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.

External validation of a prediction model for estimating fat mass in children and adolescents in 19 countries: individual participant data meta-analysis.

OBJECTIVE: To evaluate the performance of a UK based prediction model for estimating fat-free mass (and indirectly fat mass) in children and adolescents in non-UK settings. DESIGN: Individual participant data meta-analysis. SETTING: 19 countries. PARTICIPANTS: 5693 children and adolescents (49.7% boys) aged 4 to 15 years with complete data on the predictors included in the UK based model (weight, height, age, sex, and ethnicity) and on the independently assessed outcome measure (fat-free mass determined by deuterium dilution assessment). MAIN OUTCOME MEASURES: The outcome of the UK based prediction model was natural log transformed fat-free mass (lnFFM). Predictive performance statistics of R2, calibration slope, calibration-in-the-large, and root mean square error were assessed in each of the 19 countries and then pooled through random effects meta-analysis. Calibration plots were also derived for each country, including flexible calibration curves. RESULTS: The model showed good predictive ability in non-UK populations of children and adolescents, providing R2 values of >75% in all countries and >90% in 11 of the 19 countries, and with good calibration (ie, agreement) of observed and predicted values. Root mean square error values (on fat-free mass scale) were <4 kg in 17 of the 19 settings. Pooled values (95% confidence intervals) of R2, calibration slope, and calibration-in-the-large were 88.7% (85.9% to 91.4%), 0.98 (0.97 to 1.00), and 0.01 (-0.02 to 0.04), respectively. Heterogeneity was evident in the R2 and calibration-in-the-large values across settings, but not in the calibration slope. Model performance did not vary markedly between boys and girls, age, ethnicity, and national income groups. To further improve the accuracy of the predictions, the model equation was recalibrated for the intercept in each setting so that country specific equations are available for future use. CONCLUSION: The UK based prediction model, which is based on readily available measures, provides predictions of childhood fat-free mass, and hence fat mass, in a range of non-UK settings that explain a large proportion of the variability in observed fat-free mass, and exhibit good calibration performance, especially after recalibration of the intercept for each population. The model demonstrates good generalisability in both low-middle income and high income populations of healthy children and adolescents aged 4-15 years.

Nonpharmacological Interventions to Lengthen Sleep Duration in Healthy Children: A Systematic Review and Meta-analysis.

Importance: Adequate sleep duration is necessary for many aspects of child health, development, and well-being, yet sleep durations for children are declining, and effective strategies to increase sleep in healthy children remain to be elucidated. Objective: To determine whether nonpharmaceutical interventions to improve sleep duration in healthy children are effective and to identify the key components of these interventions. Data Sources: CENTRAL, MEDLINE, Embase, PsycINFO, Web of Science Core collection, ClinicalTrials.gov, and WHO trials databases were searched from inception to November 15, 2021. Study Selection: Randomized clinical trials of interventions to improve sleep duration in healthy children were independently screened by 2 researchers. A total of 28 478 studies were identified. Data Extraction and Synthesis: Data were processed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) reporting guideline. Random-effects meta-analytic models were used to estimate pooled effect sizes. Main Outcomes and Measures: Difference in sleep duration, measured in minutes. Results: A total of 13 539 child participants from 45 randomized clinical trials were included. Of these, 6897 (50.9%) were in the intervention group and 6642 (49.1%) in the control group, and the mean age ranged from 18 months to 19 years. Pooled results indicate that sleep interventions were associated with 10.5 minutes (95% CI, 5.6-15.4) longer nocturnal sleep duration. There was substantial variation between trials. Sources of variation that were not associated with the study effect size included age group, whether the population was identified as having a sleep problem or being at a socioeconomic disadvantage (eg, coming from a low-income family or area), method of assessment of sleep duration (objective vs subjective), location of intervention delivery (home vs school), whether interventions were delivered in person or used parental involvement, whether behavioral theory was used, environmental change, or had greater or lower intensity. Interventions that included earlier bedtimes were associated with a 47-minute sleep extension (95% CI, 18.9-75.0; 3 trials) compared with remaining studies (7.4 minutes; 95% CI, 2.9-11.8; 42 trials) (P = .006 for group difference). Trials of shorter duration (6 months or less) had larger effects. Conclusions and Relevance: Interventions focused on earlier bedtimes may offer a simple, pragmatic, effective way to meaningfully increase sleep duration that could have important benefits for child health.

