales, training of nursing staff on accurate birth weight measurement, recording and scale calibration practices, and quality maintenance support that consisted of enhanced supervision and feedback (prospective arm). The historically controlled data were birth weights from the same facilities recorded in maternity registers for the same calendar months from the previous year measured using routine practices and manual scales. We calculated mean birth weight (95% confidence interval CI), mean difference in LBW prevalence, and respective risk ratio (95% CI) between study arms.

RESULTS

Between October 2019 and February 2020, we prospectively collected birth weights from 8441 newborns in Kenya and 4294 in Tanzania. Historical data were available from 9318 newborns in Kenya and 12,007 in Tanzania. In the prospective sample, the prevalence of LBW was 12.6% (95% confidence intervals [CI]: 10.9%-14.4%) in Kenya and 18.2% (12.2%-24.2%) in Tanzania. In the historical sample, the corresponding prevalence estimates were 7.8% (6.5%-9.2%) and 10.0% (8.6%-11.4%). Compared to the retrospective sample, the LBW prevalence in the prospective sample was 4.8% points (3.2%-6.4%) higher in Kenya and 8.2% points (2.3%-14.0%) higher in Tanzania, corresponding to a risk ratio of 1.61 (1.38-1.88) in Kenya and 1.81 (1.30-2.52) in Tanzania.

CONCLUSION

Routine birth weight records underestimate the risk of LBW among facility-born infants in Kenya and Tanzania. The quality of birth weight data can be improved by a simple intervention consisting of provision of digital scales and supportive training.

Sibling rivalry between twins in utero and childhood: Evidence from birthweight and survival of 95 919 twin pairs in 72 low- and middle-income countries

BACKGROUND

This study explores the magnitude and timing of sex and gender disparities in child development by describing differences in health outcomes for male and female siblings, comparing twins to control for all aspects of life circumstances other than sex and gender.

METHODS

We construct a repeat cross-sectional dataset of 191 838 twins among 1.7 million births recorded in 214 nationally representative household surveys for 72 countries between 1990 and 2016. To test for biological or social mechanisms that might favor the health of male or female infants, we describe differences in birthweights, attained heights, weights, and survival to distinguish gestational health from care practices after each child is born.

RESULTS

We find that male fetuses grow at the expense of their co-twin, significantly reducing their sibling's birthweight and survival probabilities, but only if the other fetus is male. Female fetuses are born significantly heavier when they share the uterus with a male co-twin and have no significant difference in survival probability whether they happen to draw a male or a female co-twin. These findings demonstrate that sex-specific sibling rivalry and male frailty begin in utero, prior to gender bias after birth that typically favors male children.

CONCLUSIONS

Sex differences in child health may have competing effects with gender bias that occurs during childhood. Worse health outcomes for males with a male co-twin could be linked to hormone levels or male frailty, and could lead to underestimates of the effect sizes of later gender bias against girls. Gender bias favoring surviving male children may explain the lack of differences in height and weight observed for twins with either male or female co-twins.

A subnational reproductive, maternal, newborn, child, and adolescent health and development atlas of India

Understanding the fine scale and subnational spatial distribution of reproductive, maternal, newborn, child, and adolescent health and development indicators is crucial for targeting and increasing the efficiency of resources for public health and development planning. National governments are committed to improve the lives of their people, lift the population out of poverty and to achieve the Sustainable Development Goals. We created an open access collection of high resolution gridded and district level health and development datasets of India using mainly the 2015-16 National Family Health Survey (NFHS-4) data, and provide estimates at higher granularity than what is available in NFHS-4, to support policies with spatially detailed data. Bayesian methods for the construction of 5 km × 5 km high resolution maps were applied for a set of indicators where the data allowed (36 datasets), while for some other indicators, only district level data were produced. All data were summarised using the India district administrative boundaries. In total, 138 high resolution and district level datasets for 28 indicators were produced and made openly available.

Identifying neonatal intensive care (NICU) admissions using administrative claims data

BACKGROUND

To define a method for identifying neonatal intensive care unit (NICU) admissions using administrative claims data.

METHODS

This was a retrospective cohort study using claims from Optum's de-identified Clinformatics® Data Mart Database (CDM) from 2016 -2020. We developed a definition to identify NICU admissions using a list of codes from the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), Current Procedural Terminology (CPT), and revenue codes frequently associated with NICU admissions. We compared agreement between codes using Kappa statistics and calculated positive predictive values (PPV) and 95% confidence intervals (CI).

