*FILE NAME: CST 2019 - SES and potential LD *** ABSTRACT INFORMATION * ABSTRACT TITLE: Association between socioeconomic factors and having a potential living kidney donor identified * LIST OF AUTHORS: Noor El-Dassouki, Dmitri Belenko, Sara Macanovic, Vernon Li, Aysha Afzal, Daniel Breitner, Heather Ford, Dr. Istvan Mucsi, Dr. Marta Novak, * CONFERENCE DATE AND LOCATION: CST 2019, Banff, AB *** #################### *** ANALYSIS INFORMATION *** #################### cls clear set more off set trace off use "U:\data\dump\archive\2019-08-20\Data_Sets14\MergedSet-20-Aug-2019.dta" include "U:\data\dump\archive\2019-08-20\Data_Sets14/VariableNamesForAbstracts.do" *** ################## *** PATIENT POPULATION *** ################## * keep all Barriers, ETO patients, and PROMIS-57/CAT/CAT-A/CAT-B patients keep if researchstudy2==1| researchstudy2==3| researchstudy2==8| researchstudy2==9| researchstudy2== 10| researchstudy2== 11| researchstudy2==12 codebook real_enrollment_status keep if real_enrollment_status==3 * remove duplicates bysort partial_sig: gen dup = cond(_N == 1, 0 , _n) if !mi(partial_sig) drop if dup > 1 & !mi(dup) drop dup *remove all patients who have received transplant drop if rrt_simplified ==2 *** ############# *** NEW VARIABLES *** ############# ** NEIGHBOURHOOD SAFETY (exposure 1) ** dichotomous variable (very safe, somewhat safe/not safe) generate neighbourhood_bin = . replace neighbourhood_bin = 1 if neighbourhood_safety==1 replace neighbourhood_bin = 0 if neighbourhood_safety==2 | neighbourhood_safety==3 label variable neighbourhood_bin "Neighbourhood safety - dichotomous variable" label define neighbourhood_bin 1 "Very safe" 0 "Somewhat safe/Not safe" label values neighbourhood_bin neighbourhood_bin ** FINANCIAL STABILITY (exposure 2) ** three category variable (low stability, medium stability, high stability) generate fin_stab_bin = . replace fin_stab_bin = 1 if income_lost==4| income_lost==5 replace fin_stab_bin = 0 if income_lost==2| income_lost==3 label variable fin_stab_bin "Financial stability - low, medium, high" label define fin_stab_bin 1 "High stability" 0 "Low stability" label values fin_stab_bin fin_stab_bin ** ACCESS TO TRANSPORTATION (exposure 3) ** dichotomous variable (yes/no) generate transport_bin = . replace transport_bin = 0 if vehicle==0 replace transport_bin = 1 if vehicle==1 label variable transport_bin "Access to transportation - household vehicle ownership - binary" label define transport_bin 1 "Household vehicle" 0 "No household vehicle" label values transport_bin transport_bin ** SUMMARY SES SCORE (exposure 4) * EMPLOYMENT(three category) generate employment_bin = . replace employment_bin = 1 if employment == 1|employment == 3 |employment ==4 replace employment_bin = 0 if employment == 3| employment == 2 & !mi(employment) label variable employment_bin "Employment status - binary " label define employment_bin 1 "Employed" 0 "Unemployed" label values employment_bin employment_bin *** COMPOSITE SES *total 8 possible responses *generate raw SES score egen ses = rowtotal(income3 education2 employment_bin neighbourhood_bin washer_dryer fin_stab_bin drug_cov transport_bin) *count missing number of variables of each obs./row egen nmis = rowmiss(income3 education2 employment_bin neighbourhood_bin washer_dryer fin_stab_bin drug_cov transport_bin) *drop *replace ses = . if nmis > 4 *standardized ses score using weights gen ses_std = . replace ses_std = ((ses+nmis*1/2)/4)+1 *generate ses categories capture drop SES_cat gen SES_cat = . replace SES_cat = 1 if ses_std <= 1.75 replace SES_cat = 2 if ses_std > 1.75 & ses_std <=2.375 replace SES_cat = 3 if ses_std >=2.375 & !mi(ses_std) label define SES_cat 1 "Low" 2 "Medium" 3 "High" label values SES_cat SES_cat label variable SES_cat "Composite SES summary score - low/med/high" *** ################################# *** VARIABLE DESCRIPTION/DISTRIBUTION *** ################################# * Exposure variable 1: Neighbourhood Safety codebook neighbourhood_bin tab neighbourhood_bin * Exposure variable 2: Financial stability codebook fin_stab_bin tab fin_stab_bin * Exposure variable 3: Access to transportation codebook transport_bin tab transport_bin * Exposure variable 4: Summary SES Score codebook SES_cat tab SES_cat * Outcome variable 3: Potential LD identified codebook