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. 2021 Jan 26;64(4):845–849. doi: 10.1007/s00125-020-05377-0

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — Non-linear Mendelian randomisation investigating the relationship between genetically proxied average blood glucose levels (measured by HbA_1c) and risk of incident CHD in individuals without diabetes mellitus: (a) men and women combined; (b) men only; and (c) women only. The x-axis depicts HbA_1c levels in mmol/mol. The y-axis depicts the hazard ratio for coronary heart disease (HR for CHD) with respect to the reference, plotted on a log scale. Reference is set to an HbA_1c of 30 mmol/mol (4.9%). The grey lines represent the 95% CIs. The fractional polynomial test is a goodness-of-fit test that assesses whether any improvement of fit when using a non-linear function to model the association, compared with a linear function, is greater than would be expected due to chance (a significant p value indicates that a non-linear model is preferred to a linear model)