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      Global, regional and national burden of disease attributable to 19 selected occupational risk factors for 183 countries, 2000–2016: A systematic analysis from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

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          Abstract

          Objectives

          We provide a brief introduction to the objectives, data, methods and results of the World Health Organization (WHO)/International Labor Organization (ILO) Joint Estimates of the Work-related Burden of Disease and Injury (WHO/ILO Joint Estimates), which estimated the burden attributable to 19 selected occupational risk factors.

          Methods

          The WHO/ILO Joint Estimates were produced within the global Comparative Risk Assessment framework, which attributes the burden of one specific health outcome (ie, disease/injury) to a specific occupational risk factor. For 39 established occupational risk factor-health outcome pairs, estimates are produced using population attributable fractions (PAF) from recent burden of disease estimates. For two additional pairs, PAF are calculated from new databases of exposure and risk ratios produced in WHO/ILO systematic reviews. Attributable disease burdens were estimated by applying the PAF to total disease burdens.

          Results

          Globally in 2016, it is estimated that 1.88 [95% uncertainty range (UR) 1.84–1.92] million deaths and 89.72 (95% UR 88.61–90.83) million disability-adjusted life years were attributable to the 19 selected occupational risk factors and their health outcomes. A disproportionately large work-related burden of disease is observed in the WHO African Region (for disability-adjusted life years), South-East Asia Region, and Western Pacific Region (for deaths), males and older age groups.

          Conclusions

          The WHO/ILO Joint Estimates can be used for global monitoring of exposure to occupational risk factors and work-related burden of disease and to identify, plan, cost, implement and evaluate policies, programs and actions to prevent exposure to occupational risk factors and their associated burden.

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          Most cited references44

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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

          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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            Bootstrap Methods: Another Look at the Jackknife

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              Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement

              Measurements of health indicators are rarely available for every population and period of interest, and available data may not be comparable. The Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) define best reporting practices for studies that calculate health estimates for multiple populations (in time or space) using multiple information sources. Health estimates that fall within the scope of GATHER include all quantitative population-level estimates (including global, regional, national, or subnational estimates) of health indicators, including indicators of health status, incidence and prevalence of diseases, injuries, and disability and functioning; and indicators of health determinants, including health behaviours and health exposures. GATHER comprises a checklist of 18 items that are essential for best reporting practice. A more detailed explanation and elaboration document, describing the interpretation and rationale of each reporting item along with examples of good reporting, is available on the GATHER website.
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                Author and article information

                Journal
                Scand J Work Environ Health
                Scand J Work Environ Health
                Scandinavian Journal of Work, Environment & Health
                Nordic Association of Occupational Safety and Health (Finland )
                0355-3140
                1795-990X
                1 March 2022
                22 November 2021
                25 February 2022
                : 48
                : 2
                : 158-168
                Affiliations
                [1 ]Department of Environment, Climate Change and Health, World Health Organization, Geneva, Switzerland
                [2 ]Labor Administration, Labor Inspection and Occupational Safety and Health Branch, International Labor Organization, Geneva, Switzerland
                Author notes
                Corresponding author: Dr Frank Pega, Department of Environment, Climate Change and Health, World Health Organization, Avenue Appia 20, 1211 Geneva 27, Switzerland. [E-mail: pegaf@ 123456who.int ]
                Article
                4001
                10.5271/sjweh.4001
                9045235
                34806754
                490d4734-8fca-4853-995b-427272b47cc0
                Copyright: © Scandinavian Journal of Work, Environment & Health

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 8 September 2021
                Categories
                Discussion Paper

                occupational epidemiology,work-related disease,work-related injury,working hour

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