Assessing the quality of evidence in studies estimating prevalence of exposure to occupational risk factors: The QoE-SPEO approach applied in the systematic reviews from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

Pega, Frank; Momen, Natalie C.; Gagliardi, Diana; Bero, Lisa; Boccuni, Fabio; Chartres, Nicholas; Descatha, Alexis; Dzhambov, Angel M.; Godderis, Lode; Loney, Tom; Mandrioli, Daniele; Modenese, Alberto; Molen, H. F. van der; Neupane, Subas; Pachito, Daniela Vianna; Paulo, Marília Silva; Prakash, K C; Scheepers, Paul T.J.; Teixeira, Liliane Reis; Tenkate, Thomas; Woodruff, Tracey J.; Norris, Susan L.

doi:10.1016/j.envint.2022.107136

Cited by 6 publications

(5 citation statements)

References 57 publications

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“…Software commonly used for systematic reviews of effect, such as RevMan for Cochrane Reviews, often cannot be used to pool such skewed data; Meta-XL is one software that can be used. “Expected heterogeneity” is defined as the “real and non-spurious heterogeneity (i.e., variability) that can be expected in the prevalence of exposure, within or between individual persons, because exposure to the risk factor may change over space and/or time” ([ 8 ], p3). When “expected heterogeneity” is high, statistical heterogeneity can genuinely (non-erroneously) be very high in meta-analyses, so high statistical heterogeneity is not necessarily problematic and could be explored in relevant subgroup analyses (e.g., by occupation and industrial sector).…”

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confidence: 99%

“…However, these tools were developed to support certainty of evidence assessments for systematic reviews of the effect of environmental and occupational exposures on health outcomes (or their association); they may, therefore, require modification to be applicable to systematic review of prevalence studies of environmental and occupational exposures. To fill the gap, WHO, supported by individual experts, has developed QoE-SPEO (Quality of Evidence in Studies estimating Prevalence of Exposure to Occupational risk factors) [ 8 ], an approach for assessing certainty of evidence in studies estimating prevalence of exposure to occupational risk factors, including external validity (indirectness), inconsistency, and publication bias. Relevant steps, domains and components from GRADE were adopted or adapted for QoE-SPEO.…”

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confidence: 99%

“…As noted above, in addition to pilot tests [ 10 ], the performance of the RoB-SPEO tool was also comprehensively evaluated in terms of assessor burden, inter-rater agreement and user experience across four systematic reviews [ 5 ]. Additionally, the QoE-SPEO approach was pilot tested and case studies of user experience were also conducted across two systematic reviews [ 8 ]. These assessments and feedback have provided evidence supporting the use of these new tools/approaches, and they have also been applied across five systematic reviews for the WHO/ILO Joint Estimates (see [ 9 ]).…”

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confidence: 99%

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Towards a framework for systematic reviews of the prevalence of exposure to environmental and occupational risk factors

Pega

Momen²,

Bero³

et al. 2022

Environ Health

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Exposure prevalence studies (as here defined) record the prevalence of exposure to environmental and occupational risk factors to human health. Applying systematic review methods to the synthesis of these studies would improve the rigour and transparency of normative products produced based on this evidence (e.g., exposure prevalence estimates). However, a dedicated framework, including standard methods and tools, for systematically reviewing exposure prevalence studies has yet to be created. We describe the need for this framework and progress made towards it through a series of such systematic reviews that the World Health Organization and the International Labour Organization conducted for their WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury (WHO/ILO Joint Estimates).We explain that existing systematic review frameworks for environmental and occupational health cannot be directly applied for the generation of exposure prevalence estimates because they seek to synthesise different types of evidence (e.g., intervention or exposure effects on health) for different purposes (e.g., identify intervention effectiveness or exposure toxicity or carcinogenicity). Concepts unique to exposure prevalence studies (e.g., “expected heterogeneity”: the real, non-spurious variability in exposure prevalence due to exposure changes over space and/or time) also require new assessment methods. A framework for systematic reviews of prevalence of environmental and occupational exposures requires adaptation of existing methods (e.g., a standard protocol) and development of new tools or approaches (e.g., for assessing risk of bias and certainty of a body of evidence, including exploration of expected heterogeneity).As part of the series of systematic reviews for the WHO/ILO Joint Estimates, the World Health Organization collaborating with partners has created a preliminary framework for systematic reviews of prevalence studies of exposures to occupational risk factors. This included development of protocol templates, data extraction templates, a risk of bias assessment tool, and an approach for assessing certainty of evidence in these studies. Further attention and efforts are warranted from scientific and policy communities, especially exposure scientists and policy makers, to establish a standard framework for comprehensive and transparent systematic reviews of studies estimating prevalence of exposure to environmental and occupational risk factors, to improve estimates, risk assessments and guidelines.

