Effects of long-term HbA1c variability on serious infection risks in patients with type 2 diabetes and the influence of age, sex and ethnicity: A cohort study of primary care data.

AIMS: Long-term HbA1c (glycated haemoglobin) variability is associated with micro- and macrovascular complications in Type 2 diabetes (T2D). We explored prospective associations between HbA1c variability and serious infections, and how these vary by HbA1c level, age, sex and ethnicity. METHODS: 411,963 T2D patients in England, aged 18-90, alive on 01/01/2015 in the Clinical Practice Research Datalink with ≥ 4 HbA1c measurements during 2011-14. Poisson regression estimated incidence rate ratios (IRRs) for infections requiring hospitalisation during 2015-19 by HbA1c variability score (HVS) and average level, adjusting for confounders, and stratified by age, sex, ethnicity and average level. Attributable risk fractions (AF) were calculated using reference categories for variability (HVS < 20) and average level (42-48 mmol/mol). RESULTS: An increased infection risk (IRR > 1.2) was seen with even modest variability (HVS ≥ 20, 73 % of T2D patients), but only at higher average levels (≥64 mmol/mol, 27 % patients). Estimated AFs were markedly greater for variability than average level (17.1 % vs. 4.1 %). Associations with variability were greater among older patients, and those with lower HbA1c levels, but not observed among Black ethnicities. CONCLUSIONS: HbA1c variability between T2D patients' primary care visits appears to be associated with more serious infections than average level overall. Well-designed trials could test whether these associations are causal.

A matched cohort study evaluating the risks of infections in people with type 1 diabetes and their associations with glycated haemoglobin.

AIMS: People with type 1 diabetes (T1D) have raised infection rates compared to those without, but how these risks vary by age, sex and ethnicity, or by glycated haemoglobin (HbA1c), remain uncertain. METHODS: 33,829 patients with T1D in Clinical Practice Research Datalink on 01/01/2015 were age-sex-ethnicity matched to two non-diabetes patients. Infections were collated from primary care and linked hospitalisation records during 2015-2019, and incidence rate ratios (IRRs) were estimated versus non-diabetes. For 26,096 people with T1D, with ≥3 HbA1c measurements in 2012-2014, mean and coefficient of variation were estimated, and compared across percentiles. RESULTS: People with T1D had increased risk for infections presenting in primary care (IRR = 1.81, 95%CI 1.77-1.85) and hospitalisations (IRR = 3.37, 3.21-3.53) compared to non-diabetes, slightly attenuated after further adjustment. Younger ages and non-White ethnicities had greater relative risks, potentially explained by higher HbA1c mean and variability amongst people with T1D within these sub-groups. Both mean HbA1c and greater variability were strongly associated with infection risks, but the greatest associations were at the highest mean levels (hospitalisations IRR = 4.09, 3.64-4.59) for >97 versus ≤53 mmol/mol. CONCLUSIONS: Infections are a significant health burden in T1D. Improved glycaemic control may reduce infection risks, while prompter infection treatments may reduce hospital admissions.

Cross-sectional study of the associations between circulating vitamin D concentrations and insulin resistance in children aged 9-10 years of South Asian, black African Caribbean and white European origins.

BACKGROUND: Lower circulating vitamin D 25-hydroxyvitamin D (25(OH)D) concentrations are associated with higher type 2 diabetes risk in adults, although causality remains uncertain. However, associations between 25(OH)D and type 2 diabetes risk markers in children have been little studied, particularly in ethnic minority populations. We examined whether 25(OH)D concentrations were associated with insulin resistance in children and whether lower 25(OH)D concentrations in South Asians and black African Caribbeans could contribute to their higher insulin resistance. METHODS: Cross-sectional study of 4650 UK primary school children aged 9-10 years of predominantly South Asian, black African Caribbean and white European ethnicity. Children had fasting blood measurements of circulating 25(OH)D metabolite concentrations, insulin and glucose. RESULTS: Lower 25(OH)D concentrations were observed in girls, South Asians and black African Caribbeans. In analyses adjusted for age, sex, month, ethnic group and school, circulating 25(OH)D was inversely associated with fasting insulin (-0.38%, 95% CI -0.49% to -0.27%), homoeostasis model assessment (HOMA) insulin resistance (-0.39%, 95% CI -0.50% to -0.28%) and fasting glucose (-0.03%, 95% CI -0.05% to -0.02%) per nmol/L increase in 25(OH)D; associations did not differ between ethnic groups. Ethnic differences in fasting insulin and HOMA insulin resistance (higher among South Asian and black African Caribbeans) were reduced by >40% after adjustment for circulating 25(OH)D concentrations. CONCLUSION: Circulating vitamin D was inversely associated with insulin resistance in all ethnic groups; higher insulin resistance in South Asian and black African children were partly explained by their lower vitamin D levels. Whether vitamin D supplementation can reduce emerging type 2 diabetes risk needs further evaluation.

