Dataset Information

Validation of maternal reports for low birthweight and preterm birth indicators in rural Nepal.

ABSTRACT: Tracking progress towards global newborn health targets depends largely on maternal reported data collected through large, nationally representative surveys. We evaluated the validity, across a range of recall period lengths (1 to 24 months post-delivery), of maternal report of birthweight, birth size and length of pregnancy.We compared maternal reports to reference standards of birthweights measured within 72 hours of delivery and gestational age generated from reported first day of the last menstrual period (LMP) prospectively collected as part of a population-based study (n?=?1502). We calculated sensitivity, specificity, area the under the receiver operating curve (AUC) as a measure of individual-level accuracy, and the inflation factor (IF) to quantify population-level bias for each indicator. We assessed if length of recall period modified accuracy by stratifying measurements across time bins and using a modified Poisson regression with robust error variance to estimate the relative risk (RR) of correctly classifying newborns as low birthweight (LBW) or preterm, adjusting for child sex, place of delivery, maternal age, maternal education, parity, and ethnicity.The LBW indicator using maternally reported birthweight in grams had low individual-level accuracy (AUC?=?0.69) and high population-level bias (inflation factor IF?=?0.62). LBW using maternally reported birth size and the preterm birth indicator had lower individual-level accuracy (AUC?=?0.58 and 0.56, respectively) and higher population-level bias (IF?=?0.28 and 0.35, respectively) up to 24 months following birth. Length of recall time did not affect accuracy of LBW indicators. For the preterm birth indicator, accuracy did not change with length of recall up to 20 months after birth and improved slightly beyond 20 months.The use of maternal reports may underestimate and bias indicators for LBW and preterm birth. In settings with high prevalence of LBW and preterm births, these indicators generated from maternal reports may be more vulnerable to misclassification. In populations where an important proportion of births occur at home or where weight is not routinely measured, mothers perhaps place less importance on remembering size at birth. Further work is needed to explore whether these conclusions on the validity of maternal reports hold in similar rural and low-income settings.

SUBMITTER: Chang KT

PROVIDER: S-EPMC5997365 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Validation of maternal reports for low birthweight and preterm birth indicators in rural Nepal.

Chang Karen T KT Mullany Luke C LC Khatry Subarna K SK LeClerq Steven C SC Munos Melinda K MK Katz Joanne J

Journal of global health 20180601 1

<h4>Background</h4>Tracking progress towards global newborn health targets depends largely on maternal reported data collected through large, nationally representative surveys. We evaluated the validity, across a range of recall period lengths (1 to 24 months post-delivery), of maternal report of birthweight, birth size and length of pregnancy.<h4>Methods</h4>We compared maternal reports to reference standards of birthweights measured within 72 hours of delivery and gestational age generated fro ...[more]

PMID: 29899981

Similar Datasets

Project description:ObjectivesObservational studies have identified associations between periodontitis and adverse pregnancy outcomes, but randomised controlled trials evaluating the efficacy of periodontal therapy have yielded inconsistent results. Few studies have explored relationships between gingival inflammation and these outcomes or been conducted in rural, low-income communities, where confounding risk factors differ from other settings.MethodsWe conducted a community-based, prospective cohort study with the aim of estimating associations between the extent of gingival inflammation in pregnant women and incidence of preterm birth in rural Nepal. Our primary exposure was gingival inflammation, defined as bleeding on probing (BOP) ≥10%, stratified by BOP <30% and BOP ≥30%. A secondary exposure, mild periodontitis, was defined as ≥2 interproximal sites with probing depth (PD) ≥4 mm (different teeth) or one site with PD ≥5 mm. Our primary outcome was preterm birth (<37 weeks gestation). We used Poisson regression to model this relationship, adjusting for potential confounders.ResultsOf 1394 participants, 554 (39.7%) had gingival inflammation, 54 (3.9%) mild periodontitis and 197 (14.1%) delivered preterm. In the adjusted regression model, increasing extent of gingival inflammation was associated with a non-significant increase in risk of preterm birth (BOP ≥30% vs no BOP: adjusted relative risk (aRR) 1.37, 95% CI: 0.81 to 2.32). A secondary analysis, stratifying participants by when in pregnancy their oral health status was assessed, showed an association between gingival inflammation and preterm birth among women examined in their first trimester (BOP ≥30% vs no BOP: aRR 2.57, 95% CI: 1.11 to 5.95), but not later in pregnancy (BOP ≥30% vs no BOP: aRR 1.05, 95% CI: 0.52 to 2.11).ConclusionsGingival inflammation in women examined early in pregnancy and poor oral hygiene behaviours were risk factors for preterm birth. Future studies should evaluate community-based oral health interventions that specifically target gingival inflammation, delivered early in or before pregnancy, on preterm birth.Trial registration numberNepal Oil Massage Study, NCT01177111.

