R/number-conditions.R
multiple_conditions_fun1.RdThis function generates a derived variable (number_conditions) that counts the number of chronic conditions a respondent has. This function takes 5 CCHS-defined conditions (heart disease, cancer, stroke, bowel disorder, and arthritis), and well one derived variable (respiratory condition) to count the number of conditions a respondent has.
multiple_conditions_fun1( CCC_121, CCC_131, CCC_151, CCC_171, resp_condition_der, CCC_051 )
| CCC_121 | variable indicating if respondent has heart disease (1 = respondent has heart disease, 2 = respondent does not have heart disease) |
|---|---|
| CCC_131 | variable indicating if respondent has active cancer (1 = respondent has active cancer, 2 = respondent does not have active cancer) |
| CCC_151 | variable indicating if respondent suffers from the effects of a stroke (1 = respondent suffers from stroke effects, 2 = respondent does not suffer from stroke effects) |
| CCC_171 | variable indicating if respondent has a bowel disorder (1 = respondent has bowel disorder, 2 = respondent does not have a bowel disorder) |
| resp_condition_der | derived variable indicating if respondent has a
respiratory condition (1 = respondent is over the age of 35 and has
a respiratory condition, 2 = respondent is under the age of 35 and has a
respiratory conditions, 3 = respondent does not have a respiratory
condition). See |
| CCC_051 | variable indicating if respondent has arthritis or rheumatism (1 = respondent has arthritis or rheumatism, 2 = respondent does not have arthritis or rheumatism) |
A categorical variable indicating the number of chronic conditions a respondent has. Respondents with 5 or more conditions are grouped in the "5+" category.
mood disorder (CCC_280) was not asked to respondents in the 2001
CCHS survey cycle. This mean respondents in this cycle will only be able to
have a maximum of 6 chronic conditions as opposed to 7 for respondents in
other cycles. multiple_conditions_fun2 is used for CCHS cycles
from 2003 to 2014.
# Using rec_with_table() to generate multiple_conditions in a CCHS # cycle. # multiple_conditions_fun1() is specified in variable_details.csv along with # the CCHS variables and cycles included. # To generate multiple_conditions, use rec_with_table() and specify the # multiple_conditions, along with the variables that are derived from it. # Since resp_condition_der is also a derived variable, you will have to # specify the variables that are derived from it. In this example, data # from the 2001 CCHS will be used, so DHHGAGE_cont, CCC_091, and CCC_91A, # and CCC_031 will be specified along with resp_condition_der. library(cchsflow) conditions_2001 <- suppressWarnings(rec_with_table(cchs2001_p, c("DHHGAGE_cont", "CCC_091", "CCC_91A", "CCC_031", "CCC_121","CCC_131","CCC_151", "CCC_171","CCC_280", "resp_condition_der","CCC_051", "number_conditions")))#> #>#>#> CCC_031 CCC_051 CCC_091 CCC_121 CCC_131 CCC_151 CCC_171 CCC_91A DHHGAGE_cont #> 1 2 2 2 1 2 2 2 2 85 #> 2 2 2 2 2 2 2 2 2 85 #> 3 2 2 2 2 2 2 2 2 32 #> 4 2 2 2 2 2 2 2 2 77 #> 5 2 2 NA(a) 2 2 2 2 2 22 #> 6 2 2 2 2 2 2 2 2 77 #> resp_condition_der number_conditions #> 1 3 1 #> 2 3 0 #> 3 3 0 #> 4 3 0 #> 5 3 0 #> 6 3 0# Generating multiple_conditions with user inputted values # Let's say you are an individual that has heart disease, bowel disorder, # and arthritis. multiple_conditions_fun1() can be used to count the number # of chronic conditions you have library(cchsflow) num_conditions <- multiple_conditions_fun1(CCC_121 = 1, CCC_131 = 2, CCC_151 = 2, CCC_171 = 1, resp_condition_der = 3, CCC_051 = 1) print(num_conditions)#> [1] 3