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PURPOSE: Understanding seasonal variation in physical activity is important for informing public health surveillance and intervention design. The aim of the current study was to describe seasonal variation in children's objectively measured physical activity and sedentary time. METHODS: Data are from the UK Millennium Cohort Study. Participants were invited to wear an accelerometer for 7 d on five occasions between November 2008 and January 2010. Outcome variables were sedentary time (2241 counts per minute, min·d(-1)). The season was characterized using a categorical variable (spring, summer, autumn, or winter) and a continuous function of day of the year. Cross-classified linear regression models were used to estimate the association of each of these constructs with the outcome variables. Modification of the seasonal variation by sex, weight status, urban/rural location, parental income, and day of the week (weekday/weekend) was examined using interaction terms in regression models. RESULTS: At least one wave of valid accelerometer data was obtained from 704 participants (47% male; baseline age, 7.6 (0.3) yr). MVPA was lower in autumn and winter relative to spring, with the magnitude of this difference varying by weekday/weekend, sex, weight status, urban/rural location, and family income (P for interaction <0.05 in all cases). Total sedentary time was greater in autumn and winter compared with spring; the seasonal effect was stronger during the weekend than during the weekday (P for interaction <0.01). CONCLUSIONS: Lower levels of MVPA and elevated sedentary time support the implementation of intervention programs during autumn and winter. Evidence of greater seasonal variation in weekend behavior and among certain sociodemographic subgroups highlights targets for tailored intervention programs. ; The co-operation of the participating families is gratefully acknowledged. The fourth sweep of the Millennium Cohort Study was funded by grants to Professor Health Joshi, former director of the study, from the Economic and Social Research Council and a consortium of government funders. The current director is Professor Lucinda Platt. The authors acknowledge: the Centre for Longitudinal Studies, Institute of Education for the use of these data; the UK Data Service for making them available; the MRC Centre of Epidemiology for Child Health (Grant reference G0400546), Institute of Child Health, University College London for creating the accelerometer data resource which was funded by the Wellcome Trust (grant reference 084686/Z/08/A). The institutions and funders acknowledged bear no responsibility for the analysis or interpretation of these data. The work of Andrew J Atkin, Flo Harrison, and Esther M F van Sluijs was supported, wholly or in part, by the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence (RES-590-28-0002). Funding from the British Heart Foundation, Department of Health, Economic and Social Research Council, Medical Research Council, and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged. The work of Soren Brage, Stephen Sharp and Esther MF van Sluijs was supported by the Medical Research Council (MC_UU_12015/7, MC_UU_12015/3, MC_UU_12015/1). ; This is the final version of the article. It first appeared from Wolters Kluwer via http://dx.doi.org/10.1249/MSS.0000000000000786

Abstract Background: The disease or mortality burdens of unhealthy lifestyle behaviours are often reported. The positive side of the story, the burden that existing levels have averted, is rarely discussed. We present what we believe to be global application of the Prevented Fraction for the Population to obtain estimates of the percentage of premature mortality and number of premature deaths averted by total physical activity levels for 168 countries. Methods: We combined previously published activity prevalence data (2001-2016) and relative risks of mortality in Monte-Carlo simulations to estimate country-specific Prevented Fractions for the Population (percentage of mortality averted) and their 95% confidence intervals. Higher Prevented Fractions indicate a greater proportion of deaths averted due to physical activity. Using mortality data for 40-74 year olds, we estimated the number of premature deaths averted due to activity levels for all adults and by sex. We presented the median and range of the Prevented Fractions globally, by region, and by income classification. Results: The global median Prevented Fraction for the Population was 15.0% (range 6.6-20.5%), conservatively equating to 3.9 million (95% confidence interval: 2.5-5.6) premature deaths averted annually. The African region had the highest median (16.6%, range 12.1-20.5%), the Americas had the lowest (13.1%, range 10.8-16.6%). Low income countries tended to have higher median Prevented Fractions (17.9%, range 12.3-20.5%) than high income countries (14.1%, range 6.6-17.8%). Globally, the median Prevented Fraction was higher for men than women (16.0% (range 7.8-20.7% and 14.1% (range 5.0-20.4%), respectively). Interpretation: Existing physical activity levels have contributed to averting premature mortality across all countries. The Prevented Fraction for the Population has utility as an advocacy tool to promote healthy lifestyle behaviours as, by making the case of what has been achieved, it could demonstrate the value of current investment and services. This may be more conducive to political support. ; TS, SJS, and SB are funded by the UK Medical Research Council (MC_UU_12015/1 and MC_UU_12015/3). DD is funded by a Future Leader Fellowship by Heart Foundation Australia (No. 101234). At the time of this work, MT was a member of the Centre for Diet and Activity Research (MR/K023187/1), a UKCRC Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Cancer Research UK, Economic and Social Research Council, Medical Research Council, National Institute for Health Research (NIHR), and Wellcome Trust, under the auspices of the UKClinical Research Collaboration, is gratefully acknowledged. MT was also funded on the METAHIT project (Medical Research Council grant MR/P02663X/1).

