To examine whether improvements in health behaviours are associated with reduced risk of cardiovascular disease (CVD) in individuals with newly-diagnosed type 2 diabetes.
RESEARCH DESIGN AND METHODS
Population-based prospective cohort study of 867 newly diagnosed diabetes patients aged between 40 and 69 years from the treatment phase of the ADDITION-Cambridge study. As the results for all analyses were similar by trial arm, data were pooled and results presented for the whole cohort. Participants were identified via population-based stepwise screening between 2002 and 2006 and underwent assessment of physical activity (EPAQ questionnaire), diet (plasma vitamin C and self-report), and alcohol consumption (self-report) at baseline and one year. A composite primary CVD outcome was examined, comprised of cardiovascular mortality, non-fatal myocardial infarction, nonfatal stroke and revascularisation.
After a mean (SD) follow-up of 5.1 (1.1) years, 6% of the cohort experienced a CVD event (12.2/1000-person years; 95% CI 9.3 to 15.9). CVD risk was inversely related to the number of positive health behaviours changed in the year following diabetes diagnosis. The relative risk (95% CI) for primary CVD event in individuals who did not change any health behavior compared to those who adopted three/four healthy behaviors was 4.17 (1.02 to 17.09), adjusting for age, sex, study group, social class occupation and prescription of cardio-protective medication (ptrend = 0.005).
Cardiovascular disease risk was inversely associated with the number of healthy behaviour changes adopted in the year following diagnosis of diabetes. Interventions that promote early achievement of these goals in newly diagnosed patients could help reduce the burden of diabetes-related morbidity and mortality.
Understanding the determinants of sedentary time during childhood contributes to the development of effective intervention programmes.
To examine family and home-environmental determinants of 1-year change in objectively measured sedentary time after-school and at the weekend.
Participants wore accelerometers at baseline and 1 year later. Longitudinal data for after-school and weekend analyses were available for 854 (41.5%male, mean±SD age 10.2±0.3years) and 718 (41.8%male, age 10.2±0.3years) participants. Information on 26 candidate determinants, including socioeconomic status (SES), availability of electronic media and parental rules for sedentary behaviours was self-reported by children or their parents at baseline. Change in the proportion of registered time spent sedentary was used as the outcome variable in multi-level linear regression models, adjusted for age, sex, body mass index and baseline sedentary time. Simple and multiple models were run and interactions with sex explored.
Children from higher socioeconomic status families exhibited greater increases in after-school (beta; 95% CI for change in % time spent sedentary 1.02; 0.37, 1.66) and weekend (1.42; 0.65, 2.18) sedentary time. Smaller increases in after-school sedentary time were observed in children with more siblings (−1.00; −1.69, −0.30), greater availability of electronic media (−0.81; −1.29, −0.33) and, for boys, more frequent family visits to the park (−1.89; −3.28, −0.51) and family participation in sport (−1.28; −2.54, −0.02). Greater maternal weekend screen-time (0.45; 0.08, 0.83) and, in girls, greater parental restriction on playing outside (0.91; 0.08, 1.74) were associated with larger increases in weekend sedentary time. The analytical sample was younger, more likely to be female, had lower BMI and was of higher SES than the original baseline sample.
Intervention strategies aimed at reducing parents’ weekend screen-time, increasing family participation in sports or recreation (boys) and promoting freedom to play outside (girls) may contribute towards preventing the age-related increase in sedentary time.
A healthy diet is an integral component of successful diabetes management. However, the comparative importance of adopting a healthy diet for cardiovascular risk factor reduction over and above medication use among newly diagnosed diabetes patients remains unclear.
We computed a dietary score consistent with American Diabetes Association and Diabetes UK recommendations in 574 newly diagnosed diabetes patients by summing standardised values for the intake of total energy, saturated fat, sodium, fibre and plasma vitamin C. In linear regression analyses, stratified by cardio-protective medication use (yes/no), we quantified the comparative longitudinal associations of baseline diet and change in diet over 1-year with change in blood pressure, HbA1c and lipids.
