The role of cardiovascular health and vascular events in the relationship between excessive daytime sleepiness and dementia risk.

Many studies suggest a relationship between excessive daytime sleepiness (EDS) and dementia incidence, but the underlying mechanisms remain uncertain. The study aimed to investigate the role of cardiovascular burden in the relationship between EDS and dementia incidence over a 12-year follow-up in community-dwelling older adults. We performed analyses on 6171 subjects (aged ≥65 years) free of dementia and vascular disease at baseline. Participants self-reported EDS at baseline and an expert committee validated both prevalent and incident dementia. We defined cardiovascular burden by a low Cardiovascular Health score, constructed using the American Heart Association metrics, and incident vascular events. To explore the potential role of the cardiovascular burden in the relationship between EDS and dementia, we conducted mediation analyses with inverse odds ratio-weighted estimation, using multivariable-adjusted proportional hazard Cox and logistic regression models. Subjects with EDS had a higher risk of all-cause dementia (hazard ratio [HR] 1.39, 95% confidence interval [CI] 1.13-1.69) and dementia with vascular component (DVC) (HR 2.14, 95% CI 1.30-3.51), but not Alzheimer's disease (HR 1.18, 95% CI 0.93-1.51). Cardiovascular burden explained 5% (95% CI 4.1-5.2) and 11% (95% CI 9.7-11.3) of the relationship between EDS and all-cause dementia and DVC, respectively. These findings confirm that EDS may be implicated in the development of dementia and indicate a weaker than expected role of cardiovascular burden in the relationship between EDS and DVC.

Trajectories of sleep duration and timing before dementia: a 14-year follow-up study.

BACKGROUND: given the complex relationship between sleep and neurodegenerative processes, it is important to examine whether changes in sleep patterns occur prior or close to dementia onset. OBJECTIVE: to examine the relationship between sleep parameters and dementia incidence and, to characterize trajectories of sleep patterns before dementia diagnosis. DESIGN: a 14-year longitudinal study including a nested case-control study. SETTING: the French Three-City Study. SUBJECTS: overall, 1,749 cognitively healthy participants (≥65 years) for the longitudinal study and, 182 incident dementia cases and 719 controls matched by sex, age and educational level for the case-control study. METHODS: dementia cases were assessed at each visit and self-reported sleep parameters at baseline, 2, 8, 10, 12 and 14 years. Cox models were used to estimate the risk of dementia associated with baseline sleep parameters (sleep duration, time in bed (TIB), sleep timing, sleepiness and insomnia). Latent-process mixed models were performed to compare sleep trajectories according to the case-control status. RESULTS: long baseline nighttime and 24-h sleep durations (≥9 h) as well as being persistent or becoming long sleepers during follow-up were associated with dementia incidence. Trajectories of sleep durations and TIB showed faster increases in cases compared with controls up to 12 years before dementia. The mean differences [95%CI] for 24-h sleep duration between cases and controls were: 0.27 h [0.01;0.52], 0.34 [0.09;0.58] and 0.67 [0.44;0.90] at -12, -8 and -2 years, respectively. Bedtime trajectories showed an earlier bedtime in cases up to -8 years. CONCLUSION: long sleep duration and earlier bedtime may impact dementia incidence.

Disentangling the causal effects of education and participation bias on Alzheimer's disease using Mendelian Randomization.