Pot_Liv_Donor summarize Pot_Liv_Donor * Potential confounders codebook age sex marital_status2 CharlsComInd_Cat ethnicity_4cat Immigrant_Status dialysis_type days_since_dialaysis_Cat diabetes *** ##################### *** PRELIMINARY ANALYSIS *** ##################### * Table 1: Descriptive Statistics kwallis age, by (SES_cat) tabstat age, statistics (n mean sd) by (SES_cat) tab SES_cat sex, chi2 row column tab SES_cat marital_status2, chi2 row column tab SES_cat ethnicity_4cat, chi2 row column tab SES_cat Immigrant_Status, chi2 row column tab SES_cat education2, chi2 row column tab SES_cat CharlsComInd_Cat, chi2 row column tab SES_cat dialysis_type, chi2 row column tab SES_cat days_since_dialaysis_Cat, chi2 row column tab SES_cat diabetes, chi2 row column * Outcome vs. Exposure (Chi2) tabulate Pot_Liv_Donor neighbourhood_bin, chi2 row column tabulate Pot_Liv_Donor fin_stab_bin, chi2 row column tabulate Pot_Liv_Donor transport_bin, chi2 row column tabulate Pot_Liv_Donor SES_cat, chi2 row column * Outcomes vs. Exposure (graphs) graph bar if neighbourhood_bin == 0, over(Pot_Liv_Donor, relabel (1 "No Potential Donor" 2"Potential Donor")) ascategory asyvars bar(1, fcolor(maroon)) bar(2, fcolor(navy)) over(neighbourhood_bin) ytitle(Percentage of Participants) legend (on) graphregion(fcolor(none) ifcolor(none)) name (House_5) graph bar if neighbourhood_bin == 1, over(Pot_Liv_Donor, relabel (1 "No Potential Donor" 2"Potential Donor")) ascategory asyvars bar(1, fcolor(maroon)) bar(2, fcolor(navy)) over(neighbourhood_bin) ytitle(Percentage of Participants) legend (on) graphregion(fcolor(none) ifcolor(none)) name (House_6) graph combine House_5 House_6, title (Neighbourhood and Household Safety) graph bar if fin_stab_bin == 0, over(Pot_Liv_Donor, relabel (1 "No Potential Donor" 2"Potential Donor")) ascategory asyvars bar(1, fcolor(maroon)) bar(2, fcolor(navy)) over(fin_stab_bin) ytitle(Percentage of Participants) legend (on) graphregion(fcolor(none) ifcolor(none)) name (Finance_1) graph bar if fin_stab_bin == 1, over(Pot_Liv_Donor, relabel (1 "No Potential Donor" 2"Potential Donor")) ascategory asyvars bar(1, fcolor(maroon)) bar(2, fcolor(navy)) over(fin_stab_bin) ytitle(Percentage of Participants) legend (on) graphregion(fcolor(none) ifcolor(none)) name (Finance_2) graph combine Finance_1 Finance_2, title (Financial Stability) graph bar if transport_bin == 0, over(Pot_Liv_Donor, relabel (1 "No Potential Donor" 2"Potential Donor")) ascategory asyvars bar(1, fcolor(maroon)) bar(2, fcolor(navy)) over(transport_bin) ytitle(Percentage of Participants) legend (on) name (Car_1) graph bar if transport_bin == 1, over(Pot_Liv_Donor, relabel (1 "No Potential Donor" 2"Potential Donor")) ascategory asyvars bar(1, fcolor(maroon)) bar(2, fcolor(navy)) over(transport_bin) ytitle(Percentage of Participants) legend (on) name (Car_2) graph combine Car_1 Car_2, title (Household Vehicle Ownership) graph bar if SES_cat == 1, over(Pot_Liv_Donor, relabel (1 "No Potential Donor" 2"Potential Donor")) ascategory asyvars bar(1, fcolor(maroon)) bar(2, fcolor(navy)) over(SES_cat) ytitle(Percentage of Participants) legend (on) graphregion(fcolor(none) ifcolor(none)) name (SES_1) graph bar if SES_cat == 2, over(Pot_Liv_Donor, relabel (1 "No Potential Donor" 2"Potential Donor")) ascategory asyvars bar(1, fcolor(maroon)) bar(2, fcolor(navy)) over(SES_cat) ytitle(Percentage of Participants) legend (on) graphregion(fcolor(none) ifcolor(none)) name (SES_2) graph bar if SES_cat == 3, over(Pot_Liv_Donor, relabel (1 "No Potential Donor" 2"Potential Donor")) ascategory asyvars bar(1, fcolor(maroon)) bar(2, fcolor(navy)) over(SES_cat) ytitle(Percentage of Participants) legend (on) graphregion(fcolor(none) ifcolor(none)) name (SES_3) graph combine SES_1 SES_2 SES_3, title (Overall Socio-Economic Status) *** ################### *** CONTINUING ANALYSIS *** ################### *** LOGISTIC REGRESSION W/O MULTIPLE IMPUTATION ** Potential living donor vs. neighbourhood safety *logistic Pot_Liv_Donor i.neighbourhood_bin *logistic Pot_Liv_Donor i.neighbourhood_bin age i.sex i.marital_status2 *logistic Pot_Liv_Donor i.neighbourhood_bin age i.sex i.marital_status2 i.CharlsComInd_Cat *logistic Pot_Liv_Donor i.neighbourhood_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat *logistic Pot_Liv_Donor