scholarly journals Associations Between Sedentary Behaviors and Cognitive Function: Cross-Sectional and Prospective Findings From the UK Biobank

2017 ◽  
Vol 187 (3) ◽  
pp. 441-454 ◽  
Author(s):  
Kishan Bakrania ◽  
Charlotte L Edwardson ◽  
Kamlesh Khunti ◽  
Stephan Bandelow ◽  
Melanie J Davies ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Uk Biobank ◽  
Sedentary Behaviors ◽  
Cross Sectional ◽  
The Uk

scholarly journals Consumption of Red Meat Is Negatively Associated with Cognitive Function: A Cross-Sectional Analysis of UK Biobank

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1510-1510
Author(s):  
Huifeng Zhang ◽  
Janet Cade ◽  
Laura Hadie
Keyword(s):  
Cognitive Function ◽  
Prospective Memory ◽  
Red Meat ◽  
Uk Biobank ◽  
Cross Sectional ◽  
Meat Intake ◽  
Visual Spatial ◽  
Additional Portion ◽  
The Uk ◽  
Sectional Analysis

Abstract Objectives In the largest study of its type, we tested for associations between red meat consumption and cognitive function using data from half a million participants enrolled into the UK Biobank cohort study. Methods Baseline data was obtained from the UK Biobank cohort, comprising half a million participants aged 37–73 years recruited between 2006 and 2010. The intake of red meat (frequency per week) was obtained using a self-reported food frequency questionnaire. Cognitive tests included the reaction-time (RT) test (reaction ability, N = 496, 695), fluid intelligence (FI) (reasoning ability, N = 165,467), the numeric memory test (short-term memory, N = 50,364), the pairs-matching (PM) test (visual-spatial memory, N = 482,650) and the prospective memory test (N = 171,509). Logistic and linear regression modelling was conducted with adjustment for potential confounders including age at recruitment, sex, ethnicity, Townsend deprivation index, smoking, alcohol, education, body mass index, physical activity level, sleeping hours, stroke history, and family history of dementia. Results Each additional portion per week of red-meat intake was associated with slower reaction time by 0.26 milliseconds (95% CI: 0.02, 0.50), lower FI score by 0.01 points (−0.02, −0.00), reduced numeric memory by 0.02 digits (−0.03, −0.01), and increased odds of incorrect prospective memory by 1% (0%, 2%). In men these associations were larger regarding the RT test (β = 0.54, [0.21, 0.87]), FI score (β = −0.02, [−0.03, −0.01]), and prospective memory (OR = 1.03, [1.01, 1.04]), while in women these were not significant. In terms of the PM test, a single additional portion of red-meat intake was associated with reduced incorrect matches by 0.004 pairs (−0.003, −0.006), both in men (β = −0.003, [−0.001, −0.005]) and women (β = −0.006, [−0.004, −0.008]). Conclusions In this cross-sectional analysis of the adult UK population, higher intake of red meat was associated with poorer cognitive function including reaction and reasoning ability, short-term and prospective memory especially among men; but not visual-spatial memory which showed a weak protective effect of red meat. Funding Sources The joint scholarship of University of Leeds and China Scholarship Council.

scholarly journals Is glycaemia associated with poorer brain health and risk of dementia? Cross sectional and follow-up analysis of the UK Biobank

2020 ◽  
Author(s):  
Victoria Garfield ◽  
Aliki-Eleni Farmaki ◽  
Sophie V. Eastwood ◽  
Rohini Mathur ◽  
Christopher T. Rentsch ◽  
...  
Keyword(s):  
Cognitive Function ◽  
White Matter ◽  
Cognitive Decline ◽  
Visual Memory ◽  
White Matter Hyperintensities ◽  
Undiagnosed Diabetes ◽  
Uk Biobank ◽  
Brain Health ◽  
Cross Sectional ◽  
The Uk

