Cross-sectional and longitudinal associations between the 24-hour movement behaviours, including muscle and bone strengthening activity, with bone and lean mass from childhood to adolescence.

BACKGROUND: This study aimed to assess whether moderate-to-vigorous physical activity (MVPA), sport and exercise as a proxy measure of muscle and bone strengthening activity, sedentary behaviour, and sleep were associated with total-body-less-head (TBLH) bone mineral content (BMC) and TBLH lean mass cross-sectionally and longitudinally from age 6 to 9 years and age 9 to 11 years to age 15 to 17 years. METHODS: We used longitudinal data from a population sample of Finnish children from the Physical Activity and Nutrition in Children study (age 6 to 9 years: n = 478, 229 females; age 9 to 11 years: n = 384, 197 females; age 15 to 17 years: n = 222, 103 females). Linear regression analysed the cross-sectional and longitudinal associations between accelerometer-assessed MVPA, sedentary time and sleep, and questionnaire-assessed sport and exercise participation and screen time with dual-energy X-ray absorptiometry-assessed TBLH BMC and lean mass. RESULTS: In females, MVPA at age 6 to 9 years was positively associated with TBLH BMC at age 15 to 17 years (ß = 0.008, p = 0.010). Sport and exercise at age 9 to 11 years was positively associated with TBLH BMC (ß = 0.020, p = 0.002) and lean mass (ß = 0.343, p = 0.040) at age 15 to 17 years. MVPA at age 9 to 11 years was positively associated with TBLH lean mass (ß = 0.272, p = 0.004) at age 15 to 17 years. In males, sleep at age 6 to 9 years was positively associated with TBLH lean mass (ß = 0.382, p = 0.003) at age 15 to 17 years. Sport and exercise at age 9 to 11 years was positively associated with TBLH BMC (ß = 0.027, p = 0.012) and lean mass (ß = 0.721, p < 0.001) at age 15 to 17 years. CONCLUSIONS: Promoting engagement in the 24-hour movement behaviours in childhood, particularly sport and exercise to strengthen muscle and bone, is important in supporting bone and lean mass development in adolescence. TRIAL REGISTRATION: NCT01803776; first trial registration date: 04/03/2013.

Associations between change in physical activity and sedentary time and health-related quality of life in older english adults: the EPIC-Norfolk cohort study.

BACKGROUND: No previous studies have examined the associations between changes in objectively-measured physical behaviours with follow-up QoL in older adults. Based on cross-sectional evidence, it is biologically plausible that such associations exist. If so, this bolsters the case for the commissioning of activity interventions and for including QoL as an outcome in trials of such interventions. METHODS: We assessed physical behaviours (total physical activity, moderate-to-vigorous physical activity (MVPA), light physical activity, total sedentary time and prolonged sedentary bout time) for 7 days using hip-worn accelerometers at baseline (2006-2011) and follow-up (2012-2016) and health-related quality-of-life (QoL) using EQ-5D questionnaires at follow-up in 1433 participants (≥ 60 years) of the EPIC (European Prospective Investigation into Cancer)-Norfolk study. The EQ-5D summary score was used, with 0 as the worst to 1 as best perceived quality-of-life. We evaluated the prospective associations of baseline physical behaviours with follow-up QoL, and of changes in behaviours with follow-up QoL using multi-level regression. RESULTS: On average, MVPA decreased by 4.0 min/day/year (SD 8.3) for men and 4.0 min/day/year for women (SD 12.0) between baseline and follow-up. Total sedentary time increased by an average 5.5 min/day/yr (SD 16.0) for men and 6.4 min/day/yr (SD 15.0) for women between baseline and follow-up. Mean (SD) follow-up time was 5.8 (1.8) years. We found that higher baseline MVPA and lower sedentary time was associated with higher subsequent QoL (e.g. 1 h/day greater baseline MVPA was associated with 0.02 higher EQ-5D score, 95% CI 0.06, 0.36). More pronounced declines in activity were associated with worse Hr-QoL (0.005 (95% CI 0.003, 0.008) lower EQ-5D per min/day/yr decrease in MVPA). Increases in sedentary behaviours were also associated with poorer QoL (0.002 lower EQ-5D, 95% CI -0.003, -0.0007 per hour/day/yr increase in total sedentary time). CONCLUSIONS: Promotion of physical activity and limiting sedentary time among older adults may improve quality-of-life, and therefore this relationship ought to be included in future cost effectiveness analyses so that greater commissioning of activity interventions can be considered.

