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. Funding: Bill & Melinda Gates Foundation

Balancing the energy budget between star formation and active galactic nuclei in high-redshift infrared luminous galaxies

We present deep Spitzer mid-infrared spectroscopy, along with 16, 24, 70, and 850 μm photometry, for 22 galaxies located in the Great Observatories Origins Deep Survey-North (GOODS-N) field. The sample spans a redshift range of 0.6 lsim z lsim 2.6, 24 μm flux densities between ~0.2 and 1.2 mJy, and consists of submillimeter galaxies (SMGs), X-ray or optically selected active galactic nuclei (AGNs), and optically faint (zAB > 25 mag) sources. We find that infrared (IR; 8-1000 μm) luminosities derived by fitting local spectral energy distributions (SEDs) with 24 μm photometry alone are well matched to those when additional mid-infrared spectroscopic and longer wavelength photometric data are used for galaxies having z lsim 1.4 and 24 μm-derived IR luminosities typically lsim3 × 1012 L sun. However, for galaxies in the redshift range between 1.4 lsim z lsim 2.6, typically having 24-μm-derived IR luminosities gsim3 × 1012 L sun, IR luminosities are overestimated by an average factor of ~5 when SED fitting with 24 μm photometry alone. This result arises partly due to the fact that high-redshift galaxies exhibit aromatic feature equivalent widths that are large compared to local galaxies of similar luminosities. Using improved estimates for the IR luminosities of these sources, we investigate whether their infrared emission is found to be in excess relative to that expected based on extinction-corrected UV star formation rates (SFRs), possibly suggesting the presence of an obscured AGN. Through a spectral decomposition of mid-infrared spectroscopic data, we are able to isolate the fraction of IR luminosity arising from an AGN as opposed to star formation activity. This fraction is only able to account for ~30% of the total IR luminosity among the entire sample and ~35% of the "excess" IR emission among these sources, on average, suggesting that AGNs are not the dominant cause of the inferred "mid-infrared excesses" in these systems. Of the sources identified as having mid-infrared excesses, half are accounted for by using proper bolometric corrections while half show the presence of obscured AGNs. This implies sky and space densities for Compton-thick AGNs of ~1600 deg-2 and ~1.3 × 10-4 Mpc-3, respectively. We also note that IR luminosities derived from SED fitting the mid-infrared and 70 μm broadband photometry agree within ~50% to those values estimated using the additional mid-infrared spectroscopic and submillimeter data. An inspection of the far-infrared (FIR)-radio correlation shows no evidence for evolution over this redshift range. However, we find that the SMGs have IR/radio ratios which are a factor of ~3 lower, on average, than what is measured for star-forming galaxies in the local universe

Evaluating the utility of self-reported questionnaire data to screen for dysglycemia in young adults: Findings from the US National Health and Nutrition Examination Survey

Dysglycemia, including prediabetes and type 2 diabetes, is dangerous and widespread. Yet, the condition is transiently reversible and sequelae preventable, prompting the use of prediction algorithms to quickly assess dysglycemia status through self-reported data. However, as current algorithms have largely been developed in older populations, their application to younger adults is uncertain considering associations between risk factors and dysglycemia vary by age. We sought to identify sex-specific predictors of current dysglycemia among young adults and evaluate their ability to screen for prediabetes and undiagnosed diabetes. We analyzed 2005–2014 data from the National Health and Nutrition Examination Survey for 3251 participants aged 20–39, who completed an oral glucose tolerance test (OGTT), had not been diagnosed with diabetes, and, for females, were not pregnant. Sex-specific stepwise logistic models were fit with predictors identified from univariate analyses. Risk scores were developed using adjusted odds ratios and model performance was assessed using area under the curve (AUC) measures. The OGTT identified 906 (27.9%) and 78 (2.4%) participants with prediabetes or undiagnosed diabetes, respectively. Predictors of dysglycemia status for males were BMI, age, race, and first-degree family history of diabetes, and, in addition to those, education, delivered baby weight, waist circumference, and vigorous physical activity for females. Our male- and female-specific models demonstrated improved validity to assess dysglycemia presence among young adults relative to the widely-used American Diabetes Association test (AUC = 0.69 vs. 0.61; 0.92 vs. 0.71, respectively). Thus, age-specific scoring algorithms employing questionnaire data show promise and are effective in identifying dysglycemia among young adults

Radon and cancers other than lung cancer in underground miners: a collaborative analysis of 11 studies

Background: Exposure to the radioactive gas radon and its progeny (222Rn and its radioactive decay products) has recently been linked to a variety of cancers other than lung cancer ingeographic correlation studies of domestic radon exposure and in individual cohorts of occupationally exposed miners.<p></p> Purpose: This study was designed to characterize further the risks for cancers other than lung cancer (i.e., non-lung cancers) from atmospheric radon.<p></p> Methods: Mortality from non-lung cancer was examined in a collaborative analysis of data from 11 cohorts of underground miners in which radon-related excesses of lung cancer had been established. The study included 64 209 men who were employed in the mines for 6.4 years on average, received average cumulative exposures of 155 working-level months (WLM), and were followed for 16.9 years on average.<p></p> Results: For all non-lung cancers combined, mortality was close to that expected from mortality rates in the areas surrounding the mines (ration of observed to expected deaths (O/E) = 1.01; 95% confidence interval (CI) = 0.95–1.07, based on 1179 deaths), and mortality did not increase with increasing cumulative exposure. Among 28 individual cancer categories, statistically significant increases in mortality for cancers of the stomach (O/E = 1.33; 95% CI = 1.16–1.52) and liver (O/E = 1.73; 95% CI = 1.29–2.28) and statistically significant decreases for cancers of the tongue and mouth (O/E = 0.52; 95% CI = 0.26–0.93), pharynx (O/E = 0.5; 95% CI = 0.16–0.66), and colon (O/E = 0.77; 95% CI = 0.63–0.95) were observed. For leukemia, mortality was increased in the period less than 10 years since starting work (O/E = 1.93; 95% CI = 1.19–2.95) but not subsequently. For none of these diseases was mortality significantly related to cumulative exposure. Among the remaining individual categories of non-lung cancer, mortality was related to cumulative exposure only for cancer of the pancreas (excess relative risk per WLM = 0.07%; 95% CI = 0.01–0.12) and, in the period less than 10 years since the start of employment, for other and unspecified cancers (excess relative risk per WLM = 0.22%; 95% CI = 0.08–0.37).<p></p> Conclusions: The increases in mortality from stomach and liver cancers and leukemia are unlikely to have been caused by radon, since they are unrelated to cumulative exposure. The association between cumulative exposure and pancreatic cancer seems likely to be a chance finding, while the association between cumulative exposure and other and unspecified cancers was caused by deaths certified as due to carcinomatosis (widespread disseminated cancer throughout the body) that were likely to have been due to lung cancers. This study, therefore, provides considerable evidence that high concentrations of radon in air do not cause a material risk of mortality from cancers other than lung cancer.<p></p> Implications: Protection standards for radon should continue to be based on consideration of the lung cancer risk alone.<p></p&gt