The UK Biobank Cohort Study enrolled over 500,000 participants aged 37-73 years at baseline from the general population (5.5% response rate) [13]. Briefly, between 2006 and 2010, participants attended one of 22 assessment centers in Scotland, England and Wales. [14, 15]. All participants completed a touchscreen questionnaire, had physical measurements taken, and provided blood, urine, and saliva samples at baseline. Among all UK Biobank participants, approximately half had linked primary care data and were included in this study (Additional file 1: Figure S1).
BP measured by device
Axivity AX3 triaxial wrist accelerometers were used to collect objective BP measurements from 103,686 UK Biobank participants between 2013 and 2015. The dominant wrist of each individual was worn for a period of 7 days at 100 Hz and pooled into periods. 5 s for analysis [16]. The 7,161 participants with insufficient wear time (<72 h of wear), missing data, or poor device calibration were excluded, leaving 96,525 participants with valid device-measured BP data. The mean time of use was 6.91 days and less than 20% of the participants used it < 6 days. More details about data collection and processing can be found elsewhere. [16].
Minutes per week (min/week) of light (LPA), moderate (MPA), and vigorous (VPA) physical activity were determined as the time between >30 milligravities (milligrams) and 125 milligrams>125 milligrams and 400 milligramsand >400 milligramsrespectively [17, 18], extrapolated from the fraction of the time spent over the total time of use. This assumes that the time spent in various PAs was similar in the measured and unmeasured period. Total physical activity was expressed as the total metabolic equivalent of the task (MET)-minutes/week taking into account both intensity and duration and was calculated as the time spent in LPA × 2 + MPA × 4 + VPA × 8, adapting the score recommendation of the International Physical Activity Questionnaire[[[[19].
affective disorders
Incident affective disorders were extracted from hospital and primary care records to ensure comprehensive verification. The dates and causes of hospital admissions were identified by register linkage with the Health Event Statistics (England and Wales) and the Scottish Morbidity Registers (Scotland). Details of the binding procedure can be found at http://content.digital.nhs.uk/services. The start of follow-up was the date all BP measurements measured with the device were completed. Participants with affective disorders prior to that date, based on retrospective record linkage, were excluded from analyzes (Additional file 1: Figure S1). Retrospective linked data going back to 2004 was used as a framework for quality and outcomes in primary care practices that were implemented that year. Hospital admission data were available through September 2021 in England, July 2021 in Scotland, and February 2018 in Wales. Using the International Classification of Diseases, 10th revision (ICD-10), affective disorders were defined as F30-F39 and F40-F44, depression as F32-33, and anxiety as F40-44.
Adjustment variables
Age, when PA data was collected, was determined from dates of birth and PA assessment. Ethnicity was self-reported and categorized as white, South Asian, black, Chinese, mixed ethnicity, and other. Area-based deprivation was derived from zip code of residence, using the Townsend score [20]. Educational level was based on self-report of the highest level of qualification. Sleep duration was self-reported in hours as there were no reliable objectively measured data. Smoking status was self-reported and categorized as never, former, or current smoker. Alcohol consumption was calculated based on self-reported frequency and volume of alcohol consumption. Dietary intake of fruits and vegetables, red meat, processed meat, and oily fish was self-reported. Trained nurses measured height and body weight during the initial evaluation. Body mass index (BMI) was calculated as (weight in kg)/(height in m)two. Long-term illnesses were self-reported as any long-term illness, disability, or nursing.
Statistic analysis
Descriptive characteristics by quartile of total PA are presented as means with standard deviation (SD) for continuous variables and frequencies with percentages for categorical variables.
Nonlinear associations between BP and incident affective disorders were investigated using fitted penalized cubic splines in Cox proportional hazards models. The penalized spline is chosen because it is not sensitive to the numbers and locations of nodes. [21]. In these analyses, PA variables were truncated to be between 2,000 and 12,000 MET-min/week for total PA, 300 and 3,600 min/week for MPA, 0 and 1,800 min/week for MPA, and 0 and 240 min/week. for VPA to ensure reliability at the end of the grooves. These truncation thresholds were approximately the 1st and 99th percentile for each of the variables. The reference points were the minimum of the truncated PA variables. An analysis was performed assuming linearity in the range where the associations appeared linear to extract easily interpretable estimates. This was replicated to use MET-minutes/week instead of time spent. Analyzes were adjusted for these confounders: age, gender, ethnicity, deprivation, education, sleep duration, smoking, alcohol intake, and dietary intake depending on the causal hypothesis shown in the Additional File. 1: Figure S1. For the LPA, MPA, and VPA analysis, the three PA variables were mutually adjusted. Because LPA, MPA, VPA, and sleep duration were included in the model, AP hazard indices could be interpreted as replacement of time spent sedentary by that AP. [22].
To illustrate the joint association of MPA and VPA with affective disorders, a risk matrix was constructed using the MPA and VPA categorized variables: 0–<150, 150–<300, 300–<600, and ≥600 min for MPA and 0–<15, 15–<45, 45–<75, and ≥75 min for VPA. These cut-off points were chosen based on current WHO Palestinian Authority recommendations. [23] and the forms of the associations, as well as the distributions. The least active were used as reference groups.
In addition, three sensitivity analyzes were performed. First, PAs did not adjust for each other like LPA and MPA (r = 0.42) and MPA and VPA (r = 0.49) were moderately correlated, which may lead to unstable HRs. Second, we further adjusted for BMI and long-term illnesses reported at baseline, as they could limit participants’ ability to perform PA, but could also be mediators (Additional file 1: Figure S1). Third, a 2-year historical analysis was performed that excluded participants who developed affective disorders in the first 2 years of follow-up (north = 795), in order to minimize the risk of reverse causality due to subclinical or preclinical mental health problems at baseline.
Population Preventable Fractions (PFPs) [24] were estimated to estimate the proportions of all incident affective disorders that could have been prevented if individuals in a specific PA category were as active as the most active group, assuming the association was causal. It should be noted that this study was unable to determine causality and this analysis only illustrates the relative importance of intensity-specific PA for the study population. All analyzes were performed using the “survival” packages in R 4.2.0. The proportional hazard assumption was tested using Schoenfeld residuals. A P-value below 0.05 was considered statistically significant.
ethical approval
UK Biobank was approved by the North West Multicentre Research Ethics Committee (Ref: eleven/NO/0382). Written informed consent was obtained from all participants.
