Determining the association between physical activity and stroke a case-control study using Bayesian model averaging - Reandelar, Macario F., Jr
The protective benefits of increased physical activity in relation to cardiovascular diseases have been thoroughly studied. Relationship between physical activity and stroke however has not been conclusively established. This paper aims to study the relationship of habitual physical activity and stroke. This is a re-analysis of a paper authored by Myra Chua aimed at establishing such a relationship using classical logistic regression. Cases were hospital patients with stroke from two government hospitals and controls were patients in the same hospitals with other chronic diseases. In this paper, another approach in the analyses is done - a Bayesian Model Averaging, the aim being the same, to determine the relationship between physical activity and stroke. It hopes to establish that relationship using a strategy in the analyses. Confounding variables that were controlled were socio-demographic data, smoking and alcoholism and medical history of hypertension, diabetes, and cardiovascular diseases. Multiple logistic regression was used initially to estimate the association between physical activity and stroke and the results were used as basis for analyses using Bayesian model averaging. Using low level of physical activity as the reference, results using the method of BMA showed that subjects with moderate to high physical activity have higher odds of developing stroke, 1.23 (0.67) to 1.79) controlling for the other variables. Its posterior probability that physical activity is a risk factor to stroke is 2.93%. BMA can be seen as another way of looking at the significance of a variable in terms of posterior probabilities instead of p-values.