i.neighbourhood_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat i.Immigrant_Status ** Potential living donor vs. financial stability *logistic Pot_Liv_Donor i.fin_stab_bin *logistic Pot_Liv_Donor i.fin_stab_bin age i.sex i.marital_status2 *logistic Pot_Liv_Donor i.fin_stab_bin age i.sex i.marital_status2 i.CharlsComInd_Cat *logistic Pot_Liv_Donor i.fin_stab_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat *logistic Pot_Liv_Donor i.fin_stab_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat i.Immigrant_Status ** Potential living donor vs. access to transportation *logistic Pot_Liv_Donor i.transport_bin *logistic Pot_Liv_Donor i.transport_bin age i.sex i.marital_status2 *logistic Pot_Liv_Donor i.transport_bin age i.sex i.marital_status2 i.CharlsComInd_Cat *logistic Pot_Liv_Donor i.transport_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat *logistic Pot_Liv_Donor i.transport_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat i.Immigrant_Status ** Potential living donor vs. SES *logistic Pot_Liv_Donor i.SES_cat *logistic Pot_Liv_Donor i.SES_cat age i.sex i.marital_status2 *logistic Pot_Liv_Donor i.SES_cat age i.sex i.marital_status2 i.CharlsComInd_Cat *logistic Pot_Liv_Donor i.SES_cat age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat *logistic Pot_Liv_Donor i.SES_cat age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat i.Immigrant_Status *** ################### *** MULTIPLE IMPUTATION *** ################### misstable summarize Pot_Liv_Donor neighbourhood_bin fin_stab_bin transport_bin SES_cat age sex marital_status2 CharlsComInd_Cat ethnicity_4cat Immigrant_Status misstable patterns Pot_Liv_Donor neighbourhood_bin fin_stab_bin transport_bin SES_cat age sex marital_status2 CharlsComInd_Cat ethnicity_4cat Immigrant_Status capture mi extract 0, clear mi set wide mi register imputed Pot_Liv_Donor neighbourhood_bin fin_stab_bin transport_bin SES_cat marital_status2 CharlsComInd_Cat ethnicity_4cat Immigrant_Status mi register regular age sex mi impute chained (logit) Pot_Liv_Donor CharlsComInd_Cat Immigrant_Status neighbourhood_bin transport_bin fin_stab_bin (mlogit) SES_cat marital_status2 ethnicity_4cat = age sex, add(5) rseed(33) augment force noisily ** Potential living donor vs. neighbourhood safety mi estimate, or: logistic Pot_Liv_Donor i.neighbourhood_bin mi estimate, or: logistic Pot_Liv_Donor i.neighbourhood_bin age i.sex i.marital_status2 mi estimate, or: logistic Pot_Liv_Donor i.neighbourhood_bin age i.sex i.marital_status2 i.CharlsComInd_Cat mi estimate, or: logistic Pot_Liv_Donor i.neighbourhood_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat mi estimate, or: logistic Pot_Liv_Donor i.neighbourhood_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat i.Immigrant_Status ** Potential living donor vs. financial stability mi estimate, or: logistic Pot_Liv_Donor i.fin_stab_bin mi estimate, or: logistic Pot_Liv_Donor i.fin_stab_bin age i.sex i.marital_status2 mi estimate, or: logistic Pot_Liv_Donor i.fin_stab_bin age i.sex i.marital_status2 i.CharlsComInd_Cat mi estimate, or: logistic Pot_Liv_Donor i.fin_stab_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat mi estimate, or: logistic Pot_Liv_Donor i.fin_stab_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat i.Immigrant_Status ** Potential living donor vs. access to transportation mi estimate, or: logistic Pot_Liv_Donor i.transport_bin mi estimate, or: logistic Pot_Liv_Donor i.transport_bin age i.sex i.marital_status2 mi estimate, or: logistic Pot_Liv_Donor i.transport_bin age i.sex i.marital_status2 i.CharlsComInd_Cat mi estimate, or: logistic Pot_Liv_Donor i.transport_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat mi estimate, or: logistic Pot_Liv_Donor i.transport_bin age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat i.Immigrant_Status ** Potential living donor vs. SES mi estimate, or: logistic Pot_Liv_Donor i.SES_cat mi estimate, or: logistic Pot_Liv_Donor i.SES_cat age i.sex i.marital_status2 mi estimate, or: logistic Pot_Liv_Donor i.SES_cat age i.sex i.marital_status2 i.CharlsComInd_Cat mi estimate, or: logistic Pot_Liv_Donor i.SES_cat age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat mi estimate, or: logistic Pot_Liv_Donor i.SES_cat age i.sex i.marital_status2 i.CharlsComInd_Cat i.ethnicity_4cat i.Immigrant_Status