To address major societal challenges and enhance cooperation in research across Europe, the European Commission has initiated and facilitated ‘joint programming’. Joint programming is a process by which Member States engage in defining, developing and implementing a common strategic research agenda, based on a shared vision of how to address major societal challenges that no Member State is capable of resolving independently. Setting up a Joint Programming Initiative (JPI) should also contribute to avoiding unnecessary overlap and repetition of research, and enable and enhance the development and use of standardised research methods, procedures and data management. The Determinants of Diet and Physical Activity (DEDIPAC) Knowledge Hub (KH) is the first act of the European JPI ‘A Healthy Diet for a Healthy Life’. The objective of DEDIPAC is to contribute to improving understanding of the determinants of dietary, physical activity and sedentary behaviours. DEDIPAC KH is a multi-disciplinary consortium of 46 consortia and organisations supported by joint programming grants from 12 countries across Europe. The work is divided into three thematic areas: (I) assessment and harmonisation of methods for future research, surveillance and monitoring, and for evaluation of interventions and policies; (II) determinants of dietary, physical activity and sedentary behaviours across the life course and in vulnerable groups; and (III) evaluation and benchmarking of public health and policy interventions aimed at improving dietary, physical activity and sedentary behaviours. In the first three years, DEDIPAC KH will organise, develop, share and harmonise expertise, methods, measures, data and other infrastructure. This should further European research and improve the broad multi-disciplinary approach needed to study the interactions between multilevel determinants in influencing dietary, physical activity and sedentary behaviours. Insights will be translated into more effective interventions and policies for the promotion of healthier behaviours and more effective monitoring and evaluation of the impacts of such interventions.
Electronic supplementary material
The online version of this article (doi:10.1186/s12966-014-0143-7) contains supplementary material, which is available to authorized users.
Diet; Physical activity; Sedentary behaviour; Joint programming; Lifestyle; Prevention; Measurement; Determinants; Interventions; Policy
Background: Twin and family studies that estimated the heritability of daily physical activity have been limited by poor measurement quality and a small sample size.
Objective: We examined the heritability of daily physical activity and sedentary behavior assessed objectively by using combined heart rate and movement sensing in a large twin study.
Design: Physical activity traits were assessed in daily life for a mean (±SD) 6.7 ± 1.1 d in 1654 twins from 420 monozygotic and 352 dizygotic same-sex twin pairs aged 56.3 ± 10.4 y with body mass index (in kg/m2) of 26.1 ± 4.8. We estimated the average daily movement, physical activity energy expenditure, and time spent in moderate-to-vigorous intensity physical activity and sedentary behavior from heart rate and acceleration data. We used structural equation modeling to examine the contribution of additive genetic, shared environmental, and unique environmental factors to between-individual variation in traits.
Results: Additive genetic factors (ie, heritability) explained 47% of the variance in physical activity energy expenditure (95% CI: 23%, 53%) and time spent in moderate-to-vigorous intensity physical activity (95% CI: 29%, 54%), 35% of the variance in acceleration of the trunk (95% CI: 0%, 44%), and 31% of the variance in the time spent in sedentary behavior (95% CI: 9%, 51%). The remaining variance was predominantly explained by unique environmental factors and random error, whereas shared environmental factors played only a marginal role for all traits with a range of 0–15%.
Conclusions: The between-individual variation in daily physical activity and sedentary behavior is mainly a result of environmental influences. Nevertheless, genetic factors explain up to one-half of the variance, suggesting that innate biological processes may be driving some of our daily physical activity.
Background: Data on objectively measured physical activity are lacking in low- and middle-income countries. The aim of this study was to describe objectively measured overall physical activity and time spent in moderate-to-vigorous physical activity (MVPA) in individuals from the Pelotas (Brazil) birth cohorts, according to weight status, socioeconomic status (SES) and sex.
Methods: All children born in 1982, 1993 and 2004 in hospitals in the city of Pelotas, Brazil, constitute the sampling frame; of these 99% agreed to participate. The most recent follow-ups were conducted between 2010 and 2013. In total, 8974 individuals provided valid data derived from raw triaxial wrist accelerometry. The average acceleration is presented in milli-g (1 mg = 0.001g), and time (min/d) spent in MVPA (>100 mg) is presented in 5- and 10-min bouts.
Results: Mean acceleration in the 1982 (mean age 30.2 years), 1993 (mean age 18.4 years) and 2004 (mean age 6.7 years) cohorts was 35 mg, 39 mg and 60 mg, respectively. Time spent in MVPA was 26 [95% confidence interval (CI) 25; 27], 43 (95% CI 42; 44) and 45 (95% CI 43; 46) min/d in the three cohorts, respectively, using 10-min bouts. Mean MVPA was on average 42% higher when using 5-min bouts. Males were more active than females and physical activity was inversely associated with age of the cohort and SES. Normal-weight individuals were more active than underweight, overweight and obese participants.
Conclusions: Overall physical activity and time spent in MVPA differed by cohort (age), sex, weight status and SES. Higher levels of activity in low SES groups may be explained by incidental physical activity.
Activity monitor; cohort studies; motor activity; movement
To examine the independent and combined association of isometric muscle strength of the abdomen and back and cardiorespiratory fitness (CRF) in youth with indices of glucose metabolism in young adulthood among boys and girls from the European Youth Heart Study.
