Maternal Education, Linkages and Child Nutrition in the Long and Shortrun: Evidence from the Ethiopia Demographic and Health Surveys

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1 Maternal Educaton, Lnkages and Chld Nutrton n the Long and Shortrun: Evdence from the Ethopa Demographc and Health Surveys Ambel Alemayehu Azeze, World Bank We-Chao Huang,* Western Mchgan Unversty Abstract: We used the 2 and 25 Ethopan Demographc and Health Surveys to analyze the effect of maternal educaton and ts pathways on chronc (long-run) and acute (short-run) malnutrton n Ethopa. The pathways examned n ths study are socoeconomc status, maternal health-seekng behavor, maternal knowledge of health and famly plannng and reproductve behavor. We fnd that maternal educaton works through all except health-seekng behavor. We also fnd that maternal educaton and ts pathways are more relevant and robust n explanng chronc than acute malnutrton. Socoeconomc status s the most mportant factor lnkng maternal educaton and chld nutrtonal status. Although grls educaton s a hgh polcy prorty, t may take tme before ts drect and ndrect mpacts materalze and substantally mprove chld health outcomes. Faster results would requre drect nterventons on key elements of soco-economc status. 1. Introducton The strong relatonshp between maternal educaton and chld health outcomes s wdely documented and largely undsputed (Frongllo & Hanson, 1997; Varyam et al., 1999; Alderman et al., 2; Smth and Haddad, 2). A large body of lterature documents that maternal educaton works through a number of pathway varables that drectly affect chld health outcomes. The lst ncludes a number of maternal, household, and communty characterstcs such as socoeconomc status, geographc resdence, nutrtonal and health knowledge, autonomy, and health-seekng and reproductve behavor (Desa & Alva, 1998; Glewwe, 1999; Webb & Block, 24; Frost, Forste, & Haas, 25). Therefore, the pure mpact of educaton on chld health s greatly attenuated when selected medatng factors are ncluded n the model. However, there s a broad dsagreement on the role of the varous lnkages through whch the mpacts of maternal educaton on chld health outcomes are transmtted. Moreover, t s noted that the mpact of maternal educaton could be dfferent to dfferent measures of chld nutrtonal status (Webb & Block, 24). Ths study models selected pathways lnkng maternal educaton and chld nutrtonal status n Ethopa usng the 2 and 25 Ethopa Demographc and Health Surveys (EDHS). The study nvestgates how maternal educaton and ts varous pathways affect chronc (heght for age) and acute (weght for heght) malnutrton n chldren younger than fve years. The study addresses the followng three questons: (1) Does maternal educaton work through selected pathways such Internatonal Journal of Afrcan Development v.1 n.2 Sprng 214 5

2 as socoeconomc status, maternal health-seekng behavor, and maternal knowledge of famly plannng and health? (2) How do maternal educaton and ts pathways perform n models of dfferent types of chld malnutrton? (3) What are the polcy and program mplcatons? The study s motvated by some recent developments on chld nutrtonal status n Ethopa. Frst, the 25 EDHS shows sgnfcant mprovement n chld nutrtonal status when compared to the results of the precedng survey conducted n 2. Second, the changes have been dfferent for dfferent types of chld malnutrton. Chronc malnutrton declned whle acute malnutrton remaned the same on average (Central Statstcal Authorty, 21; ORC Macro, 26). Thrd, the avalablty of comparable data would provde an opportunty to nvestgate the performance of the determnants of chld nutrtonal status over tme. Fourth, malnutrton s a leadng cause of chld death n developng countres (Black, Morrs & Bryce, 23), and reducng chld mortalty s among the top prortes ncluded n the Mllennum Development Goals (MDGs). Because prevalence of chld malnutrton and nfant mortalty n Ethopa s among the hghest n developng regons, the ssue s of natonal and nternatonal concern. Prevous studes on chld nutrtonal status n Ethopa focused on dentfyng the determnants of chronc malnutrton from a one-tme survey (Grma & Genebo, 22) or wthout suffcent consderaton of the mpact of educaton n varous contexts (Chrstaensen & Alderman, 24). Our study expands the dscusson n two ways. Frst, the study analyzes the effect of maternal educaton on chld nutrtonal status consderng a more comprehensve array of lnkages. Second, the study consders both chronc and acute malnutrton. The rest of the paper proceeds as follows: Secton 2 presents a bref summary of prevous studes. Secton 3 provdes a background on the prevalence and recent changes n chld nutrtonal status n Ethopa. Secton 4 descrbes the multvarate analyss ncludng the emprcal framework and the data. Secton 5 dscusses the results, followed by concludng remarks n Secton Prevous Studes Educaton determnes health knowledge and other socoeconomc outcomes that are essental to chld health. Therefore, the quest for the lnks through whch maternal educaton nfluences chld health has been an mportant area of research and polcy dalogue (Desa & Alva, 1998; Frost, Forste & Haas, 25). The pathways consdered usually nclude nutrtonal knowledge, health knowledge, socoeconomc status, atttude toward modern health care servces, autonomy, and reproductve behavor, and even place of resdence (Desa & Alva, 1998; Glewwe, 1999; Frost Forste, & Haas, 25). The nqury to the relatonshp between maternal educaton and ts pathways has touched on several aspects of the ssue. One of these concerns s the relatonshps between formal schoolng and nutrtonal and health knowledge (Glewwe, 1999; Webb & Block, 24). Glewwe (1999) argues that there exst three possble mechansms through whch formal schoolng nfluences maternal health knowledge. Frst, future mothers drectly acqure health knowledge 6

