Maternal health care in vietnam, demand for antenatal care and choice of delivery care services

HO CHI MINH CITY VIETNAM VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS MATERNAL HEALTH CARE IN VIETNAM: DEMAND FOR ANTENATAL CARE AND CHOICE OF DELIVERY CARE By Nguyen Thi Hoai Trang A Thesis Submitted in Partial Fulfilment of the Requirements for the Degree of Master of Art in Development Economics Academic Supervisor: Dr Truong Dang Thuy HO CHI MINH CITY, June 2016 DECLARATION “This is to certify that this thesis entitled “MATERNAL HEALTH CARE IN VIETNAM: DEMAND FOR ANTENATAL CARE AND CHOICE OF DELIVERY CARE SERVICES”, which is submitted by me in fulfillment of the requirements for the degree of Master of Art in Development Economics to the Vietnam – The Netherlands Programme (VNP) The thesis constitutes only my original work and due supervision and acknowledgement have been made in the text to all materials used th HCMC, June 06 , 2016 Nguyen Thi Hoai Trang i ACKNOWLEDGEMENT I would like to acknowledge my supervisor, Dr Truong Dang Thuy for his great contribution to my thesis Without his support, my thesis would be not possible By his large knowledge and experiences, he gave me the informative comments and enabled me to understand my work better I would like to express my sincere gratitude to his guidance and encouragement, which make me stronger to overcome the challenges and fulfill my work completely By this chance, I would like to express my appreciation toward all lecturers of the Vietnam – Netherlands Program who have provided with valuable economic knowledge during my study in this program Next, I wish to thank to all my friends here at VNP- MDE 19, who share unforgettable memories in studying together Finally, I would like to express my deep gratitude to my family for their support and endurance when I pursue my postgraduate studies ii ABSTRACT This thesis research aims to analyze the impact of individual characteristics, household characteristic and communities in utilization of maternal health care services in Vietnam Using the latest data of Vietnam’s Multiple Indicator Cluster Survey 2013-2014, it employs the Negative Nominal Model for demand of prenatal care visits and Multinomial Logistic Model for the choice of delivery facility With respect to the demand of prenatal care visits, the result shows that higher education, higher age, exposure to mass media and no religion increase the number of prenatal care visits while higher birth order, unmarried or separated status, ethnicity group and lower household wealth index decrease the number of prenatal care Moreover, living in rural, disadvantaged areas and the community with higher illiteracy rate decrease the demand of prenatal care visits while living in the community with higher proportion of women giving birth at health facilities increase the demand Concerning the choice of delivery facility, more prenatal care visits and exposure to mass media are positively associated with the choice of giving birth at public hospital In contrast, suffering the burden of taking care more children, lower household wealth index, living in rural and the community with higher illiteracy ratio adversely affect the choice of public hospital delivery The results suggest the improvement of maternal health program in rural and underdeveloped areas as well as universal education over the country, especially for the ethnic minority group Keywords: prenatal care visits, the place of childbirth, individual characteristics, household characteristics, community characteristics, Vietnam iii Contents DECLARATION ACKNOWLEDGEMENT ABSTRACT LIST of TABLES and FIGURES ABBREVIATION CHAPTER I INTRODUCTION 1.1Problem statement 1.2Research objectives 1.3Research questions 1.4Structure CHAPTER II LITERATURE REVIEW 2.1The role of maternity health care 2.2 Overview of maternal health and health care in Vietnam 2.2.1The culture 2.2.2The two-child policy 