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. 2022 Apr 27;20:149. doi: 10.1186/s12916-022-02337-w

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© The Author(s) 2022

Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 1 — Population attributable fractions for risk factors by ethnic group. Numbers in cells are population attributable fractions for that ethnic group. PAFs with 95% CIs overlapping 0 are greyed out. Model 1: adjusted for age and sex only. Model 2: additionally adjusted for deprivation. Model 3: additionally adjusted for lifestyle factors. Model 4: additionally adjusted for adiposity markers. TV, television; BMI, body mass index; HbA1c, glycated haemoglobin; GGT, gamma-glutamyl transferase. Continuous variables were categorised as quintiles in this analysis. Obesity defined as BMI≥30.0 kg/m², central obesity as WHR >0.85 for women and >0.90 for men, low grip strength as 1st quintile, and high blood pressure, LDL-c, triglycerides, HbA1c, cystatin C, and GGT as the 5th quintile