RESULTS

On average, revenue codes (3.3%) alone identified more NICU hospitalizations compared to CPT codes alone (1.5%), whereas the use of CPT and revenue (8.9%) and CPT or revenue codes (13.7%) captured the most NICU hospitalizations, which aligns with rates of preterm birth. Gestational age alone (4.2%) and birthweight codes alone (2.0%) identified the least number of potential NICU hospitalizations. Setting CPT codes as the standard and revenue codes as the "test,", revenue codes resulted in identifying 86% of NICU admissions (sensitivity) and 97% of non-NICU admissions (specificity).

CONCLUSIONS

Using administrative data, we developed a robust definition for identifying neonatal admissions. The identified definition of NICU codes is easily adaptable, repeatable, and flexible for use in other datasets.

Ghana's Livelihood Empowerment Against Poverty (1000) Program Seasonally Impacts Birthweight: A Difference-in-Differences Analysis

Objectives: Low birthweight (LBW) prevalence remains high in African countries and evidence of cash transfer impacts on birthweight, particularly by season of infant birth, is limited. This study examines overall and seasonal cash transfer impacts on LBW in rural Ghana. Methods: Data come from a longitudinal, quasi-experimental impact evaluation of the Livelihood Empowerment Against Poverty (LEAP) 1,000 unconditional cash transfer program for impoverished pregnant or lactating women in rural districts of Northern Ghana. LEAP1000 program impacts on average birthweight and LBW were estimated for a multiply imputed sample of 3,258 and a panel sample of 1,567 infants using differences-in-differences models and triple difference models to assess impacts by season. Results: LEAP1000 decreased LBW prevalence by 3.5 and 4.1 percentage points overall and in the dry season, respectively. LEAP1000 increased average birthweight by 94, 109, and 79 g overall, in the dry season, and in the rainy season, respectively. Conclusion: Our findings of positive LEAP1000 impacts on birthweight across seasons and on LBW in the dry season demonstrate the need to take seasonal vulnerabilities into account when designing and implementing programs for rural populations in Africa.

Data quality of birthweight reporting in India: Evidence from cross-sectional surveys and service statistics

The study aims to assess the quality of birthweight data collected in two surveys, including the National Family Health Survey (NFHS) and the Comprehensive National Nutrition Survey (CNNS), and as reported in the statistics from the Health Management Information System (HMIS). The study also aims to assess the implications of the data on the estimates of low birthweight (LBW). The percentage of newborns whose birthweight is missing continues to be high in the recent surveys (NFHS-4: 22%, CNNS: 30%) despite an improvement from 66% in NFHS-3. The under-coverage of birthweight data in HMIS is around 40%. In the surveys, the percentage of missing data on birthweight is higher among newborns belonging to poor households, Scheduled Tribes, and Scheduled Castes. Irrespective of whether birthweights are reported from the health cards or from mother's recall, there's a high reporting at multiples of 500g and heaping at 2,500g. The prevalence of missing data on birthweight and of heaping is higher among children born at home in comparison to facility-based births. Birthweight data of dead children who were more likely to have had a lower birthweight is highly underreported. The paper demonstrates state-level variations in birthweight reporting and inconsistencies across surveys and HMIS. In 2015–16, the prevalence of LBW as per HMIS data was 12.5%, whereas during the same period, NFHS-4 and CNNS reported a prevalence of 18%. The findings suggest that LBW is likely to be underestimated when missing data as well as heaping at 2,500g are highly prevalent. To generate robust LBW estimates in India, there is an urgent need to devise methods to ensure coverage of all live births (including early neo-natal deaths) as well as the stillbirths, irrespective of the facility where the deliveries take place.

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Birthweight data in India is highly incomplete, which led to an underestimation of LBW prevalence.

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Live births from lower socio-economic groups have significant missing birthweight data.

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HMIS underreports birthweight data and gives lower LBW estimates than surveys.

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Reported data from both cards and recall show the heaping pattern that further reduces LBW.

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Programmatic efforts to improve the quality of birthweight data are needed to get robust LBW estimates.