RESEARCH DESIGN AND METHODS
We used data from a population-based prospective cohort study among youth followed up for up to 12 years (n = 317). In youth, maximal voluntary contractions during isometric back extension and abdominal flexion were determined using a strain-gauge dynamometer and CRF was obtained from a maximal cycle ergometer test. Insulin resistance (homeostasis model assessment of insulin resistance [HOMA-IR]) and β-cell function (homeostasis model assessment of β-cell function [HOMA-B]) were estimated from fasting serum insulin and glucose that were obtained in youth and at follow-up in young adulthood.
For each 1-SD difference in isometric muscle strength (0.16 N/kg) in youth, fasting insulin, HOMA-IR, and HOMA-B in young adulthood changed by −11.3% (95% CI −17.0 to −5.2), −12.2% (−18.2 to −5.7), and −8.9% (−14.4 to −3.0), respectively, in young adulthood after adjustment for CRF and personal lifestyle and demographic factors. Results for CRF were very similar in magnitude, and the magnitude of associations for both exposures was unchanged with additional adjustment for general or abdominal adiposity in youth. Combined associations of muscle strength and CRF with fasting insulin, HOMA-IR, and HOMA-B were additive, and adolescents in the highest sex-specific tertile for both isometric muscle strength and CRF had the lowest levels of these glucose metabolism outcomes.
Increasing muscle strength and CRF should be targets in youth primordial prevention strategies of insulin resistance and β-cell dysfunction.
This difference in how populations living in low-, middle or upper-income countries accumulate daily PA, i.e. patterns and intensity, is an important part in addressing the global PA movement. We sought to characterize objective PA in 2,500 participants spanning the epidemiologic transition. The Modeling the Epidemiologic Transition Study (METS) is a longitudinal study, in 5 countries. METS seeks to define the association between physical activity (PA), obesity and CVD risk in populations of African origin: Ghana (GH), South Africa (SA), Seychelles (SEY), Jamaica (JA) and the US (suburban Chicago).
Baseline measurements of objective PA, SES, anthropometrics and body composition, were completed on 2,500 men and women, aged 25–45 years. Moderate and vigorous PA (MVPA, min/d) on week and weekend days was explored ecologically, by adiposity status and manual labor.
Among the men, obesity prevalence reflected the level of economic transition and was lowest in GH (1.7%) and SA (4.8%) and highest in the US (41%). SA (55%) and US (65%) women had the highest levels of obesity, compared to only 16% in GH. More men and women in developing countries engaged in manual labor and this was reflected by an almost doubling of measured MPVA among the men in GH (45 min/d) and SA (47 min/d) compared to only 28 min/d in the US. Women in GH (25 min/d), SA (21 min/d), JA (20 min/d) and SEY (20 min/d) accumulated significantly more MPVA than women in the US (14 min/d), yet this difference was not reflected by differences in BMI between SA, JA, SEY and US. Moderate PA constituted the bulk of the PA, with no study populations except SA men accumulating > 5 min/d of vigorous PA. Among the women, no sites accumulated >2 min/d of vigorous PA. Overweight/obese men were 22% less likely to engage in manual occupations.
While there is some association for PA with obesity, this relationship is inconsistent across the epidemiologic transition and suggests that PA policy recommendations should be tailored for each environment.
Physical activity patterns; Manual labor; Epidemiologic transition
Sedentary behavior is ubiquitous in modern adults' daily lives and it has been suggested to be associated with incident cancer. However, the results have been inconsistent. In this study, we performed a systematic review and meta-analysis of prospective cohort studies to clarify the association between sedentary behavior and incident cancer.
PubMed and Embase databases were searched up to March 2014. All prospective cohort studies on the association between sedentary behavior and incident cancer were included. The summary relative risks (RRs) with 95% confidence intervals (CIs) were estimated using random effect model.
A total of 17 prospective studies from 14 articles, including a total of 857,581 participants and 18,553 cases, were included in the analysis for sedentary behavior and risk of incident cancer. The overall meta-analysis suggested that sedentary behavior increased risk of cancer (RR = 1.20, 95%CI = 1.12–1.28), with no evidence of heterogeneity between studies (I2 = 7.3%, P = 0.368). Subgroup analyses demonstrated that there were statistical associations between sedentary behavior and some cancer types (endometrial cancer: RR = 1.28, 95% CI = 1.08–1.53; colorectal cancer: RR = 1.30, 95%CI = 1.12–1.49; breast cancer: RR = 1.17, 95%CI = 1.03–1.33; lung cancer: RR = 1.27, 95%CI = 1.06–1.52). However, there was no association of sedentary behavior with ovarian cancer (RR = 1.26, 95%CI = 0.87–1.82), renal cell carcinoma (RR = 1.11, 95%CI = 0.87–1.41) or non-Hodgkin lymphoid neoplasms (RR = 1.09, 95%CI = 0.82–1.43).
The present meta-analysis suggested that prolonged sedentary behavior was independently associated with an increased risk of incident endometrial, colorectal, breast, and lung cancers, but not with ovarian cancer, renal cell carcinoma or non-Hodgkin lymphoid neoplasms.
Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate–increasing and heart rate–decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.
Detailed assessment of physical activity (PA) in older adults is required to comprehensively describe habitual PA-levels in this growing population segment. Current evidence of population PA-levels is predominantly based on self-report.
We examined PA and sedentary behaviour in a nationally representative sample of British people aged 60–64, using individually-calibrated combined heart-rate and movement sensing and a validated questionnaire (EPAQ2), and the socio-demographic and behavioural factors that may explain between-individual variation in PA.