ABSTRACTObjectiveTo understand the relationship across the glycaemic spectrum with incident dementia, brain structure, and cognitive decline.Research Design and Methods: UK Biobank participants, aged 40-69 at recruitment. HbA1c and diabetes diagnosis define baseline glycaemic categories. Outcomes included incident vascular dementia (VD), Alzheimer’s dementia (AD), hippocampal volume (HV), white matter hyperintensity (WMH) volume, cognitive function and decline. All results are in reference to normoglycaemic individuals (HbA1c 35-<42 mmol/mol).Results210433 (47%), 15246 (3%), 3280 (0.7%), 20793 (5%) individuals had low HbA1c, pre-diabetes, undiagnosed diabetes, and known diabetes, respectively. Pre- and known diabetes markedly increased incident VD, (hazard ratios (HR) 1.51, 95%CI=1.01;2.25 and 1.96, 95%CI=1.49;2.58, respectively), less so AD (1.18, 0.92;1.52 and 1.13 0.95,1.33), adjusting for demographic and socioeconomic variables. For VD, multivariate adjustment, driven by antihypertensives, attenuated associations, HR 1.27, 0.84;1.91 and 1.45,1.07;1.97. Pre- and known diabetes conferred elevated risks of cognitive decline (odds ratio OR 1.53, 1.02;2.29 and 1.49, 1.02;2.18, respectively). People with pre-diabetes, undiagnosed and known diabetes had higher WMH volumes (4%, 30%, 3%, respectively), and lower HV (34.51 mm3, 11.73 mm3 and 61.13 mm3 respectively). People with low-normal HbA1c (<35 mmol/mol) had 5% lower WMH volume and 13.6 mm3 greater HV than normoglycaemic individuals.ConclusionsPre and known diabetes increase VD risks, less so AD. Excess VD risks were largely accounted for by treated hypertension. Hyperglycaemic states were associated with adverse, whereas low normal HbA1c was associated with favourable brain structure compared to normoglycaemic individuals. Our findings have implications for cardiovascular medication in hyperglycaemia for brain health.Type-2 diabetes and, more generally, hyperglycaemic states, have been associated with poorer cognitive function (such as learning and memory)(1), increased risk of dementia(2) and alterations in key brain structures, particularly the hippocampus(3). In contrast, recent evidence from a randomised crossover trial also suggests that, in people with diabetes, even modest hypoglycaemia has a detrimental effect on cognitive function(4). Thus, it is also important to explore how low levels of glycated haemoglobin (HbA1c) relate to these outcomes. A previous paper explored the cross sectional association between baseline diabetes and two cognition measures in the UK Biobank (reaction time and visual memory)(5). The authors found that diabetes was associated with poorer scores on the reaction time test, but paradoxically, better scores on the visual memory test. They did not explore other outcomes or lesser glycaemic states.Memory loss is the most conclusively reported adverse effect of hyperglycaemia on cognitive function(6). Hippocampal atrophy is a crucial feature of age-related memory loss and the hippocampus is particularly vulnerable to the neurotoxic consequences of diabetes(7). Evidence relating diabetes to the presence and progression of white matter hyperintensities is equivocal(8), but some research suggests that those with diabetes have greater volumes of white matter hyperintensities(9,10). Although there have been numerous studies in this area, the role of glycaemia in brain health across the entire glycaemic spectrum remains unclear, in particular no studies have investigated how lesser hyperglycaemic states relate to these outcomes, as most studies have focused on diagnosed diabetes only.Thus, the aim of this study was to investigate the associations between five glycaemic states across the entire spectrum (low HbA1c, normoglycaemia, pre-diabetes, undiagnosed diabetes and known diabetes) and Alzheimer’s dementia (AD) risk, vascular dementia (VD) risk, baseline cognitive function and cognitive decline, hippocampal volume, and white matter hyperintensities volume in the UK Biobank. We hypothesised that there would be a U-shaped association between glycaemia and our outcomes of interest, such that those with lower and higher HbA1c would have worse outcomes than those with normal glycaemic levels.

scholarly journals Is Environmental and Occupational Particulate Air Pollution Exposure Related to Type-2 Diabetes and Dementia? A Cross-Sectional Analysis of the UK Biobank

2020 ◽  
Vol 17 (24) ◽  
pp. 9581
Author(s):  
Eirini Dimakakou ◽  
Helinor J. Johnston ◽  
George Streftaris ◽  
John W. Cherrie
Keyword(s):  
Air Pollution ◽  
Occupational Exposure ◽  
Environmental Exposure ◽  
Uk Biobank ◽  
Job Exposure Matrix ◽  
Cross Sectional ◽  
Particulate Air Pollution ◽  
The Uk ◽  
Sectional Analysis

Human exposure to particulate air pollution (e.g., PM2.5) can lead to adverse health effects, with compelling evidence that it can increase morbidity and mortality from respiratory and cardiovascular disease. More recently, there has also been evidence that long-term environmental exposure to particulate air pollution is associated with type-2 diabetes mellitus (T2DM) and dementia. There are many occupations that may expose workers to airborne particles and that some exposures in the workplace are very similar to environmental particulate pollution. We conducted a cross-sectional analysis of the UK Biobank cohort to verify the association between environmental particulate air pollution (PM2.5) exposure and T2DM and dementia, and to investigate if occupational exposure to particulates that are similar to those found in environmental air pollution could increase the odds of developing these diseases. The UK Biobank dataset comprises of over 500,000 participants from all over the UK. Environmental exposure variables were used from the UK Biobank. To estimate occupational exposure both the UK Biobank’s data and information from a job exposure matrix, specifically developed for UK Biobank (Airborne Chemical Exposure–Job Exposure Matrix (ACE JEM)), were used. The outcome measures were participants with T2DM and dementia. In appropriately adjusted models, environmental exposure to PM2.5 was associated with an odds ratio (OR) of 1.02 (95% CI 1.00 to 1.03) per unit exposure for developing T2DM, while PM2.5 was associated with an odds ratio of 1.06 (95% CI 0.96 to 1.16) per unit exposure for developing dementia. These environmental results align with existing findings in the published literature. Five occupational exposures (dust, fumes, diesel, mineral, and biological dust in the most recent job estimated with the ACE JEM) were investigated and the risks for most exposures for T2DM and for all the exposures for dementia were not significantly increased in the adjusted models. This was confirmed in a subgroup of participants where a full occupational history was available allowed an estimate of workplace exposures. However, when not adjusting for gender, some of the associations become significant, which suggests that there might be a bias between the occupational assessments for men and women. The results of the present study do not provide clear evidence of an association between occupational exposure to particulate matter and T2DM or dementia.

