Post 3: Cross-sectional Study Design

Cross sectional studies involve the simultaneous collection of exposure and outcome data from a selected group of individuals belonging to a specified population group at a given point in time¹. Collected data can be grouped into diseased/non-diseased and exposed/non-exposed groups and associations can be studied, however as temporality is not taken into account, causality cannot be determined.  Possible limitations include bias from both outcomes that have an effect on the exposure variable and population group selection.  

Image 2: Schematic diagram of Cross-sectional study design

Particularly useful in assessing the burden of disease of health needs of a population, it is a preferred design to find out the prevalence and associated risk factors of a particular outcome or  disease2 .  Application of cross sectional studies are valuable in planning health care, for example, a physiotherapist planning an aged strength training programme, might wish to know the prevalence of different risk factors of osteoporosis in the group under their care so that interventions could be tailored accordingly.

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1    Dickinson K. Ecological Study [unpublished lecture notes]. Flinders University; lecture notes  provided at lecture given 2015 February 20.

2    British Medical Journal [internet]. Case control and cross-sectional study [cited 2015 May 4]. Available from http://www.bmj.com/about-bmj/resources-readers/publications/ epidemiology-uninitiated/8-case-control-and-cross-sectional

Post 4: Case-Control Study Design

These studies are based on the observation of naturally occurring exposures and test hypotheses that look to answer questions that may have risen from population based studies.  They are often called retrospective studies because researchers start with an end point and work backwards to determine what might have caused the outcome and allow multiple risk factors to be considered¹.  For example, researchers could take two groups of participants, one who have been diagnosed with osteoporosis (cases) and those who haven’t (controls).  Researchers could then work backwards and survey the two groups about their earlier health behaviours to determine what might have caused the disease to develop or not.  They may explore issues such as calcium intake or dietary intake to compare differences in risk factors or exposures that emerge in each group².  

Image 3: Schematic diagram of Case-Control study design

	While the main problem with case-control studies is that they are susceptible to recall bias and confounding, that is a third, difficult to predict, variable. However they are useful in measuring the strength of the association between an exposure and the outcome, identify possible predictors of outcome and yield an odds ratio which usually then approximates the relative risk.

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1   Lewallen S Courtright P.  Epidemiology in Practice: Case-Control Studies. Comm Eye Hlth. 1998; 11(28):57-58

2   Himmelfarb Health Sciences Library.  Study Design 101: Case Control Study, [cited May 4 2015] https://himmelfarb.gwu.edu/tutorials/studydesign101/casecontrols. html