R/smoking.R
In Big-Life-Lab/cchsflow: Transforming and Harmonizing CCHS Variables
Defines functions
SMKG207_fun
SMKG203_fun
SMKDSTY_fun
pack_years_fun_cat
SMKG040_fun
pack_years_fun
smoke_simple_fun
time_quit_smoking_fun
Documented in
pack_years_fun
pack_years_fun_cat
SMKDSTY_fun
SMKG040_fun
SMKG203_fun
SMKG207_fun
smoke_simple_fun
time_quit_smoking_fun
#' @title Time since quit smoking
#'
#' @description This function creates a derived variable (time_quit_smoking_der)
#' that calculates the approximate time a former smoker has quit smoking based
#' on various CCHS smoking variables. This variable is for CCHS respondents in
#' CCHS surveys 2003-2014.
#'
#' @param SMK_09A_B number of years since quitting smoking. Variable asked to
#' former daily smokers who quit <3 years ago.
#'
#' @param SMKG09C number of years since quitting smoking. Variable asked to
#' former daily smokers who quit >=3 years ago.
#'
#' @return value for time since quit smoking in time_quit_smoking_der.
#'
#' @examples
#' # Using time_quit_smoking_fun() to create pack-years values across CCHS
#' # cycles.
#' # time_quit_smoking_fun() is specified in variable_details.csv along with the
#' # CCHS variables and cycles included.
#'
#' # To transform time_quit_smoking across cycles, use rec_with_table() for each
#' # CCHS cycle and specify time_quit_smoking, along with each smoking variable.
#' # Then by using merge_rec_data(), you can combine time_quit_smoking across
#' # cycles.
#'
#' library(cchsflow)
#'
#' time_quit2009_2010 <- rec_with_table(
#' cchs2009_2010_p, c(
#' "SMK_09A_B", "SMKG09C", "time_quit_smoking"
#' )
#' )
#'
#' head(time_quit2009_2010)
#'
#' time_quit2011_2012 <- rec_with_table(
#' cchs2011_2012_p, c(
#' "SMK_09A_B", "SMKG09C", "time_quit_smoking"
#' )
#' )
#'
#' tail(time_quit2011_2012)
#'
#' combined_time_quit <- suppressWarnings(merge_rec_data(time_quit2009_2010,
#' time_quit2011_2012))
#'
#' head(combined_time_quit)
#' tail(combined_time_quit)
#' @export
time_quit_smoking_fun <- function(SMK_09A_B, SMKG09C) {
SMKG09C_cont <-
if_else2(
SMKG09C == 1, 4,
if_else2(
SMKG09C == 2, 8,
if_else2(SMKG09C == 3, 12,
if_else2(SMKG09C == "NA(a)", tagged_na("a"), tagged_na("b")
)
)
)
)
tsq_ds <-
if_else2(
SMK_09A_B == 1, 0.5,
if_else2(
SMK_09A_B == 2, 1.5,
if_else2(
SMK_09A_B == 3, 2.5,
if_else2(SMK_09A_B == 4, SMKG09C_cont,
if_else2(SMK_09A_B == "NA(a)", tagged_na("a"), tagged_na("b")
)
)
)
)
)
return(tsq_ds)
}
#' @title Simple smoking status
#'
#' @description This function creates a derived smoking variable (smoke_simple)
#' with four categories:
#'
#' \itemize{
#' \item non-smoker (never smoked)
#' \item current smoker (daily and occasional?)
#' \item former daily smoker quit =<5 years or former occasional smoker
#' \item former daily smoker quit >5 years
#' }
#'
#' @param SMKDSTY_cat5 derived variable that classifies an individual's smoking
#' status. This variable captures cycles 2001-2018.
#'
#' @param time_quit_smoking derived variable that calculates the approximate
#' time a former smoker has quit smoking.
#' See \code{\link{time_quit_smoking_fun}} for documentation on how variable
#' was derived.
#'
#' @examples
#' # Using the 'smoke_simple_fun' function to create the derived smoking
#' # variable across CCHS cycles.
#' # smoke_simple_fun() is specified in the variable_details.csv
#'
#' # To create a harmonized smoke_simple variable across CCHS cycles, use
#' # rec_with_table() for each CCHS cycle and specify smoke_simple_fun and
#' # the required base variables. Since time_quit_smoking_der is also a derived
#' # variable, you will have to specify the variables that are derived from it.
#' # Using merge_rec_data(), you can combine smoke_simple across cycles.
#'
#' library(cchsflow)
#'
#' smoke_simple2009_2010 <- rec_with_table(
#' cchs2009_2010_p, c(
#' "SMKDSTY", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "smoke_simple"
#' )
#' )
#'
#' head(smoke_simple2009_2010)
#'
#' smoke_simple2011_2012 <- rec_with_table(
#' cchs2011_2012_p,c(
#' "SMKDSTY", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "smoke_simple"
#' )
#' )
#'
#' tail(smoke_simple2011_2012)
#'
#' combined_smoke_simple <-
#' suppressWarnings(merge_rec_data(smoke_simple2009_2010,smoke_simple2011_2012))
#'
#' head(combined_smoke_simple)
#' tail(combined_smoke_simple)
#' @export
smoke_simple_fun <-
function(SMKDSTY_cat5, time_quit_smoking) {
# Nested function: current smoker status
derive_current_smoker <- function(SMKDSTY_cat5) {
smoker <-
ifelse(SMKDSTY_cat5 %in% c(1, 2), 1,
ifelse(SMKDSTY_cat5 %in% c(3, 4, 5), 0,
ifelse(SMKDSTY_cat5 == "NA(a)", "NA(a)", "NA(b)")))
return(smoker)
}
smoker <- derive_current_smoker(SMKDSTY_cat5)
# Nested function: ever smoker status
derive_ever_smoker <- function(SMKDSTY_cat5) {
eversmoker <-
ifelse(SMKDSTY_cat5 %in% c(1, 2, 3, 4), 1,
ifelse(SMKDSTY_cat5 == 5, 0,
ifelse(SMKDSTY_cat5 == "NA(a)", "NA(a)", "NA(b)")))
return(eversmoker)
}
eversmoker <- derive_ever_smoker(SMKDSTY_cat5)
# smoke_simple 0 = non-smoker
smoke_simple <-
ifelse(smoker == 0 & eversmoker == 0, 0,
# smoke_simple 1 = current smoker
ifelse(smoker == 1 & eversmoker == 1, 1,
# smoke_simple 2 = former daily smoker quit =<5 years or former occasional
# smoker
ifelse(smoker == 0 & eversmoker == 1 & time_quit_smoking <= 5 |
SMKDSTY_cat5 == 4, 2,
# smoke_simple 3 = former daily smoker quit > 5 years
ifelse(smoker == 0 & eversmoker == 1 & time_quit_smoking > 5,
3,
ifelse(smoker == "NA(a)" & eversmoker == "NA(a)" &
time_quit_smoking == "NA(a)", "NA(a)", "NA(b)")))))
return(smoke_simple)
}
#' @title Smoking pack-years
#'
#' @description This function creates a derived variable (pack_years_der) that
#' measures an individual's smoking pack-years based on various CCHS smoking
#' variables. This is a popular variable used by researchers to quantify
#' lifetime exposure to cigarette use.