Baseline diet was generally not predictive of change in cardiovascular risk factor levels at 1-year. In contrast, dietary change over 1-year among patients prescribed and not prescribed cardio-protective medication after baseline was associated with comparative (p-interaction all ≥0.95) reductions in diastolic blood pressure (−2.38 vs. −2.93 mmHg, respectively) and triglycerides (−0.31 vs. −0.21 mmol/l, respectively), independent of potential confounding factors and change from baseline to follow-up in physical activity and smoking status.
Modest dietary change over the first year following diagnosis of diabetes was associated with reductions in blood pressure and triglycerides, over and above the effects of cardio-protective medication. Our findings support the notion that dietary change should be viewed as an integral component of successful diabetes self-management, irrespective of medication use.
Diabetes Mellitus, Type 2; Diet; Medication; Cardiovascular risk; Prevention
To evaluate the incidence and relative risk of type 2 diabetes defined by the newly proposed HbA1c diagnostic criteria in groups categorized by different baseline HbA1c levels.
RESEARCH DESIGN AND METHODS
Using data from the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort with repeat HbA1c measurements, we estimated the prevalence of known and previously undiagnosed diabetes at baseline (baseline HbA1c ≥6.5%) and the incidence of diabetes over 3 years. We also examined the incidence and corresponding odds ratios (ORs) by different levels of baseline HbA1c. Incident diabetes was defined clinically (self-report at follow-up, prescribed diabetes medication, or inclusion on a diabetes register) or biochemically (HbA1c ≥6.5% at the second health assessment), or both.
The overall prevalence of diabetes was 4.7%; 41% of prevalent cases were previously undiagnosed. Among 5,735 participants without diabetes at baseline (identified clinically or using HbA1c criteria, or both), 72 developed diabetes over 3 years (1.3% [95% CI 1.0–1.5]), of which 49% were identified using the HbA1c criteria. In 6% of the total population, the baseline HbA1c was 6.0–6.4%; 36% of incident cases arose in this group. The incidence of diabetes in this group was 15 times higher than in those with a baseline HbA1c of <5.0% (OR 15.5 [95% CI 7.2–33.3]).
The cumulative incidence of diabetes defined using a newly proposed HbA1c threshold in this middle-aged British cohort was 1.3% over 3 years. Targeting interventions to individuals with an HbA1c of 6.0–6.4% might represent a feasible preventive strategy, although complementary population-based preventive strategies are also needed to reduce the growing burden of diabetes.
Intensive treatment of multiple cardiovascular risk factors can halve mortality among people with established type 2 diabetes. We investigated the effect of early multifactorial treatment after diagnosis by screening.
In a pragmatic, cluster-randomised, parallel-group trial done in Denmark, the Netherlands, and the UK, 343 general practices were randomly assigned screening of registered patients aged 40–69 years without known diabetes followed by routine care of diabetes or screening followed by intensive treatment of multiple risk factors. The primary endpoint was first cardiovascular event, including cardiovascular mortality and morbidity, revascularisation, and non-traumatic amputation within 5 years. Patients and staff assessing outcomes were unaware of the practice's study group assignment. Analysis was done by intention to treat. This study is registered with ClinicalTrials.gov, number NCT00237549.
Primary endpoint data were available for 3055 (99·9%) of 3057 screen-detected patients. The mean age was 60·3 (SD 6·9) years and the mean duration of follow-up was 5·3 (SD 1·6) years. Improvements in cardiovascular risk factors (HbA1c and cholesterol concentrations and blood pressure) were slightly but significantly better in the intensive treatment group. The incidence of first cardiovascular event was 7·2% (13·5 per 1000 person-years) in the intensive treatment group and 8·5% (15·9 per 1000 person-years) in the routine care group (hazard ratio 0·83, 95% CI 0·65–1·05), and of all-cause mortality 6·2% (11·6 per 1000 person-years) and 6·7% (12·5 per 1000 person-years; 0·91, 0·69–1·21), respectively.
An intervention to promote early intensive management of patients with type 2 diabetes was associated with a small, non-significant reduction in the incidence of cardiovascular events and death.