Between 2006–2010, 2224 participants completed EPAQ2 capturing the past year’s activity in four domains (leisure, work, transportation and domestic life) and 1787 participants provided 2–5 days of combined-sensing data. According to objective estimates, median(IQR) physical activity energy expenditure (PAEE) was 33.5 (25.3-42.2) and 35.5 (26.6- 47.3) kJ/kg/day for women and men, respectively. Median (IQR) time spent in moderate-to-vigorous PA (MVPA; >3MET), light-intensity PA (1.5-3 MET) and sedentary (<1.5 MET) was 26.0 (12.3-48.1) min/day, 5.4 (4.2-6.7) h/day and 18.0 (16.6-19.4) h/day, respectively, in women; and 41.0 (18.8-73.0) min/day, 5.2 (4.0-6.5) h/day and 17.9 (16.3-19.4) h/day in men. PAEE and time spent in MVPA were lower and sedentary time was greater in obese individuals, those with poor health, and those with lower educational attainment (women only). Questionnaire-derived PAEE and MVPA tended to have similar patterns of variation across socio-demographic strata. In the whole sample, domestic PA had the greatest relative contribution to total questionnaire-derived PAEE (58%), whereas occupational PA was the main driver among employed participants (54%). Only 2.2% of participants achieved an average of >30 min MVPA per day combined with >60 min strength-training per week.
The use of both self-report and objective monitoring to assess PA in early old age provides important information on the domains of PA, PAEE and time spent at different intensity levels. Our findings suggest PA levels are generally low and observed patterns of variation indicate specific subgroups who might benefit from targeted interventions to increase PA.
Physical activity; Sedentary behaviour; Physical activity questionnaire; Combined sensing; Birth cohort; Old age
Examination of patterns and intensity of physical activity (PA) across cultures where obesity prevalence varies widely provides insight into one aspect of the ongoing epidemiologic transition. The primary hypothesis being addressed is whether low levels of PA are associated with excess weight and adiposity.
We recruited young adults from five countries (500 per country, 2500 total, ages 25–45 years), spanning the range of obesity prevalence. Men and women were recruited from a suburb of Chicago, Illinois, USA; urban Jamaica; rural Ghana; peri-urban South Africa; and the Seychelles. PA was measured using accelerometry and expressed as minutes per day of moderate-to-vigorous activity or sedentary behavior.
Obesity (BMI ≥ 30) prevalence ranged from 1.4% (Ghanaian men) to 63.8% (US women). South African men were the most active, followed by Ghanaian men. Relatively small differences were observed across sites among women; however, women in Ghana accumulated the most activity. Within site-gender sub-groups, the correlation of activity with BMI and other measures of adiposity was inconsistent; the combined correlation across sites was -0.17 for men and -0.11 for women. In the ecological analysis time spent in moderate-to-vigorous activity was inversely associated with BMI (r = -0.71).
These analyses suggest that persons with greater adiposity tend to engage in less PA, although the associations are weak and the direction of causality cannot be inferred because measurements are cross-sectional. Longitudinal data will be required to elucidate direction of association.
Physical activity; Obesity; Epidemiologic transition
The aim of this study was to assess whether or not a theory-based behaviour change intervention delivered by trained and quality-assured lifestyle facilitators can achieve and maintain improvements in physical activity, dietary change, medication adherence and smoking cessation in people with recently diagnosed type 2 diabetes.
An explanatory randomised controlled trial was conducted in 34 general practices in Eastern England (Anglo–Danish–Dutch Study of Intensive Treatment in People with Screen Detected Diabetes in Primary Care-Plus [ADDITION-Plus]). In all, 478 patients meeting eligibility criteria (age 40 to 69 years with recently diagnosed screen or clinically detected diabetes) were individually randomised to receive either intensive treatment (n = 239) or intensive treatment plus a theory-based behaviour change intervention led by a facilitator external to the general practice team (n = 239). Randomisation was central and independent using a partial minimisation procedure to balance stratifiers between treatment arms. Facilitators taught patients skills to facilitate change in and maintenance of key health behaviours, including goal setting, self-monitoring and building habits. Primary outcomes included physical activity energy expenditure (individually calibrated heart rate monitoring and movement sensing), change in objectively measured fruit and vegetable intake (plasma vitamin C), medication adherence (plasma drug levels) and smoking status (plasma cotinine levels) at 1 year. Measurements, data entry and laboratory analysis were conducted with staff unaware of participants’ study group allocation.
Of 475 participants still alive, 444 (93%; intervention group 95%, comparison group 92%) attended 1-year follow-up. There were no significant differences between groups in physical activity (difference: +1.50 kJ kg−1 day−1; 95% CI −1.74, 4.74), plasma vitamin C (difference: −3.84 μmol/l; 95% CI −8.07, 0.38), smoking (OR 1.37; 95% CI 0.77, 2.43) and plasma drug levels (difference in metformin levels: −119.5 μmol/l; 95% CI −335.0, 95.9). Cardiovascular risk factors and self-reported behaviour improved in both groups with no significant differences between groups.
For patients with recently diagnosed type 2 diabetes receiving intensive treatment in UK primary care, a facilitator-led individually tailored behaviour change intervention did not improve objectively measured health behaviours or cardiovascular risk factors over 1 year.