#'
#' @details pack-years is calculated by multiplying the number of cigarette
#' packs per day (20 cigarettes per pack) by the number of years. Example 1:
#' a respondent who is a current smoker who smokes 1 package of cigarettes for
#' the last 10 years has smoked 10 pack-years. Pack-years is also calculated
#' for former smokers. Example 2: a respondent who started smoking at age
#' 20 years and smoked half a pack of cigarettes until age 40 years smoked for
#' 10 pack-years.
#'
#' @param SMKDSTY_A variable used in CCHS cycles 2001-2014 that classifies an
#' individual's smoking status.
#'
#' @param DHHGAGE_cont continuous age variable.
#'
#' @param time_quit_smoking derived variable that calculates the approximate
#' time a former smoker has quit smoking.
#' See \code{\link{time_quit_smoking_fun}} for documentation on how variable
#' was derived
#'
#' @param SMKG203_cont age started smoking daily. Variable asked to daily
#' smokers.
#'
#' @param SMKG207_cont age started smoking daily. Variable asked to former
#' daily smokers.
#'
#' @param SMK_204 number of cigarettes smoked per day. Variable asked to
#' daily smokers.
#'
#' @param SMK_05B number of cigarettes smoked per day. Variable asked to
#' occasional smokers
#'
#' @param SMK_208 number of cigarettes smoked per day. Variable asked to former
#' daily smokers
#'
#' @param SMK_05C number of days smoked at least one cigarette
#'
#' @param SMK_01A smoked 100 cigarettes in lifetime (y/n)
#'
#' @param SMKG01C_cont age smoked first cigarette
#'
#' @return value for smoking pack-years in the pack_years_der variable
#'
#' @examples
#' # Using pack_years_fun() to create pack-years values across CCHS cycles
#' # pack_years_fun() is specified in variable_details.csv along with the CCHS
#' # variables and cycles included.
#'
#' # To transform pack_years_der across cycles, use rec_with_table() for each
#' # CCHS cycle and specify pack_years_der, along with each smoking variable.
#' # Since time_quit_smoking_der is also a derived
#' # variable, you will have to specify the variables that are derived from it.
#' # Then by using merge_rec_data(), you can combine pack_years_der across
#' # cycles
#'
#' library(cchsflow)
#'
#' pack_years2009_2010 <- rec_with_table(
#' cchs2009_2010_p, c(
#' "SMKDSTY_A", "DHHGAGE_cont", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "SMKG203_cont", "SMKG207_cont", "SMK_204", "SMK_05B", "SMK_208",
#' "SMK_05C", "SMK_01A", "SMKG01C_cont", "pack_years_der"
#' )
#' )
#'
#' head(pack_years2009_2010)
#'
#' pack_years2011_2012 <- rec_with_table(
#' cchs2011_2012_p,c(
#' "SMKDSTY_A", "DHHGAGE_cont", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "SMKG203_cont", "SMKG207_cont", "SMK_204", "SMK_05B", "SMK_208",
#' "SMK_05C", "SMK_01A", "SMKG01C_cont", "pack_years_der"
#' )
#' )
#'
#' tail(pack_years2011_2012)
#'
#' combined_pack_years <- suppressWarnings(merge_rec_data(pack_years2009_2010,
#' pack_years2011_2012))
#'
#' head(combined_pack_years)
#' tail(combined_pack_years)
#' @export
pack_years_fun <-
function(SMKDSTY_A, DHHGAGE_cont, time_quit_smoking, SMKG203_cont,
SMKG207_cont, SMK_204, SMK_05B,
SMK_208, SMK_05C, SMKG01C_cont, SMK_01A) {
# Age verification
if (is.na(DHHGAGE_cont)) {
return(tagged_na("b"))
} else if (DHHGAGE_cont < 0) {
return(tagged_na("b"))
}
# PackYears for Daily Smoker
pack_years <-
if_else2(
SMKDSTY_A == 1, pmax(((DHHGAGE_cont - SMKG203_cont) *
(SMK_204 / 20)), 0.0137),
# PackYears for Occasional Smoker (former daily)
if_else2(
SMKDSTY_A == 2, pmax(((DHHGAGE_cont - SMKG207_cont -
time_quit_smoking) * (SMK_208 / 20)), 0.0137) +
(pmax((SMK_05B * SMK_05C / 30), 1) *time_quit_smoking),
# PackYears for Occasional Smoker (never daily)
if_else2(
SMKDSTY_A == 3, (pmax((SMK_05B * SMK_05C / 30), 1) / 20) *
(DHHGAGE_cont - SMKG01C_cont),
# PackYears for former daily smoker (non-smoker now)
if_else2(
SMKDSTY_A == 4, pmax(((DHHGAGE_cont - SMKG207_cont -
time_quit_smoking) *
(SMK_208 / 20)), 0.0137),
# PackYears for former occasional smoker (non-smoker now) who
# smoked at least 100 cigarettes lifetime
if_else2(
SMKDSTY_A == 5 & SMK_01A == 1, 0.0137,
# PackYears for former occasional smoker (non-smoker now) who
# have not smoked at least 100 cigarettes lifetime
if_else2(
SMKDSTY_A == 5 & SMK_01A == 2, 0.007,
# Non-smoker
if_else2(SMKDSTY_A == 6, 0,
# Account for NA(a)
if_else2(SMKDSTY_A == "NA(a)", tagged_na("a"),
tagged_na("b"))
)
)
)
)
)
)
)
return(pack_years)
}
#' @title Age started smoking daily - daily/former daily smokers
#'
#' @description This function creates a continuous derived variable
#' (SMKG040_fun) that calculates the approximate age that a daily or former
#' daily smoker began smoking daily.
#'
#' @details SMKG203 (daily smoker) and SMKG207 (former daily) are present in
#' CCHS 2001-2014, and are separate variables. For CCHS 2015 and onward, SMKG040
#' (daily/former daily) combines the two previous variables. SMKG040_fun takes
#' the continuous functions (SMKG203_cont and SMKG207_cont) to create SMKG040
#' for 2001-2014.
#'
#' @note In previous cycles, both SMKG203 and SMKG207 included respondents who
#' did not state their smoking status. From CCHS 2015 and onward, SMKG040 only
#' included respondents who specified daily smoker or former daily smoker. As
#' a result, SMKG040 has a large number of missing respondents for CCHS 2015
#' survey cycles and onward.
#'
#' @param SMKG203_cont age started smoking daily. Variable asked to daily
#' smokers.
#'
#' @param SMKG207_cont age started smoking daily. Variable asked to former
#' daily smokers.
#'
#' @return value for age started smoking daily for daily/former daily smokers in
#' the SMKG040_cont variable
#'
#' @examples
#' # Using SMKG040_fun() to create age values across CCHS cycles
#' # SMKG040_fun() is specified in variable_details.csv under SMKG040_cont.
#'
#' # To create a continuous harmonized variable for SMKG040, use rec_with_table()
#' # for each CCHS cycle and specify SMKG040_cont.