Fetal growth restriction and stillbirth: Biomarkers for identifying at risk fetuses

Fetal growth restriction (FGR) is a major cause of stillbirth, prematurity and impaired neurodevelopment. Its etiology is multifactorial, but many cases are related to impaired placental development and dysfunction, with reduced nutrient and oxygen supply. The fetus has a remarkable ability to respond to hypoxic challenges and mounts protective adaptations to match growth to reduced nutrient availability. However, with progressive placental dysfunction, chronic hypoxia may progress to a level where fetus can no longer adapt, or there may be superimposed acute hypoxic events. Improving detection and effective monitoring of progression is critical for the management of complicated pregnancies to balance the risk of worsening fetal oxygen deprivation in utero, against the consequences of iatrogenic preterm birth. Current surveillance modalities include frequent fetal Doppler ultrasound, and fetal heart rate monitoring. However, nearly half of FGR cases are not detected in utero, and conventional surveillance does not prevent a high proportion of stillbirths. We review diagnostic challenges and limitations in current screening and monitoring practices and discuss potential ways to better identify FGR, and, critically, to identify the “tipping point” when a chronically hypoxic fetus is at risk of progressive acidosis and stillbirth.

Demographic, socio-economic, obstetric, and behavioral factors associated with small-and large-for-gestational-age from a prospective, population-based pregnancy cohort in rural Nepal: a secondary data analysis

BACKGROUND

In South Asia, a third of babies are born small-for-gestational age (SGA). The risk factors are well described in the literature, but many studies are in high-and-middle income countries or measure SGA on facility births only. There are fewer studies that describe the prevalence of risk factors for large-for-gestational age (LGA) in low-income countries. We aim to describe the factors associated with SGA and LGA in a population-based cohort of pregnant women in rural Nepal.

METHODS

This is a secondary data analysis of community-based trial on neonatal oil massage (22,545 women contributing 39,479 pregnancies). Demographic, socio-economic status (SES), medical/obstetric history, and timing of last menstruation were collected at enrollment. Vital signs, illness symptoms, and antenatal care (ANC) attendance were collected throughout the pregnancy and neonatal weight was measured for live births. We conducted multivariate analysis using multinomial, multilevel logistic regression, reporting the odds ratio (OR) with 95% confidence intervals (CIs). Outcomes were SGA, LGA compared to appropriate-for-gestational age (AGA) and were multiply imputed using birthweight recalibrated to time at delivery.

RESULTS

SGA was associated with nulligravida (OR: 2.12 95% CI: 1.93-2.34), gravida/nulliparous (OR: 1.86, 95% CI: 1.26-2.74), interpregnancy intervals less than 18 months (OR: 1.16, 95% CI: 1.07-1.27), and poor appetite/vomiting in the second trimester, (OR: 1.27, 95% CI: 1.19-1.35). Greater wealth (OR: 0.78, 95% CI: 0.69-0.88), swelling of hands/face in the third trimester (OR: 0.81, 95% CI: 0.69-0.94) parity greater than five (OR: 0.77, 95% CI: 0.65-0.92), male fetal sex (OR: 0.91, 95% CI: 0.86-0.98), and increased weight gain (OR: 0.93 per weight kilogram difference between 2^nd and 3^rd trimester, 95% CI: 0.92-0.95) were protective for SGA. Four or more ANC visits (OR: 0.53, 95% CI: 0.41-0.68) and respiratory symptoms in the third trimester (OR: 0.67, 95% CI: 0.54-0.84) were negatively associated with LGA, and maternal age < 18 years (OR: 1.39, 95% CI: 1.03-1.87) and respiratory symptoms in the second trimester (OR: 1.27, 95% CI: 1.07-1.51) were positively associated with LGA.

CONCLUSIONS

Our findings are in line with known risk factors for SGA. Because the prevalence and mortality risk of LGA babies is low in this population, it is likely LGA status does not indicate underlaying illness. Improved and equitable access to high quality antenatal care, monitoring for appropriate gestational weight gain and increased monitoring of women with high-risk pregnancies may reduce prevalence and improve outcomes of SGA babies.

TRIAL REGISTRATION

The study used in this secondary data analysis was registered at Clinicaltrials.gov NCT01177111.

