Given the controversy about the impact of modifiable risk factors on mood and cognition in ageing, we sought to investigate the associations between cardio-vascular risk, mental health, cognitive performance and brain anatomy in mid- to old age. We analyzed a set of risk factors together with multi-parameter magnetic resonance imaging (MRI) in the CoLaus|PsyCoLaus cohort (n > 1200). Cardio-vascular risk was associated with differences in brain tissue properties - myelin, free tissue water, iron content - and regional brain volumes that we interpret in the context of micro-vascular hypoxic lesions and neurodegeneration. The interaction between clinical subtypes of major depressive disorder and cardio-vascular risk factors showed differential associations with brain structure depending on individuals' lifetime trajectory. There was a negative correlation between melancholic depression, anxiety and MRI markers of myelin and iron content in the hippocampus and anterior cingulate. Verbal memory and verbal fluency performance were positively correlated with left amygdala volumes. The concomitant analysis of brain morphometry and tissue properties allowed for a neuro-biological interpretation of the link between modifiable risk factors and brain health.

INTRODUCTION:Daytime sleepiness is highly prevalent in the general adult population and has been linked to an increased risk of workplace and vehicle accidents, lower professional performance and poorer health. Despite the established relationship between noise and daytime sleepiness, little research has explored the individual-level spatial distribution of noise-related sleep disturbances. We assessed the spatial dependence of daytime sleepiness and tested whether clusters of individuals exhibiting higher daytime sleepiness were characterized by higher nocturnal noise levels than other clusters. DESIGN AND METHODS:Population-based cross-sectional study, in the city of Lausanne, Switzerland. Sleepiness was measured using the Epworth Sleepiness Scale (ESS) for 3697 georeferenced individuals from the CoLaus|PsyCoLaus cohort (period = 2009-2012). We used the sonBASE georeferenced database produced by the Swiss Federal Office for the Environment to characterize nighttime road traffic noise exposure throughout the city. We used the GeoDa software program to calculate the Getis-Ord Gi* statistics for unadjusted and adjusted ESS in order to detect spatial clusters of high and low ESS values. Modeled nighttime noise exposure from road and rail traffic was compared across ESS clusters. RESULTS:Daytime sleepiness was not randomly distributed and showed a significant spatial dependence. The median nighttime traffic noise exposure was significantly different across the three ESS Getis cluster classes (p < 0.001). The mean nighttime noise exposure in the high ESS cluster class was 47.6, dB(A) 5.2 dB(A) higher than in low clusters (p < 0.001) and 2.1 dB(A) higher than in the neutral class (p < 0.001). These associations were independent of major potential confounders including body mass index and neighborhood income level. CONCLUSIONS:Clusters of higher daytime sleepiness in adults are associated with higher median nighttime noise levels. The identification of these clusters can guide tailored public health interventions.

Previous research found an association between sleep disturbances and cognitive deficits on the one hand, and between increased cortisol levels and poor cognitive performance on the other hand. We hypothesized that cortisol may, at least partially, mediate the link between sleep disturbances and cognitive impairment (CI). We analyzed data from 440 nondemented subjects aged ≥65 years (72.4 ± 4.5 years old, 55.7% women) participating at the population-based CoLaus/PsyCoLaus study, who underwent cognitive evaluation, complete polysomnography and cortisol measures during the day. Subjects with CI (N = 207, 47.05% of the sample) had lower sleep efficiency, less deep sleep (stage N3) and rapid eye movement sleep, and higher apnea/hypopnea index and oxygen desaturation index. After adjustment for possible confounders, oxygen desaturation index (≥4% and ≥6% per hour of sleep) were significantly associated with impaired cognitive performance. The results of Sobel's test for mediation using the regressions between the sleep-related variables and cortisol values, and between the cortisol and the Clinical Dementia Rating score were not significant (all p > 0.05). Our data suggest that sleep-disordered breathing is associated with CI, but that this association is not mediated by increased diurnal cortisol levels.