2.2.3Maternal mortality ratio and materna 2.3The demand for health care 2.3.1Theoretical background 2.3.2Empirical Literature Review 2.4The choice of health care provider 2.4.1Theoretical background: iv 2.4.2Empirical literature review CHAPTER III METHODOLOGY AND DATA DESCRIPTION 3.1Conceptual framework 3.2Empirical framework 3.2.1Demand for Prenatal care 3.2.2Choice of birth delivery facility 3.3Data 3.4Variables definition 3.4.1Dependent variables 3.4.2Independent variables RESULTS AND DISCUSSIONS 4.1Descriptive Results 4.2Analysis of Demand for prenatal care 4.2.1Bivariate analysis 4.2.2Analysis of Negative Binomial Model 4.3Analysis of Choice in the delivery care providers 4.3.1Bivariate analysis 4.3.2Analysis of Multinomial Logistic Mod CHAPTER V CONCLUSION, RECOMMENDATION and LIMITATION 5.1Main findings 5.2Policy Recommendation 5.3Limitation and Further Research v REFERENCE 51 APPENDIX 56 STATA RESULTS 71 vi LIST of TABLES and FIGURES List of Tables Table 1: Description of Variables 30 Table 2:Descriptive Results – Numeric Variables .33 Table : Descriptive Results - Dummy Variables .33 Table 4: Bivariate analysis in the demand of prenatal care visits 35 Table 5: Negative binomial regression for the demand of prenatal care visits 40 Table : Bivariate analysis in the choice of delivery care providers - numeric independent variables .41 Table 7:Bivariate analysis in the choice of delivery care provider – dummy independent variables 43 Table 8: Multinomial Logistic Regression for the choice of delivery care provider 46 Table 9: Marginal effects for the choice of delivery care provider 47 List of Figures Figure 1: MMR in Vietnam in the period of 2000 – 2015 .8 Figure 2: MMR of the Asian countries in the period of 2000 – 2015 Figure 3: Percentage of women having at least visit and at least visits during pregnancy .9 Figure 4: The percentage of the women taking antenatal care visits by residence in 2011 and 2014 10 Figure 5: The percentage of the women taking antenatal care visits by ethnicity in 2011 and 2014 10 Figure The association between individual level, household level and community level characteristics with the utilization of maternal health care services 25 Figure 7: The association between the demand of maternal care visits and numerical independent variables .37 vii ANC CSDH GSO IMR MDGs MICS MMR WHO viii CHAPTER I INTRODUCTION 1.1 Problem statement There is a growing concern about the maternal health care globally, especially in low income countries World Health Organization (WHO 2014) reported that the global maternal mortality ratio (MMR) in 2013 was 210 maternal deaths per 100 000 live births, decreasing from 380 maternal deaths per 100 000 live births in 1990 However, the ratio in developing regions was 14 times higher than in developed regions Even though maternal death is generally decreasing worldwide, it has yet to achieve the target of Millennium Development Goal by reducing the MMR by three quarters between 1990 and 2015 (WHO 2014) The maternal death has direct causes and indirect causes The direct cause results from arising complications during pregnancy, delivery and postpartum, or improper treatment such as hemorrhage, infection, obstructed labor, unsafe abortion, ectopic pregnancy and anesthesia-related deaths while the indirect cause results from the disease which previously exists or be not due to indirect obstetric causes like hepatitis anemia, malaria, heart disease and tetanus (WHO 2005) It was reported that direct causes made up the higher number of maternal death than indirect causes with 80% of the total MMR (WHO 2005) These complications could be preventable thanks to the intervention of health care such as antenatal care and delivery care, which was introduced by WHO in the safe motherhood package in 1994 (Tran 2012) Antenatal cares provide the opportunities to pregnancy women and their family to be informed of their health and the growth status of unborn