Identifying risk for type 2 diabetes in different age cohorts: does one size fit all?
Author(s)
Alva, ML
Hoerger, TJ
Zhang, P
Gregg, EW
Type
Journal Article
Abstract
Objective: To estimate age-specific risk equations for type 2 diabetes onset in young, middle-aged, and older US adults, and to compare the performance of simple equations based on readily available demographic information alone, against enhanced equations that require both demographic and clinical information (fasting plasma glucose, high-density lipoprotein, and triglyceride levels). Research design and methods: We estimated the probability of developing diabetes by age group using data from the Coronary Artery Risk Development in Young Adults (for ages 18-40 years), Atherosclerosis Risk in Communities (for ages 45-64 years), and the Cardiovascular Health Study (for ages 65 years and older). Simple and enhanced equations were estimated using logistic regression models, and performance was compared by age group. Thresholds based on these risk equations were evaluated using split-sample bootstraps and calibrating the constant of one age cohort to others. Results: Simple risk equations had an area under the receiver-operating curve (AUROC) of 0.72, 0.79, 0.75, and 0.69 for age groups 18-30, 28-40, 45-64, and 65 and older, respectively. The corresponding AUROCs for enhanced equations were 0.75, 0.85, 0.85, and 0.81. Risk equations based on younger populations, when applied to older cohorts, underpredict diabetes incidence and risk. Conversely, risk equations based on older populations overpredict the likelihood of diabetes in younger cohorts. Conclusions: In general, risk equations are more successful in middle-aged adults than in young and old populations. The results demonstrate the importance of applying age-specific risk equations to identify target populations for intervention. While the predictive capacity of equations that include biomarkers is better than of those based solely on self-reported variables, biomarkers are more important in older populations than in younger ones.
Date Issued
2017-10-27
Online Publication Date
2019-08-23T15:29:26Z
Date Acceptance
2017-09-03
ISSN
2052-4897
Publisher
BMJ
Start Page
1
End Page
7
Journal / Book Title
BMJ Open Diabetes Res Care
Volume
5
Issue
1
Copyright Statement
© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Identifier
https://drc.bmj.com/content/bmjdrc/5/1/e000447.full.pdf
https://www.ncbi.nlm.nih.gov/pubmed/29118992
bmjdrc-2017-000447
Subjects
risk predictors
type 2 diabetes
risk predictors
type 2 diabetes
Publication Status
Published
Country
England
Date Publish Online
2017-10-27