Amercan Journal of Economcs 2013, 3(6): 243-251 DOI: 10.5923/j.economcs.20130306.01 Health Campagns and Use of Reproductve Health Care Servces b Women n Ghana Emmanuel E. Asmah 1,*, Danel K. Twerefou 2, Jessca E. Smth 3 1 Department of Economcs, Unverst of Cape Coast, Cape Coast, Ghana 2 Department of Economcs, Unverst of Ghana, P. O. Box LG 57, Accra, Ghana 3 Afrca Growth Intatve, Brookngs Insttuton, 1775 Massachusetts Avenue, NW, Washngton DC, USA Abstract The avalablt of health nformaton and knowledge to women s mportant n efforts to rase women s awareness about health practces needed to promote good health outcomes. Polc makers can use dfferent forms of knowledge nfrastructure to for example, nduce faster dffuson of health nformaton among women. In ths stud, we have used the Ghana Demographc and Health Surve for 2008 to evaluate dfferentals n health campagns (transmtted through televson, rado and newspapers) on the use of reproductve health care servces b women. Ths objectve s motvated b the fact that Ghana s stll off-track n achevng the 2015 maternal health targets, despte the modest gans n other areas. After controllng for other varables n the model, a seres of logt regressons showed that health nformaton delvered va televson s a sgnfcant predctor of the lkelhood that a woman would choose sklled delver care and utlze antenatal care servces. Besdes health campagn varables, the fndngs also confrm the mportance of wealth, educaton and locaton n drvng nformaton asmmetr as well as the promoton of good maternal health. These fndngs mpl that faml plannng campagns through the medums of TV and rado need to be ntensfed and extended to all women, ncludng those n rural areas. Health polc should also encourage nvestments n educaton and wealth creaton. Kewords Reproductve Health Care, Women, Health Campagns, Logt Regresson 1. Introducton Globall, the health of women has engaged the attenton of man governments, as has been demonstrated b the manstreamng of maternal health mprovement as the ffth goal n the nternatonall agreed Mllennum Development Goals (MDGs). Despte ts fundamental mportance to the countr s wellbeng, the statstcs on maternal health especall n Afrca leave so much to be desred. The 2008 maternal mortalt rato (MMR) of maternal deaths per 100,000 lve brths was 640 n sub-saharan Afrca, compared wth an average of onl 14 for developed regons and 290 for developng regons[1]. 1 However, the phenomenon of hgh maternal death n sub-saharan Afrca s preventable and health solutons are readl avalab le. Ghana, lke other developng countres has a hgh * Correspondng author: eeasmah@mal.com (Emmanuel E. Asmah) Publshed onlne at http://journal.sapub.org/economcs Coprght 2013 Scentfc & Academc Publshng. All Rghts Reserved maternal mortalt rate. The WHO report estmates a maternal mortalt rato of 350 per 100,000 lve brths; whle n-countr reports quote a hgher fgure of 450. However, as fgure 1 show, the maternal mortalt rato snce 1990 has been reducng. Despte the modest gans made n achevng other MDGs and an mprovement n maternal health, Ghana stll lags behnd other countres n achevng the 2015 maternal health targets. Gven the above statstcs and the role women pla n the process of human captal formaton, t s mportant for polc makers and health workers to make an effort to promote safe motherhood. Reproductve health servces, n partcular faml plannng and maternal health servces, can help women avod unplanned brths, unsafe abortons, and pregnanc-related dsablt es[2]. One wa to make ths happen s to provde mothers wth nformaton on best maternal health care practces. For example, nformaton and servces made avalable to women through sex educaton and reproductve health servces can help them understand ther sexualt and protect them from unwanted pregnances, sexuall transmtted dseases and subsequent rsk of nfert lt[3]. 1 The MMR s smpl the total number of maternal deaths occurrng for a gven number of brths (tpcall 100,000).