PURPOSE: Assess the agreement between commonly used self-report methods compared with objectively measured physical activity (PA) in defining the prevalence of individuals compliant with PA recommendations. METHODS: Time spent in moderate and vigorous PA (MVPA) was measured at two time points in 1713 healthy individuals from nine European countries using individually calibrated combined heart rate and movement sensing. Participants also completed the Recent Physical Activity Questionnaire (RPAQ), short form of the International Physical Activity Questionnaire (IPAQ), and short European Prospective Investigation into Cancer and Nutrition Physical Activity Questionnaire (EPIC-PAQ). Individuals were categorized as active (e.g., reporting ≥150 min of MVPA per week) or inactive, based on the information derived from the different measures. Sensitivity and specificity analyses and Kappa statistics were performed to evaluate the ability of the three PA questionnaires to correctly categorize individuals as active or inactive. RESULTS: Prevalence estimates of being sufficiently active varied significantly (P for all <0.001) between self-report measures (IPAQ 84.2% [95% confidence interval {CI}, 82.5-85.9], RPAQ 87.6% [95% CI, 85.9-89.1], EPIC-PAQ 39.9% [95% CI, 37.5-42.1] and objective measure 48.5% [95% CI, 41.6-50.9]. All self-report methods showed low or moderate sensitivity (IPAQ 20.0%, RPAQ 18.7%, and EPIC-PAQ 69.8%) to correctly classify inactive people and the agreement between objective and self-reported PA was low (ĸ = 0.07 [95% CI, 0.02-0.12], 0.12 [95% CI, 0.06-0.18], and 0.19 [95% CI, 0.13-0.24] for IPAQ, RPAQ, and EPIC-PAQ, respectively). CONCLUSIONS: The modest agreement between self-reported and objectively measured PA suggests that population levels of PA derived from self-report should be interpreted cautiously. Implementation of objective measures in large-scale cohort studies and surveillance systems is recommended. ; The preparation of this paper was supported by the DEterminants of DIet and Physical ACtivity (DEDIPAC) knowledge hub. This work is supported by the Joint Programming Initiative 'Healthy Diet for a Healthy Life'. The funding agencies supporting this work are Ireland: The Health Research Board (HRB); The Netherlands: The Netherlands Organisation for Health Research and Development (ZonMw); Norway: The Research Council of Norway, Division for Society and Health The data collection was supported by funding from the European Union (Integrated Project LSHM-CT-2006-037197 in the Framework Programme 6 of the European Community) and the MRC Epidemiology Unit Programmes (MC_UU_12015/3). We would like to thank the Interact validation group* and MRC Epidemiology Unit physical activity technical team and data management team, in particular Mark Betts, Laura Lamming, Stefanie Mayle, Kate Westgate and Nicola Kerrison who assisted with data reduction, cleaning and processing. The InterAct validation working group* are Anne M May, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; Wanda Wendel-Vos, National Institute for Public Health and the Environment, Centre for Nutrition, Prevention and Health Services, Bilthoven, The Netherlands; Kristin Benjaminsen Borch, Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway; Kim Overvad, Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark and Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark; Marie-Aline Charles, Inserm, Centre for research in Epidemiology and Population Health, U1018, Lifelong epidemiology of obesity, diabe`tes and chronic renal disease Team, F-94807, Villejuif, France; Univ Paris-Sud, UMRS 1018, F-94807, Villejuif, France; Maria Jose Tormo Diaz, Department of Epidemiology, Murcia Regional Health Authority, Murcia, Spain, CIBER Epidemiologıa y Salud Publica (CIBERESP), Spain and Department Sociosanitary Sciences, Murcia School of Medicine, Murcia, Spain; Pilar Amiano, Public Health Division of Gipuzkoa, BioDonostia Research Isntitute, Basque Region, San Sebastian ; CIBER Epidemiologıa y Salud Publica (CIBERESP), Madrid, Spain; Domenico Palli ,Molecular and Nutritional Epidemiology Unit, ISPO, Cancer Prevention and Research Institute, Florence, Italy; Eliavet Valanou, Hellenic Health Foundation (HHF), Athens, Greece;, Department