3 from formal schoolng. Second, the lteracy and numeracy sklls acqured n school assst future mothers n dagnosng and treatng chld health problems. Thrd, exposure to modern socety through formal schoolng makes women more receptve to modern medcal treatments. Based on data from Morocco, Glewwe fnds that mother s health knowledge alone appears to be the crucal skll for rasng chld health. He then suggests that health educaton should be drectly taught n schools at a young age so that grls wll have some knowledge even f they drop out of school early. The multdmensonal mpacts that educaton and ts pathways have on chld health outcome are far from trval. Important connectons exst not only between maternal educaton and ts lnkages but also between the lnkages themselves. Socoeconomc status affects healthseekng behavor by facltatng access to modern health care utlzaton. Socoeconomc status also enhances maternal nutrtonal and health knowledge. Nutrtonal knowledge may also augment the mpact of ncome or socoeconomc status on chld health. Chrstaensen and Alderman (24) explore the role of maternal nutrtonal knowledge n augmentng the mpact of ncome on chld stuntng n Ethopa. In ther study, maternal nutrtonal knowledge s measured by the communty s dagnostc capablty of growth falterng. Usng data from three consecutve welfare-montorng surveys over the perod , they fnd that that household resources, food prces, and parental educaton are key determnants of chld malnutrton. Most mportantly, Chrstansen and Alderman show that maternal nutrtonal knowledge plays an mportant role n the determnaton of chld malnutrton. The avalable fndngs on the relatonshps between maternal educaton and chld health are also challenged by the choce of a proxy for chld health. Unlke most of the lterature that does not dscrmnate between types of malnutrton, Webb and Block (24) nvestgate the effect of formal schoolng and mother s nutrtonal knowledge on chronc and acute malnutrton. Usng data from rural Central Java, Indonesa, Webb and Block argue that t s crtcal to dstngush the effects of formal schoolng from the effects of specfc nutrton knowledge. Ther fndngs show that formal schoolng s more responsve to long-term malnutrton than short-term. They also note that formal schoolng s among the mportant sources of nutrton knowledge. Another aspect of the debate on maternal educaton and chld nutrtonal status deals wth the effectveness of the lnks. Some studes argue that the effect of maternal educaton on chld health s fully medated by selected pathways. For nstance, Desa and Alva (1998) analyze the effect of maternal educaton on three measures of chld health: nfant mortalty, heght for age, and mmunzaton status. Based on the frst round of DHS data from 22 developng countres, they argue that educaton s a proxy for socoeconomc status and geographc resdence. Therefore, they argue that, when these varables are ncorporated n the model, the effect of maternal educaton largely dsappears and only retans ts sgnfcance n a handful of countres. However, recent evdence shows that the drect effect of educaton remans sgnfcant n fully specfed models. In ths regard, Frost, Forste, and Haas (25) consder a more Internatonal Journal of Afrcan Development v.1 n.2 Sprng 214 7

