405 research outputs found
sj-pdf-1-jrs-10.1177_01410768211073923 - Supplemental material for Association between household size and COVID-19: A UK Biobank observational study
No full textSupplemental material, sj-pdf-1-jrs-10.1177_01410768211073923 for Association between household size and COVID-19: A UK Biobank observational study by Clare L Gillies, Alex V Rowlands, Cameron Razieh, Vahé Nafilyan, Yogini Chudasama, Nazrul Islam, Francesco Zaccardi, Daniel Ayoubkhani, Claire Lawson, Melanie J Davies, Tom Yates and Kamlesh Khunti in Journal of the Royal Society of Medicine</p
Reference values for accelerometer metrics and associations with cardiorespiratory fitness: a prospective cohort study of healthy adults and patients with heart failure
No full textBackground
Accelerometry has gained increasing popularity and yields numerous physical activity (PA) outcomes (Rowlands et al., 2019). These include traditional cut-point-based (i.e. light, moderate, and vigorous PA) and cut-point-free metrics (i.e. intensity gradient [IG] and average acceleration [AvAcc]). IG reflects the intensity distribution of PA across the day (Rowlands et al., 2018; Fairclough et al., 2019). AvAcc is a proxy for the daily volume of PA ( Rowlands et al., 2018; Fairclough et al., 2019). Cut-point-based metrics are commonly expressed in minutes per day, making their interpretation simple (Troiano et al., 2014). Yet, the measured acceleration needs to be categorised by setting population- and device-dependent cut-points to obtain these metrics (Troiano et al., 2014). Cut-point-free metrics, on the other hand, are comparable across studies, accelerometer brands (Migueles et al., 2022), and diverse populations (Rowlands et al., 2018). However, their interpretation is not easy. Besides, it is unknown how cut-point-free metrics are associated with cardiorespiratory fitness (CRF), an important health indicator in healthy individuals and patient populations with impaired CRF (Kodama et al., 2009). We thus aimed to 1) compare the association of CRF with cut-point-free metrics to that with cut-point-based metrics in a prospective cohort of healthy adults aged 20 to 89 years and patients with heart failure, and 2) provide age-, sex-, and CRF-related reference values for healthy adults.
Methods
The COmPLETE study was cross-sectional. Healthy individuals were recruited via unaddressed letters sent to randomly selected postal districts in the Basel area (Wagner et al., 2019). Patients with heart failure were approached as described elsewhere (Wagner et al., 2019). Subjects were asked to wear GENEActiv accelerometers on their non-dominant wrist for up to 14 days and undergo cardiopulmonary exercise testing on a cycle ergometer to determine CRF. Raw accelerometer data were processed using the R-package GGIR (Migueles et al., 2019; van Hees et al., 2013). Associations between CRF and accelerometer metrics were examined using multiple linear regression models adjusted for sex, age, and body mass index. Percentile curves were generated with Generalised Additive Models for Location, Scale, and Shape (Stasinopoulos & Rigby, 2008).
Results
Four hundred and sixty-three healthy adults and 67 patients with heart failure were included in the analyses. IG and AvAcc provide complementary information on PA. Both metrics were independently associated with CRF in healthy individuals. The best cut-point-free regression model (AvAcc+IG) performed similar to the best cut-point-based model (vigorous activity) and explained 73.9% and 74.2% of the variance in CRF, respectively. In patients with heart failure, IG was associated with CRF, independent of AvAcc. Cut-point-free models (IG+AvAcc, IG alone) had comparable predictive value for CRF as the best cut-point-based metric (moderate-to-vigorous activity). We produced age-, sex-, and CRF-related reference values for IG, AvAcc, moderate-to-vigorous, and vigorous activity for healthy adults. Moreover, we developed a web-based application (rawacceleration) facilitating the interpretation of cut-point-free metrics.