Introduction: People with university degrees have a lower incidence of Alzheimer's Disease (AD). However, the relationship between education and AD could be due to selection, collider, and ascertainment biases, such as lower familiarity with cognitive testing or the fact that those with degrees are more likely to participate in research. Here, we use two-sample Mendelian randomization (MR) to investigate the causal relationships between education, participation, and AD. Method: We used genome-wide association study (GWAS) summary statistics for educational attainment, three different measures of participation, AD (clinically diagnosed AD), and AD/ADRD (clinical diagnosis and family history of AD and related dementias). Independent genome-wide significant single nucleotide polymorphisms (SNPs) were extracted from the exposure summary statistics and harmonized with the outcome SNPs. Fixed-effects inverse variance weighted meta-analysis was the primary MR method; Cochran's Q statistic and MR Egger intercept were used to test for heterogeneity and pleiotropy, and Radial-MR was used to identify outliers. Sensitivity analyses included MR Egger, Weighted Median, and Weighted mode. Bidirectional analyses were used to test if AD pathology affects participation and multivariable MR (MVMR) assessed independent exposure-outcome effects. Results: Educational attainment reduced the risk of AD (OR IVW 95% CI= 0.70 [0.63, 0.79], p = 8e-10), and the results were robust based on sensitivity analyses. However, education increased the risk of AD/ADRD, though the results were not robust to sensitivity analyses (OR IVW 95% CI= 1.09 [1.02, 1.15], p = 0.006). Participation in MHQ reduced the odds of AD (OR IVW 95% CI= 0.325 [0.128, 0.326], p = 0.01). When adjusting for participation in MVMR, education remained associated with a reduced risk of AD (OR IVW 95% CI= 0.76 [0.62, 0.92], p = 0.006). Conclusion: Univariate MR analyses indicated that education and participation reduced the risk of AD. However, MR also suggested that education increased the risk of AD/ADRD, highlighting the inconsistencies between clinical and proxy diagnoses of AD, as proxy-AD may be affected by selection, collider, or ascertainment bias. MVMR indicated that participation is unlikely to explain the effect of education on AD identified in MR, and the protective effect of educational attainment may be due to other biological mechanisms, such as cognitive reserve.

Causal Associations of Sleep Apnea With Alzheimer Disease and Cardiovascular Disease: A Bidirectional Mendelian Randomization Analysis.

BACKGROUND: Sleep apnea (SA) has been linked to an increased risk of dementia in numerous observational studies; whether this is driven by neurodegenerative, vascular, or other mechanisms is not clear. We sought to examine the bidirectional causal relationships between SA, Alzheimer disease (AD), coronary artery disease (CAD), and ischemic stroke using Mendelian randomization. METHODS AND RESULTS: Using summary statistics from 4 recent, large genome-wide association studies of SA (n=523 366), AD (n=94 437), CAD (n=1 165 690), and stroke (n=1 308 460), we conducted bidirectional 2-sample Mendelian randomization analyses. Our primary analytic method was fixed-effects inverse variance-weighted (IVW) Mendelian randomization; diagnostics tests and sensitivity analyses were conducted to verify the robustness of the results. We identified a significant causal effect of SA on the risk of CAD (odds ratio [ORIVW]=1.35 per log-odds increase in SA liability [95% CI=1.25-1.47]) and stroke (ORIVW=1.13 [95% CI=1.01-1.25]). These associations were somewhat attenuated after excluding single-nucleotide polymorphisms associated with body mass index (ORIVW=1.26 [95% CI=1.15-1.39] for CAD risk; ORIVW=1.08 [95% CI=0.96-1.22] for stroke risk). SA was not causally associated with a higher risk of AD (ORIVW=1.14 [95% CI=0.91-1.43]). We did not find causal effects of AD, CAD, or stroke on risk of SA. CONCLUSIONS: These results suggest that SA increased the risk of CAD, and the identified causal association with stroke risk may be confounded by body mass index. Moreover, no causal effect of SA on AD risk was found. Future studies are warranted to investigate cardiovascular pathways between sleep disorders, including SA, and dementia.

Prospective associations between neighborhood features and body mass index in Montreal adolescents.

PURPOSE: To investigate the association between the neighborhood built environment and trajectories of body mass index (BMI) in youth. METHODS: Data were collected in a prospective study of 1293 adolescents in Montreal. Built environment variables were obtained from public databases for road networks, land use, and the Canadian Census. Anthropometric data were collected when participants were ages 12.5, 15 and 17 years. We undertook hierarchical cluster analysis to identify contrasting neighborhood types based on features of the built environment (e.g., vegetation, population density, walkability). Associations between neighborhood type and trajectories of BMI z-score (BMIz) were estimated using multivariable linear mixed regression analyses, stratified by sex. RESULTS: We identified three neighborhood types: Urban, Suburban, and Village. In contrast to the Urban type, the Suburban type was characterized by more vegetation, few services and low population density. Village and Suburban types were similar, but the former had greater land use diversity, population density with more parks and a denser food environment. Among girls, living in Urban types was associated with decreasing BMIz trajectories. Living in Village types was associated with increasing BMIz trajectories. No associations were observed among boys. CONCLUSIONS: Neighborhoods characterized by greater opportunities for active living appear to be less obesogenic, particularly among girls.

