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| 위험 조정된 생태학 연구× | 생태학 연구× | |
|---|---|---|
| 분야 | 역학 | 역학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1980s–1990s | 19th century (Snow 1854); formalised mid-20th century |
| 창시자≠ | Extension of ecological study methodology; risk adjustment concepts formalized by Morgenstern (1982) and developed further in health outcomes research | Various; foundational work by John Snow (1854) and systematised in modern form by Brian MacMahon and colleagues |
| 유형≠ | Observational ecological design with statistical confounding control | Observational epidemiological study |
| 원전≠ | Morgenstern, H. (1982). Uses of ecologic analysis in epidemiologic research. American Journal of Public Health, 72(12), 1336–1344. DOI ↗ | Morgenstern, H. (1995). Ecologic studies in epidemiology: concepts, principles, and methods. Annual Review of Public Health, 16(1), 61–81. DOI ↗ |
| 별칭 | risk-adjusted ecological analysis, confounder-adjusted ecological study, ecological regression with risk adjustment, adjusted area-level study | aggregate study, correlational study, ecological correlation study, population-level study |
| 관련≠ | 4 | 5 |
| 요약≠ | A risk-adjusted ecological study is an observational epidemiological design that examines associations between exposures and outcomes measured at the group or area level — such as regions, hospitals, or countries — while statistically controlling for known risk factors also measured at that level. By incorporating risk adjustment through ecological regression or standardization, the design reduces (though cannot eliminate) confounding from group-level variables, enabling more valid comparisons across populations or settings. | 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. |
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