I need counts of all levels used in a glm, including the reference levels. Here is code I am using with an example dataset:

library(tidyverse)
library(writexl)
install.packages("AER")
library("AER")
data(Affairs, package="AER")
Affairs$ynaffair[Affairs$affairs >  0] <- 1
Affairs$ynaffair[Affairs$affairs == 0] <- 0

Affairs <- Affairs %>% 
  mutate_at(c("affairs", "religiousness", "occupation", "rating", "ynaffair"), as.factor)

Affairs$religiousness <- relevel(Affairs$religiousness, ref="1")
Affairs$rating <- relevel(Affairs$rating, ref="1")
Affairs$gender <- relevel(Affairs$gender, ref="female")

example_model <- glm(ynaffair~gender + age + yearsmarried + children + religiousness + education + occupation + rating,
               family = binomial,
             data = Affairs)

n <- colSums(model.matrix(example_model)) ##Suggestion from another post
n_tidy <- tidy(n) %>% 
  rename("Covariate" = 'names') %>% 
  rename("n" = 'x')

output_ex <- tidy(example_model) %>% 
  select(-c(statistic, std.error)) %>% 
  mutate(OR = exp(estimate)) %>% 
  rename("Covariate" = 'term') %>% 
  left_join(n_tidy, by = "Covariate")  %>% 
  select(Covariate, n, OR, p.value) 

write_xlsx(output_ex, "output_ex.xlsx")

This is what I currently get:

This is what I would like:

Another post suggested using colSums(model.matrix(example_model)), which gets me some of the counts I need, but not all of them.

Any advice or suggestions for a simpler way would be greatly appreciated.