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...
Gespeichert in:
| Veröffentlicht in: | Maternal and child health journal 2024-08, Vol.28 (8), p.1308-1314 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1314 |
|---|---|
| container_issue | 8 |
| container_start_page | 1308 |
| container_title | Maternal and child health journal |
| container_volume | 28 |
| creator | Bolduc, Michele L.F. Mercado, Carla I. Zhang, Yan Lundeen, Elizabeth A. Ford, Nicole D. Bullard, Kai McKeever Carty, Denise C. |
| description | 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. |
| doi_str_mv | 10.1007/s10995-024-03935-1 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11269331</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3061784406</sourcerecordid><originalsourceid>FETCH-LOGICAL-c356t-a7f509d9dbcfee92649fe4365d3cecabc14e88f796c430c0e7e692023b24563b3</originalsourceid><addsrcrecordid>eNp9kUtLxDAUhYMovv-ACym4cWH15tlkJeJjFAQFdR3SzK1WOq0mHcF_b-qM42PhKiH3uyfn3kPIDoVDClAcRQrGyByYyIEbLnO6RNapLHiuFNPL6Q6G5YUu5BrZiPEZILWBWCVrXGswAuQ6GY0w9q6vu9Y12VntSuwxZrcB31yDrcfsPPb1xA2PVegm2f1TQMzOXO-yu24aPMaDjAHVW2Slck3E7fm5SR4uzu9PL_Prm9HV6cl17rlUfe6KSoIZm3HpK0TDlDAVCq7kmHv0rvRUoNZVYZQXHDxggcowYLxkQipe8k1yPNN9mZYTHHts--Aa-xKSyfBuO1fb35W2frKP3ZullCnDOU0K-3OF0L1O0_R2UkePTeNa7KbRclC00EKASujeH_Q5zZw2NVBapG1SMVBsRvnQxRiwWrihYIeg7Cwom4Kyn0HZwcXuzzkWLV_JJIDPgJhK7SOG77__kf0A20mdbQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3084100146</pqid></control><display><type>article</type><title>Gestational Diabetes Prevalence Estimates from Three Data Sources, 2018</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><creator>Bolduc, Michele L.F. ; Mercado, Carla I. ; Zhang, Yan ; Lundeen, Elizabeth A. ; Ford, Nicole D. ; Bullard, Kai McKeever ; Carty, Denise C.</creator><creatorcontrib>Bolduc, Michele L.F. ; Mercado, Carla I. ; Zhang, Yan ; Lundeen, Elizabeth A. ; Ford, Nicole D. ; Bullard, Kai McKeever ; Carty, Denise C.</creatorcontrib><description>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.</description><identifier>ISSN: 1092-7875</identifier><identifier>ISSN: 1573-6628</identifier><identifier>EISSN: 1573-6628</identifier><identifier>DOI: 10.1007/s10995-024-03935-1</identifier><identifier>PMID: 38809405</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Adolescent ; Adult ; Brief Report ; Databases, Factual ; Demographics ; Diabetes, Gestational - epidemiology ; Female ; Gestational diabetes ; Gynecology ; Humans ; Information Sources ; Jurisdiction ; Maternal and Child Health ; Medicine ; Medicine & Public Health ; Pediatrics ; Population Economics ; Population Surveillance - methods ; Pregnancy ; Prevalence ; Public Health ; Risk assessment ; Risk Assessment - methods ; Sociology ; Surveillance ; United States - epidemiology ; Vital statistics ; Young Adult</subject><ispartof>Maternal and child health journal, 2024-08, Vol.28 (8), p.1308-1314</ispartof><rights>This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024</rights><rights>2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.</rights><rights>This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2024 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c356t-a7f509d9dbcfee92649fe4365d3cecabc14e88f796c430c0e7e692023b24563b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10995-024-03935-1$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10995-024-03935-1$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>230,314,777,781,882,27905,27906,41469,42538,51300</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38809405$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bolduc, Michele L.F.</creatorcontrib><creatorcontrib>Mercado, Carla I.</creatorcontrib><creatorcontrib>Zhang, Yan</creatorcontrib><creatorcontrib>Lundeen, Elizabeth A.</creatorcontrib><creatorcontrib>Ford, Nicole D.</creatorcontrib><creatorcontrib>Bullard, Kai McKeever</creatorcontrib><creatorcontrib>Carty, Denise C.</creatorcontrib><title>Gestational Diabetes Prevalence Estimates from Three Data Sources, 2018</title><title>Maternal and child health journal</title><addtitle>Matern Child Health J</addtitle><addtitle>Matern Child Health J</addtitle><description>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.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Brief Report</subject><subject>Databases, Factual</subject><subject>Demographics</subject><subject>Diabetes, Gestational - epidemiology</subject><subject>Female</subject><subject>Gestational diabetes</subject><subject>Gynecology</subject><subject>Humans</subject><subject>Information Sources</subject><subject>Jurisdiction</subject><subject>Maternal and Child Health</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Pediatrics</subject><subject>Population Economics</subject><subject>Population Surveillance - methods</subject><subject>Pregnancy</subject><subject>Prevalence</subject><subject>Public Health</subject><subject>Risk assessment</subject><subject>Risk Assessment - methods</subject><subject>Sociology</subject><subject>Surveillance</subject><subject>United