Abstract P019: Insulin resistance indexes and lower heart rate variability in older adults: the Atherosclerosis Risk in Communities Study (ARIC)

Circulation ◽  
2018 ◽  
Vol 137 (suppl_1) ◽  
Author(s):  
Anna K Poon ◽  
Eric Whitsel ◽  
Gerardo Heiss ◽  
Elsayed Soliman ◽  
Lynne Wagenknecht ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
Time Domain ◽  
Low Frequency ◽  
Poor Quality ◽  
Model Assessment ◽  
Lower Heart Rate ◽  
Cardiac Autonomic Dysfunction

Introduction: Lower heart rate variability (HRV) is an indicator of cardiac autonomic dysfunction which is associated with cardiovascular disease in diabetes. Whether pre-diabetes insulin resistance contributes to lower HRV is not clear; insulin resistance (IR) indexes reflect different aspects of IR, including dysregulation of glucose, insulin, and lipids. We hypothesized that IR indexes are inversely associated with HRV. Methods: We analyzed 48-hour ambulatory electrocardiograms on 759 adults in a sample of the ARIC Study, excluding diabetes, antiarrhythmic medications, and missing/poor quality recordings. Insulin resistance indexes were defined as quartiles for the homeostatic model assessment of insulin resistance (HOMA-IR), triglyceride to HDL-C ratio (TG/HDL-C), and triglyceride-glucose index (TyG). Low HRV was defined as <25 th percentile for time domain measures -- including the standard deviation of all NN intervals (SDNN) and square root of the mean squared differences of successive NN intervals (RMSSD), and frequency domain measures -- including the high-frequency (HF) and low-frequency (LF) spectral components. Logistic regression with weights for sampling and nonresponse was used to estimate odds ratios and 95% confidence intervals (OR, 95% CI). Results: Mean age was 75 years [993 (63%) women, 688 (43%) African American]. The following results are reported for TyG. For time domain measures, high IR indexes were significantly associated with low SDNN (OR 1.83, 95% CI 1.09, 3.07), but not with low RMSSD (OR 1.48, 95% CI 0.89, 2.46). For frequency domain measures, high IR indexes were not associated with low HF (OR 1.62, 95% CI 0.96, 2.74), but significantly associated with low LF (OR 1.95, 95% CI 1.15, 3.30). Although results for other indexes were in the same direction, most were not statistically significant. Conclusions: Insulin resistance indexes may be inversely associated with HRV. An understanding of this relationship informs public health strategies for prevention of cardiovascular risk.

EFFECT OF PHYSICAL ACTIVITIES ON HEART RATE VARIABILITY AND SKIN CONDUCTANCE

2021 ◽  
pp. 2150038
Author(s):  
Ankita Soni ◽  
Kirti Rawal
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
Skin Conductance ◽  
Time Domain ◽  
Low Frequency ◽  
Physical Activities ◽  
Rr Intervals ◽  
Warm Up ◽  
Frequency Domain Methods

The sympathetic and parasympathetic function of the Autonomic Nervous System[Formula: see text]ANS[Formula: see text] is the primary cause of the variations in Heart Rate and Skin Conductance[Formula: see text]SC[Formula: see text] during different physical activities. This paper aims to analyze the effect of different physical activities i.e. (a) Supine (b) Standing and (c) Warm-up, on Heart Rate Variability (HRV) and SC. The standard dataset of 18 subjects has been used to analyze the effect of physical activities on the HRV and SC. In the used dataset, the subjects are in supine, standing, and warm-up positions. The linear methods (time domain & frequency domain) of HRV are implemented on the standard dataset for analyzing the effect of physical activities. It has been observed with the analysis of the HRV that the mean value of time domain methods i.e. the NN interval’s standard deviation (SDNN), the successive RR interval’s root mean square (RMSSD), RR intervals with more than 50 ms differences in between them (NN50), percentage of successive RR intervals that have the difference of more than 50 ms (pNN50) are decreased and the value of Heart rate (HR) increased when the activity has been changed from supine to standing and standing to the warm-up positions. The value of frequency domain methods, such as low frequency (LF) and the ratio of low and high frequency (LF/HF) increased, while the value of HF decreases as activity changes from supine to standing and from supine to warm-up position. Further, the increment is also observed in the value of SC when activity is switched from supine to standing and from standing to the warm-up position. It is concluded from the results that there is a significant decrement that is observed in the value of HRV, while the increment is observed in the value of SC and HR. Decrement of HRV reflects that the sympathetic activity is increased as activity changed from supine to standing and further from standing to warm-up positions.