244 Emmanuel E. Asmah et al.: Health Campagns and Use of Reproductve Health Care Servces b Women n Ghana 700 600 500 M M R 400 300 200 MMR 100 0 1990 1995 2000 2005 2008 Year Fgure 1. Trends n Marternal Mortalt Rato n Ghana: 1990-2008 In ths age of nformaton and communcaton revoluton, the role plaed b socal networks, nternet assocatons, moble phone servces, televson and rado for conveng nformaton to a vast majort of ctzens s not n doubt. The challenge for polc makers s to ensure that health messages and campagns transmtted through varous channels are accessble to all women, especall those n rural settngs. But the emprcal prerequste s to frst ascertan whether havng access to health nformaton obtaned through dfferent sources matters for the knd of reproductve health care servces mothers choose to use. Prevous emprcal studes on the of the determnants of maternal reproductve have mostl been lmted to nvestgatng the mpact of mother s schoolng onl and, as a consequence, largel have not consdered health campagns and other health lterac programs. 2 The purpose of ths stud s to test the hpothess that access to faml plannng campagns (transmtted through TV, rado etc) among women partl explans dfferentals n the use of reproductve health care servces n Ghana, condtonal on selected ndvdual characterstcs. In lne wth the Reproductve Health Acton Plan (RHAP) n Ghana and also to reduce the extent of complext and sta wthn the relevant lmts and scope, the stud focuses on three reproductve health care servces -faml plannng (contraceptve use), antenatal vsts and delver care. Frst, we nvestgate whether or not a woman s decson to be attended b a sklled or tradtonal attendant durng delver s nfluenced b the access to health nformaton. Ths follows[4], who estmate that the choce of delver care s an mportant determnant for reducng the rsk of nfant and maternal death. Second, we examne whether a woman s decson to use (or not use) contraceptves s nfluenced b nequaltes n health nformaton. Accordng to[4], access to contracepton generall allows a woman to lmt and space 2 See [3] [5]; [6]; [7]; [8], [9]; [10]. pregnances; thereb, lowerng each woman s lfetme rsk of unsafe aborton and obstetrc mortalt. Thrd, we explore the relatonshp between the number of antenatal vsts that women make and how that s nfluenced b exposure to health campagns transmtted through TV, rado and newspapers. Perodc health check-ups durng the antenatal perod are necessar to establsh confdence between women and ther health care provder, and manage an maternal complcatons or rsk factors[11]. 2. Overvew of the Lterature Reproductve Health, as defned b the World Health Organzaton (WHO) refers to a state of complete phscal, mental and socal well-beng and not merel the absence of dsease or nfrmt, n all matters relatng to the reproductve sstem and to ts functons and processes. In lne wth the above defnton, reproductve health care s also defned as the constellaton of methods, technques and servces that contrbute to reproductve health and well-beng b preventng and solvng reproductve health problems. Reproductve health care ncludes a varet of preventon, wellness and faml plannng servces as well as dagnoss and treatment of reproductve health concerns[2]. The Internatonal Conference on Populaton and Development (ICPD), held n Caro n 1994, was noteworth for achevng a global consensus that all people regardless of age, part, martal status, ethnct, or sexual orentaton are enttled to reproductve health and rghts. Reproductve health s a crtcal component of women s general health. When women lack access to safe, comprehensve reproductve health care, the consequences can be damagng. Sexual and reproductve ll health accounts for almost twent per cent of the global burden of dsease for women and fourteen per cent for men[12]. Postve reproductve health means that ndvduals can manage ther own sexualt and
Amercan Journal of Economcs 2013, 3(6): 243-251 245 have unrestrcted access to the full range of reproductve health care optons. The choce of reproductve health care servces b women, as wth other areas of health care optons, s nfluenced b a complex nterpla of economc and socal determnants ([2],[13],[14] and[15]). The Unted Natons sxt-seventh sesson of the General Assembl resolutons on Global Health and Foregn Polc acknowledges that man of the underlng determnants of health and rsk factors of both non-communcable and communcable dseases, n partcular tuberculoss, malara and HIV and AIDS, as well as the causes of maternal and nfant mortalt, are assocated wth socal and economc condtons, the mprovement of whch s a socal and economc polc ssue [16]. An extenson of the socal determnants to cover meda exposure s graduall becomng an mportant consderaton. Exposure to televson, rado, newspapers or magaznes are mportant sources from whch women obtan nformaton that can help them understand ther sexualt and protect them from unwanted pregnances, sexuall