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.

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.

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.

Variations in accelerometry measured physical activity and sedentary time across Europe - harmonized analyses of 47,497 children and adolescents.

BACKGROUND: Levels of physical activity and variation in physical activity and sedentary time by place and person in European children and adolescents are largely unknown. The objective of the study was to assess the variations in objectively measured physical activity and sedentary time in children and adolescents across Europe. METHODS: Six databases were systematically searched to identify pan-European and national data sets on physical activity and sedentary time assessed by the same accelerometer in children (2 to 9.9 years) and adolescents (≥10 to 18 years). We harmonized individual-level data by reprocessing hip-worn raw accelerometer data files from 30 different studies conducted between 1997 and 2014, representing 47,497 individuals (2-18 years) from 18 different European countries. RESULTS: Overall, a maximum of 29% (95% CI: 25, 33) of children and 29% (95% CI: 25, 32) of adolescents were categorized as sufficiently physically active. We observed substantial country- and region-specific differences in physical activity and sedentary time, with lower physical activity levels and prevalence estimates in Southern European countries. Boys were more active and less sedentary in all age-categories. The onset of age-related lowering or leveling-off of physical activity and increase in sedentary time seems to become apparent at around 6 to 7 years of age. CONCLUSIONS: Two third of European children and adolescents are not sufficiently active. Our findings suggest substantial gender-, country- and region-specific differences in physical activity. These results should encourage policymakers, governments, and local and national stakeholders to take action to facilitate an increase in the physical activity levels of young people across Europe.

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.

The effect of moving to East Village, the former London 2012 Olympic and Paralympic Games Athletes' Village, on physical activity and adiposity (ENABLE London): a cohort study.

BACKGROUND: The built environment can affect health behaviours, but longitudinal evidence is limited. We aimed to examine the effect of moving into East Village, the former London 2012 Olympic and Paralympic Games Athletes' Village that was repurposed on active design principles, on adult physical activity and adiposity. METHODS: In this cohort study, we recruited adults seeking new accommodation in East Village and compared physical activity and built environment measures with these data in control participants who had not moved to East Village. At baseline and after 2 years, we objectively measured physical activity with accelerometry and adiposity with body-mass index and bioimpedance, and we assessed objective measures of and participants' perceptions of change in their built environment. We examined the change in physical activity and adiposity between the East Village and control groups, after adjusting for sex, age group, ethnicity, housing tenure, and household (as a random effect). FINDINGS: We recruited participants for baseline assessment between Jan 24, 2013, and Jan 7, 2016, and we followed up the cohort after 2 years, between Feb 24, 2015, and Oct 24, 2017. At baseline, 1819 households (one adult per household) consented to initial contact by the study team. 1278 adults (16 years and older) from 1006 (55%) households participated at baseline; of these participants, 877 (69%) adults from 710 (71%) households were assessed after 2 years, of whom 441 (50%) participants from 343 (48%) households had moved to East Village. We found no effect associated with moving to East Village on daily steps, the time spent doing moderate-to-vigorous physical activity (either in total or in 10-min bouts or more), daily sedentary time, body-mass index, or fat mass percentage between participants who had moved to East Village and those in the control group, despite sizeable improvements in walkability and neighbourhood perceptions of crime and quality among the East Village group relative to their original neighbourhood at baseline. INTERPRETATION: Despite large improvements in neighbourhood perceptions and walkability, we found no clear evidence that moving to East Village was associated with increased physical activity. Improving the built environment on its own might be insufficient to increase physical activity. FUNDING: National Institute for Health Research and National Prevention Research Initiative.

Development and validation of a prediction model for fat mass in children and adolescents: meta-analysis using individual participant data.

