Insulin resistance and reduced cardiac autonomic function in older adults: the Atherosclerosis Risk in Communities study

Background: Prior studies have shown insulin resistance is associated with reduced cardiac autonomic function measured at rest, but few studies have determined whether insulin resistance is associated with reduced cardiac autonomic function measured during daily activities. Methods: We examined older adults without diabetes with 48-h ambulatory electrocardiography (n = 759) in an ancillary study of the Atherosclerosis Risk in Communities Study. Insulin resistance, the exposure, was defined by quartiles for three indexes: 1) the homeostatic model assessment of insulin resistance (HOMA-IR), 2) the triglyceride and glucose index (TyG), and 3) the triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C). Low heart rate variability, the outcome, was defined by <25th percentile for four measures: 1) standard deviation of normal-to-normal R-R intervals (SDNN), a measure of total variability; 2) root mean square of successive differences in normal-to-normal R-R intervals (RMSSD), a measure of vagal activity; 3) low frequency spectral component (LF), a measure of sympathetic and vagal activity; and 4) high frequency spectral component (HF), a measure of vagal activity. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals weighted for sampling/non-response, adjusted for age at ancillary visit, sex, and race/study-site. Insulin resistance quartiles 4, 3, and 2 were compared to quartile 1; high indexes refer to quartile 4 versus quartile 1. Results: The average age was 78 years, 66% (n = 497) were women, and 58% (n = 438) were African American. Estimates of association were not robust at all levels of HOMA-IR, TyG, and TG/HDL-C, but suggest that high indexes were associated consistently with indicators of vagal activity. High HOMA-IR, high TyG, and high TG/HDL-C were consistently associated with low RMSSD (OR: 1.68 (1.00, 2.81), OR: 2.03 (1.21, 3.39), and OR: 1.73 (1.01, 2.91), respectively). High HOMA-IR, high TyG, and high TG/HDL-C were consistently associated with low HF (OR: 1.90 (1.14, 3.18), OR: 1.98 (1.21, 3.25), and OR: 1.76 (1.07, 2.90), respectively). Conclusions: In older adults without diabetes, insulin resistance was associated with reduced cardiac autonomic function - specifically and consistently for indicators of vagal activity - measured during daily activities. Primary prevention of insulin resistance may reduce the related risk of cardiac autonomic dysfunction

A longitudinal study of DNA methylation as a potential mediator of age-related diabetes risk

DNA methylation (DNAm) has been found to show robust and widespread age-related changes across the genome. DNAm profiles from whole blood can be used to predict human aging rates with great accuracy. We sought to test whether DNAm-based predictions of age are related to phenotypes associated with type 2 diabetes (T2D), with the goal of identifying risk factors potentially mediated by DNAm. Our participants were 43 women enrolled in the Women's Health Initiative. We obtained methylation data via the Illumina 450K Methylation array on whole blood samples from participants at three timepoints, covering on average 16 years per participant. We employed the method and software of Horvath, which uses DNAm at 353 CpGs to form a DNAm-based estimate of chronological age. We then calculated the epigenetic age acceleration, or Δage, at each timepoint. We fit linear mixed models to characterize how Δage contributed to a longitudinal model of aging and diabetes-related phenotypes and risk factors. For most participants, Δage remained constant, indicating that age acceleration is generally stable over time. We found that Δage associated with body mass index (p = 0.0012), waist circumference (p = 0.033), and fasting glucose (p = 0.0073), with the relationship with BMI maintaining significance after correction for multiple testing. Replication in a larger cohort of 157 WHI participants spanning 3 years was unsuccessful, possibly due to the shorter time frame covered. Our results suggest that DNAm has the potential to act as a mediator between aging and diabetes-related phenotypes, or alternatively, may serve as a biomarker of these phenotypes

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

Can we identify non-stationary dynamics of trial-to-trial variability?"

