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      Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

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      GBD 2017 Risk Factor Collaborators
      Lancet (London, England)
      Elsevier

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          Summary

          Background

          The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations.

          Methods

          We used the CRA 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 groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. 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. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017.

          Findings

          In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low.

          Interpretation

          By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning.

          Funding

          Bill & Melinda Gates Foundation.

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          Most cited references13

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          Consequences of bullying victimization in childhood and adolescence: A systematic review and meta-analysis

          AIM To identify health and psychosocial problems associated with bullying victimization and conduct a meta-analysis summarizing the causal evidence. METHODS A systematic review was conducted using PubMed, EMBASE, ERIC and PsycINFO electronic databases up to 28 February 2015. The study included published longitudinal and cross-sectional articles that examined health and psychosocial consequences of bullying victimization. All meta-analyses were based on quality-effects models. Evidence for causality was assessed using Bradford Hill criteria and the grading system developed by the World Cancer Research Fund. RESULTS Out of 317 articles assessed for eligibility, 165 satisfied the predetermined inclusion criteria for meta-analysis. Statistically significant associations were observed between bullying victimization and a wide range of adverse health and psychosocial problems. The evidence was strongest for causal associations between bullying victimization and mental health problems such as depression, anxiety, poor general health and suicidal ideation and behaviours. Probable causal associations existed between bullying victimization and tobacco and illicit drug use. CONCLUSION Strong evidence exists for a causal relationship between bullying victimization, mental health problems and substance use. Evidence also exists for associations between bullying victimization and other adverse health and psychosocial problems, however, there is insufficient evidence to conclude causality. The strong evidence that bullying victimization is causative of mental illness highlights the need for schools to implement effective interventions to address bullying behaviours.
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            Tobacco taxes as a tobacco control strategy.

            Increases in tobacco taxes are widely regarded as a highly effective strategy for reducing tobacco use and its consequences. The voluminous literature on tobacco taxes is assessed, drawing heavily from seminal and recent publications reviewing the evidence on the impact of tobacco taxes on tobacco use and related outcomes, as well as that on tobacco tax administration. Well over 100 studies, including a growing number from low-income and middle-income countries, clearly demonstrate that tobacco excise taxes are a powerful tool for reducing tobacco use while at the same time providing a reliable source of government revenues. Significant increases in tobacco taxes that increase tobacco product prices encourage current tobacco users to stop using, prevent potential users from taking up tobacco use, and reduce consumption among those that continue to use, with the greatest impact on the young and the poor. Global experiences with tobacco taxation and tax administration have been used by WHO to develop a set of 'best practices' for maximising the effectiveness of tobacco taxation. Significant increases in tobacco taxes are a highly effective tobacco control strategy and lead to significant improvements in public health. The positive health impact is even greater when some of the revenues generated by tobacco tax increases are used to support tobacco control, health promotion and/or other health-related activities and programmes. In general, oppositional arguments that higher taxes will have harmful economic effects are false or overstated.
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              Air Pollution and Type 2 Diabetes