Study protocol for UNICEF and WHO estimates of global, regional, and national low birthweight prevalence for 2000 to 2020

Background Reducing low birthweight (LBW, weight at birth less than 2,500g) prevalence by at least 30% between 2012 and 2025 is a target endorsed by the World Health Assembly that can contribute to achieving Sustainable Development Goal 2 (Zero Hunger) by 2030. The 2019 LBW estimates indicated a global prevalence of 14.6% (20.5 million newborns) in 2015. We aim to develop updated LBW estimates at global, regional, and national levels for up to 202 countries for the period of 2000 to 2020. Methods Two types of sources for LBW data will be sought: national administrative data and population-based surveys. Administrative data will be searched for countries with a facility birth rate ≥80% and included when birthweight data account for ≥80% of UN estimated live births for that country and year. Surveys with birthweight data published since release of the 2019 edition of the LBW estimates will be adjusted using the standard methodology applied for the previous estimates. Risk of bias assessments will be undertaken. Covariates will be selected based on a conceptual framework of plausible associations with LBW, covariate time-series data quality, collinearity between covariates and correlations with LBW. National LBW prevalence will be estimated using a Bayesian multilevel-mixed regression model, then aggregated to derive regional and global estimates through population-weighted averages. Conclusion Whilst availability of LBW data has increased, especially with more facility births, gaps remain in the quantity and quality of data, particularly in low-and middle-income countries. Challenges include high percentages of missing data, lack of adherence to reporting standards, inaccurate measurement, and data heaping. Updated LBW estimates are important to highlight the global burden of LBW, track progress towards nutrition targets, and inform investments in programmes. Reliable, nationally representative data are key, alongside investments to improve the measurement and recording of an accurate birthweight for every baby.

A, Ruysen H, El Arifeen S, Mee P, Gladstone ME, Blencowe H, Lawn JE. Birthweight: EN-BIRTH multi-country validation study

BACKGROUND

Accurate birthweight is critical to inform clinical care at the individual level and tracking progress towards national/global targets at the population level. Low birthweight (LBW) < 2500 g affects over 20.5 million newborns annually. However, data are lacking and may be affected by heaping. This paper evaluates birthweight measurement within the Every Newborn Birth Indicators Research Tracking in Hospitals (EN-BIRTH) study.

METHODS

The EN-BIRTH study took place in five hospitals in Bangladesh, Nepal and Tanzania (2017-2018). Clinical observers collected time-stamped data (gold standard) for weighing at birth. We compared accuracy for two data sources: routine hospital registers and women's report at exit interview survey. We calculated absolute differences and individual-level validation metrics. We analysed birthweight coverage and quality gaps including timing and heaping. Qualitative data explored barriers and enablers for routine register data recording.

RESULTS

Among 23,471 observed births, 98.8% were weighed. Exit interview survey-reported weighing coverage was 94.3% (90.2-97.3%), sensitivity 95.0% (91.3-97.8%). Register-reported coverage was 96.6% (93.2-98.9%), sensitivity 97.1% (94.3-99%). Routine registers were complete (> 98% for four hospitals) and legible > 99.9%. Weighing of stillbirths varied by hospital, ranging from 12.5-89.0%. Observed LBW rate was 15.6%; survey-reported rate 14.3% (8.9-20.9%), sensitivity 82.9% (75.1-89.4%), specificity 96.1% (93.5-98.5%); register-recorded rate 14.9%, sensitivity 90.8% (85.9-94.8%), specificity 98.5% (98-99.0%). In surveys, "don't know" responses for birthweight measured were 4.7%, and 2.9% for knowing the actual weight. 95.9% of observed babies were weighed within 1 h of birth, only 14.7% with a digital scale. Weight heaping indices were around two-fold lower using digital scales compared to analogue. Observed heaping was almost 5% higher for births during the night than day. Survey-report further increased observed birthweight heaping, especially for LBW babies. Enablers to register birthweight measurement in qualitative interviews included digital scale availability and adequate staffing.

CONCLUSIONS

Hospital registers captured birthweight and LBW prevalence more accurately than women's survey report. Even in large hospitals, digital scales were not always available and stillborn babies not always weighed. Birthweight data are being captured in hospitals and investment is required to further improve data quality, researching of data flow in routine systems and use of data at every level.

Pregnancy intention data completeness, quality and utility in population-based surveys: EN-INDEPTH study

BACKGROUND

An estimated 40% of pregnancies globally are unintended. Measurement of pregnancy intention in low- and middle-income countries relies heavily on surveys, notably Demographic and Health Surveys (DHS), yet few studies have evaluated survey questions. We examined questions for measuring pregnancy intention, which are already in the DHS, and additional questions and investigated associations with maternity care utilisation and adverse pregnancy outcomes.

