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Introduction: Childhood adiposity markers can be standardised for height in the form of indices (marker/height p ) to make meaningful comparisons of adiposity patterns within and between individuals of differing heights. The optimal value of p has been shown to differ by birth year, sex, age, and ethnicity. We investigated whether height powers for childhood weight and fat mass (FM) differed by birth year, sex, or age over the period before and during the child obesity epidemic in Copenhagen., Setting/methods: Population-based cross-sectional study of 391,801 schoolchildren aged 7 years, 10 years and 13 years, born between 1930 and 1996, from the Copenhagen School Health Records Register. Sex- and age-specific estimates of the height powers for weight and FM were obtained using log-log regression, stratified by a decade of birth., Results: For weight, amongst children born 1930-39, optimal height powers at 7 years were 2.20 (95% CI: 2.19-2.22) for boys and 2.28 (95% CI: 2.26-2.30) for girls. These increased with birth year to 2.82 (95% CI: 2.76-2.87) and 2.92 (95% CI: 2.87-2.97) for boys and girls born in 1990-96, respectively. For FM, amongst those born 1930-39, powers at 7 years were 2.46 (95% CI: 2.42-2.51) and 2.58 (95% CI: 2.53-2.63) for boys and girls, respectively, and increased with birth year reaching 3.89 (95% CI: 3.75-4.02) and 3.93 (95% CI: 3.80-4.06) for boys and girls born 1990-96, respectively. Powers within birth cohort groups for weight and FM were higher at 10 years than at 7 years, though similar increases across groups were observed at both ages. At 13 years, height powers for weight and FM initially increased with the birth year before declining from the 1970s/80s., Conclusion: Due to increases in the standard deviation of weight and FM during the obesity epidemic, optimal height powers needed to standardise childhood weight and FM varied by birth year, sex, and age. Adiposity indices using a uniform height power mean different things for different birth cohort groups, sexes, and ages thus should be interpreted with caution. Alternative methods to account for height in epidemiological analyses are needed., (© 2024. The Author(s).)

Background: Randomised, cluster-based study designs in schools are commonly used to evaluate children's physical activity interventions. Sample size estimation relies on accurate estimation of the intra-cluster correlation coefficient (ICC), but published estimates, especially using accelerometry-measured physical activity, are few and vary depending on physical activity outcome and participant age. Less commonly-used cluster-based designs, such as stepped wedge designs, also need to account for correlations over time, e.g. cluster autocorrelation (CAC) and individual autocorrelation (IAC), but no estimates are currently available. This paper estimates the school-level ICC, CAC and IAC for England children's accelerometer-measured physical activity outcomes by age group and gender, to inform the design of future school-based cluster trials., Methods: Data were pooled from seven large English datasets of accelerometer-measured physical activity data between 2002-18 (> 13,500 pupils, 540 primary and secondary schools). Linear mixed effect models estimated ICCs for weekday and whole week for minutes spent in moderate-to-vigorous physical activity (MVPA) and being sedentary for different age groups, stratified by gender. The CAC (1,252 schools) and IAC (34,923 pupils) were estimated by length of follow-up from pooled longitudinal data., Results: School-level ICCs for weekday MVPA were higher in primary schools (from 0.07 (95% CI: 0.05, 0.10) to 0.08 (95% CI: 0.06, 0.11)) compared to secondary (from 0.04 (95% CI: 0.03, 0.07) to (95% CI: 0.04, 0.10)). Girls' ICCs were similar for primary and secondary schools, but boys' were lower in secondary. For all ages, combined the CAC was 0.60 (95% CI: 0.44-0.72), and the IAC was 0.46 (95% CI: 0.42-0.49), irrespective of follow-up time. Estimates were higher for MVPA vs sedentary time, and for weekdays vs the whole week., Conclusions: Adequately powered studies are important to evidence effective physical activity strategies. Our estimates of the ICC, CAC and IAC may be used to plan future school-based physical activity evaluations and were fairly consistent across a range of ages and settings, suggesting that results may be applied to other high income countries with similar school physical activity provision. It is important to use estimates appropriate to the study design, and that match the intended study population as closely as possible., (© 2024. The Author(s).)

