Evidence map›Paper›PMID 37600703›Full record

ArticleFrontiers in endocrinology2023

Area deprivation and demographic factors associated with diabetes technology use in adults with type 1 diabetes in Germany.

Marie Auzanneau, Alexander J Eckert, Sebastian M Meyhöfer, Martin Heni, Anton Gillessen, Lars Schwettmann, Peter M Jehle, Michael Hummel, Reinhard W Holl

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Review
  2. Narrative Review: Continuous Glucose Monitoring (CGM) in Older Adults with Diabetes.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025
    Review
  3. Time to Initiation of Omnipod DASH® vs. Tubed Insulin Pump Therapy: A Time-and-Motion Study.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025
    Article
  4. Review
  5. Observational
  6. Article
  7. Article
  8. 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

9 authors.

Marie AuzanneauInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
Alexander J EckertInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
Sebastian M MeyhöferGerman Center for Diabetes Research (DZD), Munich-Neuherberg, Germany.
Martin HeniDivision of Endocrinology and Diabetology, Department of Internal Medicine 1, University Hospital Ulm, Ulm, Germany.
Anton GillessenDepartment of Internal Medicine, Sacred Heart Hospital, Muenster, Germany.
Lars SchwettmannDivision of Health Economics, Department of Health Services Research, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany.
Peter M JehleDepartment of Internal Medicine I, University Medicine, Academic Hospital Paul-Gerhardt-Stift, Martin-Luther-University Halle-Wittenberg, Lutherstadt Wittenberg, Germany.
Michael HummelResearch Group Diabetes e.V., Helmholtz Center Munich, Munich-Neuherberg, Germany.
Reinhard W HollInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Diabetes technology improves glycemic control and quality of life for many people with type 1 diabetes (T1D). However, inequalities in access to diabetes technology exist in many countries. In Germany, disparities in technology use have been described in pediatric T1D, but no data for adults are available so far. We therefore aimed to analyze whether demographic factors and area deprivation are associated with technology use in a representative population of adults with T1D. Materials and methods: In adults with T1D from the German prospective diabetes follow-up registry (DPV), we analyzed the use of continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring (CGM), and sensor augmented pump therapy (SAP, with and without automated insulin delivery) in 2019-2021 by age group, gender, migration background, and area deprivation using multiple adjusted regression models. Area deprivation, defined as a relative lack of area-based resources, was measured by quintiles of the German index of Multiple Deprivation (GIMD 2015, from Q1, least deprived, to Q5, most deprived districts). Results: Among 13,351 adults with T1D, the use of technology decreased significantly with older age: CSII use fell from 56.1% in the 18-<25-year age group to 3.1% in the ≥80-year age group, CGM use from 75.3% to 28.2%, and SAP use from 45.1% to 1.5% (all p for trend <0.001). The use of technology was also significantly higher in women than in men (CSII: 39.2% vs. 27.6%; CGM: 61.9% vs. 58.0%; SAP: 28.7% vs. 19.6%, all p <0.001), and in individuals without migration background than in those with migration background (CSII: 38.8% vs. 27.6%; CGM: 71.1% vs. 61.4%; SAP: 30.5% vs. 21.3%, all p <0.001). Associations with area deprivation were not linear: the use of each technology decreased only from Q2 to Q4. Discussion: Our real-world data provide evidence that higher age, male gender, and migration background are currently associated with lower use of diabetes technology in adults with T1D in Germany. Associations with area deprivation are more complex, probably due to correlations with other factors, like the higher proportion of migrants in less deprived areas or the federal structure of the German health care system.

Indexed as

Diabetes Mellitus, Type 1AdultBlood GlucoseBlood Glucose Self-MonitoringChildFemaleGermanyHumansInsulinMaleProspective StudiesQuality of LifeTechnologyBlood GlucoseInsulinadultsageCGMdeprivationdiabetes technologygenderpumpType 1 diabetes

Identifiers

PMID37600703
PMCPMC10433185

What Socratic holds

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LicenceCC BY
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Registered trials

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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.