METHODS

The EN-INDEPTH study surveyed 69,176 women of reproductive age in five Health and Demographic Surveillance System sites in Ghana, Guinea-Bissau, Ethiopia, Uganda and Bangladesh (2017-2018). We investigated responses to survey questions regarding pregnancy intention in two ways: (i) pregnancy-specific intention and (ii) desired-versus-actual family size. We assessed data completeness for each and level of agreement between the two questions, and with future fertility desire. We analysed associations between pregnancy intention and number and timing of antenatal care visits, place of delivery, and stillbirth, neonatal death and low birthweight.

RESULTS

Missing data were <2% in all questions. Responses to pregnancy-specific questions were more consistent with future fertility desire than desired-versus-actual family size responses. Using the pregnancy-specific questions, 7.4% of women who reported their last pregnancy as unwanted reported wanting more children in the future, compared with 45.1% of women in the corresponding desired family size category. Women reporting unintended pregnancies were less likely to attend 4+ antenatal care visits (aOR 0.73, 95% CI 0.64-0.83), have their first visit during the first trimester (aOR 0.71, 95% CI 0.63-0.79), and report stillbirths (aOR 0.57, 95% CI 0.44-0.73) or neonatal deaths (aOR 0.79, 95% CI 0.64-0.96), compared with women reporting intended pregnancies. We found no associations for desired-versus-actual family size intention.

CONCLUSIONS

We found the pregnancy-specific intention questions to be a much more reliable assessment of pregnancy intention than the desired-versus-actual family size questions, despite a reluctance to report pregnancies as unwanted rather than mistimed. The additional questions were useful and may complement current DHS questions, although these are not the only possibilities. As women with unintended pregnancies were more likely to miss timely and frequent antenatal care, implementation research is required to improve coverage and quality of care for those women.

Stillbirth maternity care measurement and associated factors in population-based surveys: EN-INDEPTH study

BACKGROUND

Household surveys remain important sources of maternal and child health data, but until now, standard surveys such as Demographic and Health Surveys (DHS) have not collected information on maternity care for women who have experienced a stillbirth. Thus, nationally representative data are lacking to inform programmes to address the millions of stillbirths which occur annually.

METHODS

The EN-INDEPTH population-based survey of women of reproductive age was undertaken in five Health and Demographic Surveillance System sites in Bangladesh, Ethiopia, Ghana, Guinea-Bissau and Uganda (2017-2018). All women answered a full birth history with additional questions on pregnancy losses (FBH+) or full pregnancy history (FPH). A sub-sample, including all women reporting a recent stillbirth or neonatal death, was asked additional maternity care questions. These were evaluated using descriptive measures. Associations between stillbirth and maternal socio-demographic characteristics, babies' characteristics and maternity care use were assessed using a weighted logistic regression model for women in the FBH+ group.

RESULTS

A total of 15,591 women reporting a birth since 1 January 2012 answered maternity care questions. Completeness was very high (> 99%), with similar proportions of responses for both live and stillbirths. Amongst the 14,991 births in the FBH+ group, poorer wealth status, higher parity, large perceived baby size-at-birth, preterm or post-term birth, birth in a government hospital compared to other locations and vaginal birth were associated with increased risk of stillbirth after adjusting for potential confounding factors. Regarding association with reported postnatal care, women with a stillbirth were more likely to report hospital stays of > 1 day. However, women with a stillbirth were less likely to report having received a postnatal check compared to those with a live birth.

CONCLUSIONS

Women who had experienced stillbirth were able to respond to questions about pregnancy and birth, and we found no reason to omit questions to these women in household surveys. Our analysis identified several potentially modifiable factors associated with stillbirth, adding to the evidence-base for policy and action in low- and middle-income contexts. Including these questions in DHS-8 would lead to increased availability of population-level data to inform action to end preventable stillbirths.

Gestational age data completeness, quality and validity in population-based surveys: EN-INDEPTH study

BACKGROUND

Preterm birth (gestational age (GA) <37 weeks) is the leading cause of child mortality worldwide. However, GA is rarely assessed in population-based surveys, the major data source in low/middle-income countries. We examined the performance of new questions to measure GA in household surveys, a subset of which had linked early pregnancy ultrasound GA data.

