Birthweight: EN-BIRTH multi-country validation study

Abstract

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.

Keywords: Birth; Birthweight; Coverage; Health management information systems; Low birthweight; Maternal; Newborn; Stillbirth; Survey; Validity.

Fig. 1

Birthweight validation design, EN-BIRTH study. Adapted from EN-BIRTH protocol [23]

Fig. 2

Flow diagram for birthweight cases, EN-BIRTH study (n=23,471). Adapted from EN-BIRTH protocol [23]

Fig. 3

a Coverage rates for babies weighed at birth and b prevalence of low birthweight newborns measured by observation, exit-survey and register, EN-BIRTH study. *Random effects. a n = 22,880 births, b n = 22,423 births. BD Bangladesh, NP Nepal, TZ Tanzania

Fig. 4

Validity ratios for survey-reported and register-recorded low/normal birthweight prevalence compared to observation, EN-BIRTH study. Heat-mapped using WHO's Data Quality Review (DQR) 5%, 10%, 15% and 20% cutoffs [30]

Fig. 5

Gap analysis for coverage and quality of weighing practice at birth, EN-BIRTH study (n = 23,471). Stratified by vaginal and caesarean births in EN-BIRTH study (observer assessed n = 23,471, survey reported n = 20,349, and register recorded n = 21,440). BD Bangladesh, NP Nepal, TZ Tanzania

Fig. 6

Routine register design and data quality dimensions for birthweight by site, EN-BIRTH study. For basis of ranges, see WHO Data Quality Review [31]

Fig. 7

Barriers and enablers to routine register recording of birthweight, EN-BIRTH study. This figure illustrates the overall barriers and enablers to facility-based data collection identified by EN-BIRTH participants. The bold text are the issues specific to birthweight. The transition from red to green is a reminder that most factors identified by participants could serve as either a barrier or enabling factor depending on the facility-level resources and management