Conclusions
Cut-point-free metrics are not only more robust than cut-point-based metrics, but also have similar predictive value for CRF and, in turn, indirectly for the risk of mortality and longevity (Kodama et al., 2009; Mok et al., 2019). This may be the case in both healthy individuals and patients with heart failure. Our findings together with those of previous studies (Rowlands et al., 2018; Fairclough et al., 2019), therefore, provide a rationale that cut-point-free metrics facilitate the capture of the volume and intensity distribution of the PA profile across populations, and thus may be a viable alternative to cut-point-based metrics in describing PA. Our reference values will enhance the utility of IG and AvAcc and facilitate their interpretation. Finally, our web-based application will simplify this process and also support the translation of cut-point-free metrics into meaningful outcomes.
References
Fairclough, S. J., Taylor, S., Rowlands, A. V., Boddy, L. M., & Noonan, R. J. (2019) Average acceleration and intensity gradient of primary school children and associations with indicators of health and well-being. Journal of Sports Sciences, 37(18), 2159-2167. https://doi.org/10.1080/02640414.2019.1624313
Kodama, S., Saito, K., Tanaka, S., Maki, M., Yachi, Y., Asumi, M., Sugawara, A., Totsuka, K., Shimano, H., Ohashi, Y., Yamada, N., & Sone, H. (2009). Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: A meta-analysis. JAMA, 301(19), 2024-35.https://doi.org/10.1001/jama.2009.681
Migueles, J. H., Molina-Garcia, P., Torres-Lopez, L. V., Cadenas-Sanchez, C., Rowlands, A. V., Ebner-Priemer, U. W., Koch, E. D., Reif, A., & Ortega, F. B. (2022). Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance. Science Reports, 12, Article 5525. https://doi.org/10.1038/s41598-022-09469-2
Migueles, J. H., Rowlands, A. V., Huber, F., Sabia, S., & van Hees, V. T. (2019). GGIR: A research community–driven open source R package for generating physical activity and sleep outcomes from multi-day raw accelerometer data. Journal for the Measurement of Physical Behaviour, 2(3),188-96. https://doi.org/10.1123/jmpb.2018-0063
Mok, A., Khaw, K.-T., Luben, R., Wareham, N., & Brage, S. (2019). Physical activity trajectories and mortality: Population based cohort study. BMJ, 365, l2323. https://doi.org/10.1136/bmj.l2323
Rowlands, A. V., Edwardson, C. L., Davies, M. J., Khunti, K., Harrington, D. M., & Yates, T. (2018). Beyond cut points: Accelerometer metrics that capture the physical activity profile. Medicine & Science in Sports & Exercise, 50(6), 1323-32. https://doi.org/10.1249/MSS.0000000000001561
Rowlands, A. V., Fairclough, S. J., Yates, T., Edwardson, C. L., Davies, M., Munir, F., Khunti, K., & Stiles, V. H. (2019). Activity intensity, volume, and norms: Utility and interpretation of accelerometer metrics. Medicine & Science in Sports & Exercise, 51(11), 2410-2422. https://doi.org/10.1249/MSS.0000000000002047
Stasinopoulos, D. M., & Rigby, R. A. (2008). Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, 23(7), 1 - 46. https://doi.org/10.18637/jss.v023.i07
Troiano, R. P., McClain, J. J., Brychta, R. J., & Chen, K. Y. (2014). Evolution of accelerometer methods for physical activity research. British Journal of Sports Medicine, 48(13), 1019-1023. https://doi.org/10.1136/bjsports-2014-093546
van Hees, V. T., Gorzelniak, L., Dean León, E. C., Eder, M., Pias, M., Taherian, S., Ekelung, U., Renström, F., Franks, P. W., Horsch, A., & Brage, S. (2013). Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity. PloS one, 8(4), Article e61691. https://doi.org/10.1371/journal.pone.0061691
Wagner, J., Knaier, R., Infanger, D., Arbeev, K., Briel, M., Dieterle, T., Hanssen, H., Faude, O., Roth, R., Hinrichs, T., & Schmidt-Trucksäss, A. (2019). Functional aging in health and heart failure: The COmPLETE Study. BMC Cardiovascular Disorders, 19, Article 180. https://doi.org/10.1186/s12872-019-1164-
Open access self-archiving: An author study