Multiple imputation approaches for epoch-level accelerometer data in trials.

Clinical trials that investigate physical activity interventions often use accelerometers to measure step count at a very granular level, for example in 5-second epochs. Participants typically wear the accelerometer for a week-long period at baseline, and for one or more week-long follow-up periods after the intervention. The data is aggregated to provide daily or weekly step counts for the primary analysis. Missing data are common as participants may not wear the device as per protocol. Approaches to handling missing data in the literature have defined missingness on the day level using a threshold on daily weartime, which leads to loss of information on the time of day when data are missing. We propose an approach to identifying and classifying missingness at the finer epoch-level and present two approaches to handling missingness using multiple imputation. Firstly, we present a parametric approach which accounts for the number of missing epochs per day. Secondly, we describe a non-parametric approach where missing periods during the day are replaced by donor data from the same person where possible, or data from a different person who is matched on demographic and physical activity-related variables. Our simulation studies show that the non-parametric approach leads to estimates of the effect of treatment that are least biased while maintaining small standard errors. We illustrate the application of these different multiple imputation strategies to the analysis of the 2017 PACE-UP trial. The proposed framework is likely to be applicable to other digital health outcomes and to other wearable devices.

Evaluating Ethnic Variations in the Risk of Infections in People With Prediabetes and Type 2 Diabetes: A Matched Cohort Study.

OBJECTIVE: People living with type 2 diabetes (T2D) are at higher infection risk, but it is unknown how this risk varies by ethnicity or whether the risk is similarly observed in people with nondiabetic hyperglycemia ("prediabetes"). RESEARCH DESIGN AND METHODS: We included 527,151 patients in England with T2D and 273,216 with prediabetes, aged 18-90, and alive on 1 January 2015 on the Clinical Practice Research Datalink. Each was matched to two patients without diabetes or prediabetes on age, sex, and ethnic group. Infections during 2015-2019 were collated from primary care and linked hospitalization records. Infection incidence rate ratios (IRRs) for those with prediabetes or T2D were estimated, unadjusted and adjusted for confounders. RESULTS: People with T2D had increased risk for infections presenting in primary care (IRR 1.51, 95% CI 1.51-1.52) and hospitalizations (IRR 1.91, 1.90-1.93). This was broadly consistent overall within each ethnic group, although younger White T2D patients (age <50) experienced a greater relative risk. Adjustment for socioeconomic deprivation, smoking, and comorbidity attenuated associations, but IRRs remained similar by ethnicity. For prediabetes, a significant but smaller risk was observed (primary care IRR 1.35, 95% CI 1.34-1.36; hospitalization IRR 1.33, 1.31-1.35). These were similar within each ethnicity for primary care infections, but less consistent for infection-related hospitalizations. CONCLUSIONS: The elevated infection risk for people with T2D appears similar for different ethnic groups and is also seen in people with prediabetes. Infections are a substantial cause of ill-health and health service use for people with prediabetes and T2D. This has public health implications with rising prediabetes and diabetes prevalence.

Prevalence of co-morbidity and history of recent infection in patients with neuromuscular disease: A cross-sectional analysis of United Kingdom primary care data.

BACKGROUND: People with neuromuscular disease (NMD) experience a broader range of chronic diseases and health symptoms compared to the general population. However, no comprehensive analysis has directly quantified this to our knowledge. METHODS: We used a large UK primary care database (Clinical Practice Research Datalink) to compare the prevalence of chronic diseases and other health conditions, including recent infections between 23,876 patients with NMD ever recorded by 2019 compared to 95,295 age-sex-practice matched patients without NMD. Modified Poisson regression estimated Prevalence Ratios (PR) to summarise the presence of the disease/condition ever (or for infections in 2018) in NMD patients versus non-NMD patients. RESULTS: Patients with NMD had significantly higher rates for 16 of the 18 conditions routinely recorded in the primary care Quality and Outcomes Framework (QOF). Approximately 1-in-10 adults with NMD had ≥4 conditions recorded (PR = 1.39, 95%CI 1.33-1.45). Disparities were more pronounced at younger ages (18-49). For other (non-QOF) health conditions, significantly higher recorded levels were observed for rarer events (pulmonary embolism PR = 1.96 95%CI 1.76-2.18, hip fractures PR = 1.65 95%CI 1.47-1.85) as well as for more common primary care conditions (constipation PR = 1.52 95%CI 1.46-1.57, incontinence PR = 1.52 95%CI 1.44-1.60). The greatest co-morbidity burden was in patients with a myotonic disorder. Approximately 1-in-6 (17.1%) NMD patients had an infection recorded in the preceding year, with the risk of being hospitalised with an infection nearly double (PR = 1.92, 95%CI 1.79-2.07) compared to non-NMD patients. CONCLUSION: The burden of chronic co-morbidity among patients with NMD is extremely high compared to the general population, and they are also more likely to present in primary and secondary care for acute events such as infections.

