Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

GBD 2015 Risk Factors Collaborators

Abstract

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context.

Methods: We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors-the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI).

Findings: Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6-58·8) of global deaths and 41·2% (39·8-42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa.

Interpretation: Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden.

Funding: Bill & Melinda Gates Foundation.

Copyright © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license. Published by Elsevier Ltd.. All rights reserved.

Figures

Figure 1
Figure 1
Global proportion of all-cause DALYs attributable to behavioural, environmental and occupational, and metabolic risk factors and their overlaps by region for both sexes combined in 2015 Locations are reported in order of total all-cause DALYs population attributable fraction. DALYs=disability-adjusted life-years. ∩=interaction.
Figure 2
Figure 2
Global DALYs attributable to Level 2 risk factors for (A) men and (B) women in 2015 DALYs=disability-adjusted life-years.
Figure 3
Figure 3
Leading 30 Level 3 global risk factors for DALYs for both sexes combined, 1990, 2005, and 2015, with percentage change in number of DALYs, and all-age, and age-standardised rates Risks are connected by lines between time periods. For the time period of 1990 to 2005 and for 2005 to 2015, 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. Changes that are statistically significant are shown in bold. DALYs=disability-adjusted life-years.
Figure 4
Figure 4
Global attributable DALYs in 2015 for each Level 3 risk factor versus percentage change in SEV from 1990 to 2015 for both sexes combined Risks with 100 000 DALYs or more are presented. DALYs are represented on a logarithmic scale. We have excluded occupational exposure to benzene, diesel engine exhaust, and occupational exposure to silica, which all had SEV increases of greater than 50%. Ambient PM=ambient particulate matter pollution. Arsenic=occupational exposure to arsenic. Asbestos=occupational exposure to asbestos. Asthmagens=occupational asthmagens. Beryllium=occupational exposure to beryllium. BMD=low bone mineral density. BMI=high body-mass index. Cadmium=occupational exposure to cadmium. Calcium=diet low in calcium. Cholesterol=high total cholesterol. Chromium=occupational exposure to chromium. DALYs=disability-adjusted life-years. Ergonomic=occupational ergonomic factors. Fibre=diet low in fibre. Formaldehyde=occupational exposure to formaldehyde. FPG=high fasting plasma glucose. Fruits=diet low in fruits. GFR=low glomerular filtration rate. Handwashing=no handwashing with soap. Household air=household air pollution. IPV=intimate partner violence. Lead=lead exposure. 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. 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. SEV=summary exposure value. SHS=second-hand smoke. Sodium=diet high in sodium. Sugar-sweetened beverages=diet high in sugar-sweetened beverages. Sulphuric acid=occupational exposure to sulphuric acid. Stunting=childhood stunting. Trans fatty acids=diet high in trans fatty acids. Trichloroethylene=occupational exposure to trichloroethylene. Underweight=childhood underweight. Vegetables=diet low in vegetables. Wasting=childhood wasting. Water=unsafe water. Whole grains=diet low in whole grains.
Figure 5
Figure 5
Global decomposition of changes in all-cause DALYs attributable to Level 3 risk factors from 1990 to 2015 Risks are reported in order of percentage change in the number of attributable DALYs from 1990 to 2015. We excluded DALYs attributable to unsafe sex because this risk factor is not estimated on the basis of exposure and relative risk. Changes due to population growth, population ageing, risk exposure, and the risk-deleted DALY rate are shown. DALYs=disability-adjusted life-years.
Figure 6
Figure 6
Coevolution of SEV and SDI for the top ten global risks in terms of attributable disability-adjusted life-years in 2015 Coloured points show SEVs for Global Burden of Disease regions. Each point represents 1 year in 5 year intervals from 1990 to 2015. The solid black line represents the expected SEV on the basis of SDI alone. SDI=Socio-demographic Index. SEV=summary exposure values.
Figure 7
Figure 7