Sleep-disordered breathing is a common condition, related to a higher cardiometabolic and neurocognitive risk. The main risk factors for sleep-disordered breathing include obesity, craniofacial characteristics, male sex and age. However, some studies have suggested that adverse socioeconomic circumstances and lifestyle-related behaviours such as smoking and alcohol use, may also be risk factors for sleep-disordered breathing. Here, we investigate the associations between socioeconomic status and sleep-disordered breathing, as measured by sleep apnea-hypopnea and oxygen desaturation indexes. Furthermore, we assess whether these associations are explained by lifestyle-related factors (smoking, sedentary behaviour, alcohol use and body mass index [BMI]). We used data from the CoLaus|HypnoLaus study, a population-based study including 2162 participants from Lausanne (Switzerland). Socioeconomic status was measured through occupation and education. Sleep-disordered breathing was assessed through polysomnography and measured using the apnea-hypopnea index (AHI: number of apnea/hypopnea events/hr: ≥15/≥30 events), and the ≥3% oxygen desaturation index (ODI: number of oxygen desaturation events/hr: ≥15/≥30 events). Lower occupation and education were associated with higher AHI and ODI (occupation: AHI30, odds ratio (OR) = 1.88, 95% confidence interval (CI) [1.07; 3.31]; ODI30, OR = 2.29, 95% CI [1.19; 4.39]; education: AHI30, OR = 1.21, 95% CI [0.85; 1.72]; ODI30, OR = 1.26, 95% CI [0.83; 1.91]). BMI was associated with socioeconomic status and AHI/ODI, and contributed to the socioeconomic gradient in SDB, with mediation estimates ranging between 43% and 78%. In this Swiss population-based study, we found that low socioeconomic status is a risk factor for sleep-disordered breathing, and that these associations are partly explained by BMI. These findings provide a better understanding of the mechanisms underlying social differences in sleep-disordered breathing and may help implement policies for identifying high-risk profiles for this disorder.

To determine the prevalence and clinical associations of respiratory effort-related arousals (RERA) in a general population sample. A total of 2,162 participants (51.2

BACKGROUND:Since the clinical presentation of obstructive sleep apnea syndrome (OSAS) shares common features with major depressive (MDE), the screening of OSAS is challenging in this population. The aim of this study was to assess the effectiveness of the NoSAS score in predicting the presence of OSAS among participants with current MDE and to compare it with the performance of existing screening tools. METHODS:A random sample of the population-based cohort CoLaus (Lausanne, Switzerland) underwent a psychiatric evaluation (PsyCoLaus) and a complete polysomnography at home (HypnoLaus). The effectiveness of the NoSAS score in detecting the risk of significant OSAS among current MDE participants was assessed and compared with STOP-BANG and Berlin scores. RESULTS:Among the 1761 subjects (58,75 ± 11y.o.; 47,8%men) who underwent polysomnography, significant OSAS was present in 24.0% with and 26.1% without current MDE. Using a threshold of ≥ 8 points, the NoSAS score identified OSAS in MDE participants with a sensitivity of 0.79, a specificity of 0.66, a negative predictive value of 0.91, and a positive predictive value of 0.41. The area under the ROC curve was 0.72 for NoSAS, 0.66 for STOP-BANG and 0.69 for the Berlin score (NS). LIMITATIONS:Only 44% of the PsyCoLaus participants had a polysomnography. The studied population was mainly of Caucasian ancestry and above 40 years of age. CONCLUSIONS:This is the first study assessing the performance of screening tools for OSAS in MDE. The NoSAS score is a simple and efficient screening tool for OSAS in this population, and may be a helpful instrument for clinicians.

ObjectivePeriodic limb movements during sleep (PLMS) are sleep phenomena characterized by periodic episodes of repetitive stereotyped limb movements. The aim of this study was to describe the prevalence and determinants of PLMS in a middle to older aged general population.MethodsData from 2,162 subjects (51.2% women, mean age = 58.4 ± 11.1 years) participating in a population‐based study (HypnoLaus, Lausanne, Switzerland) were collected. Assessments included laboratory tests, sociodemographic data, personal and treatment history, and full polysomnography at home. PLMS index (PLMSI) was determined, and PLMSI > 15/h was considered as significant.ResultsPrevalence of PLMSI > 15/h was 28.6% (31.3% in men, 26% in women). Compared to subjects with PLMSI ≤ 15/h, subjects with PLMSI > 15/h were older (p < 0.001), were predominantly males (p = 0.007), had a higher proportion of restless legs syndrome (RLS; p < 0.001), had a higher body mass index (p = 0.001), and had a lower mean glomerular filtration rate (p < 0.001). Subjects with PLMSI > 15/h also had a higher prevalence of diabetes, hypertension, and beta‐blocker or hypnotic treatments. The prevalence of antidepressant use was higher, but not statistically significant (p = 0.07). Single nucleotide polymorphisms (SNPs) within BTBD9 (rs3923809), TOX3 (rs3104788), and MEIS1 (rs2300478) genes were significantly associated with PLSMI > 15/h. Conversely, mean hemoglobin and ferritin levels were similar in both groups. In the multivariate analysis, age, male gender, antidepressant intake, RLS, and rs3923809, rs3104788, and rs2300478 SNPs were independently associated with PLMSI > 15/h.InterpretationPLMS are highly prevalent in our middle‐aged European population. Age, male gender, RLS, antidepressant treatment, and specific BTBD9, TOX3, and MEIS1 SNP distribution are independent predictors of PLMSI > 15/h. ANN NEUROL 2016;79:464–474

