Nothing
R/AH_TOBU_M_ASM.R
In surveyPrev: Mapping the Prevalence of Binary Indicators using Survey Data in Small Areas
Defines functions
AH_TOBU_M_ASM
Documented in
AH_TOBU_M_ASM
##'AH_TOBU_M_ASM
#' @param MRdata data.frame from surveyPrev::getDHSdata
#'
#' @return A partially processed data.frame that will be used in surveyPrev::getDHSindicator. The whole function can be used as a parameter in surveyPrev::getDHSindicator
#'
#' @author Miaolei Bao, Yunhan Wu, Qianyu Dong
#' @examples
#' \dontrun{
#' dhsData <- getDHSdata(country = "Zambia", indicator = "AH_TOBU_M_ASM", year = 2018)
#' }
#'
#' @export
AH_TOBU_M_ASM <- function(MRdata){
# ******************************************************************************
# Program: RC_CHAR_MN.R
# Purpose: Code to compute respondent characteristics of men
# Data inputs: MR dataset
# Data outputs: coded variables
# Author: Mahmoud Elkasabi
# Date last modified: April 01 2021 by Mahmoud Elkasabi
# ******************************************************************************
#Please check the note on health insurance. This can be country specific and also reported for specific populations.
#Please check the variables available for smoking and tobacco and see notes for these variables. Variable names have changed and these indicators are country specific.
# -----------------------------------------------------------------------------#
# # Variables created in this file:
# rc_edu "Highest level of schooling attended or completed"
# rc_edu_median "Median years of education"
# rc_litr_cats "Level of literacy"
# rc_litr "Literate - higher than secondary or can read part or whole sentence"
# rc_media_newsp "Reads a newspaper at least once a week"
# rc_media_tv "Watches television at least once a week"
# rc_media_radio "Listens to radio at least once a week"
# rc_media_allthree "Accesses to all three media at least once a week"
# rc_media_none "Accesses none of the three media at least once a week"
# rc_intr_ever "Ever used the internet"
# rc_intr_use12mo "Used the internet in the past 12 months"
# rc_intr_usefreq "Internet use frequency in the past month - among users in the past 12 months"
# rc_empl "Employment status"
# rc_occup "Occupation among those employed in the past 12 months"
# rc_empl_type "Type of employer among those employed in the past 12 months"
# rc_empl_earn "Type of earnings among those employed in the past 12 months"
# rc_empl_cont "Continuity of employment among those employed in the past 12 months"
# rc_hins_ss "Health insurance coverage - social security"
# rc_hins_empl "Health insurance coverage - other employer-based insurance"
# rc_hins_comm "Health insurance coverage - mutual health org. or community-based insurance"
# rc_hins_priv "Health insurance coverage - privately purchased commercial insurance"
# rc_hins_other "Health insurance coverage - other type of insurance"
# rc_hins_any "Have any health insurance"
# rc_tobc_cig "Smokes cigarettes"
# rc_tobc_other "Smokes other type of tobacco"
# rc_tobc_smk_any "Smokes any type of tobacco"
# rc_smk_freq "Smoking frequency"
# rc_cig_day "Average number of cigarettes smoked per day"
# rc_tobc_snuffm "Uses snuff smokeless tobacco by mouth"
# rc_tobc_snuffn "Uses snuff smokeless tobacco by nose"
# rc_tobc_chew "Chews tobacco"
# rc_tobv_betel "Uses betel quid with tobacco"
# rc_tobc_osmkless "Uses other type of smokeless tobacco"
# rc_tobc_anysmkless "Uses any type of smokeless tobacco"
# rc_tobc_any "Uses any type of tobacco - smoke or smokeless"
# -----------------------------------------------------------------------------#
MRdata <- MRdata %>%
mutate(wt = mv005/1000000) %>%
mutate(rc_edu = mv149,
rc_edu = set_label(rc_edu, label = "Highest level of schooling attended or completed")) %>%
mutate(eduyr = case_when(
mv133<=20 ~ mv133,
mv133>20 & mv133<95 ~ 20,
mv133>95 | mv149>7 ~ 99)) %>%
replace_with_na(replace = list(eduyr = c(99)))
MRdata <- MRdata %>%
mutate(rc_litr_cats = case_when(
!mv106 == 3 & mv155 == 2 ~ 1,
!mv106 == 3 & mv155 == 1 ~ 2,
!mv106 == 3 & mv155 == 0 ~ 3,
!mv106 == 3 & mv155 == 3 ~ 4,
!mv106 == 3 & mv155 == 4 ~ 5,
mv106 == 3 ~ 0),
rc_litr_cats = add_labels(rc_litr_cats, labels = c("Higher than secondary education"=0, "Can read a whole sentence"=1,
"Can read part of a sentence"=2, "Cannot read at all"=3,
"No card with required language"=4, "Blind/visually impaired"=5)),
