Sol Rodriguez-Colon

Metabolic Syndrome Clusters and the Risk of Incident Stroke. The Atherosclerosis Risk in Communities (ARIC) Study

Background and Purpose— Little is known about the metabolic syndrome (MetS) and the risk of incident stroke. This study is designed to identify particular clusters of MetS components that carry the highest risk of incident stroke. Methods— We analyzed the public use data from the population-based Atherosclerosis Risk in Communities study. At baseline, 14 993 stroke-free middle-aged individuals were followed-up over 9 years for incident stroke. MetS components were defined according to the National Heart, Lung, and Blood Institute/American Heart Association criteria. Incident stroke was identified using a standardized incident events identification and classification protocol. Proportional hazard models were used to assess the RRs and 95% CIs of ischemic stroke associated with MetS and its different clusters. Results— At baseline, the prevalence of MetS was 39%. The mean age was 54, with 26% blacks and 55% females. The hazard ratio of incident ischemic stroke associated with MetS among women (hazard ratio, 2.41; 95% CI, 1.69 to 3.49) and men (hazard ratio, 2.11; 95% CI, 1.56–2.85) was similar. There was a dose–response relationship between the numbers of MetS components and the risk of incidence stroke. Persons with either elevated blood pressure or elevated fasting glucose in the clusters to form a MetS had the highest risk for incident stroke (hazard ratio, 2.74–4.16 comparing to the reference group) than MetS without these 2 components (hazard ratio, ≤2.00 comparing to the reference group). Conclusions— The data support the need to target MetS, especially MetS, with these 2 highest risk components (elevated blood pressure or elevated fasting glucose) in the clusters.

Fine Particulate Air Pollution is Associated with Higher Vulnerability to Atrial Fibrillation—the Apacr Study

The acute effects and the time course of fine particulate pollution (PM2.5) on atrial fibrillation/flutter (AF) predictors, including P-wave duration, PR interval duration, and P-wave complexity, were investigated in a community-dwelling sample of 106 nonsmokers. Individual-level 24-h beat-to-beat electrocardiogram (ECG) data were visually examined. After identifying and removing artifacts and arrhythmic beats, the 30-min averages of the AF predictors were calculated. A personal PM2.5 monitor was used to measure individual-level, real-time PM2.5 exposures during the same 24-h period, and corresponding 30-min average PM2.5 concentration were calculated. Under a linear mixed-effects modeling framework, distributed lag models were used to estimate regression coefficients (βs) associating PM2.5 with AF predictors. Most of the adverse effects on AF predictors occurred within 1.5–2 h after PM2.5 exposure. The multivariable adjusted βs per 10-μg/m3 rise in PM 2.5 at lag 1 and lag 2 were significantly associated with P-wave complexity. PM2.5 exposure was also significantly associated with prolonged PR duration at lag 3 and lag 4. Higher PM2.5 was found to be associated with increases in P-wave complexity and PR duration. Maximal effects were observed within 2 h. These findings suggest that PM2.5 adversely affects AF predictors; thus, PM2.5 may be indicative of greater susceptibility to AF.

Individual-level PM 2.5 exposure and the time course of impaired heart rate variability: the APACR Study

In 106 community-dwelling middle-aged non-smokers we examined the time-course and the acute effects of fine particles (PM2.5) on heart rate variability (HRV), which measures cardiac autonomic modulation (CAM). Twenty-four hours beat-to-beat ECG data were visually examined. Artifacts and arrhythmic beats were removed. Normal beat-to-beat RR data were used to calculate HRV indices. Personal PM2.5 nephelometry was used to estimate 24-h individual-level real-time PM2.5 exposures. We use linear mixed-effects models to assess autocorrelation- and other major confounder-adjusted regression coefficients between 1–6 h moving averages of PM2.5 and HRV indices. The increases in preceding 1–6 h moving averages of PM2.5 was significantly associated with lower HF, LF, and SDNN, with the largest effect size at 4–6 h moving averages and smallest effects size at 1 h moving average. For example, a 10 μg/m3 increase in 1 and 6-h moving averages was associated with 0.027 and 0.068 ms2 decrease in log-HF, respectively, and with 0.024 and 0.071 ms2 decrease in log-LF, respectively, and with 0.81 and 1.75 ms decrease in SDNN, respectively (all P-values <0.05). PM2.5 exposures are associated with immediate impairment of CAM. With a time-course of within 6 h after elevated PM2.5 exposure, with the largest effects around 4–6 h.