transmtted dseases and subsequent rsk of nfert lt[2]. Qute a number of emprcal studes exst on the effects of meda exposure on dfferent reproductve health ndcators. For examp le, n Ngera, use of modern contracepton, ntent to use, and desre for fewer chldren were found to be assocated wth exposure to meda messages on faml plannng[17]. A smlar stud n Tanzana found that women exposed to a mx of meda promotng faml plannng were more lkel to use faml plannng[18]. Accordng to a stud n Nepal, exposure to mass meda had an ndrect effect on contraceptve use through ncreases n nterpersonal communcaton, as well as postve changes n atttudes and perceved socal norms regardng faml plannng[19]. In Mal, exposure to a campagn was lnked to more favorable atttudes towards faml plannng and a declne n the proporton of men and women who beleved that Islam opposes faml plannng[20]. Gupta et al[21] examned the nfluences of mult-meda Behavor change communcaton campagns (BCC) on women's and men's use of and ntentons to use contracepton n target areas of Uganda. Results ndcated that exposure to BCC messages was assocated wth hgher contraceptve ntentons and use. A few related studes based on Ghana nclude the work b[22],[23],[24],[25],[26],[27] and[28]. A comprehensve revew of the lterature b Women s Health West[2] ctes man other countr nstances where mass meda campagns have proved successful n promotng faml plannng. Another WHO stud found that whles factors such as meda exposure, mgraton, connectedness to school and faml among others were dentfed as mportant n ndustralzed countres; research on these factors n developng countres s too scant[29]. The stud found that man of the research focused on ndvdual soco-demographc factors, such as age, sex, socoeconomc status, and geographc locaton, man of whch are not amenable to programmatc nterventons. An earler snthess of the research evdence on reproductve health n Ghana amed at dentfng research gaps b Awusabo-Asare et al[3] found that much of the exstng studes on Ghana shows the levels and patterns n rsk sexual and health behavors, but provde ver lttle evdence to explan wh. The current research s smlar n sprt and concepton to most of the above cted studes, especall the one b Kwanke and Augustt[26]. Instead of the focus on sexual and reproductve rsk factors, ths present stud nvestgates the extent to whch meda exposure affects the use of contraceptves, antenatal care and sklled delver based on new data for Ghana. 3. Theoretcal Framework To provde a theoretcal frame of reference for analzng the relatonshp between the use of reproductve health care servces b women and health campagns, ths stud draws fro m Gar Becker s[30] household producton theor, whch was also extended b Grossman[31]. The analss s also smlar n sprt and concepton to the studes b[32] and Mwabu[33]. In these models, health, defned as a state of phscal, mental and socal well-beng of the ndvdual s vewed as a consumer good as well as a durable captal good. As a consumer good, ndvduals derve satsfacton and have a hgh preference for a good health status. Gven an ntal stock of health captal that tends to deterorate overtme, ndvduals nvest n ther health status n order to earn some economc return (normall n the form of health tme for the capablt to functon). A mother s health s a scarce commodt relatve to the capabltes t can eld n terms of functonng. Thus, ndvdual women wthn ther households need to allocate resources n an optmal wa to derve the maxmum benefts from the consumpton and producton of health. The standard neoclasscal approach to utlt maxmzaton serves as a good framework for understandng ndvdual behavor n ths context. Followng[33], the approach consders a woman whose utlt (U) s assumed to depend on a health-neutral (X), a health-related good or behavor (Y) and home produced maternal health, H. It s also assumed that the maternal health producton functon s gven b: H = f ( Y, M, η) (1) Where, M stands for market and/or non-market nputs nto the woman s health producton such as medcal care, antenatal vsts, delver care choces, contraceptve use etc. η captures the component of the mother s health due to genetc endowments, envronmental factors and other components not nfluenced b preferences. Thus, the objectve functon becomes: Max U= U(X, Y, H) (2) Subject to the budget and tme constrants as n equatons (3) and (4) below wh = XP + YP + MP (3) x m