National Health Service Denmark, Danish Council for Strategic Research, Danish Research Foundation for General Practice, Danish Centre for Evaluation and Health Technology Assessment, Danish National Board of Health, Danish Medical Research Council, Aarhus University Research Foundation, Wellcome Trust, UK Medical Research Council, UK NIHR Health Technology Assessment Programme, UK National Health Service R&D, UK National Institute for Health Research, Julius Center for Health Sciences and Primary Care, University Medical Center, Utrecht, Novo Nordisk, Astra, Pfizer, GlaxoSmithKline, Servier, HemoCue, Merck.
Data are available on correlates of physical activity in children and adolescents, less is known about the determinants of change. This review aims to systematically review the published evidence regarding determinants of change in physical activity in children and adolescents.
Prospective quantitative studies investigating change in physical activity in children and adolescents aged 4–18 years were identified from seven databases (to November 2010): PubMed, SCOPUS, PsycINFO, Ovid MEDLINE, SPORTDdiscus, Embase, and Web of Knowledge. Study inclusion, quality assessment, and data extraction were independently validated by two researchers. Semi-quantitative results were stratified by age (4–9 years, 10–13 years, and 14–18 years).
Of the 46 studies that were included, 31 used self-reported physical activity; average methodologic quality was 3.2 (SD=1.2), scored 0–5. Of 62 potential determinants identified, 30 were studied more than three times and 14 reported consistent findings (66% of the reported associations were in the same direction). For children aged 4–9 years, girls reported larger declines than boys. Among those aged 10–13 years, higher levels of previous physical activity and self-efficacy resulted in smaller declines. Among adolescents (aged 14–18 years), higher perceived behavioral control, support for physical activity, and self-efficacy were associated with smaller declines in physical activity.
Few of the variables studied were consistently associated with changes in physical activity, although some were similar to those identified in cross-sectional studies. The heterogeneity in study samples, exposure and outcome variables, and the reliance on self-reported physical activity limit conclusions and highlight the need for further research to inform development and targeting of interventions.
Supplemental digital content is available in the text.
The objective of this study is to examine test–retest reliability, criterion validity, and absolute agreement of a self-report, last 7-d sedentary behavior questionnaire (SIT-Q-7d), which assesses total daily sedentary time as an aggregate of sitting/lying down in five domains (meals, transportation, occupation, nonoccupational screen time, and other sedentary time). Dutch (DQ) and English (EQ) versions of the questionnaire were examined.
Fifty-one Flemish adults (ages 39.4 ± 11.1 yr) wore a thigh accelerometer (activPAL3™) and simultaneously kept a domain log for 7 d. The DQ was subsequently completed twice (median test–retest interval: 3.3 wk). Thigh-acceleration sedentary time was log annotated to create comparable domain-specific and total sedentary time variables. Four hundred two English adults (ages 49.6 ± 7.3 yr) wore a combined accelerometer and HR monitor (Actiheart®) for 6 d to objectively measure total sedentary time. The EQ was subsequently completed twice (median test–retest interval: 3.4 wk). In both samples, the questionnaire reference frame overlapped with the criterion measure administration period. All participants had five or more valid days of criterion data, including one or more weekend day.
Test–retest reliability (intraclass correlation coefficient (95% CI)) was fair to good for total sedentary time (DQ: 0.68 (0.50–0.81); EQ: 0.53 (0.44–0.62)) and poor to excellent for domain-specific sedentary time (DQ: from 0.36 (0.10–0.57) (meals) to 0.66 (0.46–0.79) (occupation); EQ: from 0.45 (0.35–0.54) (other sedentary time) to 0.76 (0.71–0.81) (meals)). For criterion validity (Spearman rho), significant correlations were found for total sedentary time (DQ: 0.52; EQ: 0.22; all P <0.001). Compared with domain-specific criterion variables (DQ), modest-to-strong correlations were found for domain-specific sedentary time (from 0.21 (meals) to 0.76 (P < 0.001) (screen time)). The questionnaire generally overestimated sedentary time compared with criterion measures.
The SIT-Q-7d appears to be a useful tool for ranking individuals in large-scale observational studies examining total and domain-specific sitting.
