dc.contributor.author |
Lawrence, Robyn L |
en |
dc.contributor.author |
Wall, Clare |
en |
dc.contributor.author |
Bloomfield, Francis |
en |
dc.date.accessioned |
2020-01-13T00:01:52Z |
en |
dc.date.issued |
2019-10-11 |
en |
dc.identifier.citation |
BMC pregnancy and childbirth 19(1):349 11 Oct 2019 |
en |
dc.identifier.issn |
1471-2393 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/49652 |
en |
dc.description.abstract |
BACKGROUND:It is well recognized that prevalence of gestational diabetes mellitus (GDM) varies depending on the population studied and the diagnostic criteria used. The data source used also can lead to substantial differences in the reporting of GDM prevalence but is considered less frequently. Accurate estimation of GDM prevalence is important for service planning and evaluation, policy development, and research. We aimed to determine the prevalence of GDM in a cohort of New Zealand women using a variety of data sources and to evaluate the agreement between different data sources. METHODS:A retrospective analysis of prospectively collected data from the Growing Up in New Zealand Study, consisting of a cohort of 6822 pregnant women residing in a geographical area defined by three regional health boards in New Zealand. Prevalence of GDM was estimated using four commonly used data sources. Coded clinical data on diabetes status were collected from regional health boards and the Ministry of Health's National Minimum Dataset, plasma glucose results were collected from laboratories servicing the recruitment catchment area and coded according to the New Zealand Society for the Study of Diabetes diagnostic criteria, and self-reported diabetes status collected via interview administered questionnaires. Agreement between data sources was calculated using the proportion of agreement with 95% confidence intervals for both a positive and negative diagnosis of GDM. RESULTS:Prevalence of GDM combining data from all sources in the Growing Up in New Zealand cohort was 6.2%. Estimates varied from 3.8 to 6.9% depending on the data source. The proportion of agreement between data sources for presence of GDM was 0.70 (95% CI 0.65, 0.75). A third of women who had a diagnosis of GDM according to medical data reported having no diabetes in interview administered questionnaires. CONCLUSION:Prevalence of GDM varies considerably depending on the data source used. Health services need to be aware of this and to understand the limitations of local data sources to ensure service planning and evaluation, policy development and research are appropriate for the local prevalence. Improved communication of the diagnosis may assist women's self-management of GDM. |
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dc.format.medium |
Electronic |
en |
dc.language |
eng |
en |
dc.relation.ispartofseries |
BMC pregnancy and childbirth |
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dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
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dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.rights.uri |
https://creativecommons.org/licenses/by/4.0/ |
en |
dc.subject |
Humans |
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dc.subject |
Diabetes, Gestational |
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dc.subject |
Blood Glucose |
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dc.subject |
Prevalence |
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dc.subject |
Cohort Studies |
en |
dc.subject |
Pregnancy |
en |
dc.subject |
Social Class |
en |
dc.subject |
Information Storage and Retrieval |
en |
dc.subject |
Databases, Factual |
en |
dc.subject |
Adult |
en |
dc.subject |
Asian Continental Ancestry Group |
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dc.subject |
European Continental Ancestry Group |
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dc.subject |
Oceanic Ancestry Group |
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dc.subject |
Laboratories |
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dc.subject |
New Zealand |
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dc.subject |
Female |
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dc.subject |
Young Adult |
en |
dc.subject |
Self Report |
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dc.subject |
Surveys and Questionnaires |
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dc.title |
Prevalence of gestational diabetes according to commonly used data sources: an observational study. |
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dc.type |
Journal Article |
en |
dc.identifier.doi |
10.1186/s12884-019-2521-2 |
en |
pubs.issue |
1 |
en |
pubs.begin-page |
349 |
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pubs.volume |
19 |
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dc.rights.holder |
Copyright: The authors |
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pubs.publication-status |
Published |
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dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
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pubs.subtype |
research-article |
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pubs.subtype |
Journal Article |
en |
pubs.subtype |
Observational Study |
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pubs.elements-id |
784195 |
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pubs.org-id |
Liggins Institute |
en |
pubs.org-id |
LiFePATH |
en |
pubs.org-id |
Medical and Health Sciences |
en |
pubs.org-id |
Medical Sciences |
en |
pubs.org-id |
Nutrition |
en |
dc.identifier.eissn |
1471-2393 |
en |
pubs.record-created-at-source-date |
2019-10-13 |
en |
pubs.dimensions-id |
31604463 |
en |