#'
#' library(cchsflow)
#'
#' age_smoke_dfd_2009_2010 <- rec_with_table(
#' cchs2009_2010_p, c(
#' "SMKG203_cont", "SMKG207_cont","SMKG040_cont"
#' )
#' )
#'
#' head(age_smoke_dfd_2009_2010)
#'
#' age_smoke_dfd_2011_2012 <- rec_with_table(
#' cchs2011_2012_p,c(
#' "SMKG203_cont", "SMKG207_cont","SMKG040_cont"
#' )
#' )
#'
#' tail(age_smoke_dfd_2011_2012)
#'
#' combined_age_smoke_dfd <- suppressWarnings(merge_rec_data
#' (age_smoke_dfd_2009_2010,age_smoke_dfd_2011_2012))
#'
#' head(combined_age_smoke_dfd)
#' tail(combined_age_smoke_dfd)
#' @export
SMKG040_fun <- function(SMKG203_cont, SMKG207_cont){
SMKG040_cont <-
if_else2((SMKG203_cont == tagged_na("a") & SMKG207_cont == tagged_na("a")),
tagged_na("a"),
if_else2((SMKG203_cont == tagged_na("b") &
SMKG207_cont == tagged_na("b")), tagged_na("b"),
if_else2(!is.na(SMKG203_cont), SMKG203_cont,
if_else2(!is.na(SMKG207_cont), SMKG207_cont,
tagged_na("b")))))
return(SMKG040_cont)
}
#' @title Categorical smoking pack-years
#'
#' @description This function creates a categorical derived variable
#' (pack_years_cat) that categorizes smoking pack-years (pack_years_der).
#'
#' @details pack-years is calculated by multiplying the number of cigarette
#' packs per day (20 cigarettes per pack) by the number of years.The categories
#' were based on the Cardiovascular Disease Population Risk Tool
#' (Douglas Manuel et al. 2018).
#'
#' pack_years_cat uses the derived variable pack_years_der. Pack_years_der uses
#' age and various smoking variables that have been transformed by cchsflow (see
#' documentation on pack_year_der). In order to categorize pack years across CCHS
#' cycles, age and smoking variables must be transformed and harmonized.
#'
#' @param pack_years_der derived variable that calculates smoking pack-years
#' See \code{\link{pack_years_fun}} for documentation on how variable
#' was derived.
#'
#' @return value for pack year categories in the pack_years_cat variable.
#'
#' @examples
#' # Using pack_years_fun_cat() to categorize pack year values across CCHS cycles
#' # pack_years_fun_cat() is specified in variable_details.csv along with the
#' # CCHS variables and cycles included.
#'
#' # To transform pack_years_cat across cycles, use rec_with_table() for each
#' # CCHS cycle and specify pack_years_cat.
#' # Since pack_year_der is also also derived variable, you will have to specify
#' # the variables that are derived from it.
#' # Since time_quit_smoking_der is also a derived variable in pack_year_der,
#' # you will have to specify the variables that are derived from it.
#' # Then by using merge_rec_data(), you can combine pack_years_cat across
#' # cycles.
#'
#' library(cchsflow)
#'
#' pack_years_cat_2009_2010 <- rec_with_table(
#' cchs2009_2010_p, c(
#' "SMKDSTY_A", "DHHGAGE_cont", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "SMKG203_cont", "SMKG207_cont", "SMK_204", "SMK_05B", "SMK_208",
#' "SMK_05C", "SMK_01A", "SMKG01C_cont", "pack_years_der", "pack_years_cat"
#' )
#' )
#'
#' head(pack_years_cat_2009_2010)
#'
#' pack_years_cat_2011_2012 <- rec_with_table(
#' cchs2011_2012_p,c(
#' "SMKDSTY_A", "DHHGAGE_cont", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "SMKG203_cont", "SMKG207_cont", "SMK_204", "SMK_05B", "SMK_208",
#' "SMK_05C", "SMK_01A", "SMKG01C_cont", "pack_years_der", "pack_years_cat"
#' )
#' )
#'
#' tail(pack_years_cat_2011_2012)
#'
#' combined_pack_years_cat <- suppressWarnings(merge_rec_data
#' (pack_years_cat_2009_2010,pack_years_cat_2011_2012))
#'
#' head(combined_pack_years_cat)
#' tail(combined_pack_years_cat)
#' @export
#'
pack_years_fun_cat <- function(pack_years_der){
pack_years_cat <-
if_else2(pack_years_der == 0, 1,
if_else2(pack_years_der > 0 & pack_years_der <= 0.01, 2,
if_else2(pack_years_der > 0.01 & pack_years_der <= 3.0, 3,
if_else2(pack_years_der > 3.0 & pack_years_der <= 9.0, 4,
if_else2(pack_years_der > 9.0 & pack_years_der <= 16.2, 5,
if_else2(pack_years_der > 16.2 & pack_years_der <= 25.7, 6,
if_else2(pack_years_der > 25.7 & pack_years_der <= 40.0, 7,
if_else2(pack_years_der > 40.0, 8,
if_else2(haven::is_tagged_na(pack_years_der, "a"), "NA(a)", "NA(b)")))))))))
return(pack_years_cat)
}
#' @title Type of smokers
#'
#' @description This function creates a derived variable (SMKDSTY_A) for
#' smoker type with 5 categories:
#'
#' \itemize{
#' \item daily smoker
#' \item current occasional smoker (former daily)
#' \item current occasional smoker (never daily)
#' \item current nonsmoker (former daily)
#' \item current nonsmoker (never daily)
#' \item nonsmoker
#' }
#'
#' @details For CCHS 2001-2014, smoker type is derived from smoking more than
#' 100 cigarettes in lifetime, type of smoker at present time, and ever smoked
#' daily. For CCHS 2015-2018, smoker type was derived differently with different
#' variables and categories. A function was created for a consistent smoker
#' status across all cycles.
#'
#' @param SMK_005 type of smoker presently
#'
#' @param SMK_030 smoked daily - lifetime (occasional/former smoker)
#'
#' @param SMK_01A smoked 100 or more cigarettes in lifetime
#'
#' @return value for smoker type in the SMKDSTY_A variable
#'
#' @examples
#' # Using SMKDSTY_fun() to derive smoke type values across CCHS cycles
#' # SMKDSTY_fun() is specified in variable_details.csv along with the
#' # CCHS variables and cycles included.
#'
#' # To transform SMKDSTY_A across cycles, use rec_with_table() for each
#' # CCHS cycle and specify SMKDSTY_A.
#' # For CCHS 2001-2014, only specify SMKDSTY_A for smoker type.
#' # For CCHS 2015-2018, specify the parameters and SMKDSTY_A for smoker type.
