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Tiêu đề Maternal Health Care in Vietnam: Demand for Antenatal Care and Choice of Delivery Care Services
Tác giả Nguyen Thi Hoai Trang
Người hướng dẫn Dr. Truong Dang Thuy
Trường học University of Economics
Chuyên ngành Development Economics
Thể loại thesis
Năm xuất bản 2016
Thành phố Ho Chi Minh City
Định dạng
Số trang 108
Dung lượng 726,65 KB

Cấu trúc

  • 1.1 Problem statement (11)
  • 1.2 Researchobjectives (14)
  • 1.3 Researchquestions (15)
  • 1.4 Structure (15)
  • 2.1 Theroleofmaternityhealthcare (16)
  • 2.2 Overviewofmaternalhealth andhealthcareinVietnam (17)
    • 2.2.1 Theculture (17)
    • 2.2.2 Thetwo-childpolicy (17)
    • 2.2.3 MaternalmortalityratioandmaternalhealthcareinVietnam (19)
  • 2.3 Thedemandforhealthcare (23)
    • 2.3.1 Theoreticalbackground (23)
    • 2.3.2 EmpiricalLiterature Review (25)
  • 2.4 Thechoiceofhealthcare provider (35)
    • 2.4.1 Theoreticalbackground (35)
    • 2.4.2 Empiricalliteraturereview (36)
  • 3.1 Conceptualframework (41)
  • 3.2 Empiricalframework (43)
    • 3.2.1 DemandforPrenatalcare (44)
    • 3.2.2 Choiceofbirthdeliveryfacility (45)
  • 3.3 Data (47)
  • 3.4 Variablesdefinition (47)
    • 3.4.1 Dependentvariables (47)
    • 3.4.2 Independentvariables (48)
  • 4.1 DescriptiveResults (51)
  • 4.2 Analysis ofDemandforprenatalcare (53)
    • 4.2.1 Bivariateanalysis (53)
    • 4.2.2 Analysis ofNegative BinomialModel (56)
  • 4.3 Analysis ofChoiceinthedeliverycareproviders (60)
    • 4.3.1 Bivariateanalysis (60)
    • 4.3.2 Analysis ofMultinomialLogisticModel (64)
  • 5.1 Mainfindings (71)
  • 5.2 PolicyRecommendation (73)
  • 5.3 LimitationandFurtherResearch (75)

Nội dung

Problem statement

Thereisagrowingconcernaboutthematernalhealthcareglobally,especiallyinlowi n c o m e countries.WorldHealthOrganization(WHO2014)reportedthattheglobalmaternalm o r t a l i t y ratio(MMR)in2013was210maternaldeathsper100000livebirths,decreasingfrom3 80maternaldeathsper100000livebirthsin1990.However,theratioindevelopingregionsw as14timeshigherthanindevelopedregions.Eventhoughmaternaldeathisgenerallydecreasingworldwi de,ithasyettoachievethetargetofMillenniumDevelopmentGoal5byreducingthe

Thematernaldeathhasdirectcausesandindirectcauses.Thedirectcauseresultsfromarisingc omplicationsduringpregnancy,deliveryandpostpartum,orimpropertreatmentsuchashemorrhage, infection,obstructedlabor,unsafeabortion,ectopicpregnancyandanesthesia- relateddeathswhiletheindirectcauseresultsfromthediseasewhichpreviouslyexistsorben o t duetoindirectobstetric causeslike hepatitisanemia,malaria,heartdiseaseandtetanus( W H

O 2005).Itwasreportedthatdirectcausesmade upthehighernumberofmaternaldeatht h a n indirectcauseswith 80% ofthe total MMR (WHO2005).

Preventable complications during pregnancy can be significantly reduced through healthcare interventions like antenatal and delivery care, as introduced by the WHO in the Safe Motherhood Package in 1994 (Tran, 2012) Antenatal care provides pregnant women and their families with vital information regarding their health and the growth status of the unborn baby, allowing for dietary improvements that can prevent low birth weights Regular check-ups during this period help identify danger signs and risks associated with pregnancy and delivery, facilitating timely interventions, such as tetanus immunization, which is crucial for the health of both mother and child Managing high blood pressure during pregnancy is also essential for maternal health and infant survival (WHO and UNICEF, 2003) Furthermore, delivery care plays a critical role in reducing maternal mortality rates The WHO recommends that childbirth occurs in a healthcare facility or under the supervision of skilled health staff to ensure safe delivery and the birth of healthy babies Adequate hygiene and medical equipment at these facilities can minimize complications from labor, such as hemorrhage and obstructed labor, while skilled health professionals ensure safe delivery and effective emergency management (Tran, 2012).

InpursuitofMillenniumDevelopmentGoal5“Improvingmaternalhealth”,Vietnamalso ismakingprogressinimprovingthematernalhealthwiththedropofmaternalmortalityratio.The WorldBankshowsthatMMRinVietnamhasremarkableimprovementsinlast15yearsindecrease from81deathsper100,000livebirthsin2000to54per100,000in2015.T h e accesstoantenatalc are,animportantperiodforhealthofpregnantwomenandtheirbabyanddeliveryservicehasalsoinc reased.Multiple indicatorclustersurveyin2014(MICS5)s h o w s thatthepercentageofwo menaged15-

49withalivebirthinthelasttwoyearswhoreceivedantenatalcareatleastonceis95.8percentna tionwide.However,thereareconsiderabledisparityinmaternalmortalityratioandutilizationofmat ernalhealthcareamonge t h n i c i t y group,placeofresidenceandtheregionswherethepregnant women areliving.MPI2 0 1 5 reportedthatmaternalmortalityinmountainous areasismorethanth reetimeshighert ha n i n l o w l a n d areas.Furthermore,MICS5indicatest h a t t h e t i m e s o f pren atalc a r e v i s i t s differsamongthewomenlivingruralandurbanarea,especiallyregardinghavingmor ethan

4v i s i t s Inaddition,t h e ethnicm i n o r i t y groupsgetm o r e disadvantageo f accesst o maternalh ealthcarew i t h 7 9 % o f t h o s e having1 v i s i t a n d 3 2 7 % o f t h o s e h a v i n g atleast4 v i s i t s comparedto 99.2%and82.1 %of theKinhgroupasshown.Therefore,growingdisparities inhealthoutcomesandhealthcareutilizationhaveposed agreatchallenginginrecentyears.

Theabovechallengesleadtoseveralstudiesintheutilizationofmaternalhealthcarei n Vie tnam.Mostofthemfocusedontheinfluenceofdemographicandsocioeconomicfactors(Sepherietal.2

2012,Malqvistetal.2013).Demographicfactorswhichwereshowntoincreasetheprobabilityofthehealth servicesareyoungerage,l o w b i r t h orderw h i l e t h e f a c t o r s reportedt o decreaset h e p r o b a b i l i t y a r e separatedorunmarriedstatus,unintendedpregnancy.Inaddition,socio- economicfactorsmakegreaterinfluenceontheuseofthematernalhealthcareservices.Highereduc ationlevelofawomanisthemostimportantdeterminantreportedinthepreviousstudies(Sepherietal.2

008,Tranetal.2011,Golandetal.2012,Malqvistetal.2012,Malqvistetal.2013,Wakabayashi2014)

.Lowerhouseholdincomeisalsoshowntobeastrongfactorinthelikelihoodofusingmaternalhealt hcare(Sepherietal.2008,Golandetal.2012).Somestudiesemphasizedthed i s p a r i t y inth e maternalhealthcareutilization amongethnicmajority andminority groups(Malqvistetal.2012,Malqvistetal.2013).Ontheotherhand,majorequityinruralandurban areasalsowasidentifiedbyTranetal.(2011)andSepherietal.

(2008)estimatingtheimpactsofpovertyrate.Theomissionofthefactormaybiastheinfluenceo nm a t e r n i t y health c a r e utilizat ion, especiallyforth e disadvantagedw o m e n T h e o mi ss io n o f c o m m u n i t y effectsmayresultinbiasedestimatesoftherolesoffactors(Singhetal

2014).C o m m u n i t y b e l i e f s andn o r m s encourageorpreventhealthc a r e s e e k i n g beha viorso f t h e women.Ina d d i t i o n , community economicde ve lo pm en t may influence the accesst o health servicesandindirectlyincreasedecisionmakingpowerofwomenandpositiveattitudestow ardhealthserviceuse.

Community-level factors significantly influence maternal health care utilization Key indicators include the poverty rate, the proportion of women with higher education, and the rate of facility-based childbirth Research indicates that higher poverty rates correlate with lower likelihoods of receiving antenatal care and facility deliveries Conversely, a greater proportion of educated women is linked to increased utilization of maternal health services, highlighting the importance of education and economic status in improving maternal health outcomes.

Therefore,thereisaneedtoproperlyinvestigatethedeterminantsonhealthcareserviceutilizationi n c l u d i n g individuallevel,householdlevelandc o m m u n i t y l e v e l characteristics.Usingthelate stdatasetfromVietnamMultipleindicatorclustersurveyin2014(MICS5),thiss t u d y appliesthePo issonModeltoestimatetheimpactofsocialdeterminantsonthedemandf o r prenatalcarevisits,andt heMultinomialLogisticModeltomeasuretheassociationbetweensocialfactorsandchoiceon deliverycareproviders.

Researchobjectives

Theoverallobjectiveofthisthesisresearchistwofold.First,weanalyzethedemandofprenatalhealthcare.Particularly,weexaminethedeterminantsofthenumberofantenatalcarevisitsofwomentakingdurin gthelasttwoyearsusingdatafromMICS5.Second,weinvestigatethechoiceonservicefacilityfor deliveryofpregnantwomeninVietnam.

Researchquestions

Toinvestigatetheaboveobjectives,the followingquestionsneedto be answeredthoroughly:

Question 2: What arethedeterminantsof the choiceon deliverycareprovider?

Structure

Thep a p e r i s o r g a n i z e d asf o l l o w s InC h a p t e r 2,t h e generaltheoriesrelatedt o t h e d emandofhealthcareandthechoiceofhealthcareproviderarediscussedandthepreviousstudiesont heimpactofsocialdeterminantsonutilizationofmaternalhealthcarearereviewed.Chapter2presentsth econceptualframeworkandthemethodology withtwoappliedmethodsu s i n g thedatasetnamelyMultipleIndicatorClusterSurvey2013-2014(MICS5).Inthesamechapter,methodsinvestigatingthedeterminantsofthedemandofprenatal healthcareandthechoiceofservicefacilityfordeliverywillbepresented.Theresultsanddiscussionarepresent edChapter4.Chapter5concludes thepaperanddiscusses policyimplications.

Thischapterpresentsthetheoreticalreviewandempiricalreviewregardingthedemandf o r p renatalcarevisitsandthechoiceoffacilityfordelivery.Thefirstpartistoprovidether o l e ofm aternalhealthcareandtheoverviewofmaternalhealthcareinVietnam.Thenextparti s topresentthetheo reticalbackgroundforthedemandforhealthcareservices,andthechoiceo f healthcaref a c i l i t y a n d t h e i r determinants.T h e finals e c t i o n reviewst h e determinantsaffectingthedemandofpre natalcarevisitsandthechoiceofdeliverycareprovidersreportedi n thepreviousstudiesindeveloped countriesanddevelopingcountries,especiallyinVietnam.

