To develop and validate an algorithm that provides a continuous estimate of sleep depth from the electroencephalogram (EEG).
Retrospective analysis of polysomnograms.
Research laboratory.
114 ...patients who underwent clinical polysomnography in sleep centers at the University of Manitoba (n = 58) and the University of Calgary (n = 56).
None.
Power spectrum of EEG was determined in 3-second epochs and divided into delta, theta, alpha-sigma, and beta frequency bands. The range of powers in each band was divided into 10 aliquots. EEG patterns were assigned a 4-digit number that reflects the relative power in the 4 frequency ranges (10,000 possible patterns). Probability of each pattern occurring in 30-s epochs staged awake was determined, resulting in a continuous probability value from 0% to 100%. This was divided by 40 (% of epochs staged awake) producing the odds ratio product (ORP), with a range of 0-2.5. In validation testing, average ORP decreased progressively as EEG progressed from wakefulness (2.19 ± 0.29) to stage N3 (0.13 ± 0.05). ORP < 1.0 predicted sleep and ORP > 2.0 predicted wakefulness in > 95% of 30-s epochs. Epochs with intermediate ORP occurred in unstable sleep with a high arousal index (> 70/h) and were subject to much interrater scoring variability. There was an excellent correlation (r(2) = 0.98) between ORP in current 30-s epochs and the likelihood of arousal or awakening occurring in the next 30-s epoch.
Our results support the use of the odds ratio product (ORP) as a continuous measure of sleep depth.
The objective of this study was to evaluate the association between spinal cord injury (SCI) and type 2 diabetes in a large representative sample and to determine whether an association exists ...irrespective of known risk factors for type 2 diabetes.
Data were obtained on 60,678 respondents to the Statistics Canada 2010 Cycle of the cross-sectional Canadian Community Health Survey. Multivariable logistic regression, incorporating adjustment for confounders and probability weights to account for the Canadian Community Health Survey sampling method, was conducted to quantify this association.
After adjustment for both sex and age, SCI was associated with a significant increased odds of type 2 diabetes (adjusted odds ratio = 1.66, 95% confidence interval 1.16-2.36). These heightened odds persisted after additional adjustment for smoking status, hypertension status, body mass index, daily physical activity, alcohol intake, and daily consumption of fruits and vegetables (fully adjusted odds ratio = 2.45, 95% confidence interval 1.34-4.47).
There is a strong association between SCI and type 2 diabetes, which is not explained by known risk factors for type 2 diabetes.
The authors examined the prospective relationship between physical activity and incident depression and explored potential moderators.
Prospective cohort studies evaluating incident depression were ...searched from database inception through Oct. 18, 2017, on PubMed, PsycINFO, Embase, and SPORTDiscus. Demographic and clinical data, data on physical activity and depression assessments, and odds ratios, relative risks, and hazard ratios with 95% confidence intervals were extracted. Random-effects meta-analyses were conducted, and the potential sources of heterogeneity were explored. Methodological quality was assessed using the Newcastle-Ottawa Scale.
A total of 49 unique prospective studies (N=266,939; median proportion of males across studies, 47%) were followed up for 1,837,794 person-years. Compared with people with low levels of physical activity, those with high levels had lower odds of developing depression (adjusted odds ratio=0.83, 95% CI=0.79, 0.88; I
=0.00). Furthermore, physical activity had a protective effect against the emergence of depression in youths (adjusted odds ratio=0.90, 95% CI=0.83, 0.98), in adults (adjusted odds ratio=0.78, 95% CI=0.70, 0.87), and in elderly persons (adjusted odds ratio=0.79, 95% CI=0.72, 0.86). Protective effects against depression were found across geographical regions, with adjusted odds ratios ranging from 0.65 to 0.84 in Asia, Europe, North America, and Oceania, and against increased incidence of positive screen for depressive symptoms (adjusted odds ratio=0.84, 95% CI=0.79, 0.89) or major depression diagnosis (adjusted odds ratio=0.86, 95% CI=0.75, 0.98). No moderators were identified. Results were consistent for unadjusted odds ratios and for adjusted and unadjusted relative risks/hazard ratios. Overall study quality was moderate to high (Newcastle-Ottawa Scale score, 6.3). Although significant publication bias was found, adjusting for this did not change the magnitude of the associations.
Available evidence supports the notion that physical activity can confer protection against the emergence of depression regardless of age and geographical region.
The logistic regression model is frequently used in epidemiologic studies, yielding odds ratio or relative risk interpretations. Inspired by the theory of linear normal models, the logistic ...regression model has been extended to allow for correlated responses by introducing random effects. However, the model does not inherit the interpretational features of the normal model. In this paper, the authors argue that the existing measures are unsatisfactory (and some of them are even improper) when quantifying results from multilevel logistic regression analyses. The authors suggest a measure of heterogeneity, the median odds ratio, that quantifies cluster heterogeneity and facilitates a direct comparison between covariate effects and the magnitude of heterogeneity in terms of well-known odds ratios. Quantifying cluster-level covariates in a meaningful way is a challenge in multilevel logistic regression. For this purpose, the authors propose an odds ratio measure, the interval odds ratio, that takes these difficulties into account. The authors demonstrate the two measures by investigating heterogeneity between neighborhoods and effects of neighborhood-level covariates in two examples—public physician visits and ischemic heart disease hospitalizations—using 1999 data on 11,312 men aged 45–85 years in Malmö, Sweden.
