Evidence map›Paper›PMID 37265999›Full record

ArticleGates open research2022

Study protocol for UNICEF and WHO estimates of global, regional, and national low birthweight prevalence for 2000 to 2020.

Julia Krasevec, Hannah Blencowe, Christopher Coffey, Yemisrach B Okwaraji, Diana Estevez, Gretchen A Stevens, Eric O Ohuma, Joel Conkle, Giovanna Gatica-Domínguez, Ellen Bradley and 5 more

Abstract read
In one paragraph

Article in Gates open research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

  1. Article
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  4. Article
  5. Article
  6. Observational
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Prenatal Aflatoxin BToxins · 2026
    Review
  13. Article
  14. Temporal and spatial analysis of low birth weight cases in Sergipe.Revista latino-americana de enfermagem · 2026
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Julia KrasevecDivision of Data, Analytics, Planning and Monitoring, United Nations Children's Fund, New York, NY, 10017, USA.ORCID https://orcid.org/0000-0003-0343-0404
Hannah BlencoweCentre for Maternal, Adolescent, Reproductive & Child Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Christopher CoffeyDivision of Data, Analytics, Planning and Monitoring, United Nations Children's Fund, New York, NY, 10017, USA.
Yemisrach B OkwarajiCentre for Maternal, Adolescent, Reproductive & Child Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Diana EstevezDivision of Data Analytics and Delivery for Impact, World Health Organization, Geneva, 1202, Switzerland.ORCID https://orcid.org/0000-0002-9966-2463
Gretchen A StevensIndependent Researcher, Los Angeles, CA, 90245, USA.
Eric O OhumaCentre for Maternal, Adolescent, Reproductive & Child Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.ORCID https://orcid.org/0000-0002-3116-2593
Joel ConkleDivision of Data, Analytics, Planning and Monitoring, United Nations Children's Fund, New York, NY, 10017, USA.
Giovanna Gatica-DomínguezDepartment of Nutrition and Food Safety, World Health Organization, Geneva, 1202, Switzerland.
Ellen BradleyCentre for Maternal, Adolescent, Reproductive & Child Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.ORCID https://orcid.org/0009-0009-4457-0762
Ben Kimathi MuthamiaDivision of Data, Analytics, Planning and Monitoring, United Nations Children's Fund, New York, NY, 10017, USA.
Nita DalmiyaProgramme Group, United Nations Children's Fund, New York, NY, 10017, USA.
Joy E LawnCentre for Maternal, Adolescent, Reproductive & Child Health, London School of Hygiene & Tropical Medicine, London, WC1E 7HT, UK.
Elaine Borghi *Department of Nutrition and Food Safety, World Health Organization, Geneva, 1202, Switzerland.
Chika Hayashi *Division of Data, Analytics, Planning and Monitoring, United Nations Children's Fund, New York, NY, 10017, USA.ORCID https://orcid.org/0000-0003-1583-6620

Funding

World Health Organization 001
6 · The paper itself

Abstract

Background Reducing low birthweight (LBW, weight at birth less than 2,500g) prevalence by at least 30% between 2012 and 2025 is a target endorsed by the World Health Assembly that can contribute to achieving Sustainable Development Goal 2 (Zero Hunger) by 2030. The 2019 LBW estimates indicated a global prevalence of 14.6% (20.5 million newborns) in 2015. We aim to develop updated LBW estimates at global, regional, and national levels for up to 202 countries for the period of 2000 to 2020. Methods Two types of sources for LBW data will be sought: national administrative data and population-based surveys. Administrative data will be searched for countries with a facility birth rate ≥80% and included when birthweight data account for ≥80% of UN estimated live births for that country and year. Surveys with birthweight data published since release of the 2019 edition of the LBW estimates will be adjusted using the standard methodology applied for the previous estimates. Risk of bias assessments will be undertaken. Covariates will be selected based on a conceptual framework of plausible associations with LBW, covariate time-series data quality, collinearity between covariates and correlations with LBW. National LBW prevalence will be estimated using a Bayesian multilevel-mixed regression model, then aggregated to derive regional and global estimates through population-weighted averages. Conclusion Whilst availability of LBW data has increased, especially with more facility births, gaps remain in the quantity and quality of data, particularly in low-and middle-income countries. Challenges include high percentages of missing data, lack of adherence to reporting standards, inaccurate measurement, and data heaping. Updated LBW estimates are important to highlight the global burden of LBW, track progress towards nutrition targets, and inform investments in programmes. Reliable, nationally representative data are key, alongside investments to improve the measurement and recording of an accurate birthweight for every baby.

Indexed as

Bayesian modellingglobal estimatesLow birthweightnewbornnutrition

Identifiers

PMID37265999
PMCPMC10229761

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.