Energy expenditure and intensity of ritual jumping-dancing in male Maasai.

OBJECTIVES: Traditional jumping-dance rituals performed by Maasai men involve prolonged physical exertion that may contribute significantly to overall physical activity level. We aimed to objectively quantify the metabolic intensity of jumping-dance activity and assess associations with habitual physical activity and cardiorespiratory fitness (CRF). METHODS: Twenty Maasai men (18-37 years) from rural Tanzania volunteered to participate in the study. Habitual physical activity was monitored using combined heart rate (HR) and movement sensing over 3 days, and jumping-dance engagement was self-reported. A 1-h jumping-dance session resembling a traditional ritual was organized, during which participants' vertical acceleration and HR were monitored. An incremental, submaximal 8-min step test was performed to calibrate HR to physical activity energy expenditure (PAEE) and assess CRF. RESULTS: Mean (range) habitual PAEE was 60 (37-116) kJ day-1 kg-1 , and CRF was 43 (32-54) mL O2 min-1 kg-1 . The jumping-dance activity was performed at an absolute HR of 122 (83-169) beats·min-1 , and PAEE of 283 (84-484) J min-1 kg-1 or 42 (18-75)% when expressed relative to CRF. The total PAEE for the session was 17 (range 5-29) kJ kg-1 , ~28% of the daily total. Self-reported engagement in habitual jumping-dance frequency was 3.8 (1-7) sessions/week, with a total duration of 2.1 (0.5-6.0) h/session. CONCLUSIONS: Intensity during traditional jumping-dance activity was moderate, but on average sevenfold higher than habitual physical activity. These rituals are common, and can make a substantial contribution to overall physical activity in Maasai men, and thus be promoted as a culture-specific activity to increase energy expenditure and maintain good health in this population.

Resting heart rate is a population-level biomarker of cardiorespiratory fitness: The Fenland Study.

INTRODUCTION: Few large studies have evaluated the relationship between resting heart rate (RHR) and cardiorespiratory fitness. Here we examine cross-sectional and longitudinal relationships between RHR and fitness, explore factors that influence these relationships, and demonstrate the utility of RHR for remote population monitoring. METHODS: In cross-sectional analyses (The UK Fenland Study: 5,722 women, 5,143 men, aged 29-65y), we measured RHR (beats per min, bpm) while seated, supine, and during sleep. Fitness was estimated as maximal oxygen consumption (ml⋅min-1⋅kg-1) from an exercise test. Associations between RHR and fitness were evaluated while adjusting for age, sex, adiposity, and physical activity. In longitudinal analyses (6,589 participant subsample), we re-assessed RHR and fitness after a median of 6 years and evaluated the association between within-person change in RHR and fitness. During the coronavirus disease-2019 pandemic, we used a smartphone application to remotely and serially measure RHR (1,914 participant subsample, August 2020 to April 2021) and examined differences in RHR dynamics by pre-pandemic fitness level. RESULTS: Mean RHR while seated, supine, and during sleep was 67, 64, and 57 bpm. Age-adjusted associations (beta coefficients) between RHR and fitness were -0.26, -0.29, and -0.21 ml⋅kg-1⋅beat-1 in women and -0.27, -0.31, and -0.19 ml⋅kg-1⋅beat-1 in men. Adjustment for adiposity and physical activity attenuated the RHR-to-fitness relationship by 10% and 50%, respectively. Longitudinally, a 1-bpm increase in supine RHR was associated with a 0.23 ml⋅min-1⋅kg-1 decrease in fitness. During the pandemic, RHR increased in those with low pre-pandemic fitness but was stable in others. CONCLUSIONS: RHR is a valid population-level biomarker of cardiorespiratory fitness. Physical activity and adiposity attenuate the relationship between RHR and fitness.

Shorter sleep among adolescents is associated with lower fruit and vegetable consumption the following day.

