866 research outputs found

    Physical Activity and Mental Well-being in a Cohort Aged 60–64 Years

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    Introduction: Although evidence suggests physical activity (PA) may be associated with mental well-being at older ages, it is unclear whether some types of PA are more important than others. The purpose of this study is to investigate associations of monitored total PA under free-living conditions, self-reported leisure-time PA (LTPA), and walking for pleasure with mental well-being at age 60–64 years. Methods: Data on 930 (47%) men and 1,046 (53%) women from the United Kingdom MRC National Survey of Health and Development collected in 2006–2011 at age 60–64 were used in 2013–2014 to test the associations of PA (PA energy expenditure and time spent in different intensities of activity assessed using combined heart rate and acceleration monitors worn for 5 days, self-reported LTPA, and walking for pleasure) with the Warwick-Edinburgh Mental Well-being Scale (WEMWBS; range, 14–70). Results: In linear regression models adjusted for gender, long-term limiting illness, smoking, employment, socioeconomic position, personality, and prior PA, those who walked for >1 hour/week had mean WEMWBS scores 1.47 (95% CI=0.60, 2.34) points higher than those who reported no walking. Those who participated in LTPA at least five times/month had WEMWBS scores 1.25 (95% CI=0.34, 2.16) points higher than those who did not engage in LTPA. There were no statistically significant associations between free-living PA and WEMWBS scores. Conclusions: In adults aged 60–64 years, participation in self-selected activities such as LTPA and walking are positively related to mental well-being, whereas total levels of free-living PA are not

    Frequency and duration of physical activity bouts in school-aged children: A comparison within and between days

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    Understanding how physical activity (PA) patterns vary within and between days may guide PA promotion in young people. We aimed to 1) describe and compare the frequency (bouts/day) and duration (min/bout) of bouts of moderate-to-vigorous intensity PA (MVPA) on weekdays vs. weekends and in-school vs. out-of-school, and 2) assess associations of bout frequency and duration in these time-segments with overall PA. We used cross-sectional accelerometer data from 2737 children (aged 6-19 years) in the United States National Health and Nutrition Examination Survey (NHANES) 2003-2006. A bout was defined as MVPA (≥ 2000 counts per minute [cpm]) lasting ≥ 3 min. Adjusted Wald tests were used to assess differences in bout characteristics between time-segments. Linear regression was used to examine the association of time-segment specific bout characteristics with daily minutes of MVPA and PA volume (average cpm). Bout frequency was higher on weekdays than weekends (median [IQR] 4.3 [2.2-7.2] vs. 3.0 [1.0-6.5] bouts/day, p < 0.001); however, bout duration did not differ (4.7 [4.0-5.7] vs. 4.5 [3.7-5.8] min/bout, p = 0.33). More bouts were accumulated out-of-school compared with in-school (2.2 [1.0-4.0] vs. 1.8 [0.8-3.2] bouts/day, p < 0.001), but bout duration was similar (4.7 [3.8-5.8] vs. 4.5 [3.8-5.7] min/bout, p = 0.158). For all time-segments, the frequency and duration of bouts of MVPA were independently and positively associated with overall MVPA and PA volume. In conclusion, the characteristics of children's PA vary within and between days; accounting for this in intervention design may improve future interventions. However, increasing bout frequency or duration in any time-segment may be beneficial for overall PA.This work was supported by the Medical Research Council [Unit Programme numbers MC_UU_12015/7 and MC_UU_12015/3] and the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research: Centre of Excellence. Funding from the British Heart Foundation, Economic and Social Research Council, Medical Research Council, the National Institute for Health Research, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration (RES-590-28-0002), is gratefully acknowledged