rc_litr_cats = set_label(rc_litr_cats, label = "Level of literacy")) %>%
mutate(rc_litr = case_when(
mv106==3 | mv155==1 | mv155==2 ~ 1, TRUE ~ 0),
rc_litr = add_labels(rc_litr, labels = c("No"=0, "Yes"=1)),
rc_litr = set_label(rc_litr, label = "Literate"))
# Media exposure
MRdata <- MRdata %>%
mutate(rc_media_newsp = case_when(
mv157 == 2 | mv157 == 3 ~ 1,
mv157 == 0 | mv157 == 1 ~ 0),
rc_media_newsp = add_labels(rc_media_newsp, labels = c("No"=0, "Yes"=1)),
rc_media_newsp = set_label(rc_media_newsp, label = "Reads a newspaper at least once a week")) %>%
mutate(rc_media_tv = case_when(
mv159 == 2 | mv159 == 3 ~ 1,
mv159 == 0 | mv159 == 1 ~ 0),
rc_media_tv = add_labels(rc_media_tv, labels = c("No"=0, "Yes"=1)),
rc_media_tv = set_label(rc_media_tv, label = "Watches television at least once a week")) %>%
mutate(rc_media_radio = case_when(
mv158 == 2 | mv158 == 3 ~ 1,
mv158 == 0 | mv158 == 1 ~ 0),
rc_media_radio = add_labels(rc_media_radio, labels = c("No"=0, "Yes"=1)),
rc_media_radio = set_label(rc_media_radio, label = "Listens to radio at least once a week")) %>%
mutate(rc_media_allthree = case_when(
rc_media_newsp == 1 & rc_media_tv == 1 & rc_media_radio == 1 ~ 1, TRUE ~ 0),
rc_media_allthree = add_labels(rc_media_allthree, labels = c("No"=0, "Yes"=1)),
rc_media_allthree = set_label(rc_media_allthree, label = "Accesses to all three media at least once a week")) %>%
mutate(rc_media_none = case_when(
rc_media_newsp == 0 & rc_media_tv == 0 & rc_media_radio == 0 ~ 1,
TRUE ~ 0),
rc_media_none = add_labels(rc_media_none, labels = c("No"=0, "Yes"=1)),
rc_media_none = set_label(rc_media_none, label = "Accesses none of the three media at least once a week"))
if (!is.null(MRdata$mv171a)){
MRdata <- MRdata %>%
mutate(rc_intr_ever = case_when(
mv171a == 1 | mv171a == 2 | mv171a == 3 ~ 1,
mv171a == 0 ~ 0),
rc_intr_ever = add_labels(rc_intr_ever, labels = c("No"=0, "Yes"=1)),
rc_intr_ever = set_label(rc_intr_ever, label = "Ever used the internet")) %>%
mutate(rc_intr_use12mo = case_when(
mv171a == 1 ~ 1,
mv171a == 0 | mv171a == 2 | mv171a == 3 ~ 0),
rc_intr_use12mo = add_labels(rc_intr_use12mo, labels = c("No"=0, "Yes"=1)),
rc_intr_use12mo = set_label(rc_intr_use12mo, label = "Used the internet in the past 12 months")) %>%
mutate(rc_intr_usefreq = case_when(
mv171a == 1 ~ mv171b, TRUE ~ 99)) %>%
replace_with_na(replace = list(rc_intr_usefreq = c(99))) %>%
mutate(rc_intr_usefreq = set_label(rc_intr_usefreq, label = "Internet use frequency in the past month - among users in the past 12 months"))
}
## Employment
MRdata <- MRdata %>%
mutate(rc_empl = case_when(
mv731 == 0 ~ 0,
mv731 == 1 ~ 1,
mv731 == 2 | mv731 == 3 ~ 2,
mv731 == 8 ~ 9),
rc_empl = add_labels(rc_empl, labels = c("Not employed in last 12 months"=0,
"Not curcently working but was employed in last 12 months"=1,
"Curcently employed"=2,
"Don't know/missing"=9)),
rc_empl = set_label(rc_empl, label = "Employment status")) %>%
mutate(emp = case_when(
mv731 == 1 | mv731 == 2 | mv731 == 3 ~ 1,
TRUE ~ 0)) %>%
mutate(rc_occup = case_when(
emp == 1 & mv717 == 1 ~ 1,
emp == 1 & mv717 == 2 ~ 2,
emp == 1 & (mv717 == 3 | mv717 == 7) ~ 3,
emp == 1 & mv717 == 8 ~ 4,
emp == 1 & mv717 == 9 ~ 5,
emp == 1 & mv717 == 6 ~ 6,
emp == 1 & (mv717 == 4 | mv717 == 5) ~ 7,
emp == 1 & (mv717 == 96 | mv717 == 99 | is.na(mv717)) ~ 9 ),
rc_occup = add_labels(rc_occup, labels = c("Professional"=1,
"Clerical"=2,
"Sales and services"=3,
"Skilled manual"=4,
"Unskilled manual"=5,
"Domestic service"=6,
"Agriculture"=7,
"Don't know/missing"=9)),
rc_occup = set_label(rc_occup, label = "Occupation among those employed in the past 12 months")) %>%
mutate(rc_empl_type = case_when(
emp == 1 ~ mv719),
rc_empl_type = set_label(rc_empl_type, label = "Type of employer among those employed in the past 12 months")) %>%
mutate(rc_empl_earn = case_when(
emp == 1 ~ mv741),
rc_empl_earn = set_label(rc_empl_earn, label = "Type of earnings among those employed in the past 12 months")) %>%
mutate(rc_empl_cont = case_when(
emp == 1 ~ mv732),
rc_empl_cont = set_label(rc_empl_cont, label = "Continuity of employment among those employed in the past 12 months")) %>%
mutate(rc_agri = case_when(
rc_occup == 7 ~ 1,
!is.na(rc_occup) & !rc_occup==7 ~ 0),
rc_agri = add_labels(rc_agri, labels = c("Non-Agriculture"=0, "Agriculture"=1)))
## Health insurance
# Note: The different types of health insurance can be country specific. Please check the v481* variables to see which ones you need.