OBJECTIVES: To develop and validate a prediction model for fat mass in children aged 4-15 years using routinely available risk factors of height, weight, and demographic information without the need for more complex forms of assessment. DESIGN: Individual participant data meta-analysis. SETTING: Four population based cross sectional studies and a fifth study for external validation, United Kingdom. PARTICIPANTS: A pooled derivation dataset (four studies) of 2375 children and an external validation dataset of 176 children with complete data on anthropometric measurements and deuterium dilution assessments of fat mass. MAIN OUTCOME MEASURE: Multivariable linear regression analysis, using backwards selection for inclusion of predictor variables and allowing non-linear relations, was used to develop a prediction model for fat-free mass (and subsequently fat mass by subtracting resulting estimates from weight) based on the four studies. Internal validation and then internal-external cross validation were used to examine overfitting and generalisability of the model's predictive performance within the four development studies; external validation followed using the fifth dataset. RESULTS: Model derivation was based on a multi-ethnic population of 2375 children (47.8% boys, n=1136) aged 4-15 years. The final model containing predictor variables of height, weight, age, sex, and ethnicity had extremely high predictive ability (optimism adjusted R2: 94.8%, 95% confidence interval 94.4% to 95.2%) with excellent calibration of observed and predicted values. The internal validation showed minimal overfitting and good model generalisability, with excellent calibration and predictive performance. External validation in 176 children aged 11-12 years showed promising generalisability of the model (R2: 90.0%, 95% confidence interval 87.2% to 92.8%) with good calibration of observed and predicted fat mass (slope: 1.02, 95% confidence interval 0.97 to 1.07). The mean difference between observed and predicted fat mass was -1.29 kg (95% confidence interval -1.62 to -0.96 kg). CONCLUSION: The developed model accurately predicted levels of fat mass in children aged 4-15 years. The prediction model is based on simple anthropometric measures without the need for more complex forms of assessment and could improve the accuracy of assessments for body fatness in children (compared with those provided by body mass index) for effective surveillance, prevention, and management of clinical and public health obesity.

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.

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.

Housing, neighbourhood and sociodemographic associations with adult levels of physical activity and adiposity: baseline findings from the ENABLE London study.

OBJECTIVES: The neighbourhood environment is increasingly shown to be an important correlate of health. We assessed associations between housing tenure, neighbourhood perceptions, sociodemographic factors and levels of physical activity (PA) and adiposity among adults seeking housing in East Village (formerly London 2012 Olympic/Paralympic Games Athletes' Village). SETTING: Cross-sectional analysis of adults seeking social, intermediate and market-rent housing in East Village. PARTICIPANTS: 1278 participants took part in the study (58% female). Complete data on adiposity (body mass index (BMI) and fat mass %) were available for 1240 participants (97%); of these, a subset of 1107 participants (89%) met the inclusion criteria for analyses of accelerometer-based measurements of PA. We examined associations between housing sector sought, neighbourhood perceptions (covariates) and PA and adiposity (dependent variables) adjusted for household clustering, sex, age group, ethnic group and limiting long-standing illness. RESULTS: Participants seeking social housing had the fewest daily steps (8304, 95% CI 7959 to 8648) and highest BMI (26.0 kg/m2, 95% CI 25.5kg/m2 to 26.5 kg/m2) compared with those seeking intermediate (daily steps 9417, 95% CI 9106 to 9731; BMI 24.8 kg/m2, 95% CI 24.4 kg/m2 to 25.2 kg/m2) or market-rent housing (daily steps 9313, 95% CI 8858 to 9768; BMI 24.6 kg/m2, 95% CI 24.0 kg/m2 to 25.2 kg/m2). Those seeking social housing had lower levels of PA (by 19%-42%) at weekends versus weekdays, compared with other housing groups. Positive perceptions of neighbourhood quality were associated with higher steps and lower BMI, with differences between social and intermediate groups reduced by ~10% following adjustment, equivalent to a reduction of 111 for steps and 0.5 kg/m2 for BMI. CONCLUSIONS: The social housing group undertook less PA than other housing sectors, with weekend PA offering the greatest scope for increasing PA and tackling adiposity in this group. Perceptions of neighbourhood quality were associated with PA and adiposity and reduced differences in steps and BMI between housing sectors. Interventions to encourage PA at weekends and improve neighbourhood quality, especially among the most disadvantaged, may provide scope to reduce inequalities in health behaviour.

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.

Reassessing Ethnic Differences in Mean BMI and Changes Between 2007 and 2013 in English Children.