The trial is supported by the Medical Research Council, the Wellcome Trust, National Health Service R&D support funding (including the Primary Care Research and Diabetes Research Networks) and National Institute of Health Research under its Programme Grants for Applied Research scheme. The Primary Care Unit is supported by NIHR Research funds. Bio-Rad provided equipment for HbA1c testing during the screening phase.
Electronic supplementary material
The online version of this article (doi:10.1007/s00125-014-3236-6) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
ADDITION-Plus; Diabetes; General practice; Health behaviour; Randomised trial
Physicians assessing chest pain patients in the emergency department (ED) base the likelihood of acute coronary syndrome (ACS) mainly on ECG, symptom history and blood markers of myocardial injury. Among these, the ECG has been stated to be the most important diagnostic tool. We aimed to analyze the relative contributions of these three diagnostic modalities to the ED physicians’ evaluation of ACS likelihood in clinical practice.
1151 consecutive ED chest pain patients were prospectively included. The ED physician’s subjective assessment of the patient’s likelihood of ACS (obvious ACS, strong, vague or no suspicion of ACS), the symptoms and the ECG were recorded on a special form. The ED TnT value was retrieved from the medical records. Frequency tables and logistic regression models were used to evaluate the contributions of the diagnostic tests to the level of ACS suspicion.
Symptoms determined whether the physician had any suspicion of ACS (odds ratio, OR 526 for symptoms typical compared to not suspicious of ACS) since neither ECG nor TnT contributed significantly (ORs not significantly different from 1) to this assessment. ACS was suspected in only one in ten patients with symptoms not suspicious of ACS. Symptoms were also more important (OR 620 for typical symptoms) than ECG (OR 31 for ischemic ECG) and TnT (OR 3.4 for a positive TnT) for the assessment of obvious ACS/strong suspicion versus vague/no suspicion. Of the patients with ST-elevation on ECG, 71% were considered to have an obvious ACS, as opposed to only 6% of those with symptoms typical of ACS and 10% of those with a positive TnT.
The ED physicians used symptoms as the most important assessment tool and applied primarily the symptoms to determine the level of ACS suspicion and to rule out ACS. The ECG was primarily used to rule in ACS. The TnT level played a minor role for the assessment of ACS likelihood. Further studies regarding ACS prediction based on symptoms may help improve decision-making in ED patients with possible ACS.
Physical activity is of vital importance to older peoples’ health. Physical activity intervention studies with older people often have low recruitment, yet little is known about non-participants.
Patients aged 60–74 years from three UK general practices were invited to participate in a nurse-supported pedometer-based walking intervention. Demographic characteristics of 298 participants and 690 non-participants were compared. Health status and physical activity of 298 participants and 183 non-participants who completed a survey were compared using age, sex adjusted odds ratios (OR) (95% confidence intervals). 15 non-participants were interviewed to explore perceived barriers to participation.
Recruitment was 30% (298/988). Participants were more likely than non-participants to be female (54% v 47%; p = 0.04) and to live in affluent postcodes (73% v 62% in top quintile; p < 0.001). Participants were more likely than non-participants who completed the survey to have an occupational pension OR 2.06 (1.35-3.13), a limiting longstanding illness OR 1.72 (1.05-2.79) and less likely to report being active OR 0.55 (0.33-0.93) or walking fast OR 0.56 (0.37-0.84). Interviewees supported general practice-based physical activity studies, particularly walking, but barriers to participation included: already sufficiently active, reluctance to walk alone or at night, physical symptoms, depression, time constraints, trial equipment and duration.
Gender and deprivation differences suggest some selection bias. However, trial participants reported more health problems and lower activity than non-participants who completed the survey, suggesting appropriate trial selection in a general practice population. Non-participant interviewees indicated that shorter interventions, addressing physical symptoms and promoting confidence in pursuing physical activity, might increase trial recruitment and uptake of practice-based physical activity endeavours.
Physical activity; Non-participation; Primary care; Older people; Recruitment
To assess feasibility and acceptability of a multifaceted, culturally appropriate intervention for preventing obesity in South Asian children, and to obtain data to inform sample size for a definitive trial.
Phase II feasibility study of a complex intervention.
8 primary schools in inner city Birmingham, UK, within populations that are predominantly South Asian.
1090 children aged 6–8 years took part in the intervention. 571 (85.9% from South Asian background) underwent baseline measures. 85.5% (n=488) were followed up 2 years later.
The 1-year intervention consisted of school-based and family-based activities, targeting dietary and physical activity behaviours. The intervention was modified and refined throughout the period of delivery.
Main outcome measures
Acceptability and feasibility of the intervention and of measurements required to assess outcomes in a definitive trial. The difference in body mass index (BMI) z-score between arms was used to inform sample size calculations for a definitive trial.
Some intervention components (increasing school physical activity opportunities, family cooking skills workshops, signposting of local leisure facilities and attending day event at a football club) were feasible and acceptable. Other components were acceptable, but not feasible. Promoting walking groups was neither acceptable nor feasible. At follow-up, children in the intervention compared with the control group were less likely to be obese (OR 0.41; 0.19 to 0.89), and had lower adjusted BMI z-score (−0.15 kg/m2; 95% CI −0.27 to −0.03).
The feasibility study informed components for an intervention programme. The favourable direction of outcome for weight status in the intervention group supports the need for a definitive trial. A cluster randomised controlled trial is now underway to assess the clinical and cost-effectiveness of the intervention.
