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.

Associations Between Heart Rate Variability, Metabolic Syndrome Risk Factors and Insulin Resistance

2013 ◽  
Vol 29 (10) ◽  
pp. S320-S321
Author(s):  
M.I. Stuckey ◽  
A. Kiviniemi ◽  
D.P. Gill ◽  
R.J. Petrella
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Heart Rate ◽  
Heart Rate Variability

scholarly journals Periodized Aerobic Interval Training Modifies Geometric Indices of Heart Rate Variability in Metabolic Syndrome

Medicina ◽  
2019 ◽  
Vol 55 (9) ◽  
pp. 532
Author(s):  
Laís Manata Vanzella ◽  
Denise Brugnoli Balbi Dagostinho ◽  
Maria Paula Ferreira de Figueiredo ◽  
Carlos Iván Mesa Castrillón ◽  
Jayme Netto Junior ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Standard Deviation ◽  
Interval Training ◽  
Training Group ◽  
Control Group ◽  
Autonomic Modulation ◽  
Poincaré Plot ◽  
Aerobic Interval Training

Background: Metabolic syndrome (MetS) influences the autonomic modulation, increasing the risk of cardiovascular events, which demands the identification of effective treatments for this population. Considering this, the study has the objective of evaluating the effects of periodized aerobic interval training (AIT) on geometrical methods of heart rate variability (HRV) on individuals with MetS. Methods: 52 individuals with MetS were considered for analysis. They were divided into two groups: aerobic interval training group (AITG; n = 26) and control group (CG; n = 26). The AITG performed 16 weeks of periodized AIT. For HRV analysis, the heart rate was recorded beat-by-beat at the beginning and the end of the AIT program and geometrical methods were used for analysis. Results: significant increase was observed for triangular index (RRtri, −1.25 ± 0.58 vs. 1.41 ± 0.57), standard deviation of distances from diagonal to points (SD1, −0.13 ± 1.52 vs. 4.34 ± 1.49), and standard deviation of distances from points to lines (SD2, −2.14 ± 3.59 vs. 11.23 ± 3.52) on AITG compared to CG. Significant differences were not observed for triangular interpolation of normal heartbeats interval histogram (TINN, −4.05 ± 17.38 vs. 25.52 ± 17.03) and SD1/SD2 ratio (0.03 ± 0.02 vs. 0.00 ± 0.02). Qualitative analysis of the Poincaré plot identified increase on dispersion of both short and long-term intervals between successive heartbeats (RR interval) on AITG after the AIT program. Conclusion: geometric indices of HRV suggest an increase in cardiac autonomic modulation in individuals with MetS after 16 weeks of periodized AIT.

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.

scholarly journals Insulin Resistance in Association with Thyroid Function, Psychoemotional State, and Cardiovascular Risk Factors

2021 ◽  
Vol 18 (7) ◽  
pp. 3388
Author(s):  
Nijole Kazukauskiene ◽  
Aurelija Podlipskyte ◽  
Giedrius Varoneckas ◽  
Narseta Mickuviene
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Thyroid Function ◽  
Study Groups ◽  
Model Assessment ◽  
Psychoemotional State ◽  
Study Participants

Background: Individuals with insulin resistance (IR) have a high risk of diabetes or metabolic syndrome, and they are more likely to have depression. Furthermore, IR by itself is a major cardiovascular risk factor in healthy persons. Thus, we aimed to investigate IR in association with thyroid function, psychoemotional state, and cardiovascular risk factors among 45–84-year-old citizens of Palanga. Methods: A randomized epidemiological study was performed with 850 subjects. All participants were evaluated for sociodemographic, clinical, and cardiovascular risk factors and biochemical analysis. IR was evaluated by the homeostasis model assessment of IR (HOMA-IR). Results: All study participants were stratified into groups without IR (HOMA-IR ≤ 2.7) and with IR (HOMA-IR > 2.7). The analysis of parameters between the two study groups showed some statistically significant relationships between IR and cardiovascular risk factors. The predictable accuracy was presented using receiver performance characteristic curves for HOMA-IR scores in women and men separately. If the HOMA-IR score is higher than 3.45, individuals are significantly more likely to have type 2 diabetes mellitus (T2DM). Conclusions: An increase of fasting glucose and more frequent incidence of metabolic syndrome, diabetes, and cardiovascular diseases in subjects with IR are associated with the prevalence of cardiovascular risk factors. There was no significant association between thyroid function and HOMA-IR. HOMA-IR cut-offs could predict the presence of T2DM.

