add more health information to the cleaning

STAPM · Mar 12, 2024 · d27b30c · d27b30c
1 parent 0af2771
commit d27b30c
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Showing 25 changed files with 314 additions and 74 deletions.
diff --git a/R/lfs_clean_health.R b/R/lfs_clean_health.R
@@ -8,53 +8,188 @@ lfs_clean_health <- function(
     data
 ) {
 
+  ################################################
   # Disability (under the Equality Act 2010)
   if ("disea" %in% colnames(data)) {
   data[disea == 1 , disability := "disabled"]
   data[disea == 2 , disability := "not_disabled"]
   } else {
 
-  data[, disability := NULL]
+  data[, disability := NA]
   }
 
-  # Main health problem/disability
+  #############################################################################################
+  # Main health problem/disability (that limits the kind of paid work the respondent can do)
+
+  if ("health" %in% colnames(data)){
+  data[ , main_health_condition := "none"]
+  data[health == 1 , main_health_condition := "msk_arms_hands"]
+  data[health == 2 , main_health_condition := "msk_legs_feet"]
+  data[health == 3 , main_health_condition := "msk_back_neck"]
+  data[health == 4 , main_health_condition := "difficulty_seeing"]
+  data[health == 5 , main_health_condition := "difficulty_hearing"]
+  data[health == 6 , main_health_condition := "speech_impediment"]
+  data[health == 7 , main_health_condition := "skin_conditions_disfigurement"]
+  data[health == 8 , main_health_condition := "respiratory_problems"]
+  data[health == 9 , main_health_condition := "heart_blood_circulatory_problems"]
+  data[health == 10 , main_health_condition := "digestive_problems"]
+  data[health == 11 , main_health_condition := "diabetes"]
+  data[health == 12 , main_health_condition := "depression_anxiety"]
+  data[health == 13 , main_health_condition := "epilepsy"]
+  data[health == 18 , main_health_condition := "autism"]
+  data[health == 14 , main_health_condition := "learning_difficulties"]
+  data[health == 15 , main_health_condition := "mental_illness"]
+  data[health == 16 , main_health_condition := "progressive_illness_nec"]
+  data[health == 17 , main_health_condition := "other_problems"]
+
+
+  ## only applies to those who are working age so set NA if not otherwise
+  ## the "none" category will be incorrect
+  data[(sex == 1 & !(age %in% 16:64)) | (sex == 2 & !(age %in% 16:59)), main_health_condition := NA]
+  } else {
+
+  data[, main_health_condition := NA]
+  }
 
   if ("health" %in% colnames(data)){
-  data[ , health_condition := "none"]
-  data[health == 1 , health_condition := "msk_arms_hands"]
-  data[health == 2 , health_condition := "msk_legs_feet"]
-  data[health == 3 , health_condition := "msk_back_neck"]
-  data[health == 4 , health_condition := "difficulty_seeing"]
-  data[health == 5 , health_condition := "difficulty_hearing"]
-  data[health == 6 , health_condition := "speech_impediment"]
-  data[health == 7 , health_condition := "skin_conditions_disfigurement"]
-  data[health == 8 , health_condition := "respiratory_problems"]
-  data[health == 9 , health_condition := "heart_blood_circulatory_problems"]
-  data[health == 10 , health_condition := "digestive_problems"]
-  data[health == 11 , health_condition := "diabetes"]
-  data[health == 12 , health_condition := "depression_anxiety"]
-  data[health == 13 , health_condition := "epilepsy"]
-  data[health == 18 , health_condition := "autism"]
-  data[health == 14 , health_condition := "learning_difficulties"]
-  data[health == 15 , health_condition := "mental_illness"]
-  data[health == 16 , health_condition := "progressive_illness_nec"]
-  data[health == 17 , health_condition := "other_problems"]
+    data[ , main_health_condition_8cat := "none"]
+    data[health %in% 1:3 , main_health_condition_8cat := "musculoskeletal"]
+    data[health %in% 4:5 , main_health_condition_8cat := "sight_hearing"]
+    data[health %in% 8 , main_health_condition_8cat := "respiratory"]
+    data[health %in% 9:11 , main_health_condition_8cat := "blood_digestive_diabetes"]
+    data[health %in% c(12,15) , main_health_condition_8cat := "mental_health"]
+    data[health %in% c(14,18) , main_health_condition_8cat := "lda"]
+    data[health %in% c(16,17,13,6,7) , main_health_condition_8cat := "other_health_cond"]
+
+    ## only applies to those who are working age so set NA if not otherwise
+    ## the "none" category will be incorrect
+    data[(sex == 1 & !(age %in% 16:64)) | (sex == 2 & !(age %in% 16:59)), main_health_condition_8cat := NA]
   } else {
 
