Cross Sectional Data Studies


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Cross-sectional studies a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time—that is, cross-sectional data. Some strengths of a cross-sectional study are relatively quick and easy to conduct (no long periods of follow-up), data on all variables is only collected once,able to measure prevalence for all factors under investigation, multiple outcomes and exposures can be studied. (Hennekens & Buring 1987) )Some of the weakness of a cross sectional study are difficult to determine whether the outcome followed exposure in time or exposure resulted from the outcome, not suitable for studying rare diseases or diseases with a short duration, as cross-sectional studies measure prevalent rather than incident cases, the data will always reflect determinants of survival as well as ontology and unable to measure incidence.(Hennekens & Buring 1987) They are used as descriptive and analytic by measuring the frequency of several factors, and hence the size of the problem. The prevalence of an outcome depends on the incidence of the disease as well as the length of survival following the outcome. For example, even if the incidence of HIV (number of new cases) goes down in one particular community, the prevalence (total number of cases – old as well as new) may increase. (Setia 2016)