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| Studium ekologiczne prospektywne× | Badanie przekrojowe w epidemiologii× | |
|---|---|---|
| Dziedzina | Epidemiologia | Epidemiologia |
| Rodzina | Process / pipeline | Process / pipeline |
| Rok powstania≠ | 1950s–1970s (ecological epidemiology); prospective variant widely applied from 1980s onward | 1960s (formal codification); widely practiced since mid-20th century |
| Twórca≠ | Ecological study design formalised in epidemiology mid-20th century; prospective variant established through environmental and chronic disease research | Classical epidemiology tradition; systematized by Brian MacMahon and Thomas Pugh (1960s) |
| Typ≠ | Observational epidemiological study design | Observational, descriptive/analytic epidemiological design |
| Źródło pierwotne≠ | Morgenstern, H. (1998). Ecological studies. In K. J. Rothman & S. Greenland (Eds.), Modern Epidemiology (2nd ed., pp. 459–480). Lippincott-Raven. link ↗ | Kelsey, J. L., Whittemore, A. S., Evans, A. S., & Thompson, W. D. (1996). Methods in Observational Epidemiology (2nd ed.). Oxford University Press. ISBN: 978-0195080407 |
| Inne nazwy | prospective ecologic study, prospective aggregate-level study, prospective group-level study, ecological cohort study | prevalence study, cross-sectional survey, transversal study, cross-sectional design |
| Pokrewne≠ | 4 | 6 |
| Podsumowanie≠ | A prospective ecological study is an observational epidemiological design in which groups — not individuals — serve as the unit of analysis, and exposure data are collected going forward in time before outcomes are measured. Investigators define geographically, politically, or socially bounded populations, characterise their aggregate exposures at baseline, then ascertain group-level outcomes (disease rates, mortality rates) at one or more later time points. Because exposure precedes outcome measurement, this design provides stronger temporal evidence than retrospective ecological studies. | A cross-sectional epidemiological study measures the exposure(s) and outcome(s) of interest simultaneously in a defined population at a single point in time (or over a short period). Because there is no follow-up, it is the most efficient observational design for estimating disease prevalence and for generating hypotheses about associations between risk factors and health outcomes. |
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