#'
#' library(cchsflow)
#'
#' smoker_type_2009_2010 <- rec_with_table(
#' cchs2009_2010_p, "SMKDSTY_A")
#'
#' head(smoker_type_2009_2010)
#'
#' smoker_type_2017_2018 <- rec_with_table(
#' cchs2017_2018_p,c(
#' "SMK_01A", "SMK_005","SMK_030","SMKDSTY_A"
#' )
#' )
#'
#' tail(smoker_type_2017_2018)
#'
#' combined_smoker_type <- suppressWarnings(merge_rec_data
#' (smoker_type_2009_2010,smoker_type_2017_2018))
#'
#' head(combined_smoker_type)
#' tail(combined_smoker_type)
#'
#' @export
SMKDSTY_fun<-function(SMK_005, SMK_030, SMK_01A){
if_else2(SMK_005 == 1, 1, # Daily smoker
if_else2(SMK_005 == 2 & SMK_030 == 1, 2, # Occasional smoker (former daily)
if_else2(SMK_005 == 2 & (SMK_030 == 2|SMK_030 == "NA(a)"|SMK_030 == "NA(b)"),
3, # Occasional Smoker (never daily)
if_else2(SMK_005 == 3 & SMK_030 == 1 , 4, # Former daily
if_else2(SMK_005 == 3 & SMK_030 == 2 & SMK_01A == 1, 5, # Former occasional
if_else2(SMK_005 == 3 & SMK_01A == 2, 6, # Never smoked
if_else2(SMK_005 == "NA(a)", tagged_na("a"), tagged_na("b"))))))))
}
#' @title Age started to smoke daily - daily smoker
#'
#' @description This function creates a continuous derived variable
#' (SMKG203_cont) for age started to smoke daily for daily smokers.
#'
#' @details For CCHS 2015-2018, age started to smoke daily was combined for daily
#' and former daily smokers.Previous cycles had separate variables for age
#' started to smoke daily. Type of smoker presently is used to define daily
#' smoker.
#'
#' @param SMK_005 type of smoker presently
#'
#' @param SMKG040 age started to smoke daily - daily/former daily smoker
#'
#' @return value for continuous age started to smoke daily for daily smokers
#' in the SMKG203_cont variable
#'
#' @examples
#' # Using SMKG203_fun() to derive age started to smoke daily values across
#' # CCHS cycles.
#' # SMKG203_fun() is specified in variable_details.csv along with the
#' # CCHS variables and cycles included.
#'
#' # To transform SMKG203_A across cycles, use rec_with_table() for each
#' # CCHS cycle and specify SMKG203_A.
#' # For CCHS 2001-2014, only specify SMKG203_A.
#' # For CCHS 2015-2018, specify the parameters and SMKG203_A for daily smoker
#' # age.
#'
#' library(cchsflow)
#'
#' agecigd_2009_2010 <- rec_with_table(
#' cchs2009_2010_p, "SMKG203_A")
#'
#' head(agecigd_2009_2010)
#'
#' agecigd_2017_2018 <- rec_with_table(
#' cchs2017_2018_p,c(
#' "SMK_005","SMKG040","SMKG203_A"
#' )
#' )
#'
#' tail(agecigd_2017_2018)
#'
#' combined_agecigd <- suppressWarnings(merge_rec_data
#' (agecigd_2009_2010,agecigd_2017_2018))
#'
#' head(combined_agecigd)
#' tail(combined_agecigd)
#'
#' @export
SMKG203_fun <- function(SMK_005, SMKG040){
SMKG203 <- if_else2(
SMK_005 == 1, SMKG040,
if_else2(
SMK_005 == "NA(a)"|SMKG040 == "NA(a)", tagged_na("a"), tagged_na("b")))
SMKG203_cont <- if_else2(
SMKG203 == 1, 8,
if_else2(
SMKG203 == 2, 13,
if_else2(
SMKG203 == 3, 16,
if_else2(
SMKG203 == 4, 18.5,
if_else2(
SMKG203 == 5, 22,
if_else2(
SMKG203 == 6, 27,
if_else2(
SMKG203 == 7, 32,
if_else2(
SMKG203 == 8, 37,
if_else2(
SMKG203 == 9, 42,
if_else2(
SMKG203 == 10, 47,
if_else2(
SMKG203 == 11, 55,
if_else2(SMKG203 == "NA(a)",
tagged_na("a"), tagged_na("b")
)
)
)
)
)
)
)
)
)
)
)
)
return(SMKG203_cont)
}
#' @title Age started to smoke daily - former daily smoker
#'
#' @description This function creates a continuous derived variable
#' (SMKG207_cont) for age started to smoke daily for former daily smokers.
#'
#' @details For CCHS 2015-2018, age started to smoke daily was combined for daily
#' and former daily smokers.Previous cycles had separate variables for age
#' started to smoke daily. Smoked daily in lifetime is used to define former
#' daily smoker.
#'
#' @param SMK_030 smoked daily - lifetime (occasional/former smoker)
#'
#' @param SMKG040 age started to smoke daily - daily/former daily smoker
#'
#' @return value for continuous age started to smoke daily for former daily
#' smokers in the SMKG207_cont variable
#'
#' @examples
#' # Using SMKG207_fun() to derive age started to smoke daily values across
#' # CCHS cycles.
#' # SMKG207_fun() is specified in variable_details.csv along with the
#' # CCHS variables and cycles included.
#'
#' # To transform SMKG207_A across cycles, use rec_with_table() for each
#' # CCHS cycle and specify SMKG207_A.
#' # For CCHS 2001-2014, only specify SMKG207_A.
#' # For CCHS 2015-2018, specify the parameters and SMKG207_A for former daily
#' # smoker age.
#'
#' library(cchsflow)
#'
#' agecigfd_2009_2010 <- rec_with_table(
#' cchs2009_2010_p, "SMKG207_A")
#'
#' head(agecigfd_2009_2010)
#'
#' agecigfd_2017_2018 <- rec_with_table(
#' cchs2017_2018_p,c(
#' "SMK_030","SMKG040","SMKG207_A"
#' )
#' )
#'
#' tail(agecigfd_2017_2018)
#'
#' combined_agecigfd <- suppressWarnings(merge_rec_data
#' (agecigfd_2009_2010,agecigfd_2017_2018))
#'
#' head(combined_agecigfd)
#' tail(combined_agecigfd)
#'
#' @export
#' @export
SMKG207_fun <- function(SMK_030, SMKG040){
SMKG207 <- if_else2(
SMK_030 == 1, SMKG040,
if_else2(
SMK_030 == "NA(a)"|SMKG040 == "NA(a)", tagged_na("a"), tagged_na("b")))
SMKG207_cont <- if_else2(
SMKG207 == 1, 8,
if_else2(
SMKG207 == 2, 13,
if_else2(
SMKG207 == 3, 16,
if_else2(
SMKG207 == 4, 18.5,
if_else2(
SMKG207 == 5, 22,
if_else2(
SMKG207 == 6, 27,
if_else2(
SMKG207 == 7, 32,
if_else2(
SMKG207 == 8, 37,
if_else2(
SMKG207 == 9, 42,
if_else2(
SMKG207 == 10, 47,
if_else2(
SMKG207 == 11, 55,
if_else2(SMKG207 == "NA(a)",
tagged_na("a"), tagged_na("b")
)
)
)
)
)
)
)
)
)
)
)
)
return(SMKG207_cont)
}
Big-Life-Lab/cchsflow documentation built on Feb. 23, 2024, 12:04 a.m.