No full textThis, our second author international, cross-disciplinary study on open access had 1296 respondents. Its focus was on self-archiving. Almost half (49%) of the respondent population have self-archived at least one article during the last three years. Use of institutional repositories for this purpose has doubled and usage has increased by almost 60% for subject-based repositories. Self-archiving activity is greatest amongst those who publish the largest number of papers. There is still a substantial proportion of authors unaware of the possibility of providing open access to their work by self-archiving. Of the authors who have not yet self-archived any articles, 71% remain unaware of the option. With 49% of the author population having self-archived in some way, this means that 36% of the total author population (71% of the remaining 51%), has not yet been appraised of this way of providing open access. Authors have frequently expressed reluctance to self-archive because of the perceived time required and possible technical difficulties in carrying out this activity, yet findings here show that only 20% of authors found some degree of difficulty with the first act of depositing an article in a repository, and that this dropped to 9% for subsequent deposits. Another author worry is about infringing agreed copyright agreements with publishers, yet only 10% of authors currently know of the SHERPA/RoMEO list of publisher permissions policies with respect to self-archiving, where clear guidance as to what a publisher permits is provided. Where it is not known if permission is required, however, authors are not seeking it and are self-archiving without it. Communicating their results to peers remains the primary reason for scholars publishing their work; in other words,
researchers publish to have an impact on their field. The vast majority of authors (81%) would willingly comply with a mandate from their employer or research funder to deposit copies of their articles in an institutional or subject-based repository. A further 13% would comply reluctantly; 5% would not comply with such a mandate
Ethnic minorities and COVID-19: examining whether excess risk is mediated through deprivation
No full textBackground: people from South Asian and black minority ethnic groups are disproportionately affected by the COVID-19 pandemic. It is unknown whether deprivation mediates this excess ethnic risk.Methods: we used UK Biobank with linked COVID-19 outcomes occurring between 16th March 2020 and 24th August 2020. A four-way decomposition mediation analysis was used to model the extent to which the excess risk of testing positive, severe disease and mortality for COVID-19 in South Asian and black individuals, relative to white individuals, would be eliminated if levels of high material deprivation were reduced within the population.Results: we included 15 044 (53.0% women) South Asian and black and 392 786 (55.2% women) white individuals. There were 151 (1.0%) positive tests, 91 (0.6%) severe cases and 31 (0.2%) deaths due to COVID-19 in South Asian and black individuals compared with 1471 (0.4%), 895 (0.2%) and 313 (0.1%), respectively, in white individuals. Compared with white individuals, the relative risk of testing positive for COVID-19, developing severe disease and COVID-19 mortality in South Asian and black individuals were 2.73 (95% CI: 2.26, 3.19), 2.96 (2.31, 3.61) and 4.04 (2.54, 5.55), respectively. A hypothetical intervention moving the 25% most deprived in the population out of deprivation was modelled to eliminate between 40 and 50% of the excess risk of all COVID-19 outcomes in South Asian and black populations, whereas moving the 50% most deprived out of deprivation would eliminate over 80% of the excess risk of COVID-19 outcomes.Conclusions: the excess risk of COVID-19 outcomes in South Asian and black communities could be substantially reduced with population level policies targeting material deprivation
Physical Activity, Inactivity and Health During Youth—2016
No full text2016 has been an exciting year for research in physical activity, inactivity and health. Recognition of the importance of all physical behaviors (physical activity, sedentary time and sleep) across the 24-hr day continues to grow. Notable advances have included: applications of recent methodological innovations that account for the codependence of the behaviors in the finite 24-hr period showing that the balance of these behaviors is associated with health; methodological innovations focusing on the classification of behaviors and/or quantification of the 24-hr diurnal activity pattern; and a series of systematic reviews that helped provide the evidence base for the release of the innovative 24-hr movement guidelines earlier this year. This commentary focuses on just two of these papers: the first by Goldsmith and colleagues who demonstrate a new statistical method that exploits the time series nature of accelerometer data facilitating new insights into time-specific determinants of children’s activity patterns and associations with health; the second by Tremblay and colleagues who describe the evidence base for associations between each physical behavior and children’s health, the emerging evidence base for associations between the balance of behaviors and health, and development of the world’s first 24-hr movement guidelines.</jats:p