246 Emmanuel E. Asmah et al.: Health Campagns and Use of Reproductve Health Care Servces b Women n Ghana Where w s the wage rate, h the number of hours P, P, P are prces of health neutral good, worked and x m health related consumer goods and maternal health servces. The tme constrant s also gven as: T = h + L (4) Where,T, s the total tme avalable, and L s lesure. Substtutng (4) nto (3) elds; w ( T L) = XP + YP + MP (5) Maxmzng the objectve functon subject to the constrants elds the Lagrangan functon as follows: 2 1 { H FYM (,, η) } x { λ x m } L = U ( X, Y, H ) + λ w( L) ( XP + YP + MP ) + λ The task facng the woman s to smultaneousl choose the amount of health-neutral goods, health related goods and maternal health producton nputs so as to maxmze utlt. Takng frst order condtons and jontl solvng the resultng equatons provdes the optmal soluton to the above problem n the form of health nput demand functons gven b: X = Dx ( Px, P, Pm, w, h, η) (7) = (8) Y M D ( Px, P, Pm, w, h, η) D ( P, P, P, w, h, η) x m m (6) = (9) Ideall, the sstem of equatons (7)-(9) should be estmated smultaneousl, but the focus s placed on equaton (9) for smplct. The use or non-use of reproductve health care servces b the woman depends on several factors ncludng: the cost of medcal care, ncome, educaton, genetc trats or envronmental factors such as place of resdence, ethnct, and other relevant varables. The role of health nformaton n the framework s to help women as consumers and producers of health to make the rght choces and decsons about health reproductve practces. Clearl, the use of maternal reproductve care servces s assumed to be derved from the desre to have good health status, whch s also based on the desre to maxmze utlt. 4. Estmaton Methods and Emprcal Strateg In order to assess the nfluence of health campagns on the use of reproductve health care servces b women n Ghana, we follow a general specfcaton of the form: M = X β + ε (10) Where M the dependent s a varable representng selected reproductve health care servces, X s a vector of ndvdual characterstcs of the woman (age, educaton, relgon, ethnct, etc.) that also ncludes varables on access to health campagns. β s a vector of parameters to be estmated and ε s the dsturbance term whch ncludes all the unobserved factors that affect the woman s use of reproductve health care servces. The dependent varable n equaton (10) s defned as a dscrete dchotomous varable. In that regard, the approprate emprcal technque for emp rcal estmat on s a lnear probablt model,.e. logt, probt, nested logt, or some varaton. The partcular choce of probablt model between logt or probt depends largel on preference as there are no compellng statstcal reasons for usng one or the other[34]. The major dfferences between the two models are the dstrbutonal assumptons of the dsturbance term, ε. In the logt model the dstrbuton of the error term s assumed to be logstcall dstrbuted; whle the n the probt model a normal dstrbuton N (0, 1) s assumed. For ease of nterpretaton of the sgn and sgnfcance of the coeffcents, ths stud adopts the logt model[35]. The general logt model takes the followng form: 1 woman uses a partcular = reproductve health servce 0 woman does not choose servce PP = EE( = 1 xx ) = ββ 1 + ββ 2 χχ (11) 5. Dscusson and Results The Data used n the stud were drawn from the 2008 natonall representatve Ghana Demographc and Health Surve (GDHS). Table 1 descrbes the dependant varables and ther dchotomous responses. The number observatons used n the three logt models var from 1,311-2,358. Varaton n observatons s due to the fact that f a surve response s not recorded, the entre observaton s dropped from the model n STATA. Table 2 presents the summar statstcs of the control varables for each of the logt models. The mean educaton levels are 5.24, 6.35, and 5.18, respectvel, and educaton levels range from 1 to 19 ears of schoolng. Ages of the surve respondents var from 15-49, and the mean age s approxmatel 29.8 ears for each of the three models. Table 3 provdes the mean and standard devaton for the ndependent varables that represent a surve respondent s access to health campagns. As reported, each of these varables s a dumm for havng receved faml plannng nformaton from varous meda or health resources. These varables along wth the controls were entered nto the three logt models to estmate whether the have an mpact on a wo man s reproductve health decsons. Thus, there are three panels representng each of the logt models. Model 1 represents the sklled delver, model 2 contraceptve use, and model 3 antenatal vst responses. 5.1. Model 1 Health Campagns and Sklled Delver Care The frst logt model, as shown n table 4, determnes the lkelhood that the average surve respondent wll use a sklled delver, n the event of pregnanc, deld. The predctor varables are a vector of control varables and a
