A Practical Guide to Conducting Dose-Response Meta-Analyses in Epidemiology
Dose-response relationships between continuous risk factors and disease outcomes are necessary for understanding the risks related to different levels of exposure. Dose-response risk curves can lead to more targeted public health messaging, prevention efforts, and policy implementation. Meta-analyse...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
PsychOpen GOLD/ Leibniz Institute for Psychology
2025-06-01
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| Series: | Methodology |
| Subjects: | |
| Online Access: | https://doi.org/10.5964/meth.14733 |
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| Summary: | Dose-response relationships between continuous risk factors and disease outcomes are necessary for understanding the risks related to different levels of exposure. Dose-response risk curves can lead to more targeted public health messaging, prevention efforts, and policy implementation. Meta-analyses are often used to combine statistical results from different studies and can be used to model dose-response relationships. However, several challenges are encountered when performing dose-response meta-analysis, such as having heterogeneous reference categories, inconsistent measures of risk, and determining the most accurate shape of the curve. In this paper, we propose a three-step process for estimating dose-response relationships via meta-analysis, which involves: 1) harmonizing the measures of risk, 2) homogenizing the reference category, and 3) selecting meta-regression models. We use data obtained from a systematic review on the dose-response relationship between alcohol consumption and the risk of chronic liver disease to provide an example of the proposed process. |
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| ISSN: | 1614-2241 |