Mendelian randomization investigations are becoming more powerful and simpler to perform, due to the increasing size and coverage of genome-wide association studies and the increasing availability of ...summarized data on genetic associations with risk factors and disease outcomes. However, when using multiple genetic variants from different gene regions in a Mendelian randomization analysis, it is highly implausible that all the genetic variants satisfy the instrumental variable assumptions. This means that a simple instrumental variable analysis alone should not be relied on to give a causal conclusion. In this article, we discuss a range of sensitivity analyses that will either support or question the validity of causal inference from a Mendelian randomization analysis with multiple genetic variants. We focus on sensitivity analyses of greatest practical relevance for ensuring robust causal inferences, and those that can be undertaken using summarized data. Aside from cases in which the justification of the instrumental variable assumptions is supported by strong biological understanding, a Mendelian randomization analysis in which no assessment of the robustness of the findings to violations of the instrumental variable assumptions has been made should be viewed as speculative and incomplete. In particular, Mendelian randomization investigations with large numbers of genetic variants without such sensitivity analyses should be treated with skepticism.
Evidence is emerging that poor mental health is associated with the environmental exposures of surrounding green, air pollution and traffic noise. Most studies have evaluated only associations of ...single exposures with poor mental health.
To evaluate associations of combined exposure to surrounding green, air pollution and traffic noise with poor mental health.
In this cross-sectional study, we linked data from a Dutch national health survey among 387,195 adults including questions about psychological distress, based on the Kessler 10 scale, to an external database on registered prescriptions of anxiolytics, hypnotics & sedatives and antidepressants. We added data on residential surrounding green in a 300 m and a 1000 m buffer based on the Normalized Difference Vegetation Index (NDVI) and a land-use database (TOP10NL), modeled annual average air pollutant concentrations (including particulate matter (PM10, PM2.5), and nitrogen dioxide (NO2)) and modeled road- and rail-traffic noise (Lden and Lnight) to the survey. We used logistic regression to analyze associations of surrounding green, air pollution and traffic noise exposure with poor mental health.
In single exposure models, surrounding green was inversely associated with poor mental health. Air pollution was positively associated with poor mental health. Road-traffic noise was only positively associated with prescription of anxiolytics, while rail-traffic noise was only positively associated with psychological distress. For prescription of anxiolytics, we found an odds ratio OR of 0.88 (95% CI: 0.85, 0.92) per interquartile range IQR increase in NDVI within 300 m, an OR of 1.14 (95% CI: 1.10, 1.19) per IQR increase in NO2 and an OR of 1.07 (95% CI: 1.03, 1.11) per IQR increase in road-traffic noise. In multi exposure analyses, associations with surrounding green and air pollution generally remained but attenuated. Joint odds ratios JOR, based on the Cumulative Risk Index (CRI) method, of combined exposure to air pollution, traffic noise and decreased surrounding green were higher than the ORs of single exposure models. Associations of environmental exposures with poor mental health differed somewhat by age.
Studies including only one of these three correlated exposures may overestimate the influence of poor mental health attributed to the studied exposure, while underestimating the influence of combined environmental exposures.
•Surrounding green was inversely associated with poor mental health.•Air pollution and to a limited extent traffic noise were positively associated with poor mental health.•In multi exposure models, associations with surrounding green and air pollution attenuated, but remained significant.•The most consistent associations were observed with prescription of anxiolytics and prescription of hypnotics & sedatives.•Joint odds ratios of combined exposure were higher than the ORs of single exposure models.
To investigate the effectiveness of a school-based program promoting outdoor activities in Taiwan for myopia prevention and to identify protective light intensities.
Multi-area, cluster-randomized ...intervention controlled trial.
A total 693 grade 1 schoolchildren in 16 schools participated. Two hundred sixty-seven schoolchildren were in the intervention group and 426 were in the control group.
Initially, 24 schools were randomized into the intervention and control groups, but 5 and 3 schools in the intervention and control groups, respectively, withdrew before enrollment. A school-based Recess Outside Classroom Trial was implemented in the intervention group, in which schoolchildren were encouraged to go outdoors for up to 11 hours weekly. Data collection included eye examinations, cycloplegic refraction, noncontact axial length measurements, light meter recorders, diary logs, and questionnaires.
Change in spherical equivalent and axial length after 1 year and the intensity and duration of outdoor light exposures.
The intervention group showed significantly less myopic shift and axial elongation compared with the control group (0.35 diopter D vs. 0.47 D; 0.28 vs. 0.33 mm; P = 0.002 and P = 0.003) and a 54% lower risk of rapid myopia progression (odds ratio, 0.46; 95% confidence interval CI, 0.28-0.77; P = 0.003). The myopic protective effects were significant in both nonmyopic and myopic children compared with controls. Regarding spending outdoor time of at least 11 hours weekly with exposure to 1000 lux or more of light, the intervention group had significantly more participants compared with the control group (49.79% vs. 22.73%; P < 0.001). Schoolchildren with longer outdoor time in school (≥200 minutes) showed significantly less myopic shift (measured by light meters; ≥1000 lux: 0.14 D; 95% CI, 0.02-0.27; P = 0.02; ≥3000 lux: 0.16 D; 95% CI, 0.002-0.32; P = 0.048).
The school-based outdoor promotion program effectively reduced the myopia change in both nonmyopic and myopic children. Outdoor activities with strong sunlight exposure may not be necessary for myopia prevention. Relatively lower outdoor light intensity activity with longer time outdoors, such as in hallways or under trees, also can be considered.
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