Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.
paper
Cited
Public
- Authors
- GBD 2016 Risk Factors Collaborators
- Year
- 2017
- Journal
- Lancet (London, England)
- PMID
- 28919119
- DOI
- 10.1016/S0140-6736(17)32366-8
- PMCID
- PMC5614451
BACKGROUND: The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of risk factor exposure and attributable burden of disease. By providing estimates over a long time series, this study can monitor risk exposure trends critical to health surveillance and inform policy debates on the importance of addressing risks in context. METHODS: We used the comparative risk assessment framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2016. This study included 481 risk-outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk (RR) and exposure estimates from 22 717 randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources, according to the GBD 2016 source counting methods. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. Finally, we explored four drivers of trends in attributable burden: population growth, population ageing, trends in risk exposure, and all other factors combined. FINDINGS: Since 1990, exposure increased significantly for 30 risks, did not change significantly for four risks, and decreased significantly for 31 risks. Among risks that are leading causes of burden of disease, child growth failure and household air pollution showed the most significant declines, while metabolic risks, such as body-mass index and high fasting plasma glucose, showed significant increases. In 2016, at Level 3 of the hierarchy, the three leading risk factors in terms of attributable DALYs at the global level for men were smoking (124·1 million DALYs [95% UI 111·2 million to 137·0 million]), high systolic blood pressure (122·2 million DALYs [110·3 million to 133·3 million], and low birthweight and short gestation (83·0 million DALYs [78·3 million to 87·7 million]), and for women, were high systolic blood pressure (89·9 million DALYs [80·9 million to 98·2 million]), high body-mass index (64·8 million DALYs [44·4 million to 87·6 million]), and high fasting plasma glucose (63·8 million DALYs [53·2 million to 76·3 million]). In 2016 in 113 countries, the leading risk factor in terms of attributable DALYs was a metabolic risk factor. Smoking remained among the leading five risk factors for DALYs for 109 countries, while low birthweight and short gestation was the leading risk factor for DALYs in 38 countries, particularly in sub-Saharan Africa and South Asia. In terms of important drivers of change in trends of burden attributable to risk factors, between 2006 and 2016 exposure to risks explains an 9·3% (6·9-11·6) decline in deaths and a 10·8% (8·3-13·1) decrease in DALYs at the global level, while population ageing accounts for 14·9% (12·7-17·5) of deaths and 6·2% (3·9-8·7) of DALYs, and population growth for 12·4% (10·1-14·9) of deaths and 12·4% (10·1-14·9) of DALYs. The largest contribution of trends in risk exposure to disease burden is seen between ages 1 year and 4 years, where a decline of 27·3% (24·9-29·7) of the change in DALYs between 2006 and 2016 can be attributed to declines in exposure to risks. INTERPRETATION: Increasingly detailed understanding of the trends in risk exposure and the RRs for each risk-outcome pair provide insights into both the magnitude of health loss attributable to risks and how modification of risk exposure has contributed to health trends. Metabolic risks warrant particular policy attention, due to their large contribution to global disease burden, increasing trends, and variable patterns across countries at the same level of development. GBD 2016 findings show that, while it has huge potential to improve health, risk modification has played a relatively small part in the past decade. FUNDING: The Bill & Melinda Gates Foundation, Bloomberg Philanthropies.
Relationship between SEVs and SDI for the three metabolic, behavioural, and environmental or occupational risk factors that are responsible for the largest number of attributable DALYs globallyEach point corresponds to a country in either 1990 (red) or 2016 (blue). Pearson correlation coefficients have been estimated to summarise the relationship between SEVs and SDI in 1990 and in 2016. SEVs=summary exposure values. SDI=Socio-demographic Index. DALYs=disability-adjusted life-years.
Figure 2
DALYs attributable to all Level 2 risk factors apportioned by Level 2 cause for each risk, both sexes combined, 2016, at the global level (A); for low SDI countries (B); for low-middle SDI countries (C); for middle SDI countries (D); for middle-high SDI countries (E); and for high SDI countries (F)DALYs from causes attributable to each risk factor are shown in different colours. Cutoffs on the SDI scale for the quintiles were selected based on examining the entire distribution of locations between 1980 and 2016. DALYs=disability-adjusted life-years. SDI=Socio-demographic Index.
Leading 30 Level 3 risk factors by attributable DALYs at the global level, 1990, 2006, and 2016, for males (A) and females (B)Risks are connected by lines between time periods. Behavioural risk factors are shown in red, environmental risks in blue, and metabolic risks in green. For the time period of 1990 to 2006 and for 2006–16, three measures of change are shown: percent change in the number of DALYs, percent change in the all-age DALY rate, and percent change in the age-standardised DALY rate. Statistically significant increases or decreases are shown in bold (p<0·05). DALYs=disability-adjusted life-years.