Associations between heart rate variability, metabolic syndrome risk factors, and insulin resistance

2015 ◽  
Vol 40 (7) ◽  
pp. 734-740 ◽  
Author(s):  
Melanie I. Stuckey ◽  
Antti Kiviniemi ◽  
Dawn P. Gill ◽  
J. Kevin Shoemaker ◽  
Robert J. Petrella
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Standard Deviation ◽  
Waist Circumference ◽  
Frequency Domain ◽  
Model Assessment ◽  
Poincaré Plot

The purpose of this study was to examine differences in heart rate variability (HRV) in metabolic syndrome (MetS) and to determine associations between HRV parameters, MetS risk factors, and insulin resistance (homeostasis model assessment for insulin resistance (HOMA-IR)). Participants (n = 220; aged 23–70 years) were assessed for MetS risk factors (waist circumference, blood pressure, fasting plasma glucose, triglycerides, and high-density lipoprotein cholesterol) and 5-min supine HRV (time and frequency domain and nonlinear). HRV was compared between those with 3 or more (MetS+) and those with 2 or fewer MetS risk factors (MetS–). Multiple linear regression models were built for each HRV parameter to investigate associations with MetS risk factors and HOMA-IR. Data with normal distribution are presented as means ± SD and those without as median [interquartile range]. In women, standard deviation of R–R intervals 38.0 [27.0] ms, 44.5 [29.3] ms; p = 0.020), low-frequency power (5.73 ± 1.06 ln ms2, 6.13 ± 1.05 ln ms2; p = 0.022), and the standard deviation of the length of the Poincaré plot (46.8 [31.6] ms, 58.4 [29.9] ms; p = 0.014) were lower and heart rate was higher (68 [13] beats/min, 64 [12] beats/min; p = 0. 018) in MetS+ compared with MetS–, with no differences in men. Waist circumference was most commonly associated with HRV, especially frequency domain parameters. HOMA-IR was associated with heart rate. In conclusion, MetS+ women had a less favourable HRV profile than MetS– women, but there were no differences in men. HOMA-IR was associated with heart rate, not HRV.

Validity of a Smartphone Application and Chest Strap for Recording RR Intervals at Rest in Athletes

2020 ◽  
Vol 15 (6) ◽  
pp. 896-899
Author(s):  
Reabias de A. Pereira ◽  
José Luiz de B. Alves ◽  
João Henrique da C. Silva ◽  
Matheus da S. Costa ◽  
Alexandre S. Silva
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
Time Domain ◽  
High Frequency ◽  
Low Frequency ◽  
Smartphone Application ◽  
Smartphone App ◽  
Heart Rate Variability Analysis ◽  
Rr Intervals

Objective: To evaluate the accuracy of the smartphone application (app) HRV Expert (CardioMood) and a chest strap (H10 Polar) for recording R-R intervals compared with electrocardiogram (ECG). Methods: A total of 31 male recreational runners (age 36.1 [6.3] y) volunteered for this study. R-R intervals were recorded simultaneously by the smartphone app and ECG for 5 minutes to analyze heart-rate variability in both the supine and sitting positions. Time-domain indexes (heart rate, mean R-R, SD of RR intervals, count of successive normal R-R intervals differing by more than 50 ms, percentage of successive normal R-R intervals differing by more than 50 ms, and root mean square of successive differences between normal R-R intervals), frequency-domain indexes (low frequency, normalized low frequency, high frequency, normalized high frequency, low-frequency to high-frequency ratio, and very low frequency), and nonlinear indexes (SD of instantaneous beat-to-beat variability and long-term SD of continuous R-R intervals) were compared by unpaired t test, Pearson correlation, simple linear regression, and Bland–Altman plot to evaluate the agreement between the devices. Results: High similarity with P value varying between .97 and 1.0 in both positions was found. The correlation coefficient of the heart-rate-variability indexes was perfect (r = 1.0; P = .00) for all variables. The constant error, standard error of estimation, and limits of agreement between ECG and the smartphone app were considered small. Conclusion: The smartphone app and chest strap provide excellent ECG compliance for all variables in the time domain, frequency domain, and nonlinear indexes, regardless of the assessed position. Therefore, the smartphone app replaces ECG for any heart-rate-variability analysis in runners.

