Screening Model for Estimating Undiagnosed Diabetes among People with a Family History of Diabetes Mellitus: A KNHANES-Based Study.

Kwang Sun Ryu,Yul Hwangbo,Kui Son Choi,Hyun Woo Park,Ha Ye Jin Kang,Hyo Soung Cha,Sang Won Lee,Na Young You,Jae Ho Kim

doi:10.3390/ijerph17238903

Abstract

A screening model for estimating undiagnosed diabetes mellitus (UDM) is important for early medical care. There is minimal research and a serious lack of screening models for people with a family history of diabetes (FHD), especially one which incorporates gender characteristics. Therefore, the primary objective of our study was to develop a screening model for estimating UDM among people with FHD and enable its validation. We used data from the Korean National Health and Nutrition Examination Survey (KNHANES). KNAHNES (2010–2016) was used as a developmental cohort (n = 5939) and was then evaluated in a validation cohort (n = 1047) KNHANES (2017). We developed the screening model for UDM in male (SMM), female (SMF), and male and female combined (SMP) with FHD using backward stepwise logistic regression analysis. The SMM and SMF showed an appropriate performance (area under curve (AUC) = 76.2% and 77.9%) compared with SMP (AUC = 72.9%) in the validation cohort. Consequently, simple screening models were developed and validated, for the estimation of UDM among patients in the FHD group, which is expected to reduce the burden on the national health care system.

Highlights

Diabetes mellitus affected 422 million people worldwide in 2014, and this number continues to increase [1]
Population-wide screening models for undiagnosed diabetes mellitus (UDM) allow for the estimation of individuals at a high risk of developing diabetes without requiring invasive laboratory tests [7]
The ratio of Impaired fasting glucose (IFG) and undiagnosed diabetes were higher in the family history of diabetes (FHD) group (Table 1)

Summary

Introduction

Diabetes mellitus affected 422 million people worldwide in 2014, and this number continues to increase [1]. The proportion of patients with undiagnosed diabetes mellitus (UDM) varies from 30 to 80% [2], with most cases being asymptomatic [3,4]. Diagnosis allows for optimized treatment of patients with type 2 diabetes mellitus, which helps to achieve good outcomes among individuals with a long asymptomatic disease phase [5,6]. The oral glucose tolerance test, fasting plasma glucose level, and hemoglobin A1C level are established biochemical indicators in people with diabetes mellitus [7], it is insufficient to stratify a large population in developing countries [8]. Population-wide screening models for UDM allow for the estimation of individuals at a high risk of developing diabetes without requiring invasive laboratory tests [7]. Public Health 2020, 17, 8903; doi:10.3390/ijerph17238903 www.mdpi.com/journal/ijerph

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