Amercan Journal of Economcs 2013, 3(6): 243-251 247 seres of dummes relatng whether the respondent has receved faml plannng knowledge from the followng sources: rado, televson, health extenson and/or a health faclt. The dumm s alwas 1 - has receved faml plannng nformaton (for each nformaton channel) or 0 - has not receved faml plannng nformaton. In the frst model there are 1,346 observatons and the lkelhood rato ch square 382.46 (12 degrees of freedom) wth a small p value can be nterpreted as the logt model has a good ft as compared to a model wthout predctors. For all models age squared s negatve and sgnfcant. The varable age squared s ncluded n the model to show that the relatonshp between age and the dependant value deterorates over tme,.e. as women age the no longer make these maternal health decsons. An ncrease n a respondent s age, educaton level, and level of wealth are all sgnfcant predctors that she wll use a sklled delver. If the respondent belongs to a Chrstan relgon then she s more lkel to use a sklled delver than respondents belongng to non-chrstan relgons, as desgnated b the postve sgnfcant coeffcent for relgon. Respondents from rural areas are less lkel to use a sklled delver as the varable loc s negatve and sgnfcant. Ethnct, akan, of the surve respondent s not a sgnfcant predctor of whether or not she wll use a sklled delver. Lookng at the health campagn varables as predctors, recevng health messages through televson and health extenson sgnfcantl predcts deld. Thus, vewng faml plannng nformaton on televson ncreases the probablt that a respondent wll use a sklled delver. Unexpectedl, f a respondent has receved faml plannng nformaton from a health extenson agent she s less lkel to use a sklled delver. Perhaps ths s because respondents who are served b health extenson agents are n more remote locatons wth less access to sklled delver servces. The remanng health nformaton channels were not statstcall sgnfcant. 5.2. Model 2 Health Campagns and Contraceptve Use b Wome n The second logt model estmates the lkelhood that a surve respondent wll use contraceptves, contra, usng 2,358 observatons. Table 5 shows that the predctor varables reman the same as the prevous logt model for sklled delver, and that the model also has a small p value. In model 2, the age, educaton, wealth, and Chrstan relgon are sgnfcant predctors that a respondent wll use contraceptves. That s the older, more educated, wealther, and f a woman s Chrstan, the more lkel she s to use some form of contraceptve. Accordng to the Ghana Maternal Health surve, locaton and ethnct of the respondent are not sgnfcant predctors of her decson to use brth control. The health campagn varable, fp_fp fac, was postve and sgnfcant, thus women who receve faml plannng nformaton from a health faclt are more lkel to use contraceptves n ths sample. Addtonall, faml plannng nformaton vewed on televson, fp_telev, s slghtl sgnfcant at the 0.10 level. The other health nformaton channels were not sgnfcant for contraceptve use. 5.3. Model 3 - Health Campagns and Antenatal Care Vsts b Women The thrd logt model n the logt seres, represented n table 6, estmates the lkelhood that a surve respondent wll have one or more antenatal vsts, anted. Ths model used 1,311 observatons, and the same predctor varables as the contra and deld logt models wth a small p value. When estmatng the lkelhood that a surve respondent wll have one or more antenatal vsts, model 3 fnds that age, educaton, and wealth are sgnfcant and postve. Ths suggests that wealther, older, and more educated women are more lkel to attend antenatal vsts. As expected, locaton s negatve and sgnfcant showng that women n rural areas are less lkel to go to antenatal care; probabl due to access ssues. Relgon and ethnct are not sgnfcant predctors of a woman s tendenc toward antenatal vsts. The varable fp_telev, the prox for faml plannng nformaton receved va televson s postve and sgnfcant. Thus, women who receve faml plannng nformaton va televson are more lkel to attend one or more antenatal vsts. 6. Conclusons The avalablt of health nformaton and knowledge to women s mportant when consderng efforts to rase awareness of health practces and postvel nfluence maternal health behavors. In ths stud, we have used the Ghana Demographc and Health Surve for 2008 to nvestgate whether access to faml plannng messages transmtted through dfferent forms of knowledge nfrastructure affect maternal reproductve health decsons. After controllng for some ndvdual characterstcs n the model, the logt regressons revealed that, women who receved health messages conveed through televson have a hgher lkelhood to use sklled delver care and utlze antenatal servces. Besdes showng the sgnfcance of nformaton access, the logt model confrms most of prevous theoretcal and emprcal expectatons about the postve nfluence of educaton, wealth and health endowments on maternal reproductve health decsons. In addton, households who lve n urban communtes were predcted to have a hgher probablt of exposure to health campagns and utlze reproductve health servces. Varous post estmaton tests for the models were conducted. Most of the tests passed as requred except for the heteroskedastct test whch was corrected b reportng the robust estmates. The results from the control varables mpl that health polc should encourage nvestments n educaton and wealth creaton. In addton, health campagns need to be ntensfed and extended to all women, ncludng those n rural areas, through the medum of TV and rado.