    The assessment of efforts to return to work in the European Union

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    Background: Assessment of efforts to promote return-to-work (RTW) includes all efforts (vocational and non-vocational) designed to improve the work ability of the sick-listed employee and increase the chance to return to work. Aim of the study was to investigate whether in 13 European countries these RTW efforts are assessed and to compare the procedures by means of six criteria. METHODS: Data were gathered in the taxonomy project of the European Union of Medicine in Assurance and Social Security and by means of an additional questionnaire. RESULTS: In seven countries RTW efforts are subject of the assessment in relation to the application for disability benefits. Description of RTW efforts is a prerequisite in five countries. Guidelines on the assessment of RTW efforts are only available in the Netherlands and no countries report the use of the ICF model. Based on the results of the additional questionnaire, the assessor is a social scientist or a physician. The information used to assess RTW efforts differs, from a report on the RTW process to medical information. A negative outcome of the assessment leads to delay of the application for disability benefits or to application for rehabilitation subsidy. Conclusion: RTW efforts are assessed in half of the participating European countries. When compared, the characteristics of the assessment of RTW efforts in the participating European countries show both similarities and differences. This study may facilitate the gathering and exchange of knowledge and experience between countries on the assessment of RTW efforts

    Using alternatives to the car and risk of all-cause, cardiovascular and cancer mortality

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    Abstract: Objective: To investigate the associations between using alternatives to the car which are more active for commuting and non-commuting purposes and morbidity and mortality Methods: We conducted a prospective study using 358799 participants aged 37-73 from UK Biobank. Commute and non-commute travel were assessed at baseline in 2006-2010. We classified participants according to whether they relied exclusively on the car, or used alternative modes of transport that were more active at least some of the time. Main outcome measures were incident CVD and cancer, and CVD, cancer and all-cause mortality. We excluded events in the first two years and conducted analyses separately for those who regularly commuted and those who did not. Results: In maximally-adjusted models, regular commuters with more active patterns of travel on the commute had a lower risk of incident (HR 0.89, 95% CI 0.79 to 1.00) and fatal CVD (HR 0.70, 95% CI 0.51 to 0.95). Those regular commuters who also had more active patterns of non-commute travel had an even lower risk of fatal CVD (HR 0.57, 95% CI 0.39 to 0.85). Among those who were not regular commuters, more active patterns of travel were associated with a lower risk of all-cause mortality (HR 0.92, 95% CI 0.86 to 0.99). Conclusions: More active patterns of travel are associated with a reduced risk of incident and fatal CVD and all-cause mortality in adults. This is an important message for clinicians advising people about how to be physically active and reduce their risk of disease.JP, DO, SB and SS are supported by the Medical Research Council (Unit Programme Nos MC_UU_12015/1, MC_UU_12015/3 and MC_UU_12015/6) and KW is also supported by the British Heart Foundation (Intermediate Basic Science Research Fellowship grant No FS/12/58/29709). AAL is funded by the NIHR (RP 014-04-032), and the Public Health Policy Evaluation Unit are grateful for the support of the NIHR School of Public Health Research. This research was conducted using the UK Biobank resource (application No 20684). The work was also supported under the auspices of the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence at the University of Cambridge, for which funding from the British Heart Foundation, Economic and Social Research Council, Medical Research Council, National Institute for Health Research and the Wellcome Trust, under the auspices of the United Kingdom Clinical Research Collaboration, is gratefully acknowledged

    SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data

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    Machine learning and deep learning have shown great promise in mobile sensing applications, including Human Activity Recognition. However, the performance of such models in real-world settings largely depends on the availability of large datasets that captures diverse behaviors. Recently, studies in computer vision and natural language processing have shown that leveraging massive amounts of unlabeled data enables performance on par with state-of-the-art supervised models. In this work, we present SelfHAR, a semi-supervised model that effectively learns to leverage unlabeled mobile sensing datasets to complement small labeled datasets. Our approach combines teacher-student self-training, which distills the knowledge of unlabeled and labeled datasets while allowing for data augmentation, and multi-task self-supervision, which learns robust signal-level representations by predicting distorted versions of the input. We evaluated SelfHAR on various HAR datasets and showed state-of-the-art performance over supervised and previous semi-supervised approaches, with up to 12% increase in F1 score using the same number of model parameters at inference. Furthermore, SelfHAR is data-efficient, reaching similar performance using up to 10 times less labeled data compared to supervised approaches. Our work not only achieves state-of-the-art performance in a diverse set of HAR datasets, but also sheds light on how pre-training tasks may affect downstream performance
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