BACKGROUND: Insufficient sleep has been associated with weight gain and metabolic dysregulation, with one suggested mechanism being through reduction in diet quality. Experimental evidence supports a causal effect of sleep timings on diet but this may not be applicable to a free-living adolescent population. In this analysis we use daily measures of sleep timings and diet quality, to examine the effect of sleep duration and timing on diet quality the following day among free-living adolescents. METHODS: The ROOTS study is a prospective cohort recruited from secondary schools in Cambridgeshire and Suffolk (UK). Participants (n = 815) at mean age 15.0y (SD 0.3y) completed a diet diary and wore a combined heart rate and accelerometer device over 4 consecutive days. Sleep duration and timing (midpoint) were derived from acceleration and heart rate traces, while daily energy density and fruit and vegetable intake were calculated from dietary data. Analyses were performed at day-level (1815 person-days). Multilevel random effects models were used to test associations between sleep each night and subsequent day diet, with daily sleep and diet measures nested within individuals and schools, and adjusted for day-level and individual-level confounding variables. RESULTS: Adolescents slept a mean of 7.88 hrs (SD 1.10) per night, reporting a mean energy density of 2.12 kcal/g (SD 0.48) and median energy-adjusted daily fruit and vegetable intake of 137.3 g (IQR 130.4). One hour shorter sleep duration was associated with lower intake of fruit and vegetables (-6.42 g, 95%CI -1.84, -10.99) the following day. An association with higher dietary energy density (0.016 kcal/g, 95%CI 0.034, -0.002) the following day was observed but did not reach statistical significance. Sleep timing was not associated with either fruit and vegetable intake (-2.52 g/d, 95%CI -7.66, 2.62) or dietary energy density (-0.001 kcal/g, 95%CI -0.022, 0.020). CONCLUSIONS: Our observational findings from a free-living adolescent population support the experimental evidence for a causal role of sleep on diet, with shorter sleep duration at night leading to a small decrease in diet quality the following day. These findings support experimental evidence to suggest inclusion of sleep duration as one component of interventions designed to improve diet quality and weight status in adolescents.

Descriptive Epidemiology of Cardiorespiratory Fitness in UK Adults: The Fenland Study.

INTRODUCTION: Cardiorespiratory fitness (CRF) is rarely measured in population studies. Most studies of CRF do not examine differences by population subgroups or seasonal trends. We examined how estimated CRF levels vary by anthropometric, sociodemographic, and behavioral characteristics in a population-based cohort of UK adults (the Fenland Study). METHODS: We used a validated submaximal exercise test to obtain CRF estimates (CRF estimated ) in 5976 women and 5316 men, residing in the East of England. CRF estimated was defined as estimated maximal oxygen consumption per kilogram total body mass (V̇O 2 max tbm ) and fat-free mass (V̇O 2 max ffm ). Descriptive statistics were computed across anthropometric and sociodemographic characteristics, and across the year. Progressive multivariable analyses were performed to examine associations with physical activity energy expenditure (PAEE) and body mass index (BMI). RESULTS: Mean ± SD V̇O 2 max tbm was lower in women (35.2 ± 7.5 mL·min -1 ·kg -1 ) than men (41.7 ± 7.3 mL·min -1 ·kg -1 ) but V̇O 2 max ffm was similar (women: 59.2 ± 11.6 mL·min -1 ·kg -1 ; men: 62.0 ± 10.3 mL·min -1 ·kg -1 ). CRF estimated was inversely associated with age but not after adjustment for PAEE. People in more physically demanding jobs were fitter compared with those in sedentary jobs, but this association was attenuated in women and reversed in men after adjustment for total PAEE. Physical activity energy expenditure and BMI were positively associated with CRF estimated at all levels of adjustment when expressed relative to fat-free mass. CRF estimated was 4% higher in summer than in winter among women, but did not differ by season among men. CONCLUSIONS: CRF estimated was inversely associated with age but less steeply than anticipated, suggesting older generations are comparatively fitter than younger generations. Physical activity energy expenditure and BMI were stronger determinants of the variance in CRF estimated than other characteristic including age. This emphasizes the importance of modifiable physical activity behaviors in public health interventions.

Physical activity volume and intensity distribution in relation to bone, lean and fat mass in children.

Considering physical activity (PA) volume and intensity may provide novel insights into the relationships of PA with bone, lean, and fat mass. This study aimed to assess the associations of PA volume, PA intensity distribution, including moderate-to-vigorous PA (MVPA) with total-body-less-head bone mineral content (BMC), lean, and fat mass in children. A population sample of 290 Finnish children (158 females) aged 9-11 years from the Physical Activity and Nutrition in Children (PANIC) Study was studied. PA, including MVPA, was assessed with a combined heart rate and movement sensor, and the uniaxial acceleration was used to calculate average-acceleration (a proxy metric for PA volume) and intensity-gradient (reflective of PA intensity distribution). Linear regression analyzed the associations of PA volume, PA intensity and MVPA with BMC, lean mass, and fat mass assessed by dual-energy X-ray absorptiometry. PA volume was positively associated with BMC in females (unstandardised regression coefficient [ß] = 0.26) and males (ß = 0.47), and positively associated with lean (ß = 7.33) and negatively associated with fat mass in males (ß = -20.62). PA intensity was negatively associated with BMC in males (ß = -0.13). MVPA was positively associated with lean mass in females and males (ß = 0.007 to 0.012), and negatively associated with fat mass in females and males (ß = -0.030 to -0.029). PA volume may be important for improving BMC in females and males, and increasing lean and reducing fat mass in males, whereas MVPA may be important for favorable lean and fat outcomes in both sexes.