Leading ten Level 3 risk factors in terms of disability-adjusted life-years for both sexes combined in 2015, by location The 15 leading risk factors are coloured. Bone mineral density=low bone mineral density. Handwashing=no handwashing with soap. Int partner violence=intimate partner violence. Nuts and seeds=diet low in nuts and seeds. Occ=occupational. Particulate matter=ambient particulate matter pollution. Physical activity=low physical activity. Processed meat=diet high in processed meat. SDI=Socio-demographic Index. Subopt=suboptimal. Sweetened beverages=diet high in sugar-sweetened beverages. Vegetables=diet low in vegetables.
Figure 7
Figure 7
Leading ten Level 3 risk factors in terms of disability-adjusted life-years for both sexes combined in 2015, by location The 15 leading risk factors are coloured. Bone mineral density=low bone mineral density. Handwashing=no handwashing with soap. Int partner violence=intimate partner violence. Nuts and seeds=diet low in nuts and seeds. Occ=occupational. Particulate matter=ambient particulate matter pollution. Physical activity=low physical activity. Processed meat=diet high in processed meat. SDI=Socio-demographic Index. Subopt=suboptimal. Sweetened beverages=diet high in sugar-sweetened beverages. Vegetables=diet low in vegetables.
Figure 7
Figure 7
Leading ten Level 3 risk factors in terms of disability-adjusted life-years for both sexes combined in 2015, by location The 15 leading risk factors are coloured. Bone mineral density=low bone mineral density. Handwashing=no handwashing with soap. Int partner violence=intimate partner violence. Nuts and seeds=diet low in nuts and seeds. Occ=occupational. Particulate matter=ambient particulate matter pollution. Physical activity=low physical activity. Processed meat=diet high in processed meat. SDI=Socio-demographic Index. Subopt=suboptimal. Sweetened beverages=diet high in sugar-sweetened beverages. Vegetables=diet low in vegetables.
Figure 7
Figure 7
Leading ten Level 3 risk factors in terms of disability-adjusted life-years for both sexes combined in 2015, by location The 15 leading risk factors are coloured. Bone mineral density=low bone mineral density. Handwashing=no handwashing with soap. Int partner violence=intimate partner violence. Nuts and seeds=diet low in nuts and seeds. Occ=occupational. Particulate matter=ambient particulate matter pollution. Physical activity=low physical activity. Processed meat=diet high in processed meat. SDI=Socio-demographic Index. Subopt=suboptimal. Sweetened beverages=diet high in sugar-sweetened beverages. Vegetables=diet low in vegetables.
Figure 7
Figure 7
Leading ten Level 3 risk factors in terms of disability-adjusted life-years for both sexes combined in 2015, by location The 15 leading risk factors are coloured. Bone mineral density=low bone mineral density. Handwashing=no handwashing with soap. Int partner violence=intimate partner violence. Nuts and seeds=diet low in nuts and seeds. Occ=occupational. Particulate matter=ambient particulate matter pollution. Physical activity=low physical activity. Processed meat=diet high in processed meat. SDI=Socio-demographic Index. Subopt=suboptimal. Sweetened beverages=diet high in sugar-sweetened beverages. Vegetables=diet low in vegetables.
Figure 7
Figure 7
Leading ten Level 3 risk factors in terms of disability-adjusted life-years for both sexes combined in 2015, by location The 15 leading risk factors are coloured. Bone mineral density=low bone mineral density. Handwashing=no handwashing with soap. Int partner violence=intimate partner violence. Nuts and seeds=diet low in nuts and seeds. Occ=occupational. Particulate matter=ambient particulate matter pollution. Physical activity=low physical activity. Processed meat=diet high in processed meat. SDI=Socio-demographic Index. Subopt=suboptimal. Sweetened beverages=diet high in sugar-sweetened beverages. Vegetables=diet low in vegetables.
Figure 7
Figure 7
Leading ten Level 3 risk factors in terms of disability-adjusted life-years for both sexes combined in 2015, by location The 15 leading risk factors are coloured. Bone mineral density=low bone mineral density. Handwashing=no handwashing with soap. Int partner violence=intimate partner violence. Nuts and seeds=diet low in nuts and seeds. Occ=occupational. Particulate matter=ambient particulate matter pollution. Physical activity=low physical activity. Processed meat=diet high in processed meat. SDI=Socio-demographic Index. Subopt=suboptimal. Sweetened beverages=diet high in sugar-sweetened beverages. Vegetables=diet low in vegetables.