Prevalence and incidence of neuromuscular conditions in the UK between 2000 and 2019: A retrospective study using primary care data.

BACKGROUND: In the UK, large-scale electronic primary care datasets can provide up-to-date, accurate epidemiological information on rarer diseases, where specialist diagnoses from hospital discharges and clinic letters are generally well recorded and electronically searchable. Current estimates of the number of people living with neuromuscular disease (NMD) have largely been based on secondary care data sources and lacked direct denominators. OBJECTIVE: To estimate trends in the recording of neuromuscular disease in UK primary care between 2000-2019. METHODS: The Clinical Practice Research Datalink (CPRD) database was searched electronically to estimate incidence and prevalence rates (per 100,000) for a range of NMDs in each year. To compare trends over time, rates were age standardised to the most recent CPRD population (2019). RESULTS: Approximately 13 million patients were actively registered in each year. By 2019, 28,230 active patients had ever received a NMD diagnosis (223.6), which was higher among males (239.0) than females (208.3). The most common classifications were Guillain-Barre syndrome (40.1), myasthenia gravis (33.7), muscular dystrophy (29.5), Charcot-Marie-Tooth (29.5) and inflammatory myopathies (25.0). Since 2000, overall prevalence grew by 63%, with the largest increases seen at older ages (≥65-years). However, overall incidence remained constant, though myasthenia gravis incidence has risen steadily since 2008, while new cases of muscular dystrophy fell over the same period. CONCLUSIONS: Lifetime recording of many NMDs on primary care records exceed current estimates of people living with these conditions; these are important data for health service and care planning. Temporal trends suggest this number is steadily increasing, and while this may partially be due to better recording, it cannot be simply explained by new cases, as incidence remained constant. The increase in prevalence among older ages suggests increases in life expectancy among those living with NMDs may have occurred.

Risk factors for excess all-cause mortality during the first wave of the COVID-19 pandemic in England: A retrospective cohort study of primary care data.

BACKGROUND: The COVID-19 pandemic's first wave in England during spring 2020 resulted in an approximate 50% increase in all-cause mortality. Previously, risk factors such as age and ethnicity, were identified by studying COVID-related deaths only, but these were under-recorded during this period. OBJECTIVE: To use a large electronic primary care database to estimate the impact of risk factors (RFs) on excess mortality in England during the first wave, compared with the impact on total mortality during 2015-19. METHODS: Medical history, ethnicity, area-based deprivation and vital status data were extracted for an average of 4.8 million patients aged 30-104 years, for each year between 18-March and 19-May over a 6-year period (2015-2020). We used Poisson regression to model total mortality adjusting for age and sex, with interactions between each RF and period (pandemic vs. 2015-19). Total mortality during the pandemic was partitioned into "usual" and "excess" components, assuming 2015-19 rates represented "usual" mortality. The association of each RF with the 2020 "excess" component was derived as the excess mortality ratio (EMR), and compared with the usual mortality ratio (UMR). RESULTS: RFs where excess mortality was greatest and notably higher than usual were age >80, non-white ethnicity (e.g., black vs. white EMR = 2.50, 95%CI 1.97-3.18; compared to UMR = 0.92, 95%CI 0.85-1.00), BMI>40, dementia, learning disability, severe mental illness, place of residence (London, care-home, most deprived). By contrast, EMRs were comparable to UMRs for sex. Although some co-morbidities such as cancer produced EMRs significantly below their UMRs, the EMRs were still >1. In contrast current smoking has an EMR below 1 (EMR = 0.80, 95%CI 0.65-0.98) compared to its UMR = 1.64. CONCLUSIONS: Studying risk factors for excess mortality during the pandemic highlighted differences from studying cause-specific mortality. Our approach illustrates a novel methodology for evaluating a pandemic's impact by individual risk factor without requiring cause-specific mortality data.

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.

A framework for handling missing accelerometer outcome data in trials.

