OBJECTIVES: To evaluate in a general population, the relationships between dysglycaemia, insulin resistance and metabolic variables, and heart rate, heart rate recovery and heart rate variability. METHODS: Four hundred and forty-seven participants in the Data from an Epidemiological Study on the Insulin Resistance syndrome (DESIR) study were classified according to glycaemic status over the preceding 9 years. All were free of self-reported cardiac antecedents and were not taking drugs which alter heart rate. During five consecutive periods: rest, deep breathing, recovery, rest and lying to standing, heart rate and heart rate varability were evaluated and compared by ANCOVA and trend tests across glycaemic classes. Spearman correlation coefficients quantified the relations between cardio-metabolic risk factors, heart rate and heart rate varability. RESULTS: Heart rate differed between glycaemic groups, except during deep breathing. Between rest and deep-breathing periods, patients with diabetes had a lower increase in heart rate than others (P(trend) < 0.01); between deep breathing and recovery, the heart rate of patients with diabetes continued to increase, for others, heart rate decreased (P(trend) < 0.009). Heart rate was correlated with capillary glucose and triglycerides during the five test periods. Heart rate variability differed according to glycaemic status, especially during the recovery period. After age, sex and BMI adjustment, heart rate variability was correlated with triglycerides at two test periods. Change in heart rate between recovery and deep breathing was negatively correlated with heart rate variability at rest, (r=-0.113, P < 0.05): lower resting heart rate variability was associated with heart rate acceleration. CONCLUSIONS: Heart rate, but not heart rate variability, was associated with glycaemic status and capillary glucose. After deep breathing, heart rate recovery was altered in patients with known diabetes and was associated with reduced heart rate variability. Being overweight was a major correlate of heart rate variability.
OBJECTIVES: To evaluate in a general population, the relationships between dysglycaemia, insulin resistance and metabolic variables, and heart rate, heart rate recovery and heart rate variability. METHODS: Four hundred and forty-seven participants in the Data from an Epidemiological Study on the Insulin Resistance syndrome (DESIR) study were classified according to glycaemic status over the preceding 9 years. All were free of self-reported cardiac antecedents and were not taking drugs which alter heart rate. During five consecutive periods: rest, deep breathing, recovery, rest and lying to standing, heart rate and heart rate varability were evaluated and compared by ANCOVA and trend tests across glycaemic classes. Spearman correlation coefficients quantified the relations between cardio-metabolic risk factors, heart rate and heart rate varability. RESULTS: Heart rate differed between glycaemic groups, except during deep breathing. Between rest and deep-breathing periods, patients with diabetes had a lower increase in heart rate than others (P(trend) < 0.01); between deep breathing and recovery, the heart rate of patients with diabetes continued to increase, for others, heart rate decreased (P(trend) < 0.009). Heart rate was correlated with capillary glucose and triglycerides during the five test periods. Heart rate variability differed according to glycaemic status, especially during the recovery period. After age, sex and BMI adjustment, heart rate variability was correlated with triglycerides at two test periods. Change in heart rate between recovery and deep breathing was negatively correlated with heart rate variability at rest, (r=-0.113, P < 0.05): lower resting heart rate variability was associated with heart rate acceleration. CONCLUSIONS: Heart rate, but not heart rate variability, was associated with glycaemic status and capillary glucose. After deep breathing, heart rate recovery was altered in patients with known diabetes and was associated with reduced heart rate variability. Being overweight was a major correlate of heart rate variability.
Authors: M Berkelaar; E M W Eekhoff; A M C Simonis-Bik; D I Boomsma; M Diamant; R G Ijzerman; J M Dekker; L M 't Hart; E J C de Geus Journal: Diabetologia Date: 2013-02-13 Impact factor: 10.122
Authors: Marina Sirota; Gonneke Willemsen; Purnima Sundar; Steven J Pitts; Shobha Potluri; Edi Prifti; Sean Kennedy; S Dusko Ehrlich; Jacoline Neuteboom; Cornelis Kluft; Karen E Malone; David R Cox; Eco J C de Geus; Dorret I Boomsma Journal: PLoS One Date: 2015-04-08 Impact factor: 3.240
Authors: Lan Shou; Wendy Wenyu Huang; Andrew Barszczyk; Si Jia Wu; Helen Han; Alex Waese-Perlman; Lulu Chen; Jing Wei; Hong Luo; Kang Lee Journal: Biomed Res Int Date: 2021-06-01 Impact factor: 3.411
Authors: Brinnae Bent; Peter J Cho; Maria Henriquez; April Wittmann; Connie Thacker; Mark Feinglos; Matthew J Crowley; Jessilyn P Dunn Journal: NPJ Digit Med Date: 2021-06-02