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. 2020 Apr 21;11:1770. doi: 10.1038/s41467-020-15553-w

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© The Author(s) 2020

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — a Heatmap of z-scores for the associations between sedentary phenotypes. Numbers in white show the correlations. b Forestplot depicting the results of the two-sided Cox regression analysis between sedentary phenotypes and CAD. On the X-axis, hazard ratios are shown and results are represented as hazard ratio and 95% confidence intervals. Three regression models were used to study the association between sedentary behaviour phenotypes and CAD events; Model 1: univariable analysis; Model 2: adjusted for age and sex; Model 3: adjusted for age, sex, body mass index, smoking status, hypertension, diabetes, Townsend deprivation index as proxy for income, physical activity levels, alcohol use per weak and years of education. We considered two-sided P < 0.05 statistically significant, no adjustments were made for multiple testing. R correlation, HR hazard ratio, CI confidence interval.