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Internet of Medical Things: Current and Future Trends
Published in Manuel Cardona, Vijender Kumar Solanki, Cecilia E. García Cena, Internet of Medical Things, 2021
Lucia Alonso Virgos, Miguel A. Sanchez Vidales, Fernando López Hernández, J. Javier Rainer Granados
The underlying studies have been traditionally classified into observational and experimental studies [8]. Observational studies do not expose participants to the risk factors; the most common observational types are: Case study surveys the evolution of a particular individual suffering from a certain disease, within a particular situation or period of time.Case-control study is a retrospective survey of two groups: one with the disease (the case) and another one without the disease (the control). Typically, the odds ratio between the exposure levels of both groups is measured aiming to determine the level of causality between the exposure and the disease.Cohort study is a longitudinal study that samples a cohort (group of individuals at risk of developing the disease) [9]. The study registers through time the level of exposure of the individuals to the risk factors and those who have developed the disease.
Measures of Association and Public Health Impact
Published in Frank R. Spellman, Fundamentals of Wastewater-Based Epidemiology, 2021
Another measure of association is an odds ratio; it quantifies the relationship between an exposure with two categories and health outcome. Moreover, the odds ratio is the measure of choice in a case-control study. A case-control study is based on enrolling a group of persons with disease (“case-patients”) and a comparable group without disease (“controls”). The number of persons in the control group is usually decided by the investigation. Often, the size of the population from which the case-patients came is not known. As a result, risks, rates, risk ratios, or rater ratios can’t be calculated from the typical case-control study. However, you can calculate an odds ratio and interpret it as an approximation of the risk ratio, particularly when the disease is uncommon in the population.
Epidemiology
Published in Samuel C. Morris, Cancer Risk Assessment, 2020
As the name suggests, this design consists of a case-control study “nested” in a cohort study. It combines some advantages of both types. A single population is defined at the outset and followed for a given period, identifying incident cases or deaths. At some point in the study, often after an etiologic hypothesis emerges from the preliminary cohort study results, the cases are compared with a group of controls selected from the same cohort population on either a random or matched basis. This assures that the cases and controls are from the same well-defined population.
Describing the appropriate use and interpretation of odds and risk ratios
Published in Research in Sports Medicine, 2023
M. R. Lininger, H. J. Root, R. Camplain, S. D. Barger
In a case-control study, researchers retrospectively compare those who already have the outcome of interest to “healthy” controls who are otherwise similar but do not have the outcome to determine what specific risk factors (exposures) likely contributed to the outcome. For example, researchers compared those with Chronic Ankle Instability (CAI) to those without CAI (Figure 2) by reviewing clinical notes to determine distance on the Star Excursion Balance Test (SEBT), a common metric used to measure balance deficits (Freeman et al., 1965; Hertel & Corbett, 2019). In Figure 2, the odds of having a previous history of balance deficits as measured by the SEBT among those who have CAI was 3.90 times the odds of having a history of balance deficits and not suffering from CAI. Because this is a retrospective study design, causal attributions regarding balance deficits are not appropriate, but the observed OR may warrant further study of this association.
Comment on “Anxiety and depression predict musculoskeletal disorders in health care workers” by Del Campo et al
Published in Archives of Environmental & Occupational Health, 2018
Finally, Del Campo et al handled a limited number of cases, and wide ranges of 95% CI would present an unstable estimate of OR. In addition, conditional logistic regression analysis would be appropriate for a case-control study. Furthermore, the authors selected 1:1 matching in their case-control study. If there is pooled large data, matching ratio of controls should be kept higher. Anyway, a limited number of controls should be avoided.4