Acute adverse effects of fine particulate air pollution on ventricular repolarization

Background The mechanisms for the relationship between particulate pollution and cardiac disease are not fully understood. Objective We examined the effects and time course of exposure to fine particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5) on ventricular repolarization of 106 nonsmoking adults who were living in communities in central Pennsylvania. Methods The 24-hr beat-to-beat electrocardiogram (ECG) data were obtained using a high-resolution 12-lead Holter system. After visually identifying and removing artifacts and arrhythmic beats, we summarized normal beat-to-beat QTs from each 30-min segment as heart rate (HR)-corrected QT measures: QT prolongation index (QTI), Bazett’s HR-corrected QT (QTcB), and Fridericia’s HR-corrected QT (QTcF). A personal PM2.5 monitor was used to measure individual-level real-time PM2.5 exposures for 24 hr. We averaged these data and used 30-min time-specific average PM2.5 exposures. Results The mean age of the participants was 56 ± 8 years, with 41% male and 74% white. The means ± SDs for QTI, QTcB, and QTcF were 111 ± 6.6, 438 ± 23 msec, and 422 ± 22 msec, respectively; and for PM2.5, the mean ± SD was 14 ± 22 μg/m3. We used distributed lag models under a framework of linear mixed-effects models to assess the autocorrelation-corrected regression coefficients (β) between 30-min PM2.5 and the HR-corrected QT measures. Most of the adverse ventricular repolarization effects from PM2.5 exposure occurred within 3–4 hr. The multivariable adjusted β (SE, p-value) due to a 10-μg/m3 increase in lag 7 PM2.5 on QTI, QTcB, and QTcF were 0.08 (0.04, p < 0.05), 0.22 (0.08, p < 0.01), and 0.09 (0.05, p < 0.05), respectively. Conclusions Our results suggest a significant adverse effect of PM2.5 on ventricular repolarization. The time course of the effect is within 3–4 hr of elevated PM2.5.

Acute Effects of Fine Particulate Air Pollution on Cardiac Arrhythmia: The APACR Study

Background: The mechanisms underlying the relationship between particulate matter (PM) air pollution and cardiac disease are not fully understood. Objectives: We examined the effects and time course of exposure to fine PM [aerodynamic diameter ≤ 2.5 μm (PM2.5)] on cardiac arrhythmia in 105 middle-age community-dwelling healthy nonsmokers in central Pennsylvania. Methods: The 24-hr beat-to-beat electrocardiography data were obtained using a high-resolution Holter system. After visually identifying and removing artifacts, we summarized the total number of premature ventricular contractions (PVCs) and premature atrial contractions (PACs) for each 30-min segment. A personal PM2.5 nephelometer was used to measure individual-level real-time PM2.5 exposures for 24 hr. We averaged these data to obtain 30-min average time–specific PM2.5 exposures. Distributed lag models under the framework of negative binomial regression and generalized estimating equations were used to estimate the rate ratio between 10-μg/m3 increases in average PM2.5 over 30-min intervals and ectopy counts. Results: The mean ± SD age of participants was 56 ± 8 years, with 40% male and 73% non-Hispanic white. The 30-min mean ± SD for PM2.5 exposure was 13 ± 22 μg/m3, and PAC and PVC counts were 0.92 ± 4.94 and 1.22 ± 7.18. Increases of 10 μg/m3 in average PM2.5 concentrations during the same 30 min or the previous 30 min were associated with 8% and 3% increases in average PVC counts, respectively. PM2.5 was not significantly associated with PAC count. Conclusion: PM2.5 exposure within approximately 60 min was associated with increased PVC counts in healthy individuals.