Life expectancy following a cardiovascular event in individuals with and without type 2 diabetes: A UK multi-ethnic population-based observational study
No full textBackground and Aims We aimed to evaluate the life expectancy following the first cardiovascular disease (CVD) event by type 2 diabetes (T2D) status and ethnicity. Methods and Results We used the Clinical Practice Research Datalink database in England (UK), linked to the Hospital Episode Statistics information, to identify individuals with and without T2D who survived a first CVD event between 1st Jan 2007 and 31st Dec 2017; subsequent death events were extracted from the Office for National Statistics database. Ethnicity was categorised as White, South Asian (SA), Black, or other. Flexible parametric survival models were used to estimate survival and predict life expectancy. 59,939 individuals with first CVD event were included: 7,596 (12.7%) with T2D (60.9% men; mean age at event: 69.7 years [63.2 years in SA, 65.9 in Black, 70.2 in White]) and 52,343 without T2D (56.7% men; 65.9 years [54.7 in Black, 58.2 in SA, 66.3 in White]). Accounting for potential confounders (sex, deprivation, lipid-lowering medication, current smoking, and pre-existing hypertension), comparing individuals with vs without T2D the mortality rate was 53% higher in White (hazard ratio [HR]: 1.53 [95% CI: 1.44, 1.62]), corresponding to a potential loss of 3.87 (3.30, 4.44) life years at the age of 50 years in individuals with T2D. No evidence of a difference in life expectancy was observed in individuals of SA (HR: 0.82 [0.52, 1.29]; -1.36 [-4.58, 1.86] life years), Black (HR: 1.26 [0.59, 2.70]; 1.21 [-2.99, 5.41] life years); and other (HR: 1.64 [0.80, 3.39]; 3.89 [-2.28, 9.99] life years) ethnic group. Conclusion Following a CVD event, T2D is associated with a different prognosis and life years lost among ethnic groups
Measuring and comparing descend in elite race cycling with a perspective on real-time feedback for improving individual performance
No full textDescend technique and performance vary among elite racing cyclists and it is not clear what slower riders should do to improve their performance. An observation study was performed of the descending technique of members of a World Tour cycling team and the technique of each member was compared with the fastest descender amongst them. The obtained data gives us guidelines for rider specific feedback in order to improve his performance. The bicycles were equipped with a system that could measure: velocity, cadence, pedal power, position, steer angle, 3D orientation, rotational speeds and linear accelerations of the rear frame and brake force front and rear. From our observation study, the brake point and apex position turned out to be distinctive indicators of a fast cornering technique in a descent for a tight, hairpin corner. These two indicators can be used as feedback for a slower rider to improve his descend performance.Biomechatronics & Human-Machine ControlResearch Funding Nationa
Association between household size and COVID-19: A UK Biobank observational study
No full textObjective To assess the association between household size and risk of non-severe or severe COVID-19. Design A longitudinal observational study. Setting This study utilised UK Biobank linked to national SARS-CoV-2 laboratory test data. Participants 401,910 individuals with available data on household size in UK Biobank. Main outcome measures Household size was categorised as single occupancy, two-person households and households of three or more. Severe COVID-19 was defined as a positive SARS-CoV-2 test on hospital admission or death with COVID-19 recorded as the underlying cause; and non-severe COVID-19 as a positive test from a community setting. Logistic regression models were fitted to assess associations, adjusting for potential confounders. Results Of 401,910 