-  data[, health_condition := NULL]
+    data[, main_health_condition_8cat := NA]
   }
 
+  ############################################################################
+  # Dummies for each health condition (in the 8 category specification above)
+
+  if ("health" %in% colnames(data)){
+    data[, musculoskeletal := ifelse(heal01 %in% 1:3 |
+                                     heal02 %in% 1:3 |
+                                     heal03 %in% 1:3 |
+                                     heal04 %in% 1:3 |
+                                     heal05 %in% 1:3 |
+                                     heal06 %in% 1:3 |
+                                     heal07 %in% 1:3 |
+                                     heal08 %in% 1:3 |
+                                     heal09 %in% 1:3 |
+                                     heal10 %in% 1:3, 1, 0)]
+
+    data[, sight_hearing := ifelse(heal01 %in% 4:5 |
+                                   heal02 %in% 4:5 |
+                                   heal03 %in% 4:5 |
+                                   heal04 %in% 4:5 |
+                                   heal05 %in% 4:5 |
+                                   heal06 %in% 4:5 |
+                                   heal07 %in% 4:5 |
+                                   heal08 %in% 4:5 |
+                                   heal09 %in% 4:5 |
+                                   heal10 %in% 4:5, 1, 0)]
+
+    data[, respiratory := ifelse(heal01 %in% 8 |
+                                 heal02 %in% 8 |
+                                 heal03 %in% 8 |
+                                 heal04 %in% 8 |
+                                 heal05 %in% 8 |
+                                 heal06 %in% 8 |
+                                 heal07 %in% 8 |
+                                 heal08 %in% 8 |
+                                 heal09 %in% 8 |
+                                 heal10 %in% 8, 1, 0)]
+
+    data[, blood_digestive_diabetes := ifelse(heal01 %in% 9:11 |
+                                              heal02 %in% 9:11 |
+                                              heal03 %in% 9:11 |
+                                              heal04 %in% 9:11 |
+                                              heal05 %in% 9:11 |
+                                              heal06 %in% 9:11 |
+                                              heal07 %in% 9:11 |
+                                              heal08 %in% 9:11 |
+                                              heal09 %in% 9:11 |
+                                              heal10 %in% 9:11, 1, 0)]
+
+    data[, mental_health := ifelse(heal01 %in% c(12,15) |
+                                   heal02 %in% c(12,15) |
+                                   heal03 %in% c(12,15) |
+                                   heal04 %in% c(12,15) |
+                                   heal05 %in% c(12,15) |
+                                   heal06 %in% c(12,15) |
+                                   heal07 %in% c(12,15) |
+                                   heal08 %in% c(12,15) |
+                                   heal09 %in% c(12,15) |
+                                   heal10 %in% c(12,15), 1, 0)]
+
+    data[, lda := ifelse(heal01 %in% c(14,18) |
+                         heal02 %in% c(14,18) |
+                         heal03 %in% c(14,18) |
+                         heal04 %in% c(14,18) |
+                         heal05 %in% c(14,18) |
+                         heal06 %in% c(14,18) |
+                         heal07 %in% c(14,18) |
+                         heal08 %in% c(14,18) |
+                         heal09 %in% c(14,18) |
+                         heal10 %in% c(14,18), 1, 0)]
+
+
+    data[, other_health_cond := ifelse(heal01 %in% c(16,17,13,6,7) |
+                                       heal02 %in% c(16,17,13,6,7) |
+                                       heal03 %in% c(16,17,13,6,7) |
+                                       heal04 %in% c(16,17,13,6,7) |
+                                       heal05 %in% c(16,17,13,6,7) |
+                                       heal06 %in% c(16,17,13,6,7) |
+                                       heal07 %in% c(16,17,13,6,7) |
+                                       heal08 %in% c(16,17,13,6,7) |
+                                       heal09 %in% c(16,17,13,6,7) |
+                                       heal10 %in% c(16,17,13,6,7), 1, 0)]
+
+    data[(sex == 1 & !(age %in% 16:64)) | (sex == 2 & !(age %in% 16:59)), musculoskeletal := NA]
+    data[(sex == 1 & !(age %in% 16:64)) | (sex == 2 & !(age %in% 16:59)), sight_hearing := NA]
+    data[(sex == 1 & !(age %in% 16:64)) | (sex == 2 & !(age %in% 16:59)), respiratory := NA]
+    data[(sex == 1 & !(age %in% 16:64)) | (sex == 2 & !(age %in% 16:59)), blood_digestive_diabetes := NA]
+    data[(sex == 1 & !(age %in% 16:64)) | (sex == 2 & !(age %in% 16:59)), mental_health := NA]
+    data[(sex == 1 & !(age %in% 16:64)) | (sex == 2 & !(age %in% 16:59)), lda := NA]
+    data[(sex == 1 & !(age %in% 16:64)) | (sex == 2 & !(age %in% 16:59)), other_health_cond := NA]
+
+  } else {
+
+    data[, musculoskeletal := NA]
+    data[, sight_hearing := NA]
+    data[, respiratory := NA]
+    data[, blood_digestive_diabetes := NA]
+    data[, mental_health := NA]
+    data[, lda := NA]
+    data[, other_health_cond := NA]
+
+  }
+
+  ####################################
+  # Main health problem/disability
+
   ### convert the variables to factors
-  data$disability          <- as.factor(data$disability)
-  data$health_condition    <- as.factor(data$health_condition)
+  data$disability                 <- as.factor(data$disability)
+  data$main_health_condition      <- as.factor(data$main_health_condition)
+  data$main_health_condition_8cat <- as.factor(data$main_health_condition_8cat)
 
