Resting Heartbeat Complexity Predicts All-Cause and Cardiorespiratory Mortality in Middle- to Older-Aged Adults From the UK Biobank

Psychosocial stress and cardiovascular disease

Mahatma Gandhi once famously said: "poverty is the worst type of violence". He was referring to the state of political and social unrest that was pervading his nation, and the impact that humiliating defeat had on those who suffered in dire straits. Today, there is mounting evidence that social disparities cause intense psychosocial stress on those on whom they are imposed and can result in adverse cardiovascular outcomes. In modern society we still witness large disparities in living conditions between races, regions, continents and nations. Even in more privileged nations, we often witness the existence of "food and social deserts" in the middle of large urban centers. Sizable segments of the population are deprived of the comforts and privileges enjoyed by others; food quality and choices are limited, opportunities to exercise and play are scarce or unsafe, physical and verbal violence are prevalent, and racially driven conflicts are frequent. It has become apparent that these conditions predispose to the development of cardiovascular disease and affect its outcome negatively. Besides the increase in incidence of traditional risk factors, such as smoking, hypertension, insulin resistance and obesity, several other pathophysiological mechanisms involving the neuro-endocrine, inflammatory and immune pathways may be responsible for the noted negative outcomes. In this manuscript we review some of the evidence linking social distress with adverse cardiovascular outcomes and the potential subtending mechanisms and therapeutic interventions.

Daytime eating during simulated night work mitigates changes in cardiovascular risk factors: secondary analyses of a randomized controlled trial

Effective countermeasures against the adverse cardiovascular effects of circadian misalignment, such as effects experienced due to night work or jet lag, remain to be established in humans. Here, we aim to test whether eating only during daytime can mitigate such adverse effects vs. eating during the night and day (typical for night shift workers) under simulated night work (secondary analysis of NCT02291952). This single-blind, parallel-arm trial randomized 20 healthy participants (non-shift workers) to simulated night work with meals consumed during night and day (Nighttime Meal Control Group) or only during daytime (Daytime Meal Intervention Group). The primary outcomes were pNN50 (percentage consecutive heartbeat intervals >50 ms), RMSSD (root mean square of successive heartbeat differences), and LF/HF (low/high cardiac frequency). The secondary outcome was blood concentrations of prothrombotic factor plasminogen activator inhibitor-1 (PAI-1). These measures were assessed under Constant Routine conditions, before (baseline) and after (postmisalignment) simulated night work. The meal timing intervention significantly modified the impact of simulated night work on cardiac vagal modulation and PAI-1 (pFDR = 0.001). In the Control Group, the postmisalignment Constant Routine showed a decrease in pNN50 by 25.7% (pFDR = 0.008) and RMMSD by 14.3% (pFDR = 0.02), and an increase in LF/HF by 5.5% (pFDR = 0.04) and PAI-1 by 23.9% (pFDR = 0.04), vs. the baseline Constant Routine. In the Intervention Group, there were no significant changes in these outcomes. For exploratory outcomes, the intervention significantly modified the impact of simulated night work on blood pressure (P < 0.05), with no significant change in the Control Group, and a significant reduction by 6-8% (P < 0.01) in the Intervention Group; without significant effects for heart rate or cortisol. These findings indicate that daytime eating, despite mistimed sleep, may mitigate changes in cardiovascular risk factors and offer translational evidence for developing a behavioral strategy to help minimize the adverse changes in cardiovascular risk factors in individuals exposed to circadian misalignment, such as shift workers.

Associations of Rest-Activity Rhythm Disturbances With Stroke Risk and Poststroke Adverse Outcomes

BACKGROUND

Many disease processes are influenced by circadian clocks and display ~24-hour rhythms. Whether disruptions to these rhythms increase stroke risk is unclear. We evaluated the association between 24-hour rest-activity rhythms, stroke risk, and major poststroke adverse outcomes.