              Epidemic of Cardiometabolic Disease in Developing Nations: A Threat to Global Prosperity According to the International Diabetes Federation in the year 2011, diabetes mellitus (DM) affects at least 366 million people worldwide, and that number is expected to reach 566 million by the year 2030. Over 99% of all diabetes cases represent type 2 DM with most of these projected to occur in low- to middle-income countries. Technology innovations, globalization with its free movement of food and services, seismic shifts in agrarian practices, and nutritional transition to freely available high-caloric diets have irrevocably altered energy expenditures during work and leisure. These and other factors are helping to foster the continued epidemiological transition occurring across the globe. Scientific effort over the last few decades has focused primarily on components of urbanization such as inactivity and dietary factors. More recent observations have provided additional links between exposure to environmental factors in air/water and propensity to chronic diseases (1). This issue is of importance given the extraordinary confluence of high levels of airborne and water pollutants in urbanized environments. Multiple studies in China, India, and other rapidly urbanizing economies demonstrate a steep gradient in urban–rural prevalence. This review will summarize recent evidence on how outdoor air pollution may represent an underappreciated yet critical linkage between urbanization and the emergence of cardiometabolic diseases, with a focus on type 2 DM. We define cardiometabolic disease as the confluence of cardiovascular disease and type 2 DM in recognition of the fact that the milieu of diabetes fundamentally alters the pathophysiology of coronary, cerebrovascular, and peripheral arterial disease. Thus, alteration in susceptibility to DM automatically increases the likelihood of cardiovascular disease. Indoor air pollution is not discussed owing to the paucity of data. It should be noted that our current understanding of air pollution–mediated cardiometabolic disease is derived from outdoor air pollution studies, with there being no good reasons to believe that the dose-response relationship to indoor air pollution will be any different. An understanding of potentially reversible environmental factors responsible for this rapid burgeoning of cardiometabolic disorders among developing nations is crucial in order to devise a societal response that is proportionate and adequate (2). In this review, the association between air pollution and type 2 DM is discussed unless this distinction cannot be made in the cited study (typically health registry data sets). Exposure to Environmental Toxins and Metabolic Disease Epidemiologic studies that have attempted to investigate environmental factors that accentuate risk for development of cardiometabolic disorders have uncovered a number of factors other than traditional suspects related to diet and exercise. These variables include factors such as stress (mental and emotional), cultural and socioeconomic variables, chronic low-grade infection, and environmental pollutants (Fig. 1). In many instances, these factors are strongly correlated, rendering isolation of cause and effect difficult. FIG. 1. A model for development of cardiometabolic disease highlighting importance of gene–environment interactions. (A high-quality digital representation of this figure is available in the online issue.) The plausibility that environmental exposures are linked to metabolic disease is exemplified by persistent organic pollutants, toxins that have consistently shown to associate with insulin resistance (IR) and type 2 DM. Prospective cohort studies of subjects exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin or other persistent organic pollutants in occupational and other settings have reported increased risk of DM and IR (1,3). Air pollution in Asia, Latin America, and Africa is a significant public health burden, especially given the often extraordinarily high concentrations of pollutants (e.g., particulate matter), high population density, and pervasive nature of air pollution. Table 1 lists the top countries for particulate matter (PM) air pollution in the world, all of which have rapidly urbanized populations based on a World Health Organization (WHO) database that reviewed pollution data in >1,100 cities in 91 countries. The mean annual average for the top 10 countries is roughly fivefold higher than the U.S. National Ambient Air Quality Standard of 15 μg/m3 for PM 176 ng/mL associated with a fourfold excess risk. Addition to SP-D levels to traditional risk factors improved c-statistic (from 0.76 to 0.78) and net reclassification across all levels of risk (52). In the Dallas Heart Study, increasing levels of SP-B was associated with other traditional cardiac risk factors and higher levels of inflammatory biomarkers. In multivariable analyses after adjusting for risk factors, SP-B remained associated with aortic plaque in smokers (odds ratio 1.87, fourth versus first quartiles; P < 0.0001) (53). How does one reconcile increases in plasma SP levels in population studies to increase susceptibility? Increased levels of surfactants in plasma seen in smoking and lung inflammation have been hypothesized to indicate translocation from the lung to the circulation with lung damage. Surfactants A and D are assembled as large multimeric units composed of lectin-containing globular domains and a collagenous domain. In the presence of DAMPs, they may exert proinflammatory effects by binding to CD47 (thrombospondin receptor) (48). It is also highly possible that increased levels may indicate oxidatively modified forms of surfactant that are not functional. Surfactants are often assembled as multimers and are well-known to undergo oxidative modification to oligomeric forms. Current assays for SPs do not distinguish between these various forms. Future Directions A growing body of evidence has implicated inflammatory responses to diet and environmental factors as a key mechanism that help explain the emerging epidemic in diabetes and cardiovascular disease. Both genetic and environmental factors undoubtedly play a role, although the role of the physical and social environment in determining susceptibility appears to be critical. Nontraditional factors such as air pollution that are pervasive in the urban environment may provide low-level synergism with other dominant factors in accelerating propensity for type 2 DM. Emerging data from both experimental and epidemiologic studies are beginning to provide insights into this association. There are a number of areas that would benefit from further studies and enable additional insights into the mechanisms by which environmental signals modulate susceptibility to metabolic disease. The effects of air-pollution exposure on β-cell function, counterregulatory hormones such as glucagon, and effects on insulinotropic mechanisms deserve further study. The effects of air pollution on hypothalamic mechanisms of appetite and satiety are areas of emerging interest, as it is entirely possible that air pollutants may modulate inflammation in key brain homeostatic centers. In addition, the effects on central autonomic control of peripheral inflammation may represent additional pathways by which environmental triggers may play an important role in determining peripheral inflammation. The societal costs of this link, if indeed true, are staggering given the ubiquitous nature of air pollution and the economic costs of obesity/DM-related complications. Given the already established nature of the links between air pollution and cardiovascular disease and regulations already in place, at least in countries like the U.S. and Europe, these additional links, if they can be established in additional large cohorts, would provide persuasive rationale for limiting exposure to air pollution.
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                Author and article information

                Journal
                Lancet
                Lancet
                Lancet (London, England)
                Elsevier
                0140-6736
                1474-547X
                10 November 2018
                10 November 2018
                : 392
                : 10159
                : 1923-1994
                Author notes
                [†]

                Collaborators listed at the end of the paper

                Article
                S0140-6736(18)32225-6
                10.1016/S0140-6736(18)32225-6
                6227755
                30496105
                b59b7b27-7aec-4241-80b5-ecdbcae35894
                © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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