Dataset Information

Sleep and cognitive performance: cross-sectional associations in the UK Biobank.

ABSTRACT:

Objective

The relationship between insomnia symptoms and cognitive performance is unclear, particularly at the population level. We conducted the largest examination of this association to date through analysis of the UK Biobank, a large population-based sample of adults aged 40-69 years. We also sought to determine associations between cognitive performance and self-reported chronotype, sleep medication use and sleep duration.

Methods

This cross-sectional, population-based study involved 477,529 participants, comprising 133,314 patients with frequent insomnia symptoms (age: 57.4 ± 7.7 years; 62.1% female) and 344,215 controls without insomnia symptoms (age: 56.1 ± 8.2 years; 52.0% female). Cognitive performance was assessed by a touchscreen test battery probing reasoning, basic reaction time, numeric memory, visual memory, and prospective memory. Adjusted models included relevant demographic, clinical, and sleep variables.

Results

Frequent insomnia symptoms were associated with cognitive impairment in unadjusted models; however, these effects were reversed after full adjustment, leaving those with frequent insomnia symptoms showing statistically better cognitive performance over those without. Relative to intermediate chronotype, evening chronotype was associated with superior task performance, while morning chronotype was associated with the poorest performance. Sleep medication use and both long (>9 h) and short (<7 h) sleep durations were associated with impaired performance.

Conclusions

Our results suggest that after adjustment for potential confounding variables, frequent insomnia symptoms may be associated with a small statistical advantage, which is unlikely to be clinically meaningful, on simple neurocognitive tasks. Further work is required to examine the mechanistic underpinnings of an apparent evening chronotype advantage in cognitive performance and the impairment associated with morning chronotype, sleep medication use, and sleep duration extremes.

SUBMITTER: Kyle SD

PROVIDER: S-EPMC5930168 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Publications

Sleep and cognitive performance: cross-sectional associations in the UK Biobank.

Kyle Simon D SD Sexton Claire E CE Feige Bernd B Luik Annemarie I AI Lane Jacqueline J Saxena Richa R Anderson Simon G SG Bechtold David A DA Dixon William W Little Max A MA Ray David D Riemann Dieter D Espie Colin A CA Rutter Martin K MK Spiegelhalder Kai K

Sleep medicine 20170714

<h4>Objective</h4>The relationship between insomnia symptoms and cognitive performance is unclear, particularly at the population level. We conducted the largest examination of this association to date through analysis of the UK Biobank, a large population-based sample of adults aged 40-69 years. We also sought to determine associations between cognitive performance and self-reported chronotype, sleep medication use and sleep duration.<h4>Methods</h4>This cross-sectional, population-based study ...[more]

PMID: 29031762

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Project description:BackgroundLong-term exposure to air pollution concentrations is known to be adversely associated with a broad range of single non-communicable diseases, but its role in multimorbidity has not been investigated in the UK. We aimed to assess associations between long-term air pollution exposure and multimorbidity status, severity, and patterns using the UK Biobank cohort.MethodsMultimorbidity status was calculated based on 41 physical and mental conditions. We assessed cross-sectional associations between annual modeled particulate matter (PM)2.5, PMcoarse, PM10, and nitrogen dioxide (NO2) concentrations (μg/m3-modeled to residential address) and multimorbidity status at the baseline assessment (2006-2010) in 364,144 people (mean age: 52.2 ± 8.1 years, 52.6% female). Air pollutants were categorized into quartiles to assess dose-response associations. Among those with multimorbidity (≥2 conditions; n = 156,395) we assessed associations between air pollutant exposure levels and multimorbidity severity and multimorbidity patterns, which were identified using exploratory factor analysis. Associations were explored using generalized linear models adjusted for sociodemographic, behavioral, and environmental indicators.ResultsHigher exposures to PM2.5, and NO2 were associated with multimorbidity status in a dose-dependent manner. These associations were strongest when we compared the highest air pollution quartile (quartile 4: Q4) with the lowest quartile (Q1) [PM2.5: adjusted odds ratio (adjOR) = 1.21 (95% CI = 1.18, 1.24); NO2: adjOR = 1.19 (95 % CI = 1.16, 1.23)]. We also observed dose-response associations between air pollutant exposures and multimorbidity severity scores. We identified 11 multimorbidity patterns. Air pollution was associated with several multimorbidity patterns with strongest associations (Q4 vs. Q1) observed for neurological (stroke, epilepsy, alcohol/substance dependency) [PM2.5: adjOR = 1.31 (95% CI = 1.14, 1.51); NO2: adjOR = 1.33 (95% CI = 1.11, 1.60)] and respiratory patterns (COPD, asthma) [PM2.5: adjOR = 1.24 (95% CI = 1.16, 1.33); NO2: adjOR = 1.26 (95% CI = 1.15, 1.38)].ConclusionsThis cross-sectional study provides evidence that exposure to air pollution might be associated with having multimorbid, multi-organ conditions. Longitudinal studies are needed to further explore these associations.

Project description:ObjectivesTo examine whether there are associations between active travel and markers of a healthy, low-carbon (HLC) diet (increased consumption of fruit and vegetables (FV), reduced consumption of red and processed meat (RPM)).DesignCross-sectional analysis of a cohort study.SettingsPopulation cohort of over 500 000 people recruited from 22 centres across the UK. Participants aged between 40 and 69 years were recruited between 2006 and 2010.Participants412 299 adults with complete data on travel mode use, consumption of FV and RPM, and sociodemographic covariates were included in the analysis.Exposure measuresMutually exclusive mode or mode combinations of travel (car, public transport, walking, cycling) for non-work and commuting journeys.Outcome measuresConsumption of FV measured as portions per day and RPM measured as frequency per week.ResultsEngaging in all types of active travel was positively associated with higher FV consumption and negatively associated with more frequent RPM consumption. Cycling exclusively or in combination with walking was most strongly associated with increased dietary consumption of FV and reduced consumption of RPM for both non-work and commuting journeys. Overall, the strongest associations were between non-work cycling and FV consumption (males: adjusted OR=2.18, 95% CI 2.06 to 2.30; females: adjusted OR=2.50, 95% CI 2.31 to 2.71) and non-work cycling and RPM consumption (males: adjusted OR=0.57, 95% CI 0.54 to 0.60; females: adjusted OR=0.54, 95% CI 0.50 to 0.59). Associations were generally similar for both commuting and non-work travel, and were robust to adjustment with sociodemographic and behavioural factors.ConclusionsThere are strong associations between engaging in active travel, particularly cycling, and HLC dietary consumption, suggesting that these HLC behaviours are related. Further research is needed to better understand the drivers and dynamics between these behaviours within individuals, and whether they share common underlying causes.

Dataset Information

Sleep and cognitive performance: cross-sectional associations in the UK Biobank.

Objective

Methods

Results

Conclusions

Publications

Sleep and cognitive performance: cross-sectional associations in the UK Biobank.

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