scholarly journals Effects of exercise on heart rate variability by time-domain, frequency-domain and non-linear analyses in equine athletes

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 147 ◽  
Author(s):  
Ka Hou Christien Li ◽  
Rachel Wing Chuen Lai ◽  
Yimei Du ◽  
Vivian Ly ◽  
David Chun Yin Li ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
Time Domain ◽  
High Frequency ◽  
Low Frequency ◽  
Total Power ◽  
Series Data ◽  
Non Linear ◽  
Term Fluctuation

Background: Heart rate variability (HRV) is an intrinsic property that reflects autonomic balance and has been shown to be predictive of all-cause and cardiovascular mortality. It can be altered by physiological states such as exercise or pathological conditions. However, there are only a handful of studies on HRV in horses. The aim of this study is to compare HRV parameters before and during exercise in horses. Methods: Time-domain, frequency-domain and non-linear analyses were applied to quantify time series data on RR intervals before and during exercise in horses (n=7). Results: Exercise increased heart rate from 44±8 to 113±17 bpm (ANOVA, P<0.05) and decreased standard deviation (SD) from 7±2 to 4±2 bpm, coefficient of variation (CoV) from 16±4% to 3±2% and root mean square of successive RR interval differences (RMSSD) from 89.4±91.5 to 6.5±3.7 ms. Contrastingly, no difference in low-frequency (0.10±0.03 vs. 0.09±0.03 Hz) and high-frequency (0.19±0.03 vs. 0.18±0.03 Hz) peaks, nor in their percentage powers (2±1 vs. 4±5%; 59±9 vs. 64±20%; 39±10 vs. 32±19%) were observed but very low-frequency, low-frequency, and high-frequency powers (ms2) were reduced from 29±17 to 2±5, 1138±372 to 22±22 and 860±564 to 9±6, respectively, as was total power (in logarithms) (7.52±0.52 to 3.25±0.73). Poincaré plots of RRn+1 against RRn revealed similar ellipsoid shapes before and after exercise. The SD along the line-of-identity (SD2) and SD perpendicular to the line-of-identity (SD1) were decreased by exercise (62±17 vs. 9±5 and 63±65 vs. 5±3), corresponding to increased SD2/SD1 ratio from 1.33±0.45 to 2.19±0.72. No change in approximate and sample entropy was detected (0.97±0.23 vs. 0.82±0.22 and 1.14±0.43 vs. 1.37±0.49). Detrended fluctuation analysis revealed unaltered short-term fluctuation slopes (0.76±0.27 vs. 1.18±0.55) but increased long-term fluctuation slopes (0.16±0.11 vs. 0.50±0.16) after exercise. Conclusion: Exercise leads to a decrease in HRV but did not affect signal entropy in horses.

scholarly journals Diet-Induced Metabolic Syndrome Reduced Heart Rate Variability and Increased Irregularity and Complexity of Short-Term RR Time Series in Rabbits

Animals ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 572 ◽  
Author(s):  
Wilson Lozano ◽  
Conrado Calvo ◽  
Oscar Arias-Mutis ◽  
Ana Díaz ◽  
Luis Such-Miquel ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Heart Rate ◽  
Time Series ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
Time Domain ◽  
Rabbit Model ◽  
Low Frequency ◽  
Nonlinear Analyses ◽  
Short Term