Multidimensional Sleep Profiles via Machine learning and Risk of Dementia and Cardiovascular Disease.

Importance: Sleep health comprises several dimensions such as duration and fragmentation of sleep, circadian activity, and daytime behavior. Yet, most research has focused on individual sleep characteristics. Studies are needed to identify sleep profiles incorporating multiple dimensions and to assess how different profiles may be linked to adverse health outcomes. Objective: To identify actigraphy-based 24-hour sleep/circadian profiles in older men and to investigate whether these profiles are associated with the incidence of dementia and cardiovascular disease (CVD) events over 12 years. Design: Data came from a prospective sleep study with participants recruited between 20032005 and followed until 2015-2016. Setting: Multicenter population-based cohort study. Participants: Among the 3,135 men enrolled, we excluded 331 men with missing or invalid actigraphy data and 137 with significant cognitive impairment at baseline, leading to a sample of 2,667 participants. Exposures: Leveraging 20 actigraphy-derived sleep and circadian activity rhythm variables, we determined sleep/circadian profiles using an unsupervised machine learning technique based on multiple coalesced generalized hyperbolic mixture modeling. Main Outcomes and Measures: Incidence of dementia and CVD events. Results: We identified three distinct sleep/circadian profiles: active healthy sleepers (AHS; n=1,707 (64.0%); characterized by normal sleep duration, higher sleep quality, stronger circadian rhythmicity, and higher activity during wake periods), fragmented poor sleepers (FPS; n=376 (14.1%); lower sleep quality, higher sleep fragmentation, shorter sleep duration, and weaker circadian rhythmicity), and long and frequent nappers (LFN; n=584 (21.9%); longer and more frequent naps, higher sleep quality, normal sleep duration, and more fragmented circadian rhythmicity). Over the 12-year follow-up, compared to AHS, FPS had increased risks of dementia and CVD events (Hazard Ratio (HR)=1.35, 95% confidence interval (CI)=1.02-1.78 and HR=1.32, 95% CI=1.08-1.60, respectively) after multivariable adjustment, whereas LFN showed a marginal association with increased CVD events risk (HR=1.16, 95% CI=0.98-1.37) but not with dementia (HR=1.09, 95%CI=0.86-1.38). Conclusion and Relevance: We identified three distinct multidimensional profiles of sleep health. Compared to healthy sleepers, older men with overall poor sleep and circadian activity rhythms exhibited worse incident cognitive and cardiovascular health. These results highlight potential targets for sleep interventions and the need for more comprehensive screening of poor sleepers for adverse outcomes.

Five-year changes in 24-hour sleep-wake activity and dementia risk in oldest old women.

INTRODUCTION: Sleep disruptions are associated with cognitive aging in older adults. However, it is unclear whether longitudinal changes in 24-hour multidimensional sleep-wake activity are linked to cognitive impairment in the oldest old. METHODS: We studied 733 cognitively unimpaired women (mean age=82.5±2.9 years) who completed two actigraphy assessments over five years. We performed hierarchical clustering on principal components in nine sleep, napping, and circadian rest-activity rhythm parameters to identify multidimensional sleep-wake change profiles and multinomial logistic regression to evaluate the associations between sleep-wake changes and risk of cognitive impairment at follow-up. RESULTS: We identified three sleep-wake change profiles: Stable Sleep (43.8%), Declining Nighttime Sleep (34.9%), and Increasing Sleepiness (21.3%). After adjustment for demographics and comorbidities, women with Increasing Sleepiness had approximately doubled (odds ratio=2.21, p=0.018) risk of dementia compared to those with Stable Sleep. DISCUSSION: Increasing sleepiness may be an independent marker or risk factor for dementia in oldest old women.

