Evidence map›Paper›PMID 33933801›Full record

ArticleSocial science & medicine (1982)2021

Type 1 Diabetes incidence among youth in Utah: A geographical analysis.

Matthew L McCullough, Neng Wan, Marcus G Pezzolesi, Timothy W Collins, Sara Elizbeth Grineski, Yehua Dennis Wei, Jose Lazaro-Guevara, Scott G Frodsham, James A Vanderslice, John R Holmen and 2 more

Abstract read
In one paragraph

Article in Social science & medicine (1982), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 2 pooled it
–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

5 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Observational
  5. 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

12 authors.

Matthew L McCulloughDepartment of Geography, University of Utah, Salt Lake City, UT, USA. Electronic address: matthew.mccullough@geog.utah.edu.
Neng WanDepartment of Geography, University of Utah, Salt Lake City, UT, USA.
Marcus G PezzolesiDiabetes and Metabolism Research Center, University of Utah School of Medicine, Salt Lake City, UT, USA; Division of Nephrology and Hypertension, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA; Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Timothy W CollinsDepartment of Geography, University of Utah, Salt Lake City, UT, USA.
Sara Elizbeth GrineskiDepartment of Sociology, University of Utah, Salt Lake City, UT, USA.
Yehua Dennis WeiDepartment of Geography, University of Utah, Salt Lake City, UT, USA.
Jose Lazaro-GuevaraDivision of Nephrology and Hypertension, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA; Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Scott G FrodshamDivision of Nephrology and Hypertension, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA.
James A VandersliceDivision of Public Health, University of Utah School of Medicine, Salt Lake City, UT, USA.
John R HolmenMedical Informatics Department, Intermountain Healthcare, Salt Lake City, UT, USA.
Titte R SrinivasDivision of Nephrology and Hypertension, Case Western Reserve University/University Hospitals Cleveland Medical Center, Cleveland, OH, USA.
Scott A ClementsDepartment of Pediatrics, University of Utah, Salt Lake City, UT, USA.

Funding

UTAH REGIONAL CANCER CENTERP30CA042014 · NCI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI KATHARINE S ULLMAN · 1986 to 2026
$72.6M
Utah Center for Clinical and Translational ScienceUL1TR002538 · NCATS · UNIVERSITY OF UTAH · PI HESS, RACHEL, MAJERSIK, JENNIFER JUHL · 2018 to 2022
$26.0M
NCATS NIH HHS UL1 TR002538NCI NIH HHS P30 CA042014
6 · The paper itself

Abstract

Type 1 Diabetes (T1D) poses an increasing threat to public health, as incidence rates continue to rise globally. However, the etiology of T1D is still poorly understood, especially from the perspective of geography. The objective of this research is to examine the incidence of T1D among youth and to identify high-risk clusters and their association with socio-demographic and geographic variables. The study area was the entire state of Utah and included youth with T1D from birth to 19 years of age from 1998 to 2015 (n = 4161). Spatial clustering was measured both globally and locally using the Moran's I statistic and spatial scan statistic. Ordinary least squares (OLS) regression was used to measure the association of high-risk clusters with certain risk factors at the Census Block Group (CBG) level. The mean age at diagnosis was 9.3 years old. The mean incidence rate was 25.67 per 100,000 person-years (95% CI, 24.57-26.75). The incidence rate increased by 14%, from 23.94 per100,000 person-years in 1998 to 27.98 per 100,000 person-years in 2015, with an annual increase of 0.80%. The results of the spatial scan statistic found 42 high-risk clusters throughout the state. OLS regression analysis found a significant association with median household income, population density, and latitude. This study provides evidence that incidence rates of T1D are increasing annually in the state of Utah and that significant geographic high-risk clusters are associated with socio-demographic and geographic factors.

Indexed as

Diabetes Mellitus, Type 1AdolescentChildCluster AnalysisGeographyHumansIncidenceSpatial AnalysisUtahDiabetes epidemiologyGeographySpatial analysisSpatial scan statisticType 1 diabetesUtah

Identifiers

PMID33933801
PMCPMC8686266

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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 OpenQuestion graph.