of Epidemiology; Mattheaus Vigl, German Institute of Human Nutrition (DIfE) Potsdam-Rehbruecke, Germany and Paul W Franks, Department of Clinical Sciences, Genetic & Molecular Epidemiology Unit, Skåne University Hospital, Lund University, Malmö, Sweden, Genetic Epidemiology & Clinical Research Group, Department of Public Health & Clinical Medicine, Section for medicine, Umeå University, Sweden. The results of the current study do not constitute an endorsement by the American College of Sports Medicine. The authors have no conflict of interest to report. ; This is the author accepted manuscript. The final version is available from Lippincott Williams & Wilkins via http://dx.doi.org/10.1249/MSS.0000000000000760

The influence of the physical activity environment in the home and at work on cardiorespiratory fitness (CRF) and objectively-measured physical activity has not been extensively studied. We recruited 147 women with a (mean ± SD) age of 54 ± 7 years and without evidence of chronic disease. The physical activity environment was assessed by self-report (Assessing Levels of PHysical Activity or ALPHA questionnaire), CRF using a submaximal step test, usual physical activity using combined heart rate and accelerometry, as well as by a validated questionnaire (Recent Physical Activity Questionnaire). Summary scores of the home environment and the work environment derived from the ALPHA questionnaire were positively correlated with CRF after adjustment for age ($r$ = 0.18, $p$ = 0.03 and $r$ = 0.28, $p$ < 0.01, respectively). Women owning a bicycle or having a garden (which may prompt physical activity) had higher CRF; those with a bicycle at home also had a higher physical activity energy expenditure. Similarly, women who had access to fitness equipment at work had higher CRF. In conclusion, these results provide new insights into potential environmental influences on physical capacity and physical activity that could inform the design of physical activity promotion strategies. ; European Union (Integrated Project LSHM-CT-2006-037197 in the Framework Programme 6 of the European Community), Medical Research Council (Grant ID: MC_UU_12015/3)

OBJECTIVE: To assess the levels of physical activity among young children with moderate acute malnutrition and to identify clinical, biochemical, anthropometric, and sociodemographic correlates of physical activity. STUDY DESIGN: In a cross-sectional study, 1609 children aged 6-23 months wore a triaxial accelerometer (ActiGraph GT3x+; ActiGraph, Pensacola, Florida) for 6 consecutive days, from which total physical activity were determined. Data on morbidity were collected based by history and physical examination, and serum C-reactive protein and α₁-acid glycoprotein were measured. RESULTS: A total of 1544 (96%) children had physical activity measured, of whom 1498 (97%) completed 6 consecutive days of physical activity recording with a daily median wear time of 24 hours. The mean (±SD) total physical activity was 707 (±180) vector magnitude counts per minute (cpm). Age was negatively correlated with physical activity; compared with children below 12 months of age, those 12-17 months of age, and 18-23 months of age had 51 (95% CI, 26; 75) and 106 (95% CI, 71; 141) cpm lower physical activity, respectively. Fever and malaria were associated with 49 (95% CI, 27; 70) and 44 (95% CI, 27; 61) cpm lower activity, respectively. Elevated serum C-reactive protein and α₁-acid glycoprotein were both negative correlates of physical activity, and hemoglobin was a positive correlate. CONCLUSIONS: Physical activity declines with age in children with moderate acute malnutrition and is also inversely related to infection and inflammatory status. Future studies are needed to ascertain cause and effect of these associations. TRIAL REGISTRATION: Controlled-Trials.com: ISRCTN42569496. ; Funded by the Danish International Development Assistance (DANIDA; 09-097 LIFE [to C.W.]), Médecins Sans Frontières (Denmark and Norway), World Food Program (received support from the US Agency for International Development's Office of Food for Peace), Alliance for International Medical Action, the European Union, Action Contre la Faim, and Arvid Nilsson Foundation. The authors declare no conflicts of interest.