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Defines functions SMKG207_fun SMKG203_fun SMKDSTY_fun pack_years_fun_cat SMKG040_fun pack_years_fun smoke_simple_fun time_quit_smoking_fun
Documented in pack_years_fun pack_years_fun_cat SMKDSTY_fun SMKG040_fun SMKG203_fun SMKG207_fun smoke_simple_fun time_quit_smoking_fun
#' @title Time since quit smoking
#'
#' @description This function creates a derived variable (time_quit_smoking_der)
#' that calculates the approximate time a former smoker has quit smoking based
#' on various CCHS smoking variables. This variable is for CCHS respondents in
#' CCHS surveys 2003-2014.
#'
#' @param SMK_09A_B number of years since quitting smoking. Variable asked to
#' former daily smokers who quit <3 years ago.
#'
#' @param SMKG09C number of years since quitting smoking. Variable asked to
#' former daily smokers who quit >=3 years ago.
#'
#' @return value for time since quit smoking in time_quit_smoking_der.
#'
#' @examples
#' # Using time_quit_smoking_fun() to create pack-years values across CCHS
#' # cycles.
#' # time_quit_smoking_fun() is specified in variable_details.csv along with the
#' # CCHS variables and cycles included.
#'
#' # To transform time_quit_smoking across cycles, use rec_with_table() for each
#' # CCHS cycle and specify time_quit_smoking, along with each smoking variable.
#' # Then by using merge_rec_data(), you can combine time_quit_smoking across
#' # cycles.
#'
#' library(cchsflow)
#'
#' time_quit2009_2010 <- rec_with_table(
#' cchs2009_2010_p, c(
#' "SMK_09A_B", "SMKG09C", "time_quit_smoking"
#' )
#' )
#'
#' head(time_quit2009_2010)
#'
#' time_quit2011_2012 <- rec_with_table(
#' cchs2011_2012_p, c(
#' "SMK_09A_B", "SMKG09C", "time_quit_smoking"
#' )
#' )
#'
#' tail(time_quit2011_2012)
#'
#' combined_time_quit <- suppressWarnings(merge_rec_data(time_quit2009_2010,
#' time_quit2011_2012))
#'
#' head(combined_time_quit)
#' tail(combined_time_quit)
#' @export
time_quit_smoking_fun <- function(SMK_09A_B, SMKG09C) {
SMKG09C_cont <-
if_else2(
SMKG09C == 1, 4,
if_else2(
SMKG09C == 2, 8,
if_else2(SMKG09C == 3, 12,
if_else2(SMKG09C == "NA(a)", tagged_na("a"), tagged_na("b")
)
)
)
)
tsq_ds <-
if_else2(
SMK_09A_B == 1, 0.5,
if_else2(
SMK_09A_B == 2, 1.5,
if_else2(
SMK_09A_B == 3, 2.5,
if_else2(SMK_09A_B == 4, SMKG09C_cont,
if_else2(SMK_09A_B == "NA(a)", tagged_na("a"), tagged_na("b")
)
)
)
)
)
return(tsq_ds)
}
#' @title Simple smoking status
#'
#' @description This function creates a derived smoking variable (smoke_simple)
#' with four categories:
#'
#' \itemize{
#' \item non-smoker (never smoked)
#' \item current smoker (daily and occasional?)
#' \item former daily smoker quit =<5 years or former occasional smoker
#' \item former daily smoker quit >5 years
#' }
#'
#' @param SMKDSTY_cat5 derived variable that classifies an individual's smoking
#' status. This variable captures cycles 2001-2018.
#'
#' @param time_quit_smoking derived variable that calculates the approximate
#' time a former smoker has quit smoking.
#' See \code{\link{time_quit_smoking_fun}} for documentation on how variable
#' was derived.
#'
#' @examples
#' # Using the 'smoke_simple_fun' function to create the derived smoking
#' # variable across CCHS cycles.
#' # smoke_simple_fun() is specified in the variable_details.csv
#'
#' # To create a harmonized smoke_simple variable across CCHS cycles, use
#' # rec_with_table() for each CCHS cycle and specify smoke_simple_fun and
#' # the required base variables. Since time_quit_smoking_der is also a derived
#' # variable, you will have to specify the variables that are derived from it.
#' # Using merge_rec_data(), you can combine smoke_simple across cycles.
#'
#' library(cchsflow)
#'
#' smoke_simple2009_2010 <- rec_with_table(
#' cchs2009_2010_p, c(
#' "SMKDSTY", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "smoke_simple"
#' )
#' )
#'
#' head(smoke_simple2009_2010)
#'
#' smoke_simple2011_2012 <- rec_with_table(
#' cchs2011_2012_p,c(
#' "SMKDSTY", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "smoke_simple"
#' )
#' )
#'
#' tail(smoke_simple2011_2012)
#'
#' combined_smoke_simple <-
#' suppressWarnings(merge_rec_data(smoke_simple2009_2010,smoke_simple2011_2012))
#'
#' head(combined_smoke_simple)
#' tail(combined_smoke_simple)
#' @export
smoke_simple_fun <-
function(SMKDSTY_cat5, time_quit_smoking) {
# Nested function: current smoker status
derive_current_smoker <- function(SMKDSTY_cat5) {
smoker <-
ifelse(SMKDSTY_cat5 %in% c(1, 2), 1,
ifelse(SMKDSTY_cat5 %in% c(3, 4, 5), 0,
ifelse(SMKDSTY_cat5 == "NA(a)", "NA(a)", "NA(b)")))
return(smoker)
}
smoker <- derive_current_smoker(SMKDSTY_cat5)
# Nested function: ever smoker status
derive_ever_smoker <- function(SMKDSTY_cat5) {
eversmoker <-
ifelse(SMKDSTY_cat5 %in% c(1, 2, 3, 4), 1,
ifelse(SMKDSTY_cat5 == 5, 0,
ifelse(SMKDSTY_cat5 == "NA(a)", "NA(a)", "NA(b)")))
return(eversmoker)
}
eversmoker <- derive_ever_smoker(SMKDSTY_cat5)
# smoke_simple 0 = non-smoker
smoke_simple <-
ifelse(smoker == 0 & eversmoker == 0, 0,
# smoke_simple 1 = current smoker
ifelse(smoker == 1 & eversmoker == 1, 1,
# smoke_simple 2 = former daily smoker quit =<5 years or former occasional
# smoker
ifelse(smoker == 0 & eversmoker == 1 & time_quit_smoking <= 5 |
SMKDSTY_cat5 == 4, 2,
# smoke_simple 3 = former daily smoker quit > 5 years
ifelse(smoker == 0 & eversmoker == 1 & time_quit_smoking > 5,
3,
ifelse(smoker == "NA(a)" & eversmoker == "NA(a)" &
time_quit_smoking == "NA(a)", "NA(a)", "NA(b)")))))
return(smoke_simple)
}
#' @title Smoking pack-years
#'
#' @description This function creates a derived variable (pack_years_der) that
#' measures an individual's smoking pack-years based on various CCHS smoking
#' variables. This is a popular variable used by researchers to quantify
#' lifetime exposure to cigarette use.
