What protects against pre-diabetes progressing to diabetes? Observational study of integrated health and social data

Author: Teng, Andrea; Blakely, Tony; Scott, Nina; Jansen, Rawiri; Masters-Awatere, Bridgette; Krebs, Jeremy; Oetzel, John

Date: 2019-02

Publisher: ScienceDirect

Type: Journal article

Link to this item using this URL: http://hdl.handle.net/10523/9884

University of Otago

Abstract

Aims To examine the incidence of type 2 diabetes in people with newly diagnosed prediabetes and the factors that protect against this progression. Methods The study population was 14,043 adults with pre-diabetes enrolled in a primary health organization in the upper North Island of New Zealand. Glycated hemoglobin (HbA1c) and body mass index (BMI) were linked to government health, census and social datasets in the Statistics New Zealand Integrated Data Infrastructure. Adults with a first diagnosis of pre-diabetes between 2009 and 2017 (HbA1c in range 5.9-6.6% [41-49 mmol/mol]) were followed-up for type 2 diabetes incidence. Cox regression was used to examine protective factors and adjust for potential confounding. Results Cumulative diabetes incidence was 5.0% after three years. Progression was greater in younger adults, men, people with higher HbA1c, greater BMI and a more recent diagnosis. Progression was lower in people treated with metformin, and Indigenous language speakers. Higher progression rates for Māori (Indigenous population) and Pacific peoples (migrants to New Zealand) were related to higher baseline HbA1c. Conclusions This is the first study to identify Indigenous language as a protective factor against diabetes, and results confirm obesity as a key target for population prevention. People with identified risk factors should be prioritized for pre-diabetes interventions.

Subjects: intermediate hyperglycemia, glycated haemoglobin, race, Indigenous, language, linked data

Citation: ["Teng A, Blakely T, Scott N, et al. What protects against pre-diabetes progressing to diabetes? Observational study of integrated health and social data. Diabetes Res Clin Pract. 2019;148:119-129. https://doi.org/10.1016/j.diabres.2018.12.003"]

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