METHODS

The EN-INDEPTH population-based survey of 69,176 women was undertaken (2017-2018) in five Health and Demographic Surveillance System sites in Bangladesh, Ethiopia, Ghana, Guinea-Bissau and Uganda. We included questions regarding GA in months (GAm) for all women and GA in weeks (GAw) for a subset; we also asked if the baby was 'born before expected' to estimate preterm birth rates. Survey data were linked to surveillance data in two sites, and to ultrasound pregnancy dating at <24 weeks in one site. We assessed completeness and quality of reported GA. We examined the validity of estimated preterm birth rates by sensitivity and specificity, over/under-reporting of GAw in survey compared to ultrasound by multinomial logistic regression, and explored perceptions about GA and barriers and enablers to its reporting using focus group discussions (n = 29).

RESULTS

GAm questions were almost universally answered, but heaping on 9 months resulted in underestimation of preterm birth rates. Preference for reporting GAw in even numbers was evident, resulting in heaping at 36 weeks; hence, over-estimating preterm birth rates, except in Matlab where the peak was at 38 weeks. Questions regarding 'born before expected' were answered but gave implausibly low preterm birth rates in most sites. Applying ultrasound as the gold standard in Matlab site, sensitivity of survey-GAw for detecting preterm birth (GAw <37) was 60% and specificity was 93%. Focus group findings suggest that women perceive GA to be important, but usually counted in months. Antenatal care attendance, women's education and health cards may improve reporting.

CONCLUSIONS

This is the first published study assessing GA reporting in surveys, compared with the gold standard of ultrasound. Reporting GAw within 5 years' recall is feasible with high completeness, but accuracy is affected by heaping. Compared to ultrasound-GAw, results are reasonably specific, but sensitivity needs to be improved. We propose revised questions based on the study findings for further testing and validation in settings where pregnancy ultrasound data and/or last menstrual period dates/GA recorded in pregnancy are available. Specific training of interviewers is recommended.

Stillbirth outcome capture and classification in population-based surveys: EN-INDEPTH study

BACKGROUND

Household surveys remain important sources of stillbirth data, but omission and misclassification are common. Classifying adverse pregnancy outcomes as stillbirths requires accurate reporting of vital status at birth and gestational age or birthweight for every pregnancy. Further categorisation, e.g. by sex, or timing (intrapartum/antepartum) improves data to understand and prevent stillbirth.

METHODS

We undertook a cross-sectional population-based survey of women of reproductive age in five health and demographic surveillance system sites in Bangladesh, Ethiopia, Ghana, Guinea-Bissau and Uganda (2017-2018). All women answered a full birth history with pregnancy loss questions (FBH+) or a full pregnancy history (FPH). A sub-sample across both groups were asked additional stillbirth questions. Questions were evaluated using descriptive measures. Using an interpretative paradigm and phenomenology methodology, focus group discussions with women exploring barriers to reporting birthweight for stillbirths were conducted. Thematic analysis was guided by an a priori codebook.

RESULTS

Overall 69,176 women reported 98,483 livebirths (FBH+) and 102,873 pregnancies (FPH). Additional questions were asked for 1453 stillbirths, 1528 neonatal deaths and 12,620 surviving children born in the 5 years prior to the survey. Completeness was high (> 99%) for existing FBH+/FPH questions on signs of life at birth and gestational age (months). Discordant responses in signs of life at birth between different questions were common; nearly one-quarter classified as stillbirths on FBH+/FPH were reported born alive on additional questions. Availability of information on gestational age (weeks) (58.1%) and birthweight (13.2%) was low amongst stillbirths, and heaping was common. Most women (93.9%) were able to report the sex of their stillborn baby. Response completeness for stillbirth timing (18.3-95.1%) and estimated proportion intrapartum (15.6-90.0%) varied by question and site. Congenital malformations were reported in 3.1% stillbirths. Perceived value in weighing a stillborn baby varied and barriers to weighing at birth a nd knowing birthweight were common.

CONCLUSIONS

Improving stillbirth data in surveys will require investment in improving the measurement of vital status, gestational age and birthweight by healthcare providers, communication of these with women, and overcoming reporting barriers. Given the large burden and effect on families, improved data must be made available to end preventable stillbirths.