Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Phylogeny of Neobursaridium reshapes the systematics of Paramecium (Oligohymenophorea, Ciliophora)

The subclass Peniculia (Oligohymenophorea, Intramacronucleata) is one of the most known groups of the phylum Ciliophora, being composed by very notorious representatives, such as Paramecium and Frontonia. Nevertheless, phylogenetic relationships among genera within this subclass are still far from being resolved. Moreover, for several members of the group the characterization by molecular markers is still lacking, such as for Wenrichia, Clathrostoma, Paraclathrostoma, Didieria and, to date, also for Neobursaridium. The finding of one strain of Neobursaridium gigas from India led to the first molecular characterization of this uncommonly sampled ciliate. The 18S rDNA sequence and the COI sequence were obtained and used for phylogenetic analyses. Moreover, the partial mitochondrial genome of N. gigas was sequenced, annotated and employed for phylogenomics analysis. To increase the sampling effort for the Paramecium clade, several newly obtained 18S rDNA sequences of parameciids are herein presented. Unexpectedly, the inclusion of N. gigas's molecular data in phylogenetics/phylogenomics analyses did not help to solve the complex evolution relationships inside Peniculia. Conversely, it raised new and intriguing questions about Paramecium phylogeny, since N. gigas clustered inside Paramecium clade as sister species of Paramecium bursaria in all the performed analyses. A critical revision of past and present data led to rename N. gigas as Paramecium gigas (Balech, 1941) comb. nov., and triggered the revision of genus Paramecium, with the proposal of the new subgenus Gigaparamecium subgen. nov. Hypotheses on the evolution of giant morphologies in ciliates are also discussed

Tuberculosis: integrated studies for a complex disease 2050

Tuberculosis (TB) has been a disease for centuries with various challenges [1]. Like other places where challenges and opportunities come together, TB challenges were the inspiration for the scientific community to mobilize different groups for the purpose of interest. For example, with the emergence of drug resistance, there has been a huge volume of research on the discovery of new medicines and drug delivery methods and the repurposing of old drugs [2, 3]. Moreover, to enhance the capacity to detect TB cases, studies have sought diagnostics and biomarkers, with much hope recently expressed in the direction of point-of-care tests [4]. Despite all such efforts as being highlighted in 50 Chapters of this volume, we are still writing about TB and thinking about how to fight this old disease–implying that the problem of TB might be complex, so calling the need for an integrated science to deal with multiple dimensions in a simultaneous and effective manner. We are not the first one; there have been proposed integrated platform for TB research, integrated prevention services, integrated models for drug screening, integrated imaging protocol, integrated understanding of the disease pathogenesis, integrated control models, integrated mapping of the genome of the pathogen, etc. [5–12], to name some. These integrated jobs date back decades ago. So, a question arises: why is there a disease named TB yet? It might be due to the fact that this integration has happened to a scale that is not global, and so TB remains to be a problem, especially in resource-limited settings. Hope Tuberculosis: Integrated Studies for a Complex Disease helps to globalize the integrated science of TB.info:eu-repo/semantics/publishedVersio