References

    1. Public Health England . From evidence into action: opportunities to protect and improve the nation's health. Public Health England; London: 2014.
    1. Institute for Health Metrics and Evaluation President Ian Khama: emboldened by evidence to reduce harms of alcohol use in Botswana. (accessed July 24, 2016).
    1. Lim SS, Vos T, Flaxman AD. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2224–2260.
    1. GBD 2013 Risk Factors Collaborators. Forouzanfar MH, Alexander L. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;386:2287–2323.
    1. Kellerborg K, Danielsson AK, Allebeck P, Coates MM, Agardh E. Disease burden attributed to alcohol: how methodological advances in the Global Burden of Disease 2013 Study have changed the estimates in Sweden. Scand J Public Health. 2016;44:604–610.
    1. Murray CJ, Richards MA, Newton JN. UK health performance: findings of the Global Burden of Disease Study 2010. Lancet. 2013;381:997–1020.
    1. Yang G, Wang Y, Zeng Y. Rapid health transition in China, 1990–2010: findings from the Global Burden of Disease Study 2010. Lancet. 2013;381:1987–2015.
    1. Kivimäki M, Vineis P, Brunner EJ. How can we reduce the global burden of disease? Lancet. 2015;386:2235–2237.
    1. American Institute for Cancer Research . Food, nutrition, physical activity, and the prevention of cancer: a global perspective. American Institute for Cancer Research; Washington, DC: 2007.
    1. SPRINT Research Group. Wright JT, Williamson JD. A randomized trial of intensive versus standard blood-pressure control. N Engl J Med. 2015;373:2103–2116.
    1. Yusuf S, Lonn E, Pais P. Blood-pressure and cholesterol lowering in persons without cardiovascular disease. N Engl J Med. 2016;374:2032–2043.
    1. Boekholdt SM, Hovingh GK, Mora S. Very low levels of atherogenic lipoproteins and the risk for cardiovascular events: a meta-analysis of statin trials. J Am Coll Cardiol. 2014;64:485–494.
    1. Mente A, O'Donnell M, Rangarajan S. Associations of urinary sodium excretion with cardiovascular events in individuals with and without hypertension: a pooled analysis of data from four studies. Lancet. 2016;388:465–475.
    1. Burnett RT, Pope CA, Ezzati M. An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environ Health Perspect. 2014;122:397–403.
    1. Ioannidis JP. Implausible results in human nutrition research. BMJ. 2013;347:f6698.
    1. Murray CJ, Lopez AD. On the comparable quantification of health risks: lessons from the Global Burden of Disease Study. Epidemiol. 1999;10:594–605.
    1. Stevens GA, Alkema L, Black RE. Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement. Lancet. 2016 published online June 28.
    1. Ng M, Freeman MK, Fleming TD. Smoking prevalence and cigarette consumption in 187 countries, 1980–2012. JAMA. 2014;311:183–192.
    1. Das Gupta P. Standardization and decomposition of rates: a user's manual. US Bureau of the Census; Washington, DC: 1993.
    1. UNDP . Human Development Report 2015. United Nations Development Programme; New York: 2015.
    1. Popkin BM. The nutrition transition in low-income countries: an emerging crisis. Nutr Rev. 1994;52:285–298.
    1. Omran AR. The epidemiologic transition. A theory of the epidemiology of population change. Milbank Mem Fund Q. 1971;49:509–538.
    1. Preston SH. The changing relation between mortality and level of economic development. Popul Stud. 1975;29:231–248.
    1. Vallin J, Meslé F. Convergences and divergences in mortality: a new approach of health transition. Demogr Res. 2004;2:11–44.
    1. Goryakin Y, Suhrcke M. Economic development, urbanization, technological change and overweight: what do we learn from 244 Demographic and Health Surveys? Econ Hum Biol. 2014;14:109–127.
    1. Popkin BM. Global nutrition dynamics: the world is shifting rapidly toward a diet linked with noncommunicable diseases. Am J Clin Nutr. 2006;84:289–298.