Engagement With mHealth COVID-19 Digital Biomarker Measurements in a Longitudinal Cohort Study: Mixed Methods Evaluation.

BACKGROUND: The COVID-19 pandemic accelerated the interest in implementing mobile health (mHealth) in population-based health studies, but evidence is lacking on engagement and adherence in studies. We conducted a fully remote study for ≥6 months tracking COVID-19 digital biomarkers and symptoms using a smartphone app nested within an existing cohort of adults. OBJECTIVE: We aimed to investigate participant characteristics associated with initial and sustained engagement in digital biomarker collection from a bespoke smartphone app and if engagement changed over time or because of COVID-19 factors and explore participants' reasons for consenting to the smartphone substudy and experiences related to initial and continued engagement. METHODS: Participants in the Fenland COVID-19 study were invited to the app substudy from August 2020 to October 2020 until study closure (April 30, 2021). Participants were asked to complete digital biomarker modules (oxygen saturation, body temperature, and resting heart rate [RHR]) and possible COVID-19 symptoms in the app 3 times per week. Participants manually entered the measurements, except RHR that was measured using the smartphone camera. Engagement was categorized by median weekly frequency of completing the 3 digital biomarker modules (categories: 0, 1-2, and ≥3 times per week). Sociodemographic and health characteristics of those who did or did not consent to the substudy and by engagement category were explored. Semistructured interviews were conducted with 35 participants who were purposively sampled by sex, age, educational attainment, and engagement category, and data were analyzed thematically; 63% (22/35) of the participants consented to the app substudy, and 37% (13/35) of the participants did not consent. RESULTS: A total of 62.61% (2524/4031) of Fenland COVID-19 study participants consented to the app substudy. Of those, 90.21% (2277/2524) completed the app onboarding process. Median time in the app substudy was 34.5 weeks (IQR 34-37) with no change in engagement from 0 to 3 months or 3 to 6 months. Completion rates (≥1 per week) across the study between digital biomarkers were similar (RHR: 56,517/77,664, 72.77%; temperature: 56,742/77,664, 73.06%; oxygen saturation: 57,088/77,664, 73.51%). Older age groups and lower managerial and intermediate occupations were associated with higher engagement, whereas working, being a current smoker, being overweight or obese, and high perceived stress were associated with lower engagement. Continued engagement was facilitated through routine and personal motivation, and poor engagement was caused by user error and app or equipment malfunctions preventing data input. From these results, we developed key recommendations to improve engagement in population-based mHealth studies. CONCLUSIONS: This mixed methods study demonstrated both high initial and sustained engagement in a large mHealth COVID-19 study over a ≥6-month period. Being nested in a known cohort study enabled the identification of participant characteristics and factors associated with engagement to inform future applications in population-based health research.

Bidirectional associations of accelerometer-assessed physical activity and sedentary time with physical function among older English adults: the EPIC-Norfolk cohort study.