METHODS AND RESULTS

We examined ~100 000 participants from the UK Biobank (aged 44-79 years; ~57% women) assessed with actigraphy (6-7 days) and 5-year median follow-up. We derived (1) most active 10-hour activity counts across the 24-hour cycle and the timing of its midpoint timing; (2) the least active 5-hour count and its midpoint; (3) relative amplitude; (4) interdaily stability; and (5) intradaily variability, for stability and fragmentation of the rhythm. Cox proportional hazard models were constructed for time to (1) incident stroke (n=1652) and (2) poststroke adverse outcomes (dementia, depression, disability, or death). Suppressed relative amplitude (lowest quartile [quartile 1] versus the top quartile [quartile 4]) was associated with stroke risk (hazard ratio [HR], 1.61 [95% CI, 1.35-1.92]; P<0.001) after adjusting for demographics. Later most active 10-hour activity count midpoint timing (14:00-15:26; HR, 1.26 [95% CI, 1.07-1.49]; P=0.007) also had higher stroke risk than earlier (12:17-13:10) participants. A fragmented rhythm (intradaily variability) was also associated with higher stroke risk (quartile 4 versus quartile 1; HR, 1.26 [95% CI, 1.06-1.49]; P=0.008). Suppressed relative amplitude was associated with risk for poststroke adverse outcomes (quartile 1 versus quartile 4; HR, 2.02 [95% CI, 1.46-2.48]; P<0.001). All associations were independent of age, sex, race, obesity, sleep disorders, cardiovascular diseases or risks, and other comorbidity burdens.

CONCLUSIONS

Suppressed 24-hour rest-activity rhythm may be a risk factor for stroke and an early indicator of major poststroke adverse outcomes.

Stress and cardiovascular disease: an update

Psychological stress is generally accepted to be associated with an increased risk of cardiovascular disease (CVD), but results have varied in terms of how stress is measured and the strength of the association. Additionally, the mechanisms and potential causal links have remained speculative despite decades of research. The physiological responses to stress are well characterized, but their contribution to the development and progression of CVD has received little attention in empirical studies. Evidence suggests that physiological responses to stress have a fundamental role in the risk of CVD and that haemodynamic, vascular and immune perturbations triggered by stress are especially implicated. Stress response physiology is regulated by the corticolimbic regions of the brain, which have outputs to the autonomic nervous system. Variation in these regulatory pathways might explain interindividual differences in vulnerability to stress. Dynamic perturbations in autonomic, immune and vascular functions are probably also implicated as CVD risk mechanisms of chronic, recurring and cumulative stressful exposures, but more data are needed from prospective studies and from assessments in real-life situations. Psychological assessment remains insufficiently recognized in clinical care and prevention. Although stress-reduction interventions might mitigate perceived stress levels and potentially reduce cardiovascular risk, more data from randomized trials are needed.

Association of Rest-Activity Rhythm and Risk of Developing Dementia or Mild Cognitive Impairment in the Middle-Aged and Older Population: Prospective Cohort Study

BACKGROUND

The relationship between 24-hour rest-activity rhythms (RARs) and risk for dementia or mild cognitive impairment (MCI) remains an area of growing interest. Previous studies were often limited by small sample sizes, short follow-ups, and older participants. More studies are required to fully explore the link between disrupted RARs and dementia or MCI in middle-aged and older adults.

OBJECTIVE

We leveraged the UK Biobank data to examine how RAR disturbances correlate with the risk of developing dementia and MCI in middle-aged and older adults.

METHODS

We analyzed the data of 91,517 UK Biobank participants aged between 43 and 79 years. Wrist actigraphy recordings were used to derive nonparametric RAR metrics, including the activity level of the most active 10-hour period (M10) and its midpoint, the activity level of the least active 5-hour period (L5) and its midpoint, relative amplitude (RA) of the 24-hour cycle [RA=(M10-L5)/(M10+L5)], interdaily stability, and intradaily variability, as well as the amplitude and acrophase of 24-hour rhythms (cosinor analysis). We used Cox proportional hazards models to examine the associations between baseline RAR and subsequent incidence of dementia or MCI, adjusting for demographic characteristics, comorbidities, lifestyle factors, shiftwork status, and genetic risk for Alzheimer's disease.