Project description:BackgroundAccurate 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.MethodsThe 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.ResultsAmong 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.ConclusionsHospital 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.

Project description:BACKGROUND:Approximately 20.5 million infants were born weighing <2500 g (defined as low birthweight or LBW) in 2015, primarily in low- and middle-income countries (LMICs). Infants born LBW, including those born preterm (<37 weeks gestation), are at increased risk for numerous consequences, including neonatal mortality and morbidity as well as suboptimal health and nutritional status later in life. The objective of this study was to identify predictors of LBW and preterm birth among infants in rural Uganda. METHODS:Data were derived from a prospective birth cohort study conducted from 2014-2016 in 12 districts across northern and southwestern Uganda. Birth weights were measured in triplicate to the nearest 0.1 kg by trained enumerators within 72 hours of delivery. Gestational age was calculated from the first day of last menstrual period (LMP). Associations between household, maternal, and infant characteristics and birth outcomes (LBW and preterm birth) were assessed using bivariate and multivariable logistic regression with stepwise, backward selection analyses. RESULTS:Among infants in the study, 4.3% were born LBW (143/3,337), and 19.4% were born preterm (744/3,841). In multivariable analysis, mothers who were taller (>150 cm) (adjusted Odds Ratio (aOR) = 0.42 (95% CI = 0.24, 0.72)), multigravida (aOR = 0.62 (95% CI = 0.39, 0.97)), or with adequate birth spacing (>24 months) (aOR = 0.60 (95% CI = 0.39, 0.92)) had lower odds of delivering a LBW infant Mothers with severe household food insecurity (aOR = 1.84 (95% CI = 1.22, 2.79)) or who tested positive for malaria during pregnancy (aOR = 2.06 (95% CI = 1.10, 3.85)) had higher odds of delivering a LBW infant. In addition, in multivariable analysis, mothers who resided in the Southwest (aOR = 0.64 (95% CI = 0.54, 0.76)), were ?20 years old (aOR = 0.76 (95% CI = 0.61, 0.94)), with adequate birth spacing (aOR = 0.76 (95% CI = 0.63, 0.93)), or attended ?4 antenatal care (ANC) visits (aOR = 0.56 (95% CI = 0.47, 0.67)) had lower odds of delivering a preterm infant; mothers who were neither married nor cohabitating (aOR = 1.42 (95% CI = 1.00, 2.00)) or delivered at home (aOR = 1.25 (95% CI = 1.04, 1.51)) had higher odds. CONCLUSIONS:In rural Uganda, severe household food insecurity, adolescent pregnancy, inadequate birth spacing, malaria infection, suboptimal ANC attendance, and home delivery represent modifiable risk factors associated with higher rates of LBW and/or preterm birth. Future studies on interventions to address these risk factors may be warranted.

Project description:BackgroundPreterm birth continues to be a major public health problem contributing to 75% of the neonatal mortality worldwide. Low birth weight (LBW) is an important but imperfect surrogate for prematurity when accurate assessment of gestational age is not possible. While there is overlap between preterm birth and LBW newborns, those that are both premature and LBW are at the highest risk of adverse neonatal outcomes. Understanding the epidemiology of preterm birth and LBW is important for prevention and improved care for at risk newborns, but in many countries, data are sparse and incomplete.MethodsWe conducted data analyses using the Global Network's (GN) population-based registry of pregnant women and their babies in rural communities in six low- and middle-income countries (Democratic Republic of Congo, Kenya, Zambia, Guatemala, India and Pakistan). We analyzed data from January 2014 to December 2018. Trained study staff enrolled all pregnant women in the study catchment area as early as possible during pregnancy and conducted follow-up visits shortly after delivery and at 42 days after delivery. We analyzed the rates of preterm birth, LBW and the combination of preterm birth and LBW and studied risk factors associated with these outcomes across the GN sites.ResultsA total of 272,192 live births were included in the analysis. The overall preterm birth rate was 12.6% (ranging from 8.6% in Belagavi, India to 21.8% in the Pakistani site). The overall LBW rate was 13.6% (ranging from 2.7% in the Kenyan site to 21.4% in the Pakistani site). The overall rate of both preterm birth and LBW was 5.5% (ranging from 1.2% in the Kenyan site to 11.0% in the Pakistani site). Risk factors associated with preterm birth, LBW and the combination were similar across sites and included nulliparity [RR - 1.27 (95% CI 1.21-1.33)], maternal age under 20 [RR 1.41 (95% CI 1.32-1.49)] years, severe antenatal hemorrhage [RR 5.18 95% CI 4.44-6.04)], hypertensive disorders [RR 2.74 (95% CI - 1.21-1.33], and 1-3 antenatal visits versus four or more [RR 1.68 (95% CI 1.55-1.83)].ConclusionsPreterm birth, LBW and their combination continue to be common public health problems at some of the GN sites, particularly among young, nulliparous women who have received limited antenatal care services. Trial registration The identifier of the Maternal and Newborn Health Registry at ClinicalTrials.gov is NCT01073475.Trial registrationThe identifier of the Maternal and Newborn Health Registry at ClinicalTrials.gov is NCT01073475.