#'
#' @details pack-years is calculated by multiplying the number of cigarette
#' packs per day (20 cigarettes per pack) by the number of years. Example 1:
#' a respondent who is a current smoker who smokes 1 package of cigarettes for
#' the last 10 years has smoked 10 pack-years. Pack-years is also calculated
#' for former smokers. Example 2: a respondent who started smoking at age
#' 20 years and smoked half a pack of cigarettes until age 40 years smoked for
#' 10 pack-years.
#'
#' @param SMKDSTY_A variable used in CCHS cycles 2001-2014 that classifies an
#' individual's smoking status.
#'
#' @param DHHGAGE_cont continuous age variable.
#'
#' @param time_quit_smoking derived variable that calculates the approximate
#' time a former smoker has quit smoking.
#' See \code{\link{time_quit_smoking_fun}} for documentation on how variable
#' was derived
#'
#' @param SMKG203_cont age started smoking daily. Variable asked to daily
#' smokers.
#'
#' @param SMKG207_cont age started smoking daily. Variable asked to former
#' daily smokers.
#'
#' @param SMK_204 number of cigarettes smoked per day. Variable asked to
#' daily smokers.
#'
#' @param SMK_05B number of cigarettes smoked per day. Variable asked to
#' occasional smokers
#'
#' @param SMK_208 number of cigarettes smoked per day. Variable asked to former
#' daily smokers
#'
#' @param SMK_05C number of days smoked at least one cigarette
#'
#' @param SMK_01A smoked 100 cigarettes in lifetime (y/n)
#'
#' @param SMKG01C_cont age smoked first cigarette
#'
#' @return value for smoking pack-years in the pack_years_der variable
#'
#' @examples
#' # Using pack_years_fun() to create pack-years values across CCHS cycles
#' # pack_years_fun() is specified in variable_details.csv along with the CCHS
#' # variables and cycles included.
#'
#' # To transform pack_years_der across cycles, use rec_with_table() for each
#' # CCHS cycle and specify pack_years_der, along with each smoking variable.
#' # Since time_quit_smoking_der is also a derived
#' # variable, you will have to specify the variables that are derived from it.
#' # Then by using merge_rec_data(), you can combine pack_years_der across
#' # cycles
#'
#' library(cchsflow)
#'
#' pack_years2009_2010 <- rec_with_table(
#' cchs2009_2010_p, c(
#' "SMKDSTY_A", "DHHGAGE_cont", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "SMKG203_cont", "SMKG207_cont", "SMK_204", "SMK_05B", "SMK_208",
#' "SMK_05C", "SMK_01A", "SMKG01C_cont", "pack_years_der"
#' )
#' )
#'
#' head(pack_years2009_2010)
#'
#' pack_years2011_2012 <- rec_with_table(
#' cchs2011_2012_p,c(
#' "SMKDSTY_A", "DHHGAGE_cont", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "SMKG203_cont", "SMKG207_cont", "SMK_204", "SMK_05B", "SMK_208",
#' "SMK_05C", "SMK_01A", "SMKG01C_cont", "pack_years_der"
#' )
#' )
#'
#' tail(pack_years2011_2012)
#'
#' combined_pack_years <- suppressWarnings(merge_rec_data(pack_years2009_2010,
#' pack_years2011_2012))
#'
#' head(combined_pack_years)
#' tail(combined_pack_years)
#' @export
pack_years_fun <-
function(SMKDSTY_A, DHHGAGE_cont, time_quit_smoking, SMKG203_cont,
SMKG207_cont, SMK_204, SMK_05B,
SMK_208, SMK_05C, SMKG01C_cont, SMK_01A) {
# Age verification
if (is.na(DHHGAGE_cont)) {
return(tagged_na("b"))
} else if (DHHGAGE_cont < 0) {
return(tagged_na("b"))
}
# PackYears for Daily Smoker
pack_years <-
if_else2(
SMKDSTY_A == 1, pmax(((DHHGAGE_cont - SMKG203_cont) *
(SMK_204 / 20)), 0.0137),
# PackYears for Occasional Smoker (former daily)
if_else2(
SMKDSTY_A == 2, pmax(((DHHGAGE_cont - SMKG207_cont -
time_quit_smoking) * (SMK_208 / 20)), 0.0137) +
(pmax((SMK_05B * SMK_05C / 30), 1) *time_quit_smoking),
# PackYears for Occasional Smoker (never daily)
if_else2(
SMKDSTY_A == 3, (pmax((SMK_05B * SMK_05C / 30), 1) / 20) *
(DHHGAGE_cont - SMKG01C_cont),
# PackYears for former daily smoker (non-smoker now)
if_else2(
SMKDSTY_A == 4, pmax(((DHHGAGE_cont - SMKG207_cont -
time_quit_smoking) *
(SMK_208 / 20)), 0.0137),
# PackYears for former occasional smoker (non-smoker now) who
# smoked at least 100 cigarettes lifetime
if_else2(
SMKDSTY_A == 5 & SMK_01A == 1, 0.0137,
# PackYears for former occasional smoker (non-smoker now) who
# have not smoked at least 100 cigarettes lifetime
if_else2(
SMKDSTY_A == 5 & SMK_01A == 2, 0.007,
# Non-smoker
if_else2(SMKDSTY_A == 6, 0,
# Account for NA(a)
if_else2(SMKDSTY_A == "NA(a)", tagged_na("a"),
tagged_na("b"))
)
)
)
)
)
)
)
return(pack_years)
}
#' @title Age started smoking daily - daily/former daily smokers
#'
#' @description This function creates a continuous derived variable
#' (SMKG040_fun) that calculates the approximate age that a daily or former
#' daily smoker began smoking daily.
#'
#' @details SMKG203 (daily smoker) and SMKG207 (former daily) are present in
#' CCHS 2001-2014, and are separate variables. For CCHS 2015 and onward, SMKG040
#' (daily/former daily) combines the two previous variables. SMKG040_fun takes
#' the continuous functions (SMKG203_cont and SMKG207_cont) to create SMKG040
#' for 2001-2014.
#'
#' @note In previous cycles, both SMKG203 and SMKG207 included respondents who
#' did not state their smoking status. From CCHS 2015 and onward, SMKG040 only
#' included respondents who specified daily smoker or former daily smoker. As
#' a result, SMKG040 has a large number of missing respondents for CCHS 2015
#' survey cycles and onward.
#'
#' @param SMKG203_cont age started smoking daily. Variable asked to daily
#' smokers.
#'
#' @param SMKG207_cont age started smoking daily. Variable asked to former
#' daily smokers.
#'
#' @return value for age started smoking daily for daily/former daily smokers in
#' the SMKG040_cont variable
#'
#' @examples
#' # Using SMKG040_fun() to create age values across CCHS cycles
#' # SMKG040_fun() is specified in variable_details.csv under SMKG040_cont.
#'
#' # To create a continuous harmonized variable for SMKG040, use rec_with_table()
#' # for each CCHS cycle and specify SMKG040_cont.