Natural history of sleep disordered breathing in prepubertal children transitioning to adolescence

Because there is a lack of agreed upon diagnostic criteria, it is critical to understand the natural history of obstructive sleep apnoea (OSA) in children in order to establish treatment strategies based on objective data. The Penn State Child Cohort is a representative, general-population sample of 700 elementary school children at baseline, of whom 421 were reassessed 8 years later, during adolescence. The remission of childhood apnoea–hypopnoea index (AHI) ≥2 events per h in adolescence was 52.9%. Using the higher threshold of AHI ≥5 events per h, remission was 100.0%, with 50.0% partially remitting to AHI 2– <5 events per h and the other half remitting to AHI <2 events per h. The incidence of adolescent AHI ≥2 events per h in those with childhood AHI <2 events per h was 36.5%, while the incidence of AHI ≥5 events per h in those with childhood AHI <5 events per h was 10.6%. This longitudinal study confirms that prepubertal OSA tends to resolve naturally during the transition to adolescence, and that primary snoring and mild sleep disordered breathing (SDB) do not appear to be strongly associated with progression to more severe SDB. The key risk factors for SDB in adolescence are similar to those found in middle-aged adults (i.e. male sex, older age and obesity). Moreover, consistent with recent studies in adults, this study includes the novel cross-sectional finding that visceral fat is associated with SDB as early as adolescence. Prepubertal sleep disordered breathing tends to resolve naturally during transition to adolescence http://ow.ly/X2Uv8

Abdominal Obesity and Metabolic Syndrome Burden in Adolescents-Penn State Children Cohort Study

To investigate the association between abdominal obesity and metabolic syndrome (MetS) burden in a population-based sample of adolescents, we used data from 421 adolescents who completed the follow-up examination in the Penn State Children Cohort study. Dual-energy x-ray absorptiometry (DXA) was used to assess abdominal obesity, as measured by android/gynoid fat ratio (A/G ratio), android/whole body fat proportion (A/W proportion), visceral (VAT) and subcutaneous fat (SAT) areas. Continuous metabolic syndrome score (cMetS), calculated as the sum of the age and sex-adjusted standardized residual (Z-score) of five established MetS components, was used to assess the MetS burden. Linear regression models were used to analyze the impact of DXA measures on cMetS components. All models were adjusted for age, race, sex, and general obesity. We found abdominal obesity is significantly associated with increased cMetS. With 1 standard deviation (SD) increase in A/G ratio, A/W proportion, VAT area, and SAT area, cMetS increased by 1.34 (SE=0.17), 1.25 (SE=0.19), 1.67 (SE=0.17), and 1.84 (SE=0.20) units, respectively. At individual component level, strongest association was observed between abdominal obesity and insulin resistance (IR) than lipid-based or blood pressure-based components. VAT and SAT had a stronger impact on IR than android ratio-based DXA measurements. In conclusion, abdominal obesity is associated with higher MetS burden in adolescent population. The association between abdominal obesity and IR measure is the strongest, suggesting the key impact of abdominal obesity on IR in adolescents MetS burden.

Insulin resistance and circadian rhythm of cardiac autonomic modulation

BackgroundInsulin resistance (IR) has been associated with cardiovascular diseases (CVD). Heart rate variability (HRV), an index of cardiac autonomic modulation (CAM), is also associated with CVD mortality and CVD morbidity. Currently, there are limited data about the impairment of IR on the circadian pattern of CAM. Therefore, we conducted this investigation to exam the association between IR and the circadian oscillations of CAM in a community-dwelling middle-aged sample.MethodHomeostasis models of IR (HOMA-IR), insulin, and glucose were used to assess IR. CAM was measured by HRV analysis from a 24-hour electrocardiogram. Two stage modeling was used in the analysis. In stage one, for each individual we fit a cosine periodic model based on the 48 segments of HRV data. We obtained three individual-level cosine parameters that quantity the circadian pattern: mean (M), measures the overall average of a HRV index; amplitude (Â), measures the amplitude of the oscillation of a HRV index; and acrophase time (θ), measures the timing of the highest oscillation. At the second stage, we used a random-effects-meta-analysis to summarize the effects of IR variables on the three circadian parameters of HRV indices obtained in stage one of the analysis.ResultsIn persons without type diabetes, the multivariate adjusted β (SE) of log HOMA-IR and M variable for HRV were -0.251 (0.093), -0.245 (0.078), -0.19 (0.06), -4.89 (1.76), -3.35 (1.31), and 2.14 (0.995), for log HF, log LF, log VLF, SDNN, RMSSD and HR, respectively (all P < 0.05). None of the IR variables were significantly associated with  or θ of the HRV indices. However, in eight type 2 diabetics, the magnitude of effect due to higher HOMA-IR on M, Â, and θ are much larger.ConclusionElevated IR, among non-diabetics significantly impairs the overall mean levels of CAM. However, the  or θ of CAM were not significantly affected by IR, suggesting that the circadian mechanisms of CAM are not impaired. However, among persons with type 2 diabetes, a group clinically has more severe form of IR, the adverse effects of increased IR on all three HRV circadian parameters are much larger.