Identifying sources of the apparent variability in non-stationary scenarios is a fundamental problem in many biological data analysis settings. For instance, neurophysiological responses to the same task often vary from each repetition of the same experiment (trial) to the next. The origin and functional role of this observed variability is one of the fundamental questions in neuroscience. The nature of such trial-to-trial dynamics however remains largely elusive to current data analysis approaches. A range of strategies have been proposed in modalities such as electro-encephalography but gaining a fundamental insight into latent sources of trial-to-trial variability in neural recordings is still a major challenge. In this paper, we present a proof-of-concept study to the analysis of trial-to-trial variability dynamics founded on non-autonomous dynamical systems. At this initial stage, we evaluate the capacity of a simple statistic based on the behaviour of trajectories in classification settings, the trajectory coherence, in order to identify trial-to-trial dynamics. First, we derive the conditions leading to observable changes in datasets generated by a compact dynamical system (the Duffing equation). This canonical system plays the role of a ubiquitous model of non-stationary supervised classification problems. Second, we estimate the coherence of class-trajectories in empirically reconstructed space of system states. We show how this analysis can discern variations attributable to non-autonomous deterministic processes from stochastic fluctuations. The analyses are benchmarked using simulated and two different real datasets which have been shown to exhibit attractor dynamics. As an illustrative example, we focused on the analysis of the rat's frontal cortex ensemble dynamics during a decision-making task. Results suggest that, in line with recent hypotheses, rather than internal noise, it is the deterministic trend which most likely underlies the observed trial-to-trial variability. Thus, the empirical tool developed within this study potentially allows us to infer the source of variability in in-vivo neural recordings

Neighborhood socioeconomic disparities and 1-year case fatality after incident myocardial infarction: The Atherosclerosis Risk in Communities (ARIC) Community Surveillance (1992-2002)

Declines in case-fatality post-myocardial infarction (MI) have been observed over the past three decades. Few studies report socioeconomic disparities in survival post-MI

Neighborhood socioeconomic and racial disparities in angiography and coronary revascularization: the ARIC surveillance study

Disparities in the receipt of angiography and subsequent coronary revascularization have not been well-studied

Variation in Rates of Fatal Coronary Heart Disease by Neighborhood Socioeconomic Status: The Atherosclerosis Risk in Communities Surveillance (1992–2002)

Racial and gender disparities in out-of-hospital deaths from coronary heart disease (CHD) have been well-documented, yet disparities by neighborhood socioeconomic status have been less systematically studied in US population-based surveillance efforts

Air Pollution and the Dynamic Association Between Depressive Symptoms and Memory in Oldest-Old Women

BACKGROUND/OBJECTIVES Exposure to air pollution may contribute to both increasing depressive symptoms and decreasing episodic memory in older adulthood, but few studies have examined this hypothesis in a longitudinal context. Accordingly, we examined the association between air pollution and changes in depressive symptoms (DS) and episodic memory (EM) and their interrelationship in oldest-old (aged 80 and older) women. DESIGN Prospective cohort data from the Women\u27s Health Initiative Memory Study-Epidemiology of Cognitive Health Outcomes. SETTING Geographically diverse community-dwelling population. PARTICIPANTS A total of 1,583 dementia-free women aged 80 and older. MEASUREMENTS Women completed up to six annual memory assessments (latent composite of East Boston Memory Test and Telephone Interview for Cognitive Status) and the 15-item Geriatric Depression Scale (GDS-15). We estimated 3-year average exposures to regional particulate matter with aerodynamic diameter below 2.5 μm (PM2.5) (interquartile range [IQR] = 3.35 μg/m3) and gaseous nitrogen dioxide (NO2) (IQR = 9.55 ppb) at baseline and during a remote period 10 years earlier, using regionalized national universal kriging. RESULTS Latent change structural equation models examined whether residing in areas with higher pollutant levels was associated with annual changes in standardized EM and DS while adjusting for potential confounders. Remote NO2 (β = .287 per IQR; P = .002) and PM2.5 (β = .170 per IQR; P = .019) exposure was significantly associated with larger increases in standardized DS, although the magnitude of the difference, less than 1 point on the GDS-15, is of questionable clinical significance. Higher DS were associated with accelerated EM declines (β = −.372; P = .001), with a significant indirect effect of remote NO2 and PM2.5 exposure on EM declines mediated by DS. There were no other significant indirect exposure effects. CONCLUSION These findings in oldest-old women point to potential adverse effects of late-life exposure to air pollution on subsequent interplay between DS and EM, highlighting air pollution as an environmental health risk factor for older women