Metabolic syndrome (MetS) has been linked to a higher prevalence of sudden cardiac death (SCD), but the mechanisms are not well understood. One possible underlying mechanism may be an abnormal modulation of autonomic activity, which can be quantified by analyzing heart rate variability (HRV). Our aim was to investigate the modifications of short-term HRV in an experimental rabbit model during the time-course of MetS development. NZW rabbits were randomly assigned to a control (n = 10) or a MetS group (n = 13), fed 28 weeks with control or high-fat, high-sucrose diets. After anesthesia, a 15-min ECG recording was acquired before diet administration and at weeks 14 and 28. We analyzed short RR time series using time-domain, frequency-domain and nonlinear analyses. A mixed-model factorial ANOVA was used for statistical analysis. Time-domain analysis showed a 52.4% decrease in the standard deviation of heart rate in animals from the MetS group at week 28, but no changes in the rest of parameters. In the frequency domain, we found a 9.7% decrease in the very low frequency and a 380.0% increase of the low frequency bands in MetS animals at week 28, whereas high frequency remained unchanged. Nonlinear analyses showed increased complexity and irregularity of the RR time series in MetS animals.

scholarly journals Sex differences in associations between insulin resistance, heart rate variability, and arterial stiffness in healthy women and men: a physiology study

2017 ◽  
Vol 95 (4) ◽  
pp. 349-355 ◽  
Author(s):  
Luke Anthony Rannelli ◽  
Jennifer M. MacRae ◽  
Michelle C. Mann ◽  
Sharanya Ramesh ◽  
Brenda R. Hemmelgarn ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Sex Differences ◽  
Arterial Stiffness ◽  
Spectral Power ◽  
Applanation Tonometry ◽  
Healthy Population ◽  
Model Assessment ◽  
Healthy Women

Diabetes confers greater cardiovascular risk to women than to men. Whether insulin-resistance-mediated risk extends to the healthy population is unknown. Measures of insulin resistance (fasting insulin, homeostatic model assessment, hemoglobin A1c, quantitative insulin sensitivity check index, glucose) were determined in 48 (56% female) healthy subjects. Heart rate variability (HRV) was calculated by spectral power analysis and arterial stiffness was determined using noninvasive applanation tonometry. Both were measured at baseline and in response to angiotensin II infusion. In women, there was a non-statistically significant trend towards increasing insulin resistance being associated with an overall unfavourable HRV response and increased arterial stiffness to the stressor, while men demonstrated the opposite response. Significant differences in the associations between insulin resistance and cardiovascular physiological profile exist between healthy women and men. Further studies investigating the sex differences in the pathophysiology of insulin resistance in cardiovascular disease are warranted.

scholarly journals Heart Rate Variability and Cardiovascular Reflex Tests for Assessment of Autonomic Functions in Preeclampsia

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Meenakshi Chaswal ◽  
Raj Kapoor ◽  
Achla Batra ◽  
Savita Verma ◽  
Bhupendra S. Yadav
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Pregnant Women ◽  
Frequency Domain ◽  
Low Frequency ◽  
Normal Pregnancy ◽  
Total Power ◽  
Autonomic Functions ◽  
Cardiovascular Reflex ◽  
Cardiovascular Reflex Tests

Alterations in the autonomic cardiovascular control have been implicated to play an important etiologic role in preeclampsia. The present study was designed to evaluate autonomic functions in preeclamptic pregnant women and compare the values with normotensive pregnant and healthy nonpregnant controls. Assessment of autonomic functions was done by cardiovascular reflex tests and by analysis of heart rate variability (HRV). Cardiovascular reflex tests included deep breathing test (DBT) and lying to standing test (LST). HRV was analyzed in both time and frequency domain for quantifying the tone of autonomic nervous system to the heart. The time domain measures included standard deviation of normal R-R intervals (SDNN) and square root of mean squared differences of successive R-R intervals (RMSSD). In the frequency domain we measured total power (TP), high frequency (HF) power, low frequency (LF) power, and LF/HF ratio. Cardiovascular reflex tests showed a significant parasympathetic deficit in preeclamptic women. Among parameters of HRV, preeclamptic group had lower values of SDNN, RMSSD, TP, HF, and LF (ms2) and higher value of LF in normalised units along with high LF/HF ratio compared to normotensive pregnant and nonpregnant controls. Furthermore, normotensive pregnant women had lower values of SDNN, TP, and LF component in both absolute power and normalised units compared to nonpregnant females. The results confirm that normal pregnancy is associated with autonomic disturbances which get exaggerated in the state of preeclampsia.

