Evidence map›Paper›PMID 41161827›Full record

ArticleBMJ open2025

Mapping fine-scale spatial risk patterns of gestational diabetes over time in Australia: a nationwide geospatial study.

Wubet Worku Takele, Siew Lim, Kiki Adhinugraha, David Taniar, Lachlan L Dalli, Jacqueline A Boyle

Abstract read
In one paragraph

Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

6 authors.

Wubet Worku TakeleEastern Health Clinical School, Monash University, Melbourne, Victoria, Australia.ORCID http://orcid.org/0000-0003-3121-5808
Siew LimEastern Health Clinical School, Monash University, Melbourne, Victoria, Australia.ORCID http://orcid.org/0000-0002-5333-6451
Kiki AdhinugrahaDepartment of Computer Science and Information Technology, La Trobe University, Melbourne, Victoria, Australia.
David TaniarFaculty of Information Technology, Monash University, Melbourne, Victoria, Australia.
Lachlan L Dalli *Stroke and Ageing Research, Department of Medicine, Monash University, Clayton, Victoria, Australia.
Jacqueline A Boyle *Eastern Health Clinical School, Monash University, Melbourne, Victoria, Australia jacqueline.boyle@monash.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo examine the geospatial distribution of gestational diabetes mellitus (GDM) over time in Australia.

designAn ecological study was conducted using data from the National Diabetes Services Scheme (GDM cases). Data at Statistical Area Level 2 (SA2) level, a medium-sized spatial unit, on population denominators (women who gave birth) were obtained from the Australian Bureau of Statistics. The spatiotemporal distribution of GDM was explored at the SA2 level over three periods: 2016-2017, 2018-2019 and 2020-2021. Hotspot and cluster analyses were undertaken using Getis-Ord Gi* and local Moran's I statistics.

settingA nationwide study in Australia was conducted between 2016 and 2021.

participantsWomen diagnosed with GDM and those who gave birth were included. OUTCOME MEASURES: Age-standardised and crude incidence of GDM per SA2.

resultsDuring 2016-2021, 1 718 963 eligible women who gave birth in Australia were included. Hotspot areas of GDM were consistently observed in Victoria (Southwest and North Melbourne); Western Australia (South and Southwest Perth); Australian Capital Territory (ACT) (East and North Canberra); Queensland (North Brisbane) and New South Wales (West and Southwest Sydney and Southeast New South Wales). ACT (South Canberra), North Tasmania, Northern Territory (North Darwin) and Victoria (South East Melbourne) had new hotspot regions recorded in the last two consecutive study periods.

conclusionGDM incidence varies by geographical area over time, with hotspots in specific regions suggesting the need for geographically targeted policy interventions to curb the growing burden of GDM.

Indexed as

Diabetes, GestationalAdultAustraliaFemaleHumansIncidencePregnancyRisk FactorsSpatio-Temporal AnalysisDiabetes in pregnancyHealthHealth Equity

Identifiers

PMID41161827
PMCPMC12574405

What Socratic holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

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 Socratic graph.