Trial registration number
Obesity; Children; Prevention
To examine the validity of the Recent Physical Activity Questionnaire (RPAQ) which assesses physical activity (PA) in 4 domains (leisure, work, commuting, home) during past month.
580 men and 1343 women from 10 European countries attended 2 visits at which PA energy expenditure (PAEE), time at moderate-to-vigorous PA (MVPA) and sedentary time were measured using individually-calibrated combined heart-rate and movement sensing. At the second visit, RPAQ was administered electronically. Validity was assessed using agreement analysis.
RPAQ significantly underestimated PAEE in women [median(IQR) 34.1 (22.1, 52.2) vs. 40.6 (32.4, 50.9) kJ/kg/day, 95%LoA: −44.4, 63.4 kJ/kg/day) and in men (43.7 (29.0, 69.0) vs. 45.5 (34.1, 57.6) kJ/kg/day, 95%LoA: −47.2, 101.3 kJ/kg/day]. Using individualised definition of 1MET, RPAQ significantly underestimated MVPA in women [median(IQR): 62.1 (29.4, 124.3) vs. 73.6 (47.8, 107.2) min/day, 95%LoA: −130.5, 305.3 min/day] and men [82.7 (38.8, 185.6) vs. 83.3 (55.1, 125.0) min/day, 95%LoA: −136.4, 400.1 min/day]. Correlations (95%CI) between subjective and objective estimates were statistically significant [PAEE: women, rho = 0.20 (0.15–0.26); men, rho = 0.37 (0.30–0.44); MVPA: women, rho = 0.18 (0.13–0.23); men, rho = 0.31 (0.24–0.39)]. When using non-individualised definition of 1MET (3.5 mlO2/kg/min), MVPA was substantially overestimated (∼30 min/day). Revisiting occupational intensity assumptions in questionnaire estimation algorithms with occupational group-level empirical distributions reduced median PAEE-bias in manual (25.1 kJ/kg/day vs. −9.0 kJ/kg/day, p<0.001) and heavy manual workers (64.1 vs. −4.6 kJ/kg/day, p<0.001) in an independent hold-out sample.
Relative validity of RPAQ-derived PAEE and MVPA is comparable to previous studies but underestimation of PAEE is smaller. Electronic RPAQ may be used in large-scale epidemiological studies including surveys, providing information on all domains of PA.
It is difficult to compare accelerometer-derived estimates of moderate-to-vigorous physical activity (MVPA) between studies due to differences in data processing procedures. We aimed to evaluate the effects of accelerometer processing options on total and bout-accumulated time spent in MVPA in adults.
267 participants from the ProActive Trial provided 1236 days of valid physical activity (PA) data, collected using a 5-s epoch with ActiGraph GT1M accelerometers. We integrated data over 5-s to 60-s epoch lengths (EL) and applied two-level mixed effects regression models to MVPA time, defined using 1500 to 2500 counts/minute (cpm) cut-points (CP) and bout durations (BD) from 1 to 15 min.
Total MVPA time was lower on longer EL and higher CP (47 vs 26 min/day and 26 vs 5 min/day on 1500 vs 2500 cpm on 5-s and 60-s epoch, respectively); this could be approximated as MVPA = exp[2.197 + 0.279*log(CP) + 6.120*log(EL) - 0.869*log(CP)*log(EL)] with an 800 min/day wear-time. In contrast, EL was positively associated with time spent in bout-accumulated MVPA; the approximating equation being MVPA = exp[54.679 - 6.268*log(CP) + 6.387*log(EL) - 10.000*log(BD) - 0.162*log(EL)*log(BD) - 0.626*log(CP)*log(EL) + 1.033*log(CP)*log(BD)]. BD and CP were inversely associated with MVPA, with higher values attenuating the influence of EL.
EL, CP and BD interact to influence estimates of accelerometer-determined MVPA. In general, higher CP and longer BD result in lower MVPA but the direction of association for EL depends on BD. Reporting scaling coefficients for these key parameters across their frequently used ranges would facilitate comparisons of population-level accelerometry estimates of MVPA.
Moderate-to-vigorous; Adults; Measurement; Wear-time; Actigraph; Objective
Few studies have quantified levels of habitual physical activity across the entire intensity range. We aimed to describe variability in total and intensity-specific physical activity levels in UK adolescents across gender, socio-demographic, temporal and body composition strata.
Physical activity energy expenditure and minutes per day (min/d) spent sedentary and in light, moderate, and vigorous intensity physical activity were assessed in 825 adolescents from the ROOTS study (43.5% boys; mean age 15.0 ± 0.30 years), by 4 days of individually calibrated combined heart rate and movement sensing. Measurement days were classified as weekday or weekend and according to the three school terms: summer (April-July), autumn (September-December), and spring (January-March). Gender and age were self-reported and area-level SES determined by postcode data. Body composition was measured by anthropometry and bio-electrical impedance. Variability in physical activity and sedentary time was analysed by linear multilevel modelling, and logistic multilevel regression was used to determine factors associated with physical inactivity (<60 min moderate-to-vigorous intensity physical activity/d).