BACKGROUND: In 2014 the Danish Government introduced a wide-ranging school reform that applies to all public schools in Denmark. The reform involves changes in several aspects of the school structure and content. In a physical activity promotion perspective, a distinctive feature of the school reform is that it has become mandatory to integrate an average of 45 min of daily physical activity in the regular school day. The overarching objective of the PHASAR study is to evaluate the implementation and effect of this ambitious policy-driven physical activity promotion initiative on physical activity and overweight. This paper describes in detail the study protocol. METHODS: The evaluation is divided into a quantitative effect evaluation and a combined quantitative and qualitative process evaluation. A total of 31 schools are enrolled in the PHASAR study including more than 2,000 school-aged children. Objectively measured physical activity data are obtained in the PHASAR study in 2017/18 and compared to repeated cross sectional data collected in four historical school-based studies from 1998 to 2012. Body mass index data from 2012 to 2018 will be collected from The Child Database, which includes repeated cross-sectional assessments on approximately 100,000 children annually. In the absence of a control group, interrupted time-series analysis will be used to evaluate pre- and post-reform physical activity and body mass index levels and trends. A characterization of the school environment for physical activity promotion on a political, environmental, organizational and individual level and school implementation processes will be conducted to evaluate the implementation process. Data will be collected using interviews, surveys, document analyses and observations. DISCUSSION: The PHASAR study is a rare opportunity to evaluate the effectiveness of a nation-wide policy-driven school-based physical activity promotion initiative. The use of objectively measured pre- and post-reform physical activity and body mass index data combined with a characterization of the school implementation processes for physical activity promotion will provide a comprehensive source to evaluate the school reform. The study findings have the potential to influence national and international policy makers, health professionals and school staff.

Hand grip strength is a widely used proxy of muscular fitness, a marker of frailty, and predictor of a range of morbidities and all-cause mortality. To investigate the genetic determinants of variation in grip strength, we perform a large-scale genetic discovery analysis in a combined sample of 195,180 individuals and identify 16 loci associated with grip strength (P<5 × 10−8) in combined analyses. A number of these loci contain genes implicated in structure and function of skeletal muscle fibres (ACTG1), neuronal maintenance and signal transduction (PEX14, TGFA, SYT1), or monogenic syndromes with involvement of psychomotor impairment (PEX14, LRPPRC and KANSL1). Mendelian randomization analyses are consistent with a causal effect of higher genetically predicted grip strength on lower fracture risk. In conclusion, our findings provide new biological insight into the mechanistic underpinnings of grip strength and the causal role of muscular strength in age-related morbidities and mortality. ; This research has been conducted using the UK Biobank Resource. The Fenland Study is supported by the UK Medical Research Council (MRC) (MC_UU_12015/1; MC_UU_12015/2; MC_UU_12015/3). EPIC-Norfolk is supported by the MRC (G401527, G1000143) and Cancer Research UK (A8257). The HCS is gratefully supported by the University of Newcastle (Australia) and the Fairfax Family Foundation. Sydney MAS is supported by the Australian National Health and Medical Research Council (NHMRC), grants ID568969, ID350833 and ID109308. Sydney MAS DNA was extracted by Genetic Repositories Australia, funded by NHMRC Enabling Grant 401184. The GEFOS Study, used as controls for the US and Jamaican athletes, was supported in part by NIH grants U01 HG004436 and P30 DK072488, and the Baltimore Geriatrics Research, Education, and Clinical Center of the Department of Veterans Affairs. The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent Research Center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (www.metabol.ku.dk). TwinsUK was funded by the Wellcome Trust (WT), MRC, and European Union. The study also receives support from the National Institute for Health Research (NIHR) BioResource Clinical Research Facility and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust and King's College London. SNP Genotyping was performed by The WT Sanger Institute and National Eye Institute via NIH/CIDR. M.McC is a WT Senior Investigator and receives support from WT 090532 and 098381. TW is the recipient of a studentship from MedImmune. Research by A. Lucia is supported by Fondo de Investigaciones Sanitarias and Fondos Feder (grant # PI15/0558). EM-M. was a recipient of a Grant-in-Aid for JSPS Fellow from the Japan Society for the Promotion of Science. This work was supported in part by grants from the Grant-in-Aid for Scientific Research (B) (15H03081 to NF) of the Japanese Ministry of Education, Culture, Sports, Science and Technology and by a grant-in-aid for scientific research (to M. Miyachi) from the Japanese Ministry of Health, Labor, and Welfare. This work was further supported by NIH grants R01 AR41398 and U24 AG051129.