248 Emmanuel E. Asmah et al.: Health Campagns and Use of Reproductve Health Care Servces b Women n Ghana Appendx Summar Statstcs and Table of Results Ta ble 1. Summar Statstcs of Dependant Varables De pen dan t Var ables No. of Obs. Mean Std. Dev. Model 1 Del d-bnar response: 1-respondent used a sklled attendant 1346 0.6501 0.4771 was used for delver; 0-sklled attendant was not used Model 2 Contra-bnar response: 1-respondent used contraceptve; 0-2358 0.5823 0.4933 no contraceptve used Model 3 Ante d-dumm varable: 1-respondent made 1-4 ant enatal 1311 0.7155 0.4514 clnc vsts; 0-respondent dd not make an antenatal vsts Model 4 BMI a contnuous varable representng the respondent s bod mass ndex whch measures the woman s weght n klograms b her heght n meters, squared. 2137 7.771769 0.2778487 Ta ble 2. Summar Statstcs of Control Varables Control Varables Age-contnuous: respondent s age n ears Agesq-contnuous: respondent s age squared; represents the relatonshp of age to the dependant varable over tme. Loc-dumm coded: 1-urban; 0-rural Edu c-contnuous ears of educaton completed b respondent Rel-dumm coded: 1-Chrstan; 0-non-Chrst an Akan-dumm coded: 1-Akan; 0-non-Akan Rch-dumm coded: 1-wealth; 0-non-wealth Model 1-deld No. obs-1346 Model 2-contra No. obs-2358 Model 3-ante d No. obs-1311 mean std. de v. mean std. de v. Mean std. de v. 29.8009 6.9198 29.8817 8.6969 29.8322 6.9308 935.9406 432.3296 968.5195 548.3369 937.9588 433.2076 1.6114 0.4876 1.5254 0.4995 1.6110 0.4877 5.1790 4.5538 6.3503 4.6730 5.2410 4.5374 0.6865 0.4641 0.7328 0.4426 0.6934 0.4613 0.3811 0.4858 0.4321 0.4955 0.3875 0.4874 0.5245 0.4996 0.6336 0.4819 0.5294 0.4993 Ta ble 3. Summar Statstcs of Knowledge Infrastructure Varables Inde penden t Varables fp_rado-dumm coded: 1-respondent receved faml plannng nformaton from rado; 0- respondent dd not receve faml plannng nformaton from rado fp_telev-dumm coded: 1-respondent receved faml plannng nformaton from televson; 0-respondent dd not receve faml plannng nformaton from televson fp_newsp-1-dumm coded: 1-respondent receved faml plannng nformaton from newspaper; 0-respondent dd not receve faml plannng nformaton newspaper fp_hextw-dumm coded: 1-dumm coded: 1-respondent receved faml plannng nformaton from health extenson worker; 0-respondent dd not receve faml plannng nformaton from health faclt fp_fpfac-1-dumm coded: 1-respondent receved faml plannng nformaton from ; 0-respondent dd not receve faml plannng nformaton from health faclt Model 1-deld No. obs-1346 Model 2-contra No. obs-2358 Model 3-ante d No. obs-1311 mean std. de v. mean std. de v. Mean std. de v. 0.6018 0.4897 0.6158 0.4865 0.6095 0.4881 0.3826 0.4862 0.4512 0.4977 0.3883 0.4875 0.0780 0.2683 0.1170 0.3215 0.0793 0.2704 0.1932 0.3949 0.1531 0.3602 0.1983 0.3989 0.4339.4958 0.3142 0.4643 0.4287 0.4951