Sleep Disordered Breathing in Children is Associated with Impairment of Sleep Stage Specific Shift of Cardiac Autonomic Modulation

We examined the effects of sleep stages and sleep‐disordered breathing (SDB) on autonomic modulation in 700 children. Apnea hypopnea index (AHI) during one 9 h night‐time polysomnography was used to define SDB. Sleep stage‐specific autonomic modulation was measured by heart rate variability (HRV) analysis of the first available 5 min RR intervals from each sleep stage. The mean [standard deviation (SD)] age was 112 (21) months (49% male and 25% non‐Caucasian). The average AHI was 0.79 (SD = 1.03) h−1, while 73.0%, 25.8% and 1.2% of children had AHI <1 (no SDB), 1–5 (mild SDB) and ≥5 (moderate SDB), respectively. In the no SDB group, the high frequency (HF) and root mean square SD (RMSSD) increased significantly from wake to Stage 2 and slow wave sleep (SWS), and then decreased dramatically when shifting into rapid eye movement (REM) sleep. In the moderate SDB group, the pattern of HRV shift was similar to that of no SDB. However, the decreases in HF and RMSSD from SWS to REM were more pronounced in moderate SDB children [between‐group differences in HF (−24% in moderate SDB versus −10% in no SDB) and RMSSD (−27% versus −12%) were significant (P < 0.05)]. The REM stage HF is significantly lower in the moderate SDB group compared to the no SDB group [mean (standard error): 4.49 (0.43) versus 5.80 (0.05) ms2, respectively, P < 0.05]. Conclusions are that autonomic modulation shifts significantly towards higher parasympathetic modulation from wake to non‐rapid eye movement sleep, and reverses to a less parasympathetic modulation during REM sleep. However, the autonomic modulation is impaired among children with moderate SDB in the directions of more reduction in parasympathetic modulation from SWS to REM sleep and significantly weaker parasympathetic modulation in REM sleep, which may lead to higher arrhythmia vulnerability, especially during REM sleep.

Metabolic syndrome burden in apparently healthy adolescents is adversely associated with cardiac autonomic modulation--Penn State Children Cohort.

BACKGROUND Reduced cardiac autonomic modulation (CAM) has been associated with metabolic syndrome (MetS) in adults. However, the association between MetS component cluster and CAM has not been examined in adolescents. METHODS We conducted a cross-sectional analysis using data from the Penn State Child Cohort follow-up examination. CAM was assessed by heart rate variability (HRV) analysis of 39-h RR intervals, including frequency (high frequency, HF; low frequency, LF; and LF/HF ratio) and time (SDNN, standard deviation of all RR intervals; RMSSD, square root of the mean of the sum of the squares of differences between adjacent RR intervals; and HR, heart rate) domain variables. To assess the MetS burden, we used continuous MetS score (cMetS)--sum of the age and sex-adjusted standardized residual (Z-score) of five established MetS components. Linear mixed-effect models were used to analyze the association between cMetS and CAM in the entire population and stratified by gender. RESULTS After adjusting for age, sex, and race, cMetS was significantly associated with reduced HRV and higher HR. With 1 standard deviation increase in cMetS, there was a significant decrease in HF (-0.10 (SE = 0.02)), LF (-0.07 (SE = 0.01)), SDNN (-1.97 (SE = 0.50)), and RMSSD (-1.70 (SE = 0.72)), and increase in LF/HF (0.08 (SE = 0.02)) and HR (1.40 (SE = 0.26)). All cMetS components, with the exception of high-density lipoprotein (HDL), were associated with significantly decreased HRV and increased HR. High blood pressure (MAP) and triglyceride (TG) levels were also associated with an increase in LF/HF and decrease in RMSSD. An increase in high-density lipoprotein was only associated with higher LF and SDNN. Moreover, cMetS and HRV associations were more pronounced in males than in females. The associations between HRV and. MAP, TG, and HDL were more pronounced in females. CONCLUSIONS cMetS score is associated with lower HRV, suggesting an adverse impact on CAM, even in apparently healthy adolescents.