SITTING; ADULT; ACCELEROMETER; LOG; POSTURE; PSYCHOMETRIC
Interventions to promote physical activity have had limited success. One reason may be that inactive adults are unaware that their level of physical activity is inadequate and do not perceive a need to change their behaviour. We aimed to assess awareness of physical activity, defined as the agreement between self-rated and objective physical activity, and to investigate associations with sociodemographic, biological, behavioural, and psychological factors.
We conducted an exploratory, cross-sectional analysis of awareness of physical activity using baseline data collected from 453 participants of the Feedback, Awareness and Behaviour study (Cambridgeshire, UK). Self-rated physical activity was measured dichotomously by asking participants if they believed they were achieving the recommended level of physical activity. Responses were compared to objective physical activity, measured using a combined accelerometer and heart rate monitor (Actiheart®). Four awareness groups were created: overestimators, realistic inactives, underestimators, and realistic actives. Logistic regression was used to assess associations between awareness group and potential correlates.
The mean (standard deviation) age of participants was 47.0 (6.9) years, 44.4% were male, and 65.1% were overweight (body mass index ≥ 25). Of the 258 (57.0%) who were objectively classified as inactive, 130 (50.4%) misperceived their physical activity by incorrectly stating that they were meeting the guidelines (overestimators). In a multivariable logistic regression model adjusted for age and sex, those with a lower body mass index (Odds Ratio (OR) = 0.95, 95% Confidence Interval (CI) = 0.90 to 1.00), higher physical activity energy expenditure (OR = 1.03, 95% CI = 1.00 to 1.06) and self-reported physical activity (OR = 1.13, 95% CI = 1.07 to 1.19), and lower intention to increase physical activity (OR = 0.69, 95% CI = 0.48 to 0.99) and response efficacy (OR = 0.53, 95% CI = 0.31 to 0.91) were more likely to overestimate their physical activity.
Overestimators have more favourable health characteristics than those who are realistic about their inactivity, and their psychological characteristics suggest that they are less likely to change their behaviour. Personalised feedback about physical activity may be an important first step to behaviour change.
Physical activity; Objective measurement; Awareness; Misperception; Barriers; Correlates; Behaviour change; Personalised feedback
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
There is little evidence to inform the targeted treatment of individuals found early in the diabetes disease trajectory.
To describe cardiovascular disease (CVD) risk profiles and treatment of individual CVD risk factors by modelled CVD risk at diagnosis; changes in treatment, modelled CVD risk, and CVD risk factors in the 5 years following diagnosis; and how these are patterned by socioeconomic status.
Design and setting
Cohort analysis of a cluster-randomised trial (ADDITION-Europe) in general practices in Denmark, England, and the Netherlands.
A total of 2418 individuals with screen-detected diabetes were divided into quartiles of modelled 10-year CVD risk at diagnosis. Changes in treatment, modelled CVD risk, and CVD risk factors were assessed at 5 years.
The largest reductions in risk factors and modelled CVD risk were seen in participants who were in the highest quartile of modelled risk at baseline, suggesting that treatment was offered appropriately. Participants in the lowest quartile of risk at baseline had very similar levels of modelled CVD risk at 5 years and showed the least variation in change in modelled risk. No association was found between socioeconomic status and changes in CVD risk factors, suggesting that treatment was equitable.
Diabetes management requires setting of individualised attainable targets. This analysis provides a reference point for patients, clinicians, and policymakers when considering goals for changes in risk factors early in the course of the disease that account for the diverse cardiometabolic profile present in individuals who are newly diagnosed with type 2 diabetes.
cardiovascular diseases; diabetes mellitus, type 2; prevention and control; primary health care; risk assessment; risk factors; treatment heterogeneity
There is a well-established association between type 2 diabetes and non-alcoholic fatty liver disease (NAFLD) secondary to excess accumulation of intrahepatic lipid (IHL), but the mechanistic basis for this association is unclear. Emerging evidence suggests that in addition to being associated with insulin resistance, NAFLD may be associated with relative beta-cell dysfunction. We sought to determine the influence of liver fat on hepatic insulin extraction and indices of beta-cell function in a cohort of apparently healthy older white adults.
We performed a cross-sectional analysis of 70 healthy participants in the Hertfordshire Physical Activity Trial (39 males, age 71.3 ± 2.4 years) who underwent oral glucose tolerance testing with glucose, insulin and C-Peptide levels measured every 30 minutes over two hours. The areas under the concentration curve for glucose, insulin and C-Peptide were used to quantify hepatic insulin extraction (HIE), the insulinogenic index (IGI), the C-Peptide increment (CGI), the Disposition Index (DI) and Adaptation Index (AI). Visceral fat was quantified with magnetic resonance (MR) imaging and IHL with MR spectroscopy. Insulin sensitivity was measured with the Oral Glucose Insulin Sensitivity (OGIS) model.
29 of 70 participants (41%) exceeded our arbitrary threshold for NAFLD, i.e. IHL >5.5%. Compared to those with normal IHL, those with NAFLD had higher weight, BMI, waist and MR visceral fat, with lower insulin sensitivity and hepatic insulin extraction. Alcohol consumption, age, HbA1c and alanine aminotransferase (ALT) levels were similar in both groups. Insulin and C-Peptide excursions after oral glucose loading were higher in the NAFLD group, but the CGI and AI were significantly lower, indicating a relative defect in beta-cell function that is only apparent when C-Peptide is measured and when dynamic changes in glucose levels and also insulin sensitivity are taken into account. There was no difference in IGI or DI between the groups.
Although increased IHL was associated with greater insulin secretion, modelled parameters suggested relative beta-cell dysfunction with NAFLD in apparently healthy older adults, which may be obscured by reduced hepatic insulin extraction. Further studies quantifying pancreatic fat content directly and its influence on beta cell function are warranted.
Adaptation index; Beta cell dysfunction; C-peptide-genic index; Disposition index; Hepatic insulin extraction; Insulinogenic index; Intrahepatic lipid; Non-alcoholic fatty liver disease
Promoting physical activity in youth is important for health, but existing physical activity interventions have had limited success. We aimed to inform intervention design by i) describing drop-out, continuation and uptake of specific activities over the transition to adolescence; and ii) examining Variety (number of different activities/week) and Frequency (number of activity session/week) of activity participation and their associations with changes in objectively measured physical activity from childhood to adolescence.
At age 10.2±0.3 and 14.2±0.3 years, 319 children in the SPEEDY study (46% boys) wore GT1M Actigraph accelerometers for 7 days and provided self-reported participation (never, once, 2 to 3 times or four or more times, over the last 7 days) in 23 leisure-time activities. Associations of change in moderate-to-vigorous intensity PA (MVPA) (≥2000 counts/minute) and change in total physical activity (TPA) (average accelerometer counts/minute) with exposure variables Z-score transformed (change in) Variety and Frequency were examined using multilevel linear regression, clustered by school, in simple and adjusted models.
The number of children ever reporting a specific activity ranged from 30 (‘Hockey’) to 279 (‘Running or jogging’). Some activities were susceptible to drop-out (e.g. ‘Skipping’) but others were commonly continued or taken up (e.g. ‘Household chores’). Overall, Variety and Frequency declined (mean±SD ΔVariety −3.1±4.4 activities/week; ΔFrequency −7.2±12.0 session/week). ΔMVPA and ΔTPA were not associated with Variety or Frequency at baseline, nor with ΔVariety or ΔFrequency (p>0.29 in all models).
Popularity of specific activities as well as drop-out, continuation and uptake should be considered in future intervention development. Activities that are commonly continued or taken up may be more valuable to encourage in interventions than those with low participation or high drop-out. We did not find evidence to support the idea that Variety and Frequency may be key elements to include in future interventions.
Complementary strategies to shift risk factor population distributions and target high-risk individuals are required to reduce the burden of type 2 diabetes and cardiovascular disease (CVD).
To examine secular changes in glucose and CVD risk factors over 20 years during an individual and population-based CVD prevention program in Västerbotten County, Sweden.
Population-based health promotion intervention was conducted and annual invitation for individuals turning 40, 50, and 60 years to attend a health assessment, including an oral glucose tolerance test, biochemical measures, and a questionnaire. Data were collected between 1991 and 2010, analyzed in 2012 and available for 120,929 individuals. Linear regression modeling examined age-adjusted differences in CVD risk factor means over time. Data were direct-age-standardized to compare disease prevalence.
Between 1991–1995 and 2006–2010, mean age-adjusted cholesterol (men=−0.53, 95% CI=−0.55, −0.50 mmol/L; women=−0.48, 95% CI=−0.50, −0.45 mmol/L) and systolic blood pressure declined (men=−3.06, 95% CI=−3.43, −2.70 mm Hg; women=−5.27, 95% CI=−5.64, −4.90 mm Hg), with corresponding decreases in the age-standardized prevalence of hypertension and hyperlipidemia. Mean age-adjusted 2-hour plasma glucose (men=0.19, 95% CI=0.15, 0.23 mmol/L; women=0.08, 95% CI=0.04, 0.11 mmol/L) and BMI increased (men=1.12, 95% CI=1.04, 1.21; women=0.65, 95% CI=0.55, 0.75), with increases in the age-standardized prevalence of diabetes and obesity.
These data demonstrate the potential of combined individual- and population-based approaches to CVD risk factor control and highlight the need for additional strategies addressing hyperglycemia and obesity.
To examine associations between mode of travel to non-school destinations and physical activity in schoolchildren.
Analyses of data from SPEEDY, an observational study of 9-10 year old British children. In summer 2007, children reported their usual mode of travel to four destinations (to visit family, friends, the park or the shops) and wore accelerometers for at least three days. Time spent in moderate to vigorous physical activity (MVPA) was computed for the following time segments: daily, after school, weekend and out-of-school. Associations between mode of travel and physical activity were assessed using adjusted two-level multiple regression models stratified by sex.
1859 pupils provided valid data. Boys who used active modes of travel spent significantly more time in MVPA in all time segments than boys who used passive modes. The median daily time spent in MVPA was 87 minutes (IQR 68-106) for active travellers and 76 minutes (IQR 60-93) for passive travellers. In girls, median time spent in MVPA after school was significantly higher in the active (34 minutes (IQR 27-44)) than the passive travellers (29 minutes (IQR 22-37)).
Active travel to non-school destinations is associated with higher overall physical activity levels in 9-10 year old schoolchildren.
Transport; Active travel; Physical activity; School children
Little is known about school environmental factors that promote or inhibit activity, especially from studies using objective measures in large representative samples. We therefore aimed to study associations between activity intensities and physical and social school environmental factors.
A population-based sample of 1908 British children (SPEEDY study), mean age 10.3 years (SD: 0.3), recruited from 92 schools across Norfolk, UK, with valid activity data (assessed with Actigraph accelerometers). Outcome measures were school-based (8am-4pm on weekdays) time (in minutes) spent in sedentary (<100 counts/min), moderate (2000-3999 counts/min) and vigorous (≥4000 counts/min) activity. A total of 40 school physical and social environmental factors were assessed. Multivariable multilevel linear regression analyses adjusted for children’s sex and body mass index were conducted; interactions with sex were investigated.
Availability of a ‘Park and Stride’ scheme was negatively associated with sedentary minutes (−7.74; 95%CI: −14.8;−0.70). Minutes of moderate activity were associated with the availability of a lollypop person (1.33, 95%CI: 0.35;2.62) and objectively-assessed walking provision (1.70, 95%CI: 0.85;2.56). The number of sports facilities of at least medium quality (0.47, 95%CI: 0.16;0.79), not having a policy on physical activity (−2.28, 95%CI: −3.62;−0.95), and, in boys only, provision of pedestrian training (1.89; 95%CI: 0.77;3.01) were associated with minutes of vigorous activity.
Only a small number of school-level factors were associated with children’s objectively-measured physical activity intensity, giving few pointers for potential future intervention efforts. Further research should focus on using objective measures to elucidate what factors may explain the school-level variance in activity levels.
school; physical activity; behaviour; correlates; physical environment; social environment
To assess the association between active travel to school and physical activity (PA) in a large population-based sample of 11-year old children.