    1. GBD 2015 Mortality and Causes of Death Collaborators Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1459–1544.
    1. GBD 2015 Diseases and Injury Incidence and prevalence Collaborators Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1545–1604.
    1. GBD 2015 Child Mortality Collaborators Global, regional, national, and selected subnational levels of stillbirths, neonatal, infant, and under-5 mortality, 1980–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388:1605–1660.
    1. Granich R, Gupta S, Hersh B. Trends in AIDS deaths, new infections and ART coverage in the top 30 countries with the highest AIDS mortality burden; 1990–2013. PLoS One. 2015;10:e0131353.
    1. UN Programme on HIV/AIDS . The Gap Report. United Nations programme on HIV/AIDS; Geneva: 2014.
    1. UNDP World AIDS Day: record drop in cost of HIV treatment. Nov 30, 2015. (accessed July 24, 2016).
    1. Scandinavian Simvastatin Survival Study Group Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S) Lancet. 1994;344:1383–1389.
    1. Fihn SD, Gardin JM, Abrams J. 2012 ACCF/AHA/ACP/AATS/PCNA/SCAI/STS Guideline for the diagnosis and management of patients with stable ischemic heart disease: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines, and the American College of Physicians, American Association for Thoracic Surgery, Preventive Cardiovascular Nurses Association, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons. J Am Coll Cardiol. 2012;60:e44–164.
    1. Augoustides JG, Ramakrishna H. Recent advances in the management of coronary artery disease: highlights from the literature. J Cardiothorac Vasc Anesth. 2009;23:259–265.
    1. Writing Committee Members. Drozda JP, Ferguson TB. 2015 ACC/AHA Focused Update of Secondary Prevention Lipid Performance Measures: a Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures. Circ Cardiovasc Qual Outcomes. 2016;9:68–95.
    1. Yancy CW, Jessup M, Bozkurt B. 2016 ACC/AHA/HFSA Focused Update on New Pharmacological Therapy for Heart Failure: an update of the 2013 ACCF/AHA Guideline for the Management of Heart Failure: a Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Failure Society of America. Circulation. 2016 published online May 20.
    1. National Cancer Institute Progress & trends: decreased mortality, increased survival rates. (accessed July 24, 2016).
    1. Nolte E, McKee M. Measuring the health of nations: analysis of mortality amenable to health care. BMJ. 2003;327:1129.
    1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2015. CA Cancer J Clin. 2015;65:5–29.
    1. Forouzanfar MH, Foreman KJ, Delossantos AM. Breast and cervical cancer in 187 countries between 1980 and 2010: a systematic analysis. Lancet. 2011;378:1461–1484.
    1. Anderson BO, Senie RT, Vetto JT, Wong GY, McCormick B, Borgen PI. Improved survival in young women with breast cancer. Ann Surg Oncol. 1995;2:407–415.
    1. Murawa P, Murawa D, Adamczyk B, Połom K. Breast cancer: actual methods of treatment and future trends. Rep Pract Oncol Radiother. 2014;19:165–172.
    1. Kopp HG, Kuczyk M, Classen J. Advances in the treatment of testicular cancer. Drugs. 2006;66:641–659.
    1. Arulogun S, Hertzberg M, Gandhi MK. Recent treatment advances in Hodgkin lymphoma: a concise review. Intern Med J. 2016 published online March 1.
    1. UNICEF . Progress on sanitation and drinking water. United Nations International Children's Emergency Fund; New York: 2015.
    1. Millennium Project Goals, targets and indicators. (accessed July 24, 2016).
    1. UN . The Millennium Development Goals report 2015. United Nations; Geneva: 2015.
    1. WHO Sanitation. June, 2015. (accessed July 24, 2016).
    1. UN Goal 6: ensure access to water and sanitation for all. (accessed July 24, 2016).
    1. International Council for Science . Review of the Sustainable Development Goals: the science perspective. International Council for Science; Paris: 2015.
