r - Optimising mapply'ied function over large data frame

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I have following created function for my work purposes:

monthsCounter <- function(date1, date2) 
 if (date2 < date1) 
 warning("Can't calculate result if second date is older than first date")
 else 
 date1_Y <- as.numeric(format(date1, '%Y'))
 date2_Y <- as.numeric(format(date2, '%Y'))
 date1_M <- as.numeric(format(date1, '%m'))
 date2_M <- as.numeric(format(date2, '%m'))
 if (date2_Y == date1_Y) 
 date2_M - date1_M
 else if (date2_M < date1_M) 
 max(0, date2_Y - date1_Y - 1)*12 + 12 - date1_M + date2_M
 else 
 max(0, date2_Y - date1_Y)*12 + date2_M - date1_M
 
 

In a nutshel it counts months between two dates regardless of month date.
When I mapply it on my data frame:

allData$monthsSinceIssue <- mapply(monthsCounter, allData$start_month, allData$Date)

it takes very long time to calculate.

Question: Do you have any suggestions on how can I optimize my function to make it calculate faster?

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