INTRODUCTION:The aim of this study was to evaluate if there is a significant effect of lunar phases on subjective and objective sleep variables in the general population. METHODS:A total of 2125 individuals (51.2% women, age 58.8 ± 11.2 years) participating in a population-based cohort study underwent a complete polysomnography (PSG) at home. Subjective sleep quality was evaluated by a self-rating scale. Sleep electroencephalography (EEG) spectral analysis was performed in 759 participants without significant sleep disorders. Salivary cortisol levels were assessed at awakening, 30 min after awakening, at 11 am, and at 8 pm. Lunar phases were grouped into full moon (FM), waxing/waning moon (WM), and new moon (NM). RESULTS:Overall, there was no significant difference between lunar phases with regard to subjective sleep quality. We found only a nonsignificant (p = 0.08) trend toward a better sleep quality during the NM phase. Objective sleep duration was not different between phases (FM: 398 ± 3 min, WM: 402 ± 3 min, NM: 403 ± 3 min; p = 0.31). No difference was found with regard to other PSG-derived parameters, EEG spectral analysis, or in diurnal cortisol levels. When considering only subjects with apnea/hypopnea index of <15/h and periodic leg movements index of <15/h, we found a trend toward shorter total sleep time during FM (FM: 402 ± 4, WM: 407 ± 4, NM: 415 ± 4 min; p = 0.06) and shorter-stage N2 duration (FM: 178 ± 3, WM: 182 ± 3, NM: 188 ± 3 min; p = 0.05). CONCLUSION:Our large population-based study provides no evidence of a significant effect of lunar phases on human sleep.

STUDY OBJECTIVES To evaluate the association between objective sleep measures and metabolic syndrome (MS), hypertension, diabetes, and obesity. DESIGN Cross-sectional study. SETTING General population sample. PARTICIPANTS There were 2,162 patients (51.2% women, mean age 58.4 ± 11.1). INTERVENTIONS Patients were evaluated for hypertension, diabetes, overweight/obesity, and MS, and underwent a full polysomnography (PSG). MEASUREMENTS AND RESULTS PSG measured variables included: total sleep time (TST), percentage and time spent in slow wave sleep (SWS) and in rapid eye movement (REM) sleep, sleep efficiency and arousal index (ArI). In univariate analyses, MS was associated with decreased TST, SWS, REM sleep, and sleep efficiency, and increased ArI. After adjustment for age, sex, smoking, alcohol, physical activity, drugs that affect sleep and depression, the ArI remained significantly higher, but the difference disappeared in patients without significant sleep disordered breathing (SDB). Differences in sleep structure were also found according to the presence or absence of hypertension, diabetes, and overweight/obesity in univariate analysis. However, these differences were attenuated after multivariate adjustment and after excluding subjects with significant SDB. CONCLUSIONS In this population-based sample we found significant associations between sleep structure and MS, hypertension, diabetes, and obesity. However, these associations were cancelled after multivariate adjustment. We conclude that normal variations in sleep contribute little if any to MS and associated disorders.

Inflammation is one possible mechanism underlying the associations between mental disorders and cardiovascular diseases (CVD). However, studies on mental disorders and inflammation have yielded inconsistent results and the majority did not adjust for potential confounding factors. We examined the associations of several pro-inflammatory cytokines (IL-1β, IL-6 and TNF-α) and high sensitive C-reactive protein (hsCRP) with lifetime and current mood, anxiety and substance use disorders (SUD), while adjusting for multiple covariates. The sample included 3719 subjects, randomly selected from the general population, who underwent thorough somatic and psychiatric evaluations. Psychiatric diagnoses were made with a semi-structured interview. Major depressive disorder was subtyped into "atypical", "melancholic", "combined atypical-melancholic" and "unspecified". Associations between inflammatory markers and psychiatric diagnoses were assessed using multiple linear and logistic regression models. Lifetime bipolar disorders and atypical depression were associated with increased levels of hsCRP, but not after multivariate adjustment. After multivariate adjustment, SUD remained associated with increased hsCRP levels in men (β = 0.13 (95% CI: 0.03,0.23)) but not in women. After multivariate adjustment, lifetime combined and unspecified depression were associated with decreased levels of IL-6 (β = -0.27 (-0.51,-0.02); β = -0.19 (-0.34,-0.05), respectively) and TNF-α (β = -0.16 (-0.30,-0.01); β = -0.10 (-0.19,-0.02), respectively), whereas current combined and unspecified depression were associated with decreased levels of hsCRP (β = -0.20 (-0.39,-0.02); β = -0.12 (-0.24,-0.01), respectively). Our data suggest that the significant associations between increased hsCRP levels and mood disorders are mainly attributable to the effects of comorbid disorders, medication as well as behavioral and physical CVRFs.