Theroleofmaternityhealthcare

Motherhoodisapositiveexperiencewhichawomenencounters;however,thereares o m e healthproblemshappeningduringpregnancy,childbirth,andthepostpartumperiod.Theconsequ encesimpactseriouslynotonlyonthewomen’shealthbutalsoonthebabies.Threequarterofmater naldeathsisreportedtooccurduringchildbirthandthepostpartumperiod.However, antenatalcareanddeliverycarecanpreventthesecomplications.

Antenatal care (ANC) began in the early 1900s to support the health of pregnant women and their unborn children while detecting adverse conditions for timely interventions This care enhances women's understanding of fetal growth and their health status, helping to prevent issues such as low birth weight by improving nutritional status Women are also informed about the risks associated with pregnancy and delivery The World Health Organization (WHO) recommends at least one visit to a skilled health provider or a minimum of four ANC visits to any provider According to WHO guidelines, the ANC program includes assessments of both mother and fetus, such as measurements of body weight and height, blood pressure, urine and blood tests, as well as medical provisions like tetanus vaccinations and iron and folate supplements, alongside health consulting and education.

Thedeliveryathealthfacilitiesalsoplaysanimportantroletoensure womentogothrou ghchildbirthsafelyanddeliverhealthyinfants.Infact,propermedicaltechnologyandhygieni cconditionsduringd e l i v e r y c a n preventcomplicationsandinfectionsleadingt o m o r b i d i t y andm o r t a l i t y o f motherandh e r child.Inaddition,s k i l l e d b i r t h attendantsa r e avail ableinmosthealthfacilities.AccordingtoWHO,askilledbirthattendantisdefinedasamidwife,docto rorn urs e, who is wellskilled toensurenormal childbirthandthepostnatal

O recommendedthatincountrieswithveryhighMMR,atleast60%ofchilddeliveriess h o u l d beassistedbyskilledbirthattendantsby2015.During2005-

Overviewofmaternalhealth andhealthcareinVietnam

Theculture

VietnamcultureishighlyinfluencedbyConfucianism,especiallyinthenorthregiono f thecountry.AccordingtothetraditionofConfucianism,thesonofthefamilywillinheritt h e fa milyresourcesandworshiptheancestors.Inaddition,hehasresponsibility fortakingcareofth efamilymembersandmaintainsthecontinuityofthefamilyline.Therefore,givingb i r t h t o a sonbringsaproudto thefamilyandimproves the status of thewomenin thefamily.However,itwillputhighpressureofhavingasononthewomeninthefamily,especiallyfo rt h e womenwithdaughters.Thestrongpreferenceforsonsisthemainreasonforincreasingsexratioatbir th.

In many families, male members are viewed as the primary income earners and decision-makers, while female members are often seen as vulnerable and reliant on their parents After marriage, women typically move in with their husband's family, where financial control is likely held by their in-laws and husbands This dynamic, influenced by strong Confucian values and existing hierarchies, restricts women's autonomy and decision-making, particularly regarding their health For instance, the childbirth experiences of mothers and mothers-in-law significantly shape the maternity care practices of young women, potentially hindering their access to essential maternal healthcare services.

Thetwo-childpolicy

Thetwo- childp o l i c y i n Vietnamwasissuedi n l a t e 1 9 8 0 s w i t h restrictiono f t h e m a x i m u m n u m b e r o f childrenperhousehold.Vietnamgovernmentpracticeds o m e f a m i l y p l a n n i n g measures to reach thegoalsuchasprovidingthefreebirth controldevicesaswellasp r o s i n g thefacilitiesfor thosewhowasallowedforabortions.Inaddition,thefamilywhodidn o t complywiththetwo-

Vietnam's child policy imposes penalties for violations, including high fees for families and delayed salary raises for government staff This fear of repercussions has led some women to hide their pregnancies and avoid necessary maternal healthcare Additionally, having more children places a significant burden on women, both in terms of time and finances, limiting their access to healthcare services The revised 2009 Population Ordinance allows couples to decide when to have children, permitting one or two children, which has successfully reduced the total fertility rate from 2.55 in 2001 to 1.99 in 2011 However, challenges remain, such as ineffective contraceptive methods and a high abortion rate, particularly among youth, often due to a lack of knowledge about contraception and preferences for smaller families, compounded by financial and health concerns.

MaternalmortalityratioandmaternalhealthcareinVietnam

InVietnam,thegovernmentrecommendspregnantwomenshouldhaveatleastthreepren atalvisitsduring thepregnancytodetectandpreventtherisksnegativelyaffectingthehealthof motherand baby.Thecontentofprenatalcareincludesbloodpressuremeasurement,u r i n e testing,b l o o d t e s t i n g andm e a s u r e ofweightandheight.Ina d d i t i o n , t h e nationalguidelinessuggestt h a t pregnantwomens h o u l d d e l i v e r th e b a b y ath e a l t h facilities.Propermedicalattentionandhyg ienicconditionathealthfacilitiesreducethecomplicationsoccurringi n andafterthechildbirth.Inad dition,forthecomplications,Caesareansectionisrequiredbuts h o u l d b e performedbyt h e s k i l l e d obstetricd o c t o r s t o e n s u r e s a f e childbirth.D u r i n g t h e postpartumperiodtheguideline srecommendatleasttwohealthcheckupsforbothmotherandchild.

The maternal mortality ratio (MMR) measures the number of women who die from pregnancy-related causes within 42 days after childbirth, per 100,000 live births According to World Bank data, Vietnam has seen significant improvements in its MMR over the past 15 years, decreasing from 81 per 100,000 in 2000 to 54 per 100,000 in 2015 This achievement has met the Millennium Development Goal 5 target of an MMR of 58.3 per 100,000 live births by 2015 However, despite these advancements, Vietnam still lags behind developed Asian countries such as Singapore and Malaysia.

Maternal mortality ratio (per 100,000 live births)

500 Lao PDR Malaysia Indonesia Thailand Cambodia

Brunei Darussalam Singapore Myanmar Philippines Vietnam

0 andThailand.Therefore,VietnamshouldmakegreaterefforttoreducetheMMRandensuret h e pers istentpopulationgrowth.

At least 4 times by any providers At least 1 visit by skilled health worker

To reduce maternal mortality rates (MMR) and infant mortality rates (IMR), the World Health Organization (WHO) recommends that each pregnant woman should have at least four prenatal care visits, or at least one visit attended by professional health staff Antenatal care is essential for providing women and their families with information about potential risks during pregnancy and childbirth Vietnam has made significant strides in antenatal care coverage, with 95.8% of pregnant women having at least one prenatal care visit in 2014, an increase from 1999 However, only 73.7% of women receive more than four visits, indicating a need for further measures Additionally, there are considerable disparities in maternal healthcare utilization among different ethnic groups and regions, with rural women and ethnic minorities facing greater challenges For instance, only 32.7% of ethnic minority women have at least four visits compared to 82.1% of the Kinh group.

Figure3 : Percentageofwomenh a v i n g a t least1 v i s i t anda t least4 v i s i t s duringpr egnancy

Antenatal care visits by residence

Antenatal care visits by ethinicity

Thedemandforhealthcare

Theoreticalbackground

Grossman(1972)arguedthatwhatindividualdemandwhenpurchasinghealthcareisn o t healthcarebutgoodhealth.Firstly,hesetupthemodelofdemandforhealth,inwhichthe individualhaspositiveutilityofconsumptiongoodsandnegativeutilityofsicktime� 𝑠 (�). (Zweifeletal.2009)

Inaddition,thehealthstockHchangesovertime.Therefore,thehealthcapital decreaseattherate�.However,theindividualcanincreasehealthcapitalbyinvestinginI.In atwo-periodmodel,thecurrenthealthcouldbespecifiedas

Where,Uisutility,Hisstockofhealthcapital,�istherateofthedepreciationofthe heathstock,wiswagerate,Xisconsumptiongoods,Mistheconsumedamountofmedical services,Iisinvestmentinhealth,� 𝑠is sicktimeand� �is timeinvestedinfavorofh e a l t h

Grossman(1972)arguedt h a t t h e i n d i v i d u a l demandf o r h e a l t h f o r t w o reasons:first,as investmentcommodityandsecond,consumptioncommodity.

Basingonthefunction�(�,� � )and� 𝑠 (� 1 )from(1.1)and(1.2),Grossmanconstructed thedemandfunctionformedicalservicesin investmentmodel: ln�=𝑐����−(1+� � (�−1))���+(1+� � (�−1))���−(1−�)� 𝐸 𝐸 (1.3) Where,� �is theproductionelasticityofmedicalservicesand� 𝐸is theeffectivenessofedu cationE;�isthemarginalefficiencyofhealthcapital� 1

Fromtheutility function(1.1)including sicktime andconsumptiongood,heconstru ctedthedemand functionformedicalservices in consumptionmodel: ln�=𝑐����.−(1+� � (�−1))���+(1−�)(1−� � )���−(1−�)� 𝐸 𝐸−

Fromtheinvestmentmodel(1.3)andconsumptionmodel(1.4),thedemandofhealthservic esdependsonthepriceofmedicalservices,thewagerate,educationandwealth.Itcould beseenthatthe priceofmedicalservicesdecreasetheoptimumquantity of� 1whereas t h e w agerateincreasethequantityof� 1 Inthemultipleperiodmodel,bothofdemandfunctionsalsoareadd edtheagebecausethedepreciationrate�ispositivelycorrelatedwithage.(Zweifel etal.2009)

In addition to the Grossman Model, various studies have introduced models to explain individual health-seeking behavior Rosenstock's Health Belief Model (1974) posits that an individual's beliefs about health problems, along with their perceptions of benefits, barriers, and cues to action, collectively influence health-promoting behaviors Modifying variables, such as demographic and psychosocial characteristics, indirectly affect these perceptions The model emphasizes that a heightened perception of serious consequences and risks associated with health issues significantly increases the likelihood of engaging in health-promoting behaviors Following this, the perception of benefits from taking action versus barriers, such as inconvenience and side effects, determines whether health-promoting behavior occurs Cues to action, both internal (e.g., pain, symptoms) and external (e.g., information from friends and mass media), play a crucial role in prompting these behaviors The model has been effectively utilized to develop interventions aimed at changing health-related behaviors by targeting specific components within it.

ThaddeusandMaine(1994)developedthethreedelaytheorytoidentifythebarrierstot h e tim elyandadequatelyutilizationofmaternalhealthcare.Theyviewedthatthefirstphasewasdelayinsee kingcare.Thefactorseffectingthephaseincludeddecisionsofindividualandfamily,thestatusofwom en,previousexperienceregardinghealthcaresystem,financialando p p o r t u n i t y cost.Then extphasewasdelayingettingaccesstothehealthfacilityduetothea v a i l a b i l i t y o f facilitie s,distancet o facilities,transportationcostandtransportationinfrastructure.Thelastphasewasdelayi ntakingadequatecare.Therelevantcauseswerelacko f equipmentandskilledhealthstaffs,qualificat ion ofhealthstaffs.

