TY - JOUR
T1 - Birthweight
T2 - EN-BIRTH multi-country validation study
AU - EN-BIRTH Study Group
AU - Kong, Stefanie
AU - Day, Louise T.
AU - Zaman, Sojib Bin
AU - Peven, Kimberly
AU - Salim, Nahya
AU - Sunny, Avinash K.
AU - Shamba, Donat
AU - Rahman, Qazi Sadeq ur
AU - K.C, Ashish
AU - Ruysen, Harriet
AU - El Arifeen, Shams
AU - Mee, Paul
AU - Gladstone, Miriam E.
AU - Blencowe, Hannah
AU - Lawn, Joy E.
AU - Ali, Md Ayub
AU - Biswas, Bilkish
AU - Haider, Rajib
AU - Hasanuzzaman, Md Abu
AU - Hossain, Md Amir
AU - Jahan, Ishrat
AU - Jahan, Rowshan Hosne
AU - Khan, Jasmin
AU - Mannan, M. A.
AU - Mazumder, Tapas
AU - Rahman, Md Hafizur
AU - Shaikh, Md Ziaul Haque
AU - Siddika, Aysha
AU - Sumi, Taslima Akter
AU - Talha, Md Taqbir Us Samad
AU - Assenga, Evelyne
AU - Hanson, Claudia
AU - Kija, Edward
AU - Kisenge, Rodrick
AU - Manji, Karim
AU - Manzi, Fatuma
AU - Mkopi, Namala
AU - Mrisho, Mwifadhi
AU - Pembe, Andrea
AU - Ghimire, Jagat Jeevan
AU - Gurung, Regina
AU - Joshi, Elisha
AU - Kc, Naresh P.
AU - Rana, Nisha
AU - Shrestha, Shree Krishna
AU - Singh, Dela
AU - Shrestha, Parashu Ram
AU - Thakur, Nishant
AU - Amouzou, Agbessi
AU - Requejo, Jennifer
N1 - Publisher Copyright:
© 2021, The Author(s).
PY - 2021/3
Y1 - 2021/3
N2 - 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.
AB - 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.
KW - Birth
KW - Birthweight
KW - Coverage
KW - Health management information systems
KW - Low birthweight
KW - Maternal
KW - Newborn
KW - Stillbirth
KW - Survey
KW - Validity
UR - http://www.scopus.com/inward/record.url?scp=85100752035&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85100752035&partnerID=8YFLogxK
U2 - 10.1186/s12884-020-03355-3
DO - 10.1186/s12884-020-03355-3
M3 - Article
C2 - 33765936
AN - SCOPUS:85100752035
SN - 1471-2393
VL - 21
JO - BMC pregnancy and childbirth
JF - BMC pregnancy and childbirth
M1 - 240
ER -