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 addressed through effective healthcare interventions like antenatal and delivery care, as highlighted by the WHO's Safe Motherhood package introduced in 1994 Antenatal care offers pregnant women and their families essential information about maternal health and fetal growth, enabling them to make informed dietary choices to prevent low birth weight Regular check-ups during this period help identify danger signs and risks associated with pregnancy and delivery, allowing for timely interventions, such as tetanus immunization, which is crucial for the health of both mother and baby Additionally, managing high blood pressure during pregnancy is vital for maternal health and infant survival Delivery care is equally important in reducing maternal mortality, with WHO recommending that childbirth occur in healthcare facilities attended by skilled health staff to ensure safe delivery and healthy outcomes Proper hygiene and adequate medical equipment in these facilities significantly reduce complications such as hemorrhage and obstructed labor, while skilled health professionals provide essential emergency management during delivery.
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, such as poverty rates, the proportion of women with higher education, and the percentage of women delivering in health facilities, are significant indicators of maternal healthcare utilization Higher poverty rates are linked to lower probabilities of accessing antenatal care and facility delivery Conversely, a greater proportion of educated women correlates positively with increased utilization of maternal health services, emphasizing the importance of education in improving health outcomes for mothers and infants.
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 identifying potential complications for timely interventions This care enhances women's understanding of fetal growth and their health status, helping to prevent adverse outcomes like low birth weight through improved nutritional support Women are educated 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 WHO guidelines for ANC include assessments of both mother and fetus, such as body weight, height measurements, blood pressure, and various tests, alongside medical provisions like tetanus vaccinations and iron and folate supplements, as well as 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 their income and autonomy are largely controlled by their in-laws and husbands This strong influence of Confucian values and existing hierarchies restricts women's independence, particularly in health-related matters For instance, the childbirth experiences of mothers and mothers-in-law significantly impact the maternity care of young women, potentially discouraging them from seeking necessary 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 has imposed various penalties, such as high fees for non-compliance, leading some women to conceal their pregnancies and avoid necessary maternal healthcare due to fear of repercussions The burden of having more children also creates time and financial constraints on women seeking maternal health services Following several revisions, the 2009 Population Ordinance now allows couples to decide on the timing and spacing of having one or two children This policy has successfully reduced the total fertility rate from 2.55 in 2001 to 1.99 in 2011, indicating a steady population growth However, challenges remain, including ineffective contraceptive methods; while the IUD is the most commonly used, many women are hesitant due to its side effects Additionally, Vietnam faces a high abortion rate, particularly among the youth, largely due to a lack of knowledge about contraceptive methods and socioeconomic factors.
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 surpasses the Millennium Development Goal 5 target of 58.3 per 100,000 live births by 2015 However, despite this progress, Vietnam still lags behind more 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 improvements in antenatal care coverage, with 95.8% of pregnant women having at least one prenatal care visit in 2014, up from 1999 However, only 73.7% of women received more than four visits, indicating a need for further measures Additionally, there are considerable disparities in maternal healthcare utilization among different ethnic groups, places of residence, and regions Women in rural areas, in particular, have fewer prenatal care visits, with significant differences in access compared to urban populations Ethnic minority groups face greater disadvantages, with only 79% having one visit and 32.7% having at least four visits, compared to 99.2% and 82.1% of the Kinh group, respectively.
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 explored frameworks to explain individual health-seeking behavior Notably, Rosenstock's Health Belief Model (1974) posits that an individual's beliefs about health issues, their perceptions of benefits and 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 the perception of serious consequences and risks associated with health problems significantly increases the likelihood of engaging in health-promoting actions Furthermore, if perceived benefits outweigh the barriers, individuals are more likely to take action Cues to action, both internal (such as pain and symptoms) and external (such as information from friends and mass media), play a crucial role in this decision-making process The Health Belief Model has been effectively utilized to design interventions aimed at changing health-related behaviors by targeting these specific components.