Amercan Journal of Economcs 2013, 3(6): 243-251 249 Ta ble 4. Model 1 Impact of Faml Plannng Campagns on the Probablt of Usng Sklled Delver Controls Del d: 1-Used sklled delver care, or 0-Dd not use sklled delver care Coef. Std. Error Z P> z 95% Conf. Interval age 0.1331 0.0738 1.80 0.071* -0.0116 0.2778 Agesq -0.0021 0.0012-1.76 0.079* -0.0044 0.0002 Loc -1.3629 0.1911-7.13 0.000*** -1.7374-0.9884 Educ 0.1130 0.0197 5.74 0.000 *** 0.0744 0.1516 Rel 0.2480 0.1583 1.57 0.117* -0.0622 0.5584 Akan 0.0372 0.1698 0.22 0.826-0.2655 0.3700 Rch 0.6087 0.1750 3.48 0.001*** 0.2655 0.9518 fp_rado 0.0481 0.1479 0.33 0.745-0.2417 0.3379 fp_telev 0.3807 0.18 2.10 0.036** 0.0252 0.7362 fp_newsp -0.1410 0.3267-0.43 0.666-0.7812 0.4992 fp_hextw -0.5469 0.1723-3.17 0.001*** -0.8846-0.2093 fp_fpfac 0.1628 0.1395 1.17 0.243-0.1105 0.4362 LR ch2 (12): 382.36; Prob>ch2: 0.0000; Log lkelhood: -680.22178, Pseudo R2: 0.2194. Note also that * means the coeffcent s sgnfcant at 0.10, **sgnfcant at 0.05 and ***sgnfcant at 0.01. Ta ble 5. Model 2- Impact of Faml Plannng Campagns on the Probablt of Contraceptve Use Controls Contra: 1-Used contraceptves or 0-Dd not use contraceptves Coef. Std. Error Z P> z 95% Conf. Interval age 0.3686 0.0375 9.82 0.000*** 0.2951 0.4422 Agesq -0.0054 0.0006-9.07 0.000*** -0.0065-0.0042 Loc 0.1311 0.1176 1.12 0.265-0.0992 0.3616 Educ 0.0852 0.127 6.70 0.000*** 0.0603 0.1101 Rel 0.5183 0.1126 4.61 0.000*** 0.2977 0.7389 Akan 0.1048 0.1061 0.99 0.323-0.1032 0.3128 Rch 0.2714 0.1299 2.09 0.037** 0.0168 0.5261 fp_rado 0.1256 0.1037 1.21 0.226-0.0776 0.3289 fp_telev 0.1782 0.1156 1.54 0.123* -0.0483 0.4047 fp_newsp -0.1487 0.1591-0.93 0.350-0.4605 0.1631 fp_hextw 0.1925 0.1322 1.46 0.145-0.0663 0.4517 fp_fpfac 0.5777 0.1050 5.50 0.000*** 0.3719 0.783 LR ch2 (12): 347.81; Prob>ch2: 0.0000; Log lkelhood: -1428.4664, Pseudo R2: = 0.1085. Note also that * means the coeffcent s sgnfcant at 0.10, **sgnfcant at 0.05 and ***sgnfcant at 0.01. Ta ble 6. Model 3 - Impact of Faml Plannng Campagns on the Probablt of Antenatal Vsts Controls anted: 1-Attende d 1 or more antenatal vsts or 0-Dd not attend 1 or more antenatal vsts Coef. Std. Error Z P> z 95% Conf. Interval age 0.1508 0.0703 2.14 0.032** 0.0130 0.2887 Agesq -0.0024 0.0011-2.11 0.035** -0.0046-0.0002 Loc -0.4755 0.1788-2.66 0.008*** -0.8259-0.1251 Educ 0.0487 0.0190 2.56 0.010** 0.0114 0.0859 Rel 0.0134 0.1545 0.090 0.931-0.2894 0.3163 Akan -0.0996 0.1617-0.62 0.538-0.4164 0.2173 Rch 0.3485 0.1769 1.97 0.049** 0.0017 0.6953 fp_rado 0.1845 0.1423 1.30 0.195-0.0944 0.4634 fp_telev 0.4614 0.1766 2.61 0.009*** 0.1140 0.8063 fp_newsp 0.2154 0.3197 0.67 0.500-0.4112 0.1766 fp_hextw -0.1474 0.1653-0.89 0.373-0.4715 0.1767 fp_fpfac -1.212 1.1003-1.10 0.271-3.3687 0.9444 LR ch2 (12): 117.42; Prob>ch2: 0.0000; Log lkelhood: -724.17596, Pseudo R2: = 0.0750. Note also that * means the coeffcent s sgnfcant at 0.10, **sgnfcant at 0.05 and ***sgnfcant at 0.01.
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