baby Low birth weights could be prevented if the pregnant women are well acknowledged about their unborn baby’s weight and height during the antenatal care and then improve their diet In addition, antenatal check-ups detect the danger signs and risks of pregnancy and delivery and make timely interventions For example, tetanus immunization in the antenatal care period is vital to save the life of the women and their baby The management of high blood pressure during pregnancy ensures the maternal health and increase the infant survival (WHO and UNICEF 2003) Furthermore, delivery care also plays an important role in reducing maternal deaths WHO recommended the child birth at health facility or attended by skilled health staffs to ensure to the safe delivery and give birth to healthy baby With good hygiene and adequate medical equipment, the delivery at facility could decrease the complications arising from the Appendix 4: The association between the demand of maternal care visits and independent variables NOEDU = NOEDU = PRIMARY =0 PRIMARY =1 LOWSECOND = LOWSECOND = UPSECOND = UPSECOND = TERTIARY = TERTIARY = MARITAL = MARITAL = UNWANTED = UNWANTED = WORKING = WORKING = MOBIPHONE = MOBIPHONE = NEWSPAPER = NEWSPAPER = RADIO = RADIO = 66 Appendix 4: The association between the demand of maternal care visits and independent variables (continued) TV=0 TV=1 POOR = POOR = ETHNIC = ETHNIC = NORELI=0 NORELI=1 RURAL = RURAL = RRD=0 RRD=1 NM=0 NM=1 NC=0 NC=1 CH=0 CH=1 SE=0 SE=1 MD=0 MD=1 67 Appendix 5: The association between the demand of maternal care visits and numerical 10 20 30 40 10 20 30 40 independent variables 10 68 40 30 20 10 40 30 20 10 0 20 40 POVERTY 60 80 100 69 10 20 30 40 0 70 10 20 30 40 STATA RESULTS 71 Appendix 6: Negative Binomial Regression with test for alpha nbreg ANC AGE NOEDU PRIMARY LOWSECOND UPSECOND TERTIARY MOBIPHONE NEWSPAPER RADIO TV MARITAL UNWANTED WORKING CEB HHSIZ > E POOR ETHNIC NORELI RURAL POVERTY ILLITERACY hospdeliratio RRD NM NC CH SE MD note: TERTIARY omitted because of collinearity note: MD omitted because of collinearity Fitting Poisson model: Iteration Iteration Iteration Iteration 0: 1: 2: 3: log log log log likelihood likelihood likelihood likelihood = -3448.3122 = -3444.684 = -3444.6797 = -3444.6797 Fitting constant-only model: Iteration Iteration Iteration Iteration 0: 1: 2: 3: log log log log likelihood likelihood likelihood likelihood = = = = -4180.5339 -3888.5482 -3888.4566 -3888.4566 likelihood likelihood likelihood likelihood likelihood = = = = = -3535.4462 -3424.8311 -3401.3536 -3400.8474 -3400.8471 Fitting full model: Iteration Iteration Iteration Iteration Iteration 0: 1: 2: 3: 4: log log log log log Negative binomial regression LR chi2(26) Dispersion Log likelihood = ANC AGE NOEDU PRIMARY LOWSECOND UPSECOND TERTIARY MOBIPHONE NEWSPAPER RADIO TV MARITAL UNWANTED WORKING CEB HHSIZE POOR ETHNIC NORELI RURAL POVERTY ILLITERACY hospdeliratio RRD NM NC CH SE MD _cons /lnalpha alpha Likelihood-ratio 72 Negative Binomial Regression with robust nbreg ANC AGE NOEDU PRIMARY LOWSECOND UPSECOND TERTIARY MOBIPHONE NEWSPAPER RADIO TV MARITAL UNWANTED WORKING CEB HHSIZ > E POOR ETHNIC NORELI RURAL POVERTY ILLITERACY hospdeliratio RRD NM NC CH SE MD, robust note: TERTIARY omitted because of collinearity note: MD omitted because of collinearity Fitting Poisson model: Iteration 0: log pseudolikelihood = -3448.3122 Iteration 1: Iteration 2: log pseudolikelihood = -3444.684 log pseudolikelihood = -3444.6797 Iteration 3: log pseudolikelihood = -3444.6797 Fitting constant-only model: Iteration 0: Iteration 1: log pseudolikelihood = -4180.5339 log pseudolikelihood = -3888.5482 Iteration 2: Iteration 3: log pseudolikelihood = -3888.4566 log pseudolikelihood = -3888.4566 Fitting full model: Iteration 0: log pseudolikelihood = -3535.4462 Iteration 1: Iteration 2: Iteration 3: log pseudolikelihood = -3424.8311 log pseudolikelihood = -3401.3536 log pseudolikelihood = -3400.8474 Iteration 4: log pseudolikelihood = -3400.8471 Negative binomial regression Dispersion Log pseudolikelihood = -3400.8471 Robust ANC AGE NOEDU PRIMARY LOWSECOND UPSECOND TERTIARY MOBIPHONE NEWSPAPER RADIO TV MARITAL UNWANTED WORKING CEB HHSIZE POOR ETHNIC NORELI RURAL POVERTY ILLITERACY hospdeliratio RRD NM NC CH SE MD _cons /lnalpha alpha Marginal effect mfx Marginal effects after nbreg y = Predicted number of events (predict) = 5.0515799 variable AGE NOEDU* PRIMARY* LOWSEC~D* UPSECOND* MOBIPH~E* NEWSPA~R* RADIO* TV* MARITAL* UNWANTED* WORKING* CEB HHSIZE POOR* ETHNIC* NORELI* RURAL* POVERTY ILLITE~Y hospde~o RRD* NM* NC* CH* SE* (*) dy/dx is for discrete change of dummy variable from to 74 Appendix 7: Multinominal Logistics Reression mlogit DELIVERY ANC AGE NOEDU PRIMARY LOWSECOND UPSECOND TERTIARY MOBIPHONE NEWSPAPER RADIO TV MARITAL UNWANTED WORKING > CEB HHSIZE POOR ETHNIC NORELI RURAL POVERTY ILLITERACY RRD NM NC CH SE MD, robust note: TERTIARY omitted because of collinearity note: MD omitted because of collinearity Iteration 0: log pseudolikelihood = -708.35443 Iteration 1: log pseudolikelihood = -528.53357 Iteration 2: log pseudolikelihood = -432.99207 Iteration 3: log pseudolikelihood = -392.62785 Iteration 4: log pseudolikelihood = -387.30586 Iteration 5: log pseudolikelihood = -386.64721 Iteration 6: log pseudolikelihood = -386.51174 Iteration 7: log pseudolikelihood = -386.48639 Iteration 8: log pseudolikelihood = -386.48093 Iteration 9: log pseudolikelihood = -386.47959 Iteration 10: log pseudolikelihood = -386.47931 Iteration 11: log pseudolikelihood = -386.47925 Iteration 12: log pseudolikelihood = -386.47924 Multinomial logistic regression Wald chi2(52) Prob > Log pseudolikelihood = -386.47924 Robust DELIVERY ANC AGE NOEDU PRIMARY LOWSECOND UPSECOND TERTIARY MOBIPHONE NEWSPAPER RADIO TV MARITAL UNWANTED WORKING CEB HHSIZE POOR ETHNIC NORELI RURAL POVERTY ILLITERACY RRD NM NC CH SE MD _cons 75 Multinominal Logistics Reression (continued) ANC AGE NOEDU PRIMARY LOWSECOND UPSECOND TERTIARY MOBIPHONE NEWSPAPER RADIO TV MARITAL UNWANTED WORKING CEB HHSIZE POOR ETHNIC NORELI RURAL POVERTY ILLITERACY RRD NM NC CH SE MD _cons 76 Multinominal Logistics Reression – Marginal effect mfx, predict (p outcome(1)) Marginal effects after mlogit y = Pr(DELIVERY==1) (predict, p outcome(1)) = 00031878 variable ANC AGE NOEDU* PRIMARY* LOWSEC~D* UPSECOND* MOBIPH~E* NEWSPA~R* RADIO* TV* MARITAL* UNWANTED* WORKING* CEB HHSIZE POOR* ETHNIC* NORELI* RURAL* POVERTY ILLITE~Y RRD* NM* NC* CH* SE* ( dy/dx is for discrete change of dummy variable from to mfx, predict (p outcome(2)) 77 mfx, predict (p outcome(2)) Marginal effects after mlogit y = Pr(DELIVERY==2) (predict, p outcome(2)) = 99800811 variable ANC AGE NOEDU* PRIMARY* LOWSEC~D* UPSECOND* MOBIPH~E* NEWSPA~R* RADIO* TV* MARITAL* UNWANTED* WORKING* CEB HHSIZE POOR* ETHNIC* NORELI* RURAL* POVERTY ILLITE~Y RRD* NM* NC* CH* SE* (*) dy/dx is for discrete change of dummy variable 78 mfx, predict (p outcome(3)) Marginal effects after mlogit y = Pr(DELIVERY==3) (predict, p outcome(3)) = 00167311 variable ANC AGE NOEDU* PRIMARY* LOWSEC~D* UPSECOND* MOBIPH~E* NEWSPA~R* RADIO* TV* MARITAL* UNWANTED* WORKING* CEB HHSIZE POOR* ETHNIC* NORELI* RURAL* POVERTY ILLITE~Y RRD* NM* NC* CH* SE* ( dy/dx is for discrete change of dummy variable from to 79 ... ? ?MATERNAL HEALTH CARE IN VIETNAM: DEMAND FOR ANTENATAL CARE AND CHOICE OF DELIVERY CARE SERVICES? ??, which is submitted by me in fulfillment of the requirements for the degree of Master of Art in. .. review and empirical review regarding the demand for prenatal care visits and the choice of facility for delivery The first part is to provide the role of maternal health care and the overview of maternal. .. maternal health care in Vietnam The next part is to present the theoretical background for the demand for health care services, and the choice of health care facility and their determinants The final