low_drink_long_fun {cchsflow} | R Documentation |
Long term risks due to drinking
Description
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.
Usage
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 |
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.
Value
Categorical variable (ALWDVLTR_der) with two categories:
1 - Increased long term health risk
2 - No increased long term health risk
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"
)
)
head(long_low_drink2001)
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"
)
)
tail(long_low_drink2009_2010)
combined_long_low_drink <- bind_rows(long_low_drink2001,
long_low_drink2009_2010)
head(combined_long_low_drink)
tail(combined_long_low_drink)
# 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)