ThebehavioralModelofHealthServicesUtilizationbyAndersen(1995)hasbeenusedi n t h e s tudieso n utilizationo f healthservicesi n b o t h developedandd e v e l o p i n g c o u n t r i e s (Thindet al.2008).IntheAndersen’sModel,oneindividualgettingaccesstoandusinghealthcareserviceswasafun ctionofthreefactors,namelypredisposing,enablingandneedfactors.T h e predisposingfactorsw ereclassifiedintothreegroupssuchasdemographiccharacteristics,

13 socialstructureandh e a l t h beliefs.Demographiccharacteristicsrepresentt h e t e n d e n c y o f i n d i v i d u a l s touseservices,includingage,gender,maritalstatuswhilesocialstructurere flectt h e a b i l i t y o f i n d i v i d u a l s t o seekhealthc a r e s e r v i c e s , i n c l u d i n g e d u c a t i o n , o ccupationandethnicity.Healthbeliefswereperceptionandattitudesregardingthehealthcaresyste msthatinfluencet h e u t i l i z a t i o n o f t h e services.T h e n e x t wase n a b l i n g factors,b o t h pers onalandorganizational,whichmeasuretheactualabilitytoobtainhealthservices.Personalenab lingfactorsincludedi n c o m e , healthinsurance,travelandw a i t i n g t i m e s w h i l e organiz ationalenablingfactorsweretheavailabilityofhealthfacilities.Thelastoneisneedfactors,thedirectcau sestoutilizationofhealthservices.Theneedwastheself- assessmentofhealthstatusandevaluationfromhealthstaffs.

EmpiricalLiterature Review

Theoretically,prenatalcareisconsideredavitalfactorinmaternalandinfantmortality.M e a s u r i n g andc o u n s e l i n g d u r i n g prenatalcarehelpwomenu n d e r s t a n d i n g h e a l t h s t a t u s o f herselfandherbaby,detectingrisksinordertoensuresafepregnancy,childbirthaswellasd ecreasepost- partumproblems.Whilesomeresearcheswereconductedtoestimatetheassociationbetweenmater nalhealthcareandhealthoutcome,somestudiesfocusondeterminantseffectingutilizationofmat ernalhealthcare.Thebelowistopresentthefactorsinfluencingthedemand o f prenatalcare visi tsandthe c h o i c e ofdelivery locationfromthepreviousstudies.

Thedeterminantsarecategorizedintothreecharacteristicsincludingindividuallevel,hou seholdlevelandcommunitylevel.Theindividualvariablesincludeeducationattainment,maternal age,maritalstatus,religion,ethnicitywhilehouseholdcharacteristicsarehouseholds i z e andho useholdwealth.Further,community levelconsistsofp la ce ofresidence,regiond u m m i e s , povertyrate andilliteracyrate.

(Arthur2 0 1 2 , Bbaale2 0 1 1 , Navaneetham& Dharmalingam2002).Itwase x p l a i n e d t h a t educatedwomenhadmoredecision-makingpoweronhealth-

2002) However, therewasno significantdifferenceintheutilizationofmaternalhealthcareamongeducatedwomenbylevelo f educa tion,e s p e c i a l l y betweenp r i m a r y l e v e l andsecondl e v e l

(Navaneetham& Dharmalingam2002).Inaddition,whenmeasuringtheeffectoftheintroduction ofNationalHealthInsurance(NHI)inTaiwan,Chenetal.(2003)foundthateducationattainmentdid nothaveinsignificantimpactonantenatalcarebeforeNHIbutwassignificantlypositiveafterNHI.T h e reasonforthisdifferencewasambiguous.Ingeneral,educatedwomenarewellinformedo f theimpo rtanceofmaternalcareandwillincreasemorefrequenciesofantenatalcarevisitst h a n less- educatedmothers.

(2008)suggestedthatthemaritalstatusimpactedtheuseofanyprenatalcaregreaterthanthen u m b e r of vi si ts buthasnosignificantinfluenceo n decisiono f deliveryplace.Itcouldb e e x p l a i n e d thatsinglemothersunwillinglygetaccesstothehealthcareduetofaceofstigmatizationbecauseth echildbirthiswidelyconsideredtheresponsibilityofmotheraswellasherhusbandinVietnam(Sepeh rietal.2008).Researchesinothercountrieswereconsistentw i t h thestudyofSepehrietal. (2008).InthestudyinTaiwan,Chenetal.

Theageofexpectantmotherisotherfactorintheutilizationofmaternalhealthservices.T h e highe ragethemothersget,thelowertheprobabilitytheywillseekhealthcare(Arthur2012).Itc o u l d b e e x p l a i n e d t h a t experiencea n d knowledgerelatedmaternalh e a l t h mayinfluenceonthema ternalhealthseekingbehavior(Chenetal.2003).Tsawe&Susuman(2014)showedthatthewomeninth eageof15-39morelikelytotakehealthcheck- upsfrequentlyt h a n thoseintheageofabove40.H o w e v e r , thereweresomeresearchesshowingthat women’sagewasinsignificantlyassociatedwiththeattendanceofANCforexample,inTurkey(C elik

Ast h e sameast h e ageo f expectantmother,mo st studiesf o u n d th at t h e increasingn u m b e r ofchildreneverbornhadthesamenegativeeffectontheuseofmaternalhealthcareservices.T hehigherorderbirthswilldecreasethelikelihoodofusingtheservicesforsomereasons.Itm aybed u e tot i m e andresourcec o n s t r a i n t s f o r womenhavinglargerf a m i l i e s

Research indicates that first-time mothers are more likely to utilize antenatal care due to their inexperience (Navaneetham & Dharmalingam, 2002) However, Arthur (2012) suggests that women who have previously experienced childbirth may attend fewer antenatal care visits if they had negative experiences with the services This sentiment is echoed by Tsawe & Susuman (2014), who assert that maternal healthcare utilization is significantly influenced by prior experiences with the services provided When women receive quality care, they are more inclined to seek these services regularly Conversely, policies such as the two-child limit and the fear of penalties may lead women with more than one child to reduce their use of maternal healthcare services (Sepehri et al., 2008).

(2013)f o u n d thatpregnancyintentionwassignificantlyrelatedtotheutilizationofantenatalcare buti n s i g n i f i c a n t l y tothedeliverycare.Thereasonwhytheunwantedpregnantwomenlessli kelyt o receiveantenatalcareadequatelyisambiguous.Wadoetal.

(2013)hypothesizedthatwomenw i t h unwantedpregnanciesd i d n o t preparewelli n t h e respecto f emotionandfinancef o r childbirthandchildbearingsotheylesstakecareoftheirhealthandtheirun born.Oneoftheargumentisthewomenwithunintendedpregnanciesrecognizedtheirpregnancyl atesotheym i s s t h e firstt i m i n g antenatalc a r e v i s i t s W a d oeta l

( 2 0 1 3 )observedt h a t womenw i t h unwantedpregnancydetectthepregnancyaroundonem onthlatercomparedwithoneswithpregnancyintention.Ingeneral,t h e s t u d y impliedt h a t t h e pr egnancyintention wash i g h l y associatedwiththeutilizationofmaternalcare;however,itsassocia tionwiththedeliverycarewasstillunclear.

Somestudiesresultedthatfrequenciesofusingmassmedia positivelyrelatedtotheutil izationofANC.Thehigheristhelevelofexposuretomassmedialikeradioandtelevisiont h e higherist helikelihoodofusingANC.Navaneetham&Dharmalingam(2002)foundthatwomenw a t c h i n g t e l e v i s i o n andl i s t e n i n g radior e g u l a r l y increasedt h e o p p o r t u n i t i e s o f herseekingANC.Itcanbeexplainedthatthemassmediawillprovidetheinformationregarding tothematernalhealthandenhancetheawarenessoftheavailablematernal healthservices.Tsa we&Susuman(2014)reportedthatthosewhohadmoreknowledgeofthematernalhealthservicemore likelytoreceivetheservicetimelyandadequately.Infact,lackofinformationposesthechallengest o theutilization ofmaternalhealth.

The significance of working status in maternal healthcare utilization is well-documented, with studies indicating that non-working women are more likely to seek maternal health services compared to their employed counterparts This trend may be attributed to non-working women often being relatively wealthier than those who are employed, as many jobs in developing countries do not offer adequate salaries, leading to a lower likelihood of utilizing maternal healthcare services Additionally, the type of employment held by pregnant women significantly influences their use of antenatal care, as job conditions and income affect healthcare affordability For instance, women employed in factories are more inclined to access antenatal care than housewives, and those in government jobs are more likely to seek antenatal care when covered by national health insurance.

A study conducted in 2008 revealed that women from ethnic majority groups in Vietnam are more likely to give birth in health facilities compared to those from ethnic minority groups This disparity can be attributed to communication challenges with healthcare providers due to language barriers Additionally, lower levels of education and poor socio-economic conditions contribute to reduced access to maternal healthcare among ethnic minority women (Singh et al., 2014) Similar findings have been reported in other countries; for instance, Navaneetham & Dharmalingam (2002) noted that women from "Scheduled" castes and tribes in India had fewer antenatal care (ANC) check-ups, while Kudish women in Turkey were also less likely to utilize ANC services (Celik & Hotchkiss, 2000).

SimilartoEthnicity,religiousdifferenceisoneofthemostimportantdeterminantsofhealths erviceutilizationbecausereligionaffectsthewaypeopleliveandbehaveaswellast h e i r belief (Bbaale2011).Ifwomenbelievinginthetraditionalbirthattendantsmorelikelygivebirthathom eratherthangoingtohospitalorclinic(Tsawe&Susuman2014).Studyingi n India,Singhetal.

Muslimrestrictwomenamongthisreligiont o enjoyhealthcarebenefits.Similarly,Muslimwom eninKeralatendtogivebirthathomeandrefusetobeassistedbyskilledhealth providers;however,theprobabilityofantennalcarev i s i t s i n t h e firsttrimesterishigheramongthem(Navaneetham&Dharmalingam2002).

Previous research indicates that household wealth positively influences the utilization of antenatal care (ANC) services (Bbaale, 2011; Tsawe & Susuman, 2014) For instance, Navaneetham and Dharmalingam (2002) found that women from higher living standards are three times more likely to receive adequate prenatal care compared to those with lower standards Additionally, having a car is positively associated with the use of maternal healthcare services (Celik & Hotchkiss, 2000) Despite some countries offering free services, barriers remain, as healthcare may involve direct and indirect costs, such as transportation (Arthur, 2012) Women facing challenges in affording travel expenses are less likely to seek ANC than those who do not struggle financially (Tsawe & Susuman, 2014) Overall, financial constraints are a significant barrier to accessing maternal healthcare.

PlaceofresidenceiskeyconcerninANCutilization.Thepreviousstudiesresultedthatwomeni nruralareaslesslikelyusematernalhealthservicesthanurbanwomenduetolongdistancetotheh ealthfacilities.Inaddition,financialproblemsalsowereabarrierforthemtocompleteuseofmaternal healthcarebecausetheycouldnotaffordthetransportationcostaswellasANCcost(Tsawe&Susum an2014).Theshortageofskilledattendantalsoisthereasonw h y ruralwomenlessfrequentlyundertak eantenatalcarethanurbanarea.Infact,thereislacko f qualifiedhealthproviderinruralareaincompari sonwiththecities(WHO,2006).

Understandingthesematters,somecountriesappliedtheprogramtominimizetheproblems.Fo rexample,whenstudyingfourstatesinthesouthIndianin2002,Navaneetham&Dharmalingam(2 002)foundthat thereisnosignificantdifferencebetweenruralandurbanareaintermsofthede mandforantenatalcare.Theunderlyingreasonwasthatmultipurposehealthworkersprovideant enatalcaretopregnantwomenbyvisitingtheirhome.Incontrast,Celik&Hotchkiss(2000)foundthat urbanandruraldifferencedidnotsignificantlyimpacttheprenatalc a r e afterh o l d i n g t h e constantr egionals t a t u s ando t h e r variablesi n t h e s t u d y i n Turkey.

