Diurnal Physical Activity Patterns across Ages in a Large UK Based Cohort: The UK Biobank Study

Wrobel, Julia; Muschelli, John; Leroux, Andrew

doi:10.3390/s21041545

Cited by 8 publications

(6 citation statements)

References 38 publications

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“…These included studies into: functional fitness, measured through walking pace [12] or grip strength [13]; cardio vascular disease [14,15] and heart failure [16]; cancer generally [17] and specifically breast cancer [18]; mental health [19] including psychiatric conditions [20,21] and depression and anxiety [22]; mortality generally [23,24], but also concentrating on volume and intensity of activity [25,26]; sleep quality [27,28] and the relationship of sleep to morbidity outcomes [6,29]; and circadian rhythms [30,31]. Outside of health, a range of studies have been reported that correlate these objectively measured physical activity levels with other observations and outcomes such as environmental characteristics [32], travel [33], and activity [34,35].…”

Section: Introductionmentioning

confidence: 99%

Clustering Accelerometer Activity Patterns from the UK Biobank Cohort

Clark

Lomax

Morris

et al. 2021

Sensors

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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.

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Section: Introductionmentioning

confidence: 99%

Clustering Accelerometer Activity Patterns from the UK Biobank Cohort

Clark

Lomax

Morris

et al. 2021

Sensors

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“…49,50 A few recent research studies have explored the association between all-cause mortality and diurnal patterns of PA in NHANES 2003-2006 33 or in describing variations for different age group or other medical conditions. [51][52][53] Our finding is among the first to establish an association between daily patterns of PA and long-term cancer survival 54,55,27 after adjusting for age and other confounders, which could be very important for designing time-of-day specific PA interventions.…”

Section: Variablesmentioning

confidence: 69%

Functional proportional hazards mixture cure model with applications in cancer mortality in NHANES and post ICU recovery

Ghosal,

Matabuena,

Zhang

2023

Stat Methods Med Res

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We develop a functional proportional hazards mixture cure model with scalar and functional covariates measured at the baseline. The mixture cure model, useful in studying populations with a cure fraction of a particular event of interest is extended to functional data. We employ the expectation–maximization algorithm and develop a semiparametric penalized spline-based approach to estimate the dynamic functional coefficients of the incidence and the latency part. The proposed method is computationally efficient and simultaneously incorporates smoothness in the estimated functional coefficients via roughness penalty. Simulation studies illustrate a satisfactory performance of the proposed method in accurately estimating the model parameters and the baseline survival function. Finally, the clinical potential of the model is demonstrated in two real data examples that incorporate rich high-dimensional biomedical signals as functional covariates measured at the baseline and constitute novel domains to apply cure survival models in contemporary medical situations. In particular, we analyze (i) minute-by-minute physical activity data from the National Health And Nutrition Examination Survey 2003–2006 to study the association between diurnal patterns of physical activity at baseline and all cancer mortality through 2019 while adjusting for other biological factors; (ii) the impact of daily functional measures of disease severity collected in the intensive care unit on post intensive care unit recovery and mortality event. Our findings provide novel epidemiological insights into the association between daily patterns of physical activity and cancer mortality. Software implementation and illustration of the proposed estimation method are provided in R.

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“…For example, the 2020/2021 census data in England reported that 24.2% [95% CIs 24 to 24.5] of women were inactive (defined as engaging in less than 30 min of physical activity per week), compared to 22.4% [from 22.4 to 22.6] of men [9]. Furthermore, as age and BMI increases, physical activity levels decline [40,41]. However, this sample does include high educational and SES levels, which are not diverse, and people in national statistics socio-economic classification (NS-SEC) 1-2 are more likely to be active [9].…”

Section: Discussionmentioning

confidence: 99%

“Couch-to-5k or Couch to Ouch to Couch!?” Who Takes Part in Beginner Runner Programmes in the UK and Is Non-Completion Linked to Musculoskeletal Injury?

Relph,

Taylor,

Christian

et al. 2023

IJERPH

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Physical activity has mental and physical health benefits; however, globally, three-quarters of the population do not meet physical activity guidelines. The Couch-to-5k is a beginner runner programme aimed at increasing physical activity. However, this programme lacks an evidence base, and it is unclear who is attracted to the programme; running also has a high rate of musculoskeletal (MSK) injuries. The aims of this study were to identify the characteristics of people taking part and the incidence of MSK injuries as well as exploring the experiences of people who dropped out of a modified 9-week Couch-to-5k programme. A total of 110 runners (average age was 47.1 ± 13.7 years) participated in the study, which involved completion of questionnaires (running experience and footwear information, quality of life (EQ-5D-5L), physical activity level (IPAQ-short form), MSK injury history and knee condition (SNAPPS and KOOS-PS)) at the start, middle and end of the programme and collecting sociodemographic information (age, gender, social economic status, relationship status, education level), as well as body mass index, running experience, footwear information, quality of life, physical activity levels, MSK injuries and knee condition. Fifteen drop-outs were interviewed to explore experiences of the programme. Runners were mainly females (81.8%) with an average age 47.1 years, average body mass index of 28.1 kg.m2, mainly from high socio-economic levels, married and educated to degree level. In total, 64% of the sample had previous running experience and were classified as active. Half the sample self-reported pain/discomfort and 37.2% reported anxiety/depression at the start of the programme via the EQ-5D-5L scale. Self-reported health scores increased (p = 0.047) between baseline (73.1 ± 18.8 out of 100) and at the midpoint (81.2 ± 11.6), but there were no significant differences between any other time points (end point 79.7 ± 17.5, p > 0.05). Twenty-one injuries were reported during the programme (19%). Previous injury increased the risk of new injury (OR 7.56 95% CI from 2.06 to 27.75). Only 27.3% completed the programme. Three themes emerged from interviews; MSK injury, negative emotions linked to non-completion and design of the programme. The Couch-to-5k may not attract diverse inactive populations, but future work with larger sample sizes is needed to substantiate this finding. Dropping out was linked to MSK injury and progressive design, so future programmes should consider including injury prevention advice and more flexible designs.

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Diurnal Physical Activity Patterns across Ages in a Large UK Based Cohort: The UK Biobank Study

Cited by 8 publications

References 38 publications

Clustering Accelerometer Activity Patterns from the UK Biobank Cohort

Clustering Accelerometer Activity Patterns from the UK Biobank Cohort

Functional proportional hazards mixture cure model with applications in cancer mortality in NHANES and post ICU recovery

“Couch-to-5k or Couch to Ouch to Couch!?” Who Takes Part in Beginner Runner Programmes in the UK and Is Non-Completion Linked to Musculoskeletal Injury?

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