    1. WHO MPOWER: a policy package to reverse the tobacco epidemic. 2008. (accessed July 24, 2016).
    1. International Agency for Research on Cancer . Evaluating the effectiveness of smoke-free policies. International Agency for Research on Cancer; Lyon: 2009.
    1. US Department of Health and Human Services . The health consequences of involuntary exposure to tobacco smoke: a report of the Surgeon General. US Department of Health and Human Services; Atlanta: 2006.
    1. Hopkins DP, Razi S, Leeks KD. Smokefree policies to reduce tobacco use. A systematic review. Am J Prev Med. 2010;38:S275–S289.
    1. Callinan JE, Clarke A, Doherty K, Kelleher C. Legislative smoking bans for reducing secondhand smoke exposure, smoking prevalence and tobacco consumption. Cochrane Database Syst Rev. 2010;14 CD005992.
    1. WHO Turkey marks progress in fight against noncommunicable diseases. September, 2012. (accessed July 24, 2016).
    1. WHO . Global status report on noncommunicable diseases 2010. World Health Organization; Geneva: 2011.
    1. Peto R, Lopez AD, Boreham J, Thun M, Heath C. Mortality from tobacco in developed countries: indirect estimation from national vital statistics. Lancet. 1992;339:1268–1278.
    1. Carter BD, Abnet CC, Feskanich D. Smoking and mortality—beyond established causes. N Engl J Med. 2015;372:631–640.
    1. Subar AF, Thompson FE, Kipnis V. Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: the Eating at America's Table Study. Am J Epidemiol. 2001;154:1089–1099.
    1. Willett W. Nutritional epidemiology. Oxford University Press USA; New York: 2013.
    1. National Cancer Institute Effects of measurement error. (accessed July 24, 2016).
    1. Blackwell M, Honaker J, King G. A unified approach to measurement error and missing data: overview and applications. Sociol Methods Res. 2015 published online June 30.
    1. Brenner H, Loomis D. Varied forms of bias due to nondifferential error in measuring exposure. Epidemiol. 1994;5:510–517.
    1. Hill RJ, Davies PS. The validity of self-reported energy intake as determined using the doubly labelled water technique. Br J Nutr. 2001;85:415–430.
    1. McLean RM. Measuring population sodium intake: a review of methods. Nutrients. 2014;6:4651–4662.
    1. Harvard T.H. Chan School of Public Health. Pooling project of prospective studies of diet and cancer: cohort study participants. (accessed July 24, 2016).
    1. Chowdhury R, Warnakula S, Kunutsor S. Association of dietary, circulating, and supplement fatty acids with coronary risk: a systematic review and meta-analysis. Ann Intern Med. 2014;160:398–406.
    1. Pimpin L, Wu JH, Haskelberg H, Del Gobbo L, Mozaffarian D. Is butter back? A systematic review and meta-analysis of butter consumption and risk of cardiovascular disease, diabetes, and total mortality. PLoS One. 2016;11:e0158118.
    1. WHO About 9 voluntary global targets—global monitoring framework for NCDs. (accessed July 24, 2016).
    1. US Food and Drug Administration FDA issues draft guidance to food industry for voluntarily reducing sodium in processed and commercially prepared food. June 1, 2016. (accessed July 24, 2016).
    1. Lachat C, Otchere S, Roberfroid D. Diet and physical activity for the prevention of noncommunicable diseases in low- and middle-income countries: a systematic policy review. PLoS Med. 2013;10:e1001465.
    1. Trieu K, Neal B, Hawkes C. Salt reduction initiatives around the world—a systematic review of progress towards the global target. PLoS One. 2015;10:e0130247.
    1. Bonita R, Magnusson R, Bovet P. Country actions to meet UN commitments on non-communicable diseases: a stepwise approach. Lancet. 2013;381:575–584.
    1. He FJ, MacGregor GA. Reducing population salt intake worldwide: from evidence to implementation. Prog Cardiovasc Dis. 2010;52:363–382.