Thedifferenceinutilizationofmaternalhealthca re isduetotheimplementationofhealth c a r e program,t h e a v a i l a b i l i t y anda c c e s s i b i l i t y ofth e h e a l t h careserviceamongt h e regi ons.Studyingi n Vietnam,Sepehrieta l

(2008)pointedo u t t h a t womenl i v i n g i n t h e disadvantagedregionslikeCentralHighlandsles slikelyundertakeanymaternalhealthcaret h a n thoseliving inRedRiverDelta.However,there wasnosignificantregionaldifferenceint h e frequencyofprenatalvisits(Sepehrietal.,2008).Simila rly,inTurkey,Celik&Hotchkiss(2000)alsofound thatlivingindevelopedregionsofthecountr yhadsignificant ly positiveassociationwithattendanceofprenatalcare service.

Besidei n d i v i d u a l levelandhouseholdlevelcharacteristics,c o m m u n i t y levelcha racteristicshavebeenpaidgreaterattentioninthepreviousstudiesinrecentyears(Gage2 0 0 7 , S epherietal.2008,Ononokponoetal.2013andSinghetal.2014).Stephensonetal.

(2006)arguedt h a t c o m m u n i t y couldi n f l u e n c e healthoutcomesthroughseveralways.Forexa mple,communitybeliefsandnormsmayhavegreateffectonpositiveornegativeattitudeso n healthc a r e services,whichi n t u r n l e a d t o healthc a r e s e e k i n g b e h a v i o r Inaddition,economic developmentofacommunitywillattracttheinvestmentofhealthcareinfrastructure,socials u p p o r t a swella s improvemento f k n o w l e d g e i n b e n e f i t s o f h e a l t h careservices.Studyinginru ralMali,Gage(2007)suggestedthatcommunitywithhigherportionofwell- educatedwomenwas highlyassociatedto likelihood ofgettingaccesstomaternalhealthcare.InVietnam,Sepehrietal.

(2008)pointedoutthatwomenlivingincommunity withhigherp o v e r t y ratehavefewerte ndencytodelivertheirbabyinhealthfacilitiesincomparisonwitht h o s e livingincommunitywit hlowerpovertyrate.Oneofthecommunitylevelcharacteristics,

19 whichwerealsofoundtobepositivelyassociatedwiththedemandofprenatalcarevisitsistheproportiono fwomeninsamecommunitygivingbirthathealthfacility (Ononokponoetal.2 0 1 3 ) Th eresearchshowed that thewomenlivingin thecommunitywiththehighproportionm o r e l i k e l y 5 8 t i m e s t o t a k e adequateprenatalc h e c k - u p comparedt o t h o s e i n t h e lowerc o m m u n i t y levelproportion.

Thechoiceofhealthcare provider

Theoreticalbackground

Int h e l at e1 98 0s , Gertler,LocayandS a n d e r s o n (1987)f i r s t l y developedt h e healt hseekingbehaviorinthechoice ofhealthcareproviders.Theyarguedthatatthefirststage,thei n d i v i d u a l decideswhethertosee khealthcareandatthesecondstage,heorsheselectsthehealthcareproviderswiththemaximumuti lity.Theutilityfunctionofindividualireceivinghealthcare fromproviderj ispresentedasfollows:

Inwhich,� ��i s t h e u t i l i t yofthe individual iafter receivinghealthcarefromproviderj,ℎ ��i s expectedhealthstatusoftheindividualafterreceivinghealt hcarefromproviderj and

Thehealthstatusafterreceivinghealthcarefromproviderjforanindividualidepends on the qualityofproviderj’shealthcare

Therefore,thequalityofhealthcaredependsonthecharacteristicsofhealthcareproviders� � andcharacteristicsofindividual� �as follows:

Theotherconsumptionexpenditure𝐶 �a fterreceivingthehealthcareistheremainingofthei ncome� �a fterpayinghealthcareproviderj.Theprice� ��o f thealternativejisthe paymentforthehealthcareincludingdirectcostsuchasconsultationcost,medicinecostandindirectco st suchastransportationcostandwaitingtime.

Researcherscouldnotmeasuretheutilityoftheindividualbutinvestigatethe characteristicso f t h e alternativesandt h e characteristicso f t h e i n d i v i d u a l (Train,2 0 0 9 ) Therefore,the utilityfunction oftheindividualisexpressedasfollows:

Theobservedcharacteristicso f t h e individualaregender,a g e , education,income, insurancewhereastheunobservedcharacteristicsareperceptionofqualityofthehealthcareprov ider,thepreferentialmedicaladministration.The observedcharacteristicsofthehealthcareprovid eraretheprice,thedistancefromhouseofthepatienttothehealthcareproviderwhereastheunob servedcharacteristicsarethe fame,prestigeof thehealthcareprovider.

Empiricalliteraturereview

Itiswidelyacknowledgedthatchildbirthathealthfacilitiesisassociatedwithlowerrateo fmaternalmortalityandmorbidity.However,therearestillwomenchoosingthechildb i r t h at home,especiallyindevelopingcountries.Therefore,somepreviousstudieshavefurtherconductedtoinve stigatethedeterminantsofthechoiceofdeliverycareprovider.Theyhavefocusedthecharacteristi csofindividualofthewomen,householdandcommunitywheretheyareliving.

(2006)arguedthattheprenatalcareduringpregnancywashighlyassociatedwiththechoiceofdeliverya thealthfacilitiesbyinformingthebenefitofinstitutionaldeliverya n d appropriateservices.Sepehr ieta l

(2008)agreedt h i s p o i n t t h a t t i m i n g andadequatep r e n a t a l carev i s i t s couldraiset h e awarenesso f t h e needo f c a r e f o r delivery.

Educationattainmentalsoisfoundtoplaytheimportantroleinthechoiceofchildbirthplace(Sep ehrietal.2008).Forexample,Celik&Hotchkiss(2000)pointedoutthatthewomenw i t h highereduc ationm o r e l i k e l y t o choosef a c i l i t y d e l i v e r y r a t h e r t h a n traditionalh o m e delivery.Iti s l i k e l y t h a t t h e h i g h l y educatedwomenhavet h e s t r o n g e r andindependentdecisionstot hebesthealthcareservices.Furthermore,theeducatedwomenhavemuchmorechanceto bewellinformed of thebenefit offacility-baseddelivery.

Withrespecttothebirthorder,thepreviousstudiesreportedthatithasstrongassociationw i t h t h e c h o i c e o f d e l i v e r y ath e a l t h facilities.Navaneetham& Dharmalingam(2002)f o u n d t h a t t h e womenw i t h firstb i r t h orderm o r e l i k e l y to giveb i r t h ath e a l t h carei n s t i t u t i o n s ratherthanthosewithsecondbirthorder.Therearesomeargumentsregardingthematter.Someresearc herspointedoutthatthewomenwithhigherparityfacedtimeandresourceconstraintsto utilizethefacilitiesservicesdueto largefamilies.On theotherhand,itcouldbet h e badexperiencesfrompreviouschildbirth,whichmakethemtounderes timatethedemandf o r facility-baseddelivery.

Concerningtheageofthepregnancywomen,therearemixedresultregardingitseffecti n thec hoiceofbirthdelivery alternatives.Celik&Hotchkiss(2000)reportedthattheageofwomenatlastchildbirthwasnot significantlyassociatedwith thechoiceofdeliverylocation.O n contrary,S t e p h e n s o neta l

( 2 0 0 6 )arguedt h a t t h e a g e oft h e i n t e r v i e w e d w o m e n hadsignificantassociationwitht hechoiceoffacilitydeliveryinthestudyofsixAfricacountries.H e foundthatthewomenwith a geof40-49and30-

Inaddition,maritals t a t u s showedm i x e d r e s u l t i n t h e d e c i s i o n i n t h e b i r t h d e l i v e r y location.Stephensonetal.

Thechoiceoftheplaceofdelivery isalsohighlyinfluencedbythehouseholdlevelc haracteristics,n a m e l y h o u s e h o l d wealthi n d e x , e t h n i c i t y andreligion.W i t h respectt o t h e householdwealthindex,Stephensonetal.

(2006)foundthatwomenwithhigherhouseholdi n c o m e indexmorelikelytochoosethe deliveryathealthinstitution ratherthanthosewithlowerincomeindex.Thereasonisthatthec ostrelatedbirthdeliverycareaswellastransportationrestrictst h e p o o r w o m e n fromu t i l i z i n g t h e healthservices.Somepreviousstudiesidentifiedthatethnicityhasgreatinfluenceinthechoiceo fthefacilitydelivery.Celik

&Hotchkiss(2000)agreedthattheeffectistrueinurbanwomenandruralwomen.Hesaidt h a t i tcouldbeduetotheculturalandeconomicbarriersorthepoorofhealthcareservice.Similart o t h e ethnicity,religionalsoi s consideredast h e k e y determinanti n t h e women’sdecisionintheplaceof childbirth.WhenstudyingsixAfricacountries,Stephensonetal.

(2006)f o u n d t h a t M u s l i m womeni n Ghanaarel e s s l i k e l y t o delivert h e i r b a b y i n healt hf a c i l i t y comparedtoCatholicwomen,whileProtestantwomenmorelikelytoutilizetheservic ethanCatholicwomen.

&Hotchkiss(2000)foundthaturbanwomenweremorelikelytoseekthefacilitydelivery ratherthanruralwomen.Furthermore,Celik&

Hotchkiss(2000)saidthattheEasternregionsi n TurkeyislessadvantagedthanWesternandNo rthernregions,whichcausedmoredifficultiesforthe womeninEasternregionstochoosefa ci li t y deliverycomparedtothose l i v i n g inotherregions.Gage(2007)arguedthatthe regionaldi fferencespartlyindicatetheunequalaccessibilityandavailabilityofhealthcarefacilities.

Inaddition,somepreviousstudiesinvestigatedtheimpactofcommunitylevelcharacteri sticsinthedecisiontodeliveryathealthfacilities.Thereareseveralwaysthoughwhichthecomm unityaffectthedeliveryfacilitychoiceofwomen.Stephensonetal.

(2006)reportedthatthe community ofhigher concentrationratioofwomenw i t h highereduca tioni m p r o v e thegreaterautonomylevelandprovidemoreopportunityforthewomentoseekhealth

23 careduringpregnancyanddelivery.Furthermore,healsofoundthathigherconcentrationratioo f wom eninthecommunitydeliveringtheirbabyathealthfacilitieshadasignificantlypositiveimpactonthedecisi oninthedeliverylocation.Itsuggeststhatthepracticesofothersinthec o m m u n i t y couldaff ectthehealthseekingbehavioroftheindividualinthesamecommunity.O n e o f theimportantcommunitylevelfactorsasreportedinthestudyofSepehrietal.

(2008)i n Vietnami s communitylevelp o v e r t y r a t e Hepointedt h a t t h e c o m m u n i t y pover ty rateaffectednegativelytheprobabilityofgivingbirthathealthfacilities.Womeninthecommunityw i t h higherpovertyrateabove50%lesslikelytodelivertheirbabyathealthinstitutionsincomp arisonto thosein thecommunitywith povertyrate ofequalandlessthan10%.