# In addition, some surveys report this for all women/men and some report it among those that have heard of insurance. Please check what the population of interest is for reporting these indicators.
MRdata <- MRdata %>%
mutate(rc_hins_ss = mv481c,
rc_hins_ss = set_label(rc_hins_ss, label = "Health insurance coverage - social security")) %>%
mutate(rc_hins_empl = mv481b,
rc_hins_empl = set_label(rc_hins_empl, label = "Health insurance coverage - other employer-based insurance")) %>%
mutate(rc_hins_comm = mv481a,
rc_hins_comm = set_label(rc_hins_comm, label = "Health insurance coverage - mutual health org. or community-based insurance")) %>%
mutate(rc_hins_priv = mv481d,
rc_hins_priv = set_label(rc_hins_priv, label = "Health insurance coverage - privately purchased commercial insurance")) %>%
mutate(rc_hins_other = case_when(
mv481e == 1 | mv481f == 1 | mv481g == 1 | mv481h == 1 | mv481x == 1 ~ 1,
TRUE ~ 0),
rc_hins_other = set_label(rc_hins_other, label = "Health insurance coverage - other type of insurance")) %>%
mutate(rc_hins_any = case_when(
mv481a == 1 | mv481b == 1 | mv481c == 1 | mv481d == 1 | mv481e == 1 | mv481f == 1 | mv481g == 1 | mv481h == 1 | mv481x == 1 ~ 1,
TRUE ~ 0),
rc_hins_any = set_label(rc_hins_any, label = "Have any health insurance"))
## Tobacco use
# please check all mv463* variables for types of smoking and tobacco use
MRdata <- MRdata %>%
mutate(rc_tobc_cig = case_when(
(mv464a > 0 & mv464a <= 888) | (mv464b > 0 & mv464b <= 888) | (mv464c > 0 & mv464c <= 888) |
(mv484a > 0 & mv484a <= 888) | (mv484b > 0 & mv484b <= 888) | (mv484c > 0 & mv484c <= 888) ~ 1,
TRUE ~ 0),
rc_tobc_cig = add_labels(rc_tobc_cig, labels = c("No"=0, "Yes"=1)),
rc_tobc_cig = set_label(rc_tobc_cig, label = "Smokes cigarettes"))
# for older surveys use mv463a variables
#if (!is.null(MRdata$mv463a)){
#MRdata <- MRdata %>%
# mutate(rc_tobc_cig = case_when(
# mv463a == 1 ~ 1,
# TRUE ~ 0),
# rc_tobc_cig = add_labels(rc_tobc_cig, labels = c("No"=0, "Yes"=1)),
# rc_tobc_cig = set_label(rc_tobc_cig, label = "Smokes cigarettes"))
#}
MRdata <- MRdata %>%
mutate(rc_tobc_other = case_when(
(mv464d > 0 & mv464d <= 888) | (mv464e > 0 & mv464e <= 888) | (mv464f > 0 & mv464f <= 888) | (mv464g > 0 & mv464g <= 888) |
(mv484d > 0 & mv484d <= 888) | (mv484e > 0 & mv484e <= 888) | (mv484f > 0 & mv484f <= 888) | (mv484g > 0 & mv484g <= 888) ~ 1,
TRUE ~ 0),
rc_tobc_other = add_labels(rc_tobc_other, labels = c("No"=0, "Yes"=1)),
rc_tobc_other = set_label(rc_tobc_other, label = "Smokes other type of tobacco"))
# for older surveys use mv463 variables
#if (!is.null(MRdata$mv463b)){
# MRdata <- MRdata %>%
# mutate(rc_tobc_other = case_when(
# mv463b==1 | mv463e==1 | mv463f==1 | mv463g==1 | mv463x==1 ~ 1,
# TRUE ~ 0),
# rc_tobc_other = add_labels(rc_tobc_other, labels = c("No"=0, "Yes"=1)),
# rc_tobc_other = set_label(rc_tobc_other, label = "Smokes other type of tobacco"))
#}
MRdata <- MRdata %>%
mutate(rc_tobc_smk_any = case_when(
(mv464a > 0 & mv464a <= 888) | (mv464b > 0 & mv464b <= 888) | (mv464c > 0 & mv464c <= 888) |
(mv464d > 0 & mv464d <= 888) | (mv464e > 0 & mv464e <= 888) | (mv464f > 0 & mv464f <= 888) | (mv464g > 0 & mv464g <= 888) |
(mv484a > 0 & mv484a <= 888) | (mv484b > 0 & mv484b <= 888) | (mv484c > 0 & mv484c <= 888) |
(mv484d > 0 & mv484d <= 888) | (mv484e > 0 & mv484e <= 888) | (mv484f > 0 & mv484f <= 888) | (mv484g > 0 & mv484g <= 888) ~ 1,
TRUE ~ 0),
rc_tobc_smk_any = add_labels(rc_tobc_smk_any, labels = c("No"=0, "Yes"=1)),
rc_tobc_smk_any = set_label(rc_tobc_smk_any, label = "Smokes any type of tobacco"))
# for older surveys use mv463 variables
# MRdata <- MRdata %>%
# mutate(rc_tobc_smk_any = case_when(
# mv463a==1 | mv463b==1 | mv463e==1 | mv463f==1 | mv463g==1 | mv463x==1 ~ 1,
# TRUE ~ 0),
# rc_tobc_smk_any = add_labels(rc_tobc_smk_any, labels = c("No"=0, "Yes"=1)),
# rc_tobc_smk_any = set_label(rc_tobc_smk_any, label = "Smokes any type of tobacco"))
# Smoking frequency
MRdata <- MRdata %>%
mutate(rc_smk_freq = mv463aa,