RESULTS

During the follow-up of up to 7.5 years, 555 participants developed MCI or dementia. The dementia or MCI risk increased for those with lower M10 activity (hazard ratio [HR] 1.28, 95% CI 1.14-1.44, per 1-SD decrease), higher L5 activity (HR 1.15, 95% CI 1.10-1.21, per 1-SD increase), lower RA (HR 1.23, 95% CI 1.16-1.29, per 1-SD decrease), lower amplitude (HR 1.32, 95% CI 1.17-1.49, per 1-SD decrease), and higher intradaily variability (HR 1.14, 95% CI 1.05-1.24, per 1-SD increase) as well as advanced L5 midpoint (HR 0.92, 95% CI 0.85-0.99, per 1-SD advance). These associations were similar in people aged <70 and >70 years, and in non-shift workers, and they were independent of genetic and cardiovascular risk factors. No significant associations were observed for M10 midpoint, interdaily stability, or acrophase.

CONCLUSIONS

Based on findings from a large sample of middle-to-older adults with objective RAR assessment and almost 8-years of follow-up, we suggest that suppressed and fragmented daily activity rhythms precede the onset of dementia or MCI and may serve as risk biomarkers for preclinical dementia in middle-aged and older adults.

Heart Rate Variability, Deceleration Capacity of Heart Rate, and Death: A Veteran Twins Study

BACKGROUND

Autonomic function can be measured noninvasively using heart rate variability (HRV), which indexes overall sympathovagal balance. Deceleration capacity (DC) of heart rate is a more specific metric of vagal modulation. Higher values of these measures have been associated with reduced mortality risk primarily in patients with cardiovascular disease, but their significance in community samples is less clear.

METHODS AND RESULTS

This prospective twin study followed 501 members from the VET (Vietnam Era Twin) registry. At baseline, frequency domain HRV and DC were measured from 24-hour Holter ECGs. During an average 12-year follow-up, all-cause death was assessed via the National Death Index. Multivariable Cox frailty models with random effect for twin pair were used to examine the hazard ratios of death per 1-SD increase in log-transformed autonomic metrics. Both in the overall sample and comparing twins within pairs, higher values of low-frequency HRV and DC were significantly associated with lower hazards of all-cause death. In within-pair analysis, after adjusting for baseline factors, there was a 22% and 27% lower hazard of death per 1-SD increment in low-frequency HRV and DC, respectively. Higher low-frequency HRV and DC, measured during both daytime and nighttime, were associated with decreased hazard of death, but daytime measures showed numerically stronger associations. Results did not substantially vary by zygosity.

CONCLUSIONS

Autonomic inflexibility, and especially vagal withdrawal, are important mechanistic pathways of general mortality risk, independent of familial and genetic factors.

An Interpretable Population Graph Network to Identify Rapid Progression of Alzheimer's Disease Using UK Biobank

Alzheimer's disease (AD) manifests with varying progression rates across individuals, necessitating the understanding of their intricate patterns of cognition decline that could contribute to effective strategies for risk monitoring. In this study, we propose an innovative interpretable population graph network framework for identifying rapid progressors of AD by utilizing patient information from electronic health-related records in the UK Biobank. To achieve this, we first created a patient similarity graph, in which each AD patient is represented as a node; and an edge is established by patient clinical characteristics distance. We used graph neural networks (GNNs) to predict rapid progressors of AD and created a GNN Explainer with SHAP analysis for interpretability. The proposed model demonstrates superior predictive performance over the existing benchmark approaches. We also revealed several clinical features significantly associated with the prediction, which can be used to aid in effective interventions for the progression of AD patients.

Associations between depression symptom burden and delirium risk: a prospective cohort study

BACKGROUND AND OBJECTIVES

Delirium and depression are increasingly common in aging. There is considerable clinical overlap, including shared symptoms and comorbid conditions, including Alzheimer's disease (AD), functional decline, and mortality. Despite this, the long-term relationship between depression and delirium remains unclear. This study assessed the associations of depression symptom burden and its trajectory with delirium risk in a 12-year prospective study of older individuals during hospitalization.

RESEARCH DESIGN AND METHODS

319,141 UK biobank participants between 2006-2010 (mean 58y [range 37-74, SD=8], 54% female) reported frequency (0-3) of four depressive symptoms (mood, disinterest, tenseness, or lethargy) in the preceding 2 weeks, and aggregated into a depressive symptom burden score (0-12). New-onset delirium was obtained from hospitalization records during 12y median follow-up. 40,451 (mean age 57±8; range 40-74y) had repeat assessment on average 8y after their first. Cox proportional hazard models examined whether depression symptom burden and trajectory predicted incident delirium during hospitalization.

