Size and shape of the associations of glucose, HbA(1c), insulin and HOMA-IR with incident type 2 diabetes: the Hoorn Study

葡萄糖、糖化血红蛋白 (HbA1c)、胰岛素和 HOMA-IR 与 2 型糖尿病发病率关联的大小和形状:霍恩研究

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Abstract

AIMS/HYPOTHESIS: Glycaemic markers and fasting insulin are frequently measured outcomes of intervention studies. To extrapolate accurately the impact of interventions on the risk of diabetes incidence, we investigated the size and shape of the associations of fasting plasma glucose (FPG), 2 h post-load glucose (2hPG), HbA(1c), fasting insulin and HOMA-IR with incident type 2 diabetes mellitus. METHODS: The study population included 1349 participants aged 50-75 years without diabetes at baseline (1989) from a population-based cohort in Hoorn, the Netherlands. Incident type 2 diabetes was defined by the WHO 2011 criteria or known diabetes at follow-up. Logistic regression models were used to determine the associations of the glycaemic markers, fasting insulin and HOMA-IR with incident type 2 diabetes. Restricted cubic spline logistic regressions were conducted to investigate the shape of the associations. RESULTS: After a mean follow-up duration of 6.4 (SD 0.5) years, 152 participants developed diabetes (11.3%); the majority were screen detected by high FPG. In multivariate adjusted models, ORs (95% CI) for incident type 2 diabetes for the highest quintile in comparison with the lowest quintile were 9.0 (4.4, 18.5) for FPG, 6.1 (2.9, 12.7) for 2hPG, 3.8 (2.0, 7.2) for HbA(1c), 1.9 (0.9, 3.6) for fasting insulin and 2.8 (1.4, 5.6) for HOMA-IR. The associations of FPG and HbA(1c) with incident diabetes were non-linear, rising more steeply at higher values. CONCLUSIONS/INTERPRETATION: FPG was most strongly associated with incident diabetes, followed by 2hPG, HbA(1c), HOMA-IR and fasting insulin. The strong association with FPG is probably because FPG is the most frequent marker for diabetes diagnosis. Non-linearity of associations between glycaemic markers and incident type 2 diabetes should be taken into account when estimating future risk of type 2 diabetes based on glycaemic markers.

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