To develop healthy ageing interventions, longitudinal associations between objectively assessed physical behaviours and physical function need to be better understood. We assessed associations between accelerometer-assessed total physical activity (PA), moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary time and prolonged sedentary bout time, and clinically assessed physical function (grip strength, usual walking speed (UWS), chair stand speed) at two time-points in 3188 participants (≥ 60 years) of the EPIC-Norfolk study. Bidirectional associations were assessed using multivariable linear regression. Over an average of 6.1 years, baseline physical behaviours (greater total PA, MVPA and LPA, and less sedentary time) were associated with better subsequent walking and chair stand speed. Better baseline physical function was associated with better follow-up physical behaviours. There were no bidirectional associations between changes in physical behaviours and grip strength. Improvements in UWS were associated with improvements in all physical behaviours. Improvements in chair stand speed were associated with improvements in total PA, MVPA, and sedentary bout time. Improvements in physical behaviours were associated with improvements in UWS (3.1 cm/s/yr per 100 cpm/yr  total PA, 3.6 cm/s/yr per hr/day/yr MVPA, 2.5 cm/s/yr per hr/day/yr LPA, - 2.9 cm/s/yr per hour/day/yr sedentary time, and - 1.6 cm/s/yr per hr/day/yr prolonged sedentary bout time). Only improvements in total PA, MVPA and sedentary bout time were associated with improvements in chair stand speed. In conclusion, we found bidirectional associations between changes in some physical behaviours and physical function and between baseline physical behaviours and subsequent physical function, highlighting the importance of considering the full range of physical behaviours to promote healthy ageing. Supplementary Information: The online version contains supplementary material available at 10.1007/s10433-022-00733-y.

The association between number and ages of children and the physical activity of mothers: Cross-sectional analyses from the Southampton Women's Survey.

BACKGROUND: Physical activity (PA) has many health benefits, but motherhood is often associated with reduced PA. Considering that ages and number of children may be associated with maternal PA, and that PA patterns may change as children transition to formal schooling, we aimed to investigate the associations between ages and number of children and device-measured maternal PA. METHODS: Cross-sectional analyses were conducted using data from 848 mothers from the Southampton Women's Survey at two different timepoints. Two-level random intercept linear models were used to investigate associations between ages (≤4y(ears) ("younger"), school-aged, both age groups) and number (1, 2, ≥3) of children, and their interaction, and accelerometer-assessed minutes of maternal moderate or vigorous PA (log-transformed MVPA) and light, moderate or vigorous PA (LMVPA). RESULTS: Women with any school-aged children engaged in more MVPA than those with only ≤4y (e.g. % difference in minutes of MVPA [95% confidence interval]: 46.9% [22.0;77.0] for mothers with only school-aged vs only ≤4y). Mothers with multiple children did less MVPA than those with 1 child (e.g. 12.5% [-1.1;24.3] less MVPA for those with 2 children). For mothers with multiple children, those with any school-aged children did less LMVPA than those with only ≤4y (e.g. amongst mothers with 2 children, those with only school-aged children did 34.0 [3.9;64.1] mins/day less LMVPA). For mothers with any ≤4y, those with more children did more LMVPA (e.g. amongst mothers with only ≤4y, those with 2 children did 42.6 [16.4;68.8] mins/day more LMVPA than those with 1 child). CONCLUSIONS: Mothers with multiple children and only children aged ≤4y did less MVPA. Considering that many of these women also did more LMVPA than mothers with fewer or older children, interventions and policies are needed to increase their opportunities for higher intensity PA to maximise health benefits. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04715945.

Physical behaviors and their association with type 2 diabetes mellitus risk markers in urban South African middle-aged adults: an isotemporal substitutionapproach.

INTRODUCTION: To examine the associations between physical behaviors and type 2 diabetes mellitus (T2DM) risk markers in middle-aged South African men and women. RESEARCH DESIGN AND METHODS: This cross-sectional study included middle-aged men (n=403; age: median (IQR), 53.0 (47.8-58.8) years) and women (n=324; 53.4 (49.1-58.1) years) from Soweto, South Africa. Total movement volume (average movement in milli-g) and time (minutes/day) spent in different physical behaviors, including awake sitting/lying, standing, light intensity physical activity (LPA) and moderate-to-vigorous intensity physical activity (MVPA), were determined by combining the signals from two triaxial accelerometers worn simultaneously on the hip and thigh. All participants completed an oral glucose tolerance test, from which indicators of diabetes risk were derived. Associations between physical behaviors and T2DM risk were adjusted for sociodemographic factors and body composition. RESULTS: Total movement volume was inversely associated with measures of fasting and 2-hour glucose and directly associated with insulin sensitivity, basal insulin clearance, and beta-cell function, but these associations were not independent of fat mass, except for basal insulin clearance in women. In men, replacing 30 min of sitting/lying, standing or LPA with the same amount of MVPA time was associated with 1.2-1.4 mmol/L lower fasting glucose and 12.3-13.4 mgl2/mUmin higher insulin sensitivity. In women, substituting sitting/lying with the same amount of standing time or LPA was associated with 0.5-0.8 mmol/L lower fasting glucose. Substituting 30 min sitting/lying with the same amount of standing time was also associated with 3.2 mgl2/mUmin higher insulin sensitivity, and substituting 30 min of sitting/lying, standing or LPA with the same amount of MVPA time was associated with 0.25-0.29 ng/mIU higher basal insulin clearance in women. CONCLUSION: MVPA is important in reducing T2DM risk in men and women, but LPA appears to be important in women only. Longitudinal and intervention studies warranted to provide more specific PA recommendations.