RESULTS

5,753 (15 per 1000) newly developed delirium during follow-up. Increased risk for delirium was seen for mild (aggregated scores 1-2, hazards ratio, HR=1.16, [95% confidence interval 1.08-1.25], p<0.001), modest (scores 3-5, 1.30 [1.19-1.43], p<0.001) and severe (scores ≥ 5, 1.38 [1.24-1.55], p<0.001) depressive symptoms, versus none in the fully adjusted model. These findings were independent of the number of hospitalizations and consistent across hospitalization settings (e.g., surgical, medical, or critical care) and specialty (e.g., neuropsychiatric, cardiorespiratory or other). Worsening depression symptoms (≥1 point increase), compared to no change/improved score, were associated with an additional 39% increased risk (1.39 [1.03-1.88], p=0.03) independent of baseline depression burden. The association was strongest in those over 65y at baseline (p for interaction <0.001).

DISCUSSION AND IMPLICATIONS

Depression symptom burden and worsening trajectory predicted delirium risk during hospitalization. Increased awareness of subclinical depression symptoms may be warranted for delirium prevention.

Sleep behavior traits and associations with opioid-related adverse events: a cohort study

STUDY OBJECTIVES

Opioid-related adverse events (OAEs), including opioid use disorders, overdose, and death, are serious public health concerns. OAEs are often associated with disrupted sleep, but the long-term relationship between poor sleep and subsequent OAE risk remains unknown. This study investigates whether sleep behavior traits are associated with incident OAEs in a large population cohort.

METHODS

444 039 participants (mean age ± SD 57 ± 8 years) from the UK Biobank reported their sleep behavior traits (sleep duration, daytime sleepiness, insomnia-like complaints, napping, and chronotype) between 2006 and 2010. The frequency/severity of these traits determined a poor sleep behavior impacts score (0-9). Incident OAEs were obtained from hospitalization records during 12-year median follow-up. Cox proportional hazards models examined the association between sleep and OAEs.

RESULTS

Short and long sleep duration, frequent daytime sleepiness, insomnia symptoms, and napping, but not chronotype, were associated with increased OAE risk in fully adjusted models. Compared to the minimal poor sleep behavior impacts group (scores of 0-1), the moderate (4-5) and significant (6-9) groups had hazard ratios of 1.47 (95% confidence interval [1.27, 1.71]), p < 0.001, and 2.19 ([1.82, 2.64], p < 0.001), respectively. The latter risk magnitude is greater than the risk associated with preexisting psychiatric illness or sedative-hypnotic medication use. In participants with moderate/significant poor sleep impacts (vs. minimal), subgroup analysis revealed that age <65 years was associated with a higher OAE risk than in those ≥65 years.

CONCLUSIONS

Certain sleep behavior traits and overall poor sleep impacts are associated with an increased risk for opioid-related adverse events.

Associations of rest-activity rhythm disturbances with stroke risk and post-stroke adverse outcomes

Background

Almost all biological and disease processes are influenced by circadian clocks and display ∼24-hour rhythms. Disruption of these rhythms may be an important novel risk factor for stroke. We evaluated the association between 24-h rest-activity rhythm measures, stroke risk, and major post-stroke adverse outcomes.

Methods

In this cohort study, we examined ∼100,000 participants in the UK Biobank (44-79 years old; ∼57% females) who underwent an actigraphy (6-7 days) and 5-year median follow-up. We derived: (1) most active 10 hours activity counts ( M10 ) across the 24-h cycle and the timing of its midpoint ( M10 midpoint ); (2) the least active 5 hours counts ( L5 ) and its midpoint timing ( L5 midpoint ); (3) relative amplitude ( RA ) - (M10-L5)/(M10+L5); (4) interdaily stability (IS): stability and (5) intradaily variability (IV), fragmentation of the rhythm. Cox proportional hazard models were constructed for time to (i) incident stroke (n=1,652); and (ii) post-stroke adverse outcomes (dementia, depression, disability, or death).

