Calculating relative risk in R

Question

I am working with the nhanes data from 2017-2018. I want to determine the relative risk of being overweight (Adipös) when being "Poor". And this grouped by Gender and Ethnicity. So far I have written this:

DurchgangJ%>%
  mutate( bmi = Gewicht / (Körpergröße/100)^2 ) %>%
  filter( Lebensalter >= 18 )%>%
  filter(!is.na(bmi))%>%
  filter(!is.na(Ratio))%>%
  mutate (Poor = Ratio < 1.3)%>%
  mutate (nichtarme = Ratio >= 1.3)%>%
  mutate (Adipös= bmi>=30)%>%
  mutate (Normal= bmi<30)%>%
  group_by(Geschlecht, Ethnie)%>%
  summarise (Arme = sum(Poor), Nicht_Arm= sum(nichtarme), Adipöse = sum (Adipös), Normal_Gewicht= sum (Normal))

which gives me the number of poor, overweight, normal weight and not poor people per gender and ethnicity:

I want to make the following calculations =

R1 = amount of overweight (Adipöse) not poor People (Nicht_Arm) / not poor people

R2 = amount of overweight poor people / poor people (Arme)

and then R2/R1

I got all the values I need apart from the amount of overweight not poor people and the amount of overweight poor people. I was thinking to maybe use the if/else function but I did not manage to make it work.

I am relatively new to R and therefore don't know really how to summarize TRUE and FALSE values. Because all I need for the overweight non poor people is the amount of where in both columns Adipös and Nicht_Arm it says TRUE.

Thank you for your help

Answer 1

This is more of a programming than a data science question and is therefore better suited to the stackoverflow stackexchange page. Without having a data sample it is bit difficult, but I would expect something like this to at least get close to what you're looking for:

DurchgangJ %>%
  mutate(bmi = Gewicht / (Körpergröße/100)^2) %>%
  filter(Lebensalter >= 18)%>%
  filter(!is.na(bmi))%>%
  filter(!is.na(Ratio))%>%
  mutate(Poor = Ratio < 1.3)%>%
  mutate(Overweight = bmi > 30)%>%
  group_by(Geschlecht, Ethnie)%>%
  summarise(
      R1 = sum(Overweight & !Poor) / sum(!Poor).
      R2 = sum(Overweight & Poor) / sum(Poor)
    )