Multidimensional Sleep Health and Long-Term Cognitive Decline in Community-Dwelling Older Men.

Specific sleep characteristics have been associated with cognitive decline, Alzheimer's disease, and related dementias; however, studies examining the association between multidimensional sleep (a more comprehensive integration of sleep parameters) and cognitive decline are lacking. Among 2,811 older men without dementia, those with none, 1-2, and 3-5 "poor" self-reported sleep health dimensions had an adjusted 10-year change score of global cognition (3MS) of 2.9, 4.0 and 3.5 points (p-trend = 0.05), and in executive function (Trails B) completion time of 36.7, 42.7, and 46.7 seconds (p-trend < 0.01), respectively. In conclusion, a multidimensional measure of sleep health was associated with greater cognitive decline.

Causal Associations of Sleep Apnea with Alzheimer's Disease and Cardiovascular Disease: a Bidirectional Mendelian Randomization Analysis.

Background: Sleep apnea (SA) has been linked to an increased risk of dementia in numerous observational studies; whether this is driven by neurodegenerative, vascular or other mechanisms is not clear. We sought to examine the bidirectional causal relationships between SA, Alzheimer's disease (AD), coronary artery disease (CAD), and ischemic stroke using Mendelian randomization (MR). Methods: Using summary statistics from four recent, large genome-wide association studies of SA (n=523,366), AD (n=64,437), CAD (n=1,165,690), and stroke (n=1,308,460), we conducted bidirectional two-sample MR analyses. Our primary analytic method was fixed-effects inverse variance weighted MR; diagnostics tests and sensitivity analyses were conducted to verify the robustness of the results. Results: We identified a significant causal effect of SA on the risk of CAD (odds ratio (OR IVW ) =1.35 per log-odds increase in SA liability, 95% confidence interval (CI) =1.25-1.47) and stroke (OR IVW =1.13, 95% CI =1.01-1.25). These associations were somewhat attenuated after excluding single-nucleotide polymorphisms associated with body mass index (BMI) (OR IVW =1.26, 95% CI =1.15-1.39 for CAD risk; OR IVW =1.08, 95% CI =0.96-1.22 for stroke risk). SA was not causally associated with a higher risk of AD (OR IVW =1.14, 95% CI =0.91-1.43). We did not find causal effects of AD, CAD, or stroke on risk of SA. Conclusions: These results suggest that SA increased the risk of CAD, and the identified causal association with stroke risk may be confounded by BMI. Moreover, no causal effect of SA on AD risk was found. Future studies are warranted to investigate cardiovascular pathways between sleep disorders, including SA, and dementia.

Aircraft and road traffic noise, insulin resistance, and diabetes: The role of neighborhood socioeconomic status in San Diego County.

Evidence linking traffic noise to insulin resistance and diabetes is limited and unanswered questions remain regarding the potential effect modification by neighborhood socioeconomic status (nSES). We aimed to assess socioeconomic inequalities in noise exposure, whether road and aircraft noise exposures were associated with insulin resistance or diabetes, and whether nSES modified these relationships. Among the Community of Mine Study in San Diego County, road and aircraft noise exposure at enrollment was calculated based on the static (participant's administrative boundary, and circular buffer around participant homes), and dynamic (mobility data by global positioning system, GPS) spatio-temporal aggregation methods. Associations of noise with insulin resistance (HOMA-IR) or type 2 diabetes (T2DM) were quantified using generalized estimating equation models adjusted for sex, age, ethnicity, individual income, and air pollution (nitrogen dioxide) exposure. Additive interaction between noise and nSES was assessed. Among 573 participants (mean age 58.7 y), participants living in low nSES were exposed to higher levels of aircraft and road noise using noise level at the census tract, circular buffer, or Kernel Density Estimation (KDE) of GPS data. Participants exposed to road noise greater or equal to the median (53 dB(A)) at the census tract and living in low nSES had an increased level of insulin resistance (ß = 0.15, 95%CI: -0.04, 0.34) and higher odds of T2DM (Odds Ratio = 2.34, 95%CI: 1.12, 4.90). A positive additive interaction was found as participants living in low nSES had higher odds of T2DM. The impact of noise exposure on insulin resistance and T2DM differs substantially by nSES. Public health benefits of reducing exposure to road or aircraft noise would be larger in individuals living in low nSES.

