Mean age and body mass index at type 2 diabetes diagnosis: Pooled analysis of 56 health surveys across income groups and world regions

Rodrigo M. Carrillo‐Larco; Wilmer Cristobal Guzman‐Vilca; Xiaolin Xu; Antonio Bernabe‐Ortiz

doi:10.1111/dme.15174

journal article Jul 12, 2023

Mean age and body mass index at type 2 diabetes diagnosis: Pooled analysis of 56 health surveys across income groups and world regions

Rodrigo M. Carrillo‐Larco Wilmer Cristobal Guzman‐Vilca Xiaolin Xu

Antonio Bernabe‐Ortiz

Diabetic Medicine Vol. 41 No. 2 · Wiley

View at Publisher Save 10.1111/dme.15174

Abstract

AbstractBackgroundScreening for type 2 diabetes mellitus (T2DM) targets people aged 35+ years and those with overweight/obesity. With mounting evidence on young‐onset T2DM and T2DM patients with lean phenotypes, it is worth revising the screening criteria to include younger and leaner adults. We quantified the mean age and body mass index (BMI; kg/m2) at T2DM diagnosis in 56 countries.MethodsDescriptive cross‐sectional analysis of WHO STEPS surveys. We analysed adults (25–69 years) with new T2DM diagnosis (not necessarily T2DM onset) as per fasting plasma glucose ≥126 mg/dL measured during the survey. For people with new T2DM diagnosis, we summarized the mean age and the proportion of each five‐year age group; also, we summarized the mean BMI and the proportion of mutually exclusive BMI categories.ResultsThere were 8695 new T2DM patients. Overall, the mean age at T2DM diagnosis was 45.1 years in men and 45.0 years in women; and the mean BMI at T2DM diagnosis was 25.2 in men and 26.9 in women. Overall, in men, 10.3% were 25–29 years and 8.5% were 30–34 years old; in women, 8.6% and 12.5% were 25–29 years and 30–34 years old, respectively. 48.5% of men and 37.3% of women were in the normal BMI category.ConclusionsA non‐negligible proportion of new T2DM patients were younger than 35 years. Many new T2DM patients were in the normal weight range. Guidelines for T2DM screening may consider revising the age and BMI criteria to incorporate young and lean adults.

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References

27

[1]

Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Christopher J L Murray, Aleksandr Y Aravkin, Peng Zheng et al.

The Lancet 10.1016/s0140-6736(20)30752-2

[2]

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Theo Vos, Stephen S Lim, Cristiana Abbafati et al.

The Lancet 10.1016/s0140-6736(20)30925-9

[3]

Global and regional estimates and projections of diabetes-related health expenditure: Results from the International Diabetes Federation Diabetes Atlas, 9th edition

Rhys Williams, Suvi Karuranga, Belma Malanda et al.

Diabetes Research and Clinical Practice 10.1016/j.diabres.2020.108072

[4]

10.2337/dc22-s002

[5]

(2020)

[6]

10.1038/s41574-020-0334-z

[7]

10.1016/j.diabres.2022.109785

[8]

10.1007/s11892-018-1017-1

[9]

10.7326/m16-1895

[10]

10.2337/dci19-0046

[11]

Noncommunicable Disease Surveillance Monitoring and Reporting.STEPwise approach to NCD risk factor surveillance (STEPS).https://www.who.int/teams/noncommunicable‐diseases/surveillance/systems‐tools/steps. Accessed July 10 2023.

[12]

10.1038/s41586-019-1171-x

[13]

10.1016/s0140-6736(16)00618-8

[14]

10.1016/j.diabres.2022.110030

[15]

10.15605/jafes.034.02.07

[16]

10.2337/dc22-1847

[17]

10.1001/jama.2017.7596

[18]

10.5812/ijem.109206

[19]

10.1186/1741-7015-9-103

[20]

10.1136/bmj.d7163

[21]

10.1111/dme.14114

[22]

Quantifying the impact of different approaches for handling continuous predictors on the performance of a prognostic model

Gary S. Collins, Emmanuel O. Ogundimu, JONATHAN A. COOK et al.

Statistics in Medicine 10.1002/sim.6986

[23]

10.1038/s41574-022-00669-4

[24]

10.1007/s00125-020-05132-5

[25]

10.1016/j.gheart.2015.12.010

[26]

10.1016/j.amepre.2018.05.018

[27]

10.1056/nejmsa2032271

Metrics

28

Citations

27

References

Details

Published: Jul 12, 2023
Vol/Issue: 41(2)
License: View

Authors

R

Rodrigo M. Carrillo‐Larco

Hubert Department of Global Health, Rollins School of Public Health Emory University Atlanta Georgia USA; Emory Global Diabetes Research Center Emory University Atlanta Georgia USA

W

Wilmer Cristobal Guzman‐Vilca

CRONICAS Centre of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru; School of Medicine “Alberto Hurtado” Universidad Peruana Cayetano Heredia Lima Peru; Sociedad Científica de Estudiantes de Medicina Cayetano Heredia (SOCEMCH) Universidad Peruana Cayetano Heredia Lima Peru

X

Xiaolin Xu

Department of Big Data in Health Science School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou China; School of Public Health, Faculty of Medicine The University of Queensland Brisbane Queensland Australia

A

Antonio Bernabe‐Ortiz

CRONICAS Centre of Excellence in Chronic Diseases Universidad Peruana Cayetano Heredia Lima Peru; Universidad Cientifica del Sur Lima Peru

Cite This Article

Rodrigo M. Carrillo‐Larco, Wilmer Cristobal Guzman‐Vilca, Xiaolin Xu, et al. (2023). Mean age and body mass index at type 2 diabetes diagnosis: Pooled analysis of 56 health surveys across income groups and world regions. Diabetic Medicine, 41(2). https://doi.org/10.1111/dme.15174

Mean age and body mass index at type 2 diabetes diagnosis: Pooled analysis of 56 health surveys across income groups and world regions

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