Physical Behaviors and Their Association With Adiposity in Men and Women From a Low-Resourced African Setting.

BACKGROUND: We first explored the associations between physical behaviors and total and regional adiposity. Second, we examined how reallocating time in different physical behaviors was associated with total body fat mass in men and women from a low-income South African setting. METHODS: This cross-sectional study included a sample of 692 participants (384 men and 308 women) aged 41-72 years. Physical behaviors were measured using integrated hip and thigh accelerometry to estimate total movement volume and time spent in sleeping, sitting/lying, standing, light physical activity, and moderate to vigorous physical activity (MVPA). Total body fat mass and regional adiposity were measured using dual-energy X-ray absorptiometry. RESULTS: The associations between total movement volume and measures of regional obesity were mediated by total body adiposity. In men, reallocating 30 minutes of sitting/lying to 30 minutes of MVPA was associated with 1.0% lower fat mass. In women, reallocation of 30 minutes of sitting/lying to MVPA and 30 minutes of standing to MVPA were associated with a 0.3% and 1.4% lower fat mass, respectively. CONCLUSIONS: Although the association between physical behaviors and fat mass differed between men and women, the overall public health message is similar; reallocating sedentary time to MVPA is associated with a reduction in fat mass in both men and women.

Physical Activity Behaviors of a Middle-Age South African Cohort as Determined by Integrated Hip and Thigh Accelerometry.

PURPOSE: Descriptive studies of objectively measured physical activity behaviors in African populations are rare. We developed a method of combining hip and thigh accelerometery signals to quantify and describe physical behaviors in middle-age South African men and women. METHODS: We integrated signals from two triaxial accelerometers worn simultaneously during free-living, in a subsample of the Middle-age Soweto Cohort ( n = 794; mean (SD) age, 53.7 (6.3) yr). Acceleration time series from the accelerometers were combined and movement-related acceleration was derived using Euclidean Norm Minus One (in milligrams), to determine total movement volume (mean Euclidean Norm Minus One) and nonmovement time (<28 m g ), light-intensity physical activity (LPA; 28-85 m g ), and moderate- to vigorous-intensity physical activity (MVPA; >85 m g ); thigh pitch angle and a sleep diary were used to divide nonmovement time (in minutes per day) into sleep, awake sitting/lying, and standing. Sociodemographic factors were self-reported, and weight and height were measured. RESULTS: Mean (SD) wear time was 128 (48) h. Movement volume was 15.0 (6.5) m g for men and 12.2 (3.4) m g for women. Men spent more time in MVPA and sitting/lying, whereas women spent more time standing. Age was inversely associated with movement volume, MVPA, and LPA. When compared with their normal-weight counterparts, men who were overweight or obese spent less time in MVPA, whereas women who were overweight or obese spent less time in LPA and more time sitting/lying. Socioeconomic status was inversely associated with total movement volume, MVPA, and time spent sleeping, and positively associated with time spent sitting/lying, in both men and women. CONCLUSIONS: Integrating signals from hip and thigh accelerometers enables characterization of physical behaviors that can be applied in an African population.

Associations between abdominal adiposity, body size and objectively measured physical activity in infants from Soweto, South Africa.

OBJECTIVES: Considering the importance of the early life period, in conjunction with the increasing prevalence of adiposity and insufficient physical activity already evident in early childhood, this study aimed to determine associations between abdominal adiposity, body size, and objectively measured physical activity in infancy. METHODS: Infants (n = 138, aged 3-24 months) from Soweto, South Africa were recruited to this cross-sectional study. Visceral (VAT) and subcutaneous abdominal fat (SAT) were measured using ultrasound. Physical activity was assessed using accelerometry and analysed at the hourly level. Multilevel linear regression analyses were run with body composition exposures adjusted for age, sex, and length; models with VAT and SAT were also adjusted for total abdominal fat. RESULTS: Mean (SD) age was 11.8 (7.6) months; 86% were normal weight, 7% were underweight and 7% overweight. In linear models, no body composition variable was significantly associated with physical activity. Physical activity was higher with each increasing length tertile (ANOVA p < 0.01); with a mean(95%CI) 29(60-60)mg in the lowest tertile, 39(71-71)mg in the middle tertile, and 50(81-82)mg in the highest tertile. Infants with normal weight had higher mean(95%CI) physical activity (40(70-80)mg) than underweight (34(73-85)mg, p = 0.01) or overweight infants (31(63-78)mg, ANOVA p < 0.01). When also adjusting for total abdominal fat, infants in the lowest SAT tertile had higher physical activity than those in the middle or highest SAT tertiles (p < 0.01). CONCLUSIONS: These findings lend support for higher physical activity as a marker of healthy growth in the first two years of life.