Cross-sectional analyses using data from the Avon Longitudinal Study of Parents and Children (Bristol, UK), collected in 2002-2004. The analyses include all children providing valid data on objectively-measured PA (Actigraph accelerometer), and having parent-proxy reported data on travel mode (walk, cycle, public transport, car) and distance to school (N=4688).
43.5% of children regularly walked or cycled to school (i.e. on every or most days). Compared with car travelers, walking to school was associated with 5.98 (95%CI: 3.82-8.14) more minutes of moderate-to-vigorous PA (MVPA) on weekdays in those living 0.5-1 miles from school, and with 9.77 (95%CI: 7.47-12.06) more minutes in those living at 1-5 miles. This equates to 24.6 to 40.2% of the average daily minutes of MVPA. Only modest differences were observed in those living <0.5 mile from school.
Children who regularly walk to school are more active during the week than those travelling by car, especially if the distance is >0.5 mile. Increasing participation in active travel might be a useful part of an overall strategy to increase population PA.
Physical Activity; ALSPAC; school travel; children; walking
We examined the associations between the physical, social and policy environments of schools and adiposity in 9-10 year old children in Norfolk, UK. The relationships between 56 school-level variables and Fat Mass Index (FMI; fat mass (kg)/height(m)2) were investigated among 1724 well characterised children from 92 schools in this cross-sectional study. After stepwise removal of variables from multilevel linear regression models stratified by gender, only three variables were significantly associated with FMI. Among girls, attending a school with more pupils in the year group was associated with lower FMI, and attending a school with better cycle provision was associated with higher FMI. In boys being allowed to eat any food at break-time was associated with higher FMI. There was some evidence of moderation of the relationship between cycle provision and FMI by urban-rural location. These data suggest that few school factors are associated with FMI, and provide limited pointers to inform potential future school-based interventions to reduce obesity.
Obesity; Britain; School; Environment; Fat Mass
The aim of this study was to develop, test, and employ an audit tool to objectively assess the opportunities for physical activity within school environments. A 44 item tool was developed and tested at 92 primary schools in the county of Norfolk, England, during summer term of 2007. Scores from the tool covering 6 domains of facility provision were examined against objectively measured hourly moderate to vigorous physical activity levels in 1868 9-10 year old pupils attending the schools. The tool was found to have acceptable reliability and good construct validity, differentiating the physical activity levels of children attending the highest and lowest scoring schools. The characteristics of school grounds may influence pupil’s physical activity levels.
Physical activity; school environment; children; environmental audit
To assess whether objectively-measured characteristics of the neighbourhood, route and school environments are associated with active commuting to school among children. We also explore whether distance acts as a moderator in this association.
A cross sectional study of 2012 children (899 boys and 1113 girls) aged 9-10 years attending 92 schools in the county of Norfolk, UK. During the summer of 2007 questionnaires were completed by children and parents. Attributes around the home and route to school were assessed using a Geographical Information System. School environments were assessed using a newly developed school audit and via questionnaires completed by head teachers. Data were analysed in 2008.
Almost half of the children usually walked or cycled to school. Children who lived in a more deprived area and whose route to school was direct were less likely to walk or cycle to school, whilst those who had a higher density of roads in their neighbourhood were more likely to walk. Furthermore, children whose routes had a high density of streetlights were less likely to cycle to school. Distance did not moderate the observed associations.
Objectively measured neighbourhood and route factors are associated with walking and cycling to school. However, distance did not moderate the associations found here. Creating environments which are safe, through improving urban design may influence children’s commuting behaviour. Intervention studies are needed to confirm the findings from this observational cross-sectional study.
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
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
The global prevalence of type 2 diabetes is increasing. Effective strategies to address this public health challenge are currently lacking. A number of epidemiological studies have reported associations between low concentrations of 25-hydroxy vitamin D and the incidence of diabetes, but a causal link has not been established. We investigate the effect of vitamin D supplementation on the metabolic status of individuals at increased risk of developing type 2 diabetes.