    1. Lonn EM, Bosch J, López-Jaramillo P. Blood-pressure lowering in intermediate-risk persons without cardiovascular disease. N Engl J Med. 2016;374:2009–2020.
    1. O'Donnell M, Mente A, Rangarajan S. Urinary sodium and potassium excretion, mortality, and cardiovascular events. N Engl J Med. 2014;371:612–623.
    1. Institute of Medicine . Sodium intake in populations: assessment of evidence. The National Academies Press; Washington, DC: 2013.
    1. Trinquart L, Johns DM, Galea S. Why do we think we know what we know? A metaknowledge analysis of the salt controversy. Int J Epidemiol. 2016;45:251–260.
    1. Cogswell ME, Mugavero K, Bowman BA, Frieden TR. Dietary sodium and cardiovascular disease risk—measurement matters. N Engl J Med. 2016;375:580–586.
    1. Frieden TR. Sodium reduction-saving lives by putting choice into consumers' hands. JAMA. 2016;316:579–580.
    1. He FJ, MacGregor GA. Hypertension: salt: flawed research should not divert actions to reduce intake. Nat Rev Nephrol. 2016;12:514–515.
    1. Cook NR, Appel LJ, Whelton PK. Lower levels of sodium intake and reduced cardiovascular risk. Circulation. 2014;129:981–989.
    1. WHO . Global action plan for the prevention and control of noncommunicable diseases 2013–2020. World Health Organization; Geneva: 2013.
    1. UN General Assembly Political Declaration of the High-level Meeting of the General Assembly on the Prevention and Control of Non-communicable Diseases. (accessed July 24, 2016).
    1. Afshin A, Penalvo J, Del Gobbo L. CVD prevention through policy: a review of mass media, food/menu labeling, taxation/subsidies, built environment, school procurement, worksite wellness, and marketing standards to improve diet. Curr Cardiol Rep. 2015;17:98.
    1. US Department of Agriculture . Scientific report of the 2015 Dietary Guidelines Advisory Committee. US Department of Agriculture; 2015.
    1. Mann S, Beedie C, Jimenez A. Differential effects of aerobic exercise, resistance training and combined exercise modalities on cholesterol and the lipid profile: review, synthesis and recommendations. Sports Med Auckl Nz. 2014;44:211–221.
    1. Dowse GK, Gareeboo H, Alberti KG. Changes in population cholesterol concentrations and other cardiovascular risk factor levels after five years of the non-communicable disease intervention programme in Mauritius. Mauritius Non-communicable Disease Study Group. BMJ. 1995;311:1255–1259.
    1. Vartiainen E, Laatikainen T, Tapanainen H, Puska P. Changes in Serum cholesterol and diet in North Karelia and all Finland. Glob Heart. 2016;11:179–184.
    1. Singh GM, Danaei G, Farzadfar F. The age-specific quantitative effects of metabolic risk factors on cardiovascular diseases and diabetes: a pooled analysis. PLoS One. 2013;8:e65174.
    1. Lawes CM, Rodgers A, Bennett DA. Blood pressure and cardiovascular disease in the Asia Pacific region. J Hypertens. 2003;21:707–716.
    1. Roerecke M, Rehm J. Ischemic heart disease mortality and morbidity rates in former drinkers: a meta-analysis. Am J Epidemiol. 2011;173:245–258.
    1. Roerecke M, Rehm J. Alcohol consumption, drinking patterns, and ischemic heart disease: a narrative review of meta-analyses and a systematic review and meta-analysis of the impact of heavy drinking occasions on risk for moderate drinkers. BMC Med. 2014;12:182.
    1. Fillmore KM, Stockwell T, Chikritzhs T, Bostrom A, Kerr W. Moderate alcohol use and reduced mortality risk: systematic error in prospective studies and new hypotheses. Ann Epidemiol. 2007;17:S16–S23.
    1. Bergmann MM, Rehm J, Klipstein-Grobusch K. The association of pattern of lifetime alcohol use and cause of death in the European prospective investigation into cancer and nutrition (EPIC) study. Int J Epidemiol. 2013;42:1772–1790.
    1. Holmes MV, Dale CE, Zuccolo L. Association between alcohol and cardiovascular disease: Mendelian randomisation analysis based on individual participant data. BMJ. 2014;349:g4164.
