/******************************************************************************* * Economic Status and Maternal Health. Analysis of the 2013_14 ZDHS * Mulenga Chonzi Mulenga * * 27/09/2016 *******************************************************************************/ clear all * This is to clear any previous data in the stata memory * Path for the data cd "C:\Users\mulenga\Desktop" set more off * tells stata not to pause for massages * BEGIN log log using preliminary.log, replace * Open a data file use ZMIR61FL_woman.DTA, clear numlabel, add ************************************STEP ONE (1)***************************************** ** last birth in the 2 years prior to the survey gen months_ago = v008 - b3_01 * only keep births born in the last 2 years keep if months_ago <24 *Step Two (2)**** ***Recoding of Depedent Variables****** ***************************************Generating Weights******************************** gen wt= v005/1000000 egen strata=group(v024 v025) svyset [pw=wt], psu(v001) strata(strata) ************************************************************************* *Number of ANC visits recode m14_1 (4/12=1 "4+") (1/3 =0 "<4"), gen(anc4) drop if anc4==98 label var anc4 "had 4 or more ANC visits" ta anc4 *Timing of ANC visits recode m13_1 (1/3=1 "3") (4/10 =0 ">3+"), gen (anc3) drop if anc3==98 label var anc3 "First antenatal within 3 months" tab anc3 *Receipt of Tetanus Taxoid Vaccination recode m1_1 (0=0 "no") (1/5 =1 "yes"), gen (tetanus_taxoid) drop if tetanus_taxoid==8 label var tetanus_taxoid "received tetanus taxoid vaccine" tab tetanus_taxoid *Receipt of Iron drop if h42_1==8 tab h42_1 *Place of delivery recode m15_1 (11/12 96=0 "Home") (21/32=1 "Health Facility"), gen(delivery_place) ta delivery_place ********Independent Variables****** *Wealth Index tab v190 *Region tab v024 *Place of Residence tab v025 *Recoding literacy into two categories* recode v155 (0=0 "not literate") (1/3 =1 "literate"), gen(literacy_1) label var literacy_1 "literacy" drop if v155==4 tab literacy_1 *Recoding mothers age at birth gen age=int((b3_01 - v011)/12) recode age (1/19=1 "<20") (20/34=2 "20-34") (35/49=3 "35+"), gen(age_birth) label var age_birth "Mothers age at birth" tab age_birth *Recoding Marital Status* recode v501 (0=0 "never married") (1/5 =1 "married"), gen (marital_status) label var marital_status "marital status" tab marital_status **Access to media for var v157 v158 v159: recode X .=0 gen media = v157+v158+v159 recode media (0=0 "No access/exposure") (1/9=1 "Access to media/exposed"), gen(media_exposure) ta media_exposure sum v190 v024 v025 literacy_1 age_birth marital_status media_exposure ***********************************BIVARIATE ANALYSIS********************************** //Bivariate analysis of Maternal Health indicators by Wealth quintile tabout anc4 v190 using Table1.xls, c(row ci) stats(chi2) svy nwt(wt) per pop replace tabout v190 anc3 using Table2.xls, c(row ci) stats(chi2) svy nwt(wt) per pop replace tabout v190 tetanus_taxoid using Table3.xls, c(row ci) stats(chi2) svy nwt(wt) per pop replace tabout v190 h42_1 using Table4.xls, c(row ci) stats(chi2) svy nwt(wt) per pop replace tabout v190 delivery_place using Table5.xls, c(row ci) stats(chi2) svy nwt(wt) per pop replace ********************************* LOGISTIC REGRESSION***************************** *********************************TEST FOR MULTICOLLINEARITY****************************************** pwcorr v190 v024 v025 literacy_1 age_birth marital_status media_exposure anc4 pwcorr v190 v024 v025 literacy_1 age_birth marital_status media_exposure anc3 pwcorr v190 v024 v025 literacy_1 age_birth marital_status media_exposure tetanus_taxoid pwcorr v190 v024 v025 literacy_1 age_birth marital_status media_exposure h42_1 pwcorr v190 v024 v025 literacy_1 age_birth marital_status media_exposure delivery_place *********************************BINARY LOGISTIC REGRESSION FOR THE FIVE DEPENDENT VARIABLES***************************** ****MODEL 1 svy: logistic anc4 i.v190 b5.v024 i.v025 i.literacy_1 i.age_birth i.marital_status i.media_exposure if , base outreg2 using Table6.xls, eform stats(coef ci) sideway dec(1) label(insert) alpha(0.001, 0.01, 0.05) replace ****MODEL 2 svy: logistic anc3 i.v190 b5.v024 i.v025 i.literacy_1 i.age_birth i.marital_status i.media_exposure, base outreg2 using Table7.xls, eform stats(coef ci) sideway dec(1) label(insert) alpha(0.001, 0.01, 0.05) replace ****MODEL 3 svy: logistic tetanus_taxoid i.v190 b5.v024 i.v025 i.literacy_1 i.age_birth i.marital_status i.media_exposure, base outreg2 using Table8.xls, eform stats(coef ci) sideway dec(1) label(insert) alpha(0.001, 0.01, 0.05) replace ****MODEL 4 svy: logistic h42_1 i.v190 b5.v024 i.v025 i.literacy_1 i.age_birth i.marital_status i.media_exposure, base outreg2 using Table9.xls, eform stats(coef ci) sideway dec(1) label(insert) alpha(0.001, 0.01, 0.05) replace ****MODEL 5 svy: logistic delivery_place i.v190 b5.v024 i.v025 i.literacy_1 i.age_birth i.marital_status i.media_exposure, base outreg2 using Table10.xls, eform stats(coef ci) sideway dec(1) label(insert) alpha(0.001, 0.01, 0.05) replace *****************************Construct an index for Maternal Health***************************** *************************************Maternal Health******************************************** for var anc4 anc3 tetanus_taxoid h42_1 delivery_place: recode X .=0 gen maternalhealth = anc4+anc3+tetanus_taxoid+h42_1+delivery_place recode maternalhealth (0=0 "Poor maternal health") (1/12=1 "good Maternal health"), gen(maternal_health) ta maternal_health *********************************BINARY LOGISTIC REGRESSION WITH A COMPOSITE DEPENDENT VARIABLE***************************** ****MODEL 6 svy: logistic maternal_health i.v190 b5.v024 i.v025 i.literacy_1 i.age_birth i.marital_status i.media_exposure, base outreg2 using Table11.xls, eform stats(coef ci) sideway dec(1) label(insert) alpha(0.001, 0.01, 0.05) replace log close