individuals, 3612 (1%) were identified as having suffered from a severe COVID-19 infection and 11,264 (2.8%) from a non-severe infection, between 16 March 2020 and 16 March 2021. Overall, the odds of severe COVID-19 was significantly higher among individuals living alone (adjusted odds ratio: 1.24 [95% confidence interval: 1.14 to 1.36], or living in a household of three or more individuals (adjusted odds ratio: 1.28 [1.17 to 1.39], when compared to individuals living in a household of two. For non-severe COVID-19 infection, individuals living in a single-occupancy household had lower odds compared to those living in a household of two (adjusted odds ratio: 0.88 [0.82 to 0.93]. Conclusions Odds of severe or non-severe COVID-19 infection were associated with household size. Increasing understanding of why certain households are more at risk is important for limiting spread of the infection.</div
Some effects of crosswind on the lateral dynamics of a bicycle
No full textThe bicycle, being unstable at low speed and marginally stable at high speed, is sensitive to lateral perturbations. One of the major lateral perturbations is crosswind, which can lead to accidents and fatalities. Here we investigate the effect of crosswind on the lateral dynamics and control of the bicycle in a wide range of forward speeds and various crosswinds, by means of computer model analysis and simulation. A low dimensional bicycle model is used together with experimentally identified rider control parameters. The crosswind forces are obtained from a recent experimental study. Analysis and simulation show that crosswind decreases the stability of the bicycle and is clearly a safety issue.Biomechatronics & Human-Machine ControlIntelligent Vehicle
Patterns of multimorbidity and risk of severe SARS-CoV-2 infection: an observational study in the UK
No full textBackground: pre-existing comorbidities have been linked to SARS-CoV-2 infection but evidence is sparse on the importance and pattern of multimorbidity (2 or more conditions) and severity of infection indicated by hospitalisation or mortality. We aimed to use a multimorbidity index developed specifically for COVID-19 to investigate the association between multimorbidity and risk of severe SARS-CoV-2 infection.Methods: we used data from the UK Biobank linked to laboratory confirmed test results for SARS-CoV-2 infection and mortality data from Public Health England between March 16 and July 26, 2020. By reviewing the current literature on COVID-19 we derived a multimorbidity index including: (1) angina; (2) asthma; (3) atrial fibrillation; (4) cancer; (5) chronic kidney disease; (6) chronic obstructive pulmonary disease; (7) diabetes mellitus; (8) heart failure; (9) hypertension; (10) myocardial infarction; (11) peripheral vascular disease; (12) stroke. Adjusted logistic regression models were used to assess the association between multimorbidity and risk of severe SARS-CoV-2 infection (hospitalisation/death). Potential effect modifiers of the association were assessed: age, sex, ethnicity, deprivation, smoking status, body mass index, air pollution, 25‐hydroxyvitamin D, cardiorespiratory fitness, high sensitivity C-reactive protein.Results: among 360,283 participants, the median age was 68 [range 48–85] years, most were White (94.5%), and 1706 had severe SARS-CoV-2 infection. The prevalence of multimorbidity was more than double in those with severe SARS-CoV-2 infection (25%) compared to those without (11%), and clusters of several multimorbidities were more common in those with severe SARS-CoV-2 infection. The most common clusters with severe SARS-CoV-2 infection were stroke with hypertension (79% of those with stroke had hypertension); diabetes and hypertension (72%); and chronic kidney disease and hypertension (68%). Multimorbidity was independently associated with a greater risk of severe SARS-CoV-2 infection (adjusted odds ratio 1.91 [95% confidence interval 1.70, 2.15] compared to no multimorbidity). The risk remained consistent across potential effect modifiers, except for greater risk among older age. The highest risk of severe infection was strongly evidenced in those with CKD and diabetes (4.93 [95% CI 3.36, 7.22]).Conclusion: the multimorbidity index may help identify individuals at higher risk for severe COVID-19 outcomes and provide guidance for tailoring effective treatment
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