Outdoor Air Pollution Exposure and Inter-relation of Global Cognitive Performance and Emotional Distress in Older Women

The interrelationships among long-term ambient air pollution exposure, emotional distress and cognitive decline in older adulthood remain unclear. Long-term exposure may impact cognitive performance and subsequently impact emotional health. Conversely, exposure may initially be associated with emotional distress followed by declines in cognitive performance. Here we tested the inter-relationship between global cognitive ability, emotional distress, and exposure to PM2.5 (particulate matter with aerodynamic diameter 2 (nitrogen dioxide) in 6118 older women (aged 70.6 ± 3.8 years) from the Women’s Health Initiative Memory Study. Annual exposure to PM2.5 (interquartile range [IQR] = 3.37 μg/m3) and NO2 (IQR = 9.00 ppb) was estimated at the participant’s residence using regionalized national universal kriging models and averaged over the 3-year period before the baseline assessment. Using structural equation mediation models, a latent factor capturing emotional distress was constructed using item-level data from the 6-item Center for Epidemiological Studies Depression Scale and the Short Form Health Survey Emotional Well-Being scale at baseline and one-year follow-up. Trajectories of global cognitive performance, assessed by the Modified-Mini Mental State Examination (3MS) annually up to 12 years, were estimated. All effects reported were adjusted for important confounders. Increases in PM2.5 (β = -0.144 per IQR; 95% CI = −0.261; −0.028) and NO2 (β = −0.157 per IQR; 95% CI = −0.291; −0.022) were associated with lower initial 3MS performance. Lower 3MS performance was associated with increased emotional distress (β = −0.008; 95% CI = −0.015; −0.002) over the subsequent year. Significant indirect effect of both exposures on increases in emotional distress mediated by exposure effects on worse global cognitive performance were present. No statistically significant indirect associations were found between exposures and 3MS trajectories putatively mediated by baseline emotional distress. Our study findings support cognitive aging processes as a mediator of the association between PM2.5 and NO2 exposure and emotional distress in later-life

Historical measures of social context in life course studies: Retrospective linkage of addresses to decennial censuses

Background There is evidence of a contribution of early life socioeconomic exposures to the risk of chronic diseases in adulthood. However, extant studies investigating the impact of the neighborhood social environment on health tend to characterize only the current social environment. This in part may be due to complexities involved in obtaining and geocoding historical addresses. The Life Course Socioeconomic Status, Social Context, and Cardiovascular Disease Study collected information on childhood (1930–1950) and early adulthood (1960–1980) place of residence from 12,681 black and white middle-aged and older men and women from four U.S. communities to link participants with census-based socioeconomic indicators over the life course. Results Most (99%) participants were linked to 1930–50 county level socioeconomic census data (the smallest level of aggregation universally available during this time period) corresponding to childhood place of residence. Linkage did not vary by race, gender, birth cohort, or level of educational attainment. A commercial geocoding vendor processed participants' self-reported street addresses for ages 30, 40, and 50. For 1970 and 1980 censuses, spatial coordinates were overlaid onto shape files containing census tract boundaries; for 1960 no shape files existed and comparability files were used. Several methods were tested for accuracy and to increase linkage. Successful linkage to historical census tracts varied by census (66% for 1960, 76% for 1970, 85% for 1980). This compares to linkage rates of 94% for current addresses provided by participants over the course of the ARIC examinations. Conclusion There are complexities and limitations in characterizing the past social context. However, our results suggest that it is feasible to characterize the earlier social environment with known levels of measurement error and that such an approach should be considered in future studies.http://deepblue.lib.umich.edu/bitstream/2027.42/57747/1/Historical measures of social context in life course studies Retrospective linkage of addresses to decimal censuses.pd