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
First-time mothers are more likely to utilize antenatal care due to their lack of experience (Navaneetham & Dharmalingam, 2002) Conversely, women who have previously given birth may attend fewer antenatal care visits if they had negative experiences with the services (Arthur, 2012) This sentiment is echoed by Tsawe & Susuman (2014), who noted that maternal healthcare usage is significantly influenced by prior experiences with the provided services When women receive better care, they are more inclined to utilize these services regularly However, policies such as the two-child policy and fears of penalties may deter women with more than one child from seeking adequate maternal healthcare (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 highlighted in several studies Navaneetham and Dharmalingam (2002) found that non-working women are more likely to seek maternal healthcare services than their employed counterparts, potentially due to a relative increase in wealth among non-working women In developing countries, low-paying jobs contribute to a decreased likelihood of utilizing maternal health services Additionally, Baale (2011) noted that the type of employment affects the use of antenatal care, as job conditions and income influence healthcare affordability Women employed in factories are more inclined to utilize antenatal care compared to housewives, while those in government jobs are more likely to seek antenatal care if covered by national health insurance (Chen et al., 2003).
Research indicates that women from ethnic majority groups in Vietnam are more likely to give birth in health facilities compared to those from ethnic minority groups, primarily due to language barriers that hinder communication with healthcare providers Additionally, the lower rates of maternal healthcare access among women from ethnic minorities can be linked to lower education levels and poorer socioeconomic conditions This trend is observed in other countries as well; for instance, women from "Scheduled" castes and tribes in India exhibit fewer antenatal care (ANC) check-ups, while Kurdish women in Turkey are also less likely to utilize ANC services.
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 with higher living standards are three times more likely to receive adequate prenatal care compared to those with lower living standards Additionally, having a car is associated with increased access to maternal healthcare (Celik & Hotchkiss, 2000) Despite some countries offering free healthcare services, barriers remain, including transportation costs (Arthur, 2012) Women who struggle to afford travel expenses are less likely to seek ANC checkups than those who do not face such financial difficulties (Tsawe & Susuman, 2014) Overall, financial constraints are a significant obstacle to accessing maternal healthcare services.
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, household size, ethnicity, and the religion of the household head Additionally, community-level factors such as place of residence, poverty rate, illiteracy rate, and the proportion of women giving birth in health facilities significantly impact maternal health-seeking behavior This comprehensive framework highlights the interconnectedness of these factors in shaping prenatal care access and choices.
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 focuses on 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 potential health issues for 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 several individual-level factors influencing maternal health, including the mother's age at childbirth, birth order, education, material status, exposure to mass media, and pregnancy intention Mother's age ranges from 15 to 49 years and is treated as a continuous variable Maternal education is categorized into five levels: no education, primary, lower secondary, upper secondary, and tertiary Birth order is also a continuous variable representing the number of children a woman has given birth to Material status is assessed using dummy variables, distinguishing between women who were previously married but are no longer in a union, women who have never been married, and those who are currently married Exposure to mass media is measured through four dummy variables reflecting access to mobile phones, newspapers, radio, and television Lastly, pregnancy intention is indicated as a binary variable, where a value of 1 signifies that the woman did not intend to become pregnant, and 0 indicates 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 the study is 28, with ages ranging from 15 to 47 On average, women have two children, aligning with Vietnam's two-child policy, although some women in rural areas have given birth to as many as 11 children In the poorest households, 100% of women live in communities that struggle to meet basic needs Additionally, many women in these communities are illiterate, with a significant portion lacking even primary education.
