Insulin resistance and circadian rhythm of cardiac autonomic modulation

<p>Abstract</p> <p>Background</p> <p>Insulin 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.</p> <p>Method</p> <p>Homeostasis 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.</p> <p>Results</p> <p>In 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 <it>P </it>< 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.</p> <p>Conclusion</p> <p>Elevated 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.</p

Clinical and polysomnographic predictors of the Natural History of poor sleep in the general population

Study Objectives: Approximately 8-10% of the general population suffers from chronic insomnia, whereas another 20-30% of the population has insomnia symptoms at any given time (i.e., poor sleep). However, few longitudinal studies have examined risk factors of the natural history of poor sleep, and none have examined the role of polysomnographic (PSG) variables. Design: Representative longitudinal study. Setting: Sleep laboratory. Participants: From a random, general population sample of 1,741 individuals of the adult Penn State Cohort, 1,395 were followed up after 7.5 yr. Measurements: Full medical evaluation and 1-night PSG at baseline and telephone interview at follow-up. Results: The rate of incident poor sleep was 18.4%. Physical (e.g., obesity, sleep apnea, and ulcer) and mental (e.g., depression) health conditions and behavioral factors (e.g., smoking and alcohol consumption) increased the odds of incident poor sleep as compared to normal sleep. The rates of persistent, remitted, and poor sleepers who developed chronic insomnia were 39%, 44%, and 17%, respectively. Risk factors for persistent poor sleep were physical health conditions combined with psychologic distress. Shorter objective sleep duration and a family history of sleep problems were risk factors for poor sleep evolving into chronic insomnia. Conclusions: Poor sleep appears to be primarily a symptom of physical and mental health conditions, whereas the persistence of poor sleep is associated with psychologic distress. Importantly, sleep apnea appears to be associated with incident poor sleep but not with chronic insomnia. Finally, this study suggests that objective short sleep duration in poor sleepers is a biologic marker of genetic predisposition to chronic insomniaThis research was funded in part by the National Institutes of Health grants RO1 51931, RO1 40916 (to Dr. Bixler), and RO1 64415 (to Dr. Vgontzas)

Ultrasensitive detection of waste products in water using fluorescence emission cavity-enhanced spectroscopy

Clean water is paramount to human health. In this article, we present a technique for detection of trace amounts of human or animal waste products in water using fluorescence emission cavity-enhanced spectroscopy. The detection of femtomolar concentrations of urobilin, a metabolic byproduct of heme metabolism that is excreted in both human and animal waste in water, was achieved through the use of an integrating cavity. This technique could allow for real-time assessment of water quality without the need for expensive laboratory equipment

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 PM2.5 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

Acute effects of fine particulate air pollution on ST segment height: A longitudinal study

Background The mechanisms for the relationship between particulate air pollution and cardiac disease are not fully understood. Air pollution-induced myocardial ischemia is one of the potentially important mechanisms. Methods We investigate the acute effects and the time course of fine particulate pollution (PM2.5) on myocardium ischemic injury as assessed by ST-segment height in a community-based sample of 106 healthy non-smokers. Twenty-four hour beat-to-beat electrocardiogram (ECG) data were obtained using a high resolution 12-lead Holter ECG system. After visually identifying and removing all the artifacts and arrhythmic beats, we calculated beat-to-beat ST-height from ten leads (inferior leads II, III, and aVF; anterior leads V3 and V4; septal leads V1 and V2; lateral leads I, V5, and V6,). Individual-level 24-hour real-time PM2.5 concentration was obtained by a continuous personal PM2.5 monitor. We then calculated, on a 30-minute basis, the corresponding time-of-the-day specific average exposure to PM2.5 for each participant. Distributed lag models under a linear mixed-effects models framework were used to assess the regression coefficients between 30-minute PM2.5 and ST-height measures from each lead; i.e., one lag indicates a 30-minute separation between the exposure and outcome. Results The mean (SD) age was 56 (7.6) years, with 41% male and 74% white. The mean (SD) PM2.5 exposure was 14 (22) μg/m3. All inferior leads (II, III, and aVF) and two out of three lateral leads (I and V6), showed a significant association between higher PM2.5 levels and higher ST-height. Most of the adverse effects occurred within two hours after PM2.5 exposure. The multivariable adjusted regression coefficients β (95% CI) of the cumulative effect due to a 10 μg/m3 increase in Lag 0-4 PM2.5 on ST-I, II, III, aVF and ST-V6 were 0.29 (0.01-0.56) μV, 0.79 (0.20-1.39) μV, 0.52 (0.01-1.05) μV, 0.65 (0.11-1.19) μV, and 0.58 (0.07-1.09) μV, respectively, with all p < 0.05. Conclusions Increased PM2.5 concentration is associated with immediate increase in ST-segment height in inferior and lateral leads, generally within two hours. Such an acute effect of PM2.5 may contribute to increased potential for regional myocardial ischemic injury among healthy individuals

