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BACKGROUND AND AIMS: Observational studies have associated resting heart rate with incident diabetes. Whether the associations are causal remains unclear. We aimed to examine the shape and strength of the associations and assessed the causal relevance of such associations in Chinese adults. METHODS AND RESULTS: The China Kadoorie Biobank enrolled 512,891 adults in China. Cox proportional hazard regression models was conducted to estimate hazard ratios (HRs) for the associations of resting heart rate with type 2 diabetes and total diabetes. Among 92,724 participants, 36 single-nucleotide polymorphisms (SNPs) related to resting heart rate were used to construct genetic risk score. We used Mendelian randomization analyses to make the causal inferences. During a median follow-up of 9 years, 7872 incident type 2 diabetes and 13,349 incident total diabetes were documented. After regression dilution bias adjustment, each 10 bpm higher heart rate was associated with about a 26% higher risk of type 2 diabetes (HR, 1.26 [95% CI, 1.23, 1.29]) and 23% higher risk of total diabetes (HR, 1.23 [95% CI, 1.20, 1.26]). Instrumental variable analyses showed participants at top quintile compared with those at bottom quintile had 30% higher risk for type 2 diabetes (HR, 1.30 [95% CI, 1.17, 1.43]), and 10% higher risk for total diabetes (HR, 1.10 [95% CI, 1.02, 1.20]). CONCLUSIONS: This study provides evidence that resting heart rate is an important risk factor for diabetes risk. The results suggest that novel treatment approaches targeting reduction of high heart rate for incidence of diabetes may be worth further investigation.

Original publication

DOI

10.1016/j.numecd.2021.04.015

Type

Journal article

Journal

Nutr Metab Cardiovasc Dis

Publication Date

22/07/2021

Volume

31

Pages

2328 - 2337

Keywords

Causal association, Diabetes, Heart rate, Mendelian randomization, Adult, Aged, China, Diabetes Mellitus, Type 2, Female, Genetic Predisposition to Disease, Heart Rate, Humans, Incidence, Male, Mendelian Randomization Analysis, Middle Aged, Phenotype, Polymorphism, Single Nucleotide, Risk Assessment, Risk Factors, Time Factors