Gender and Age are strings in the file so it is not clear how lm use them and if lm simply translates them to integers then it is not clear to me how you translate them.
Gender is actually a factor, not a string. Factors are a rather unqiue data type used to represent categorical data. Age can also be represented as an ordered factor, but I suggest you find a way to convert it to a continuous variable, as that makes intuitive sense.
Just a word of caution on that approach. I would recommend keeping age as a categorical variable. While intuitively, you would expect hospitalization rates to increase with age, there is one key exception to that rule: females in the "birthing years". I haven't tested it out, but I think there are enough data points in each age "bin" that you can get stable answers by keeping age as categorical.
Even without the birthing years issue, there is no reason to expect that hospitalization rates are linear with age. There may be sections of flatness and steepness as you progress in age. Better to let the data tell you what that is rather than artificially imposing a model on the age dependency.