Complaints of daytime sleepiness, insomnia, hypnotic use, and risk of dementia: a prospective cohort study in the elderly.

BACKGROUND: Sleep disturbances are common in elderly and occur frequently in dementia. The impact of excessive daytime sleepiness (EDS), insomnia complaints, sleep quality, and hypnotics on the risk of all-cause dementia, Alzheimer disease (AD), and dementia with vascular component (DVC) remains unclear, as does the association between sleep profile and plasma ß-amyloid levels. METHODS: Analyses were carried out on 6851 participants aged 65 years and over randomly recruited from three French cities and free of dementia at baseline. A structured interview and self-questionnaire assessed sleep complaints (EDS, insomnia complaints, sleep quality) and medications at baseline. Incident cases of dementia were diagnosed systematically over a 12-year period. Multivariate Cox models were used to estimate the risk of dementia associated with the sleep complaints considered individually and globally. Plasma ß-amyloid levels were measured by an xMAP-based assay technology in 984 subjects. RESULTS: After adjustment for socio-demographic characteristics, lifestyle, APOE-ε4, cardiovascular factors, and depressive status, EDS had a higher risk of all-cause dementia (HR = 1.21; 95%CI = [1.01-1.46]) and DVC (HR = 1.58; 95%CI = [1.07-2.32]) but not AD. Persistent use of hypnotics increased the risk for all-cause dementia, specifically AD (HR = 1.28; 95%CI = [1.04-1.58]), but not DVC. No association was found for insomnia complaints and sleep quality taken as individual factors or combined with EDS on the risk of dementia. No association was found between ß-amyloid, sleep complaints, and incident dementia. CONCLUSIONS: The results suggest a deleterious role of EDS and hypnotics on dementia. Further studies are required to elucidate the mechanisms involved in these associations and whether its management can prevent the risk of dementia.

Systematic assessment of autonomic symptoms in restless legs syndrome.

OBJECTIVES: To compare the clinical features of autonomic dysfunction using the SCOPA-AUT questionnaire in untreated patients with restless legs syndrome (RLS) with controls, to identify factors associated with more severe autonomic symptoms, and to assess the effect of medication in patients. METHODS: The SCOPA-AUT questionnaire that evaluates cardiovascular, gastrointestinal, urinary, thermoregulatory, pupillomotor, and sexual dysfunctions was completed by 409 consecutive untreated patients with RLS (54.1 ± 14.5 y.o; 265 women) and 331 controls (59.0 ± 17.0; 161 women). Clinical and polysomnographic data were assessed in all patients. A subgroup of 57 patients were evaluated a second time after treatment (mostly dopaminergic agonist) after an interval of 0.88 ± 1.42 year. RESULTS: Compared to controls, untreated patients with RLS were younger, more often women, obese, with increased cardiovascular diseases (CVD). The SCOPA-AUT total score was higher in patients than controls in unadjusted and adjusted models. Patients had more autonomic symptoms in all subdomains of the scale (except for sexual dysfunction in men). These results were confirmed in a subgroup of 259 cases and age-sex-matched controls. Female gender, obesity, RLS severity, diabetes mellitus, CVD, sleepiness, insomnia and depressive symptoms but neither periodic legs movements during sleep (PLMS) nor objective sleep parameters were associated with high scores. Despite RLS and PLMS improvement, medication did not change total and subdomain scores. CONCLUSIONS: Patients with RLS have frequent and large spectrum of autonomic symptoms, without effect of PLMS, sleep fragmentation and medication. These results suggest a global autonomic dysfunction in RLS that should be assessed more systematically in severe patients.