Sleep apnea is a manifestation of the metabolic syndrome. Sleep medicine reviews

Summary Obstructive sleep apnea (OSA) is a prevalent disorder particularly among middle-aged, obese men, although its existence in women as well as in lean individuals is increasingly recognized. Despite the early recognition of the strong association between OSA and obesity, and OSA and cardiovascular problems, sleep apnea has been treated as a &apos;local abnormality&apos; of the respiratory track rather than as a &apos;systemic illness.&apos; In 1997, we first reported that the pro-inflammatory cytokines interleukin-6 (IL-6) and tumor necrosis factor-a (TNFa) were elevated in patients with disorders of excessive daytime sleepiness (EDS) and proposed that these cytokines were mediators of daytime sleepiness. Also, we reported a positive correlation between IL-6 or TNFa plasma levels and the body-mass-index (BMI). In subsequent studies, we showed that IL-6, TNFa, and insulin levels were elevated in sleep apnea independently of obesity and that visceral fat, was the primary parameter linked with sleep apnea. Furthermore, our findings that women with the polycystic ovary syndrome (PCOS) (a condition associated with hyperandrogenism and insulin resistance) were much more likely than controls to have sleep disordered breathing (SDB) and daytime sleepiness, suggests a pathogenetic role of insulin resistance in OSA. Other findings that support the view that sleep apnea and sleepiness in obese patients may be manifestations of the Metabolic Syndrome, include: obesity without sleep apnea is associated with daytime sleepiness; PCOS and diabetes type 2 are independently associated with EDS after controlling for SDB, obesity, and age; increased prevalence of sleep apnea in post-menopausal women, with hormonal replacement therapy associated with a significantly reduced risk for OSA; lack of effect of continuous positive airway pressure (CPAP) in obese patients with apnea on hypercytokinemia and insulin resistance indices; and that the prevalence of the metabolic syndrome in the US population from the Third National Health and Nutrition Examination Survey (1988)(1989)(1990)(1991)(1992)(1993)(1994) parallels the prevalence of symptomatic sleep apnea in general random samples. Finally, the beneficial effect of a cytokine antagonist on EDS in obese, male apneics and that of exercise on SDB in a general random sample, supports the hypothesis that cytokines and insulin resistance are mediators of EDS and sleep apnea in humans. Sleep Medicine Reviews (2005) In conclusion, accumulating evidence provides support to our model of the bidirectional, feed forward, pernicious association between sleep apnea, sleepiness, inflammation, and insulin resistance, all promoting atherosclerosis and cardiovascular disease.

Obesity-related sleepiness and fatigue - The role of the stress system and cytokines

Obesity has epidemic proportions in Western societies and, because of its significant association with morbidity and mortality, is a major public health issue. Excessive daytime sleepiness (EDS) and fatigue (tiredness without increased sleep propensity)-which have been associated with obesity-have a significant impact on individual wellbeing and public safety. In this article, we review data that challenge the belief that sleep apnea and sleep disruption per se are the primary determinants of obesity-related daytime sleepiness and fatigue. Specifically, it appears that obesity per se is associated with objective and subjective daytime sleepiness compared to normal-weight controls regardless of sleep apnea and sleep loss. Indeed, obese patients without sleep apnea are sleepier compared to nonobese controls whereas within the morbidly obese, those who have high sleep efficiency at night are sleepier than those who have low sleep efficiency. In addition, in recent studies based on large random samples of the general population, the primary determinants of subjective EDS were depression and metabolic disturbances, that is, obesity/diabetes, and not sleep apnea or objective sleep disruption. Furthermore, sleepiness and fatigue are very prevalent in conditions associated with insulin resistance, for instance, the polycystic ovary syndrome (PCOS), independently of sleep apnea or obesity, or in conditions of insufficient physical activity. On the basis of these data, we propose that obesity-related objective daytime sleepiness and fatigue are associated primarily with metabolic and psychological factors and less with sleep apnea and sleep disruption per se. Furthermore, we suggest that objective sleepiness is primarily related to metabolic factors, whereas fatigue appears to be related to psychological distress. Finally, based on data from studies in normal controls and patients with sleep disorders, we propose that the interaction of the hypothalamic-pituitary-adrenal (HPA) axis and proinflammatory cytokines determines the level of sleep/arousal within the 24-h cycle, that is, “hypercortisolemia” plus hypercytokinemia is associated with low sleep efficiency and fatigue, whereas “eucortisolemia” or “hypocortisolemia” plus hypercytokinemia is associated with high sleep efficiency and objective sleepiness