Detecting sleep outside the clinic using wearable heart rate devices.

The adoption of multisensor wearables presents the opportunity of longitudinal monitoring of sleep in large populations. Personalized yet device-agnostic algorithms can sidestep laborious human annotations and objectify cross-cohort comparisons. We developed and tested a heart rate-based algorithm that captures inter- and intra-individual sleep differences in free-living conditions and does not require human input. We evaluated it on four study cohorts using different research- and consumer-grade devices for over 2000 nights. Recording periods included both 24 h free-living and conventional lab-based night-only data. We compared our optimized method against polysomnography, sleep diaries and sleep periods produced through a state-of-the-art acceleration based method. Against sleep diaries, the algorithm yielded a mean squared error of 0.04-0.06 and a total sleep time (TST) deviation of [Formula: see text]2.70 (± 5.74) and 12.80 (± 3.89) minutes, respectively. When evaluated with PSG lab studies, the MSE ranged between 0.06 and 0.11 yielding a time deviation between [Formula: see text]29.07 and [Formula: see text]55.04 minutes. These results showcase the value of this open-source, device-agnostic algorithm for the reliable inference of sleep in free-living conditions and in the absence of annotations.

Association of Accelerometer-Measured Sedentary Accumulation Patterns With Incident Cardiovascular Disease, Cancer, and All-Cause Mortality.

Background Emerging evidence suggests accruing sedentary behavior (SB) in relatively more prolonged periods may convey additional cardiometabolic risks, but few studies have examined prospective outcomes. We examined the association of SB accumulation patterns with incident cardiovascular disease (CVD), cancer, and all-cause mortality (ACM). Methods and Results Data were from 7671 EPIC-Norfolk (European Prospective Investigation Into Cancer and Nutrition-Norfolk) cohort middle- to older-aged adults who wore accelerometers on the right hip for 4 to 7 days. Cox proportional hazards regression modeled associations between 2 measures of SB accumulation and incident CVD, cancer, and ACM. These were usual SB bout duration (the midpoint of each individual's SB accumulation curve, fitted using nonlinear regression) and alpha (hybrid measure of bout frequency and duration, with higher values indicating relatively shorter bouts and fewer long bouts). Models were adjusted for potential confounders, then further for 24-hour time-use compositions. During mean follow-up time of 6.4 years, 339 ACM, 1106 CVD, and 516 cancer events occurred. Elevated rates of incident cancer and ACM were seen with more prolonged SB accumulation (lower alpha, higher usual SB bout duration) but not CVD. For usual SB bout duration and alpha, respectively, the confounder-adjusted hazard ratios per SD of the exposure were 1.12 (95% CI, 1.02-1.23) and 0.88 (95% CI, 0.79-0.98) with incident cancer and 1.16 (95% CI, 1.07-1.26) and 0.80 (95% CI, 0.72-0.89) with ACM (all P<0.05). Further adjustment for 24-hour time use weakened associations with ACM for usual bout duration (hazard ratio, 1.06; 95% CI, 0.97-1.16; P=0.209) and partially for alpha (hazard ratio, 0.87; 95% CI, 0.77-0.99; P=0.029). Conclusions Accruing SB in longer bout durations was associated with higher rates of incident cancer and ACM but not with incident CVD, with some evidence of direct SB accumulation effects independent of 24-hour time use. Findings provide some support for considering SB accumulation as an adjunct target of messaging to "sit less and move more."

Physical activity intensity profiles associated with cardiometabolic risk in middle-aged to older men and women.