Thischapterpresentst h e m e t h o d o l o g y anddatadescriptionusedt o investigatet h e deter minantsoftheutilizationofmaternalhealthcare.Thefirstpartistointroduce conceptual frameworkdescribingtheassociationsbetweenthedeterminantsandthedemandofprenatalcarevi sitsandthechoiceofdeliverycareprovidersrespectively.Next,twomethodsrelatedtot h e objectiveoft hestudy,namelytheNegativeBinomialmodelandtheMultinomialLogisticsm o d e l willbediscuss edtoanalyzetheassociationsasmentionedinthepreviouspart.Thefinalsectionpresentsthe datausedin thestudy.

Conceptualframework

Prenatal care visits and the choice of delivery care provider are influenced by individual, household, and community-level characteristics Individual factors include education level, access to mass media, employment status, marital status, pregnancy intention, and birth order Household characteristics encompass wealth index, size, ethnicity, and the religion of the household head Additionally, community-level factors affect maternal health-seeking behaviors, including residence location, poverty rate, illiteracy rate, and the proportion of women giving birth in health facilities This comprehensive framework highlights the multifaceted influences on maternal health decisions.

EducationExp ose tomassWo rking status

Figure6Theassociationbetweenindividuallevel,householdlevelandcommunitylevelcharact eristicswith theutilizationofmaternalhealthcare services

Empiricalframework

DemandforPrenatalcare

PoissonModelisappliedfordependentvariableswhicharenon- negativeinteger.Int h e model,Poissondistributionisusedtodescribethe likelihood ofeventsoccurringk timesi n a givenperiod oftime.Thedistributionfunctionis

Withtheconditionthat�i snon-negativeandmeanequaltovariance𝐸(�)=���(�)�.ThemeaningisthatwhenXchanges,howtheexpectedvalueofychanges

However,thelimitationofPoissonModelisthatthevarianceequaltothemean.The countdataisobservedthattheequalityisunreasonable,whichmeansthatthevariancemaybedifferentfr omt he mean Inorder tosolve this matter, thealternativeis NegativeBinomialregression,w hichallowsthevariancetodifferfromthemean.Ingeneral,NegativeBinomialregressionhasthesa memeanstructureasPoissonregressionandithasanextraparametertom o d e l t h e over- dispersion.T h e commandnbregi nStatai s implementedt o estimatet h e NegativeBinomialregr essionandprovidethetestofover-dispersion.

Inthestudy,thedependentvariableisnumberofmaternalcheck- upsthatapregnantwomantakes.T h e independentvariablesa r e d i v i d e d i n t o t h r e e group s:i n d i v i d u a l level,householdlevelandcommunitylevelcharacteristics.Differentfromthet heorybackground,t h e pricesofhealthcareandtheincomearenotincludedduetolimitationofthedata.T hedetailwill beintroducedin nextsection.

Choiceofbirthdeliveryfacility

MultinomialLogitModelisappliedtomeasuretherelationshipbetweencategoricalvariable sando t h e r e x p l a n a t o r y variables.M o t h e r s a r e assumedt o c h o o s e t h e f a c i l i t y t h a t maximeutility.Andthechoiceoffacilityjofindividualicodedas� �is 1,2,3…

Inthestudy,thedependentvariableisthelogoddsthatindividualiwillchosedelivery alternativej(j=2,3)relativetothereferencealternative.T h e alternative1isthedeliveryath o m e whilethealternative2and3 are respectivelydeliveryatpublichospitalsand deliveryatprivatehospitalsorclinics.Thealternative2issetupasthebaseoutcome.Inthestudy,onl yt h e characteristicsrelatedtothechooserwillbeinvestigatedbecausethedataMICS4doesnotcoverth echaracteristicsofthehealthcareproviders.Similartotheanalysisofthedemandofprenatalcarevisi ts,theindependentvariablesaredividedbythreegroups:individual,householdandcommunity.

ThecommandmlogitinStataisemployedtoestimatethemultinomiallogisticmodel.T h e i ndependentvariablesaredividedinto threegroups:individuallevel,householdlevelandc o m m u n i t y levelcharacteristics.Thedeta ils will beintroducedin next section.

Data

MICSwascarriedoutinVietNambyVietNamGeneralStatisticsOfficeincollaborationwi thUNICEF.ThesampleforVietNamMICSwasdesignedtoprovideestimatesforalargenumberofindi catorsonthenationallevelsituationofchildrenandwomeni n urbanandruralareasaswellassixgeogra phicregionsRedRiverDelta,NorthernMidlandsandMountainareas,NorthCentralareaandCentral Coastalarea,CentralHighlands,SouthEastandM e k o n g R i v e r Delta.T h e s u r v e y c o n d u c t s threes e t o f questionnaires:first,t h e questionnaireonhouseholdsto collectinformation r egardinghousehold membersandeconomicstatus;second,thequestionnairesonfemalehouseho ldmembersintheproductiveage(15-

49ages)andthelastoneisadministeredtochildrenunder5yearsandtheircaretakers.MICS5isbasedon asampleof10,018interviewedhouseholds,with9,827womenand3,316children.Forthepurposeoft hestudy,thesampleisnarroweddownintothewomenwhogaveb i r t h t o a l i v e childw i t h i n t w o yearsbeforet h e s u r v e y i n o r d e r t o reducer e c a l l errors.Therefore,thereare1,479women in theproductiveageappliedin thestudy.

Variablesdefinition

Dependentvariables

The study examines two key indicators of maternal healthcare service utilization: antenatal care coverage and place of delivery Antenatal care coverage is defined as the percentage of women aged 15–49 who had an alive birth in the two years prior to the survey and received care from skilled health personnel at least once The World Health Organization recommends that pregnant women have a minimum of four antenatal care visits throughout their pregnancy to prevent and detect health issues affecting both mother and baby Skilled personnel include accredited health professionals such as midwives, physicians, and nurses, excluding traditional birth attendants Thus, antenatal care visits are considered integral variables in assessing maternal health.

Placeofdeliveryisdefinedasdeliveryinahealthfacility(privateorpublic)oroutsidet h e healt hsystem( h o m e delivery).T h e increasedproportionofb i r t h s deliveredath e a l t h facilitiesi s a nimportantfactort o reduceh e a l t h r i s k s t o motherandbaby.P r o p e r m e d i c a l attentionandhy gienicconditionsd u r i n g deliveryc a n reducer i s k s o f complicationsand

Independentvariables

Theindividual-householdlevel,c o m m u n i t y - l e v e l e x p l a n a t o r y variableswereu s e d basedonthetheoreticalandempiricalliterature,c onsideringtheuseofmaternalhealthcareservicesandt h e i r a v a i l a b i l i t y int h e dataset.Becau set w o regressionsf o r t h e tworesearchobjectiveswillbeanalyzed,theywillsharethesamesetofinde pendentvariables.Thedetaileddescriptionofselectedvariablesisgivenbelow.

The study examines various individual-level factors that may influence maternal outcomes, including the mother's age at childbirth, birth order, education level, material status, exposure to mass media, and pregnancy intention Maternal age is treated as a continuous variable ranging from 15 to 49 years Education is categorized into five dummy variables: no education, primary, lower secondary, upper secondary, and tertiary Birth order, representing the total number of children a woman has given birth to, is also a continuous variable Material status is classified into dummy variables, indicating whether a woman is previously married but currently not in a union or never married (coded as 1), or otherwise (coded as 0) Exposure to mass media is assessed through four dummy variables based on access frequency to mobile phones, newspapers, radio, and television Lastly, pregnancy intention is recorded as 1 if the woman did not wish to be pregnant and 0 otherwise.

Householdlevelfactorsinclude ethnicityandreligionofhouseholdhead,householdw ealths t a t u s E t h n i c i t y wasdefinedo n eitherK i n h o r H o a ( = 1 ) o r non-Kinh/

Hoa( = 0).Althoughtheyarethe sixthlargestminoritygroupin VietNam,theirlivingstandardsareon aparwiththoseoftheKinhmajority.Thereligionvariableisusedasadummyvariable:1ifthehousehold hasn o r e l i g i o n and0 otherwise.T h e h o u s e h o l d wealths t a t u s alsoi s dummyvariable:

1 if thehousehold is in thepoorestor poorquintilesand0otherwise.

Inadditiontoindividualandhouseholdlevelfactors,communitylevelfactorsareaddedt o meas ureanyeffectinc o m m u n i t y level.First,p l a c e o f residencei s dividedi n t o t w o categories:urbancodedas1 andruralas0 Moreover,si xregionald u m m i e s represents i x socioeconomicregi onssuchasRedRiverDelta,NorthernMidlandsandMountainareas,North

CentralareaandCentralCoastalarea,CentralHighlands,SouthEastandMekongRiverDelta.Second,i lliter acy rateis basedonpercentageof illiteratewomeninthe community.Third, p o v e r t y r ateiscalculatedaspercentageofwomeninthecommunenthelowestwealthquintile.Finally,theperce ntageofthewomeninthecommunitydeliveringtheirbabyathospitalsisapplied.

ANC Number of antenatal carevisits visits

NOEDU Dummyvariableindicatingtheindividual hasnotfinished primaryschool Yes=1,No=0

PRIMARY Dummyvariableindicatingtheindividual finished primaryschool Yes=1,No=0

LOWSECOND Dummyvariableindicatingtheindividual finishedlowersecondaryschool Yes=1,No=0 UPSECOND

Dummyvariableindicatingtheindividual finished upper secondaryschoolDummyvariableindicatingtheindividual finishedthecollegeabove

Yes=1,No=0 Yes=1,No=0 Yes=1,No=0

CEB Number of childreneverborn children

NEWSPAPER WhetherthewomanreadsNewspaperor Magazineeveryday Yes=1,No=0

RADIO Whetherthewomanlistenstoradio everyday Yes=1,No=0

TV WhetherthewomanwatchesTV everyday Yes=1,No=0

UNWANTED Whetherthewomanwanted thelast child No=1,Yes=0

POOR Whetherwomenbelongtothepoorestand poorquintilesgroup Yes=1,No=0

ETHNIC Whetherthehouseholdheadbelong totheethnicminoritygroup Yes=1,No=0

RURAL Whetherthewomenliveinrural area Yes=1,No=0

MN NorthernMidlandsand MountainousArea Yes=1,No=0

CH Central Highlands Yes=1,No=0

SE South East Yes=1,No=0

MD MekongRiver Delta Yes=1,No=0

POVERTY Percentageofwomenwithpoorestandthe2nd quintileinthecommune percentage(%)

HOSPDELIRATIO Percentageofwomeninthecommunegiving birththelast child at hospitals percentage(%)

Thec h a p t e r presentst h e resultso f s t u d y t o reportt h e relationshipsbetweendetermina ntsandthedemandofprenatalcarevisitsandthechoiceofdeliverycareprovidersrespectively.T h e firstp a r t i s t o presentd e s c r i p t i v e statisticso f dependentvariablesandindependentvaria bles.Thefollowingpartistoanalyzethebivariateassociationsbetweeneachdependentvariableandinde pendentv a r i a b l e s T h e finali s t o demonstratet h e regression analysisregardingthedemandofprenatalcarevisitsandthechoiceofdeliverycareaswellast h e compa risonbetweentheresultwith theonesofpreviousstudies.

DescriptiveResults

ThesamplesummarystatisticsareshownintheTable2andTable3.Inthefirsttable,i t canbese enthatthereare1479womenreportedthatundergochildbirthinthelast2years.T h e averageof prenatal carevisits is

According to WHO guidelines, pregnant women should have at least four antenatal care visits to ensure a safe pregnancy and fetal development The average age of women in this group is 28, with ages ranging from 15 to 47 On average, these women have two children, aligning with Vietnam's two-child policy, although some women from rural areas have had as many as 11 children Alarmingly, in communities with the lowest household wealth, 100% of women may not have their basic needs met, and over half of the women in some areas are illiterate, lacking even primary education.

