This function creates a categorical variable that flags for increased long term health risks due to their drinking habits, according to Canada's Low-Risk Alcohol Drinking Guideline.

low_drink_long_fun(
  DHH_SEX,
  ALWDWKY,
  ALC_1,
  ALW_1,
  ALW_2A1,
  ALW_2A2,
  ALW_2A3,
  ALW_2A4,
  ALW_2A5,
  ALW_2A6,
  ALW_2A7
)

Arguments

DHH_SEX

Sex of respondent (1 - male, 2 - female)

ALWDWKY

Number of drinks consumed in the past week

ALC_1

Drinks in the past year (1 - yes, 2 - no)

ALW_1

Drinks in the last week (1 - yes, 2 - no)

ALW_2A1

Number of drinks on Sunday

ALW_2A2

Number of drinks on Monday

ALW_2A3

Number of drinks on Tuesday

ALW_2A4

Number of drinks on Wednesday

ALW_2A5

Number of drinks on Thursday

ALW_2A6

Number of drinks on Friday

ALW_2A7

Number of drinks on Saturday

Value

Categorical variable (ALWDVLTR_der) with two categories:

  • 1 - Increased long term health risk

  • 2 - No increased long term health risk

Details

The classification of drinkers according to their long term health risks comes from guidelines in Alcohol and Health in Canada: A Summary of Evidence and Guidelines for Low-risk Drinking, and is based on the alcohol consumption reported over the past week. Short-term or acute risks include injury and overdose.

Categories are based on CCHS 2015-2016's variable (ALWDVLTR) where long term health risk are increased when drinking more than 10 drinks a week for women, with no more than 2 drinks a day most days, and more than 15 drinks a week for men, with no more than 3 drinks a day most days.

See https://osf.io/ykau5/ for more details on the guideline. See https://osf.io/ycxaq/ for more details on the derivation of the function on page 8.