#'
#' library(cchsflow)
#'
#' age_smoke_dfd_2009_2010 <- rec_with_table(
#' cchs2009_2010_p, c(
#' "SMKG203_cont", "SMKG207_cont","SMKG040_cont"
#' )
#' )
#'
#' head(age_smoke_dfd_2009_2010)
#'
#' age_smoke_dfd_2011_2012 <- rec_with_table(
#' cchs2011_2012_p,c(
#' "SMKG203_cont", "SMKG207_cont","SMKG040_cont"
#' )
#' )
#'
#' tail(age_smoke_dfd_2011_2012)
#'
#' combined_age_smoke_dfd <- suppressWarnings(merge_rec_data
#' (age_smoke_dfd_2009_2010,age_smoke_dfd_2011_2012))
#'
#' head(combined_age_smoke_dfd)
#' tail(combined_age_smoke_dfd)
#' @export
SMKG040_fun <- function(SMKG203_cont, SMKG207_cont){
SMKG040_cont <-
if_else2((SMKG203_cont == tagged_na("a") & SMKG207_cont == tagged_na("a")),
tagged_na("a"),
if_else2((SMKG203_cont == tagged_na("b") &
SMKG207_cont == tagged_na("b")), tagged_na("b"),
if_else2(!is.na(SMKG203_cont), SMKG203_cont,
if_else2(!is.na(SMKG207_cont), SMKG207_cont,
tagged_na("b")))))
return(SMKG040_cont)
}
#' @title Categorical smoking pack-years
#'
#' @description This function creates a categorical derived variable
#' (pack_years_cat) that categorizes smoking pack-years (pack_years_der).
#'
#' @details pack-years is calculated by multiplying the number of cigarette
#' packs per day (20 cigarettes per pack) by the number of years.The categories
#' were based on the Cardiovascular Disease Population Risk Tool
#' (Douglas Manuel et al. 2018).
#'
#' pack_years_cat uses the derived variable pack_years_der. Pack_years_der uses
#' age and various smoking variables that have been transformed by cchsflow (see
#' documentation on pack_year_der). In order to categorize pack years across CCHS
#' cycles, age and smoking variables must be transformed and harmonized.
#'
#' @param pack_years_der derived variable that calculates smoking pack-years
#' See \code{\link{pack_years_fun}} for documentation on how variable
#' was derived.
#'
#' @return value for pack year categories in the pack_years_cat variable.
#'
#' @examples
#' # Using pack_years_fun_cat() to categorize pack year values across CCHS cycles
#' # pack_years_fun_cat() is specified in variable_details.csv along with the
#' # CCHS variables and cycles included.
#'
#' # To transform pack_years_cat across cycles, use rec_with_table() for each
#' # CCHS cycle and specify pack_years_cat.
#' # Since pack_year_der is also also derived variable, you will have to specify
#' # the variables that are derived from it.
#' # Since time_quit_smoking_der is also a derived variable in pack_year_der,
#' # you will have to specify the variables that are derived from it.
#' # Then by using merge_rec_data(), you can combine pack_years_cat across
#' # cycles.
#'
#' library(cchsflow)
#'
#' pack_years_cat_2009_2010 <- rec_with_table(
#' cchs2009_2010_p, c(
#' "SMKDSTY_A", "DHHGAGE_cont", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "SMKG203_cont", "SMKG207_cont", "SMK_204", "SMK_05B", "SMK_208",
#' "SMK_05C", "SMK_01A", "SMKG01C_cont", "pack_years_der", "pack_years_cat"
#' )
#' )
#'
#' head(pack_years_cat_2009_2010)
#'
#' pack_years_cat_2011_2012 <- rec_with_table(
#' cchs2011_2012_p,c(
#' "SMKDSTY_A", "DHHGAGE_cont", "SMK_09A_B", "SMKG09C", "time_quit_smoking",
#' "SMKG203_cont", "SMKG207_cont", "SMK_204", "SMK_05B", "SMK_208",
#' "SMK_05C", "SMK_01A", "SMKG01C_cont", "pack_years_der", "pack_years_cat"
#' )
#' )
#'
#' tail(pack_years_cat_2011_2012)
#'
#' combined_pack_years_cat <- suppressWarnings(merge_rec_data
#' (pack_years_cat_2009_2010,pack_years_cat_2011_2012))
#'
#' head(combined_pack_years_cat)
#' tail(combined_pack_years_cat)
#' @export
#'
pack_years_fun_cat <- function(pack_years_der){
pack_years_cat <-
if_else2(pack_years_der == 0, 1,
if_else2(pack_years_der > 0 & pack_years_der <= 0.01, 2,
if_else2(pack_years_der > 0.01 & pack_years_der <= 3.0, 3,
if_else2(pack_years_der > 3.0 & pack_years_der <= 9.0, 4,
if_else2(pack_years_der > 9.0 & pack_years_der <= 16.2, 5,
if_else2(pack_years_der > 16.2 & pack_years_der <= 25.7, 6,
if_else2(pack_years_der > 25.7 & pack_years_der <= 40.0, 7,
if_else2(pack_years_der > 40.0, 8,
if_else2(haven::is_tagged_na(pack_years_der, "a"), "NA(a)", "NA(b)")))))))))
return(pack_years_cat)
}
#' @title Type of smokers
#'
#' @description This function creates a derived variable (SMKDSTY_A) for
#' smoker type with 5 categories:
#'
#' \itemize{
#' \item daily smoker
#' \item current occasional smoker (former daily)
#' \item current occasional smoker (never daily)
#' \item current nonsmoker (former daily)
#' \item current nonsmoker (never daily)
#' \item nonsmoker
#' }
#'
#' @details For CCHS 2001-2014, smoker type is derived from smoking more than
#' 100 cigarettes in lifetime, type of smoker at present time, and ever smoked
#' daily. For CCHS 2015-2018, smoker type was derived differently with different
#' variables and categories. A function was created for a consistent smoker
#' status across all cycles.
#'
#' @param SMK_005 type of smoker presently
#'
#' @param SMK_030 smoked daily - lifetime (occasional/former smoker)
#'
#' @param SMK_01A smoked 100 or more cigarettes in lifetime
#'
#' @return value for smoker type in the SMKDSTY_A variable
#'
#' @examples
#' # Using SMKDSTY_fun() to derive smoke type values across CCHS cycles
#' # SMKDSTY_fun() is specified in variable_details.csv along with the
#' # CCHS variables and cycles included.
#'
#' # To transform SMKDSTY_A across cycles, use rec_with_table() for each
#' # CCHS cycle and specify SMKDSTY_A.
#' # For CCHS 2001-2014, only specify SMKDSTY_A for smoker type.
#' # For CCHS 2015-2018, specify the parameters and SMKDSTY_A for smoker type.
