Global, regional, and national prevalence of child and adolescent overweight and obesity, 1990–2021, with forecasts to 2050: a forecasting study for the Global Burden of Disease Study 2021

BACKGROUND: Despite the well documented consequences of obesity during childhood and adolescence and future risks of excess body mass on non-communicable diseases in adulthood, coordinated global action on excess body mass in early life is still insufficient. Inconsistent measurement and reporting are a barrier to specific targets, resource allocation, and interventions. In this Article we report current estimates of overweight and obesity across childhood and adolescence, progress over time, and forecasts to inform specific actions. METHODS: Using established methodology from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021, we modelled overweight and obesity across childhood and adolescence from 1990 to 2021, and then forecasted to 2050. Primary data for our models included 1321 unique measured and self-reported anthropometric data sources from 180 countries and territories from survey microdata, reports, and published literature. These data were used to estimate age-standardised global, regional, and national overweight prevalence and obesity prevalence (separately) for children and young adolescents (aged 5–14 years, typically in school and cared for by child health services) and older adolescents (aged 15–24 years, increasingly out of school and cared for by adult services) by sex for 204 countries and territories from 1990 to 2021. Prevalence estimates from 1990 to 2021 were generated using spatiotemporal Gaussian process regression models, which leveraged temporal and spatial correlation in epidemiological trends to ensure comparability of results across time and geography. Prevalence forecasts from 2022 to 2050 were generated using a generalised ensemble modelling approach assuming continuation of current trends. For every age-sex-location population across time (1990–2050), we estimated obesity (vs overweight) predominance using the log ratio of obesity percentage to overweight percentage. FINDINGS: Using established methodology from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021, we modelled overweight and obesity across childhood and adolescence from 1990 to 2021, and then forecasted to 2050. Primary data for our models included 1321 unique measured and self-reported anthropometric data sources from 180 countries and territories from survey microdata, reports, and published literature. These data were used to estimate age-standardised global, regional, and national overweight prevalence and obesity prevalence (separately) for children and young adolescents (aged 5–14 years, typically in school and cared for by child health services) and older adolescents (aged 15–24 years, increasingly out of school and cared for by adult services) by sex for 204 countries and territories from 1990 to 2021. Prevalence estimates from 1990 to 2021 were generated using spatiotemporal Gaussian process regression models, which leveraged temporal and spatial correlation in epidemiological trends to ensure comparability of results across time and geography. Prevalence forecasts from 2022 to 2050 were generated using a generalised ensemble modelling approach assuming continuation of current trends. For every age-sex-location population across time (1990–2050), we estimated obesity (vs overweight) predominance using the log ratio of obesity percentage to overweight percentage. INTERPRETATION: Both overweight and obesity increased substantially in every world region between 1990 and 2021, suggesting that current approaches to curbing increases in overweight and obesity have failed a generation of children and adolescents. Beyond 2021, overweight during childhood and adolescence is forecast to stabilise due to further increases in the population who have obesity. Increases in obesity are expected to continue for all populations in all world regions. Because substantial change is forecasted to occur between 2022 and 2030, immediate actions are needed to address this public health crisis

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

Measurements of differential cross-sections in top-quark pair events with a high transverse momentum top quark and limits on beyond the Standard Model contributions to top-quark pair production with the ATLAS detector at √s = 13 TeV

Cross-section measurements of top-quark pair production where the hadronically decaying top quark has transverse momentum greater than 355 GeV and the other top quark decays into ℓνb are presented using 139 fb−1 of data collected by the ATLAS experiment during proton-proton collisions at the LHC. The fiducial cross-section at s = 13 TeV is measured to be σ = 1.267 ± 0.005 ± 0.053 pb, where the uncertainties reflect the limited number of data events and the systematic uncertainties, giving a total uncertainty of 4.2%. The cross-section is measured differentially as a function of variables characterising the tt¯ system and additional radiation in the events. The results are compared with various Monte Carlo generators, including comparisons where the generators are reweighted to match a parton-level calculation at next-to-next-to-leading order. The reweighting improves the agreement between data and theory. The measured distribution of the top-quark transverse momentum is used to search for new physics in the context of the effective field theory framework. No significant deviation from the Standard Model is observed and limits are set on the Wilson coefficients of the dimension-six operators OtG and Otq(8), where the limits on the latter are the most stringent to date. [Figure not available: see fulltext.]

Improving topological cluster reconstruction using calorimeter cell timing in ATLAS

Clusters of topologically connected calorimeter cells around cells with large absolute signal-to-noise ratio (topo-clusters) are the basis for calorimeter signal reconstruction in the ATLAS experiment. Topological cell clustering has proven performant in LHC Runs 1 and 2. It is, however, susceptible to out-of-time pile-up of signals from soft collisions outside the 25 ns proton-bunch-crossing window associated with the event’s hard collision. To reduce this effect, a calorimeter-cell timing criterion was added to the signal-to-noise ratio requirement in the clustering algorithm. Multiple versions of this criterion were tested by reconstructing hadronic signals in simulated events and Run 2 ATLAS data. The preferred version is found to reduce the out-of-time pile-up jet multiplicity by ∼50% for jet pT ∼ 20 GeV and by ∼80% for jet pT 50 GeV, while not disrupting the reconstruction of hadronic signals of interest, and improving the jet energy resolution by up to 5% for 20 < pT < 30 GeV. Pile-up is also suppressed for other physics objects based on topo-clusters (electrons, photons, τ -leptons), reducing the overall event size on disk by about 6% in early Run 3 pileup conditions. Offline reconstruction for Run 3 includes the timing requirement

Software Performance of the ATLAS Track Reconstruction for LHC Run 3

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pileup) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60 pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two

Measurement and interpretation of same-sign W boson pair production in association with two jets in pp collisions at √s = 13 TeV with the ATLAS detector

This paper presents the measurement of fducial and diferential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W±W±jj) using 139 fb−1 of proton-proton collision data recorded at a centre-of-mass energy of √ s = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity diference. The measured fducial cross sections for electroweak and inclusive W±W±jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.)fb and 3.38±0.22 (stat.)±0.19 (syst.)fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confdence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H±± mass near 450 GeV, with a global signifcance of 2.5 standard deviations

Performance and calibration of quark/gluon-jet taggers using 140 fb⁻¹ of pp collisions at √s=13 TeV with the ATLAS detector

The identification of jets originating from quarks and gluons, often referred to as quark/gluon tagging, plays an important role in various analyses performed at the Large Hadron Collider, as Standard Model measurements and searches for new particles decaying to quarks often rely on suppressing a large gluon-induced background. This paper describes the measurement of the efficiencies of quark/gluon taggers developed within the ATLAS Collaboration, using √s=13 TeV proton–proton collision data with an integrated luminosity of 140 fb-1 collected by the ATLAS experiment. Two taggers with high performances in rejecting jets from gluon over jets from quarks are studied: one tagger is based on requirements on the number of inner-detector tracks associated with the jet, and the other combines several jet substructure observables using a boosted decision tree. A method is established to determine the quark/gluon fraction in data, by using quark/gluon-enriched subsamples defined by the jet pseudorapidity. Differences in tagging efficiency between data and simulation are provided for jets with transverse momentum between 500 GeV and 2 TeV and for multiple tagger working points