rc_smk_freq = add_labels(rc_smk_freq, labels = c("Non-smoker"=0, "Daily smoker"=1, "Occasional smoker"=2)),
rc_smk_freq = set_label(rc_smk_freq, label = "Smoking frequency"))
# Average number of cigarettes per day
MRdata <- MRdata %>%
mutate(ciga = case_when(
(mv464a >= 1 & mv464a < 888) ~ mv464a, TRUE ~ 0)) %>%
mutate(cigb = case_when(
(mv464b >= 1 & mv464b < 888) ~ mv464b, TRUE ~ 0)) %>%
mutate(cigc = case_when(
(mv464c >= 1 & mv464c < 888) ~ mv464c, TRUE ~ 0)) %>%
mutate(cigdaily = ciga + cigb + cigc) %>%
mutate(rc_cig_day = case_when(
(rc_smk_freq==1 ) & (cigdaily >= 1 & cigdaily <= 4) ~ 1,
(rc_smk_freq==1 ) & (cigdaily >= 5 & cigdaily <= 9) ~ 2,
(rc_smk_freq==1 ) & (cigdaily >= 10 & cigdaily <= 14) ~ 3,
(rc_smk_freq==1 ) & (cigdaily >= 15 & cigdaily <= 24) ~ 4,
(rc_smk_freq==1 ) & (cigdaily >= 25 & cigdaily <= 95) ~ 5,
(rc_smk_freq==1 ) & !(cigdaily >= 1 & cigdaily <= 95) ~ 9),
rc_cig_day = add_labels(rc_cig_day, labels = c("<5"=1, "5-9"=2, "10-14"=3, "15-24"=4, "25+"=5, "Don't know/missing"=9)),
rc_cig_day = set_label(rc_cig_day, label = "Average number of cigarettes smoked per day"))
MRdata <- MRdata %>%
mutate(rc_tobc_snuffm = case_when(
(mv464h >= 1 & mv464h < 888) | (mv484h >= 1 & mv484h < 888) ~ 1, TRUE ~ 0),
rc_tobc_snuffm = set_label(rc_tobc_snuffm, label = "Uses snuff smokeless tobacco by mouth"))
MRdata <- MRdata %>%
mutate(rc_tobc_snuffn = case_when(
(mv464i >= 1 & mv464i < 888) | (mv484i >= 1 & mv484i < 888) ~ 1, TRUE ~ 0),
rc_tobc_snuffn = set_label(rc_tobc_snuffn, label = "Uses snuff smokeless tobacco by nose"))
MRdata <- MRdata %>%
mutate(rc_tobc_chew = case_when(
(mv464j >= 1 & mv464j < 888) | (mv484j >= 1 & mv484j < 888) ~ 1, TRUE ~ 0),
rc_tobc_chew = set_label(rc_tobc_chew, label = "Chews tobacco"))
MRdata <- MRdata %>%
mutate(rc_tobv_betel = case_when(
(mv464k >= 1 & mv464k < 888) | (mv484k >= 1 & mv484k < 888) ~ 1, TRUE ~ 0),
rc_tobv_betel = set_label(rc_tobv_betel, label = "Uses betel quid with tobacco"))
MRdata <- MRdata %>%
mutate(rc_tobc_osmkless = case_when(
(mv464l >= 1 & mv464l <= 888) | (mv484l > 1 & mv484l <= 888) ~ 1, TRUE ~ 0),
rc_tobc_osmkless = add_labels(rc_tobc_osmkless, labels = c("No"=0, "Yes"=1)),
rc_tobc_osmkless = set_label(rc_tobc_osmkless, label = "Uses other type of smokeless tobacco"))
MRdata <- MRdata %>%
mutate(rc_tobc_anysmkless = case_when(
(mv464h >= 1 & mv464h <= 888) | (mv484h >= 1 & mv484h <= 888) | (mv464i >= 1 & mv464i <= 888) | (mv484i >= 1 & mv484i <= 888) |
(mv464j >= 1 & mv464j <= 888) | (mv484j >= 1 & mv484j <= 888) | (mv464k >= 1 & mv464k <= 888) | (mv484k >= 1 & mv484k <= 888) |
(mv464l >= 1 & mv464l <= 888) | (mv484l >= 1 & mv484l <= 888) ~ 1,
TRUE ~ 0),
rc_tobc_anysmkless = add_labels(rc_tobc_anysmkless, labels = c("No"=0, "Yes"=1)),
rc_tobc_anysmkless = set_label(rc_tobc_anysmkless, label = "Smokes any type of smokeless tobacco"))
colnames(MRdata)[colnames(MRdata) == 'rc_tobc_anysmkless'] <- 'value'
return(MRdata)
}
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Defines functions AH_TOBU_M_ASM
Documented in AH_TOBU_M_ASM
##'AH_TOBU_M_ASM
#' @param MRdata data.frame from surveyPrev::getDHSdata
#'
#' @return A partially processed data.frame that will be used in surveyPrev::getDHSindicator. The whole function can be used as a parameter in surveyPrev::getDHSindicator
#'
#' @author Miaolei Bao, Yunhan Wu, Qianyu Dong
#' @examples
#' \dontrun{
#' dhsData <- getDHSdata(country = "Zambia", indicator = "AH_TOBU_M_ASM", year = 2018)
#' }
#'
#' @export
AH_TOBU_M_ASM <- function(MRdata){
# ******************************************************************************
# Program: RC_CHAR_MN.R
# Purpose: Code to compute respondent characteristics of men
# Data inputs: MR dataset
# Data outputs: coded variables
# Author: Mahmoud Elkasabi
# Date last modified: April 01 2021 by Mahmoud Elkasabi
# ******************************************************************************
#Please check the note on health insurance. This can be country specific and also reported for specific populations.