scholarly journals Caffeinated Coffee and Tea Consumption, Genetic Variation and Cognitive Function in the UK Biobank

2020 ◽  
Vol 150 (8) ◽  
pp. 2164-2174
Author(s):  
Marilyn C Cornelis ◽  
Sandra Weintraub ◽  
Martha Clare Morris
Keyword(s):  
Genetic Variation ◽  
Cognitive Function ◽  
Poor Performance ◽  
Sociodemographic Factors ◽  
Caffeine Intake ◽  
Tea Consumption ◽  
Uk Biobank ◽  
Trail Making ◽  
Caffeine Metabolism ◽  
The Uk

ABSTRACT Background Coffee and tea are the major contributors of caffeine in the diet. Evidence points to the premise that caffeine may benefit cognition. Objective We examined the associations of habitual regular coffee or tea and caffeine intake with cognitive function whilst additionally accounting for genetic variation in caffeine metabolism. Methods We included white participants aged 37–73 y from the UK Biobank who provided biological samples and completed touchscreen questionnaires regarding sociodemographic factors, medical history, lifestyle, and diet. Habitual caffeine-containing coffee and tea intake was self-reported in cups/day and used to estimate caffeine intake. Between 97,369 and 445,786 participants with data also completed ≥1 of 7 self-administered cognitive functioning tests using a touchscreen system (2006–2010) or on home computers (2014). Multivariable regressions were used to examine the association between coffee, tea, or caffeine intake and cognition test scores. We also tested interactions between coffee, tea, or caffeine intake and a genetic-based caffeine-metabolism score (CMS) on cognitive function. Results After multivariable adjustment, reaction time, Pairs Matching, Trail Making test B, and symbol digit substitution, performance significantly decreased with consumption of 1 or more cups of coffee (all tests P-trend &lt; 0.0001). Tea consumption was associated with poor performance on all tests (P-trend &lt; 0.0001). No statistically significant CMS × tea, CMS × coffee, or CMS × caffeine interactions were observed. Conclusions Our findings, based on the participants of the UK Biobank, provide little support for habitual consumption of regular coffee or tea and caffeine in improving cognitive function. On the contrary, we observed decrements in performance with intakes of these beverages which may be a result of confounding. Whether habitual caffeine intake affects cognitive function therefore remains to be tested.

scholarly journals Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank

PLoS Medicine ◽  
2021 ◽  
Vol 18 (10) ◽  
pp. e1003782
Author(s):  
Michael Wainberg ◽  
Samuel E. Jones ◽  
Lindsay Melhuish Beaupre ◽  
Sean L. Hill ◽  
Daniel Felsky ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Sleep Duration ◽  
Sleep Efficiency ◽  
Risk Scores ◽  
Psychiatric Diagnoses ◽  
Uk Biobank ◽  
Major Depressive ◽  
Cross Sectional ◽  
Polygenic Risk ◽  
The Uk

Background Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort. Methods and findings In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures—bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration—were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = −0.11 (95% confidence interval −0.13 to −0.10, p = 3 × 10−56, FDR = 6 × 10−55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry. Conclusions In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.

scholarly journals The Association of Serum Lipid and Lipoprotein Levels with Total and Differential Leukocyte Counts: Results of a Cross-sectional and Longitudinal Analysis of the UK Biobank

2020 ◽  
Author(s):  
Bradley Tucker ◽  
Sonia Sawant ◽  
Hannah McDonald ◽  
Kerry-Anne Rye ◽  
Sanjay Patel ◽  
...  
Keyword(s):  
Longitudinal Analysis ◽  
Positive Association ◽  
Hdl Cholesterol ◽  
Uk Biobank ◽  
Cross Sectional ◽  
Lipoprotein A ◽  
Valid Data ◽  
Leukocyte Counts ◽  
The Uk ◽  
Relationship Of

