data-raw/create-data-riskfactors.R

In njtierney/narnia: Data Structures, Summaries, and Visualisations for Missing Data

# modify the brfss data from the MissingDataGUI dataset

library(tidyverse)
library(janitor)
library(naniar)

# downloaded from https://github.com/chxy/MissingDataGUI/blob/master/data/brfss.rda
# as I could not install MissingDataGUI
# load("~/Downloads/brfss.rda")

riskfactors <- brfss %>%
  tibble::as_tibble() %>%
  janitor::clean_names() %>%
  dplyr::rename(
    hispanic = hispanc2,
    veteran = veteran2,
    education = educa,
    employment = employ,
    income = income2,
    weight_lbs = weight2,
    height_inch = height3,
    health_general = genhlth,
    health_physical = physhlth,
    health_mental = menthlth,
    health_poor = poorhlth,
    health_cover = hlthplan,
    provide_care = caregive,
    activity_limited = qlactlm2,
    drink_any = drnkany4,
    drink_days = alcday4,
    drink_average = avedrnk2,
    smoke_100 = smoke100,
    smoke_days = smokday2,
    smoke_stop = stopsmk2,
    smoke_last = lastsmk1,
    diet_fruit = fruit,
    diet_salad = greensal,
    diet_potato = potatoes,
    diet_carrot = carrots,
    diet_vegetable = vegetabl,
    diet_juice = fruitjui,
    bmi = bmi4
  ) %>%
  # change the order slightly to group together health/demographics
  dplyr::select(
    state,
    sex,
    age,
    weight_lbs,
    height_inch,
    bmi,
    marital,
    pregnant,
    children,
    education,
    employment,
    income,
    veteran,
    hispanic,
    dplyr::everything()
  ) %>%
  # recode BMI to be decimal, as it should be
  dplyr::mutate(bmi = bmi / 100)

devtools::use_data(riskfactors, overwrite = TRUE)
# then delete the brfss dataset