Evidence map›Paper›PMID 38762324›Full record

ArticleLancet (London, England)2024

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.

GBD 2021 Risk Factors Collaborators

Erratum issuedAbstract read
In one paragraph

Article in Lancet (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1,806 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1,806citing papers in PubMed, 8 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1,806 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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1,746 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

GBD 2021 Risk Factors Collaborators

Funding

HRS Yrs29-34: Y33 SSA CoFundingU01AG009740 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jessica Faul, KENNETH M LANGA · 1990 to 2026
$555.8M
Wave IV Data CollectionP01HD031921 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI HARRIS, KATHLEEN MULLAN · 1994 to 2020
$86.1M
Understanding and Improving Healthcare Decision-Making and Outcomes for People Living with Alzheimer's Disease and Related DementiasP01AG005842 · NIA · NATIONAL BUREAU OF ECONOMIC RESEARCH · PI KOSALI ILAYPERUMA SIMON · 1986 to 2026
$56.5M
Integrting Information About Aging SurveysR01AG030153 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Sara Adar, Alden L. Gross · 2007 to 2026
$41.7M
Long Term Multidisciplinary Study of Cancer in Women: The Nurses Health StudyUM1CA186107 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI ELIASSEN, A. HEATHER, STAMPFER, MEIR · 2014 to 2023
$22.3M
WEALTH DISPARITIES AMONG MATURE AND OLDER ADULTSP01AG008291 · NIA · RAND CORPORATION · PI HURD, MICHAEL D · 1989 to 2018
$19.4M
RAND CENTER FOR THE STUDY OF AGINGP30AG012815 · NIA · RAND CORPORATION · PI HURD, MICHAEL D · 1999 to 2020
$13.7M
The Effect of Nanoparticle Encapsulated Resveratrol on Treatment of PeriodontitisKL2TR001882 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Elizabeta Nemeth · 2016 to 2026
$13.1M
Neurocognitive characteristics of short-term risk for suicidal behavior in adolescents R01MH115905 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI LIU, RICHARD T · 2018 to 2023
$3.2M
Temporal dynamics of stress, sleep, and arousal in short-term risk for adolescentsuicidal behaviorRF1MH120830 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI LIU, RICHARD T · 2019 to 2019
$3.1M
Clarifying proximal mechanisms linking interpersonal stressors to suicidal behavior in youth: A multi-informant real-time monitoring studyR01MH124899 · NIMH · RUTGERS, THE STATE UNIV OF N.J. · PI GLENN, CATHERINE ROSE, KLEIMAN, EVAN · 2021 to 2025
$2.9M
Costa Rican Health and Retirement SurveyR01AG031716 · NIA · UNIVERSITY OF CALIFORNIA BERKELEY · PI DOW, WILLIAM H. · 2008 to 2012
$1.6M
NCATS NIH HHS KL2 TR001882NCI NIH HHS UM1 CA186107NIA NIH HHS HHSN271201300071CNIA NIH HHS P01 AG005842NIA NIH HHS P01 AG008291NIA NIH HHS P30 AG012815NIA NIH HHS R01 AG030153NIA NIH HHS R01 AG031716NIA NIH HHS R03 AG043052NIA NIH HHS R21 AG025169NIA NIH HHS R21 AG032572NIA NIH HHS U01 AG009740NICHD NIH HHS P01 HD031921NIMH NIH HHS R01 MH115905NIMH NIH HHS R01 MH124899NIMH NIH HHS R21 MH130767NIMH NIH HHS RF1 MH120830Wellcome Trust
6 · The paper itself

Abstract

backgroundUnderstanding 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.

methodsThe 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.

findingsAmong 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).

interpretationSubstantial 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.

fundingBill & Melinda Gates Foundation.

Indexed as

Global Burden of DiseaseGlobal HealthAdolescentAdultAgedDisability-Adjusted Life YearsFemaleHumansMaleMiddle AgedQuality-Adjusted Life YearsRisk AssessmentRisk FactorsYoung Adult

Identifiers

PMID38762324
PMCPMC11120204

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.