Gestational Diabetes Prevalence Estimates from Three Data Sources, 2018
Introduction We investigated 2018 gestational diabetes mellitus (GDM) prevalence estimates in three surveillance systems (National Vital Statistics System, State Inpatient Database, and Pregnancy Risk Assessment Monitoring Survey). Methods We calculated GDM prevalence for jurisdictions represented i...
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Published in | Maternal and child health journal Vol. 28; no. 8; pp. 1308 - 1314 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
Springer US
01.08.2024
Springer Springer Nature B.V |
Subjects | |
Online Access | Get full text |
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Summary: | Introduction
We investigated 2018 gestational diabetes mellitus (GDM) prevalence estimates in three surveillance systems (National Vital Statistics System, State Inpatient Database, and Pregnancy Risk Assessment Monitoring Survey).
Methods
We calculated GDM prevalence for jurisdictions represented in each system; a subset of data was analyzed for people 18–39 years old in 22 jurisdictions present in all three systems to observe dataset-specific demographics and GDM prevalence using comparable categories.
Results
GDM prevalence estimates varied widely by data system and within the data subset despite comparable demographics.
Discussion
Understanding the differences between GDM surveillance data systems can help researchers better identify people and places at higher risk of GDM.
Significance
What is Already Known on this Subject?
Gestational diabetes mellitus (GDM) prevalence varies by data system and population. Estimates of GDM prevalence are essential to inform prevention, identification, and management programs.
What this Report Adds?
GDM prevalence estimates varied widely by data system (NVSS, SID, PRAMS) and participant demographics varied only slightly when a subset of comparable data were evaluated using jurisdictions available in all three systems (21 states and the District of Columbia). Understanding the differences between surveillance data systems can help researchers better identify people and places at higher risk of GDM. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1092-7875 1573-6628 1573-6628 |
DOI: | 10.1007/s10995-024-03935-1 |