#'
#' library(cchsflow)
#'
#' smoker_type_2009_2010 <- rec_with_table(
#' cchs2009_2010_p, "SMKDSTY_A")
#'
#' head(smoker_type_2009_2010)
#'
#' smoker_type_2017_2018 <- rec_with_table(
#' cchs2017_2018_p,c(
#' "SMK_01A", "SMK_005","SMK_030","SMKDSTY_A"
#' )
#' )
#'
#' tail(smoker_type_2017_2018)
#'
#' combined_smoker_type <- suppressWarnings(merge_rec_data
#' (smoker_type_2009_2010,smoker_type_2017_2018))
#'
#' head(combined_smoker_type)
#' tail(combined_smoker_type)
#'
#' @export
SMKDSTY_fun<-function(SMK_005, SMK_030, SMK_01A){
if_else2(SMK_005 == 1, 1, # Daily smoker
if_else2(SMK_005 == 2 & SMK_030 == 1, 2, # Occasional smoker (former daily)
if_else2(SMK_005 == 2 & (SMK_030 == 2|SMK_030 == "NA(a)"|SMK_030 == "NA(b)"),
3, # Occasional Smoker (never daily)
if_else2(SMK_005 == 3 & SMK_030 == 1 , 4, # Former daily
if_else2(SMK_005 == 3 & SMK_030 == 2 & SMK_01A == 1, 5, # Former occasional
if_else2(SMK_005 == 3 & SMK_01A == 2, 6, # Never smoked
if_else2(SMK_005 == "NA(a)", tagged_na("a"), tagged_na("b"))))))))
}
#' @title Age started to smoke daily - daily smoker
#'
#' @description This function creates a continuous derived variable
#' (SMKG203_cont) for age started to smoke daily for daily smokers.
#'
#' @details For CCHS 2015-2018, age started to smoke daily was combined for daily
#' and former daily smokers.Previous cycles had separate variables for age
#' started to smoke daily. Type of smoker presently is used to define daily
#' smoker.
#'
#' @param SMK_005 type of smoker presently
#'
#' @param SMKG040 age started to smoke daily - daily/former daily smoker
#'
#' @return value for continuous age started to smoke daily for daily smokers
#' in the SMKG203_cont variable
#'
#' @examples
#' # Using SMKG203_fun() to derive age started to smoke daily values across
#' # CCHS cycles.
#' # SMKG203_fun() is specified in variable_details.csv along with the
#' # CCHS variables and cycles included.
#'
#' # To transform SMKG203_A across cycles, use rec_with_table() for each
#' # CCHS cycle and specify SMKG203_A.
#' # For CCHS 2001-2014, only specify SMKG203_A.
#' # For CCHS 2015-2018, specify the parameters and SMKG203_A for daily smoker
#' # age.
#'
#' library(cchsflow)
#'
#' agecigd_2009_2010 <- rec_with_table(
#' cchs2009_2010_p, "SMKG203_A")
#'
#' head(agecigd_2009_2010)
#'
#' agecigd_2017_2018 <- rec_with_table(
#' cchs2017_2018_p,c(
#' "SMK_005","SMKG040","SMKG203_A"
#' )
#' )
#'
#' tail(agecigd_2017_2018)
#'
#' combined_agecigd <- suppressWarnings(merge_rec_data
#' (agecigd_2009_2010,agecigd_2017_2018))
#'
#' head(combined_agecigd)
#' tail(combined_agecigd)
#'
#' @export
SMKG203_fun <- function(SMK_005, SMKG040){
SMKG203 <- if_else2(
SMK_005 == 1, SMKG040,
if_else2(
SMK_005 == "NA(a)"|SMKG040 == "NA(a)", tagged_na("a"), tagged_na("b")))
SMKG203_cont <- if_else2(
SMKG203 == 1, 8,
if_else2(
SMKG203 == 2, 13,
if_else2(
SMKG203 == 3, 16,
if_else2(
SMKG203 == 4, 18.5,
if_else2(
SMKG203 == 5, 22,
if_else2(
SMKG203 == 6, 27,
if_else2(
SMKG203 == 7, 32,
if_else2(
SMKG203 == 8, 37,
if_else2(
SMKG203 == 9, 42,
if_else2(
SMKG203 == 10, 47,
if_else2(
SMKG203 == 11, 55,
if_else2(SMKG203 == "NA(a)",
tagged_na("a"), tagged_na("b")
)
)
)
)
)
)
)
)
)
)
)
)
return(SMKG203_cont)
}
#' @title Age started to smoke daily - former daily smoker
#'
#' @description This function creates a continuous derived variable
#' (SMKG207_cont) for age started to smoke daily for former daily smokers.
#'
#' @details For CCHS 2015-2018, age started to smoke daily was combined for daily
#' and former daily smokers.Previous cycles had separate variables for age
#' started to smoke daily. Smoked daily in lifetime is used to define former
#' daily smoker.
#'
#' @param SMK_030 smoked daily - lifetime (occasional/former smoker)
#'
#' @param SMKG040 age started to smoke daily - daily/former daily smoker
#'
#' @return value for continuous age started to smoke daily for former daily
#' smokers in the SMKG207_cont variable
#'
#' @examples
#' # Using SMKG207_fun() to derive age started to smoke daily values across
#' # CCHS cycles.
#' # SMKG207_fun() is specified in variable_details.csv along with the
#' # CCHS variables and cycles included.
#'
#' # To transform SMKG207_A across cycles, use rec_with_table() for each
#' # CCHS cycle and specify SMKG207_A.
#' # For CCHS 2001-2014, only specify SMKG207_A.
#' # For CCHS 2015-2018, specify the parameters and SMKG207_A for former daily
#' # smoker age.
#'
#' library(cchsflow)
#'
#' agecigfd_2009_2010 <- rec_with_table(
#' cchs2009_2010_p, "SMKG207_A")
#'
#' head(agecigfd_2009_2010)
#'
#' agecigfd_2017_2018 <- rec_with_table(
#' cchs2017_2018_p,c(
#' "SMK_030","SMKG040","SMKG207_A"
#' )
#' )
#'
#' tail(agecigfd_2017_2018)
#'
#' combined_agecigfd <- suppressWarnings(merge_rec_data
#' (agecigfd_2009_2010,agecigfd_2017_2018))
#'
#' head(combined_agecigfd)
#' tail(combined_agecigfd)
#'
#' @export
#' @export
SMKG207_fun <- function(SMK_030, SMKG040){
SMKG207 <- if_else2(
SMK_030 == 1, SMKG040,
if_else2(
SMK_030 == "NA(a)"|SMKG040 == "NA(a)", tagged_na("a"), tagged_na("b")))
SMKG207_cont <- if_else2(
SMKG207 == 1, 8,
if_else2(
SMKG207 == 2, 13,
if_else2(
SMKG207 == 3, 16,
if_else2(
SMKG207 == 4, 18.5,
if_else2(
SMKG207 == 5, 22,
if_else2(
SMKG207 == 6, 27,
if_else2(
SMKG207 == 7, 32,
if_else2(
SMKG207 == 8, 37,
if_else2(
SMKG207 == 9, 42,
if_else2(
SMKG207 == 10, 47,
if_else2(
SMKG207 == 11, 55,
if_else2(SMKG207 == "NA(a)",
tagged_na("a"), tagged_na("b")
)
)
)
)
)
)
)
)
)
)
)
)
return(SMKG207_cont)
}
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