#Please check the variables available for smoking and tobacco and see notes for these variables. Variable names have changed and these indicators are country specific.
# -----------------------------------------------------------------------------#
# # Variables created in this file:
# rc_edu "Highest level of schooling attended or completed"
# rc_edu_median "Median years of education"
# rc_litr_cats "Level of literacy"
# rc_litr "Literate - higher than secondary or can read part or whole sentence"
# rc_media_newsp "Reads a newspaper at least once a week"
# rc_media_tv "Watches television at least once a week"
# rc_media_radio "Listens to radio at least once a week"
# rc_media_allthree "Accesses to all three media at least once a week"
# rc_media_none "Accesses none of the three media at least once a week"
# rc_intr_ever "Ever used the internet"
# rc_intr_use12mo "Used the internet in the past 12 months"
# rc_intr_usefreq "Internet use frequency in the past month - among users in the past 12 months"
# rc_empl "Employment status"
# rc_occup "Occupation among those employed in the past 12 months"
# rc_empl_type "Type of employer among those employed in the past 12 months"
# rc_empl_earn "Type of earnings among those employed in the past 12 months"
# rc_empl_cont "Continuity of employment among those employed in the past 12 months"
# rc_hins_ss "Health insurance coverage - social security"
# rc_hins_empl "Health insurance coverage - other employer-based insurance"
# rc_hins_comm "Health insurance coverage - mutual health org. or community-based insurance"
# rc_hins_priv "Health insurance coverage - privately purchased commercial insurance"
# rc_hins_other "Health insurance coverage - other type of insurance"
# rc_hins_any "Have any health insurance"
# rc_tobc_cig "Smokes cigarettes"
# rc_tobc_other "Smokes other type of tobacco"
# rc_tobc_smk_any "Smokes any type of tobacco"
# rc_smk_freq "Smoking frequency"
# rc_cig_day "Average number of cigarettes smoked per day"
# rc_tobc_snuffm "Uses snuff smokeless tobacco by mouth"
# rc_tobc_snuffn "Uses snuff smokeless tobacco by nose"
# rc_tobc_chew "Chews tobacco"
# rc_tobv_betel "Uses betel quid with tobacco"
# rc_tobc_osmkless "Uses other type of smokeless tobacco"
# rc_tobc_anysmkless "Uses any type of smokeless tobacco"
# rc_tobc_any "Uses any type of tobacco - smoke or smokeless"
# -----------------------------------------------------------------------------#
MRdata <- MRdata %>%
mutate(wt = mv005/1000000) %>%
mutate(rc_edu = mv149,
rc_edu = set_label(rc_edu, label = "Highest level of schooling attended or completed")) %>%
mutate(eduyr = case_when(
mv133<=20 ~ mv133,
mv133>20 & mv133<95 ~ 20,
mv133>95 | mv149>7 ~ 99)) %>%
replace_with_na(replace = list(eduyr = c(99)))
MRdata <- MRdata %>%
mutate(rc_litr_cats = case_when(
!mv106 == 3 & mv155 == 2 ~ 1,
!mv106 == 3 & mv155 == 1 ~ 2,
!mv106 == 3 & mv155 == 0 ~ 3,
!mv106 == 3 & mv155 == 3 ~ 4,
!mv106 == 3 & mv155 == 4 ~ 5,
mv106 == 3 ~ 0),
rc_litr_cats = add_labels(rc_litr_cats, labels = c("Higher than secondary education"=0, "Can read a whole sentence"=1,
"Can read part of a sentence"=2, "Cannot read at all"=3,
"No card with required language"=4, "Blind/visually impaired"=5)),
rc_litr_cats = set_label(rc_litr_cats, label = "Level of literacy")) %>%
mutate(rc_litr = case_when(
mv106==3 | mv155==1 | mv155==2 ~ 1, TRUE ~ 0),
rc_litr = add_labels(rc_litr, labels = c("No"=0, "Yes"=1)),
rc_litr = set_label(rc_litr, label = "Literate"))
# Media exposure
MRdata <- MRdata %>%
mutate(rc_media_newsp = case_when(
mv157 == 2 | mv157 == 3 ~ 1,
mv157 == 0 | mv157 == 1 ~ 0),
rc_media_newsp = add_labels(rc_media_newsp, labels = c("No"=0, "Yes"=1)),
rc_media_newsp = set_label(rc_media_newsp, label = "Reads a newspaper at least once a week")) %>%
mutate(rc_media_tv = case_when(
mv159 == 2 | mv159 == 3 ~ 1,