Results

Suppressed RA (lower M10 and higher L5) was associated with stroke risk after adjusting for demographics; the risk was highest in the lowest quartile [Q1] for RA (HR=1.62; 95% CI:1.36-1.93, p <0.001) compared to the top quartile [Q4]. Participants with later M10 midpoint timing (14:00-15:26, HR=1.26, CI:1.07-1.49, p =0.007) also had a higher risk for stroke than earlier (12:17-13:10) participants. A fragmented rhythm (IV) was also associated with a higher risk for stroke (Q4 vs. Q1; HR=1.27; CI:1.06-1.50, p =0.008), but differences in the stability of rhythms (IS) were not. Suppressed RA was associated with an increased risk of unfavorable post-stroke outcomes (Q1 vs. Q4; 1.78 [1.29-2.47]; p <0.001). All the associations were independent of age, sex, race, obesity, sleep disorders, cardiovascular diseases or risks, and other morbidity burdens.

Conclusion

Suppressed 24-h rest-activity rhythm may be a risk factor for stroke and an early indicator of major post-stroke adverse outcomes.

Heart rate response and recovery during exercise predict future delirium risk-A prospective cohort study in middle- to older-aged adults

BACKGROUND

Delirium is a neurocognitive disorder characterized by an abrupt decline in attention, awareness, and cognition after surgical/illness-induced stressors on the brain. There is now an increasing focus on how cardiovascular health interacts with neurocognitive disorders given their overlapping risk factors and links to subsequent dementia and mortality. One common indicator for cardiovascular health is the heart rate response/recovery (HRR) to exercise, but how this relates to future delirium is unknown.

METHODS

Electrocardiogram data were examined in 38,740 middle- to older-aged UK Biobank participants (mean age = 58.1 years, range: 40-72 years; 47.3% males) who completed a standardized submaximal exercise stress test (15-s baseline, 6-min exercise, and 1-min recovery) and required hospitalization during follow-up. An HRR index was derived as the product of the heart rate (HR) responses during exercise (peak/resting HRs) and recovery (peak/recovery HRs) and categorized into low/average/high groups as the bottom quartile/middle 2 quartiles/top quartile, respectively. Associations between 3 HRR groups and new-onset delirium were investigated using Cox proportional hazards models and a 2-year landmark analysis to minimize reverse causation. Sociodemographic factors, lifestyle factors/physical activity, cardiovascular risk, comorbidities, cognition, and maximal workload achieved were included as covariates.

RESULTS

During a median follow-up period of 11 years, 348 participants (9/1000) newly developed delirium. Compared with the high HRR group (16/1000), the risk for delirium was almost doubled in those with low HRR (hazard ratio = 1.90, 95% confidence interval (95%CI): 1.30-2.79, p = 0.001) and average HRR (hazard ratio = 1.54, 95%CI: 1.07-2.22, p = 0.020)). Low HRR was equivalent to being 6 years older, a current smoker, or ≥3 additional cardiovascular disease risks. Results were robust in sensitivity analysis, but the risk appeared larger in those with better cognition and when only postoperative delirium was considered (n = 147; hazard ratio = 2.66, 95%CI: 1.46-4.85, p = 0.001).

CONCLUSION

HRR during submaximal exercise is associated with future risk for delirium. Given that HRR is potentially modifiable, it may prove useful for neurological risk stratification alongside traditional cardiovascular risk factors.

Sample, Fuzzy and Distribution Entropies of Heart Rate Variability: What Do They Tell Us on Cardiovascular Complexity?

Distribution Entropy (DistEn) has been introduced as an alternative to Sample Entropy (SampEn) to assess the heart rate variability (HRV) on much shorter series without the arbitrary definition of distance thresholds. However, DistEn, considered a measure of cardiovascular complexity, differs substantially from SampEn or Fuzzy Entropy (FuzzyEn), both measures of HRV randomness. This work aims to compare DistEn, SampEn, and FuzzyEn analyzing postural changes (expected to modify the HRV randomness through a sympatho/vagal shift without affecting the cardiovascular complexity) and low-level spinal cord injuries (SCI, whose impaired integrative regulation may alter the system complexity without affecting the HRV spectrum). We recorded RR intervals in able-bodied (AB) and SCI participants in supine and sitting postures, evaluating DistEn, SampEn, and FuzzyEn over 512 beats. The significance of "case" (AB vs. SCI) and "posture" (supine vs. sitting) was assessed by longitudinal analysis. Multiscale DistEn (mDE), SampEn (mSE), and FuzzyEn (mFE) compared postures and cases at each scale between 2 and 20 beats. Unlike SampEn and FuzzyEn, DistEn is affected by the spinal lesion but not by the postural sympatho/vagal shift. The multiscale approach shows differences between AB and SCI sitting participants at the largest mFE scales and between postures in AB participants at the shortest mSE scales. Thus, our results support the hypothesis that DistEn measures cardiovascular complexity while SampEn/FuzzyEn measure HRV randomness, highlighting that together these methods integrate the information each of them provides.