4 comprehensve lst of pathway varables. Usng data from the 1998 Bolvan DHS, they examne selected pathways, ncludng socoeconomc status, health knowledge, modern atttudes toward health care, female autonomy, and reproductve behavor (p. 4). 1 They fnd that socoeconomc factors are the most mportant pathways lnkng educaton and chld nutrtonal status. They also fnd that the effect of maternal educaton remans sgnfcant after controllng for all pathway varables as well as geographc regons and place of resdence. The revew presented here s bref, focusng only on major debates regardng maternal educaton and chld health outcomes. However, at least two observatons can be noted from the on-gong debate. Frst, although the role of maternal educaton on chld health outcome s obvous, there s a broad dsagreement on the channels through whch maternal educaton nfluences chld health n the long term (chronc case) and the short term (acute case). Second, most of the emprcal evdence s on chronc than acute malnutrton. Ths study ams to add to the exstng lterature by consderng the effect of maternal educaton and selected pathway varables on chronc and acute chld malnutrton n Ethopa. 3. Background: Chld Nutrtonal Status n Ethopa The conventonal measures of chld anthropometrcs show that the prevalence of chld malnutrton n Ethopa s among the hghest n sub-saharan Afrca. In 23, 52% of chldren were sufferng from chronc malnutrton (stuntng), 11% from acute malnutrton (wastng), and 47% from underweght. Durng the same perod, the average prevalence of stuntng, wastng, and underweght for Afrcan countres were 39%, 9%, and 29%, respectvely. A recently completed survey n Ethopa, the 25 EDHS, shows a smlar profle of under-fve malnutrton (Table 1). Another mportant feature of chld nutrtonal status n Ethopa s that the prevalence can be dstngushed by selected background characterstcs. Table 1 presents the prevalence of chld nutrtonal status by maternal educaton and place of resdence n 2 and 25. It shows that the ncdednce of malnutrton among chldren whose mothers have some educaton s lower than those whose mothers wth no educaton. The percent of chldren malnourshed consstently declnes as the hghest level of educaton attaned by the mother ncreases from no educaton to prmary educaton, and then to secondary and hgher educaton. The trend s consstent across dfferent ndcators of chld malnutrton and survey years. 1 All except reproductve behavor are constructed by prncpal component analyss from a number of related varables ncluded n the Bolvan DHS. Each pathway ncorporates several nterrelated ndcators. For nstance, socoeconomc status s measured by household wealth (ownng a televson, rado, refrgerator, or phone) and household envronment (electrcty, pped water, flush tolet, and non-drt floor) (see Frost, Forste, and Haas, 25, p. 4) 8

5 Table 1. Chld Malnutrton by Maternal Educaton and Place of Resdence % of chldren sufferng from Stuntng Wastng Underweght % % % Background 2 25 Change 2 25 Change 2 25 Change Maternal educaton No educaton Prmary Secondary & hgher Place of resdence Urban Rural Total Source: 2 and 25 EDHS (Central Statstcal Authorty, 21; ORC Macro, 26) Note: Stunted = heght for age z-scores below 2; wasted = weght for heght z scores below 2; and underweght = weght for age z scores below 2 (World Health Organzaton, 1986). Table 1 also shows that the prevalence of malnutrton n general s lower n 25 than n 2. The percentage declnes over the perod 2 25 show that the reductons n chld malnutrton (for stuntng and underweght) s the hghest for the hghest level of maternal educaton (whch s secondary and hgher educaton ) and the lowest for the lowest level of educaton (whch s no educaton ). However, there s no consstent declne for wastng. Ths could be due to the fact that stock varables such as educaton and place of resdence better explan chronc outcomes such as stuntng than acute fluctuatons n nutrtonal status. As expected, the urban advantage presented n Table 1 s unambguous when the performance of chld nutrtonal status s dsaggregated by place of resdence wthout controllng for other factors. In addton, the comparson between the 2 and 25 survey results shows that the reductons n chld stuntng and underweght are larger n urban than n rural areas. However, a number of studes fnd that any concluson based on a smple bvarate relatonshp would be msleadng because the advantage often dsappears when other mportant varables are ncluded (Fotso, 26). The kernel densty plots n Fgures 1 and 2 corroborate the results n Table 1. Fgure 1 shows that the dstrbutons can be dfferentated by maternal educaton n natonal, rural, and urban samples. In each panel, the dashed lnes are to the rght of the sold lnes showng the expected dfferences n heght for weght z-scores (HAZ) and weght for heght z-scores (WHZ) of chldren by maternal educaton. The mpact of maternal educaton s larger n HAZ and than n WHZ (compare columns: Panels A1, B1, and C1 vs. Panels A2, B2, and C2). It s also larger n rural than n urban areas (compare rows Panel B1 and B2 vs. Panels C1 and C2). Internatonal Journal of Afrcan Development v.1 n.2 Sprng 214 9