Table 3 presents descriptive statistics for dummy variables related to women's delivery choices Most women prefer to give birth in government hospitals or community health centers to ensure safe childbirth, although 136 cases indicate a preference for home deliveries Among the interviewed women, 35% completed lower secondary education, followed by upper secondary, tertiary, primary, and 6% with no education Additionally, 3% reported being previously married or never married, while nearly 20% experienced unintended pregnancies and were not employed In terms of media exposure, women predominantly watch television and read SMS messages more than they read newspapers or listen to the radio Television and mobile phones are widely used in Vietnam for accessing current affairs and facilitating quick communication.

Therearemorethan40%ofwomenlivinginthepoorestandpoorhouseholdwealthquinti lesandapproximately24%ofthosebelongingtotheethnicgroup.Mostofhouseholds inwhichthewomenlivedonotfollowanyreligion.ItisobviouslycommonthatVietnamesefamilie stend to worship theirancestors.However,consideringthereligion,Buddhismmakesu p thehighestratio,followed byChristianCatholic.Residentiallocationisoneofthemostimportantfactorsintheutilizationo fmaternalhealthcare.Mostofinterviewedwomenarel i v i n g intheruralareas,whichdonotha veheathcarecenteradequatelyandlessdevelopedeconomicconditionthanurbanareas.Howeve r,thereisnoobviousdifferenceinthenumbero f womenlivingin sixsocio-economicregions.

Variable Obs Mean Std.Dev Min Max

Analysis ofDemandforprenatalcare

Bivariateanalysis

TheTable4providesthebivariateresultsregardingtheassociationbetweenthenumbero f prenat alcarevisitswitheachsocialdeterminant.Concerningthehighestlevelofeducationwhatthewomenc ompleted,itcanbeseenthatthereislargedifferenceamongthosewhohasn o educationalcertificatea ndlittlevariationamongthehighereducatedwomen.Thosewithouteducationalcertificatehavethenumber ofvisitslowerby3prenatalcarevisitsthanthosehavehighereducationcertificates.Inaddition,thediffer encesamongthoseinrural,poorhouseholdwealthquintileandethnicgroupappeartoberemarkable.The disadvantagedwomenlesslikelygetaccesst o t h e p r e n a t a l care.Further,in t h e d e v e l o p e d regio nssuchasRedR i v e r Delta,

MekongRiverDeltaandSouthEast,theprobabilityofusingtheprenatalcareisslightlyhighert h a n theles sdevelopedregionssuchasCentralHighlandaswellasNorthernMidlandsandMountainousArea.Inc ontrast,thereislittlevarianceinthedemandofmaternalhealthcaref o r w o r k i n g womenand religiouswomen.Lookingatt h e Figure9 i t i s illustratedt h a t t h e likelihoodofutilizingmaternalhe althcaredecreaseswiththeageofwomen,thenumberofchildreneverbornandtheilliteracyrateo f the communityin which thewomen live.

ANC Observation Mean Std.Dev Min Max

Mobilephone re ca l at an et na d ve i c e re s me i T

Figure7:T h e associationbetweent h e demando f maternalc a r e v i s i t s a n d numericalinde pendentvariables

Analysis ofNegative BinomialModel

Firsto f all,t h e r e g r e s s i o n t e s t s t h e likelihoodratio,estimatingwhetherdispersionp arameteralphai s e q u a l t o z e r o T he te st statisticw it h p - v a l u e n e a r z er o suggestst h a t t h e responsevariableisover- dispersedsotheNegativeBinomialmodelispreferredtoPoisson m o d e l asshowninAppen dix6.Next,theregressionisrunwithrobustinordertosolvewithth e heteroscedasticity.Theresults ofNegative Binomialmodelaredescribed inTable5.

ThestudyfindsthatthevariableAGEhasacoefficientof0.016,whichisstatisticallysignific antwithp-valuenearzero.Concerning marginaleffect,itcouldbeinterpretedthattheincreaseoftheageby1yearwillleadtotheincreaseofpre natalcarevisitsby0.08.Itmeanst h a t thehighertheageofthewomanis, themore frequentlytheytakematernalcarevisit.TheresultisinconsistentwiththestudyofArthur(2012)and

Tsawe&Susuman(2014).Itcouldb e e x p l a i n e d t h a t t h e p r e g n a n c y women arewell- informedaboutt h e p o t e n t i a l r i s k s d u r i n g pregnancyatthehigherage.

Regardingtheeducationattainment,similartothestudies(Arthur2012,Bbaale2011,Nava neetham&Dharmalingam2002),thesignificantcoefficientsofnoeducation,primaryandlowers e c o n d certificatesuggestst h a t t h e r e areo b v i o u s differencesbetweent h e lower educationholdersandhighereducationholdersi n t h e demando f prenatalcarev i s i t s T h e margin aleffectc o e f f i c i e n t s h o w s t h a t t h o s e w i t h o u t n o certificatecomparedtot h o s e w i t h t e r t i a r y certificate,whileholdingtheothervariableconstantinthemodel,areexpectedtohavea rateof1. 67timeslowerinnumberofprenatalcarevisits.Comparedtothetertiarycertificateholder,thosewithpri maryandthosewithlowersecondareexpectedtohavearateof0.76and

4.98timesrespectivelylowerinthenumberofprenatalcarevisits.Incontrast,thereisnogreatdifference betweentheuppersecondcertificateholderandthe tertiaryholder.

Concerningtheexposuretomassmedia,theresultshowsthatonlythecoefficientoff r e q u e n c y ofreadingnewspaperandmagazinesisstatisticallysignificant.Withmarginaleffecto f 0.39 ,thedifferenceinnumber ofprenatalcare visits is higher0.39 times forthosewhoreadingn ewspaperandmagazineseverydaycomparedtothosewholessreadnewspaperornotreadatall.T h e coe fficientso f f r e q u e n c y ofr e a d i n g S M S messages,l i s t e n i n g t o radioandw a t c h i n g TVar enot statisticallysignificant.

(2013),thecoefficientofunwantedpregnancyisnots t a t i s t i c a l l y significant.Similarly,t h e coefficiento f w o r k i n g s t a t u s alsoi s n o t s t a t i s t i c a l l y significant.

Thecoefficientofnon- unioninmaritalstatusishighlysignificantwiththenegativeparameter,whichconfirms theresultsfromthestudiesofSepehrietal.(2008)andChenetal.

(2003).Thenegativesignmeansthatthewomenwholivewiththeirhusbandnolongerorbeneverma rriedlesslikely1.16timestakeprenatalcarevisitcomparedtothosewhoarelivingw i t h theirhusb and.Itcouldbeindicatedthatsingleexpectantmotherfacesthedisgracewhent a k i n g maternalch eckupatpublicbecausethechildbirthisconsideredastheresultofmaritalrelationship.

Inaddition,thecoefficientofbirthorderishighlystatisticallysignificantwithp- valuealmostzero.Thenegativecoefficientshowsthatwomenhavingonemorechildtendtohavet h e numberofvisitslowerby0.52.Thisisattributedtoburdenofchildrenthatthewoment a k i n g careofsoshedoestakeprenatalcheck- upfrequently.Theresultissimilartothestudieso f Navaneetham&Dharmalingam(2002),Sepehrie tal.(2008),Arthur(2012)andTsawe&Susuman(2014).

Theresultindicatesthatthecoefficientsoflivinginpoorhousehold,belongingtoethnicm i n o r i t y groupandnotfollowinganyreligionarestatisticallysignificantwhereastheonesofhousehol dsizeisnotsignificant.Itisremarkablethatthewomenfromthepoorandpoorestquintilesappear tohavethenumberofvisitslowerby1.1comparedtothoseinotherquintiles.D u e tofinancialproblems ,thewomenfinddifficulttoaffordthecostofprenatalcareaswellastransportationcosts.Thestudysu pportsthehypothesisofthestudies(Bbaale2011,Tsawe

SimilartothesestudiesofCelik&Hotchkiss(2000),Navaneetham&Dharmalingam(2002) andSepehrieta l

(2008),t h e womanw h o s e h o u s e h o l d h e a d belongst o t h e ethnicm i n o r i t y grouphas0.6 visitslessthanthoseinKinhorHoagroup.Languagebarrierandculturedifferencesprobablypreventtheet hnicgrouptomakeuseofprenatalcarevisits.Similarly,thewomanw h o s e householdheaddoesn o t f o l l o w a n y religionhasp o s i t i v e influenceo n t h e demandofprenatal carevisits with themarginaleffectof0.3.Itindicatesthatreligiousnormsandpracticesofthehouseholdheadpreven tthewomeninthereligiousgroupfromutilizingt h e prenatalc a r e v i s i t s T h e s t u d y reconfirm st h e resultfromBbaale( 2 0 1 1 ) andTsawe& Susuman(2014).

The study highlights the significant impact of community-level variables on maternal health, particularly the proportion of women without education and those delivering in hospitals Consistent with Gage's (2007) findings, expectant mothers in communities with higher literacy rates have 0.05 more prenatal care visits compared to those in lower literacy areas Additionally, a higher hospital delivery ratio positively influences the demand for antenatal care, with women in communities with better hospital access having 0.03 more visits This underscores the importance of community practices on women's health attitudes and care-seeking behavior, corroborating the research by Ononokpono et al (2013).

Furthermore,thereisgreatregionaldisparityinutilizationofprenatalcarevisits,whichi s thesa meresultasCelik& Hotchkiss(2000)andSepherietal.

(2008).ResidenceintheunderdevelopedareassuchasCentralCoast,CentralHighlandaswellasNo rthernMidlandsandMountainousAreafarlesslikely1.05,0.76and0.71timesrespectivelytota keprenatalcarev i s i t s f r e q u e n t l y comparedt o residencei n MekongDeltaareas.However,t h e r e i s n o s t a t i s t i c a l l y significantdifferencebetweenlivinginSouthEastareasandMekong RiverDelta.Itimpliesthatthereareremarkeddifferencesintheimplementationofhealthcareprogram,t hea v a i l a b i l i t y andaccessibilityofthehealthcare servicesamongtheregions.

MOBIPHONE(using mobile phone every day=1) 0.047 (0.030) 0.239 (0.157)

Analysis ofChoiceinthedeliverycareproviders

Bivariateanalysis

Table6presentstheassociationbetweenthechoiceof deliveryfacilityandcontinuousindependentvariables.Itcanbeseenthatthewomenwithhigherbir thordermorelikelytochoose childbirthathomethanthosewithlowerbirthorder.Inaddition,thehigheraverageofp o v e r t y ra teandilliteracyratefocusonthewomengivingbirthathomewhereasthewomendelivering childathomelivesin thecommunitywithlowerratioof facilitydelivery.

