Logistic regression - specific hypothesis I am doing a logistic model explaining if the physical health of a person has been impacted or not during COVID. To do that, I am using many socio-demographics factors as sex, income, education level, and ethnicity. My hypothesis is that women with low income, less education, and are non-white are more impacted than other groups. How can I test this specific hypothesis ?

I'll simulate some data similar to your problem and will fit a logistic regression model in R, and only look into three way interactions to compare all the combinations:
# simulate data
income = sample(c("low", "middle", "high"), 1000, replace = T)
race = sample(c("white", "non-white"), 1000, replace = T)
education = sample(c("low", "middle", "high"), 1000, replace = T)
y = rbinom(1000,1,c(0.1, 0.5, 0.9, 0.8, 0.4))

df = data.frame(y=y, income = income, race=race, education = education)

fit = glm(y ~ (income+race+education)^3 - (income+race+education)^2 - 1, data = df, family = binomial(link = 'logit'))
summary(fit)

You can visually compare the effects using GGally package like this:
GGally::ggcoef_model(fit)   