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confidence: 99%

Section: Main Textmentioning

confidence: 99%

Section: Main Textmentioning

confidence: 99%

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Towards a framework for systematic reviews of the prevalence of exposure to environmental and occupational risk factors

Pega

Momen²,

Bero³

et al. 2022

Environ Health

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“…Nevertheless, a few poor countries still fail to prioritise workplace safety and health due to social, economic, and political constraints, competing interests, and insu cient procedures for translating scienti c data and facts into laws (Nordgren & Charavaryamath, 2018). The highest health regulatory body in the world, the World Health Organization (WHO), has recognised exposures to hazards and health consequences in the line of duty as a component of the universal burden of diseases that exacerbate poverty and inevitably lead to death (WHO; ILO, 2021a; WHO; ILO, 2021b; Pega et al, 2022). According to a review of the published literature, the views and understanding of dangers and health concerns among livestock farmers in Ibadan, Nigeria, are not well documented.…”

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confidence: 99%

Perception of livestock farmers towards occupational health and hazards in Ibadan, Nigeria

Busari

2023

Preprint

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Aim The National Safety Council categorises the agrifood sector as the industry with the highest death rate per 100,000 workers in 2021. Ibadan, a major hub of livestock and micro-livestock production in Nigeria, has little or no documentation on farmers' perceptions of occupational health and safety. Methods A field survey was carried out among 151 livestock producers in Ibadan between July and September 2022, using open- and closed-ended questionnaires. A cross-tabulation was used to quantitatively compare the variables using Pearson’s Chi square to determine the level of significance. Results More than 78% of the male farmers agree and/or strongly agree that they could forego a few workplace safety precautions, while 66% strongly disagree that personal safety is important. Prior to this study, 76% and 23.5% of livestock farmers, male and female, respectively, claimed they had not heard about workplace health and safety. On a scale of 0.0 to 4.5, the average perception index score of respondents on occupational safety and health (OSH) revealed that 2.01 indicated that the OSH Act is not useful, 1.88 stated that the OSH Act is ineffective at reducing injuries and illnesses, and 1.72 opined that the OSH Act is not applicable to their job. Close to 100% of the farming population in Ibadan had access to media and smart devices, which could be explored in the dissemination of health and safety information to improve occupational safety and health awareness. Conclusion Smart technological channels should be harnessed to disseminate occupational health and safety information to workers in the agrifood sector.

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“…Improved accuracy in estimating exposure prevalence leads to more accurate burden of disease estimation. WHO and ILO have developed tools and approaches to use in systematic reviews of prevalence of exposure [26][27][28]. In this article, we describe a novel modelling approach from the WHO/ILO Joint Estimates, which can be used for producing estimates for all burden of disease studies, but here, we focus on work-related We seek to estimate the burden of disease (such as the number of deaths or disability-adjusted live years lost) at year a that is attributable to past exposure to a risk factor.…”

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confidence: 99%

Estimating the population exposed to a risk factor over a time window: A microsimulation modelling approach from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

et al. 2022

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Objectives Burden of disease estimation commonly requires estimates of the population exposed to a risk factor over a time window (yeart to yeart+n). We present a microsimulation modelling approach for producing such estimates and apply it to calculate the population exposed to long working hours for one country (Italy). Methods We developed a three-model approach: Model 1, a multilevel model, estimates exposure to the risk factor at the first year of the time window (yeart). Model 2, a regression model, estimates transition probabilities between exposure categories during the time window (yeart to yeart+n). Model 3, a microsimulation model, estimates the exposed population over the time window, using the Monte Carlo method. The microsimulation is carried out in three steps: (a) a representative synthetic population is initiated in the first year of the time window using prevalence estimates from Model 1, (b) the exposed population is simulated over the time window using the transition probabilities from Model 2; and (c) the population is censored for deaths during the time window. Results We estimated the population exposed to long working hours (i.e. 41–48, 49–54 and ≥55 hours/week) over a 10-year time window (2002–11) in Italy. We populated all three models with official data from Labour Force Surveys, United Nations population estimates and World Health Organization life tables. Estimates were produced of populations exposed over the time window, disaggregated by sex and 5-year age group. Conclusions Our modelling approach for estimating the population exposed to a risk factor over a time window is simple, versatile, and flexible. It however requires longitudinal exposure data and Model 3 (the microsimulation model) is stochastic. The approach can improve accuracy and transparency in exposure and burden of disease estimations. To improve the approach, a logical next step is changing Model 3 to a deterministic microsimulation method, such as modelling of microflows.

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Assessing the quality of evidence in studies estimating prevalence of exposure to occupational risk factors: The QoE-SPEO approach applied in the systematic reviews from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

Cited by 6 publications

References 57 publications

Towards a framework for systematic reviews of the prevalence of exposure to environmental and occupational risk factors

Towards a framework for systematic reviews of the prevalence of exposure to environmental and occupational risk factors

Perception of livestock farmers towards occupational health and hazards in Ibadan, Nigeria

Estimating the population exposed to a risk factor over a time window: A microsimulation modelling approach from the WHO/ILO Joint Estimates of the Work-related Burden of Disease and Injury

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