Relationship between attributable DALYs in 2016 for Level 3 risk factors and annualised rate of change in SEV, at the global level, both sexes combined, 1990–2016DALYs are represented on a logarithmic scale. Risks shown exhibited a statistically significant change in SEV between 1990 and 2016. The following six risks, each of which is responsible for fewer than 100 thousand DALYs, are not shown: occupational exposure to benzene, beryllium, cadmium, chromium, formaldehyde, and trichloroethylene. DALYs=disability-adjusted life-years. SEV=summary exposure value. Ambient PM=ambient particulate matter pollution. Alcohol=alcohol use. Arsenic=occupational exposure to arsenic. Asbestos=occupational exposure to asbestos. Asthmagens=occupational asthmagens. BMD=low bone mineral density. BMI=high body-mass index. Calcium=diet low in calcium. Cholesterol=high total cholesterol. Diesel=occupational exposure to diesel engine exhaust. Disc breast=discontinued breastfeeding. Drugs=drug use. Ergonomics=occupational ergonomic factors. Fibre=diet low in fibre. FPG=high fasting plasma glucose. Fruits=diet low in fruits. Handwashing=no access to handwashing facility. Household air=household air pollution from solid fuels. Impaired kidney=impaired kidney function. IPV=intimate partner violence. Iron=iron deficiency. Lead=lead exposure. Legumes=diet low in legumes. Milk=diet low in milk. Nickel=occupational exposure to nickel. Noise=occupational noise. Nuts and seeds=diet low in nuts and seeds. Occupational SHS=occupational exposure to second-hand smoke. Omega 3=diet low in seafood omega 3 fatty acids. Ozone=ambient ozone pollution. PAH=occupational exposure to polycyclic aromatic hydrocarbons. Part breastfeeding=non-exclusive breastfeeding. Physical activity=low physical activity. PM, gases, and fumes=occupational particulate matter, gases, and fumes. Processed meat=diet high in processed meat. PUFA=diet low in polyunsaturated fatty acids. Radon=residential radon. Red meat=diet high in red meat. Sanitation=unsafe sanitation. SBP=high systolic blood pressure. Sexual abuse=childhood sexual abuse. SHS=second-hand smoke. Silica=occupational exposure to silica. Smokeless=smokeless tobacco. Sodium=diet high in sodium. Stunting=child stunting. Sugar-sweetened beverages=diet high in sugar-sweetened beverages. Sulfuric acid=occupational exposure to sulfuric acid. Transfatty acids=diet high in transfatty acids. Underweight=child underweight. Vegetables=diet low in vegetables. Vitamin A=vitamin A deficiency. Wasting=child wasting. Water=unsafe water source. Whole grains=diet low in whole grains. Zinc=zinc deficiency.
Percent change in deaths (A) and DALYs (B) at the global level, 2006–16, due to population growth, population ageing, trends in exposure to all risks included in GBD 2016, and and all other (risk-deleted or residual) factorsResults are shown for all causes combined; communicable, maternal, neonatal, and nutritional diseases; non-communicable diseases; and injuries. DALYs=disability-adjusted life-years.
Figure 6
Percent change in all-cause DALYs, by age, at the global level, 2006-2016, due to the following drivers: population growth, population ageing, trends in exposure to all risks included in GBD 2016, and all other factorsDALYs=disability-adjusted life-years.
