To create the outcome variable for this analysis, we will categorise BMI into meaningful groupings that are based on the World Health Organisation (WHO) standards. Few of the sample were underweight (n=54; less than 1%) so in this example they will be included in the normal or healthy category.
Once we have created the variable, we can use the ‘tab’ command to look at the number of participants that fall into each BMI category .
Just under half (48%) of our sample were normal or healthy weight, over a third (37%) were overweight and 15% were obese.
All of the predictor variables are the same as those used in the general linear and logistic regression sections. It is always important to explore the data before running statistical models. To examine the data, please look at exploring the data. If you have not done so already you will also need to construct a few of the explanatory variables before creating your regression model, see main variables of interest.
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