Project description:BackgroundLow birthweight (LBW) (< 2500 g) is a significant determinant of infant morbidity and mortality worldwide. In low-income settings, the quality of birthweight data suffers from measurement and recording errors, inconsistent data reporting systems, and missing data from non-facility births. This paper describes birthweight data quality and the prevalence of LBW before and after implementation of a birthweight quality improvement (QI) initiative in Amhara region, Ethiopia.MethodsA comparative pre-post study was performed in selected rural health facilities located in West Gojjam and South Gondar zones. At baseline, a retrospective review of delivery records from February to May 2018 was performed in 14 health centers to collect birthweight data. A birthweight QI initiative was introduced in August 2019, which included provision of high-quality digital infant weight scales (precision 5 g), routine calibration, training in birth weighing and data recording, and routine field supervision. After the QI implementation, birthweight data were prospectively collected from late August to early September 2019, and December 2019 to June 2020. Data quality, as measured by heaping (weights at exact multiples of 500 g) and rounding to the nearest 100 g, and the prevalence of LBW were calculated before and after QI implementation.ResultsWe retrospectively reviewed 1383 delivery records before the QI implementation and prospectively measured 1371 newborn weights after QI implementation. Heaping was most frequently observed at 3000 g and declined from 26% pre-initiative to 6.7% post-initiative. Heaping at 2500 g decreased from 5.4% pre-QI to 2.2% post-QI. The percentage of rounding to the nearest 100 g was reduced from 100% pre-initiative to 36.5% post-initiative. Before the QI initiative, the prevalence of recognized LBW was 2.2% (95% confidence interval [CI]: 1.5-3.1) and after the QI initiative increased to 11.7% (95% CI: 10.1-13.5).ConclusionsA QI intervention can improve the quality of birthweight measurements, and data measurement quality may substantially affect estimates of LBW prevalence.

Project description:BackgroundPopulation-based household surveys, notably the Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), remain the main source of maternal and newborn health data for many low- and middle-income countries. As part of the Every Newborn Birth Indicators Research Tracking in Hospitals (EN-BIRTH) study, this paper focuses on testing validity of measurement of maternal and newborn indicators around the time of birth (intrapartum and postnatal) in survey-report.MethodsEN-BIRTH was an observational study testing the validity of measurement for selected maternal and newborn indicators in five secondary/tertiary hospitals in Bangladesh, Nepal and Tanzania, conducted from July 2017 to July 2018. We compared women's report at exit survey with the gold standard of direct observation or verification from clinical records for women with vaginal births. Population-level validity was assessed by validity ratios (survey-reported coverage: observer-assessed coverage). Individual-level accuracy was assessed by sensitivity, specificity and percent agreement. We tested indicators already in DHS/MICS as well as indicators with potential to be included in population-based surveys, notably the first validation for small and sick newborn care indicators.Results33 maternal and newborn indicators were evaluated. Amongst nine indicators already present in DHS/MICS, validity ratios for baby dried or wiped, birthweight measured, low birthweight, and sex of baby (female) were between 0.90-1.10. Instrumental birth, skin-to-skin contact, and early initiation of breastfeeding were highly overestimated by survey-report (2.04-4.83) while umbilical cord care indicators were massively underestimated (0.14-0.22). Amongst 24 indicators not currently in DHS/MICS, two newborn contact indicators (kangaroo mother care 1.00, admission to neonatal unit 1.01) had high survey-reported coverage amongst admitted newborns and high sensitivity. The remaining indicators did not perform well and some had very high "don't know" responses.ConclusionsOur study revealed low validity for collecting many maternal and newborn indicators through an exit survey instrument, even with short recall periods among women with vaginal births. Household surveys are already at risk of overload, and some specific clinical care indicators do not perform well and may be under-powered. Given that approximately 80% of births worldwide occur in facilities, routine registers should also be explored to track coverage of key maternal and newborn health interventions, particularly for clinical care.

Dataset Information

Validation of maternal reports for low birthweight and preterm birth indicators in rural Nepal.

Publications

Validation of maternal reports for low birthweight and preterm birth indicators in rural Nepal.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets