Quantifying childhood fat mass: comparison of a novel height-and-weight-based prediction approach with DXA and bioelectrical impedance.

Accurate assessment of childhood adiposity is important both for individuals and populations. We compared fat mass (FM) predictions from a novel prediction model based on height, weight and demographic factors (height-weight equation) with FM from bioelectrical impedance (BIA) and dual-energy X-ray absorptiometry (DXA), using the deuterium dilution method as a reference standard. FM data from all four methods were available for 174 ALSPAC Study participants, seen 2002-2003, aged 11-12-years. FM predictions from the three approaches were compared to the reference standard using; R2, calibration (slope and intercept) and root mean square error (RMSE). R2 values were high from 'height-weight equation' (90%) but lower than from DXA (95%) and BIA (91%). Whilst calibration intercepts from all three approaches were close to the ideal of 0, the calibration slope from the 'height-weight equation' (slope = 1.02) was closer to the ideal of 1 than DXA (slope = 0.88) and BIA (slope = 0.87) assessments. The 'height-weight equation' provided more accurate individual predictions with a smaller RMSE value (2.6 kg) than BIA (3.1 kg) or DXA (3.4 kg). Predictions from the 'height-weight equation' were at least as accurate as DXA and BIA and were based on simpler measurements and open-source equation, emphasising its potential for both individual and population-level FM assessments.

Evaluating an Intervention to Increase Cereal Fiber Intake in Children: A Randomized Controlled Feasibility Trial.

BACKGROUND: Observational studies have shown that higher cereal fiber intake is associated with reduced type 2 diabetes risk. However, it remains uncertain whether this association is causal. OBJECTIVE: This study evaluated the feasibility of an intervention to increase cereal fiber intake in children using breakfast cereals. METHODS: The study was a 2-arm parallel group randomized controlled trial in 9-10-y-old children, who received free supplies of high-fiber breakfast cereals (>3.5 g/portion) or low-fiber breakfast cereals (<1.0 g/portion) to eat daily for 1 mo with behavioral support to promote adherence. Children provided baseline and 1-mo fasting blood samples, physical measurements, and 24-h dietary recalls. The primary outcome was the group difference in change in plasma total alkylresorcinol (AR) concentration; secondary outcomes were group differences in nutrient intakes and adiposity indices. Analyses (complete case and multiple imputation) were conducted by regressing the final AR concentration on baseline AR in models adjusted for sex, ethnicity, age, and school (random effect). RESULTS: Two-hundred seventy-two children were randomly assigned (137 receiving a low-fiber and 135 a high-fiber diet) and 193 (71%) provided fasting blood samples at baseline and follow-up. Among randomized participants, median (IQR) of baseline AR was 43.1 (24.6-85.5) nmol/L and of cereal fiber intake was 4.5 (2.7-6.4) g; 87% of participants reported consuming the cereal on most or all days. Compared with changes in the low-fiber group, the high-fiber group had greater increases in AR (40.7 nmol/L; 95% CI: 21.7, 59.8 nmol/L, P < 0.0001) and in reported cereal fiber intake (2.9g/d; 95% CI: 2.0, 3.7 g; P < 0.0001). There were no appreciable differences in other secondary outcomes. CONCLUSIONS: We have developed a simple and acceptable nutritional intervention that increases markers of daily cereal fiber intake in children. This intervention could be used to test whether increases in cereal fiber intake in children might reduce insulin resistance. This trial was registered at www.isrctn.com as ISRCTN33260236.

Equity-specific effects of interventions to promote physical activity among middle-aged and older adults: results from applying a novel equity-specific re-analysis strategy.

BACKGROUND: Reducing inequalities in physical activity (PA) and PA-associated health outcomes is a priority for public health. Interventions to promote PA may reduce inequalities, but may also unintentionally increase them. Thus, there is a need to analyze equity-specific intervention effects. However, the potential for analyzing equity-specific effects of PA interventions has not yet been sufficiently exploited. The aim of this study was to set out a novel equity-specific re-analysis strategy tried out in an international interdisciplinary collaboration. METHODS: The re-analysis strategy comprised harmonizing choice and definition of outcomes, exposures, socio-demographic indicators, and statistical analysis strategies across studies, as well as synthesizing results. It was applied in a collaboration of a convenience sample of eight European PA intervention studies in adults aged ≥45 years. Weekly minutes of moderate-to-vigorous PA was harmonized as outcome. Any versus no intervention was harmonized as exposure. Gender, education, income, area deprivation, and marital status were harmonized as socio-demographic indicators. Interactions between the intervention and socio-demographic indicators on moderate-to-vigorous PA were analyzed using multivariable linear regression and random-effects meta-analysis. RESULTS: The collaborative experience shows that the novel re-analysis strategy can be applied to investigate equity-specific effects of existing PA interventions. Across our convenience sample of studies, no consistent pattern of equity-specific intervention effects was found. Pooled estimates suggested that intervention effects did not differ by gender, education, income, area deprivation, and marital status. CONCLUSIONS: To exploit the potential for equity-specific effect analysis, we encourage future studies to apply the strategy to representative samples of existing study data. Ensuring sufficient representation of 'hard to reach' groups such as the most disadvantaged in study samples is of particular importance. This will help to extend the limited evidence required for the design and prioritization of future interventions that are most likely to reduce health inequalities.

The rising tide of dementia deaths: triangulation of data from three routine data sources using the Clinical Practice Research Datalink.

BACKGROUND: Dementia is currently the leading certified underlying cause of death in England. We assess how dementia recording on Office for National Statistics death certificates (ONS) corresponded to recording in general practice records (GP) and Hospital Episode Statistics (HES). METHODS: Retrospective study of deaths (2001-15) in 153 English General Practices contributing to the Clinical Practice Research Datalink, with linked ONS and HES records. RESULTS: Of 207,068 total deaths from any cause, 19,627 mentioned dementia on the death certificate with 10,253 as underlying cause; steady increases occurred from 2001 to 2015 (any mention 5.3 to 15.4 %, underlying cause 2.7 to 10 %). Including all data sources, recording of any dementia increased from 13.2 to 28.6 %. In 2015, only 53.8 % of people dying with dementia had dementia recorded on their death certificates. Among deaths mentioning dementia on the death certificate, the recording of a prior diagnosis of dementia in GP and HES rose markedly over the same period. In 2001, only 76.3 % had a prior diagnosis in GP and/or HES records; by 2015 this had risen to 95.7 %. However, over the same period the percentage of all deaths with dementia recorded in GP or HES but not mentioned on the death certificate rose from 7.9 to 13.3 %. CONCLUSIONS: Dementia recording in all data sources increased between 2001 and 2015. By 2015 the vast majority of deaths mentioning dementia had supporting evidence in primary and/or secondary care. However, death certificates were still providing an inadequate picture of the number of people dying with dementia.

The effects of step-count monitoring interventions on physical activity: systematic review and meta-analysis of community-based randomised controlled trials in adults.

BACKGROUND: Step-count monitors (pedometers, body-worn trackers and smartphone applications) can increase walking, helping to tackle physical inactivity. We aimed to assess the effect of step-count monitors on physical activity (PA) in randomised controlled trials (RCTs) amongst community-dwelling adults; including longer-term effects, differences between step-count monitors, and between intervention components. METHODS: Systematic literature searches in seven databases identified RCTs in healthy adults, or those at risk of disease, published between January 2000-April 2020. Two reviewers independently selected studies, extracted data and assessed risk of bias. Outcome was mean differences (MD) with 95% confidence intervals (CI) in steps at follow-up between treatment and control groups. Our preferred outcome measure was from studies with follow-up steps adjusted for baseline steps (change studies); but we also included studies reporting follow-up differences only (end-point studies). Multivariate-meta-analysis used random-effect estimates at different time-points for change studies only. Meta-regression compared effects of different step-count monitors and intervention components amongst all studies at ≤4 months. RESULTS: Of 12,491 records identified, 70 RCTs (at generally low risk of bias) were included, with 57 trials (16,355 participants) included in meta-analyses: 32 provided change from baseline data; 25 provided end-point only. Multivariate meta-analysis of the 32 change studies demonstrated step-counts favoured intervention groups: MD of 1126 steps/day 95%CI [787, 1466] at ≤4 months, 1050 steps/day [602, 1498] at 6 months, 464 steps/day [301, 626] at 1 year, 121 steps/day [- 64, 306] at 2 years and 434 steps/day [191, 676] at 3-4 years. Meta-regression of the 57 trials at ≤4 months demonstrated in mutually-adjusted analyses that: end-point were similar to change studies (+ 257 steps/day [- 417, 931]); body-worn trackers/smartphone applications were less effective than pedometers (- 834 steps/day [- 1542, - 126]); and interventions providing additional counselling/incentives were not better than those without (- 812 steps/day [- 1503, - 122]). CONCLUSIONS: Step-count monitoring leads to short and long-term step-count increases, with no evidence that either body-worn trackers/smartphone applications, or additional counselling/incentives offer further benefit over simpler pedometer-based interventions. Simple step-count monitoring interventions should be prioritised to address the public health physical inactivity challenge. SYSTEMATIC REVIEW REGISTRATION: PROSPERO number CRD42017075810 .

Development of a structured clinical pharmacology review for specialist support for management of complex polypharmacy in primary care.

AIMS: Polypharmacy is widespread and associated with medication-related harms, including adverse drug reactions, medication errors and poor treatment adherence. General practitioners and pharmacists cite limited time and training to perform effective medication reviews for patients with complex polypharmacy, yet no specialist referral mechanism exists. To develop a structured framework for specialist review of primary care patients with complex polypharmacy. METHODS: We developed the clinical pharmacology structured review (CPSR) and stopping by indication tool (SBIT). We tested these in an age-sex stratified sample of 100 people with polypharmacy aged 65-84 years from the Clinical Practice Research Datalink, an anonymised primary care database. Simulated medication reviews based on electronic records using the CPSR and SBIT were performed. We recommended medication changes or review to optimise treatment benefits, reduce risk of harm or reduce treatment burden. RESULTS: Recommendations were made for all patients, for almost half (4.8 ± 2.4) of existing medicines (9.8 ± 3.1), most commonly stopping a drug (1.7 ± 1.3/patient) or reviewing with the patient (1.4 ± 1.2/patient). At least 1 new medicine (0.7 ± 0.9) was recommended for 51% patients. Recommendations predominantly aimed to reduce harm (44%). There was no relationship between number of recommendations made and time since last primary care medication review. We identified a core set of clinical information and investigations (polypharmacy workup) that could inform a standard screen prior to specialist review. CONCLUSION: The CPSR, SBIT and polypharmacy workup could form the basis of a specialist review for patients with complex polypharmacy. Further research is needed to test this approach in patients in general practice.

Longitudinal impact of changes in the residential built environment on physical activity: findings from the ENABLE London cohort study.

BACKGROUND: Previous research has reported associations between features of the residential built environment and physical activity but these studies have mainly been cross-sectional, limiting inference. This paper examines whether changes in a range of residential built environment features are associated with changes in measures of physical activity in adults. It also explores whether observed effects are moderated by socio-economic status. METHODS: Data from the Examining Neighbourhood Activity in Built Living Environments in London (ENABLE London) study were used. A cohort of 1278 adults seeking to move into social, intermediate, and market-rent East Village accommodation was recruited in 2013-2015, and followed up after 2 years. Accelerometer-derived steps (primary outcome), and GIS-derived measures of residential walkability, park proximity and public transport accessibility were obtained both at baseline and follow-up. Daily steps at follow-up were regressed on daily steps at baseline, change in built environment exposures and confounding variables using multilevel linear regression to assess if changes in neighbourhood walkability, park proximity and public transport accessibility were associated with changes in daily steps. We also explored whether observed effects were moderated by housing tenure as a marker of socio-economic status. RESULTS: Between baseline and follow-up, participants experienced a 1.4 unit (95%CI 1.2,1.6) increase in neighbourhood walkability; a 270 m (95%CI 232,307) decrease in distance to their nearest park; and a 0.7 point (95% CI 0.6,0.9) increase in accessibility to public transport. A 1 s.d. increase in neighbourhood walkability was associated with an increase of 302 (95%CI 110,494) daily steps. A 1 s.d. increase in accessibility to public transport was not associated with any change in steps overall, but was associated with a decrease in daily steps amongst social housing seekers (- 295 steps (95%CI - 595, 3), and an increase in daily steps for market-rent housing seekers (410 95%CI -191, 1010) (P-value for effect modification = 0.03). CONCLUSION: Targeted changes in the residential built environment may result in increases in physical activity levels. However, the effect of improved accessibility to public transport may not be equitable, showing greater benefit to the more advantaged.

The effect of moving to East Village, the former London 2012 Olympic and Paralympic Games Athletes' Village, on mode of travel (ENABLE London study, a natural experiment).

BACKGROUND: Interventions to encourage active modes of travel (walking, cycling) may improve physical activity levels, but longitudinal evidence is limited and major change in the built environment / travel infrastructure may be needed. East Village (the former London 2012 Olympic Games Athletes Village) has been repurposed on active design principles with improved walkability, open space and public transport and restrictions on residential car parking. We examined the effect of moving to East Village on adult travel patterns. METHODS: One thousand two hundred seventy-eight adults (16+ years) seeking to move into social, intermediate, and market-rent East Village accommodation were recruited in 2013-2015, and followed up after 2 years. Individual objective measures of physical activity using accelerometry (ActiGraph GT3X+) and geographic location using GPS travel recorders (QStarz) were time-matched and a validated algorithm assigned four travel modes (walking, cycling, motorised vehicle, train). We examined change in time spent in different travel modes, using multilevel linear regresssion models adjusting for sex, age group, ethnicity, housing group (fixed effects) and household (random effect), comparing those who had moved to East Village at follow-up with those who did not. RESULTS: Of 877 adults (69%) followed-up, 578 (66%) provided valid accelerometry and GPS data for at least 1 day (≥540 min) at both time points; half had moved to East Village. Despite no overall effects on physical activity levels, sizeable improvements in walkability and access to public transport in East Village resulted in decreased daily vehicle travel (8.3 mins, 95%CI 2.5,14.0), particularly in the intermediate housing group (9.6 mins, 95%CI 2.2,16.9), and increased underground travel (3.9 mins, 95%CI 1.2,6.5), more so in the market-rent group (11.5 mins, 95%CI 4.4,18.6). However, there were no effects on time spent walking or cycling. CONCLUSION: Designing walkable neighbourhoods near high quality public transport and restrictions on car usage, may offer a community-wide strategy shift to sustainable transport modes by increasing public transport use, and reducing motor vehicle travel.

Effect of pedometer-based walking interventions on long-term health outcomes: Prospective 4-year follow-up of two randomised controlled trials using routine primary care data.

BACKGROUND: Data are lacking from physical activity (PA) trials with long-term follow-up of both objectively measured PA levels and robust health outcomes. Two primary care 12-week pedometer-based walking interventions in adults and older adults (PACE-UP and PACE-Lift) found sustained objectively measured PA increases at 3 and 4 years, respectively. We aimed to evaluate trial intervention effects on long-term health outcomes relevant to walking interventions, using routine primary care data. METHODS AND FINDINGS: Randomisation was from October 2012 to November 2013 for PACE-UP participants from seven general (family) practices and October 2011 to October 2012 for PACE-Lift participants from three practices. We downloaded primary care data, masked to intervention or control status, for 1,001 PACE-UP participants aged 45-75 years, 36% (361) male, and 296 PACE-Lift participants, aged 60-75 years, 46% (138) male, who gave written informed consent, for 4-year periods following randomisation. The following new events were counted for all participants, including those with preexisting diseases (apart from diabetes, for which existing cases were excluded): nonfatal cardiovascular, total cardiovascular (including fatal), incident diabetes, depression, fractures, and falls. Intervention effects on time to first event post-randomisation were modelled using Cox regression for all outcomes, except for falls, which used negative binomial regression to allow for multiple events, adjusting for age, sex, and study. Absolute risk reductions (ARRs) and numbers needed to treat (NNTs) were estimated. Data were downloaded for 1,297 (98%) of 1,321 trial participants. Event rates were low (<20 per group) for outcomes, apart from fractures and falls. Cox hazard ratios for time to first event post-randomisation for interventions versus controls were nonfatal cardiovascular 0.24 (95% confidence interval [CI] 0.07-0.77, p = 0.02), total cardiovascular 0.34 (95% CI 0.12-0.91, p = 0.03), diabetes 0.75 (95% CI 0.42-1.36, p = 0.34), depression 0.98 (95% CI 0.46-2.07, p = 0.96), and fractures 0.56 (95% CI 0.35-0.90, p = 0.02). Negative binomial incident rate ratio for falls was 1.07 (95% CI 0.78-1.46, p = 0.67). ARR and NNT for cardiovascular events were nonfatal 1.7% (95% CI 0.5%-2.1%), NNT = 59 (95% CI 48-194); total 1.6% (95% CI 0.2%-2.2%), NNT = 61 (95% CI 46-472); and for fractures 3.6% (95% CI 0.8%-5.4%), NNT = 28 (95% CI 19-125). Main limitations were that event rates were low and only events recorded in primary care records were counted; however, any underrecording would not have differed by intervention status and so should not have led to bias. CONCLUSIONS: Routine primary care data used to assess long-term trial outcomes demonstrated significantly fewer new cardiovascular events and fractures in intervention participants at 4 years. No statistically significant differences between intervention and control groups were demonstrated for other events. Short-term primary care pedometer-based walking interventions can produce long-term health benefits and should be more widely used to help address the public health inactivity challenge. TRIAL REGISTRATIONS: PACE-UP isrctn.com ISRCTN98538934; PACE-Lift isrctn.com ISRCTN42122561.

Exploring the use of adjusted body mass index thresholds based on equivalent insulin resistance for defining overweight and obesity in UK South Asian children.

BACKGROUND: Body mass index (BMI) overweight/obesity thresholds in South Asian (SA) adults, at equivalent type-2 diabetes risk are lower than for white Europeans (WE). We aimed to define adjusted overweight/obesity thresholds for UK-SA children based on equivalent insulin resistance (HOMA-IR) to WE children. METHODS: In 1138 WE and 1292 SA children aged 9.0-10.9 years, multi-level regression models quantified associations between BMI and HOMA-IR by ethnic group. HOMA-IR levels for WE children were calculated at established overweight/obesity thresholds (at 9.5 years and 10.5 years), based on UK90 BMI cut-offs. Quantified associations in SA children were then used to estimate adjusted SA weight-status thresholds at the calculated HOMA-IR levels. RESULTS: At 9.5 years, current WE BMI overweight and obesity thresholds were 19.2 kg/m2, 21.3 kg/m2 (boys) and 20.0 kg/m2, 22.5 kg/m2 (girls). At equivalent HOMA-IR, SA overweight and obesity thresholds were lower by 2.9 kg/m2 (95% CI: 2.5-3.3 kg/m2) and 3.2 kg/m2 (95% CI: 2.7-3.6 kg/m2) in boys and 3.0 kg/m2 (95% CI: 2.6-3.4 kg/m2) and 3.3 kg/m2 (95% CI: 2.8-3.8 kg/m2) in girls, respectively. At these lower thresholds, overweight/obesity prevalences in SA children were approximately doubled (boys: 61%, girls: 56%). Patterns at 10.5 years were similar. CONCLUSIONS: SA adjusted overweight/obesity thresholds based on equivalent IR were markedly lower than BMI thresholds for WE children, and defined more than half of SA children as overweight/obese.

Longitudinal exposure of English primary care patients to pharmacogenomic drugs: An analysis to inform design of pre-emptive pharmacogenomic testing.

AIMS: To investigate the longitudinal exposure of English primary care patients to pharmacogenomic drugs to inform design of pre-emptive testing. METHODS: Sixty-three drugs were identified with dosing guidelines based on variants of 19 pharmacogenes in the Pharmacogenomics Knowledgebase on 01 September 2018. Prescribing of these pharmacogenomic drugs between 1993 and 2017 was summarised for a sample of 648 141 English patients aged 50-99 years on 01 January 2013, registered with Clinical Practice Research Datalink practices during 2011-12. Exposure of patients to pharmacogenomic drugs retrospectively (2, 10, 20 y) and prospectively (5 y) was described. RESULTS: During 2011-12, 58% of patients were prescribed at least 1 pharmacogenomic drug, increasing to 80% over the previous 20 years. Multiple exposure was common, with 47% patients prescribed ≥2 pharmacogenomic drugs and 7% prescribed ≥5 pharmacogenomic drugs over the next 5 years. The likelihood of exposure to pharmacogenomic drugs increased with age, with 89% patients ≥70 years prescribed at least 1 pharmacogenomic drug over the previous 20 years. Even among those aged 50-59 years, 71% were prescribed at least 1 pharmacogenomic drug over the previous 20 years. The pharmacogenomic drugs prescribed to the most patients were for pain relief, gastroprotection, psychiatric and cardiovascular conditions. Three pharmacogenes (CYP2D6, CYP2C19 and SLCO1B1) accounted for >95% pharmacogenomic drugs prescribed. CONCLUSIONS: In primary care patients, exposure to pharmacogenomic drugs is extremely common, multiplicitous and has commenced by relatively early adulthood. A small number of pharmacogenes account for the majority of drugs prescribed. These findings could inform design of pre-emptive pharmacogenomic testing for implementation in primary care.

Measuring change in trials of physical activity interventions: a comparison of self-report questionnaire and accelerometry within the PACE-UP trial.

BACKGROUND: Few trials have compared estimates of change in physical activity (PA) levels using self-reported and objective PA measures when evaluating trial outcomes. The PACE-UP trial offered the opportunity to assess this, using the self-administered International Physical Activity Questionnaire (IPAQ) and waist-worn accelerometry. METHODS: The PACE-UP trial (N = 1023) compared usual care (n = 338) with two pedometer-based walking interventions, by post (n = 339) or with nurse support (n = 346). Participants wore an accelerometer at baseline and 12 months and completed IPAQ for the same 7-day periods. Main outcomes were weekly minutes, all in ≥10 min bouts as per UK PA guidelines of: i) accelerometer moderate-to-vigorous PA (Acc-MVPA) ii) IPAQ moderate+vigorous PA (IPAQ-MVPA) and iii) IPAQ walking (IPAQ-Walk). For each outcome, 12 month values were regressed on baseline to estimate change. RESULTS: Analyses were restricted to 655 (64%) participants who provided data on all outcomes at baseline and 12 months. Both intervention groups significantly increased their accelerometry MVPA minutes/week compared with control: postal group 42 (95% CI 22, 61), nurse group 43 (95% CI 24, 63). IPAQ-Walk minutes/week also increased: postal 57 (95% CI 2, 112), nurse 43 (95% CI -11, 97) but IPAQ-MVPA minutes/week showed non-significant decreases: postal -11 (95% CI -65, 42), nurse -34 (95% CI -87, 19). CONCLUSIONS: Our results demonstrate the necessity of using a questionnaire focussing on the activities being altered, as with IPAQ-Walk questions. Even then, the change in PA was estimated with far less precision than with accelerometry. Accelerometry is preferred to self-report measurement, minimising bias and improving precision when assessing effects of a walking intervention. TRIAL REGISTRATION: ISRCTN, ISRCTN98538934 . Registered 2 March 2012.

'I'm sure we made it a better study ': Experiences of adults with intellectual disabilities and parent carers of patient and public involvement in a health research study.

Patient and public involvement is considered integral to health research in the United Kingdom; however, studies documenting the involvement of adults with intellectual disabilities and parent carers in health research studies are scarce. Through group interviews, this study explored the perspectives and experiences of a group of adults with intellectual disabilities and a group of parent carers about their collaborative/participatory involvement in a 3-year study which explored the effectiveness of annual health checks for adults with intellectual disabilities. Thematic analysis identified five key themes consistent across both groups; authenticity of participation, working together, generating new outcome measures, dissemination of findings and involvement in future research. Although reported anecdotally rather than originating from the analysis, increased self-confidence is also discussed. The groups' unique perspectives led to insights not previously considered by the research team which led to important recommendations to inform healthcare practice.

Physical activity levels in adults and older adults 3-4 years after pedometer-based walking interventions: Long-term follow-up of participants from two randomised controlled trials in UK primary care.

BACKGROUND: Physical inactivity is an important cause of noncommunicable diseases. Interventions can increase short-term physical activity (PA), but health benefits require maintenance. Few interventions have evaluated PA objectively beyond 12 months. We followed up two pedometer interventions with positive 12-month effects to examine objective PA levels at 3-4 years. METHODS AND FINDINGS: Long-term follow-up of two completed trials: Pedometer And Consultation Evaluation-UP (PACE-UP) 3-arm (postal, nurse support, control) at 3 years and Pedometer Accelerometer Consultation Evaluation-Lift (PACE-Lift) 2-arm (nurse support, control) at 4 years post-baseline. Randomly selected patients from 10 United Kingdom primary care practices were recruited (PACE-UP: 45-75 years, PACE-Lift: 60-75 years). Intervention arms received 12-week walking programmes (pedometer, handbooks, PA diaries) postally (PACE-UP) or with nurse support (PACE-UP, PACE-Lift). Main outcomes were changes in 7-day accelerometer average daily step counts and weekly time in moderate-to-vigorous PA (MVPA) in ≥10-minute bouts in intervention versus control groups, between baseline and 3 years (PACE-UP) and 4 years (PACE-Lift). PACE-UP 3-year follow-up was 67% (681/1,023) (mean age: 59, 64% female), and PACE-Lift 4-year follow-up was 76% (225/298) (mean age: 67, 53% female). PACE-UP 3-year intervention versus control comparisons were as follows: additional steps/day postal +627 (95% CI: 198-1,056), p = 0.004, nurse +670 (95% CI: 237-1,102), p = 0.002; total weekly MVPA in bouts (minutes/week) postal +28 (95% CI: 7-49), p = 0.009, nurse +24 (95% CI: 3-45), p = 0.03. PACE-Lift 4-year intervention versus control comparisons were: +407 (95% CI: -177-992), p = 0.17 steps/day, and +32 (95% CI: 5-60), p = 0.02 minutes/week MVPA in bouts. Neither trial showed sedentary or wear-time differences. Main study limitation was incomplete follow-up; however, results were robust to missing data sensitivity analyses. CONCLUSIONS: Intervention participants followed up from both trials demonstrated higher levels of objectively measured PA at 3-4 years than controls, similar to previously reported 12-month trial effects. Pedometer interventions, delivered by post or with nurse support, can help address the public health physical inactivity challenge. TRIAL REGISTRATIONS: PACE-UP isrctn.com ISRCTN98538934; PACE-Lift isrctn.com ISRCTN42122561.

An open-source tool to identify active travel from hip-worn accelerometer, GPS and GIS data.

BACKGROUND: Increases in physical activity through active travel have the potential to have large beneficial effects on populations, through both better health outcomes and reduced motorized traffic. However accurately identifying travel mode in large datasets is problematic. Here we provide an open source tool to quantify time spent stationary and in four travel modes(walking, cycling, train, motorised vehicle) from accelerometer measured physical activity data, combined with GPS and GIS data. METHODS: The Examining Neighbourhood Activities in Built Living Environments in London study evaluates the effect of the built environment on health behaviours, including physical activity. Participants wore accelerometers and GPS receivers on the hip for 7 days. We time-matched accelerometer and GPS, and then extracted data from the commutes of 326 adult participants, using stated commute times and modes, which were manually checked to confirm stated travel mode. This yielded examples of five travel modes: walking, cycling, motorised vehicle, train and stationary. We used this example data to train a gradient boosted tree, a form of supervised machine learning algorithm, on each data point (131,537 points), rather than on journeys. Accuracy during training was assessed using five-fold cross-validation. We also manually identified the travel behaviour of both 21 participants from ENABLE London (402,749 points), and 10 participants from a separate study (STAMP-2, 210,936 points), who were not included in the training data. We compared our predictions against this manual identification to further test accuracy and test generalisability. RESULTS: Applying the algorithm, we correctly identified travel mode 97.3% of the time in cross-validation (mean sensitivity 96.3%, mean active travel sensitivity 94.6%). We showed 96.0% agreement between manual identification and prediction of 21 individuals' travel modes (mean sensitivity 92.3%, mean active travel sensitivity 84.9%) and 96.5% agreement between the STAMP-2 study and predictions (mean sensitivity 85.5%, mean active travel sensitivity 78.9%). CONCLUSION: We present a generalizable tool that identifies time spent stationary and time spent walking with very high precision, time spent in trains or vehicles with good precision, and time spent cycling with moderate precisionIn studies where both accelerometer and GPS data are available this tool complements analyses of physical activity, showing whether differences in PA may be explained by differences in travel mode. All code necessary to replicate, fit and predict to other datasets is provided to facilitate use by other researchers.

The contribution of physical fitness to individual and ethnic differences in risk markers for type 2 diabetes in children: The Child Heart and Health Study in England (CHASE).

BACKGROUND: The relationship between physical fitness and risk markers for type 2 diabetes (T2D) in children and the contribution to ethnic differences in these risk markers have been little studied. We examined associations between physical fitness and early risk markers for T2D and cardiovascular disease in 9- to 10-year-old UK children. METHODS: Cross-sectional study of 1445 9- to 10-year-old UK children of South Asian, black African-Caribbean and white European origin. A fasting blood sample was used for measurement of insulin, glucose (from which homeostasis model assessment [HOMA]-insulin resistance [IR] was derived), glycated hemoglobin (HbA1c), urate, C-reactive protein (CRP), and lipids. Measurements of blood pressure (BP) and fat mass index (FMI) were made; physical activity was measured by accelerometry. Estimated VO2 max was derived from a submaximal fitness step test. Associations were estimated using multilevel linear regression. RESULTS: Higher VO2 max was associated with lower FMI, insulin, HOMA-IR, HbA1c, glucose, urate, CRP, triglycerides, LDL-cholesterol, BP and higher HDL-cholesterol. Associations were reduced by adjustment for FMI, but those for insulin, HOMA-IR, glucose, urate, CRP, triglycerides and BP remained statistically significant. Higher levels of insulin and HOMA-IR in South Asian children were partially explained by lower levels of VO2max compared to white Europeans, accounting for 11% of the difference. CONCLUSIONS: Physical fitness is associated with risk markers for T2D and CVD in children, which persist after adjustment for adiposity. Higher levels of IR in South Asians are partially explained by lower physical fitness levels compared to white Europeans. Improving physical fitness may provide scope for reducing risks of T2D.

Response bias to a randomised controlled trial of a lifestyle intervention in people at high risk of cardiovascular disease: a cross-sectional analysis.

BACKGROUND: Research evaluating lifestyle interventions for prevention of cardiovascular disease (CVD) may not reach those most at risk. We compared the response rate to a randomised controlled trial (RCT) of a lifestyle intervention by CVD risk, ethnicity and level of deprivation. METHODS: Primary care patients with a QRisk2 score ≥ 20% were invited to participate in a RCT of an intensive lifestyle intervention versus usual care. This cross-sectional analysis compares anonymised data of responders and non-responders with multiple logistic regression, using adjusted odds ratios (AORs) for QRisk2 score, ethnicity, Index of Multiple Deprivation (IMD 2010) quintile, age and sex. RESULTS: From 60 general practices, 8902 patients were invited and 1489 responded. The mean age was 67.3 years and 21.0% were female. Of all patients invited, 69.9% were of white ethnic background, 13.9% ethnic minority backgrounds and 16.2% had no ethnicity data recorded in their medical records. Likelihood of response decreased as QRisk2 score increased (AOR 0.82 per 5 percentage points, 95% CI 0.77-0.88). Black African or Caribbean patients (AOR 0.67; 95% CI 0.45-0.98) and those with missing ethnicity data (AOR 0.55; 95% CI 0.46-0.66) were less likely to respond compared to participants of white ethnicity, but there was no difference in the response rates between south Asian and white ethnicity (AOR 1.08; 95% CI 0.84-1.38). Patients residing in the fourth (AOR 0.70; 95% CI 0.56-0.87) and fifth (AOR 0.52; 95% CI 0.40-0.68) most deprived IMD quintile were less likely to respond compared to the least deprived quintile. CONCLUSIONS: Evaluations of interventions intended for those at high risk of CVD may fail to reach those at highest risk. Hard to reach patient groups may require different recruitment strategies to maximise participation in future trials. Improvements in primary care ethnicity data recording is required to aid understanding of how successfully study samples represent the target population. TRIAL REGISTRATION: ISRCTN, ISRCTN84864870. Registered 15 May 2012, https://doi.org/10.1186/ISRCTN84864870 .

Interpreting population reach of a large, successful physical activity trial delivered through primary care.

BACKGROUND: Failure to include socio-economically deprived or ethnic minority groups in physical activity (PA) trials may limit representativeness and could lead to implementation of interventions that then increase health inequalities. Randomised intervention trials often have low recruitment rates and rarely assess recruitment bias. A previous trial by the same team using similar methods recruited 30% of the eligible population but was in an affluent setting with few non-white residents and was limited to those over 60 years of age. METHODS: PACE-UP is a large, effective, population-based walking trial in inactive 45-75 year-olds that recruited through seven London general practices. Anonymised practice demographic data were available for all those invited, enabling investigation of inequalities in trial recruitment. Non-participants were invited to complete a questionnaire. RESULTS: From 10,927 postal invitations, 1150 (10.5%) completed baseline assessment. Participation rate ratios (95% CI), adjusted for age and gender as appropriate, were lower in men 0.59 (0.52, 0.67) than women, in those under 55 compared with those ≥65, 0.60 (0.51, 0.71), in the most deprived quintile compared with the least deprived 0.52 (0.39, 0.70) and in Asian individuals compared with whites 0.62 (0.50, 0.76). Black individuals were equally likely to participate as white individuals. Participation was also associated with having a co-morbidity or some degree of health limitation. The most common reasons for non-participation were considering themselves as being too active or lack of time. CONCLUSIONS: Conducting the trial in this diverse setting reduced overall response, with lower response in socio-economically deprived and Asian sub-groups. Trials with greater reach are likely to be more expensive in terms of recruitment and gains in generalizability need to be balanced with greater costs. Differential uptake of successful trial interventions may increase inequalities in PA levels and should be monitored. TRIAL REGISTRATION: ISRCTN.com ISRCTN98538934 . Registered 2nd March 2012.