OBJECTIVE: National body fatness (BF) data for English South Asian and Black children use BMI, which provides inaccurate ethnic comparisons. BF levels and time trends in the English National Child Measurement Programme (NCMP) between 2007 and 2013 were assessed by using ethnic-specific adjusted BMI (aBMI) for South Asian and Black children. METHODS: Analyses were based on 3,195,323 children aged 4 to 5 years and 2,962,673 children aged 10 to 11 years. aBMI values for South Asian and Black children (relating to BF as in White children) were derived independently. Mean aBMI levels and 5-year aBMI changes were obtained by using linear regression. RESULTS: In the 2007-2008 NCMP, mean aBMIs in 10- to 11-year-old children (boys, girls) were higher in South Asian children (20.1, 19.9 kg/m2 ) and Black girls, but not in Black boys (18.4, 19.2 kg/m2 ) when compared with White children (18.6, 19.0 kg/m2 ; all P < 0.001). Mean 5-year changes (boys, girls) were higher in South Asian children (0.16, 0.32 kg/m2 per 5 y; both P < 0.001) and Black boys but not girls (0.13, 0.15 kg/m2 per 5 y; P = 0.01, P = 0.41) compared with White children (0.02, 0.11 kg/m2 per 5 y). Ethnic differences at 4 to 5 years were similar. Unadjusted BMI showed similar 5-year changes but different mean BMI patterns. CONCLUSIONS: BF levels were higher in South Asian children than in other groups in 2007 and diverged from those in White children until 2013, a pattern not apparent from unadjusted BMI data.

Takeaway meal consumption and risk markers for coronary heart disease, type 2 diabetes and obesity in children aged 9-10 years: a cross-sectional study.

OBJECTIVE: To investigate associations between takeaway meal consumption and risk markers for coronary heart disease, type 2 diabetes and obesity risk markers in children. DESIGN: A cross-sectional, school-based observational study. SETTING: 85 primary schools across London, Birmingham and Leicester. PARTICIPANTS: 1948 UK primary school children in year 5, aged 9-10 years. MAIN OUTCOME MEASURES: Children reported their frequency of takeaway meal consumption, completed a 24-hour dietary recall, had physical measurements and provided a fasting blood sample. RESULTS: Among 1948 participants with complete data, 499 (26%) never/hardly ever consumed a takeaway meal, 894 (46%) did so <1/week and 555 (28%) did ≥1/week. In models adjusted for age, sex, month, school, ethnicity and socioeconomic status, more frequent takeaway meal consumption was associated with higher dietary intakes of energy, fat % energy and saturated fat % energy and higher energy density (all P trend <0.001) and lower starch, protein and micronutrient intakes (all P trend <0.05). A higher frequency of takeaway meal consumption was associated with higher serum total cholesterol and low-density lipoprotein (LDL) cholesterol (P trend=0.04, 0.01, respectively); children eating a takeaway meal ≥1/week had total cholesterol and LDL cholesterol 0.09 mmol/L (95% CI 0.01 to 0.18) and 0.10 mmol/L (95% CI 0.02 to 0.18) higher respectively than children never/hardly ever eating a takeaway meal; their fat mass index was also higher. CONCLUSIONS: More frequent takeaway meal consumption in children was associated with unhealthy dietary nutrient intake patterns and potentially with adverse longer term consequences for obesity and coronary heart disease risk.

Comparisons of depression, anxiety, well-being, and perceptions of the built environment amongst adults seeking social, intermediate and market-rent accommodation in the former London Olympic Athletes' Village.

The Examining Neighbourhood Activities in Built Living Environments in London (ENABLE London) study provides a unique opportunity to examine differences in mental health and well-being amongst adults seeking social, intermediate (affordable rent), and market-rent housing in a purpose built neighbourhood (East Village, the former London 2012 Olympic Athletes' Village), specifically designed to encourage positive health behaviours. Multi-level logistic regression models examined baseline differences in levels of depression, anxiety and well-being across the housing groups. Compared with the intermediate group, those seeking social housing were more likely to be depressed, anxious and had poorer well-being after adjustment for demographic and health status variables. Further adjustments for neighbourhood perceptions suggest that compared with the intermediate group, perceived neighbourhood characteristics may be an important determinant of depression amongst those seeking social housing, and lower levels of happiness the previous day amongst those seeking market-rent housing. These findings add to the extensive literature on inequalities in health, and provide a strong basis for future longitudinal work that will examine change in depression, anxiety and well-being after moving into East Village, where those seeking social housing potentially have the most to gain.