    1. Stockwell T, Greer A, Fillmore K, Chikritzhs T, Zeisser C. How good is the science? BMJ. 2012;344:e2276.
    1. Dam MK, Hvidtfeldt UA, Tjønneland A, Overvad K, Grønbæk M, Tolstrup JS. Five year change in alcohol intake and risk of breast cancer and coronary heart disease among postmenopausal women: prospective cohort study. BMJ. 2016;353:i2314.
    1. Koloverou E, Panagiotakos DB, Pitsavos C. Effects of alcohol consumption and the metabolic syndrome on 10-year incidence of diabetes: the ATTICA study. Diabetes Metab. 2015;41:152–159.
    1. Hange D, Sigurdsson JA, Björkelund C, Sundh V, Bengtsson C. A 32-year longitudinal study of alcohol consumption in Swedish women: reduced risk of myocardial infarction but increased risk of cancer. Scand J Prim Health Care. 2015;33:153–162.
    1. Li XH, Yu FF, Zhou YH, He J. Association between alcohol consumption and the risk of incident type 2 diabetes: a systematic review and dose-response meta-analysis. Am J Clin Nutr. 2016;103:818–829.
    1. Di Castelnuovo A, Costanzo S, Bagnardi V, Donati MB, Iacoviello L, de Gaetano G. Alcohol dosing and total mortality in men and women: an updated meta-analysis of 34 prospective studies. Arch Intern Med. 2006;166:2437–2445.
    1. Knott C, Bell S, Britton A. Alcohol consumption and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis of more than 1·9 million individuals from 38 observational studies. Diabetes Care. 2015;38:1804–1812.
    1. Naimi TS, Stockwell T, Zhao J. Selection biases in observational studies affect associations between ‘moderate’ alcohol consumption and mortality. Addict. 2016 published online June 17.
    1. Naimi TS, Brown DW, Brewer RD. Cardiovascular risk factors and confounders among nondrinking and moderate-drinking U.S. adults. Am J Prev Med. 2005;28:369–373.
    1. Stockwell T, Zhao J, Panwar S, Roemer A, Naimi T, Chikritzhs T. Do ‘moderate’ drinkers have reduced mortality risk? A systematic review and meta-analysis of alcohol consumption and all-cause mortality. J Stud Alcohol Drugs. 2016;77:185–198.
    1. Au Yeung SL, Jiang CQ, Cheng KK. Evaluation of moderate alcohol use and cognitive function among men using a Mendelian randomization design in the Guangzhou biobank cohort study. Am J Epidemiol. 2012;175:1021–1028.
    1. von Hinke Kessler Scholder S, Wehby GL, Lewis S, Zuccolo L. Alcohol exposure in utero and child academic achievement. Econ J. 2014;124:634–667.
    1. Chen L, Smith GD, Harbord RM, Lewis SJ. Alcohol intake and blood pressure: a systematic review implementing a Mendelian randomization approach. PLoS Med. 2008;5:e52.
    1. Cobiac L, Vos T, Doran C, Wallace A. Cost-effectiveness of interventions to prevent alcohol-related disease and injury in Australia. Addict. 2009;104:1646–1655.
    1. Elder RW, Lawrence B, Ferguson A. The effectiveness of tax policy interventions for reducing excessive alcohol consumption and related harms. Am J Prev Med. 2010;38:217–229.
    1. O'Donnell A, Anderson P, Newbury-Birch D. The impact of brief alcohol interventions in primary healthcare: a systematic review of reviews. Alcohol Alcohol. 2014;49:66–78.
    1. Chisholm D, Rehm J, Van Ommeren M, Monteiro M. Reducing the global burden of hazardous alcohol use: a comparative cost-effectiveness analysis. J Stud Alcohol. 2004;65:782–793.
    1. De Oliveira LH, Giglio N, Ciapponi A. Temporal trends in diarrhea-related hospitalizations and deaths in children under age 5 before and after the introduction of the rotavirus vaccine in four Latin American countries. Vaccine. 2013;31(suppl 3):C99–108.
    1. Sriplung H, Singkham P, Iamsirithaworn S, Jiraphongsa C, Bilheem S. Success of a cervical cancer screening program: trends in incidence in Songkhla, southern Thailand, 1989–2010, and prediction of future incidences to 2030. Asian Pac J Cancer Prev. 2014;15:10003–10008.