Objectives: To assess improvement in the completeness of reporting coronavirus (COVID-19) prediction models after the peer review process., Study Design and Setting: Studies included in a living systematic review of COVID-19 prediction models, with both preprint and peer-reviewed published versions available, were assessed. The primary outcome was the change in percentage adherence to the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) reporting guidelines between pre-print and published manuscripts., Results: Nineteen studies were identified including seven (37%) model development studies, two external validations of existing models (11%), and 10 (53%) papers reporting on both development and external validation of the same model. Median percentage adherence among preprint versions was 33% (min-max: 10 to 68%). The percentage adherence of TRIPOD components increased from preprint to publication in 11/19 studies (58%), with adherence unchanged in the remaining eight studies. The median change in adherence was just 3 percentage points (pp, min-max: 0-14 pp) across all studies. No association was observed between the change in percentage adherence and preprint score, journal impact factor, or time between journal submission and acceptance., Conclusions: The preprint reporting quality of COVID-19 prediction modeling studies is poor and did not improve much after peer review, suggesting peer review had a trivial effect on the completeness of reporting during the pandemic., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

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 R 2 , 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 R 2 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 R 2 , 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 R 2 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., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form and declare: this research was supported by grants from the British Heart Foundation, the Wellcome Trust, and the National Institute for Health and Care Research Applied Research Collaboration South London; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Aims: We examined associations between five body mass index (BMI) trajectories from ages 6-15 years and register-based adult-onset type 2 diabetes mellitus (T2D) and coronary heart disease (CHD) with and without adjustment for adult BMI., Methods: Child and adult BMI came from two Danish cohorts and 13,205 and 13,438 individuals were included in T2D and CHD analyses, respectively. Trajectories were estimated by latent class modelling. Incidence rate ratios (IRRs) were estimated with Poisson regression., Results: In models without adult BMI, compared to the lowest trajectory, among men the T2D IRRs were 0.92 (95 %CI:0.77-1.09) for the second lowest trajectory and 1.51 (95 %CI:0.71-3.20) for the highest trajectory. The corresponding IRRs in women were 0.92 (95 %CI:0.74-1.16) and 3.58 (95 %CI:2.30-5.57). In models including adult BMI, compared to the lowest trajectory, T2D IRRs in men were 0.57 (95 %CI:0.47-0.68) for the second lowest trajectory and 0.26 (95 %CI:0.12-0.56) for the highest trajectory. The corresponding IRRs in women were 0.60 (95 %CI:0.48-0.75) and 0.59 (95 %CI:0.36-0.96). The associations were similar in direction, but not statistically significant, for CHD., Conclusions: Incidence rates of adult-onset T2D were greater for a high child BMI trajectory than a low child BMI trajectory, but not in models that included adult BMI., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Acute oncology services (AOS) provide rapid review and expedited pathways for referral to specialist care for cancer patients. Blood tests may support AOS in providing estimates of prognosis. We aimed to develop and validate a prognostic model of 30-day mortality based on routine blood markers to inform an AOS decision to actively treat or palliate patients., Methods and Materials: Using clinical data from 752 AOS referrals, multivariable logistic regression analysis was conducted to develop a 30-day mortality prognostic model. Internal validation and then internal-external cross-validation were used to examine overfitting and generalizability of the model's predictive performance., Results: Urea, alkaline phosphatase, albumin and neutrophils were the strongest predictors of outcome. The model separated patients into distinct prognostic groups from the cross-validation (C Statistic: 0.70; 95% CI: 0.64-0.76). Admission year was included as a predictor in the model to improve the model calibration., Conclusion: The developed prediction model was able to classify patients into distinct prognostic risk groups, which is clinically useful for delivering an evidence-based AOS. Collation of data from other AOS centers would allow for the development of a more generalizable prognostic model.

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.

Clinical prediction models provide individualized outcome predictions to inform patient counseling and clinical decision making. External validation is the process of examining a prediction model's performance in data independent to that used for model development. Current external validation studies often suffer from small sample sizes, and subsequently imprecise estimates of a model's predictive performance. To address this, we propose how to determine the minimum sample size needed for external validation of a clinical prediction model with a continuous outcome. Four criteria are proposed, that target precise estimates of (i) R 2 (the proportion of variance explained), (ii) calibration-in-the-large (agreement between predicted and observed outcome values on average), (iii) calibration slope (agreement between predicted and observed values across the range of predicted values), and (iv) the variance of observed outcome values. Closed-form sample size solutions are derived for each criterion, which require the user to specify anticipated values of the model's performance (in particular R 2 ) and the outcome variance in the external validation dataset. A sensible starting point is to base values on those for the model development study, as obtained from the publication or study authors. The largest sample size required to meet all four criteria is the recommended minimum sample size needed in the external validation dataset. The calculations can also be applied to estimate expected precision when an existing dataset with a fixed sample size is available, to help gauge if it is adequate. We illustrate the proposed methods on a case-study predicting fat-free mass in children., (© 2020 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)

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; R 2 , calibration (slope and intercept) and root mean square error (RMSE). R 2 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.