Background and aims: There is some evidence of a cross-sectional, and possibly causal, relationship of lipid levels with leukocyte counts in mice and humans. This study investigates the cross-sectional and longitudinal relationship of blood lipid and lipoprotein levels with leukocyte counts in the UK Biobank cohort. Methods: The primary cross-sectional analysis included 417,132 participants with valid data on lipid measures and leukocyte counts. A subgroup analysis was performed in 333,668 participants with valid data on lipoprotein(a). The longitudinal analysis included 9,058 participants with valid baseline and follow-up data on lipid and lipoprotein levels and leukocyte counts. The association of lipid and lipoprotein levels with leukocyte counts was analysed by multivariable linear regression. Results: Several relationships were significant in both cross-sectional and longitudinal analysis. After adjustment for demographic, socioeconomic and other confounding factors a higher eosinophil count was associated with lower HDL cholesterol and apolipoproteinA-I concentration (p<0.001). Higher triglycerides levels were associated with higher total leukocyte, basophil, eosinophil, monocyte and neutrophil counts (all p<0.01). A higher lymphocyte count was associated with a higher apolipoprotein B level (p<0.001). In the longitudinal analysis lipoprotein(a) was inversely associated with basophil count in men but not women (p<0.001). Conclusion: Triglyceride levels demonstrate a robust positive association with total and differential leukocyte counts suggesting they may be directly involved in leuokogenesis. However, unlike in murine models, the remainder of these relationships are modest which suggests that cholesterol and lipoproteins are minimally involved in leukogenesis in humans.

scholarly journals Detecting retinal neurodegeneration in people with diabetes: Findings from the UK Biobank

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257836
Author(s):  
Roomasa Channa ◽  
Kyungmoo Lee ◽  
Kristen A. Staggers ◽  
Nitish Mehta ◽  
Sidra Zafar ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Glycated Hemoglobin ◽  
Retinal Thickness ◽  
Self Report ◽  
Inner Plexiform Layer ◽  
Uk Biobank ◽  
Fiber Layer ◽  
Cross Sectional ◽  
Retinal Neurodegeneration ◽  
The Uk

Importance Efforts are underway to incorporate retinal neurodegeneration in the diabetic retinopathy severity scale. However, there is no established measure to quantify diabetic retinal neurodegeneration (DRN). Objective We compared total retinal, macular retinal nerve fiber layer (mRNFL) and ganglion cell-inner plexiform layer (GC-IPL) thickness among participants with and without diabetes (DM) in a population-based cohort. Design/setting/participants Cross-sectional analysis, using the UK Biobank data resource. Separate general linear mixed models (GLMM) were created using DM and glycated hemoglobin as predictor variables for retinal thickness. Sub-analyses included comparing thickness measurements for patients with no/mild diabetic retinopathy (DR) and evaluating factors associated with retinal thickness in participants with and without diabetes. Factors found to be significantly associated with DM or thickness were included in a multiple GLMM. Exposure Diagnosis of DM was determined via self-report of diagnosis, medication use, DM-related complications or glycated hemoglobin level of ≥ 6.5%. Main outcomes and measures Total retinal, mRNFL and GC-IPL thickness. Results 74,422 participants (69,985 with no DM; 4,437 with DM) were included. Median age was 59 years, 46% were men and 92% were white. Participants with DM had lower total retinal thickness (-4.57 μm, 95% CI: -5.00, -4.14; p<0.001), GC-IPL thickness (-1.73 μm, 95% CI: -1.86, -1.59; p<0.001) and mRNFL thickness (-0.68 μm, 95% CI: -0.81, -0.54; p<0.001) compared to those without DM. After adjusting for co-variates, in the GLMM, total retinal thickness was 1.99 um lower (95% CI: -2.47, -1.50; p<0.001) and GC-IPL was 1.02 μm lower (95% CI: -1.18, -0.87; p<0.001) among those with DM compared to without. mRNFL was no longer significantly different (p = 0.369). GC-IPL remained significantly lower, after adjusting for co-variates, among those with DM compared to those without DM when including only participants with no/mild DR (-0.80 μm, 95% CI: -0.98, -0.62; p<0.001). Total retinal thickness decreased 0.40 μm (95% CI: -0.61, -0.20; p<0.001), mRNFL thickness increased 0.20 μm (95% CI: 0.14, 0.27; p<0.001) and GC-IPL decreased 0.26 μm (95% CI: -0.33, -0.20; p<0.001) per unit increase in A1c after adjusting for co-variates. Among participants with diabetes, age, DR grade, ethnicity, body mass index, glaucoma, spherical equivalent, and visual acuity were significantly associated with GC-IPL thickness. Conclusion GC-IPL was thinner among participants with DM, compared to without DM. This difference persisted after adjusting for confounding variables and when considering only those with no/mild DR. This confirms that GC-IPL thinning occurs early in DM and can serve as a useful marker of DRN.

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