During awake hours (15.8 ± 0.9 hrs/d), adolescents primarily engaged in light intensity physical activity (517 min/d) and sedentary time (364 min/d). Boys were consistently more physically active and less sedentary than girls, but gender differences were smaller at weekends, as activity levels in boys dropped more markedly when transitioning from weekday to weekend. Boys were more sedentary on both weekend days compared to during the week, whereas girls were more sedentary on Sunday but less sedentary on Saturday. In both genders light intensity physical activity was lower in spring, while moderate physical activity was lower in autumn and spring terms, compared to the summer term; sedentary time was also higher in spring than summer term. Adolescents with higher fatness engaged in less vigorous intensity physical activity. Factors associated with increased odds of physical inactivity were female gender, both weekend days in boys, and specifically Sunday in girls.
Physical activity components vary by gender, temporal factors and body composition in UK adolescents. The available data indicate that in adolescence, girls should be the primary targets of interventions designed to increase physical activity levels.
Energy expenditure; Physical activity intensity; Sedentary time; Activity monitoring; Adolescents
To compare physical activity (PA) subcomponents from EPIC Physical Activity Questionnaire (EPAQ2) and combined heart rate and movement sensing in older adults.
Participants aged 60–64y from the MRC National Survey of Health and Development in Great Britain completed EPAQ2, which assesses self-report PA in 4 domains (leisure time, occupation, transportation and domestic life) during the past year and wore a combined sensor for 5 consecutive days. Estimates of PA energy expenditure (PAEE), sedentary behaviour, light (LPA) and moderate-to-vigorous PA (MVPA) were obtained from EPAQ2 and combined sensing and compared. Complete data were available in 1689 participants (52% women).
EPAQ2 estimates of PAEE and MVPA were higher than objective estimates and sedentary time and LPA estimates were lower [bias (95% limits of agreement) in men and women were 32.3 (−61.5 to 122.6) and 29.0 (−39.2 to 94.6) kJ/kg/day for PAEE; −4.6 (−10.6 to 1.3) and −6.0 (−10.9 to −1.0) h/day for sedentary time; −171.8 (−454.5 to 110.8) and −60.4 (−367.5 to 246.6) min/day for LPA; 91.1 (−159.5 to 341.8) and 55.4 (−117.2 to 228.0) min/day for MVPA]. There were significant positive correlations between all self-reported and objectively assessed PA subcomponents (rho = 0.12 to 0.36); the strongest were observed for MVPA (rho = 0.30 men; rho = 0.36 women) and PAEE (rho = 0.26 men; rho = 0.25 women).
EPAQ2 produces higher estimates of PAEE and MVPA and lower estimates of sedentary and LPA than objective assessment. However, both methodologies rank individuals similarly, suggesting that EPAQ2 may be used in etiological studies in this population.
Little is known about preschool-aged children’s levels of physical activity (PA) over the course of the day. Using time-stamped data, we describe the levels and patterns of PA in a population-based sample of four-year-old British children.
Within the Southampton Women’s Survey the PA levels of 593 4-year-old children (51% female) were measured using (Actiheart) accelerometry for up to 7 days. Three outcome measures: minutes spent sedentary (<20 cpm); in light (LPA: ≥20 – 399 cpm) and in moderate-to-vigorous activity (MVPA: ≥400 cpm) were derived. Average daily activity levels were calculated and then segmented across the day (morning, afternoon and evening). MVPA was log-transformed. Two-level random intercept models were used to analyse associations between activity level and temporal and demographic factors.
Children were active for 67% (mean 568.5 SD 79.5 minutes) of their daily registered time on average, with 88% of active time spent in LPA. All children met current UK guidelines of 180 minutes of daily activity. There were no differences in children’s average daily levels of sedentary activity and LPA by temporal and demographic factors: differences did emerge when activity was segmented across the day. Sex differences were largest in the morning, with girls being more sedentary, spending fewer minutes in LPA and 18% less time in MVPA than boys. Children were more sedentary and less active (LPA and MVPA) in the morning if they attended childcare full-time compared to part-time, and on weekend mornings compared to weekdays. The reverse was true for weekend afternoons and evenings. Children with more educated mothers were less active in the evenings. Children were less sedentary and did more MVPA on summer evenings compared to winter evenings.
Preschool-aged children meet current physical activity guidelines, but with the majority of their active time spent in LPA, investigation of the importance of activity intensity in younger children is needed. Activity levels over the day differed by demographic and temporal factors, highlighting the need to consider temporality in future interventions. Increasing girls’ morning activity and providing opportunities for daytime activity in winter months may be worthwhile.
Most adults do not achieve the 150 minutes weekly of at least moderate intensity activity recommended for health. Adults’ most common physical activity (PA) is walking, light intensity if strolling, moderate if brisker. Pedometers can increase walking; however, most trials have been short-term, have combined pedometer and support effects, and have not reported PA intensity. This trial will investigate whether pedometers, with or without nurse support, can help less active 45–75 year olds to increase their PA over 12 months.
Design: Primary care-based 3-arm randomized controlled trial with 12-month follow-up and health economic and qualitative evaluations.
Participants: Less active 45–75 year olds (n = 993) will be recruited by post from six South West London general practices, maximum of two per household and households randomised into three groups. Step-count and time spent at different PA intensities will be assessed for 7 days at baseline, 3 and 12 months by accelerometer. Questionnaires and anthropometric assessments will be completed.
Intervention: The pedometer-alone group will be posted a pedometer (Yamax Digi-Walker SW-200), handbook and diary detailing a 12-week pedometer-based walking programme, using targets from their baseline assessment. The pedometer-plus-support group will additionally receive three practice nurse PA consultations. The handbook, diary and consultations include behaviour change techniques (e.g., self-monitoring, goal-setting, relapse prevention planning). The control group will receive usual care.
