Evidence map›Paper›PMID 39609833›Full record

ArticleDiabetology & metabolic syndrome2024

Onset of Type 2 diabetes in adults aged 50 and older in Europe: an intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy.

Julie Lorraine O'Sullivan, Enrique Alonso-Perez, Francesca Färber, Georg Fuellen, Henrik Rudolf, Jan Paul Heisig, Michaela Kreyenfeld, Paul Gellert

Abstract read
In one paragraph

Article in Diabetology & metabolic syndrome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Julie Lorraine O'SullivanInstitute for Medical Sociology and Rehabilitation Science, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, Berlin, 10117, Germany. julie.osullivan@charite.de.ORCID https://orcid.org/0000-0002-8991-9966
Enrique Alonso-PerezInstitute for Medical Sociology and Rehabilitation Science, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, Berlin, 10117, Germany.ORCID https://orcid.org/0000-0002-0228-5084
Francesca FärberInstitute for Medical Sociology and Rehabilitation Science, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, Berlin, 10117, Germany.ORCID https://orcid.org/0000-0002-5652-6971
Georg FuellenInstitute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany.ORCID https://orcid.org/0000-0002-4994-9829
Henrik RudolfInstitute for Biostatistics and Informatics in Medicine and Ageing Research, Rostock University Medical Center, Rostock, Germany.ORCID https://orcid.org/0000-0001-9114-3805
Jan Paul HeisigWZB Berlin Social Science Center, Berlin, Germany.ORCID https://orcid.org/0000-0001-8228-1907
Michaela KreyenfeldHertie School Berlin, Berlin, Germany.ORCID https://orcid.org/0000-0001-9420-3818
Paul GellertInstitute for Medical Sociology and Rehabilitation Science, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, Berlin, 10117, Germany.ORCID https://orcid.org/0000-0001-7492-7210

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDisparities in the development of Type 2 Diabetes (T2D) are associated with various social determinants, including sex/gender, migration background, living arrangement, education, and household income. This study applied an intersectional perspective to map social disparities and investigate intersectional effects regarding the onset of T2D among older adults across Europe.

methodsWe used data from the Survey of Health and Retirement in Europe (SHARE) to conduct an Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (I-MAIHDA) of T2D onset. Individuals aged 50 years or older without known T2D at Wave 4 (2011, baseline) were included and followed through Waves 5 (2013), 6 (2015), 7 (2016), and 8 (2019-2020). Intersectional models were used to estimate additive main effects of sex/gender, migration background, living arrangement, education level, and household income and intersectional interactions.

resultsA total of 39,108 individuals were included (age at baseline M = 65.18 years (SD = 9.62), 57.4% women). T2D onset was reported for 9.2% of the sample over the 9-year observation period. In the fully adjusted model, all social determinants showed significant additive associations with T2D onset, while the discriminatory accuracy of the social strata was found to be low (Variance Partition Coefficient = 0.3%).

conclusionsThis study provides a comprehensive mapping of intersectional disparities in onset of T2D among older adults in Europe. The results highlight the risk heterogeneity within the population and show social disadvantages faced by certain groups. However, while the T2D risks were higher in some strata than in others, the intersectional effects were small overall and mostly attributable to the additive main effects. The results suggest that public health strategies to prevent T2D should be universal but tailored to meet the specific situation of the different intersectional strata.

Indexed as

Health equityIntersectionalityPrevention of type 2 diabetesRisk of type 2 diabetesSocial determinants of health

Identifiers

PMID39609833
PMCPMC11605936

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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 OpenQuestion graph.