mv159 == 0 | mv159 == 1 ~ 0),
rc_media_tv = add_labels(rc_media_tv, labels = c("No"=0, "Yes"=1)),
rc_media_tv = set_label(rc_media_tv, label = "Watches television at least once a week")) %>%
mutate(rc_media_radio = case_when(
mv158 == 2 | mv158 == 3 ~ 1,
mv158 == 0 | mv158 == 1 ~ 0),
rc_media_radio = add_labels(rc_media_radio, labels = c("No"=0, "Yes"=1)),
rc_media_radio = set_label(rc_media_radio, label = "Listens to radio at least once a week")) %>%
mutate(rc_media_allthree = case_when(
rc_media_newsp == 1 & rc_media_tv == 1 & rc_media_radio == 1 ~ 1, TRUE ~ 0),
rc_media_allthree = add_labels(rc_media_allthree, labels = c("No"=0, "Yes"=1)),
rc_media_allthree = set_label(rc_media_allthree, label = "Accesses to all three media at least once a week")) %>%
mutate(rc_media_none = case_when(
rc_media_newsp == 0 & rc_media_tv == 0 & rc_media_radio == 0 ~ 1,
TRUE ~ 0),
rc_media_none = add_labels(rc_media_none, labels = c("No"=0, "Yes"=1)),
rc_media_none = set_label(rc_media_none, label = "Accesses none of the three media at least once a week"))
if (!is.null(MRdata$mv171a)){
MRdata <- MRdata %>%
mutate(rc_intr_ever = case_when(
mv171a == 1 | mv171a == 2 | mv171a == 3 ~ 1,
mv171a == 0 ~ 0),
rc_intr_ever = add_labels(rc_intr_ever, labels = c("No"=0, "Yes"=1)),
rc_intr_ever = set_label(rc_intr_ever, label = "Ever used the internet")) %>%
mutate(rc_intr_use12mo = case_when(
mv171a == 1 ~ 1,
mv171a == 0 | mv171a == 2 | mv171a == 3 ~ 0),
rc_intr_use12mo = add_labels(rc_intr_use12mo, labels = c("No"=0, "Yes"=1)),
rc_intr_use12mo = set_label(rc_intr_use12mo, label = "Used the internet in the past 12 months")) %>%
mutate(rc_intr_usefreq = case_when(
mv171a == 1 ~ mv171b, TRUE ~ 99)) %>%
replace_with_na(replace = list(rc_intr_usefreq = c(99))) %>%
mutate(rc_intr_usefreq = set_label(rc_intr_usefreq, label = "Internet use frequency in the past month - among users in the past 12 months"))
}
## Employment
MRdata <- MRdata %>%
mutate(rc_empl = case_when(
mv731 == 0 ~ 0,
mv731 == 1 ~ 1,
mv731 == 2 | mv731 == 3 ~ 2,
mv731 == 8 ~ 9),
rc_empl = add_labels(rc_empl, labels = c("Not employed in last 12 months"=0,
"Not curcently working but was employed in last 12 months"=1,
"Curcently employed"=2,
"Don't know/missing"=9)),
rc_empl = set_label(rc_empl, label = "Employment status")) %>%
mutate(emp = case_when(
mv731 == 1 | mv731 == 2 | mv731 == 3 ~ 1,
TRUE ~ 0)) %>%
mutate(rc_occup = case_when(
emp == 1 & mv717 == 1 ~ 1,
emp == 1 & mv717 == 2 ~ 2,
emp == 1 & (mv717 == 3 | mv717 == 7) ~ 3,
emp == 1 & mv717 == 8 ~ 4,
emp == 1 & mv717 == 9 ~ 5,
emp == 1 & mv717 == 6 ~ 6,
emp == 1 & (mv717 == 4 | mv717 == 5) ~ 7,
emp == 1 & (mv717 == 96 | mv717 == 99 | is.na(mv717)) ~ 9 ),
rc_occup = add_labels(rc_occup, labels = c("Professional"=1,
"Clerical"=2,
"Sales and services"=3,
"Skilled manual"=4,
"Unskilled manual"=5,
"Domestic service"=6,
"Agriculture"=7,
"Don't know/missing"=9)),
rc_occup = set_label(rc_occup, label = "Occupation among those employed in the past 12 months")) %>%
mutate(rc_empl_type = case_when(
emp == 1 ~ mv719),
rc_empl_type = set_label(rc_empl_type, label = "Type of employer among those employed in the past 12 months")) %>%
mutate(rc_empl_earn = case_when(
emp == 1 ~ mv741),
rc_empl_earn = set_label(rc_empl_earn, label = "Type of earnings among those employed in the past 12 months")) %>%
mutate(rc_empl_cont = case_when(
emp == 1 ~ mv732),
rc_empl_cont = set_label(rc_empl_cont, label = "Continuity of employment among those employed in the past 12 months")) %>%
mutate(rc_agri = case_when(
rc_occup == 7 ~ 1,
!is.na(rc_occup) & !rc_occup==7 ~ 0),
rc_agri = add_labels(rc_agri, labels = c("Non-Agriculture"=0, "Agriculture"=1)))
## Health insurance
# Note: The different types of health insurance can be country specific. Please check the v481* variables to see which ones you need.