Outcomes: Changes in average daily step-count (primary outcome), time spent sedentary and in at least moderate intensity PA weekly at 12 months, measured by accelerometry. Other outcomes include change in body mass index, body fat, self-reported PA, quality of life, mood and adverse events. Cost-effectiveness will be assessed by the incremental cost of the intervention to the National Health Service and incremental cost per change in step-count and per quality adjusted life year. Qualitative evaluations will explore reasons for trial non-participation and the interventions’ acceptability.
The PACE-UP trial will determine the effectiveness and cost-effectiveness of a pedometer-based walking intervention delivered by post or practice nurse to less active primary care patients aged 45–75 years old. Approaches to minimise bias and challenges anticipated in delivery will be discussed.
Accelerometers; Behaviour change techniques; Cognitive behavioural; Middle-aged adults; Older people; Pedometers; Physical activity; Postal; Practice nurse; Primary care; Walking intervention
Evaluate the predictive validity of ActiGraph energy expenditure equations and the classification accuracy of physical activity intensity cut-points in preschoolers.
Forty children aged 4–6 years (5.3±1.0 years) completed a ∼150-min room calorimeter protocol involving age-appropriate sedentary, light and moderate-to vigorous-intensity physical activities. Children wore an ActiGraph GT3X on the right mid-axillary line of the hip. Energy expenditure measured by room calorimetry and physical activity intensity classified using direct observation were the criterion methods. Energy expenditure was predicted using Pate and Puyau equations. Physical activity intensity was classified using Evenson, Sirard, Van Cauwenberghe, Pate, Puyau, and Reilly, ActiGraph cut-points.
The Pate equation significantly overestimated VO2 during sedentary behaviors, light physical activities and total VO2 (P<0.001). No difference was found between measured and predicted VO2 during moderate-to vigorous-intensity physical activities (P = 0.072). The Puyau equation significantly underestimated activity energy expenditure during moderate-to vigorous-intensity physical activities, light-intensity physical activities and total activity energy expenditure (P<0.0125). However, no overestimation of activity energy expenditure during sedentary behavior was found. The Evenson cut-point demonstrated significantly higher accuracy for classifying sedentary behaviors and light-intensity physical activities than others. Classification accuracy for moderate-to vigorous-intensity physical activities was significantly higher for Pate than others.
Available ActiGraph equations do not provide accurate estimates of energy expenditure across physical activity intensities in preschoolers. Cut-points of ≤25counts⋅15 s−1 and ≥420 counts⋅15 s−1 for classifying sedentary behaviors and moderate-to vigorous-intensity physical activities, respectively, are recommended.
We aimed to quantify the associations between change in objectively measured sedentary and moderate-to-vigorous physical activity (MVPA) times and self-reported television viewing over 6 years and change in a clustered cardiometabolic risk score (CCMR), including and excluding waist circumference (CCMR without adiposity component, CCMRno adip), and its individual components, among the adult children of people with type 2 diabetes.
In 171 adults (mean ± SD age 42.52 ± 6.30 years; 46% men) with a parental history of diabetes (ProActive UK), physical activity accelerometer measures and self-reported television viewing were assessed at baseline and a mean ± SD of 6.27 ± 0.46 years later. Associations between change in sedentary time, MVPA time and television viewing and cardiometabolic risk and mediation by adiposity change were examined by multiple linear regression and the product of coefficients method, respectively.
Greater increases in sedentary time (h/day) were associated with larger increases in clustered cardiometabolic risk (CCMR: 0.08 [95% CI 0.01, 0.15]; CCMRno adip: 0.08 [0.01, 0.16]) and triacylglycerol (0.15 [0.01, 0.29]), independent of baseline sedentary and MVPA times, change in MVPA time and other confounders. No evidence was found for mediation by change in waist circumference and BMI for the associations with CCMRno adip and triacylglycerol. Greater increases in MVPA time (h/day) were associated with larger decreases in waist circumference (−3.86 [−7.58, −0.14]), independently of baseline MVPA and sedentary times, change in sedentary time and other confounders. Television viewing was not independently associated with any of the cardiometabolic outcomes.
Increasing sedentary time is independently related to increasing clustered cardiometabolic risk and triacylglycerol in adults at high risk of developing diabetes. Strategies to prevent diabetes might target reducing sedentary time.
Trial registration ISRCTN61323766
Electronic supplementary material
The online version of this article (doi:10.1007/s00125-013-3102-y) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
Adiposity; Cardiovascular disease risk; Longitudinal study; Moderate-to-vigorous physical activity; Sedentary behaviour; Television viewing
Physical inactivity is responsible for 5.3 million deaths annually worldwide. To measure physical activity energy expenditure, the doubly labeled water (DLW) method is the gold standard. However, questionnaires and accelerometry are more widely used. We compared physical activity measured by accelerometer and questionnaire against total (TEE) and physical activity energy expenditure (PAEE) estimated by DLW.
TEE, PAEE (TEE minus resting energy expenditure) and body composition were measured using the DLW technique in 25 adolescents (16 girls) aged 13 years living in Pelotas, Brazil. Physical activity was assessed using the Actigraph accelerometer and by self-report. Physical activity data from accelerometry and self-report were tested against energy expenditure data derived from the DLW method. Further, tests were done to assess the ability of moderate-to-vigorous intensity physical activity (MVPA) to predict variability in TEE and to what extent adjustment for fat and fat-free mass predicted the variability in TEE.