6 Smlarly, Fgure 2 shows kernel densty plots of HAZ and WHZ for natonal (all), rural, and urban chldren by survey year. Each panel comprses two plots for each survey year. The objectve of the plots n each panel s to show f there were changes n the dstrbuton between the two surveys. Panels D1 and D2 are for the natonal sample, Panels E1 and E2 are for the rural sample, and Panels F1 and F2 are for the urban sample. In all the three cases, the denstes n 25 are to the rght of that of the 2, mplyng mprovements n chld nutrton n 25. The statstcal sgnfcance of the dfferences n chld nutrtonal status by background characterstcs and tme presented above (Fgures 1 and 2 and Table 1) s checked by executng a Kolmogorov-Smrnov (KS) test of equalty between the two emprcal dstrbutons. In ths test, the three null hypotheses are (1) H: F some educaton(z)= F no educaton,(z) z, (2) H: F urban(z)= F rural(z ) z, and (3) H: F25(z)= F2(z) z. The KS test s based on the largest absolute gap between the cumulatve dstrbutons of F 1 and F where there are m observatons for dstrbuton 1 and n observatons for dstrbuton,.e., F ( z ) 1 n n 1 1 y z otherwse and F ( 1 z ) 1 m m 1 1 y z otherwse, where z s an ndcator of chld nutrtonal status, ncludng HAZ, WHZ, and WAZ. Then, the test statstc s obtaned from the supermom of the absolute values of the dfferences n the two emprcal cumulatve dstrbuton functons,.e., D max F ( z ) F ( z ). z 1 1

7 Fgure 1. Densty Estmates of HAZ and WHZ by Maternal Educaton.5 Densty Densty Heght for Age z-scores (HAZ) No Educaton Some Educaton (A1) HAZ by Maternal Educaton: Natonal Sample Weght for Heght z-scores (WHZ) No Educaton Some Educaton (A2) WHZ by Maternal Educaton: Natonal Sample.5 Densty Densty Heght for Age z-scores (HAZ) Weght for Heght z-scores (WHZ) No Educaton Some Educaton No Educaton Some Educaton (B1) HAZ by Maternal Educaton: Rural Sample (B2) WHZ by Maternal Educaton: Rural Sample Densty Heght for Age z-scores (HAZ) No Educaton Some Educaton (C1) HAZ by Maternal Educaton: Urban Sample Densty Weght for Heght z-scores (WHZ) No Educaton Some Educaton (C2) WHZ by Maternal Educaton: Urban Sample Internatonal Journal of Afrcan Development v.1 n.2 Sprng

8 Fgure 2 Densty Estmates of Stuntng and Wastng by Survey Year n 2 and Heght-for-Age z-scores (WAZ) HAZ 2 HAZ Weght-for-Heght z-scores (WHZ) WHZ 2 WHZ 25 (D1) HAZ by Survey Year: Natonal Sample (D2) WHZ by Survey Year: Natonal Sample Heght-for-Age z-scores (HAZ) Weght-for-Heght z-scores (WHZ) HAZ 2 HAZ 25 WHZ 2 WHZ 25 (E1) HAZ by Survey Year: Rural Sample (E2) WHZ by Survey Year: Rural Sample.5 Densty Densty Heght-for-Age z-scores (HAZ) Weght-for-Heght z-scores (WHZ) HAZ 2 HAZ 25 WHZ 2 WHZ 25 (F1) HAZ by Survey Year: Urban Sample (F2) WHZ by Survey Year: Urban Sample 12

