Nutritional markers of undiagnosed type 2 diabetes in adults: Findings of a machine learning analysis with external validation and benchmarking.

ABSTRACT:

Objectives

Using a nationally-representative, cross-sectional cohort, we examined nutritional markers of undiagnosed type 2 diabetes in adults via machine learning.

Methods

A total of 16429 men and non-pregnant women ≥ 20 years of age were analysed from five consecutive cycles of the National Health and Nutrition Examination Survey. Cohorts from years 2013-2016 (n = 6673) was used for external validation. Undiagnosed type 2 diabetes was determined by a negative response to the question "Have you ever been told by a doctor that you have diabetes?" and a positive glycaemic response to one or more of the three diagnostic tests (HbA1c > 6.4% or FPG >125 mg/dl or 2-hr post-OGTT glucose > 200mg/dl). Following comprehensive literature search, 114 potential nutritional markers were

SUBMITTER: De Silva K 

PROVIDER: S-EPMC8099133 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature