Association of genetic liability for psychiatric disorders with accelerometer-assessed physical activity in the UK Biobank.
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SUBMITTER: Dennison CA
PROVIDER: S-EPMC8508577 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo quantify the association between accelerometer-assessed physical activity and coronavirus disease 2019 (COVID-19) outcomes.MethodsData from 82,253 UK Biobank participants with accelerometer data (measured 2013-2015), complete covariate data, and linked COVID-19 data from March 16, 2020, to March 16, 2021, were included. Two outcomes were investigated: severe COVID-19 (positive test result from in-hospital setting or COVID-19 as primary cause of death) and nonsevere COVID-19 (positive test result from community setting). Logistic regressions were used to assess associations with moderate to vigorous physical activity (MVPA), total activity, and intensity gradient. A higher intensity gradient indicates a higher proportion of vigorous activity.ResultsAverage MVPA was 48.1 (32.7) min/d. Physical activity was associated with lower odds of severe COVID-19 (adjusted odds ratio per standard deviation increase: MVPA, 0.75 [95% CI, 0.67 to 0.85]; total, 0.83 [0.74 to 0.92]; intensity, 0.77 [0.70 to 0.86]), with stronger associations in women (MVPA, 0.63 [0.52 to 0.77]; total, 0.76 [0.64 to 0.90]; intensity, 0.63 [0.53 to 0.74]) than in men (MVPA, 0.84 [0.73 to 0.97]; total, 0.88 [0.77 to 1.01]; intensity, 0.88 [0.77 to 1.00]). In contrast, when mutually adjusted, total activity was associated with higher odds of a nonsevere infection (1.10 [1.04 to 1.16]), whereas the intensity gradient was associated with lower odds (0.91 [0.86 to 0.97]).ConclusionOdds of severe COVID-19 were approximately 25% lower per standard deviation (∼30 min/d) MVPA. A greater proportion of vigorous activity was associated with lower odds of severe and nonsevere infections. The association between total activity and higher odds of a nonsevere infection may be through greater community engagement and thus more exposure to the virus. Results support calls for public health messaging highlighting the potential of MVPA for reducing the odds of severe COVID-19.
| S-EPMC8376658 | biostudies-literature
Project description:Background Despite the well-established capacity of physical activity to reduce blood pressure, the associations between physical activity with cardiovascular disease (CVD) incidence and mortality in people living with hypertension are not well understood. We examine the dose-response associations of device-assessed physical activity with all-cause and CVD mortality and CVD incidence (total, stroke, and coronary heart disease) in adults with hypertension. Methods and Results This prospective study included data from 39 294 participants with hypertension in the UK Biobank study who had valid accelerometry data and for whom mortality and CVD followed-up data were available. We categorized moderate-to-vigorous physical activity and total physical activity volume into 4 categories based on the 10th, 50th, and 90th percentiles and used Cox regressions to estimate their associations with CVD mortality and incidence outcomes. Splines were used to assess the dose-response associations. During a median follow-up of 6.25 years (241 418 person-years), 1518 deaths (549 attributable to CVD) and 4933 CVD (fatal and nonfatal) incident events were registered. Compared with the lowest category of moderate-to-vigorous physical activity, the relative risks (hazard ratios and 95% CIs) of all-cause mortality for increasing categories were 0.53 (0.46-0.61), 0.41 (0.34-0.49), and 0.36 (0.26-0.49). We found associations of similar magnitude for total CVD incidence, stroke, and coronary heart disease; and for total physical activity volume across all outcomes. For all outcomes, there were linear or nearly linear inverse dose-response relationships with no evidence of harms with high levels of physical activity. Results were robust to removing participants who died within the first 2 years. Conclusions Our findings underscore the importance of physical activity for people living with hypertension and provide novel insights to support the development of physical activity guideline recommendations for this high-risk group.
| S-EPMC9075331 | biostudies-literature
Project description:BackgroundSleep 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 findingsIn 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.ConclusionsIn 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.
| S-EPMC8509859 | biostudies-literature
Project description:BackgroundSuicide is a major issue for global public health. Suicidality describes a broad spectrum of thoughts and behaviours, some of which are common in the general population. Although suicide results from a complex interaction of multiple social and psychological factors, predisposition to suicidality is at least partly genetic.MethodsOrdinal genome-wide association study of suicidality in the UK Biobank cohort comparing: 'no suicidality' controls (N = 83,557); 'thoughts that life was not worth living' (N = 21,063); 'ever contemplated self-harm' (N = 13,038); 'act of deliberate self-harm in the past' (N = 2498); and 'previous suicide attempt' (N = 2666).OutcomesWe identified three novel genome-wide significant loci for suicidality (on chromosomes nine, 11 and 13) and moderate-to-strong genetic correlations between suicidality and a range of psychiatric disorders, most notably depression (rg 0·81).InterpretationThese findings provide new information about genetic variants relating to increased risk of suicidal thoughts and behaviours. Future work should assess the extent to which polygenic risk scores for suicidality, in combination with non-genetic risk factors, may be useful for stratified approaches to suicide prevention at a population level. FUND: UKRI Innovation-HDR-UK Fellowship (MR/S003061/1). MRC Mental Health Data Pathfinder Award (MC_PC_17217). MRC Doctoral Training Programme Studentship at the University of Glasgow (MR/K501335/1). MRC Doctoral Training Programme Studentship at the Universities of Glasgow and Edinburgh. UKRI Innovation Fellowship (MR/R024774/1).
| S-EPMC6442001 | biostudies-literature
Project description:Psychiatric disorders are highly heritable and associated with a wide variety of social adversity and physical health problems. Using genetic liability (rather than phenotypic measures of disease) as a proxy for psychiatric disease risk can be a useful alternative for research questions that would traditionally require large cohort studies with long-term follow up. Here we conducted a hypothesis-free phenome-wide association study in about 330,000 participants from the UK Biobank to examine associations of polygenic risk scores (PRS) for five psychiatric disorders (major depression (MDD), bipolar disorder (BP), schizophrenia (SCZ), attention-deficit/ hyperactivity disorder (ADHD) and autism spectrum disorder (ASD)) with 23,004 outcomes in UK Biobank, using the open-source PHESANT software package. There was evidence after multiple testing (p<2.55x10-06) for associations of PRSs with 294 outcomes, most of them attributed to associations of PRSMDD (n = 167) and PRSSCZ (n = 157) with mental health factors. Among others, we found strong evidence of association of higher PRSADHD with 1.1 months younger age at first sexual intercourse [95% confidence interval [CI]: -1.25,-0.92] and a history of physical maltreatment; PRSASD with 0.01% lower erythrocyte distribution width [95%CI: -0.013,-0.007]; PRSSCZ with 0.95 lower odds of playing computer games [95%CI:0.95,0.96]; PRSMDD with a 0.12 points higher neuroticism score [95%CI:0.111,0.135] and PRSBP with 1.03 higher odds of having a university degree [95%CI:1.02,1.03]. We were able to show that genetic liabilities for five major psychiatric disorders associate with long-term aspects of adult life, including socio-demographic factors, mental and physical health. This is evident even in individuals from the general population who do not necessarily present with a psychiatric disorder diagnosis.
| S-EPMC7274459 | biostudies-literature
Project description:BACKGROUND:Associations between driving and physical-activity (PA) intensities are unclear, particularly among older adults. We estimated prospective associations of travel modes with total PA, sedentary time (ST), light-intensity PA (LPA), and moderate-to-vigorous intensity PA (MVPA) among adults aged 39-70?years. METHODS:We studied 90?810 UK Biobank participants (56.1?±?7.8?years). Driving status, specific travel modes (non-work travel; commuting to/from work) and covariates were assessed by questionnaire (2006-10). PA was assessed over 7?days by wrist-worn accelerometers (2013-15). We estimated associations using overall and age-stratified multivariable linear-regression models. RESULTS:Drivers accumulated 1.4% more total PA (95% confidence interval: 0.9, 1.9), 11.2?min/day less ST (-12.9, -9.5), 12.2?min/day more LPA (11.0, 13.3) and 0.9?min/day less MVPA (-1.6, -0.2) than non-drivers. Compared with car/motor-vehicle users, cyclists and walkers had the most optimal activity profiles followed by mixed-mode users (e.g. for non-work travel, cyclists: 10.7% more total PA, 9.0, 12.4; 20.5?min/day less ST, -26.0, -15.0; 14.5?min/day more MVPA, 12.0, 17.2; walkers: 4.2% more total PA, 3.5, 5.0; 7.5?min/day less ST -10.2, -4.9; 10.1?min/day more MVPA, 8.9, 11.3; mixed-mode users: 2.3% more total PA, 1.9, 2.7; 3.4?min/day less ST -4.8, -2.1; 4.9?min/day more MVPA, 4.3, 5.5). Some associations varied by age (p interaction?<?0.05), but these differences appeared small. CONCLUSIONS:Assessing specific travel modes rather than driving status alone may better capture variations in activity. Walking, cycling and, to a lesser degree, mixed-mode use are associated with more optimal activity profiles in adults of all ages.
| S-EPMC6693808 | biostudies-literature
Project description:BACKGROUND:Physical inactivity is associated with an increased risk of major chronic diseases, although uncertainty exists about which chronic diseases, themselves, might contribute to physical inactivity. The objective of this study was to compare the physical activity of those with chronic diseases to healthy individuals using an objective measure of physical activity. METHODS:We conducted a cross-sectional analysis of data from 96 706 participants aged 40 years or older from the UK Biobank prospective cohort study (2006-10). Diagnoses were identified through ICD 9 and 10 coding within hospital admission records and a cancer registry linked to UK Biobank participants. We extracted summary physical activity information from participants who wore a wrist-worn triaxial accelerometer for 7 days. Statistical analyses included computation of adjusted geometric means and means using general linear models. RESULTS:Participants with chronic disease undertook 9% or 61 minutes (95% confidence interval: 57.8-64.8) less moderate activity and 11% or 3 minutes (95% confidence interval: 2.7-3.3) less vigorous activity per week than individuals without chronic disease. Participants in every chronic-disease subgroup undertook less physical activity than those without chronic disease. Sixty-seven diagnoses within these subgroups were associated with lower moderate activity. CONCLUSIONS:The cross-sectional association of physical activity with chronic disease is broad. Given the substantial health benefits of being physically active, clinicians and policymakers should be aware that their patients with any chronic disease are at greater health risk from other diseases than anticipated because of their physical inactivity.
| S-EPMC6693885 | biostudies-literature
Project description:Many researchers are beginning to adopt the use of wrist-worn accelerometers to objectively measure personal activity levels. Data from these devices are often used to summarise such activity in terms of averages, variances, exceedances, and patterns within a profile. In this study, we report the development of a clustering utilising the whole activity profile. This was achieved using the robust clustering technique of k-medoids applied to an extensive data set of over 90,000 activity profiles, collected as part of the UK Biobank study. We identified nine distinct activity profiles in these data, which captured both the pattern of activity throughout a week and the intensity of the activity: "Active 9 to 5", "Active", "Morning Movers", "Get up and Active", "Live for the Weekend", "Moderates", "Leisurely 9 to 5", "Sedate" and "Inactive". These patterns are differentiated by sociodemographic, socioeconomic, and health and circadian rhythm data collected by UK Biobank. The utility of these findings are that they sit alongside existing summary measures of physical activity to provide a way to typify distinct activity patterns that may help to explain other health and morbidity outcomes, e.g., BMI or COVID-19. This research will be returned to the UK Biobank for other researchers to use.
| S-EPMC8709415 | biostudies-literature
Project description:BackgroundPsychiatric morbidities have been associated with a risk of severe infections through compromised immunity, health behaviours, or both. However, data are scarce on the association between multiple types of pre-pandemic psychiatric disorders and COVID-19. We aimed to assess the association between pre-pandemic psychiatric disorders and the subsequent risk of COVID-19 using UK Biobank.MethodsFor this cohort analysis, we included participants from UK Biobank who were registered in England and excluded individuals who died before Jan 31, 2020, (the start of the COVID-19 outbreak in the UK) or had withdrawn from UK Biobank. Participants diagnosed with a psychiatric disorder before Jan 31 were included in the group of individuals with pre-pandemic psychiatric disorders, whereas participants without a diagnosis before the outbreak were included in the group of individuals without pre-pandemic psychiatric disorders. We used the Public Health England dataset, UK Biobank hospital data, and death registers to collect data on COVID-19 cases. To examine the relationship between pre-pandemic psychiatric disorders and susceptibility to COVID-19, we used logistic regression models to estimate odds ratios (ORs), controlling for multiple confounders and somatic comorbidities. Key outcomes were all COVID-19, COVID-19 specifically diagnosed in inpatient care, and COVID-19-related deaths. ORs were also estimated separately for each psychiatric disorder and on the basis of the number of pre-pandemic psychiatric disorders. As a positive disease control, we repeated analyses for hospitalisation for other infections.FindingsWe included 421 014 UK Biobank participants in our study and assessed their COVID-19 status between Jan 31 and July 26, 2020. 50 809 participants were diagnosed with psychiatric disorders before the outbreak, while 370 205 participants had no psychiatric disorders. The mean age at outbreak was 67·80 years (SD 8·12). We observed an elevated risk of COVID-19 among individuals with pre-pandemic psychiatric disorders compared with that of individuals without such conditions. The fully adjusted ORs were 1·44 (95% CI 1·28-1·62) for All COVID-19 cases, 1·55 (1·34-1·78) for Inpatient COVID-19 cases, and 2·03 (1·59-2·59) for COVID-19-related deaths. We observed excess risk, defined as risk that increased with the number of pre-pandemic psychiatric disorders, across all diagnostic categories of pre-pandemic psychiatric disorders. We also observed an association between psychiatric disorders and elevated risk of hospitalisation due to other infections (OR 1·74, 95% CI 1·58-1·93).InterpretationOur findings suggest that pre-existing psychiatric disorders are associated with an increased risk of COVID-19. These findings underscore the need for surveillance of and care for populations with pre-existing psychiatric disorders during the COVID-19 pandemic.FundingNational Natural Science Foundation of China.
| S-EPMC7832159 | biostudies-literature
Project description:BackgroundHigher levels of physical activity (PA) are associated with a lower risk of cardiovascular disease (CVD). However, uncertainty exists on whether the inverse relationship between PA and incidence of CVD is greater at the highest levels of PA. Past studies have mostly relied on self-reported evidence from questionnaire-based PA, which is crude and cannot capture all PA undertaken. We investigated the association between accelerometer-measured moderate, vigorous, and total PA and incident CVD.Methods and findingsWe obtained accelerometer-measured moderate-intensity and vigorous-intensity physical activities and total volume of PA, over a 7-day period in 2013-2015, for 90,211 participants without prior or concurrent CVD in the UK Biobank cohort. Participants in the lowest category of total PA smoked more, had higher body mass index and C-reactive protein, and were diagnosed with hypertension. PA was associated with 3,617 incident CVD cases during 440,004 person-years of follow-up (median (interquartile range [IQR]): 5.2 (1.2) years) using Cox regression models. We found a linear dose-response relationship for PA, whether measured as moderate-intensity, vigorous-intensity, or as total volume, with risk of incident of CVD. Hazard ratios (HRs) and 95% confidence intervals for increasing quarters of the PA distribution relative to the lowest fourth were for moderate-intensity PA: 0.71 (0.65, 0.77), 0.59 (0.54, 0.65), and 0.46 (0.41, 0.51); for vigorous-intensity PA: 0.70 (0.64, 0.77), 0.54 (0.49,0.59), and 0.41 (0.37,0.46); and for total volume of PA: 0.73 (0.67, 0.79), 0.63 (0.57, 0.69), and 0.47 (0.43, 0.52). We took account of potential confounders but unmeasured confounding remains a possibility, and while removal of early deaths did not affect the estimated HRs, we cannot completely dismiss the likelihood that reverse causality has contributed to the findings. Another possible limitation of this work is the quantification of PA intensity-levels based on methods validated in relatively small studies.ConclusionsIn this study, we found no evidence of a threshold for the inverse association between objectively measured moderate, vigorous, and total PA with CVD. Our findings suggest that PA is not only associated with lower risk for of CVD, but the greatest benefit is seen for those who are active at the highest level.
| S-EPMC7802951 | biostudies-literature