# In addition, some surveys report this for all women/men and some report it among those that have heard of insurance. Please check what the population of interest is for reporting these indicators.
MRdata <- MRdata %>%
mutate(rc_hins_ss = mv481c,
rc_hins_ss = set_label(rc_hins_ss, label = "Health insurance coverage - social security")) %>%
mutate(rc_hins_empl = mv481b,
rc_hins_empl = set_label(rc_hins_empl, label = "Health insurance coverage - other employer-based insurance")) %>%
mutate(rc_hins_comm = mv481a,
rc_hins_comm = set_label(rc_hins_comm, label = "Health insurance coverage - mutual health org. or community-based insurance")) %>%
mutate(rc_hins_priv = mv481d,
rc_hins_priv = set_label(rc_hins_priv, label = "Health insurance coverage - privately purchased commercial insurance")) %>%
mutate(rc_hins_other = case_when(
mv481e == 1 | mv481f == 1 | mv481g == 1 | mv481h == 1 | mv481x == 1 ~ 1,
TRUE ~ 0),
rc_hins_other = set_label(rc_hins_other, label = "Health insurance coverage - other type of insurance")) %>%
mutate(rc_hins_any = case_when(
mv481a == 1 | mv481b == 1 | mv481c == 1 | mv481d == 1 | mv481e == 1 | mv481f == 1 | mv481g == 1 | mv481h == 1 | mv481x == 1 ~ 1,
TRUE ~ 0),
rc_hins_any = set_label(rc_hins_any, label = "Have any health insurance"))
## Tobacco use
# please check all mv463* variables for types of smoking and tobacco use
MRdata <- MRdata %>%
mutate(rc_tobc_cig = case_when(
(mv464a > 0 & mv464a <= 888) | (mv464b > 0 & mv464b <= 888) | (mv464c > 0 & mv464c <= 888) |
(mv484a > 0 & mv484a <= 888) | (mv484b > 0 & mv484b <= 888) | (mv484c > 0 & mv484c <= 888) ~ 1,
TRUE ~ 0),
rc_tobc_cig = add_labels(rc_tobc_cig, labels = c("No"=0, "Yes"=1)),
rc_tobc_cig = set_label(rc_tobc_cig, label = "Smokes cigarettes"))
# for older surveys use mv463a variables
#if (!is.null(MRdata$mv463a)){
#MRdata <- MRdata %>%
# mutate(rc_tobc_cig = case_when(
# mv463a == 1 ~ 1,
# TRUE ~ 0),
# rc_tobc_cig = add_labels(rc_tobc_cig, labels = c("No"=0, "Yes"=1)),
# rc_tobc_cig = set_label(rc_tobc_cig, label = "Smokes cigarettes"))
#}
MRdata <- MRdata %>%
mutate(rc_tobc_other = case_when(
(mv464d > 0 & mv464d <= 888) | (mv464e > 0 & mv464e <= 888) | (mv464f > 0 & mv464f <= 888) | (mv464g > 0 & mv464g <= 888) |
(mv484d > 0 & mv484d <= 888) | (mv484e > 0 & mv484e <= 888) | (mv484f > 0 & mv484f <= 888) | (mv484g > 0 & mv484g <= 888) ~ 1,
TRUE ~ 0),
rc_tobc_other = add_labels(rc_tobc_other, labels = c("No"=0, "Yes"=1)),
rc_tobc_other = set_label(rc_tobc_other, label = "Smokes other type of tobacco"))
# for older surveys use mv463 variables
#if (!is.null(MRdata$mv463b)){
# MRdata <- MRdata %>%
# mutate(rc_tobc_other = case_when(
# mv463b==1 | mv463e==1 | mv463f==1 | mv463g==1 | mv463x==1 ~ 1,
# TRUE ~ 0),
# rc_tobc_other = add_labels(rc_tobc_other, labels = c("No"=0, "Yes"=1)),
# rc_tobc_other = set_label(rc_tobc_other, label = "Smokes other type of tobacco"))
#}
MRdata <- MRdata %>%
mutate(rc_tobc_smk_any = case_when(
(mv464a > 0 & mv464a <= 888) | (mv464b > 0 & mv464b <= 888) | (mv464c > 0 & mv464c <= 888) |
(mv464d > 0 & mv464d <= 888) | (mv464e > 0 & mv464e <= 888) | (mv464f > 0 & mv464f <= 888) | (mv464g > 0 & mv464g <= 888) |
(mv484a > 0 & mv484a <= 888) | (mv484b > 0 & mv484b <= 888) | (mv484c > 0 & mv484c <= 888) |
(mv484d > 0 & mv484d <= 888) | (mv484e > 0 & mv484e <= 888) | (mv484f > 0 & mv484f <= 888) | (mv484g > 0 & mv484g <= 888) ~ 1,
TRUE ~ 0),
rc_tobc_smk_any = add_labels(rc_tobc_smk_any, labels = c("No"=0, "Yes"=1)),
