Make Categorical Variable Out of Continuous Variable

Make categorical variable out of a continuous one is sometimes needed in biostatistics, especially if you encounter issues with distribution. Here is an example of some code where I do that using an NHANES dataset as demonstration (which you can read about here).

If you watch the video, you’ll see that I’m working with a blood pressure dataset called BLPS_a make categorical variables. The continuous variable I’m using is a systolic blood pressure (SBP) reading named BPXOSY1. Before I make variable, I want to view the distribution, so I use the hist command to get a histogram, and the quantile command to get quartiles.

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hist(BLPS_a$BPXOSY1)
quantile(BLPS_a$BPXOSY1, na.rm = TRUE)

Here is what the output looks like.

You should look at distributions in continuous variables before analyzing them.

You can use this output to determine data-driven cutpoints to turn your continuous variable to make categorical variable. However, we want to make empirical cutpoints. These are based on the American Heart Association classifications for SBP.

These are blood pressure classifications so you can make a grouping variable.

These are the classifications we are using.
It can be helpful to use empirical classifications even if they are not data-driven.
That way, they can be compared to other data classified the same way.

You will see in the code below how I executed those boundaries using the conditions in the code. I make the variable BPLSGrp through executing those criteria. Then I check it with a table command.

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BLPS_a$BLPSGrp <- 9
BLPS_a$BLPSGrp[BLPS_a$BPXOSY1 < 120] <- 1
BLPS_a$BLPSGrp[BLPS_a$BPXOSY1 >= 120 & BLPS_a$BPXOSY1 < 130] <- 2
BLPS_a$BLPSGrp[BLPS_a$BPXOSY1 >= 130] <- 3

table(BLPS_a$BPXOSY1, BLPS_a$BLPSGrp, useNA = c("always"))

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