   ###############################
   ### RETAIN CLEANED VARIABLES
 
   final_data <- data[, c("obs_id",
-                         "disability", "health_condition")]
+                         "disability", "main_health_condition", "main_health_condition_8cat",
+                         "musculoskeletal","sight_hearing","respiratory","blood_digestive_diabetes",
+                         "mental_health","lda","other_health_cond")]
 
-  var_names <- c("disability", "health_condition")
+  var_names <- c("disability", "main_health_condition", "main_health_condition_8cat",
+                 "musculoskeletal","sight_hearing","respiratory","blood_digestive_diabetes",
+                 "mental_health","lda","other_health_cond")
 
   setnames(final_data, var_names, paste0("h_", var_names))
 

diff --git a/R/lfs_read_2000.R b/R/lfs_read_2000.R
@@ -60,11 +60,13 @@ lfs_read_2000 <- function(
     demographic_vars <- Hmisc::Cs(age,sex,govtor,ethcen,marstt,fdpch16)
     education_vars   <- Hmisc::Cs(edage,hiqual,hiquald,btec,sctvec,gnvq,nvqlev,rsa,candg,numal,numas,numol,qgcse,
                                   quals01,quals02,quals03,quals04,quals05,quals06,quals07,quals08,quals09,quals10,quals11,qualch1)
-    health_vars      <- Hmisc::Cs(health,discurr)
+    health_vars      <- Hmisc::Cs(health,discurr,
+                                  heal01,heal02,heal03,heal04,heal05,
+                                  heal06,heal07,heal08,heal09,heal10)
     work_vars        <- Hmisc::Cs(inecacr,grsswk,ftptwk,ttachr,ttushr,mpnor,publicr,indm92m,indd92m,inds92m,socmain,socminm)
     other_vars       <- Hmisc::Cs(refwkm,thiswv)
 
