Quantitative Epidemiology

1996 ◽  
Vol 17 (4) ◽  
pp. 249-255
Author(s):  
Jonathan Freeman

AbstractWe provide guidance for new practitioners in the vocabulary of modern epidemiology and the application of quantitative methods. Most hospital epidemiology involves surveillance (observational) data that were not part of a planned experiment, so the rubric and logic of controlled experimental studies cannot be applied. Forms of incidence and prevalence often are confused. The names “cohort study” and “case-control study” are unfortunate, as cohort studies rarely involve cohorts and case-control studies allow no active control by the investigator. Either type of study can be prospective or retrospective. Results of studies with discrete outcomes (infected or not, lived or died) often are represented best by a form of the risk ratio with 95% confidence intervals. The potential distorting effects of selection bias, misclassification, and confounding need to be considered.

2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
Hui Liu

Objective. Although the relative risk from a prospective cohort study is numerically approximate to the odds ratio from a case-control study for a low-probability event, a definite relationship between case-control and cohort studies cannot be confirmed. In this study, we established a different model to determine the relationship between case-control and cohort studies. Methods. Two analysis models (the cross-sectional model and multiple pathogenic factor model) were established. Incidences in both the exposure group and the nonexposure group in a cohort study were compared with the frequency of the observed factor in each group (diseased and nondiseased) in a case-control study. Results. The relationship between the results of a case-control study and a cohort study is as follows: Pe=Pd∗m/Pc∗1−m+Pd∗m; Pn=m∗1−Pd/1−Pc∗1−m−Pd∗m, where Pe and Pn represent the incidence in the exposed group and nonexposed group, respectively, from the cohort study, while Pd and Pc represent the observed frequencies in the disease group and the control group, respectively, for the case-control study; finally, m represents the incidence in the total population. Conclusions. There is a definite relationship between the results of case-control and cohort studies assessing the same exposure. The outcomes of case-control studies can be translated into cohort study data.


2019 ◽  
pp. 169-186
Author(s):  
Daniel Westreich

In contrast to an observational cohort study in which participants are identified, exposures are measured, and then outcomes status is measured after follow-up, a case-control study is an observational study in which researchers sample participants based on their outcome status, often only after all outcomes have already occurred. This chapter echoes the structure of the previous two chapters in the discussion of case-control studies. In this chapter, the author’s focus is on understanding the relationship between cohort studies and case-control studies and on how the interpretation of the odds ratio estimated from the case-control study depends on the relationship of the case-control study to a cohort study.


2021 ◽  
pp. 75-84
Author(s):  
Noel S. Weiss

Case–control studies compare ill or injured individuals (cases) with those at risk of the illness or injury (controls) with regard to prior exposures or characteristics, and so appear to proceed backwards, from consequence to potential cause. They have the potential to identify associations that are not causal, either because of chance, or because of the influence of some other factor associated with both the exposure and outcome. However, if a case–control study is able to enrol cases and controls from the same underlying population at risk of the outcome, and can measure exposure status of these persons in a valid manner, the results obtained will closely resemble those of a properly performed cohort study.


2020 ◽  
pp. 159-180
Author(s):  
Bendix Carstensen

This chapter addresses Case-control and case-cohort studies. In a Case-control study, one samples persons based on their disease outcome, so the fraction of diseased persons in a Case-control study is usually known (at least approximately) before data collection. In a cohort (follow-up) study, the relationship between some exposure and disease incidence is investigated by following the entire cohort and measuring the rate of occurrence of new cases in the different exposure groups. The follow-up records all persons who develop the disease during the study period. Implicit in this is that the relevant exposure information is available at all times for all persons under follow-up. The chapter then looks at the statistical model for the odds ratio, before differentiating between odds ratio and rate ratio. It also considers confounding and stratified sampling; individually matched studies; and nested Case-control studies.


2017 ◽  
Vol 33 (6) ◽  
Author(s):  
Raquel Barbosa-Lorenzo ◽  
Alberto Ruano-Ravina ◽  
Sara Cerdeira-Caramés ◽  
Mónica Raíces-Aldrey ◽  
Juan M. Barros-Dios

Case-control studies show an association between residential radon and lung cancer. The aim of this paper is to investigate this association through a cohort study. We designed an ambispective cohort study using the Galician radon map, Spain, with controls drawn from a previous case-control study. Subjects were recruited between 2002 and 2009. The data were cross-checked to ascertain lung cancer incidence and then analysed using a Cox regression model. A total of 2,127 subjects participated; 24 lung cancer cases were identified; 76.6% of subjects were drawn from the radon map. The adjusted hazard ratio was 1.2 (95%CI: 0.5-2.8) for the category of subjects exposed to 50Bq/m3 or more. This risk rose when subjects from the case-control study were analyzed separately. In conclusion, we did not observe any statistically significant association between residential radon exposure and lung cancer; however, it appears that with a sample of greater median age (such as participants from the case-control study), the risk of lung cancer would have been higher.


PLoS ONE ◽  
2015 ◽  
Vol 10 (3) ◽  
pp. e0119349 ◽  
Author(s):  
Ester M. M. Klaassen ◽  
John Penders ◽  
Quirijn Jöbsis ◽  
Kim D. G. van de Kant ◽  
Carel Thijs ◽  
...  

2014 ◽  
Vol 143 (3) ◽  
pp. 515-521 ◽  
Author(s):  
J. H. PARK ◽  
H. S. JEONG ◽  
J. S. LEE ◽  
S. W. LEE ◽  
Y. H. CHOI ◽  
...  

SUMMARYIn February 2012, an outbreak of gastroenteritis was reported in school A; a successive outbreak was reported at school B. A retrospective cohort study conducted in school A showed that seasoned green seaweed with radishes (relative risk 7·9, 95% confidence interval 1·1–56·2) was significantly associated with illness. Similarly, a case-control study of students at school B showed that cases were 5·1 (95% confidence interval 1·1–24·8) times more likely to have eaten seasoned green seaweed with pears. Multiple norovirus genotypes were detected in samples from students in schools A and B. Norovirus GII.6 isolated from schools A and B were phylogenetically indistinguishable. Green seaweed was supplied by company X, and norovirus GII.4 was isolated from samples of green seaweed. Green seaweed was assumed to be linked to these outbreaks. To our knowledge, this is the first reported norovirus outbreak associated with green seaweed.


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