Accelerometers and other wearable devices are increasingly being used in clinical trials to provide an objective measure of the impact of an intervention on physical activity. Missing data are ubiquitous in this setting, typically for one of two reasons: patients may not wear the device as per protocol, and/or the device may fail to collect data (e.g. flat battery, water damage). However, it is not always possible to distinguish whether the participant stopped wearing the device, or if the participant is wearing the device but staying still. Further, a lack of consensus in the literature on how to aggregate the data before analysis (hourly, daily, weekly) leads to a lack of consensus in how to define a "missing" outcome. Different trials have adopted different definitions (ranging from having insufficient step counts in a day, through to missing a certain number of days in a week). We propose an analysis framework that uses wear time to define missingness on the epoch and day level, and propose a multiple imputation approach, at the day level, which treats partially observed daily step counts as right censored. This flexible approach allows the inclusion of auxiliary variables, and is consistent with almost all the primary analysis models described in the literature, and readily allows sensitivity analysis (to the missing at random assumption) to be performed. Having presented our framework, we illustrate its application to the analysis of the 2019 MOVE-IT trial of motivational interviewing to increase exercise.

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.

Association of Childhood Fat Mass and Weight With Adult-Onset Type 2 Diabetes in Denmark.

Importance: Childhood obesity, defined by cutoffs based on the weight-based marker of body mass index, is associated with adult type 2 diabetes (T2D) risk. Whether childhood fat mass (FM) is the driver of these associations is currently unknown. Objective: To quantify and compare height-independent associations between childhood FM and weight with adult T2D risk in a historic Danish cohort. Design, Setting, and Participants: This population-based retrospective cohort study included schoolchildren from The Copenhagen School Health Records Register born between January 1930 and December 1985 with follow-up to adulthood through December 31, 2015. Analyses were based on 269 913 schoolchildren aged 10 years with 21 896 established adult T2D cases and 261 192 children aged 13 years with 21 530 established adult T2D cases for whom childhood height and weight measurements, as well as predicted FM, were available. Statistical analyses were performed between April 2019 to August 2020. Exposures: Childhood FM and weight at ages 10 and 13 years. Main Outcomes and Measures: Diagnoses of T2D were established by linkage to national disease registers for adults aged at least 30 years. Sex-specific Cox regression quantified associations, adjusted for childhood height, which were evaluated within 5 birth-cohort groups. Group-specific results were pooled using random-effects meta-analyses accounting for heterogeneity across group-specific associations. Results: This cohort study analyzed data from 269 913 children aged 10 years (135 940 boys [50.4%]) with 21 896 established adult T2D cases and 261 192 children aged 13 years (131 025 boys [50.2%]) with 21 530 established adult T2D cases. After adjusting for childhood height, increases in FM and weight (per kilogram) among boys aged 10 years were associated with elevated T2D risks at age 50 years of 12% (hazard ratio [HR], 1.12; 95% CI, 1.10-1.14) and 7% (HR, 1.07; 95% CI, 1.05-1.09), respectively, and among girls aged 10 years of 15% (HR, 1.15; 95% CI, 1.13-1.17) and 10% (HR, 1.10; 95% CI, 1.08-1.11), respectively. Among children aged 13 years, increases in FM and weight (per kilogram) were associated with increased T2D risks at age 50 years of 10% (HR, 1.10; 95% CI, 1.09-1.10) and 6% (HR, 1.06; 95% CI, 1.05-1.07) for boys, respectively, and of 10% (HR, 1.10; 95% CI, 1.10-1.11) and 7% (HR, 1.07; 95% CI, 1.06-1.08), respectively, for girls. Conclusions and Relevance: This cohort study found that a 1-kg increase in childhood FM was more strongly associated with increased adult T2D risk than a 1-kg increase in weight, independent of childhood height. Information on FM, rather than weight-based measures, focuses on a modifiable component of weight that may be associated with adult T2D risk. These findings support the assessment of childhood FM in adiposity surveillance initiatives in an effort to reduce long-term T2D risk.

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.

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 .

Weekend and weekday associations between the residential built environment and physical activity: Findings from the ENABLE London study.