-    names <- c(demographic_vars,education_vars,work_vars, weights_vars,other_vars)
+    names <- c(demographic_vars,education_vars,work_vars,health_vars,weights_vars,other_vars)
     names <- tolower(names)
 
     data <- data[ ,names, with=F]

diff --git a/R/lfs_read_2001.R b/R/lfs_read_2001.R
@@ -60,7 +60,9 @@ lfs_read_2001 <- function(
     demographic_vars <- Hmisc::Cs(age,sex,govtof,fdpch16)
     education_vars   <- Hmisc::Cs(edage,btec,sctvec,gnvq,nvqlev,rsa,candg,numal,numas,numol,gcse,qgcse,
                                   quals01,quals02,quals03,quals04,quals05,quals06,quals07,quals08,quals09,quals10,quals11,qualch1)
-    health_vars      <- Hmisc::Cs(health,discurr)
+    health_vars      <- Hmisc::Cs(health,discurr,
+                                  heal01,heal02,heal03,heal04,heal05,
+                                  heal06,heal07,heal08,heal09,heal10)
     work_vars        <- Hmisc::Cs(inecacr,     ftptwk,ttachr,ttushr,      publicr,indm92m,indd92m,inds92m)
     other_vars       <- Hmisc::Cs(refwkm,thiswv)
 
@@ -103,7 +105,9 @@ lfs_read_2001 <- function(
     demographic_vars <- Hmisc::Cs(age,sex,govtof,eth01,marstt,fdpch16)
     education_vars   <- Hmisc::Cs(edage,btec,sctvec,gnvq,nvqlev,rsa,candg,numal,numas,numol,
                                   quals01,quals02,quals03,quals04,quals05,quals06,quals07,quals08,quals09,quals10,quals11,qualch1)
-    health_vars      <- Hmisc::Cs(health,discurr)
+    health_vars      <- Hmisc::Cs(health,discurr,
+                                  heal01,heal02,heal03,heal04,heal05,
+                                  heal06,heal07,heal08,heal09,heal10)
     work_vars        <- Hmisc::Cs(inecacr,grsswk,ftptwk,ttachr,ttushr,mpnr01,publicr,indm92m,indd92m,inds92m,soc2km,sc2kmmn)
     other_vars       <- Hmisc::Cs(refwkm)
 
@@ -147,10 +151,13 @@ lfs_read_2001 <- function(
     demographic_vars <- Hmisc::Cs(age,sex,govtof,eth01,marstt,fdpch16)
     education_vars   <- Hmisc::Cs(hiqual,hiquald,btec,sctvec,gnvq,nvqlev,rsa,candg,numal,numas,numol,
                                   quals01,quals02,quals03,quals04,quals05,quals06,quals07,quals08,quals09,quals10,quals11,qualch1)
+    health_vars      <- Hmisc::Cs(health,discurr,
+                                  heal01,heal02,heal03,heal04,heal05,
+                                  heal06,heal07,heal08,heal09,heal10)
     work_vars        <- Hmisc::Cs(inecacr,grsswk,ftptwk,ttachr,ttushr,mpnr01,publicr,indm92m,indd92m,inds92m,soc2km,sc2kmmn)
     other_vars       <- Hmisc::Cs(refwkm)
 
-    names <- c(demographic_vars,education_vars,work_vars, weights_vars,other_vars)
+    names <- c(demographic_vars,education_vars,work_vars,health_vars,weights_vars,other_vars)
     names <- tolower(names)
 
     data <- data[ ,names, with=F]

diff --git a/R/lfs_read_2002.R b/R/lfs_read_2002.R
@@ -60,11 +60,13 @@ lfs_read_2002 <- function(
     demographic_vars <- Hmisc::Cs(age,sex,govtof,eth01,marstt,fdpch16)
     education_vars   <- Hmisc::Cs(edage,hiqual,hiquald,btec,sctvec,gnvq,nvqlev,rsa,candg,numal,numas,numol,gcse,qgcse,
                                   quals01,quals02,quals03,quals04,quals05,quals06,quals07,quals08,quals09,quals10,quals11,qualch1)
-    health_vars      <- Hmisc::Cs(health,discurr)
+    health_vars      <- Hmisc::Cs(health,discurr,
+                                  heal01,heal02,heal03,heal04,heal05,
+                                  heal06,heal07,heal08,heal09,heal10)
     work_vars        <- Hmisc::Cs(inecacr,grsswk,ftptwk,ttachr,ttushr,mpnr01,publicr,indm92m,indd92m,inds92m,soc2km,sc2kmmn)
     other_vars       <- Hmisc::Cs(refwkm,thiswv)
 