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| China's carbon-neutral policies will reduce short-term PM<sub>2.5</sub>-associated excess incidence of cardiovascular diseases. | Ban J et al. | — | 2024 | → |
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| Direct and indirect consumption activities drive distinct urban-rural inequalities in air pollution-related mortality in China. | Wang J et al. | — | 2024 | → |
| Disease Burden and Prediction Analysis of Tracheal, Bronchus, and Lung Cancer Attributable to Residential Radon, Solid Fuels, and Particulate Matter Pollution Under Different Sociodemographic Transitions From 1990 to 2030. | Liu Y et al. | — | 2024 | → |
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| Formative research to understand food beliefs and practices relating to pregnancy on Kei Besar Island, Eastern Indonesia. | Mogi JG et al. | — | 2024 | → |
| Four-year longitudinal associations of physical activity, waist circumference, and blood pressure in UK adolescents. | Waterworth SP et al. | — | 2024 | → |
| Genetic evidence supports a causal relationship between air pollution and brain imaging-derived phenotypes. | Wang Q et al. | — | 2024 | → |
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| Health effects associated with exposure to secondhand smoke: a Burden of Proof study. | Flor LS et al. | — | 2024 | → |
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| Prevalence of probable substance use disorders among children in Ugandan health facilities. | Aber-Odonga H et al. | — | 2024 | → |
| Public health engagement in alcohol licensing in England and Scotland: the ExILEnS mixed-method, natural experiment evaluation. | Fitzgerald N et al. | — | 2024 | → |
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| Relationship between Climate Change, Air Pollution and Allergic Diseases Caused by <i>Ambrosia artemisiifolia</i> (Common Ragweed). | Stoian IM et al. | — | 2024 | → |
| Screening for Hypertension in Adults of a Northern Delta Province in Vietnam. | Van MH et al. | — | 2024 | → |
| Sex-specific associations between the environmental exposures and low-grade inflammation and increased blood pressure in young, healthy subjects. | Marchewka WM et al. | — | 2024 | → |
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| The burden of Cardiovascular diseases in Jordan: a longitudinal analysis from the global burden of disease study, 1990-2019. | Al-Ajlouni YA et al. | — | 2024 | → |
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| The global burden of ischemic heart disease attributed to high fasting plasma glucose: Data from 1990 to 2019. | Shen N et al. | — | 2024 | → |
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| Twenty-year trends of potentially avoidable hospitalizations for hypertension in Switzerland. | Marques-Vidal P et al. | — | 2024 | → |
| TXNIP-NLRP3-GSDMD axis-mediated inflammation and pyroptosis of islet β-cells is involved in cigarette smoke-induced hyperglycemia, which is alleviated by andrographolide. | Xu W et al. | — | 2024 | → |
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| A mixed-methods evaluation of a health-promoting café located in a small health service in rural Victoria, Australia. | Whelan J et al. | — | 2023 | → |
| An omission in guidelines. Cardiovascular disease prevention should also focus on dietary policies for healthcare facilities. | de Frel DL et al. | — | 2023 | → |
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| Different carbohydrate exposures and weight gain-results from a pooled analysis of three population-based studies. | Tammi R et al. | — | 2023 | → |
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| Editorial: Special issue: "Impact of lifestyle und behavioral risk factors on endothelial function and vascular biology"-how lifestyle and behavioral risk factors affect the vasculature. | Daiber A et al. | — | 2023 | → |
| Effects of aircraft noise cessation on blood pressure, cardio- and cerebrovascular endothelial function, oxidative stress, and inflammation in an experimental animal model. | Bayo Jimenez MT et al. | — | 2023 | → |
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| Effects of physical activity interventions on anthropometric indicators and health indices in Chilean children and adolescents: A protocol for systematic review and/or meta-analysis. | Godoy-Cumillaf A et al. | — | 2023 | → |
| Efficacy and safety of standard dose triple combination of telmisartan 80 mg/amlodipine 5 mg/chlorthalidone 25 mg in primary hypertension: A randomized, double-blind, active-controlled, multicenter phase 3 trial. | Cho EJ et al. | — | 2023 | → |
| Emergency Department Management of Patients With Alcohol Intoxication, Alcohol Withdrawal, and Alcohol Use Disorder: A White Paper Prepared for the American Academy of Emergency Medicine. | Strayer RJ et al. | — | 2023 | → |
| Environmental impacts of Indian coal thermal power plants and associated human health risk to the nearby residential communities: A potential review. | Vig N et al. | — | 2023 | → |
| Environmental tobacco smoke exposure and 24-h movement guidelines in Spanish young people. | López-Gil JF et al. | — | 2023 | → |
| Epidemiological Trends in Cardiovascular Disease Mortality Attributable to Modifiable Risk Factors and Its Association with Sociodemographic Transitions across BRICS-Plus Countries. | Nawsherwan et al. | — | 2023 | → |
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| Evaluating the impact of a prison smoking ban on the cardiovascular health of men in a UK prison. | Perrett SE et al. | — | 2023 | → |