In a randomised double-blind placebo-controlled trial individuals identified as having a high risk of type 2 diabetes (non-diabetic hyperglycaemia or positive diabetes risk score) are randomised into one of three groups and given 4 doses of either placebo, or 100,000 IU Vitamin D2 (ergocalciferol) or 100,000 IU Vitamin D3 (cholecalciferol) at monthly intervals. The primary outcome measure is the change in glycated haemoglobin level between baseline and 4 months. Secondary outcome measures include blood pressure, lipid levels, apolipoproteins, highly sensitive C-reactive protein, parathyroid hormone (PTH) and safety of supplementation. and C-reactive protein. The trial is being conducted at two sites (London and Cambridge, U.K.) and a total of 342 participants are being recruited.
Trial data examining whether supplementation of vitamin D improves glycaemic status and other metabolic parameters in people at risk of developing type 2 diabetes are sparse. This trial will evaluate the causal role of vitamin D in hyperglycaemia and risk of type 2 diabetes. Specific features of this trial include recruitment of participants from different ethnic groups, investigation of the relative effectiveness and safety of vitamin D2 and D3 and an evidence based approach to determination of the dose of supplementation.
Vitamin D2; Vitamin D3; Placebo; Type 2 diabetes; Randomised; Trial; Intervention
There is limited evidence about predictors of health behaviour change in people with type 2 diabetes. The aim of this study was to assess change in health behaviours over one year and to identify predictors of behaviour change among adults with screen-detected and recently clinically diagnosed diabetes.
ADDITION-Plus was a randomised controlled trial of a behaviour change intervention among 478 patients (40–69 years). Physical activity and diet were measured objectively (physical activity at 1 year) and by self-report at baseline and one year. Associations between baseline predictors and behaviour change were quantified using multivariable linear regression.
Participants increased their plasma vitamin C and fruit intake, reduced energy and fat intake from baseline to follow-up. Younger age, male sex, a smaller waist circumference, and a lower systolic blood pressure at baseline were associated with higher levels of objectively measured physical activity at one year. Greater increases in plasma vitamin C were observed in women (beta-coefficient [95% CI]: beta = −5.52 [−9.81, -1.22]) and in those with screen-detected diabetes (beta = 6.09 [1.74, 10.43]). Younger age predicted a greater reduction in fat (beta = −0.43 [−0.72, -0.13]) and energy intake (beta = −6.62 [−13.2, -0.05]). Patients with screen-detected diabetes (beta = 74.2 [27.92, 120.41]) reported a greater increase in fruit intake. There were no significant predictors of change in self-reported physical activity. Beliefs about behaviour change and diabetes did not predict behaviour change.
Older patients, men and those with a longer duration of diabetes may need more intensive support for dietary change. We recommend that future studies use objective measurement of health behaviours and that researchers add predictors beyond the individual level. Our results support a focus on establishing healthy lifestyle changes early in the diabetes disease trajectory.
Health behaviour; Behaviour change; Predictors; Type 2 diabetes; Newly diagnosed
Factors associated with parental awareness of children’s physical activity (PA) levels have not been explored in preschool-aged children. This paper investigates maternal awareness of preschool-aged children’s PA levels and determined correlates associated with maternal overestimation of PA.
Data from the Southampton Women’s Survey, a UK population-based study, were collected March 2006 through June 2009. Daily minutes of moderate-to-vigorous PA (MVPA) were derived using accelerometry in 478 4-year-old children. Mothers who were realistic or overestimated their child’s PA were identified. Log-binomial regression was used to analyse correlates of maternal overestimation of PA levels in children whose mothers perceived them to be active (n = 438).
40.8% of children were classified as inactive: 89.7% of these were perceived to be active by their mothers (over-estimators). These mothers were more likely to think their child sometimes lacked skills required to be physically active (RR (95% CI) = 1.29(1.03-1.63)) and their child was more likely to attend nursery full-time (RR = 1.53(1.14-2.04)). They were less likely to have older children at home (RR = 0.71(0.56-0.90)).
Almost 90% of mothers of inactive preschool-aged children perceive their child to be active. Nursery-school attendance and having older siblings at home may be important to consider when designing behavioural interventions to increase PA in preschool children.
Physical activity; Awareness; Preschool children