use "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/pvs_all_countries_v2_9-17-24.dta", clear * Country and region vars tab country_reg, gen(country_reg) rename (country_reg1 country_reg2 country_reg3 country_reg4 country_reg5 /// country_reg6 country_reg7 country_reg8 country_reg9 country_reg10 /// country_reg11 country_reg12 country_reg13 country_reg14 /// country_reg15 country_reg16 country_reg17 country_reg18) /// (Ethiopia Kenya Nigeria South_Africa Peru Colombia Mexico Uruguay /// Argentina Lao_PDR India China Korea Romania Greece Italy United_Kingdom /// United_States) global countries Ethiopia Kenya Nigeria South_Africa Peru Colombia Mexico Uruguay Argentina Lao_PDR India China Korea Romania Greece Italy United_Kingdom United_States recode country_reg (1 2 3 4 = 1 "Africa") (5 6 7 8 9 = 2 "Latin America") /// (10 11 12 13 = 3 "Asia") (14 15 16 17 18 = 4 "Europe and US"), /// gen(region2) * Deriving variables * Mental health recode health_mental (0 1 = 0 "Poor/Fair") (2 3 4 = 1 "Good/Very good/Excellent") (.r = .r "Refused"), /// gen(health_mental_gvge) label(health_mental_gvge) lab var health_mental_gvge "Self-rated mental health - GVGE" recode health_mental (0 1 = 1 "Poor/Fair") (2 3 4 = 0 "Good/Very good/Excellent") (.r = .r "Refused"), /// gen(health_mental_pf) label(health_mental_pf) lab var health_mental_pf "Self-rated mental health - PF" * Public primary care for mental health recode phc_mental (0 1 = 0 "Poor/Fair") (2 3 4 = 1 "Good/Very good/Excellent") ( .d .r = .r "Refused"), /// gen(phc_mental_gvge) recode qual_public (0 1 = 0 "Poor/Fair") (2 3 4 = 1 "Good/Very good/Excellent") (.d .r = .r "Refused"), /// gen(qual_public_gvge) recode qual_private (0 1 = 0 "Poor/Fair") (2 3 4 = 1 "Good/Very good/Excellent") (.d .r = .r "Refused"), /// gen(qual_private_gvge) * Confidence considers opinion recode conf_opinion (0 1 = 0 "Not at all / Not too confident") /// (2 3 = 1 "Somewhat or very confident") (.d .r = .r "Refused"), /// gen(conf_opinion_sv) * Health recode health (0 1 = 0 "Poor/Fair") (2 3 4 = 1 "Good/Very good/Excellent") (.r = .r "Refused"), /// gen(health_gvge) recode health (0 1 = 1 "Poor/Fair") (2 3 4 = 0 "Good/Very good/Excellent") (.r = .r "Refused"), /// gen(health_pf) label(health_pf) lab var health_pf "Self-rated health - GVGE / PF" * Education recode education (0 1 = 0 "None or Primary") (2 3 = 1 "Secondary/Post-secondary") ( .r = .r "Refused"), /// gen(educ) recode education (0 1 2 = 0 "None, Primary or Secondary") (3 = 1 "Post-secondary or higher") ( .r = .r "Refused"), /// gen(educ2) lab var educ2 "Highest level of education completed" * usual_qual recode usual_quality (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// ( 5 .a = .a "I did not receive healthcare form this provider in the past 12 months"), /// gen(usual_quality_vge) label(exc_pr_hlthcare_2) lab var usual_quality_vge "VGE: Overall quality rating of usual source of care (Q22)" * last_qual recode last_qual (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(last_qual_vge) label(exc_pr_2) lab var last_qual_vge "VGE: Last visit rating: overall quality (Q48A)" * last_skills recode last_skills (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(last_skills_vge) label(exc_pr_2) lab var last_skills_vge "VGE: Last visit rating: knowledge and skills of provider" * last_supplies recode last_supplies (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(last_supplies_vge) label(exc_pr_2) lab var last_supplies_vge "VGE: Last visit rating: equipment and supplies provider had available" * last_respect recode last_respect (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(last_respect_vge) label(exc_pr_2) lab var last_respect_vge "VGE: Last visit rating: provider respect" * last_know recode last_know (0 1 2 = 0 "Poor/Fair/Good") (3 4 5= 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(last_know_vge) label(exc_pr_2) lab var last_know_vge "VGE: Last visit rating: knowledge of prior tests and visits" * last_explain recode last_explain (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(last_explain_vge) label(exc_pr_2) lab var last_explain_vge "VGE: Last visit rating: explained things in a way you could understand" * last_decisions recode last_decisions (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(last_decisions_vge) label(exc_pr_2) lab var last_decisions_vge "VGE: Last visit rating: involved you in decisions" * last_visit_rate recode last_visit_rate (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(last_visit_rate_vge) label(exc_pr_2) lab var last_visit_rate_vge "VGE: Last visit rating: amount of time provider spent with you" * last_wait_rate recode last_wait_rate (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(last_wait_rate_vge) label(exc_pr_2) lab var last_wait_rate_vge "VGE: Last visit rating: amount of time you waited before being seen" * last_courtesy recode last_courtesy (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (6 .r = .r "Refused") /// (.a = .a "NA"), /// gen(last_courtesy_vge) label(exc_pr_2) lab var last_courtesy_vge "VGE: Last visit rating: courtesy and helpfulness of the staff" * phc_mental recode phc_mental(0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (5 .r = .r "Refused") /// (.a = .a "NA") (.d = .d "I am unable to judge") (.r = .r "Refused"), /// gen(phc_mental_vge) label(exc_pr_judge_2) lab var phc_mental_vge "VGE: Public primary care system rating for: mental health (Q50D)" * qual_private recode qual_private (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(qual_private_vge) label(exc_pr_2) lab var qual_private_vge "VGE: Overall quality rating of private healthcare system in country (Q55)" * qual_public recode qual_public (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(qual_public_vge) label(exc_pr_2) lab var qual_public_vge "VGE: Overall quality rating of gov or public healthcare system in country (Q54)" * covid_manage recode covid_manage (0 1 2 = 0 "Poor/Fair/Good") (3 4 = 1 "Very good/Excellent") (.r = .r "Refused") /// (.a = .a "NA"), /// gen(covid_manage_vge) label(exc_pr_2) lab var covid_manage_vge "VGE: Rating of the government's management of the COVID-19 pandemic (Q59)" * system outlook recode system_outlook /// (1 2 = 0 "Staying the same/Getting worse") (3 = 1 "Getting better") /// (.r = .r "Refused") , gen(system_outlook_getbet) label(system_outlook2) lab var system_outlook_getbet "Health system getting better (Q57)" * system reform recode system_reform /// (1 2 = 0 "Major changes/Rebuilt") (3 = 1 "Minor changes") /// (.r = .r "Refused") , gen(system_reform_minor) label(system_reform2) lab var system_reform_minor "System works well, only minor changes needed (Q58)" *conf_opinion recode conf_opinion /// (3 2 = 1 "Somewhat confident/Very confident") /// (0 1 = 0 "Not too confident/Not at all confident") /// (.r = .r Refused) (.a = .a na), /// gen(conf_opinion_scvc) label(vc_nc_der) lab var conf_opinion_scvc "SCVC: Confidence that the gov considers public's opinion when making decisions (Q53)" *q12_a recode q12_a /// (3 2 = 1 "Somewhat confident/Very confident") /// (0 1 = 0 "Not too confident/Not at all confident") /// (.r = .r Refused) (.a = .a na), /// gen(pat_act_1) lab var pat_act_1 "Responsible for managing own health - patient activation" *q12_b recode q12_a /// (3 2 = 1 "Somewhat confident/Very confident") /// (0 1 = 0 "Not too confident/Not at all confident") /// (.r = .r Refused) (.a = .a na), /// gen(pat_act_2) lab var pat_act_2 "Can tell a healthcare provider concerns - patient activation" * Telehealth visits gen more_than_one_tele = 1 if visits_tele > 0 & visits_tele < . recode more_than_one_tele (. = 0) if visits_tele == 0 lab def tele 0 "None" 1 "More than one visit" lab val more_than_one_tele tele lab var more_than_one_tele "More than one tele-health visit" * Poor mental health - received care gen poormh_care = 1 if health_mental_pf == 1 & care_mental == 1 recode poormh_care (. = 0) if health_mental_pf == 1 & care_mental == 0 lab var poormh_care "Poor mental health and received care" lab def poormh_care 0 "Poor mental health and did not receive care" 1 "Poor mental health and received care" /// 2 "Good mental health and did not receive care" 3 "Good mental health and received care" lab val poormh_care poormh_care clonevar poormh_care_cat = poormh_care recode poormh_care_cat (. = 2) if health_mental_pf == 0 & care_mental == 0 recode poormh_care_cat (. = 3) if health_mental_pf == 0 & care_mental == 1 * Age categories recode age_cat (1 = 1 "18-29") (2 3 = 2 "30-49") (4 5 6 7 = 3 "50+"), gen(age_cat2) lab var age_cat2 "Age" * Gender recode gender (0 = 0 "Male") (1 2 = 1 "Female or another gender"), gen(gender2) lab var gender2 "Gender" * Some checks tab health_mental [aweight=weight] tab care_mental [aweight=weight] tab phc_mental [aweight=weight] tab gender health_mental_pf [aweight=weight] if country_reg == 1, col tab health_mental_pf [aweight=weight] if country_reg == 1 tab health_mental_pf [aweight=weight] if country_reg == 2 tab health_mental_pf country_reg [aweight=weight], col tab last_visit_rate health_mental_pf [aweight=weight] if country_reg == 1, col tab poormh_care country_reg [aweight=weight], col *import excel "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/GDP_Per_cap_PPP_WB_0428.xls", sheet("gdp") firstrow clear * save "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/gdp_data.dta", replace merge m:1 country_reg using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/gdp_data.dta" * Country ordered by GDP * Recode the country variable based on GDP order recode country (12 = 1 "US") /// United States (17 = 2 "GB") /// United Kingdom (14 = 3 "IT") /// Italy (15 = 4 "KR") /// Republic of Korea (19 = 5 "RO") /// Romania (18 = 6 "GR") /// Greece (10 = 7 "UY") /// Uruguay (16 = 8 "AR") /// Argentina (13 = 9 "MX") /// Mexico (21 = 10 "CN") /// China (2 = 11 "CO") /// Colombia (7 = 12 "PE") /// Peru (9 = 13 "ZA") /// South Africa (4 = 14 "IN") /// India (11 = 15 "LA") /// Lao PDR (5 = 16 "KE") /// Kenya (20 = 17 "NG") /// Nigeria (3 = 18 "ET") /// Ethiopia , generate(country_gdp) * Calculate weighted counts for each category bysort country: egen total_weight = total(weight) bysort country: egen weighted_health_mental_pf = total(weight * health_mental_pf) * Generate weighted percentage gen percent_health_mental_pf = (weighted_health_mental_pf / total_weight) * 100 * Calculate total weighted counts for poormh_care bysort country: egen weighted_poormh_care = total(weight * poormh_care) * Generate weighted percentage for poormh_care gen percent_poormh_care = (weighted_poormh_care / total_weight) * 100 ******************************************************************************** * FIG 1A summtab2 , by(country_gdp) vars(health_mental_pf) /// type(2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_1A) sheetname(data) directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") * For FIG 1A CI's svyset psu_id_for_svy_cmds, weight(weight) svy: tab country_gdp health_mental_pf, row ci * FIG 1B summtab2 , by(country_reg) vars(health_mental_pf care_mental poormh_care poormh_care_cat) /// type(2 2 2 2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_1B_4B) sheetname(data) directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") * FIG 2A foreach c in $countries { preserve keep if `c'==1 summtab2 , by(health_mental_pf) vars(age_cat2) /// type(2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_2A) sheetname(`c') directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") restore } summtab2 , by(health_mental_pf) vars(age_cat2) /// type(2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_2A) sheetname(Total) directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") * FIG 2B foreach c in $countries { preserve keep if `c'==1 summtab2 , by(health_mental_pf) vars(gender2) /// type(2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_2B) sheetname(`c') directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") restore } summtab2 , by(health_mental_pf) vars(gender2) /// type(2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_2B) sheetname(Total) directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") * FIG 3 foreach c in $countries { preserve keep if `c'==1 summtab2 , by(health_mental_pf) vars(health_gvge health_chronic activation) /// type(2 2 2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_3) sheetname(`c') directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") restore } summtab2 , by(health_mental_pf) vars(health_gvge health_chronic activation) /// type(2 2 2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_3) sheetname(total) directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") * FIG 4A data summtab2 , by(country_reg) vars(health_mental_pf care_mental poormh_care_cat) /// type(2 2 2) /// wts(weight) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_4A) sheetname(data) directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") * FIG 5A, FIG 5B foreach c in $countries { preserve keep if `c'==1 summtab2 , by(health_mental_pf) vars(usual_source unmet_need) /// type(2 2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_5A_5B) sheetname(`c') directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") restore } * For significance foreach i in Ethiopia Kenya Nigeria South_Africa Peru Colombia Mexico Uruguay Argentina Lao_PDR India China Korea Romania Greece Italy United_Kingdom United_States { svy: logistic usual_source health_mental_pf if `i' == 1 svy: logistic unmet_need health_mental_pf if `i' == 1 } * FIG 6A foreach c in $countries { preserve keep if `c'==1 summtab2 , by(health_mental_pf) vars(last_qual_vge) /// type(2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_6A) sheetname(`c') directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") restore } * For significance foreach i in Ethiopia Kenya Nigeria South_Africa Peru Colombia Mexico Uruguay Argentina Lao_PDR India China Korea Romania Greece Italy United_Kingdom United_States { svy: logistic last_qual_vge health_mental_pf if `i' == 1 } * FIG 6B foreach c in $countries { preserve keep if `c'==1 summtab2 , by(health_mental_pf) vars(mistake discrim) /// type(2 2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_6B) sheetname(`c') directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") restore } * For significance foreach i in Ethiopia Kenya Nigeria South_Africa Peru Colombia Mexico Uruguay Argentina Lao_PDR India China Korea Romania Greece Italy United_Kingdom United_States { svy: logistic discrim health_mental_pf if `i' == 1 } * Figure 6C foreach c in $countries { preserve keep if `c'==1 summtab2 , by(health_mental_pf) vars(phc_mental_vge) /// type(2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel landscape /// excelname(fig_6C) sheetname(`c') directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") restore } * For significance foreach i in Ethiopia Kenya Nigeria South_Africa Peru Colombia Mexico Uruguay Argentina Lao_PDR India China Korea Romania Greece Italy United_Kingdom United_States { svy: logistic phc_mental_vge health_mental_pf if `i' == 1 } * Fig 7 - forest plots - code below and in R * Fig 8 compiled table foreach country in United_States India China Mexico Kenya United_Kingdom { summtab2 if `country' == 1, by(health_mental_pf) vars(age_cat2 gender2 educ activation health_gvge /// health_chronic care_mental unmet_need usual_source /// last_qual_vge discrim phc_mental_vge conf_sick /// conf_afford conf_getafford system_reform_minor system_outlook_getbet) /// type(2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2) /// wts(weight) wtfreq(off) /// catmisstype(none) /// total replace excel /// excelname(fig_8_table) sheetname("`country'") directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") } * Appendix Table 2 summtab2 , by(country_reg) vars(health_mental_pf care_mental poormh_care poormh_care_cat) /// type(2 2 2 2) /// wts(weight) wtfreq(ceiling) /// catmisstype(none) /// total replace excel landscape /// excelname(app_table2) sheetname(data) directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") * Appendix Table 3 foreach c in $countries { preserve keep if `c'==1 summtab2 , by(health_mental_pf) vars(gender2 age_cat2 health_gvge /// health_chronic activation usual_source unmet_need last_qual_vge /// discrim phc_mental_vge) /// type(2 2 2 2 2 2 2 2 2 2) /// wts(weight) wtfreq(ceiling) /// catmisstype(none) /// total replace excel landscape /// excelname(app_table3) sheetname(`c') directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") restore } summtab2 , by(health_mental_pf) vars(gender2 age_cat2 health_gvge /// health_chronic activation usual_source unmet_need last_qual_vge /// discrim phc_mental_vge) /// type(2 2 2 2 2 2 2 2 2 2) /// wts(weight) wtfreq(ceiling) /// catmisstype(none) /// total replace excel landscape /// excelname(app_table3) sheetname(total) directory("/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis") * Regressions * Survey set without weight * First regression svyset psu_id_for_svy_cmds, strata(mode) recode usual_quality_vge (.a .r = 2) if usual_source == 0 recode usual_quality_vge (0 = 1 "Usual source is poor/fair/good") (2 = 0 "No usual source") (1 = 2 "Usual source is very good/excellent"), gen(usual_qual_cat) clonevar insur_type2 = insur_type recode insur_type2 (2 3 = 0) recode insur_type2 (.a .d .r . = 4) if insured == 0 recode insur_type2 (4 = 0 "None") (0 = 1 "Public") (1 = 2 "Private"), gen(insured_type3) * Check this split * Appendix table - receive care for poor mental health eststo: svy: logistic poormh_care gender2 i.age_cat2 educ2 i.income activation urban i.insured_type3 health_chronic i.usual_qual_cat i.country_reg esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/app_reg2.rtf", /// replace wide b(2) ci(2) compress nobaselevels eform /// rename(gender2 "Gender" 2.age_cat2 "30-49" 3.age_cat2 "50+" /// educ2 "Post-secondary education" 1.income "Middle income" 2.income "High income" /// activation "Activated patient" urban "Urban" 1.insured_type3 "Public" /// 2.insured_type3 "Private" health_chronic "Chronic illness" /// 1.usual_qual_cat "Usual source is poor fair good" /// 2.usual_qual_cat "Usual source is very good exc" /// 2.country_reg "Kenya" 3.country_reg "Nigeria" /// 4.country_reg "South Africa" 5.country_reg "Peru" 6.country_reg "Colombia" /// 7.country_reg "Mexico" 8.country_reg "Uruguay" 9.country_reg "Argentina" 10.country_reg "Lao PDR" /// 11.country_reg "India" 12.country_reg "China" 13.country_reg "Rep of Korea" /// 14.country_reg "Romania" 15.country_reg "Greece" /// 16.country_reg "Italy" 17.country_reg "United Kingdom" /// 18.country_reg "United States") /// mtitles("Received care for poor mental health") /// title("Table 1") eststo clear * Confidence regressions - WIDE foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic conf_getafford health_mental_pf gender2 i.age_cat2 educ2 i.income activation urban i.insured_type3 health_chronic i.usual_qual_cat covid_manage_vge if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_1.rtf", /// replace wide b(2) ci(2) nostar compress nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Confidence in getting and affording good care") eststo clear foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic system_outlook_getbet health_mental_pf gender2 i.age_cat2 educ2 i.income activation urban i.insured_type3 health_chronic i.usual_qual_cat covid_manage_vge if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_2.rtf", /// replace wide b(2) ci(2) nostar compress nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Health system getting better") eststo