TEE varied from 1,265 to 4,143 kcal/day. It was positively correlated with physical activity (counts) estimated by accelerometry (rho = 0.57; p = 0.003) and with minutes per week of physical activity by questionnaire (rho = 0.41; p = 0.04). An increase of 10 minutes per day in moderate-to-vigorous intensity physical activity (MVPA) relates to an increase in TEE of 141 kcal/day. PAEE was positively correlated with accelerometry (rho = 0.64; p = 0.007), but not with minutes per week of physical activity estimated by questionnaire (rho = 0.30; p = 0.15). Physical activity by accelerometry explained 31% of the vssariability in TEE. By incorporating fat and fat-free mass in the model, we were able to explain 58% of the variability in TEE.
Objectively measured physical activity significantly contributes to the explained variance in both TEE and PAEE in Brazilian youth. Independently, body composition also explains variance in TEE, and should ideally be taken into account when using accelerometry to predict energy expenditure values.
To assess adolescent PA awareness and investigate associations with biological and psychosocial factors.
Cross-sectional from November 2005 to July 2007 (ROOTS study).
Population-based sample recruited via Cambridgeshire and Suffolk schools (UK).
N=799 (44% male, 14.5±0.5 years).
Self-rated PA perception, self-reported psychosocial factors, measured anthropometry.
PA measured using accelerometry over five days. ‘Inactive’ defined as accelerometry-measured <60 min/day of at least moderate PA (MVPA). Associations between awareness (agreement between self-rated and accelerometry-measured active/inactive) and potential correlates investigated using multinomial logistic regression.
70% of adolescents were inactive (81% of girls, 56% of boys, OR(95% CI) 3.41(2.41, 4.82)). 53% of all girls (63% of inactive girls) and 34% of all boys (60% of inactive boys) inaccurately rated themselves as active (over-estimators). Compared to girls accurately describing themselves as inactive (29%), girl over-estimators had lower fat mass (OR(95% CI) 0.84(0.70, 0.99)), higher SES (high vs. low 2.4(1.07, 5.32)), reported more parent-support (1.57(1.12, 2.22)) and better family relationships (0.25(0.09, 0.67)). Amongst boys accurately describing themselves as inactive (22%), over-estimators had lower fat mass (0.86(0.77, 0.96)) reported more peer-support (1.75(1.32, 2.30)) and less teasing (0.75(0.61, 0.92)).
A substantial number of adolescents believe themselves to be more physically active than they really are. They maybe unaware of potential health risks, and may be unlikely to participate in PA promotion programs. Increasing information of PA health benefits beyond weight control might help encourage behavior change.
Physical activity; perception; awareness; correlates; psychosocial
Data on the combined associations between physical activity and sedentary time with cardio-metabolic risk factors in healthy children is sparse.
To examine the independent and combined associations between objectively measured time in moderate and vigorous intensity physical activity and sedentary time with cardio-metabolic risk factors.
DESIGN, SETTING AND PARTICIPANTS
Pooled data from 14 studies collected between 1998 and 2009 comprising 20,871 children (4-18 years) from the International Children’s Accelerometry Database was used. Time spent in moderate and vigorous physical activity and sedentary time was measured using accelerometry after reanalysing raw data files. The independent associations between time in moderate and vigorous physical activity and sedentary time with outcomes were examined using meta-analysis. In combined analyses, participants were stratified by tertiles of time spent in moderate and vigorous physical activity and tertiles of sedentary time.
MAIN OUTCOME MEASURES
Waist circumference, systolic blood pressure, fasting triglycerides, HDL-Cholesterol and insulin.
Children accumulated 354±96 min/d and 30±21 min/d sedentary and in MVPA, respectively. Time in moderate and vigorous physical activity was significantly associated with all cardio-metabolic outcomes independent of sex, age, monitor wear time, time spent sedentary and waist circumference (when waist circumference was not the outcome). Sedentary time was not associated with any outcome independent of time in moderate and vigorous physical activity. In the combined analyses, higher levels of moderate and vigorous physical activity were associated with better cardiometabolic risk factors across tertiles of sedentary time. The differences in outcomes between higher and lower moderate and vigorous physical activity were greater the lower the sedentary time. The mean differences in waist circumference between the bottom and top tertiles of moderate and vigorous physical activity varied between 3.6 cm (95% CI, 2.8-4.3) for high sedentary time to 5.6 (95% CI, 4.8-6.4) for low sedentary time. For systolic blood pressure, the mean differences were 0.7 mm Hg (95% CI, −0.07-1.6) for high sedentary time and 2.5 mm Hg (95% CI, 1.7-3.3) for low sedentary time, and for HDL-cholesterol, −2.6 mg/dL (95% CI, −1.4- −3.9) for high sedentary time and −4.5 mg/dL (95% CI, −3.3- −5.6) for low. Geometric mean differences for insulin and triglycerides showed similar variation. Children in the top tertile of MVPA accumulated >35 minutes/day in this intensity level compared with <18 minutes/day for those in the bottom tertile. In prospective analyses (N=6413, 2.1 yrs follow-up time), neither MVPA nor SED were associated with WC at follow-up, whereas a higher WC at baseline was associated with higher amounts of SED at follow-up.
Higher levels of time spent in MVPA by children and adolescents were associated with better cardio-metabolic risk factors regardless of the amount of time spent sedentary.