-    names <- c(demographic_vars,education_vars,work_vars, weights_vars,other_vars)
+    names <- c(demographic_vars,education_vars,work_vars,health_vars,weights_vars,other_vars)
     names <- tolower(names)
 
     data <- data[ ,names, with=F]
@@ -104,12 +106,14 @@ lfs_read_2002 <- function(
     demographic_vars <- Hmisc::Cs(age,sex,govtof,eth01,marstt,fdpch16)
     education_vars   <- Hmisc::Cs(edage,btec,sctvec,gnvq,nvqlev,rsa,candg,numal,numas,numol,
                                   quals01,quals02,quals03,quals04,quals05,quals06,quals07,quals08,quals09,quals10,quals11,qualch1)
-    health_vars      <- Hmisc::Cs(health,discurr)
+    health_vars      <- Hmisc::Cs(health,discurr,
+                                  heal01,heal02,heal03,heal04,heal05,
+                                  heal06,heal07,heal08,heal09,heal10)
     work_vars        <- Hmisc::Cs(inecacr,grsswk,ftptwk,ttachr,ttushr,mpnr02,publicr,indm92m,indd92m,inds92m,soc2km,sc2kmmn,
                                   undemp,undhrs,ovhrs,lespay2)
     other_vars       <- Hmisc::Cs(refwkm)
 
-    names <- c(demographic_vars,education_vars,work_vars, weights_vars,other_vars)
+    names <- c(demographic_vars,education_vars,work_vars,health_vars,weights_vars,other_vars)
     names <- tolower(names)
 
     data <- data[ ,names, with=F]

diff --git a/R/lfs_read_2003.R b/R/lfs_read_2003.R
@@ -60,12 +60,14 @@ lfs_read_2003 <- function(
     demographic_vars <- Hmisc::Cs(age,sex,govtof,eth01,marstt,fdpch16)
     education_vars   <- Hmisc::Cs(edage,hiqual,hiquald,btec,sctvec,gnvq,nvqlev,rsa,candg,numal,numas,numol,gcse,qgcse,
                                   quals01,quals02,quals03,quals04,quals05,quals06,quals07,quals08,quals09,quals10,quals11,qualch1)
-    health_vars      <- Hmisc::Cs(health,discurr)
+    health_vars      <- Hmisc::Cs(health,discurr,
+                                  heal01,heal02,heal03,heal04,heal05,
+                                  heal06,heal07,heal08,heal09,heal10)
     work_vars        <- Hmisc::Cs(inecacr,grsswk,ftptwk,ttachr,ttushr,mpnr02,publicr,indm92m,indd92m,inds92m,soc2km,sc2kmmn,
                                   undemp,undhrs,ovhrs,lespay2)
     other_vars       <- Hmisc::Cs(refwkm,thiswv)
 
-    names <- c(demographic_vars,education_vars,work_vars, weights_vars,other_vars)
+    names <- c(demographic_vars,education_vars,work_vars,health_vars,weights_vars,other_vars)
     names <- tolower(names)
 
     data <- data[ ,names, with=F]

diff --git a/R/lfs_read_2004.R b/R/lfs_read_2004.R
@@ -96,12 +96,14 @@ lfs_read_2004 <- function(
                                   gcseful1,gcseful2,gcseful3,gcseful4,qgcse41,qgcse42,qgcse43,qgcse44,
                                   quals401,quals402,quals403,quals404,quals405,quals406,quals407,quals408,quals409,quals410,quals411,
                                   subcod1,subcod2,subcod3,subcod4,subcod5,subcod6,subcod7,subcod8)
-    health_vars      <- Hmisc::Cs(health,discurr)
+    health_vars      <- Hmisc::Cs(health,discurr,
+                                  heal01,heal02,heal03,heal04,heal05,
+                                  heal06,heal07,heal08,heal09,heal10)
     work_vars        <- Hmisc::Cs(inecacr,grsswk,ftptwk,ttachr,ttushr,mpnr02,publicr,indm92m,indd92m,inds92m,soc2km,sc2kmmn,
                                   undemp,undhrs,ovhrs,lespay2)
     other_vars       <- Hmisc::Cs(refwkm)
 
-    names <- c(demographic_vars,education_vars,work_vars, weights_vars,other_vars)
+    names <- c(demographic_vars,education_vars,work_vars,health_vars,weights_vars,other_vars)
     names <- tolower(names)
 
     data <- data[ ,names, with=F]