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| Étude écologique× | Étude écologique méta-analytique× | |
|---|---|---|
| Domaine | Épidémiologie | Épidémiologie |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 19th century (Snow 1854); formalised mid-20th century | 1990s |
| Auteur d'origine≠ | Various; foundational work by John Snow (1854) and systematised in modern form by Brian MacMahon and colleagues | Morgenstern, Blettner, and colleagues in epidemiology methodology |
| Type≠ | Observational epidemiological study | Quantitative synthesis design |
| Source fondatrice≠ | Morgenstern, H. (1995). Ecologic studies in epidemiology: concepts, principles, and methods. Annual Review of Public Health, 16(1), 61–81. DOI ↗ | Blettner, M., Sauerbrei, W., Schlehofer, B., Scheuchenpflug, T., & Friedenreich, C. (1999). Traditional reviews, meta-analyses and pooled analyses in epidemiology. International Journal of Epidemiology, 28(1), 1–9. DOI ↗ |
| Alias | aggregate study, correlational study, ecological correlation study, population-level study | ecological meta-analysis, aggregate-level meta-analysis, meta-analytic ecologic design, population-level meta-analysis |
| Apparentées≠ | 5 | 2 |
| Résumé≠ | An ecological study is an observational epidemiological design in which the unit of analysis is a group or population — a country, region, city, or time period — rather than an individual. Exposures and outcomes are measured as aggregates (rates, proportions, or means) and then correlated across groups to generate or evaluate hypotheses about population-level associations between risk factors and disease. | A meta-analytic ecological study synthesises data from multiple populations or geographic units — rather than from individual patients — to estimate associations between exposures and health outcomes. By pooling aggregate-level statistics across studies or regions, it extends the reach of ecological reasoning to a wider evidence base, enabling detection of exposure-outcome relationships that single-population ecological analyses may miss due to limited variability or sample size. |
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