Accelerometers provide detailed data about physical activity (PA) across the full intensity spectrum. However, when examining associations with health, results are often aggregated to only a few summary measures [e.g. time spent "sedentary" or "moderate-to-vigorous" intensity PA]. Using multivariate pattern analysis, which can handle collinear exposure variables, we examined associations between the full PA intensity spectrum and cardiometabolic risk (CMR) in a population-based sample of middle-aged to older adults. Participants (n = 3660; mean ± SD age = 69 ± 8y and BMI = 26.7 ± 4.2 kg/m2; 55% female) from the EPIC-Norfolk study (UK) with valid accelerometry (ActiGraph-GT1M) data were included. We used multivariate pattern analysis with partial least squares regression to examine cross-sectional multivariate associations (r) across the full PA intensity spectrum [minutes/day at 0-5000 counts-per-minute (cpm); 5 s epoch] with a continuous CMR score (reflecting waist, blood pressure, lipid, and glucose metabolism). Models were sex-stratified and adjusted for potential confounders. There was a positive (detrimental) association between PA and CMR at 0-12 cpm (maximally-adjusted r = 0.08 (95%CI 0.06-0.10). PA was negatively (favourably) associated with CMR at all intensities above 13 cpm ranging between r = -0.09 (0.07-0.12) at 800-999 cpm and r = -0.14 (0.11-0.16) at 75-99 and 4000-4999 cpm. The strongest favourable associations were from 50 to 800 cpm (r = 0.10-0.12) in men, but from ≥2500 cpm (r = 0.18-0.20) in women; with higher proportions of model explained variance for women (R2 = 7.4% vs. 2.3%). Most of the PA intensity spectrum was beneficially associated with CMR in middle-aged to older adults, even at intensities lower than what has traditionally been considered "sedentary" or "light-intensity" activity. This supports encouragement of PA at almost any intensity in this age-group.

Joint associations between objectively measured physical activity volume and intensity with body fatness: the Fenland study.

BACKGROUND/OBJECTIVES: Physical activity energy expenditure (PAEE) represents the total volume of all physical activity. This can be accumulated as different underlying intensity profiles. Although volume and intensity have been studied in isolation, less is known about their joint association with health. We examined this association with body fatness in a population-based sample of middle-aged British adults. METHODS: In total, 6148 women and 5320 men from the Fenland study with objectively measured physical activity from individually calibrated combined heart rate and movement sensing and DXA-derived body fat percentage (BF%) were included in the analyses. We used linear and compositional isocaloric substitution analysis to examine associations of PAEE and its intensity composition with body fatness. Sex-stratified models were adjusted for socio-economic and dietary covariates. RESULTS: PAEE was inversely associated with body fatness in women (beta = -0.16 (95% CI: -0.17; -0.15) BF% per kJ day-1 kg-1) and men (beta = -0.09 (95% CI: -0.10; -0.08) BF% per kJ day-1 kg-1). Intensity composition was significantly associated with body fatness, beyond that of PAEE; the reallocation of energy to vigorous physical activity (>6 METs) from other intensities was associated with less body fatness, whereas light activity (1.5-3 METs) was positively associated. However, light activity was the main driver of overall PAEE volume, and the relative importance of intensity was marginal compared to that of volume; the difference between PAEE in tertile 1 and 2 in women was associated with 3 percentage-point lower BF%. Higher vigorous physical activity in the same group to the maximum observed value was associated with 1 percentage-point lower BF%. CONCLUSIONS: In this large, population-based cohort study with objective measures, PAEE was inversely associated with body fatness. Beyond the PAEE association, greater levels of intense activity were also associated with lower body fatness. This contribution was marginal relative to PAEE. These findings support current guidelines for physical activity which emphasise that any movement is beneficial, rather than specific activity intensity or duration targets.

Cardiorespiratory fitness assessment using risk-stratified exercise testing and dose-response relationships with disease outcomes.

Cardiorespiratory fitness (CRF) is associated with mortality and cardiovascular disease, but assessing CRF in the population is challenging. Here we develop and validate a novel framework to estimate CRF (as maximal oxygen consumption, VO2max) from heart rate response to low-risk personalised exercise tests. We apply the method to examine associations between CRF and health outcomes in the UK Biobank study, one of the world's largest and most inclusive studies of CRF, showing that risk of all-cause mortality is 8% lower (95%CI 5-11%, 2670 deaths among 79,981 participants) and cardiovascular mortality is 9% lower (95%CI 4-14%, 854 deaths) per 1-metabolic equivalent difference in CRF. Associations obtained with the novel validated CRF estimation method are stronger than those obtained using previous methodology, suggesting previous methods may have underestimated the importance of fitness for human health.