    1. Berg J, Björck L, Lappas G, O'Flaherty M, Capewell S, Rosengren A. Continuing decrease in coronary heart disease mortality in Sweden. BMC Cardiovasc Disord. 2014;14:9.
    1. Kreatsoulas C, Anand SS. The impact of social determinants on cardiovascular disease. Can J Cardiol. 2010;26(suppl C):8C–13C.
    1. Gakidou E, Cowling K, Lozano R, Murray CJ. Increased educational attainment and its effect on child mortality in 175 countries between 1970 and 2009: a systematic analysis. Lancet. 2010;376:959–974.
    1. Sassi F, Belloni A, Capobianco C. The role of fiscal policies in health promotion. OECD Working Papers. 2013;66:1–50.
    1. Sassi F. Obesity and the economics of prevention. Organisation for Economic Co-operation and Development Publishing; Paris: 2010.
    1. Dobbs R, Sawers C, Thompson F. Overcoming obesity: an initial economic analysis. McKinsey Global Institute; London: 2014.
    1. Sheehan NA, Didelez V, Burton PR, Tobin MD. Mendelian randomisation and causal inference in observational epidemiology. PLoS Med. 2008;5:e177.
    1. Malik VS, Pan A, Willett WC, Hu FB. Sugar-sweetened beverages and weight gain in children and adults: a systematic review and meta-analysis. Am J Clin Nutr. 2013;98:1084–1902.
    1. Te Morenga L, Mallard S, Mann J. Dietary sugars and body weight: systematic review and meta-analyses of randomised controlled trials and cohort studies. BMJ. 2013;346:e7492.
    1. Mozaffarian D, Fahimi S, Singh GM. Global sodium consumption and death from cardiovascular causes. N Engl J Med. 2014;371:624–634.
    1. Navas-Acien A, Schwartz BS, Rothenberg SJ, Hu H, Silbergeld EK, Guallar E. Bone lead levels and blood pressure endpoints: a meta-analysis. Epidemiol. 2008;19:496–504.
    1. Pope CA, Burnett RT, Turner MC. Lung cancer and cardiovascular disease mortality associated with ambient air pollution and cigarette smoke: shape of the exposure-response relationships. Environ Health Perspect. 2011;119:1616–1621.
    1. Pope CA, Burnett RT, Krewski D. Cardiovascular mortality and exposure to airborne fine particulate matter and cigarette smoke: shape of the exposure-response relationship. Circulation. 2009;120:941–948.
    1. Lippmann M, Chen LC, Gordon T, Ito K, Thurston GD. National Particle Component Toxicity (NPACT) Initiative: integrated epidemiologic and toxicologic studies of the health effects of particulate matter components. Res Rep Health Eff Inst. 2013;177:5–13.
    1. Stanek LW, Sacks JD, Dutton SJ, Dubois JJ. Attributing health effects to apportioned components and sources of particulate matter: an evaluation of collective results. Atmos Environ. 2011;45:5655–5663.
    1. GBD 2013 Mortality and Causes of Death Collaborators Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;385:117–171.
    1. Global Burden of Disease Study 2013 Collaborators Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet. 2015;386:743–800.
    1. Mehta N, Preston S. Are major behavioral and sociodemographic risk factors for mortality additive or multiplicative in their effects? Soc Sci Med. 2016;154:93–99.
    1. Lim SS, Carnahan E, Nelson EC. Validation of a new predictive risk model: measuring the impact of the major modifiable risks of death for patients and populations. Popul Health Metr. 2015;13:27.
    1. Bhaskaran K, Douglas I, Forbes H, dos-Santos-Silva I, Leon DA, Smeeth L. Body-mass index and risk of 22 specific cancers: a population-based cohort study of 5·24 million UK adults. Lancet. 2014;384:755–765.
    1. Renehan AG, Tyson M, Egger M, Heller RF, Zwahlen M. Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet. 2008;371:569–578.
    1. Chafe ZA, Brauer M, Klimont Z. Household cooking with solid fuels contributes to ambient PM2·5 air pollution and the burden of disease. Environ Health Perspect. 2014;122:1314–1320.

Source: PubMed

Sponsorer og samarbejdspartnere

Medicinske tilstande

Narkotikainterventioner

3
Abonner