States - epidemiology</subject><subject>Vital statistics</subject><subject>Young Adult</subject><issn>1092-7875</issn><issn>1573-6628</issn><issn>1573-6628</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><recordid>eNp9kUtLxDAUhYMovv-ACym4cWH15tlkJeJjFAQFdR3SzK1WOq0mHcF_b-qM42PhKiH3uyfn3kPIDoVDClAcRQrGyByYyIEbLnO6RNapLHiuFNPL6Q6G5YUu5BrZiPEZILWBWCVrXGswAuQ6GY0w9q6vu9Y12VntSuwxZrcB31yDrcfsPPb1xA2PVegm2f1TQMzOXO-yu24aPMaDjAHVW2Slck3E7fm5SR4uzu9PL_Prm9HV6cl17rlUfe6KSoIZm3HpK0TDlDAVCq7kmHv0rvRUoNZVYZQXHDxggcowYLxkQipe8k1yPNN9mZYTHHts--Aa-xKSyfBuO1fb35W2frKP3ZullCnDOU0K-3OF0L1O0_R2UkePTeNa7KbRclC00EKASujeH_Q5zZw2NVBapG1SMVBsRvnQxRiwWrihYIeg7Cwom4Kyn0HZwcXuzzkWLV_JJIDPgJhK7SOG77__kf0A20mdbQ</recordid><startdate>20240801</startdate><enddate>20240801</enddate><creator>Bolduc, Michele L.F.</creator><creator>Mercado, Carla I.</creator><creator>Zhang, Yan</creator><creator>Lundeen, Elizabeth A.</creator><creator>Ford, Nicole D.</creator><creator>Bullard, Kai McKeever</creator><creator>Carty, Denise C.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20240801</creationdate><title>Gestational Diabetes Prevalence Estimates from Three Data Sources, 2018</title><author>Bolduc, Michele L.F. ; Mercado, Carla I. ; Zhang, Yan ; Lundeen, Elizabeth A. ; Ford, Nicole D. ; Bullard, Kai McKeever ; Carty, Denise C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-a7f509d9dbcfee92649fe4365d3cecabc14e88f796c430c0e7e692023b24563b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Brief Report</topic><topic>Databases, Factual</topic><topic>Demographics</topic><topic>Diabetes, Gestational - epidemiology</topic><topic>Female</topic><topic>Gestational diabetes</topic><topic>Gynecology</topic><topic>Humans</topic><topic>Information Sources</topic><topic>Jurisdiction</topic><topic>Maternal and Child Health</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Pediatrics</topic><topic>Population Economics</topic><topic>Population Surveillance - methods</topic><topic>Pregnancy</topic><topic>Prevalence</topic><topic>Public Health</topic><topic>Risk assessment</topic><topic>Risk Assessment - methods</topic><topic>Sociology</topic><topic>Surveillance</topic><topic>United States - epidemiology</topic><topic>Vital statistics</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bolduc, Michele L.F.</creatorcontrib><creatorcontrib>Mercado, Carla I.</creatorcontrib><creatorcontrib>Zhang, Yan</creatorcontrib><creatorcontrib>Lundeen, Elizabeth A.</creatorcontrib><creatorcontrib>Ford, Nicole D.</creatorcontrib><creatorcontrib>Bullard, Kai McKeever</creatorcontrib><creatorcontrib>Carty, Denise C.</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Maternal and child health journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bolduc, Michele L.F.</au><au>Mercado, Carla I.</au><au>Zhang, Yan</au><au>Lundeen, Elizabeth A.</au><au>Ford, Nicole D.</au><au>Bullard, Kai McKeever</au><au>Carty, Denise C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Gestational Diabetes Prevalence Estimates from Three Data Sources, 2018</atitle><jtitle>Maternal and child health journal</jtitle><stitle>Matern Child Health J</stitle><addtitle>Matern Child Health J</addtitle><date>2024-08-01</date><risdate>2024</risdate><volume>28</volume><issue>8</issue><spage>1308</spage><epage>1314</epage><pages>1308-1314</pages><issn>1092-7875</issn><issn>1573-6628</issn><eissn>1573-6628</eissn><abstract>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.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>38809405</pmid><doi>10.1007/s10995-024-03935-1</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1092-7875 |
| ispartof | Maternal and child health journal, 2024-08, Vol.28 (8), p.1308-1314 |
| issn | 1092-7875 1573-6628 1573-6628 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11269331 |
| source | MEDLINE; Springer Nature - Complete Springer Journals |
| subjects | Adolescent Adult Brief Report Databases, Factual Demographics Diabetes, Gestational - epidemiology Female Gestational diabetes Gynecology Humans Information Sources Jurisdiction Maternal and Child Health Medicine Medicine & Public Health Pediatrics Population Economics Population Surveillance - methods Pregnancy Prevalence Public Health Risk assessment Risk Assessment - methods Sociology Surveillance United States - epidemiology Vital statistics Young Adult |
| title | Gestational Diabetes Prevalence Estimates from Three Data Sources, 2018 |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T19%3A18%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Gestational%20Diabetes%20Prevalence%20Estimates%20from%20Three%20Data%20Sources,%202018&rft.jtitle=Maternal%20and%20child%20health%20journal&rft.au=Bolduc,%20Michele%20L.F.&rft.date=2024-08-01&rft.volume=28&rft.issue=8&rft.spage=1308&rft.epage=1314&rft.pages=1308-1314&rft.issn=1092-7875&rft.eissn=1573-6628&rft_id=info:doi/10.1007/s10995-024-03935-1&rft_dat=%3Cproquest_pubme%3E3061784406%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3084100146&rft_id=info:pmid/38809405&rfr_iscdi=true |