Blencowe, H; (2020) Counting the smallest: data to estimate global stillbirth, preterm birth and low birthweight rates. PhD (research paper style) thesis, London School of Hygiene & Tropical Medicine. DOI: https://doi.org/10.17037/PUBS.04655794
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Abstract
Background: Stillbirth, preterm birth and low birthweight are important indicators of global burden of disease, status of maternal health and healthcare, and predictors of health throughout the life-course. Data are available through Civil Registration and Vital Statistics (CRVS), Health Management Information Systems (HMIS) and household surveys. Comparisons of data by country or over time requires standard definitions and comparable data quality. Data gaps and inconsistencies necessitate adjustments and use of modelled estimates in many settings. Methods: Systematic data searches were undertaken to compile available data on these outcomes for 195 countries. Where no reliable data were available, statistical models were used to generate national estimates. Data quantity and quality were summarised for each outcome, with implications for improvement and research. Results: The estimated burden remains large: 2.6 million stillbirths (2015), 14.9 million preterm births (2010) and 20.5 million low birthweight babies (2015) based on 4,392 data-points from 148 countries. Common data quality challenges include use of non-standard definitions, omission, and misclassification. Targeted data quality assessments are required to detect these. Five data gaps identified to address are: (1) coverage of data systems (2) accurate assessment of vital status at birth, birthweight and gestational age for every birth, (3) accurate recording of these key data elements (4) comparable collation within and across data systems and (5) use of data to inform programmes and policy. Evidence exists across all data platforms of examples of solutions to close these gaps. Systematic data linkage could increase efficiency. Conclusion: Data availability has increased over the last decade, even in the poorest countries. Data quality issues currently hamper the use of these data to improve outcomes in many settings, but could be addressed with political will and targeted investment. Ending preventable deaths among the world’s smallest babies requires that these data are accurate, available and used.
Item Type | Thesis |
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Thesis Type | Doctoral |
Thesis Name | PhD (research paper style) |
Contributors | Blencowe, H |
Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology |
Research Centre | Centre for Maternal, Reproductive and Child Health (MARCH) |
Grant number | Children's Investment Fund Foundation, Save the Children (Saving Newborn Lives Program), World Health Organization, Bill & Melinda Gates Foundation |
Copyright Holders | Hannah Blencowe |
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Filename: 2020_EPH_PhD_Blencowe_H-Copy.pdf
Licence: Creative Commons: Attribution-Noncommercial-No Derivative Works 3.0
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