Obs Mean Std.Dev Min

Table 7 illustrates the relationship between the choice of delivery care providers and various independent variables Delivery locations are categorized into three types: home delivery, public hospitals, and private hospitals Home delivery is the most affordable option but often lacks hygiene and medical equipment Public hospitals, funded by the government, offer low-cost services but are frequently overloaded In contrast, private hospitals or clinics provide better services with advanced technology, albeit at a higher cost Notably, women choosing home childbirth have less exposure to mass media, such as mobile phones, television, and newspapers, compared to those delivering in health facilities The likelihood of home childbirth increases among women in disadvantaged areas with higher poverty and illiteracy rates, such as the Central Highlands and North Mountainous regions, due to limited access to healthcare centers and poor infrastructure Interestingly, many women delivering at home had been working for two years prior to the interview, often in low-paying agricultural jobs, which restricts their ability to afford healthcare costs and limits their access to health facilities Additionally, women with higher living standards and those from ethnic majority households are more likely to give birth in private hospitals, while rural women are less likely to access these facilities, as most private hospitals are located in urban or developed regions and offer expensive services.

Analysis ofMultinomialLogisticModel

Theresult of estimatedmultinomiallogisticregressioncoefficientsf o r themodelis pres entedinTable8andmarginaleffectshowninTable9.Thereferencegroupisthegroupw h o choset odeliverinpublichospital.Thesignofcoefficientsshowsthepositiveornegativerelationshipbetweeni ndependentvariablesandthelikelihoodofchoosingchildbirthathomeo r atp r i v a t e h o s p i t a l s r e l a t i v e t o d e l i v e r y atp u b l i c h o s p i t a l w h i l e t h e marginaleffecti s interpretedas howanincreaseintheindependentvariableaffectstheprobabilityofchoosingd e l i v e r y ath o m e o r d e l i v e r y atprivateclinicso r h o s p i t a l s r e l a t i v e l y t o d e l i v e r y atp u b l i c h o s p i t a l , givent h e o t h e r variableconstant.T h e variablehospdeliratioi s omittedbecausecollinearit y

Itcanbeseenthathousehold- levelcharacteristics,namelylivinginpoorhouseholdsandinethnicminoritygrouprarehighlystatisti callysignificantwithp- valuenearlyzero,livingi n thepoorandinethnicgroupisfoundtoincreasethelikelihoodofchildbirthat homerathert h a n atpublichospitals.Itindicatesthatfinancialdifficultiesaswellaslanguageandc ulturebarrierconstraintsthepregnantwomentowillinglygivebirthathealthfacilities.Theresult saffirmthepreviousstudiesofCelik&Hotchkiss(2000),Stephensonetal.(2006)andWadoeta l

(2013).Unexpectedly,t h e householdheadf o l l o w i n g n o religioni s n o t significantlyassociate dwiththechoiceofdeliveryathome,whichisdifferentfromStephensonetal.

(2006).Inrespecttothemarginaleffect,livinginthepoorandinethnicminoritygroupincreasethe p r o b a b i l i t y ofgivingb i r t h ath o m e by0 0 8 % a n d 0 0 7 % r e s p e c t i v e l y ; however,th eya r e s t a t i s t i c a l l y insignificant.

Inaddition,someindividuallevelcharacteristicsalsoaffectconsiderablythechoiceofd e l i v e r y l o c a t i o n Similart o Navaneetham& Dharmalingam(2002),t h e negativesignso f l i s t e n i n g toradioorreadingnewspaperregularlycould bereportedtobenegativelyassociatedw i t h theprobabilityforchildbirthathome.Itcouldbeexplainedthat frequentexposuretomass

45 mediaincreasetheknowledgeregardingthematernalhealthservicesandenhancetheawarenesso fneedforcareofdelivery.Inrespecttomarginaleffect,listeningtoradioandreadingnewspaper decreasethe probabilityofgivingbirthathomebyaround0.03percentagep o i n t s Inaddition,themarginaleffe cto fnumber ofprenatalcarevisits is -

0.0002,whichmeansthatthenumberofprenatalcaredecreasetheprobabilityfordeliveryathom eby0.02percentagep o i n t s , h o l d i n g allo t h e r variablesc o n s t a n t andt h e effecti s h i g h l y s t a t i s t i c a l l y significant.ManypreviousstudiessuchasStephensonetal.(2006),Sepehrietal.

(2013)alsoshowedthesameresult.I n contract,themarginaleffectofthenumbero f childreneverborn is0.0001couldbeinterpretedthatforthewomenhas onemorechildren,t h e probabilityofdeliveryathomeincreaseby0.01percentagepoints.Thear gumentisthatfrompreviousexperience,womenwithhighbirthorderunderestimatetheneedofdeli veryathealthfacilitiesortheyhavegreaterconstraintstousetheservices(Navaneetham&Dharm alingam2002,Stephensonetal.2006andSepehrietal.2008).Itissurprisingthatageandeducationatt ainmentaren o t significantlyassociatedw i t h t h e choiceo f deliveryp l a c e alternatives.

Concerningthecommunitylevelcharacteristics,livinginruralareashassignificantlyp o s i t i v e influenceinthedecisiontotheplaceofdeliveryathome,whichissimilartothestudieso f Celi k&Hotchkiss(2000)andGage(2007).Themarginaleffectof0.0003indicatesthatl i v i n g i nruralareasincreasetheprobabilityofgivebirthathomeby0.03percentagepoints.Moreover,the concentrationratioofthewomenwithnoeducationcertificatearefoundtobes i g n i f i c a n t l y positivelyassociatedwiththechoiceofchildbirthathometochildbirthatpublich o s p i t a l

Theresultshowsthatonlytheestimatedcoefficientsofworkingstatus,residenceinrura landpoorhouseholdarestatisticallysignificantwithp- valuenearzero.Itcouldimplythatthereisnosomuchgreatdifferencedeterminedbydemographic factorsin thechoicebetweenp u b l i c hospitalandprivatehospital.Indetail,themarginaleffectoflivin ginpoorhouseholdi s -

0.0012,livinginruralareadecreasetheprobabilityofdeliveryatprivateh o s p i t a l s by0.12pe rcentagepoints.Inaddition,thereareregionaldifferences in thechoiceofd e l i v e r y atprivatehospital.ComparedtoMekongRiverDelta,livinginthetwore gionssuch asNorthCentralandSouthEastdecreasestheprobabilityforgivingbirthatprivatehospitalsby0.12 and0.1percentagepointsrespectively.Itisobviouslyseenthattheprivatehospitalsareonlyavail ableintheurbanareasandthedevelopedregionsandthecostofdeliverycareinprivatehospitalsishigher thanoneof thepublichospitals.

CEB(numberofchildren) Household- levelCharacteristics HHSIZE(numbero fmembers)

NORELI(followingnoreligion=1) Com munity- levelCharacteristics RURAL(livinginru ralarea=1)

Marginal effect Marginal effect Marginal effect

Thislastchaptersummarizesallthemainfindingsintheresearch.Basedontheseconclusions,i t w i l l d i s c u s s andrecommendrelevantpolicies.Finally,limitationsof the studyanddirectionf o r furtherstudiesarediscussed.

Mainfindings

2014andtwomethods,i n c l u d i n g t h e NegativeBinomialModelandM u l t i n o m i a l Logis ticModel,t h e s t u d y h a s investigatedthedeterminantsofthedemandofprenatalcareandthec hoiceofbirthdeliveryfacility,namelyindividuallevelcharacteristics,householdlevelcharacteristic sandcommunitylevelcharacteristics.

Prenatal care demand is influenced by various individual, household, and community factors Key individual determinants include women's age, education level, marital status, and number of children Studies have shown that higher education significantly enhances prenatal care utilization, as educated women are more autonomous and aware of healthcare benefits Additionally, community illiteracy rates correlate strongly with maternal healthcare usage Women from lower household wealth and ethnic minority groups are less likely to seek adequate health check-ups compared to those in higher socioeconomic statuses Support from family is also crucial; unmarried or separated women and those with more children often face challenges in accessing prenatal care due to increased burdens and lack of support Furthermore, there are significant regional disparities in prenatal care utilization, with residents in disadvantaged areas, such as the Central Highlands and North Mountainous regions, being less likely to access maternal health check-ups compared to those in more prosperous areas.

The choice of birth delivery place is significantly influenced by individual, household, and community characteristics Individual factors, such as the number of prenatal care visits and exposure to mass media, negatively affect the preference for home delivery over public facilities, while having more children increases the likelihood of choosing home delivery However, individual characteristics do not significantly differentiate between public and private hospital deliveries At the household level, living in poverty and belonging to an ethnic minority strongly impact delivery location decisions; women from poorer households and ethnic minorities tend to prefer home births over public hospitals, although poorer women are more likely to deliver at public hospitals than private ones These findings align with previous studies by Navaneetham & Dharmalingam (2002), Stephenson et al (2006), and Celik & Hotchkiss (2000).

(2013).Finally,thereisconsiderabledifferenceint h e availabilityandaccessibilityofthehea lthfacilitiesbetweenruralandurbanareas.Ruralwomenmorelikelytogivebirthathomecomparedto publichospitalsandatpublichospitalscomparedtoprivatehospitals.Thematterhadbeenalsore portedinVietnam(Sepehrietal.2 0 0 8 )andotherdevelopingcountries (Celik & Hotchkiss2000andGage2007).

PolicyRecommendation

Theresultsp r o v i d e s o m e p o l i c y recommendation.Firstly,t h e importanceo f educations h o u l d behighlightedinindividualcharacteristics,especiallytheilliteracyrateinthetwotypeso f mat ernalhealthcare.Itmeansthatthepracticesofthewomenwithhigheducationalsoaffectt h e behavioro fotherwomeninthesamecommunity.Therefore,educationreformsshouldbeconductedextensivel ytoreducepotentialbarrierandensurethefulluniversalofprimaryandsecondeducationforallpeop le,especiallywomen.Thehigheducationattainmentenhancest h e women’sautonomy andt heirrolesinthe family inorder toseekthebestcarefortheir health.

Secondly,t h e maternalhealthcareinterventionss h o u l d reduced i s p a r i t i e s i n healthcareuti lizationinethnicsgroup.TheethnicminoritygroupsliveinremoteandmountainousareassuchasCen tralHighland andNorthernMidlandsandMountainousArea.Therefore,livingfara w a y fromt h e h o s p i t a l al ongw i t h underdevelopedinfrastructure,theyfeeldifficultt o getaccesstothehealthfacilitiesforpre natalcareandchildbirth.Inaddition,duetolanguageand

50 culturebarrier,theethnicsgroupcannotcommunicatewellwithhealthproviderandevenmayb e discri minated(Malqvistetal.2012)

Thirdly,theprenatalcarevisitisfoundtobeoneofthemostimportantdeterminantsinthechoiceofd e l i v e r y l o c a t i o n Therefore,t h e p r e n a t a l c a r e i n t h e h e a l t h facilitiess h o u l d b e e f f e c t i v e l y conductedtoobtainthetrustofthepregnantwomenandtheirfamily.Furthermore,appropri atecounselingshouldbeofferednotonlyforwomenbutalsootherfamilymembers.Becausetheap propriateadviceinprenatalcarescouldraiseawarenessofbenefitsofsubsequentserviceu s e aswel last h e p o t e n t i a l r i s k s d u r i n g p r e g n a n c y andchildbirth,t h e womanandherfamilycoul dbeencouragedtochoosethedeliveryathealthfacilitiesinsteado f d e l i v e r y athome.

Fourthly,theinfrastructuredevelopmentispaidgreaterattentionincommunitylevel.Thegover nmentshouldintensifythematernalhealthprogramandprovidethehealthfacilitiesinremotean dmountainousareas.Byapplyingthevariousmeansofcommunicationsuchasradio,televisionandnews papertheresidentsintheseareascouldeasilygetinformationregardingthebenefitsofprenatalcareandfacilit ydeliveryaswellasgetaccesstohealthfacilities.Moreover,t h e roadandp u b l i c t r a n s p o r t a t i o n me anss h o u l d b e upgradedt o removet h e difficultieso f travelingt o t h e healthfacilitiesandencoura get h e residentst o utilizethematernalhealthservice.