BACKGROUND: We assessed whether the residential built environment was associated with physical activity (PA) differently on weekdays and weekends, and contributed to socio-economic differences in PA. METHODS: Measures of PA and walkability, park proximity and public transport accessibility were derived for baseline participants (n = 1,064) of the Examining Neighbourhood Activities in Built Living Environments in London (ENABLE London) Study. Multilevel-linear-regressions examined associations between weekend and weekday steps and Moderate to Vigorous PA (MVPA), residential built environment factors, and housing tenure status as a proxy for socio-economic position. RESULTS: A one-unit decrease in walkability was associated with 135 (95% CI [28; 242]) fewer steps and 1.2 (95% CI [0.3; 2.1]) fewer minutes of MVPA on weekend days, compared with little difference in steps and minutes of MVPA observed on weekdays. A 1km-increase in distance to the nearest local park was associated with 597 (95% CI [161; 1032]) more steps and 4.7 (95% CI [1.2; 8.2]) more minutes of MVPA on weekend days; 84 fewer steps (95% CI [-253;420]) and 0.3 fewer minutes of MVPA (95%CI [-2.3, 3.0]) on weekdays. Lower public transport accessibility was associated with increased steps on a weekday (767 steps, 95%CI [-13,1546]) compared with fewer steps on weekend days (608 fewer steps, 95% CI [-44, 1658]). None of the associations between built environment factors and PA on either weekend or weekdays were modified by socio-economic status. However, socio-economic differences in PA related moderately to socio-economic disparities in PA-promoting features of the residential neighbourhood. CONCLUSIONS: The residential built environment is associated with PA differently at weekends and on weekdays, and contributes moderately to socio-economic differences in PA.

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.

Effectiveness of adult community-based physical activity interventions with objective physical activity measurements and long-term follow-up: a systematic review and meta-analysis.

OBJECTIVE: To identify randomised controlled trials (RCTs) of physical activity (PA) interventions with objective PA outcomes in adults and to evaluate whether intervention effects were sustained beyond 12 months. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Seven databases (Medline, Embase, PsycINFO, Web of Science, Cochrane library, CINAHL (Cumulative Index of Nursing and Allied Health Literature) and ASSIA (Applied Social Sciences Index and Abstracts)) were searched from January 2000 until December 2019. ELIGIBILITY CRITERIA: RCTs reporting objective PA outcomes beyond 12 months with community-based participants aged ≥18 years were included; those where controls received active interventions, including advice to increase PA levels, were excluded. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers completed extraction of aggregate data and assessed risk of bias. Meta-analyses used random-effects models at different follow-up points. Primary outcomes were daily steps and weekly minutes of moderate-to-vigorous PA (MVPA). RESULTS: Of 33 282 records identified, nine studies (at generally low risk of bias) were included, five in meta-analyses with 12 months to 4 year follow-up. We observed 12 month increases for intervention vs control participants in steps/day (mean difference (MD)=554 (95% CIs: 384 to 724) p<0.0001, I2=0%; 2446 participants; four studies) and weekly MVPA minutes (MD=35 (95% CI: 27 to 43) p<0.0001, I2=0%; 2647 participants; four studies). Effects were sustained up to 4 years for steps/day (MD=494 (95% CI: 251 to 738) p<0.0001, I2=0%; 1944 participants; four studies) and weekly MVPA minutes (MD=25 (95% CI: 13 to 37) p<0.0001, I2=0%; 1458 participants; three studies). CONCLUSIONS: There are few PA interventions with objective follow-up beyond 12 months, more studies are needed. However, this review provided evidence of PA intervention effects beyond 12 months and sustained up to 4 years for both steps/day and MVPA. These findings have important implications for potential long-term health benefits. PROSPERO REGISTRATION NUMBER: CRD42017075753.

Evaluating the effect of change in the built environment on mental health and subjective well-being: a natural experiment.

BACKGROUND: Neighbourhood characteristics may affect mental health and well-being, but longitudinal evidence is limited. We examined the effect of relocating to East Village (the former London 2012 Olympic Athletes' Village), repurposed to encourage healthy active living, on mental health and well-being. METHODS: 1278 adults seeking different housing tenures in East village were recruited and examined during 2013-2015. 877 (69%) were followed-up after 2  years; 50% had moved to East Village. Analysis examined change in objective measures of the built environment, neighbourhood perceptions (scored from low to high; quality -12 to 12, safety -10 to 10 units), self-reported mental health (depression and anxiety) and well-being (life satisfaction, life being worthwhile and happiness) among East Village participants compared with controls who did not move to East Village. Follow-up measures were regressed on baseline for each outcome with group status as a binary variable, adjusted for age, sex, ethnicity, housing tenure and household clustering (random effect). RESULTS: Participants who moved to East Village lived closer to their nearest park (528 m, 95% CI 482 to 575 m), in more walkable areas, and had better access to public transport, compared with controls. Living in East Village was associated with marked improvements in neighbourhood perceptions (quality 5.0, 95% CI 4.5 to 5.4 units; safety 3.4, 95% CI 2.9 to 3.9 units), but there was no overall effect on mental health and well-being outcomes. CONCLUSION: Despite large improvements in the built environment, there was no evidence that moving to East Village improved mental health and well-being. Changes in the built environment alone are insufficient to improve mental health and well-being.

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.