Examples

# Using low_drink_long_fun() to create ALWDVLTR_der values across CCHS cycles # low_drink_long_fun() is specified in variable_details.csv along with the # CCHS variables and cycles included. # To transform ALWDVLTR_der, use rec_with_table() for each CCHS cycle # and specify ALWDVLTR_der, along with the various alcohol and sex # variables. # Using merge_rec_data(), you can combine ALWDVLTR_der across cycles. library(cchsflow) long_low_drink2001 <- rec_with_table( cchs2001_p, c( "ALW_1", "DHH_SEX", "ALW_2A1", "ALW_2A2", "ALW_2A3", "ALW_2A4", "ALW_2A5", "ALW_2A6", "ALW_2A7", "ALWDWKY", "ALC_1","ALWDVLTR_der" ) )
#> No variable_details detected. #> Loading cchsflow variable_details
#> Using the passed data variable name as database_name
#> NOTE for ALWDWKY: shown as categorical variable in CCHS 2014 cycle
head(long_low_drink2001)
#> ALC_1 ALW_1 ALW_2A1 ALW_2A2 ALW_2A3 ALW_2A4 ALW_2A5 ALW_2A6 ALW_2A7 ALWDWKY #> 1 1 1 0 0 1 0 1 0 0 2 #> 2 2 NA(a) NA NA NA NA NA NA NA NA #> 3 1 1 0 0 0 1 6 0 1 8 #> 4 1 2 NA NA NA NA NA NA NA 0 #> 5 1 1 0 0 0 0 0 8 0 8 #> 6 1 2 NA NA NA NA NA NA NA 0 #> DHH_SEX ALWDVLTR_der #> 1 2 2 #> 2 2 NA(b) #> 3 1 1 #> 4 2 NA(b) #> 5 2 1 #> 6 1 NA(b)
long_low_drink2009_2010 <- rec_with_table( cchs2009_2010_p, c( "ALW_1", "DHH_SEX", "ALW_2A1", "ALW_2A2", "ALW_2A3", "ALW_2A4", "ALW_2A5", "ALW_2A6", "ALW_2A7", "ALWDWKY", "ALC_1","ALWDVLTR_der" ) )
#> No variable_details detected. #> Loading cchsflow variable_details
#> Using the passed data variable name as database_name
#> NOTE for ALWDWKY: shown as categorical variable in CCHS 2014 cycle
tail(long_low_drink2009_2010)
#> ALC_1 ALW_1 ALW_2A1 ALW_2A2 ALW_2A3 ALW_2A4 ALW_2A5 ALW_2A6 ALW_2A7 ALWDWKY #> 195 2 NA(a) NA NA NA NA NA NA NA NA #> 196 1 2 NA NA NA NA NA NA NA 0 #> 197 2 NA(a) NA NA NA NA NA NA NA NA #> 198 2 NA(a) NA NA NA NA NA NA NA NA #> 199 2 NA(a) NA NA NA NA NA NA NA NA #> 200 1 2 NA NA NA NA NA NA NA 0 #> DHH_SEX ALWDVLTR_der #> 195 2 NA(b) #> 196 2 NA(b) #> 197 2 NA(b) #> 198 1 NA(b) #> 199 2 NA(b) #> 200 2 NA(b)
combined_long_low_drink <- bind_rows(long_low_drink2001, long_low_drink2009_2010) head(combined_long_low_drink)
#> ALC_1 ALW_1 ALW_2A1 ALW_2A2 ALW_2A3 ALW_2A4 ALW_2A5 ALW_2A6 ALW_2A7 ALWDWKY #> 1 1 1 0 0 1 0 1 0 0 2 #> 2 2 NA(a) NA NA NA NA NA NA NA NA #> 3 1 1 0 0 0 1 6 0 1 8 #> 4 1 2 NA NA NA NA NA NA NA 0 #> 5 1 1 0 0 0 0 0 8 0 8 #> 6 1 2 NA NA NA NA NA NA NA 0 #> DHH_SEX ALWDVLTR_der #> 1 2 2 #> 2 2 NA(b) #> 3 1 1 #> 4 2 NA(b) #> 5 2 1 #> 6 1 NA(b)
tail(combined_long_low_drink)
#> ALC_1 ALW_1 ALW_2A1 ALW_2A2 ALW_2A3 ALW_2A4 ALW_2A5 ALW_2A6 ALW_2A7 ALWDWKY #> 395 2 NA(a) NA NA NA NA NA NA NA NA #> 396 1 2 NA NA NA NA NA NA NA 0 #> 397 2 NA(a) NA NA NA NA NA NA NA NA #> 398 2 NA(a) NA NA NA NA NA NA NA NA #> 399 2 NA(a) NA NA NA NA NA NA NA NA #> 400 1 2 NA NA NA NA NA NA NA 0 #> DHH_SEX ALWDVLTR_der #> 395 2 NA(b) #> 396 2 NA(b) #> 397 2 NA(b) #> 398 1 NA(b) #> 399 2 NA(b) #> 400 2 NA(b)
# Using low_drink_long_fun() to generate ALWDVLTR_der with user-inputted # values. # # Let's say you are a male, you had drinks in the last week and in the last # year. Let's say you had 5 drinks on Sunday, 1 drink on Monday, 6 drinks on # Tuesday, 4 drinks on Wednesday, 4 drinks on Thursday, 8 drinks on Friday, # and 2 drinks on Saturday with a total of 30 drinks in a week. # Using low_drink_long_fun(), we can check if you would be classified as # having an increased long term health risk due to drinking. long_term_drink <- low_drink_long_fun(DHH_SEX = 1, ALWDWKY = 30, ALC_1 = 1, ALW_1 = 1, ALW_2A1 = 5, ALW_2A2 = 1, ALW_2A3 = 6, ALW_2A4 = 4, ALW_2A5 = 4, ALW_2A6 = 8, ALW_2A7 = 2) print(long_term_drink)
#> [1] 1