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 - Moxon, Sarah G.
AU - Amouzou, Agbessi
N1 - Funding Information:
Firstly, and most importantly, we thank the women, their families, the health workers and data collectors. We credit the inspiration of the late Godfrey Mbaruku. We thank Claudia DaSilva, Veronica Ulaya, Mohammad Raisul Islam, Sudip Karki and Rabina Sarki for their administrative support and Sabrina Jabeen, Goutom Banik, Md. Shahidul Alam, Tamatun Islam Tanha and Md. Mohsiur Rahman for support during data collectors training. We acknowledge the following groups for their guidance and support: National Advisory Groups : Bangladesh : Mohammod Shahidullah, Khaleda Islam, Md Jahurul Islam. Nepal : Naresh P KC, Parashu Ram Shrestha. Tanzania : Muhammad Bakari Kambi, Georgina Msemo, Asia Hussein, Talhiya Yahya, Claud Kumalija, Eliudi Eliakimu, Mary Azayo, Mary Drake, Honest Kimaro. EN-BIRTH validation collaborative group : Bangladesh: Md. Ayub Ali, Bilkish Biswas, Rajib Haider, Md. Abu Hasanuzzaman, Md. Amir Hossain, Ishrat Jahan, Rowshan Hosne Jahan, Jasmin Khan, M A Mannan, Tapas Mazumder, Md. Hafizur Rahman, Md. Ziaul Haque Shaikh, Aysha Siddika, Taslima Akter Sumi, Md. Taqbir Us Samad Talha. Tanzania: Evelyne Assenga, Claudia Hanson, Edward Kija, Rodrick Kisenge, Karim Manji, Fatuma Manzi, Namala Mkopi, Mwifadhi Mrisho, Andrea Pembe. Nepal: Jagat Jeevan Ghimire, Rejina Gurung, Elisha Joshi, Avinash K Sunny, Naresh P. KC, Nisha Rana, Shree Krishna Shrestha, Dela Singh, Parashu Ram Shrestha, Nishant Thakur. LSHTM: Hannah Blencowe, Sarah G Moxon. EN-BIRTH Expert Advisory Group : Agbessi Amouzou, Tariq Azim, Debra Jackson, Theopista John Kabuteni, Matthews Mathai, Jean-Pierre Monet, Allisyn C Moran, Pavani K Ram, Barbara Rawlins, Jennifer Requejo, Johan Ivar Sæbø, Florina Serbanescu, Lara Vaz. We are also very grateful to fellow researchers who peer-reviewed this paper. This article has been published as part of BMC Pregnancy and Childbirth Volume 21 Supplement 1, 2021: Every Newborn BIRTH multi-country validation study: informing measurement of coverage and quality of maternal and newborn care. The full contents of the supplement are available online at https://bmcpregnancychildbirth.biomedcentral.com/articles/supplements/volume-21-supplement-1.
Funding Information:
The EN-BIRTH study was conceived by JEL, who acquired the funding and led the overall design with support from HR. Each of the three country research teams input to design of data collection tools and review processes, data collection and quality management with technical coordination from HR, GRGL, and DB. The iccdr,b team (notably AER, TT, TH, QSR, SA and SBZ) led the development of the software application, data dashboards and database development with VG and the LSHTM team. IHI (notably DS) coordinated work on barriers and enablers for data collection and use, working closely with LTD. QSR was the main lead for data management working closely with OB, KS and LTD. For this paper, SK and LTD led the analyses and first draft of manuscript working closely with KP, PM, HB, and JEL. All authors (SK, LTD, SBZ, KP, NS, AKS, DS, QSR, AKC, HR, SEA, PM, MEG, HB, JEL) revised the manuscript and gave final approval of the version to be published and agree to be accountable for the work. The EN-BIRTH study group authors made contributions to the conception, design, data collection or analysis or interpretation of data. This paper is published with permission from the Directors of Ifakara Health Institute, Muhimbili University of Health and Allied Sciences, icddr,b and Golden Community. The authors’ views are their own, and not necessarily from any of the institutions they represent. EN-BIRTH Study Group : Bangladesh : Qazi Sadeq-ur Rahman, Ahmed Ehsanur Rahman, Tazeen Tahsina, Sojib Bin Zaman, Shafiqul Ameen, Tanvir Hossain, Abu Bakkar Siddique, Aniqa Tasnim Hossain, Tapas Mazumder, Jasmin Khan, Taqbir Us Samad Talha, Rajib Haider, Md. Hafizur Rahman, Anisuddin Ahmed, Shams El Arifeen. Nepal : Omkar Basnet, Avinash K Sunny, Nishant Thakur, Rejina Gurung, Anjani Kumar Jha, Bijay Jha, Ram Chandra Bastola, Rajendra Paudel, Asmita Paudel, Ashish KC. Tanzania : Nahya Salim, Donat Shamba, Josephine Shabani, Kizito Shirima, Menna Narcis Tarimo, Godfrey Mbaruku (deceased), Honorati Masanja. LSHTM : Louise T Day, Harriet Ruysen, Kimberly Peven, Vladimir Sergeevich Gordeev, Georgia R Gore-Langton, Dorothy Boggs, Stefanie Kong, Angela Baschieri, Simon Cousens, Joy E Lawn.
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
VL - 21
JO - BMC Pregnancy and Childbirth
JF - BMC Pregnancy and Childbirth
SN - 1471-2393
M1 - 240
ER -