Association of Poor Sleep Burden in Middle Age and Older Adults With Risk for Delirium During Hospitalization

BACKGROUND

Delirium is a distressing neurocognitive disorder recently linked to sleep disturbances. However, the longitudinal relationship between sleep and delirium remains unclear. This study assessed the associations of poor sleep burden, and its trajectory, with delirium risk during hospitalization.

METHODS

About 321 818 participants from the UK Biobank (mean age 58 ± 8 years [SD]; range 37-74 years) reported (2006-2010) sleep traits (sleep duration, excessive daytime sleepiness, insomnia-type complaints, napping, and chronotype-a closely related circadian measure for sleep timing), aggregated into a sleep burden score (0-9). New-onset delirium (n = 4 775) was obtained from hospitalization records during a 12-year median follow-up. About 42 291 (mean age 64 ± 8 years; range 44-83 years) had repeat sleep assessment on average 8 years after their first.

RESULTS

In the baseline cohort, Cox proportional hazards models showed that moderate (aggregate scores = 4-5) and severe (scores = 6-9) poor sleep burden groups were 18% (hazard ratio = 1.18 [95% confidence interval: 1.08-1.28], p < .001) and 57% (1.57 [1.38-1.80], p < .001), more likely to develop delirium, respectively. The latter risk magnitude is equivalent to 2 additional cardiovascular risks. These findings appeared robust when restricted to postoperative delirium and after exclusion of underlying dementia. Higher sleep burden was also associated with delirium in the follow-up cohort. Worsening sleep burden (score increase ≥2 vs no change) further increased the risk for delirium (1.79 [1.23-2.62], p = .002) independent of their baseline sleep score and time lag. The risk was highest in those younger than 65 years at baseline (p for interaction <.001).

CONCLUSION

Poor sleep burden and worsening trajectory were associated with increased risk for delirium; promotion of sleep health may be important for those at higher risk.

Resting Heartbeat Complexity Predicts All-Cause and Cardiorespiratory Mortality in Middle- to Older-Aged Adults From the UK Biobank

Background

Spontaneous heart rate fluctuations contain rich information related to health and illness in terms of physiological complexity, an accepted indicator of plasticity and adaptability. However, it is challenging to make inferences on complexity from shorter, more practical epochs of data. Distribution entropy (DistEn) is a recently introduced complexity measure that is designed specifically for shorter duration heartbeat recordings. We hypothesized that reduced DistEn predicted increased mortality in a large population cohort.

Method and Results

The prognostic value of DistEn was examined in 7631 middle‐older–aged UK Biobank participants who had 2‐minute resting ECGs conducted (mean age, 59.5 years; 60.4% women). During a median follow‐up period of 7.8 years, 451 (5.9%) participants died. In Cox proportional hazards models with adjustment for demographics, lifestyle factors, physical activity, cardiovascular risks, and comorbidities, for each 1‐SD decrease in DistEn, the risk increased by 36%, 56%, and 73% for all‐cause, cardiovascular, and respiratory disease–related mortality, respectively. These effect sizes were equivalent to the risk of death from being >5 years older, having been a former smoker, or having diabetes mellitus. Lower DistEn was most predictive of death in those <55 years with a prior myocardial infarction, representing an additional 56% risk for mortality compared with older participants without prior myocardial infarction. These observations remained after controlling for traditional mortality predictors, resting heart rate, and heart rate variability.

Conclusions

Resting heartbeat complexity from short, resting ECGs was independently associated with mortality in middle‐ to older‐aged adults. These risks appear most pronounced in middle‐aged participants with prior MI, and may uniquely contribute to mortality risk screening.