| Evidence of the adverse effects of air pollution on the population's health in Spain: analysis of the economic costs of premature deaths. | Casal B et al. | — | 2023 | → |
| Examination of Serum Metabolome Altered by Dietary Carbohydrate, Milk Protein, and Soy Protein Interventions Identified Novel Metabolites Associated with Blood Pressure: The ProBP Trial. | Changwei L et al. | — | 2023 | → |
| Experience with 2 years' intervention to progressively reduce salt supply to kitchens in elderly care facilities-challenges and further research: post hoc analysis of the DECIDE-Salt randomized clinical trial. | Yuan Y et al. | — | 2023 | → |
| Exposure to outdoor particulate matter and risk of respiratory diseases: a systematic review and meta-analysis. | Nakhjirgan P et al. | — | 2023 | → |
| Factors associated with quitting among smoking cessation medication-assisted smokers and ex-smokers: A cross-sectional study in Australia. | Mersha AG et al. | — | 2023 | → |
| Fast Hydroxyl Radical Generation at the Air-Water Interface of Aerosols Mediated by Water-Soluble PM<sub>2.5</sub> under Ultraviolet A Radiation. | Zhang D et al. | — | 2023 | → |
| Fluid intake at work in foresters working in different thermal conditions. | Orysiak J et al. | — | 2023 | → |
| Global burden of disease attributable to high systolic blood pressure in older adults, 1990-2019: an analysis for the Global Burden of Disease Study 2019. | Huang Y et al. | — | 2023 | → |
| Hypertension and Cardiovascular Disease Risk Among Individuals With Versus Without HIV. | Siddiqui M et al. | — | 2023 | → |
| Hypertension and one-year risk of all-cause mortality among women with treated HIV in the United States. | Sadinski LM et al. | — | 2023 | → |
| Hypothetical impact of the Mexican front-of-pack labeling on intake of critical nutrients and energy. | Villaverde P et al. | — | 2023 | → |
| Impact of digital economic development and environmental pollution on residents' health: an empirical analysis based on 279 prefecture-level cities in China. | He YT et al. | — | 2023 | → |
| Impact on sales of adding a smaller serving size of beer and cider in licensed premises: an A-B-A reversal design. | Mantzari E et al. | — | 2023 | → |
| Incidence of Lower Extremity Amputation in Romania: A Nationwide 5-Year Cohort Study, 2015-2019. | Rusu E et al. | — | 2023 | → |
| Inequalities in energy drink consumption among UK adolescents: a mixed-methods study. | Vogel C et al. | — | 2023 | → |
| Influence of land-sea breeze on PM[Formula: see text] prediction in central and southern Taiwan using composite neural network. | Kibirige GW et al. | — | 2023 | → |
| Influence of secondhand smoke exposure on the retinal vasculature of children in Hong Kong. | Cheung CY et al. | — | 2023 | → |
| Interaction of Blood Pressure and Glycemic Status in Developing Cardiovascular Disease: Analysis of a Nationwide Real-World Database. | Suzuki Y et al. | — | 2023 | → |
| Joint Modeling of Blood Pressure Measurements and Survival Time to Cardiovascular Disease Complication among Hypertension Patients Follow-up at DebreTabor Hospital, Ethiopia. | Zelelew AN et al. | — | 2023 | → |
| Machine Learning Models for Ultrafine Particles in Copenhagen, Denmark | Amini H | — | 2023 | — |
| Metabolic risk factors attributed burden in Iran at national and subnational levels, 1990 to 2019. | Moradi S et al. | — | 2023 | → |
| Metabolic Syndrome and Associated Factors in Farmers in Southeastern Brazil: A Cross-Sectional Study. | Cremonini ACP et al. | — | 2023 | → |
| Metabolic Syndrome and Inflammation from Young to Mid-Adulthood and Subclinical Kidney Damage in Middle-Aged Australians. | Liu C et al. | — | 2023 | → |
| Modeling the impact of COVID-19 pandemic-driven increases in alcohol consumption on health outcomes and hospitalization costs in the United States. | Barbosa C et al. | — | 2023 | → |
| More recent insights into the breast cancer burden across BRICS-Plus: Health consequences in key nations with emerging economies using the global burden of disease study 2019. | Mubarik S et al. | — | 2023 | → |
| Mother and newborn skin-to-skin contact and timely initiation of breastfeeding in sub-Saharan Africa. | Aboagye RG et al. | — | 2023 | → |
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| Political Economy of Non-Communicable Disease (NCD) prevention and control in Lebanon: identifying challenges and opportunities for policy change and care provision reforms. | Bou-Orm IR et al. | — | 2023 | → |
| Pollutants, including Organophosphorus and Organochloride Pesticides, May Increase the Risk of Cardiac Remodeling and Atrial Fibrillation: A Narrative Review. | Le Quilliec E et al. | — | 2023 | → |
| Population attributable fraction estimates of cardiovascular diseases in different blood pressure levels in a large-scale cross-sectional study: a focus on prevention strategies and treatment coverage. | Keykhaei M et al. | — | 2023 | → |
| Predicting Alcohol Consumption Patterns for Individuals with a User-Friendly Parsimonious Statistical Model. | Liang W et al. | — | 2023 | → |
| Prevalence and associated factors of pediatric hypertension in Jazan region, south of the Kingdom of Saudi Arabia. A pilot cross-sectional study. | El-Setouhy M et al. | — | 2023 | → |
| Prevalence of Cardiovascular Risk Factors among Young Adults (18-25 Years) in Mozambique. | Silva I et al. | — | 2023 | → |
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