Background: BMI underestimates and overestimates body fat in children from South Asian and Black ethnic groups, respectively., Methods: We used cross-sectional NCMP data (2015-17) for 38 270 children in three inner-London local authorities: City & Hackney, Newham and Tower Hamlets (41% South Asian, 18.8% Black): 20 439 4-5 year-olds (48.9% girls) and 17 831 10-11 year-olds (49.1% girls). We estimated the proportion of parents who would have received different information about their child's weight status, and the area-level prevalence of obesity-defined as ≥98th centile-had ethnic-specific BMI adjustments been employed in the English National Child Measurement Programme (NCMP)., Results: Had ethnic-specific adjustment been employed, 19.7% (3112/15 830) of parents of children from South Asian backgrounds would have been informed that their child was in a heavier weight category, and 19.1% (1381/7217) of parents of children from Black backgrounds would have been informed that their child was in a lighter weight category. Ethnic-specific adjustment increased obesity prevalence from 7.9% (95% CI: 7.6, 8.3) to 9.1% (8.7, 9.5) amongst 4-5 year-olds and from 17.5% (16.9, 18.1) to 18.8% (18.2, 19.4) amongst 10-11 year-olds., Conclusions: Ethnic-specific adjustment in the NCMP would ensure equitable categorization of weight status, provide correct information to parents and support local service provision for families., (© The Author(s) 2020. Published by Oxford University Press on behalf of Faculty of Public Health.)

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/m 2 , 21.3 kg/m 2 (boys) and 20.0 kg/m 2 , 22.5 kg/m 2 (girls). At equivalent HOMA-IR, SA overweight and obesity thresholds were lower by 2.9 kg/m 2 (95% CI: 2.5-3.3 kg/m 2 ) and 3.2 kg/m 2 (95% CI: 2.7-3.6 kg/m 2 ) in boys and 3.0 kg/m 2 (95% CI: 2.6-3.4 kg/m 2 ) and 3.3 kg/m 2 (95% CI: 2.8-3.8 kg/m 2 ) 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.

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/m 2 ) and Black girls, but not in Black boys (18.4, 19.2 kg/m 2 ) when compared with White children (18.6, 19.0 kg/m 2 ; all P < 0.001). Mean 5-year changes (boys, girls) were higher in South Asian children (0.16, 0.32 kg/m 2 per 5 y; both P < 0.001) and Black boys but not girls (0.13, 0.15 kg/m 2 per 5 y; P = 0.01, P = 0.41) compared with White children (0.02, 0.11 kg/m 2 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., (© 2017 The Authors. Obesity published by Wiley Periodicals, Inc. on behalf of The Obesity Society (TOS).)

This review analyzed the incidence, mechanisms, and risk factors of aortic-related reintervention after endovascular repair of chronic dissections. The systematic review identified 28 studies describing 1,249 patients at median 27 months follow-up (range, 10.3 to 64.4). There were six reinterventions, 0.7 ruptures, and 1.2 surgical conversions per 100 patient-years of follow-up. Stent-related reinterventions were more frequent than nonstent related (80.2% vs 19.8%). Distal false lumen perfusion was the most common complication (40.5%). No individual risk factor-treatment timing, disease extent, covered aorta length, or remodelling-was associated with reintervention. Further investigation based on consistent reporting standards is required., (Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Purpose: The Examining Neighbourhood Activities in Built Living Environments in London (ENABLE London) project is a natural experiment which aims to establish whether physical activity and other health behaviours show sustained changes among individuals and families relocating to East Village (formerly the London 2012 Olympics Athletes' Village), when compared with a control population living outside East Village throughout., Participants: Between January 2013 and December 2015, 1497 individuals from 1006 households were recruited and assessed (at baseline) (including 392 households seeking social housing, 421 seeking intermediate and 193 seeking market rent homes). The 2-year follow-up rate is 62% of households to date, of which 57% have moved to East Village., Findings to Date: Assessments of physical activity (measured objectively using accelerometers) combined with Global Positioning System technology and Geographic Information System mapping of the local area are being used to characterise physical activity patterns and location among study participants and assess the attributes of the environments to which they are exposed. Assessments of body composition, based on weight, height and bioelectrical impedance, have been made and detailed participant questionnaires provide information on socioeconomic position, general health/health status, well-being, anxiety, depression, attitudes to leisure time activities and other personal, social and environmental influences on physical activity, including the use of recreational space and facilities in their residential neighbourhood., Future Plans: The main analyses will examine the changes in physical activity, health and well-being observed in the East Village group compared with controls and the influence of specific elements of the built environment on observed changes. The ENABLE London project exploits a unique opportunity to evaluate a 'natural experiment', provided by the building and rapid occupation of East Village. Findings from the study will be generalisable to other urban residential housing developments, and will help inform future evidence-based urban planning., Competing Interests: Conflicts of Interest: None declared., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)