Influence of Insulin Resistance on the Association Between Physical Activity and Heart Rate Variability: The Toon Health Study

2020 ◽  
Vol 17 (11) ◽  
pp. 1075-1082
Author(s):  
Isao Saito ◽  
Koutatsu Maruyama ◽  
Tadahiro Kato ◽  
Yasunori Takata ◽  
Kiyohide Tomooka ◽  
...  
Keyword(s):  
Physical Activity ◽  
Insulin Resistance ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Standard ◽  
Population Based ◽  
Health Study ◽  
Model Assessment ◽  
Partial Regression Coefficient ◽  
Validated Questionnaire

Background: Autonomic activity is possibly influenced by physical activity (PA). However, it remains unclear whether this association is modified by insulin resistance. Methods: This population-based study between 2009 and 2012 included 2016 men and women aged 30–79 years. The PA was assessed using a validated questionnaire based on sleep, occupation, transportation, household characteristics, and leisure-time PA. Heart rate (HR) and heart rate variability (HRV) in the sitting position were determined from 5-minute recordings of pulse waves detected by a fingertip sensor. The HRV was calculated as frequency (standard deviation of normal-to-normal [NN] intervals [SDNN]), root mean square of successive differences (RMSSD), and percentage differences between normal NN intervals >50 milliseconds [pNN50]) and time domains. Insulin resistance was evaluated using the homeostasis model assessment index (HOMA-IR). Results: HR, RMSSD, and pNN50 were related to the total and moderate/vigorous PA tertiles in models that included HOMA-IR. The partial regression coefficient of total PA per 1-SD increase was .05 (P = .019) for log-transformed RMSSD and 1.86 (P = .001) for pNN50. No interactive associations were observed between PA and HOMA-IR. Conclusions: Low total PA was associated with increased HR and low levels of RMSSD and pNN50, reflecting parasympathetic modulation that was not modified by insulin resistance.

scholarly journals Sex Differences in Time-Domain and Frequency-Domain Heart Rate Variability Measures of Fatigued Drivers

2020 ◽  
Vol 17 (22) ◽  
pp. 8499
Author(s):  
Chao Zeng ◽  
Wenjun Wang ◽  
Chaoyang Chen ◽  
Chaofei Zhang ◽  
Bo Cheng
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sex Differences ◽  
Frequency Domain ◽  
Time Domain ◽  
Mental States ◽  
Male And Female ◽  
Frequency Domain Methods ◽  
The Difference ◽  
Electrocardiogram Ecg

The effects of fatigue on a driver’s autonomic nervous system (ANS) were investigated through heart rate variability (HRV) measures considering the difference of sex. Electrocardiogram (ECG) data from 18 drivers were recorded during a simulator-based driving experiment. Thirteen short-term HRV measures were extracted through time-domain and frequency-domain methods. First, differences in HRV measures related to mental state (alert or fatigued) were analyzed in all subjects. Then, sex-specific changes between alert and fatigued states were investigated. Finally, sex differences between alert and fatigued states were compared. For all subjects, ten measures showed significant differences (Mann-Whitney U test, p < 0.01) between different mental states. In male and female drivers, eight and four measures, respectively, showed significant differences between different mental states. Six measures showed significant differences between males and females in an alert state, while ten measures showed significant sex differences in a fatigued state. In conclusion, fatigue impacts drivers’ ANS activity, and this impact differs by sex; more differences exist between male and female drivers’ ANS activity in a fatigued state than in an alert state.

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