rc_tobc_smk_any = set_label(rc_tobc_smk_any, label = "Smokes any type of tobacco"))
# for older surveys use mv463 variables
# MRdata <- MRdata %>%
# mutate(rc_tobc_smk_any = case_when(
# mv463a==1 | mv463b==1 | mv463e==1 | mv463f==1 | mv463g==1 | mv463x==1 ~ 1,
# TRUE ~ 0),
# rc_tobc_smk_any = add_labels(rc_tobc_smk_any, labels = c("No"=0, "Yes"=1)),
# rc_tobc_smk_any = set_label(rc_tobc_smk_any, label = "Smokes any type of tobacco"))
# Smoking frequency
MRdata <- MRdata %>%
mutate(rc_smk_freq = mv463aa,
rc_smk_freq = add_labels(rc_smk_freq, labels = c("Non-smoker"=0, "Daily smoker"=1, "Occasional smoker"=2)),
rc_smk_freq = set_label(rc_smk_freq, label = "Smoking frequency"))
# Average number of cigarettes per day
MRdata <- MRdata %>%
mutate(ciga = case_when(
(mv464a >= 1 & mv464a < 888) ~ mv464a, TRUE ~ 0)) %>%
mutate(cigb = case_when(
(mv464b >= 1 & mv464b < 888) ~ mv464b, TRUE ~ 0)) %>%
mutate(cigc = case_when(
(mv464c >= 1 & mv464c < 888) ~ mv464c, TRUE ~ 0)) %>%
mutate(cigdaily = ciga + cigb + cigc) %>%
mutate(rc_cig_day = case_when(
(rc_smk_freq==1 ) & (cigdaily >= 1 & cigdaily <= 4) ~ 1,
(rc_smk_freq==1 ) & (cigdaily >= 5 & cigdaily <= 9) ~ 2,
(rc_smk_freq==1 ) & (cigdaily >= 10 & cigdaily <= 14) ~ 3,
(rc_smk_freq==1 ) & (cigdaily >= 15 & cigdaily <= 24) ~ 4,
(rc_smk_freq==1 ) & (cigdaily >= 25 & cigdaily <= 95) ~ 5,
(rc_smk_freq==1 ) & !(cigdaily >= 1 & cigdaily <= 95) ~ 9),
rc_cig_day = add_labels(rc_cig_day, labels = c("<5"=1, "5-9"=2, "10-14"=3, "15-24"=4, "25+"=5, "Don't know/missing"=9)),
rc_cig_day = set_label(rc_cig_day, label = "Average number of cigarettes smoked per day"))
MRdata <- MRdata %>%
mutate(rc_tobc_snuffm = case_when(
(mv464h >= 1 & mv464h < 888) | (mv484h >= 1 & mv484h < 888) ~ 1, TRUE ~ 0),
rc_tobc_snuffm = set_label(rc_tobc_snuffm, label = "Uses snuff smokeless tobacco by mouth"))
MRdata <- MRdata %>%
mutate(rc_tobc_snuffn = case_when(
(mv464i >= 1 & mv464i < 888) | (mv484i >= 1 & mv484i < 888) ~ 1, TRUE ~ 0),
rc_tobc_snuffn = set_label(rc_tobc_snuffn, label = "Uses snuff smokeless tobacco by nose"))
MRdata <- MRdata %>%
mutate(rc_tobc_chew = case_when(
(mv464j >= 1 & mv464j < 888) | (mv484j >= 1 & mv484j < 888) ~ 1, TRUE ~ 0),
rc_tobc_chew = set_label(rc_tobc_chew, label = "Chews tobacco"))
MRdata <- MRdata %>%
mutate(rc_tobv_betel = case_when(
(mv464k >= 1 & mv464k < 888) | (mv484k >= 1 & mv484k < 888) ~ 1, TRUE ~ 0),
rc_tobv_betel = set_label(rc_tobv_betel, label = "Uses betel quid with tobacco"))
MRdata <- MRdata %>%
mutate(rc_tobc_osmkless = case_when(
(mv464l >= 1 & mv464l <= 888) | (mv484l > 1 & mv484l <= 888) ~ 1, TRUE ~ 0),
rc_tobc_osmkless = add_labels(rc_tobc_osmkless, labels = c("No"=0, "Yes"=1)),
rc_tobc_osmkless = set_label(rc_tobc_osmkless, label = "Uses other type of smokeless tobacco"))
MRdata <- MRdata %>%
mutate(rc_tobc_anysmkless = case_when(
(mv464h >= 1 & mv464h <= 888) | (mv484h >= 1 & mv484h <= 888) | (mv464i >= 1 & mv464i <= 888) | (mv484i >= 1 & mv484i <= 888) |
(mv464j >= 1 & mv464j <= 888) | (mv484j >= 1 & mv484j <= 888) | (mv464k >= 1 & mv464k <= 888) | (mv484k >= 1 & mv484k <= 888) |
(mv464l >= 1 & mv464l <= 888) | (mv484l >= 1 & mv484l <= 888) ~ 1,
TRUE ~ 0),
rc_tobc_anysmkless = add_labels(rc_tobc_anysmkless, labels = c("No"=0, "Yes"=1)),
rc_tobc_anysmkless = set_label(rc_tobc_anysmkless, label = "Smokes any type of smokeless tobacco"))
colnames(MRdata)[colnames(MRdata) == 'rc_tobc_anysmkless'] <- 'value'
return(MRdata)
}
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