Table 3 presents descriptive statistics for dummy variables related to childbirth The majority of women prefer to deliver in government hospitals or community health centers to ensure safe childbirth, although 136 women still opted for home deliveries Most interviewed women (35%) completed lower secondary education, followed by upper secondary, tertiary, primary, and 6% with no education Additionally, 3% of the women reported being previously married or never married Nearly 20% experienced unintended pregnancies, and many were unemployed In terms of media exposure, women predominantly watch television and read SMS messages rather than newspapers or listen to the radio Television and mobile phones are widely used in Vietnam, as they provide timely updates on current affairs both internationally and domestically, along with convenient 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 prenatal care and hospital delivery rates Specifically, a higher proportion of women without education and those delivering in hospitals correlates with increased prenatal care visits 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 positive relationship exists between the hospital delivery ratio and the demand for antenatal care, with women in communities with higher hospital delivery rates having 0.03 more visits This suggests that community practices greatly influence women's attitudes and healthcare-seeking behaviors, supporting the conclusions of 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, which is the most affordable but often lacks hygiene and medical equipment; public hospitals, which are government-supported and low-cost but frequently overcrowded; and private hospitals or clinics, which offer better services and advanced technology at a higher price Notably, women who opt for home childbirth are less exposed to mass media such as mobile phones, television, and newspapers compared to those delivering at health facilities Additionally, women in disadvantaged areas with higher poverty and illiteracy rates, like the Central Highlands and North Mountainous regions, are more likely to give birth at home 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 farm jobs that hinder their ability to afford healthcare costs Furthermore, women with higher living standards and those from the ethnic majority are more likely to choose private hospitals, while rural women are less likely to do so, primarily because most private hospitals are located in urban areas and are more expensive.
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 the number of children born Research indicates that higher education significantly enhances prenatal care utilization, as educated women possess greater autonomy and awareness of healthcare benefits Additionally, community literacy rates are strongly linked to maternal healthcare usage Women from lower household wealth and ethnic minority groups are less likely to access adequate health check-ups compared to those with higher living standards Support from family is crucial, as unmarried or separated women and those with more children often face barriers to prenatal care due to increased responsibilities and lack of partner support Furthermore, there are notable regional disparities in prenatal care utilization, with residents in disadvantaged areas like the Central Highlands and Central Coast being less likely to access maternal health check-ups compared to those in more affluent regions.
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 compared to public facilities, while having more children increases the likelihood of choosing home delivery These findings align with previous studies (Navaneetham & Dharmalingam, 2002; Stephenson et al., 2006; Sepehri et al., 2008) However, individual characteristics do not significantly differentiate between public and private hospital deliveries At the household level, women from poorer households and ethnic minority groups are more inclined to prefer home delivery over public hospitals, whereas poorer women tend to favor public hospitals over private ones This pattern is consistent with earlier research, including studies by Celik & Hotchkiss (2000) and Stephenson et al.
(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 delivery location is prone to recall errors, as women may forget the exact number of prenatal visits or when they first sought care To mitigate this, the study focused on women who delivered their babies within two years prior to the interview Secondly, some influencing factors, such as pregnancy complications and community practices, were not observed due to data limitations, which could affect maternal healthcare-seeking behavior and delivery decisions Additionally, community-level variables may differ from individual-level data due to aggregation Lastly, including prenatal care visits in the facility choice regression may introduce endogeneity issues that were not addressed Therefore, further research is needed to address these limitations.
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Variable Obs Mean Std.Dev Min Max
Variable Obs Mean Std.Dev
The data analysis reveals significant variations across different delivery metrics For age, the average delivery ages are 26.43, 27.68, and 28.08, with respective ranges of 15-47, 16-45, and 16-41 In terms of CEB, the averages are 2.78, 1.75, and 1.76, with ranges of 1-11, 1-7, and 1-5 Household size averages are 6.61, 5.67, and 5.65, with ranges of 3-13, 2-16, and 3-11 Poverty levels show a stark contrast, with averages of 87.40, 35.44, and 29.13, indicating ranges from 8.70 to 100 for the first delivery and 0 to 100 for the others Illiteracy rates are concerning, averaging 39.73, 4.35, and 4.36, with maximums of 77.78 Lastly, the hospital delivery ratios are notably high at 29.81, 96.93, and 98.12, with maximums reaching up to 100.
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