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.

Characterization of HRV by Poincare Plot Analysis among the Female Tea Garden Workers of Northern Hilly Regions of West Bengal

2012 ◽  
pp. 206-215
Author(s):  
Somsirsa Chatterjee ◽  
Ankur Ganguly ◽  
Saugat Bhattacharya
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Standard Deviation ◽  
West Bengal ◽  
Mean Value ◽  
Short Term ◽  
Poincaré Plot ◽  
Plot Analysis ◽  
Tea Garden

Recent research on Heart Rate Variability (HRV) has proven that Poincare Plot is a powerful tool to mark Short Term and Long Term Heart Rate Variability. This study focuses a comprehensive characterization of HRV among the Tea Garden Workers of the Northern Hilly Regions of West Bengal. The characterization, as available from the data sets, projects the average values of SD1 characteristics, that is, Short Term HRV in females as 58.265ms and SD2 as 149.474. The SDRR shows a mean value of 87.298 with a standard deviation of 119.669 and the S Characterization as 16505.99 ms and Standard deviation of 45882.31 ms. The SDRR shows a mean value of 87.298 with a standard deviation of 119.669 and the S Characterization as 16505.99 ms and Standard deviation of 45882.31 ms. ApEn Characterization showed mean value of 0.961 and standard deviation of 0.274.

Characterization of HRV by Poincare Plot Analysis among the Female Tea Garden Workers of Northern Hilly Regions of West Bengal

2010 ◽  
Vol 5 (2) ◽  
pp. 49-59 ◽  
Author(s):  
Somsirsa Chatterjee ◽  
Ankur Ganguly ◽  
Saugat Bhattacharya
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Standard Deviation ◽  
West Bengal ◽  
Mean Value ◽  
Data Sets ◽  
Short Term ◽  
Poincaré Plot ◽  
Tea Garden

Recent research on Heart Rate Variability (HRV) has proven that Poincare Plot is a powerful tool to mark Short Term and Long Term Heart Rate Variability. This study focuses a comprehensive characterization of HRV among the Tea Garden Workers of the Northern Hilly Regions of West Bengal. The characterization, as available from the data sets, projects the average values of SD1 characteristics, that is, Short Term HRV in females as 58.265ms and SD2 as 149.474. The SDRR shows a mean value of 87.298 with a standard deviation of 119.669 and the S Characterization as 16505.99 ms and Standard deviation of 45882.31 ms. The SDRR shows a mean value of 87.298 with a standard deviation of 119.669 and the S Characterization as 16505.99 ms and Standard deviation of 45882.31 ms. ApEn Characterization showed mean value of 0.961 and standard deviation of 0.274.

scholarly journals Proinsulin to insulin ratio is associated with incident type 2 diabetes but not with vascular complications in the KORA F4/FF4 study

2020 ◽  
Vol 8 (1) ◽  
pp. e001425
Author(s):  
Cornelia Then ◽  
Christina Gar ◽  
Barbara Thorand ◽  
Cornelia Huth ◽  
Holger Then ◽  
...  
Keyword(s):  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Metabolic Syndrome ◽  
Waist Circumference ◽  
Vascular Complications ◽  
Model Assessment ◽  
Incident Type ◽  
The Metabolic Syndrome ◽  
Incident Type 2 Diabetes