clear foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic system_reform_minor health_mental_pf gender2 i.age_cat2 educ2 i.income activation urban i.insured_type3 health_chronic i.usual_qual_cat covid_manage_vge if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_3.rtf", /// replace wide b(2) ci(2) nostar compress nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Health system reform minor") eststo clear * Regressions for text / appendix foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic usual_source health_mental_pf if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/app_reg3_1.rtf", /// replace b(2) ci(2) compress nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Usual source") eststo clear foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic unmet_need health_mental_pf if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/app_reg3_2.rtf", /// replace b(2) ci(2) compress nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Unmet need") eststo clear * Confidence regressions foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic conf_getafford health_mental_pf gender2 i.age_cat2 educ2 i.income activation urban i.insured_type3 health_chronic i.usual_qual_cat covid_manage_vge if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_1_v2.rtf", /// replace b(2) ci(2) compress nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Confidence in getting and affording good care") eststo clear foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic system_outlook_getbet health_mental_pf gender2 i.age_cat2 educ2 i.income activation urban i.insured_type3 health_chronic i.usual_qual_cat covid_manage_vge if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_2_v2.rtf", /// replace b(2) ci(2) compress nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Health system getting better") eststo clear foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic system_reform_minor health_mental_pf gender2 i.age_cat2 educ2 i.income activation urban i.insured_type3 health_chronic i.usual_qual_cat covid_manage_vge if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_3_v2.rtf", /// replace b(2) ci(2) compress nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Health system reform minor") eststo clear * Confidence regressions - UNADJUSTED, appendix foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic conf_getafford health_mental_pf if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_1_v3.rtf", /// replace wide b(2) ci(2) compress nostar nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Confidence in getting and affording good care") eststo clear foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic system_outlook_getbet health_mental_pf if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_2_v3.rtf", /// replace wide b(2) ci(2) compress nostar nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Health system getting better") eststo clear foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic system_reform_minor health_mental_pf if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_3_v3.rtf", /// replace wide b(2) ci(2) compress nostar nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Health system reform minor") eststo clear eststo clear * Confidence regressions - UNADJUSTED, table foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic conf_getafford health_mental_pf if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_1_v4.rtf", /// replace wide b(2) ci(2) compress nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Confidence in getting and affording good care") eststo clear foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic system_outlook_getbet health_mental_pf if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_2_v4.rtf", /// replace wide b(2) ci(2) compress nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Health system getting better") eststo clear foreach i in 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 { eststo: svy: logistic system_reform_minor health_mental_pf if country_reg == `i' } esttab using "/Users/neenakapoor/Dropbox (Harvard University)/MH Analysis/conf_reg_3_v4.rtf", /// replace wide b(2) ci(2) compress nobaselevels eform /// mtitles("Ethiopia" "Kenya" "Nigeria" "South Africa" "Peru" "Colombia" /// "Mexico" "Uruguay" "Argentina" "Lao PDR" "India" "China" "Rep of Korea" /// "Romania" "Greece" "Italy" "United Kingdom" "United States") /// title("Health system reform minor") eststo clear * Regressions for text / appendix eststo: svy: logistic health_pf health_mental_pf gender2 i.age_cat2 educ2 i.income activation urban i.insured_type3 health_chronic i.usual_qual_cat i.country_reg eststo: svy: logistic health_pf health_mental_pf eststo: svy: logistic health_chronic health_mental_pf eststo: logistic usual_source health_mental_pf gender2 i.age_cat2 educ2 i.income activation urban i.insured_type3 health_chronic i.country_reg