LimitationandFurtherResearch

This research has several limitations Firstly, the data on antenatal care utilization and place of delivery is prone to recall errors, as women may not accurately remember the number of prenatal visits or when they first sought care However, the study mitigated these errors by focusing on women who delivered their babies two years prior to the interview Additionally, certain factors, such as pregnancy complications, which could affect the number of prenatal visits and delivery location, were not observed due to data limitations Community practices and cultural influences also significantly impact maternal healthcare-seeking behaviors and delivery decisions Since community variables are derived from aggregated individual-level data, discrepancies may arise compared to lower-level data Lastly, including prenatal care visits in the facility choice regression may introduce endogeneity, which this study has not addressed Therefore, further research is necessary to address these limitations.

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Variable Obs Mean Std.Dev Min Max

Variable Obs Mean Std.Dev

The data reveals significant variations across different delivery metrics For AGE, the average ages are 26.43, 27.68, and 28.08 for deliveries 1, 2, and 3, respectively In terms of CEB, delivery 1 shows an average of 2.78, while deliveries 2 and 3 have averages of 1.75 and 1.76 HHSIZE averages are 6.61, 5.67, and 5.65 across the three deliveries The POVERTY levels indicate a stark contrast, with delivery 1 at 87.40, delivery 2 at 35.44, and delivery 3 at 29.13 Illiteracy rates are notably high in delivery 1 at 39.73, dropping significantly to 4.35 and 4.36 in deliveries 2 and 3 Lastly, the HOSPDELIRATIO shows a dramatic increase from 29.81 in delivery 1 to 96.93 in delivery 2, with delivery 3 reaching 98.12.

Variable Obs Mean Std.Dev Min Max

Variable Obs Mean Std.De v Min Max

Appendix5:T h e associationbetweenthedemandofmaternalcare vi si ts and numericalinde pendentvariables

>E POORETHNICNORELIRURALPOVERTYILLITERACYhospdeliratioRRDNMNCCHSEMD note:TERTIARYomittedbecauseofcollinearitynote:MD omittedbecauseofcollinearity

ANC Coef Std.Err z P>|z| [95%Conf.Interval]

Likelihood-ratiotestofalpha=0:chibar2(01)= 87.67Prob>=chibar2= 0.000

=5.0515799 variable dy/dx Std.Err z P>|z| [ 95%C.I ] X

AGE 0808842 01791 4.52 0.000 045774 115994 27.5842NOEDU* -1.670329 43445 -3.84 0.000 -2.52184 -.818817 060176PRIMARY* -.7639974 24053 -3.18 0.001 -1.23543 -.292565 13455LOWSEC~D* -.490159 20498 -2.39 0.017 -.891903 -.088415 344828UPSECOND* -.2702806 17973 -1.50 0.133 -.622539 081978 233942MOBIPH~E* 2393492 15673 1.53 0.127 -.067832 546531 273158NEWSPA~R* 3853626 18374 2.10 0.036 025243 745482 192698RADIO* -.307939 1898 -1.62 0.105 -.679945 064067 121704TV* -.0706393 23625 -0.30 0.765 -.533684 392405 834348MARITAL* -1.165153 41725 -2.79 0.005 -1.98295 -.347358 027045UNWANTED* -.3054536 18475 -1.65 0.098 -.667562 056655 177823WORKING* -.111988 19738 -0.57 0.570 -.49885 274874 824882CEB -.526979 10892 -4.84 0.000 -.740463 -.313495 1.84314HHSIZE -.0123077 03265 -0.38 0.706 -.076309 051694 5.75321POOR* -1.080706 23102 -4.68 0.000 -1.5335 -.62791 421231ETHNIC* -.5715099 2478 -2.31 0.021 -1.05719 -.085831 236646NORELI* 3050419 16018 1.90 0.057 -.008902 618986 745098RURAL* -.2449753 16931 -1.45 0.148 -.576808 086857 62407POVERTY -.0035125 0041 -0.86 0.392 -.011548 004523 39.9499ILLITE~Y -.0501067 01199 -4.18 0.000 -.073606 -.026608 7.60748 hospde~o 0303695 00729 4.16 0.000 016073 044666 90.8046RRD* -.5180725 25484 -2.03 0.042 -1.01755 -.018598 152806NM* -.7165916 26996 -2.65 0.008 -1.2457 -.187479 189317NC* -1.059297 21455 -4.94 0.000 -1.47981 -.638784 149425CH* -.7608472 24568 -3.10 0.002 -1.24237 -.279329 208249SE* 2804522 26002 1.08 0.281 -.229187 790091 163624(*)dy/dxisfordiscretechangeofdummyvariablefrom0to1

>CEBHHSIZEPOORETHNICNORELIRURALPOVERTYILLITERACYRRDNMNCCHSEMD,robust note:TERTIARYomittedbecauseofcollinearitynote:MDo mittedbecauseofcollinearityIteration0: logpseudolikelihood=-708.35443

ANC 0435657 0329205 1.32 0.186 -.0209573 1080886 AGE -.032046 0336321 -0.95 0.341 -.0979637 0338716 NOEDU 5487294 8578957 0.64 0.522 -1.132715 2.230174 PRIMARY -.5984313 5340849 -1.12 0.263 -1.645218 4483558 LOWSECOND -.7018067 3990452 -1.76 0.079 -1.483921 0803074 UPSECOND -.269463 358309 -0.75 0.452 -.9717358 4328098

TV -.3248382 4126861 -0.79 0.431 -1.133688 4840116 MARITAL -.474224 1.093957 -0.43 0.665 -2.61834 1.669892 UNWANTED -.0265002 3924757 -0.07 0.946 -.7957384 742738 WORKING -.5619982 3171955 -1.77 0.076 -1.18369 0596934 CEB 2349459 2036672 1.15 0.249 -.1642344 6341262 HHSIZE -.0421632 0719171 -0.59 0.558 -.1831181 0987916 POOR -.9170955 4792335 -1.91 0.056 -1.856376 022185 ETHNIC -.1205223 4615013 -0.26 0.794 -1.025048 7840037 NORELI 4736594 3281441 1.44 0.149 -.1694912 1.11681 RURAL -.6398772 2979514 -2.15 0.032 -1.223851 -.0559031 POVERTY 007296 0083815 0.87 0.384 -.0091314 0237235 ILLITERACY 0046362 0187234 0.25 0.804 -.0320609 0413334 RRD -2.097738 5949775 -3.53 0.000 -3.263873 -.9316039

Marginaleffectsaftermlogit y= Pr(DELIVERY==1)(predict,poutcome(1))

=.00031878 variable dy/dx Std.Err z P>|z| [ 95%C.I ] X

ANC -.0001634 00006 -2.61 0.009 -.000286 -.000041 5.71941 AGE -4.25e-06 00001 -0.41 0.684 -.000025 000016 27.5842 NOEDU* 0004249 00062 0.68 0.494 -.000791 001641 060176 PRIMARY* 0001634 00035 0.47 0.637 -.000514 000841 13455 LOWSEC~D* -.0001505 00023 -0.65 0.514 -.000602 000301 344828 UPSECOND* -.0001815 00021 -0.86 0.388 -.000594 000231 233942 MOBIPH~E* -.0003431 00022 -1.54 0.123 -.000779 000093 273158 NEWSPA~R* -.0033406 00174 -1.92 0.054 -.006742 000061 192698 RADIO* -.0002605 00014 -1.81 0.070 -.000542 000021 121704 TV* -.0001644 00015 -1.10 0.271 -.000457 000128 834348 MARITAL* -.0001417 00014 -1.01 0.311 -.000416 000133 027045 UNWANTED* 0000416 00014 0.29 0.769 -.000236 000319 177823 WORKING* 0001389 00011 1.26 0.208 -.000077 000355 824882 CEB 000119 00008 1.57 0.117 -.00003 000268 1.84314 HHSIZE -.0000252 00002 -1.20 0.230 -.000066 000016 5.75321 POOR* 0008473 00058 1.47 0.141 -.000281 001975 421231 ETHNIC* 0006663 00042 1.58 0.114 -.00016 001492 236646 NORELI* 0000906 0001 0.88 0.378 -.000111 000292 745098 RURAL* 0002581 00018 1.45 0.146 -.00009 000606 62407 POVERTY -4.77e-06 00000 -1.03 0.304 -.000014 4.3e-06 39.9499 ILLITE~Y 8.30e-06 00001 1.65 0.098 -1.5e-06 000018 7.60748 RRD* 0009084 00113 0.80 0.423 -.001316 003132 152806 NM* 001187 00124 0.96 0.337 -.001237 003611 189317 NC* 0013201 0015 0.88 0.378 -.001612 004253 149425 CH* 0012689 00129 0.98 0.327 -.001268 003806 208249 SE* 0008003 00096 0.84 0.402 -.001072 002672 163624 (*)dy/dxisfordiscretechangeofdummyvariablefrom0to1

Marginaleffectsaftermlogit y= Pr(DELIVERY==2)(predict,poutcome(2))

=.99800811 variable dy/dx Std.Err z P>|z| [ 95%C.I ] X

ANC 0000904 00008 1.10 0.272 -.000071 000251 5.71941AGE 0000578 00006 1.01 0.313 -.000054 00017 27.5842NOEDU* -.0016039 00244 -0.66 0.510 -.006377 00317 060176PRIMARY* 0006525 00069 0.94 0.347 -.000708 002013 13455LOWSEC~D* 0012234 00063 1.94 0.052 -.000013 00246 344828UPSECOND* 0006015 00057 1.06 0.287 -.000507 00171 233942MOBIPH~E* -2.26e-06 00063 -0.00 0.997 -.001242 001238 273158NEWSPA~R* 0032791 00183 1.79 0.073 -.000306 006864 192698RADIO* 000098 0007 0.14 0.889 -.00128 001476 121704TV* 0007713 00088 0.88 0.381 -.000956 002498 834348MARITAL* 0007809 00118 0.66 0.508 -.001532 003094 027045UNWANTED* 2.32e-06 00067 0.00 0.997 -.001303 001308 177823WORKING* 0010022 00079 1.27 0.202 -.000539 002543 824882CEB -.0005112 00036 -1.42 0.156 -.001217 000194 1.84314HHSIZE 0000956 00012 0.78 0.433 -.000144 000335 5.75321POOR* 0006292 00095 0.66 0.510 -.001242 0025 421231ETHNIC* -.0004701 00085 -0.56 0.578 -.002128 001188 236646NORELI* -.0008017 00047 -1.71 0.087 -.001721 000117 745098RURAL* 0009188 00062 1.47 0.141 -.000304 002142 62407POVERTY -7.42e-06 00001 -0.50 0.614 -.000036 000021 39.9499ILLITE~Y -.000016 00003 -0.50 0.614 -.000078 000046 7.60748RRD* 0011125 0012 0.93 0.355 -.001244 003469 152806NM* 0450928 00761 5.92 0.000 030173 060013 189317NC* -.0001213 00155 -0.08 0.938 -.003159 002916 149425CH* -.0006039 0014 -0.43 0.666 -.003343 002135 208249SE* 000242 00107 0.23 0.821 -.001854 002338 163624(*)dy/dxisfordiscretechangeofdummyvariablefrom0to1

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