Effect of a Primary Care Walking Intervention with and without Nurse Support on Physical Activity Levels in 45- to 75-Year-Olds: The Pedometer And Consultation Evaluation (PACE-UP) Cluster Randomised Clinical Trial.

BACKGROUND: Pedometers can increase walking and moderate-to-vigorous physical activity (MVPA) levels, but their effectiveness with or without support has not been rigorously evaluated. We assessed the effectiveness of a pedometer-based walking intervention in predominantly inactive adults, delivered by post or through primary care nurse-supported physical activity (PA) consultations. METHODS AND FINDINGS: A parallel three-arm cluster randomised trial was randomised by household, with 12-mo follow-up, in seven London, United Kingdom, primary care practices. Eleven thousand fifteen randomly selected patients aged 45-75 y without PA contraindications were invited. Five hundred forty-eight self-reporting achieving PA guidelines were excluded. One thousand twenty-three people from 922 households were randomised between 2012-2013 to one of the following groups: usual care (n = 338); postal pedometer intervention (n = 339); and nurse-supported pedometer intervention (n = 346). Of these, 956 participants (93%) provided outcome data (usual care n = 323, postal n = 312, nurse-supported n = 321). Both intervention groups received pedometers, 12-wk walking programmes, and PA diaries. The nurse group was offered three PA consultations. Primary and main secondary outcomes were changes from baseline to 12 mo in average daily step-counts and time in MVPA (in ≥10-min bouts), respectively, measured objectively by accelerometry. Only statisticians were masked to group. Analysis was by intention-to-treat. Average baseline daily step-count was 7,479 (standard deviation [s.d.] 2,671), and average time in MVPA bouts was 94 (s.d. 102) min/wk. At 12 mo, mean steps/d, with s.d. in parentheses, were as follows: control 7,246 (2,671); postal 8,010 (2,922); and nurse support 8,131 (3,228). PA increased in both intervention groups compared with the control group; additional steps/d were 642 for postal (95% CI 329-955) and 677 for nurse support (95% CI 365-989); additional MVPA in bouts (min/wk) were 33 for postal (95% CI 17-49) and 35 for nurse support (95% CI 19-51). There were no significant differences between the two interventions at 12 mo. The 10% (1,023/10,467) recruitment rate was a study limitation. CONCLUSIONS: A primary care pedometer-based walking intervention in predominantly inactive 45- to 75-y-olds increased step-counts by about one-tenth and time in MVPA in bouts by about one-third. Nurse and postal delivery achieved similar 12-mo PA outcomes. A primary care pedometer intervention delivered by post or with minimal support could help address the public health physical inactivity challenge. CLINICAL TRIAL REGISTRATION: isrctn.com ISRCTN98538934.

Preventable Emergency Hospital Admissions Among Adults With Intellectual Disability in England.

PURPOSE: Adults with intellectual disabilities experience poorer physical health and health care quality, but there is limited information on the potential for reducing emergency hospital admissions in this population. We describe overall and preventable emergency admissions for adults with vs without intellectual disabilities in England and assess differences in primary care management before admission for 2 common ambulatory care-sensitive conditions (ACSCs). METHODS: We used electronic records to study a cohort of 16,666 adults with intellectual disabilities and 113,562 age-, sex-, and practice-matched adults without intellectual disabilities from 343 English family practices. Incident rate ratios (IRRs) from conditional Poisson regression were analyzed for all emergency and preventable emergency admissions. Primary care management of lower respiratory tract infections and urinary tract infections, as exemplar ACSCs, before admission were compared in unmatched analysis between adults with and without intellectual disabilities. RESULTS: The overall rate for emergency admissions for adults with vs without intellectual disabilities was 182 vs 68 per 1,000 per year (IRR = 2.82; 95% CI, 2.66-2.98). ACSCs accounted for 33.7% of emergency admissions among the former compared with 17.3% among the latter (IRR = 5.62; 95% CI, 5.14-6.13); adjusting for comorbidity, smoking, and deprivation did not fully explain the difference (IRR = 3.60; 95% CI, 3.25-3.99). Although adults with intellectual disability were at nearly 5 times higher risk for admission for lower respiratory tract infections and urinary tract infections, they had similar primary care use, investigation, and management before admission as the general population. CONCLUSIONS: Adults with intellectual disabilities are at high risk for preventable emergency admissions. Identifying strategies for better detecting and managing ACSCs, including lower respiratory and urinary tract infections, in primary care could reduce hospitalizations.