Estimating risk factor attributable burden – challenges and potential solutions when using the comparative risk assessment methodology
Abstract Background Burden of disease analyses quantify population health and provide comprehensive overviews of the health status of countries or specific population groups. The comparative risk assessment (CRA) methodology is commonly used to estimate the share of the burden attributable to risk f...
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| Format: | Article |
| Language: | English |
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BMC
2022-05-01
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| Series: | Archives of Public Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13690-022-00900-8 |
| _version_ | 1818204689976524800 |
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| author | Dietrich Plass Henk Hilderink Heli Lehtomäki Simon Øverland Terje A. Eikemo Taavi Lai Vanessa Gorasso Brecht Devleesschauwer |
| author_facet | Dietrich Plass Henk Hilderink Heli Lehtomäki Simon Øverland Terje A. Eikemo Taavi Lai Vanessa Gorasso Brecht Devleesschauwer |
| author_sort | Dietrich Plass |
| collection | DOAJ |
| description | Abstract Background Burden of disease analyses quantify population health and provide comprehensive overviews of the health status of countries or specific population groups. The comparative risk assessment (CRA) methodology is commonly used to estimate the share of the burden attributable to risk factors. The aim of this paper is to identify and address some selected important challenges associated with CRA, illustrated by examples, and to discuss ways to handle them. Further, the main challenges are addressed and finally, similarities and differences between CRA and health impact assessments (HIA) are discussed, as these concepts are sometimes referred to synonymously but have distinctly different applications. Results CRAs are very data demanding. One key element is the exposure-response relationship described e.g. by a mathematical function. Combining estimates to arrive at coherent functions is challenging due to the large variability in risk exposure definitions and data quality. Also, the uncertainty attached to this data is difficult to account for. Another key issue along the CRA-steps is to define a theoretical minimal risk exposure level for each risk factor. In some cases, this level is evident and self-explanatory (e.g., zero smoking), but often more difficult to define and justify (e.g., ideal consumption of whole grains). CRA combine all relevant information and allow to estimate population attributable fractions (PAFs) quantifying the proportion of disease burden attributable to exposure. Among many available formulae for PAFs, it is important to use the one that allows consistency between definitions, units of the exposure data, and the exposure response functions. When combined effects of different risk factors are of interest, the non-additive nature of PAFs and possible mediation effects need to be reflected. Further, as attributable burden is typically calculated based on current exposure and current health outcomes, the time dimensions of risk and outcomes may become inconsistent. Finally, the evidence of the association between exposure and outcome can be heterogeneous which needs to be considered when interpreting CRA results. Conclusions The methodological challenges make transparent reporting of input and process data in CRA a necessary prerequisite. The evidence for causality between included risk-outcome pairs has to be well established to inform public health practice. |
| first_indexed | 2024-12-12T03:45:14Z |
| format | Article |
| id | doaj.art-86045a03d4734d8d8c7c7db340e91898 |
| institution | Directory Open Access Journal |
| issn | 2049-3258 |
| language | English |
| last_indexed | 2024-12-12T03:45:14Z |
| publishDate | 2022-05-01 |
| publisher | BMC |
| record_format | Article |
| series | Archives of Public Health |
| spelling | doaj.art-86045a03d4734d8d8c7c7db340e918982022-12-22T00:39:35ZengBMCArchives of Public Health2049-32582022-05-0180111210.1186/s13690-022-00900-8Estimating risk factor attributable burden – challenges and potential solutions when using the comparative risk assessment methodologyDietrich Plass0Henk Hilderink1Heli Lehtomäki2Simon Øverland3Terje A. Eikemo4Taavi Lai5Vanessa Gorasso6Brecht Devleesschauwer7German Environment Agency, Section Exposure Assessment and Environmental Health IndicatorsNational Institute for Public Health and the Environment (RIVM)Finnish Institute for Health and Welfare (THL), Health Security, Environmental HealthSection for Health Care Collaboration, Haukeland University HospitalCentre for Global Health Inequalities Research (CHAIN), Department of Sociology and Political Science, Norwegian University of Science and Technology (NTNU)Fourth View ConsultingDepartment of Epidemiology and Public Health, SciensanoDepartment of Epidemiology and Public Health, SciensanoAbstract Background Burden of disease analyses quantify population health and provide comprehensive overviews of the health status of countries or specific population groups. The comparative risk assessment (CRA) methodology is commonly used to estimate the share of the burden attributable to risk factors. The aim of this paper is to identify and address some selected important challenges associated with CRA, illustrated by examples, and to discuss ways to handle them. Further, the main challenges are addressed and finally, similarities and differences between CRA and health impact assessments (HIA) are discussed, as these concepts are sometimes referred to synonymously but have distinctly different applications. Results CRAs are very data demanding. One key element is the exposure-response relationship described e.g. by a mathematical function. Combining estimates to arrive at coherent functions is challenging due to the large variability in risk exposure definitions and data quality. Also, the uncertainty attached to this data is difficult to account for. Another key issue along the CRA-steps is to define a theoretical minimal risk exposure level for each risk factor. In some cases, this level is evident and self-explanatory (e.g., zero smoking), but often more difficult to define and justify (e.g., ideal consumption of whole grains). CRA combine all relevant information and allow to estimate population attributable fractions (PAFs) quantifying the proportion of disease burden attributable to exposure. Among many available formulae for PAFs, it is important to use the one that allows consistency between definitions, units of the exposure data, and the exposure response functions. When combined effects of different risk factors are of interest, the non-additive nature of PAFs and possible mediation effects need to be reflected. Further, as attributable burden is typically calculated based on current exposure and current health outcomes, the time dimensions of risk and outcomes may become inconsistent. Finally, the evidence of the association between exposure and outcome can be heterogeneous which needs to be considered when interpreting CRA results. Conclusions The methodological challenges make transparent reporting of input and process data in CRA a necessary prerequisite. The evidence for causality between included risk-outcome pairs has to be well established to inform public health practice.https://doi.org/10.1186/s13690-022-00900-8Burden of disease (BoD)Comparative risk assessment (CRA)Disability-adjusted life years (DALY)Health impact assessment (HIA)Population health |
| spellingShingle | Dietrich Plass Henk Hilderink Heli Lehtomäki Simon Øverland Terje A. Eikemo Taavi Lai Vanessa Gorasso Brecht Devleesschauwer Estimating risk factor attributable burden – challenges and potential solutions when using the comparative risk assessment methodology Archives of Public Health Burden of disease (BoD) Comparative risk assessment (CRA) Disability-adjusted life years (DALY) Health impact assessment (HIA) Population health |
| title | Estimating risk factor attributable burden – challenges and potential solutions when using the comparative risk assessment methodology |
| title_full | Estimating risk factor attributable burden – challenges and potential solutions when using the comparative risk assessment methodology |
| title_fullStr | Estimating risk factor attributable burden – challenges and potential solutions when using the comparative risk assessment methodology |
| title_full_unstemmed | Estimating risk factor attributable burden – challenges and potential solutions when using the comparative risk assessment methodology |
| title_short | Estimating risk factor attributable burden – challenges and potential solutions when using the comparative risk assessment methodology |
| title_sort | estimating risk factor attributable burden challenges and potential solutions when using the comparative risk assessment methodology |
| topic | Burden of disease (BoD) Comparative risk assessment (CRA) Disability-adjusted life years (DALY) Health impact assessment (HIA) Population health |
| url | https://doi.org/10.1186/s13690-022-00900-8 |
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