IntroductionWe investigated the association of the proinsulin to insulin ratio (PIR) with prevalent and incident type 2 diabetes (T2D), components of the metabolic syndrome, and renal and cardiovascular outcomes in the population-based Cooperative Health Research in the Region of Augsburg (KORA) F4 study (2006–2008)/FF4 study (2013–2014).Research design and methodsThe analyses included 1514 participants of the KORA F4 study at baseline and 1132 participants of the KORA FF4 study after a median follow-up time of 6.6 years. All-cause and cardiovascular mortality as well as cardiovascular events were analyzed after a median time of 9.1 and 8.6 years, respectively. The association of PIR with T2D, renal and cardiovascular characteristics and mortality were assessed using logistic regression models. Linear regression analyses were used to assess the association of PIR with components of the metabolic syndrome.ResultsAfter adjustment for sex, age, body mass index (BMI), and physical activity, PIR was associated with prevalent (OR: 2.24; 95% CI 1.81 to 2.77; p<0.001) and incident T2D (OR: 1.66; 95% CI 1.26 to 2.17; p<0.001). PIR was associated with fasting glucose (β per SD: 0.11±0.02; p<0.001) and HbA1c (β: 0.21±0.02; p<0.001). However, PIR was not positively associated with other components of the metabolic syndrome and was even inversely associated with waist circumference (β: −0.22±0.03; p<0.001), BMI (β: −0.11±0.03; p<0.001) and homeostatic model assessment of insulin resistance (β: −0.22±0.02; p<0.001). PIR was not significantly associated with the intima-media thickness (IMT), decline of kidney function, incident albuminuria, myocardial infarction, stroke, cardiovascular or all-cause mortality.ConclusionsIn the KORA F4/FF4 cohort, PIR was positively associated with prevalent and incident T2D, but inversely associated with waist circumference, BMI and insulin resistance, suggesting that PIR might serve as a biomarker for T2D risk independently of the metabolic syndrome, but not for microvascular or macrovascular complications.

scholarly journals Serum uric acid and its association with metabolic syndrome and carotid atherosclerosis in obese children

2009 ◽  
Vol 160 (1) ◽  
pp. 45-52 ◽  
Author(s):  
Lucia Pacifico ◽  
Vito Cantisani ◽  
Caterina Anania ◽  
Elisabetta Bonaiuto ◽  
Francesco Martino ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Uric Acid ◽  
Carotid Atherosclerosis ◽  
Resistance Index ◽  
Model Assessment ◽  
Obese Children ◽  
Pubertal Stage ◽  
Carotid Imt

ObjectiveThe association between hyperuricemia, metabolic syndrome (MS), and atherosclerotic vascular disease has been reported in adults, but very little is known about this association in children. The aims of our study were to ascertain the correlates of uric acid (UA) in a sample of obese children, and to investigate whether UA is associated with carotid intima-media thickness (IMT) independently from classical risk factors including MS.MethodsWe analyzed carotid IMT along with serum triglycerides, total and high-density lipoprotein cholesterol, glucose, insulin, insulin resistance index (as homeostasis model assessment of insulin resistance), alanine aminotransferase, γ-glutamyltransferase, creatinine, and UA in 120 obese children and 50 healthy control children.ResultsUA concentrations were significantly higher in obese children compared with controls; moreover, they correlated with the most established cardiovascular risk factors. In the group of obese children, after adjustment for age, sex, pubertal stage, and creatinine, an independent association between UA levels and the presence of MS syndrome was observed (unstandardized coefficient, 0.044 (95% confidence intervals (CI) 0.015–0.072); P<0.01). Carotid IMT significantly increased in the fourth quartile of UA compared with that in the first, second, and third quartile (0.49 (0.46–0.53), 0.53 (0.49–0.56), and 0.55 (0.52–0.59) vs 0.61 (95% CI, 0.58–0.64); P<0.01). When multivariate analysis was performed after adjusting for age, gender, pubertal stage, creatinine, and MS (considered as a single clinical entity), or the individual components of MS simultaneously included, the association between UA and carotid IMT was significant (P<0.01).ConclusionsIn obese children and adolescents, increased UA levels are associated with carotid atherosclerosis.

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.

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