9 Table 2 presents results of the KS test of equalty of dstrbutons for wastng 2, stuntng, and underweght for natonal, rural, and urban samples. The p-values show that, n all three cases, the null hypothess that the two dstrbutons are the same s rejected at less than 1% level of sgnfcance. Therefore, consstent wth the densty plots n Fgure 2, the test result ndcates sgnfcant mprovement n chld nutrtonal status. Table 2. Kolmogorov-Smrnov Test of Equalty of Dstrbutons of HAZ, WHZ, and WAZ Test category Nutrton Indcator Sample Natonal Rural Urban Maternal educaton: HAZ.15**.77**.154** Some educaton vs. No educaton WHZ.115**.67**.132** WAZ.182**.93**.182** Place of resdence: Urban vs. rural HAZ.27** - - WHZ.125** - - WAZ.246** - - Survey year: 25 vs. 2 HAZ.74**.79**.9** WHZ.8**.84**.9** WAZ.8**.89**.123** Note: The test compares cumulatve dstrbutons of each malnutrton ndcator n 2 and 25; ** = p- value <.1. It s mportant to note that the reductons n stuntng and underweght durng the perod 2 25 are not only statstcally sgnfcant but also numercally substantal, carryng mportant economc mplcatons. In 25 about 13 mllon (17%) of the total Ethopan populaton of 77.4 mllon were between ages and 4. Therefore, the declne n stuntng by 5 percentage ponts,.e., from 51.5% n 2 to 46.5% n 25, mples that there were 653, fewer stunted chldren n 25 than there would have been f the percent of stuntng remaned the same as n 2. Smlarly, the declne n underweght by 8.8 percentage ponts (from 47.2% n 2 to 38.4% n 25) would mean that there were 1.15 mllon fewer underweght chldren than there would have been f the percent of underweght remaned the same as n 2. Therefore, these developments agan motvate the questons: what are the relevant factors, and to what extent do maternal educaton and ts pathways explan chld malnutrton n Ethopa? 2 Although the test of equalty of dstrbuton shows that wastng has sgnfcantly declned n 25, the mprovement n z-scores s to the rght of the cutoff pont, -2SD (Fgure 2, Panel D2). Therefore, the proporton of wasted chldren remans the same. However, the results n Table 2 mply that those chldren who were not wasted n the 25 sample had a better nutrtonal status than those n the 2 sample Internatonal Journal of Afrcan Development v.1 n.2 Sprng

10 The Emprcal Framework 4. Multvarate Analyss The standard procedure of dentfyng the determnants of chld health outcomes nvolves maxmzng the household s utlty functon subject to the bologcal or anthropometrc producton functon and other constrants (Ptt & Rosenzweg 1985; Thomas, Lavy, & Strauss, 1996; Webb & Block, 24). Equaton (1) presents the household s utlty maxmzaton problem, whch s a functon of H (health status), F (food ntake), L (lesure), and G (consumpton of other goods). Health of household members and food ntake enter drectly and separately nto the utlty functon because health s good n tself and food s taken for reasons other than nutrtonal value. The utlty functon may also be condtoned by observable ndvdual characterstcs (X), household characterstcs (Xh), communty characterstcs (Xc), and unobserved heterogenety of preferences (ψ). max U U(H,F,L,G ;X,X,X,ψ ) U ( ), U ( ) (1) H,F,L,G h c The household maxmzes the utlty functon subject to a budget constrant and a bologcal health producton functon gven by H H(F,M,X,Xh,Xc,η ), (2) where H s nutrtonal status as measured n anthropometrcs outcomes (e.g., heght or weght), M are non-food health nputs, η s unobserved ndvdual health endowments, and all other varables are as defned earler. Then, the maxmzaton problem leads to a reduced form demand functon for nutrtonal status: H h(x,xh,xc, ν ), (3) where ν s unobserved nutrtonal outcome. Equaton (3) provdes a benchmark specfcaton for emprcal analyss. 3 Equaton (3) bascally specfes nutrtonal status as a functon of ndvdual, household, and communty characterstcs. An mportant lmtaton of ths approach s that t does not allow nferrng structural coeffcents. However, the reduced form equaton s stll nformatve about the effects on nutrton of changes n the explanatory varables thereof. There are a wde range of varatons n the specfcaton of the emprcal model of chld nutrtonal status n the lterature. Varants of the emprcal models derved from Equaton (3) often emanate from the choce of the dependent varable as well as the defnton and measurement of ndvdual, household, and communty characterstcs. The avalablty of data also dctates the 3 Estmatng structural equaton nvolves endogenous factors such as chld health nputs. However, due to dffcultes n fndng nstruments, most studes estmate a condtonal demand functon gven by Equaton (3) (e.g., Glewwe, 1999; Chrstaensen and Alderman, 24; Webb and Block, 24; Frost, Forste, and Haas, 25). 14

11 emprcal specfcaton. Equaton (3) can be rearranged to specfy an emprcal model that dstngushes maternal educaton, pathway varables, and other control varables. Incorporatng Pathway Varables Four key pathways are consdered: (1) socoeconomc status, (2) health-seekng behavor, (3) knowledge of health and famly plannng, and (4) reproductve behavor. Socoeconomc status. Maternal educaton has a clear connecton wth the varous key elements of socoeconomc status, ncludng hgh-ncome job, possesson of assets, better health, and santary condtons, to menton but a few. The emprcal evdence demonstrates the exstence of a strong postve relatonshp 4 between socoeconomc status and chld health outcomes. Therefore, socoeconomc status stands out to be an mportant pathway channel between maternal educaton and chld health. Health-seekng behavor. Educaton can also nfluence health care utlzaton and reproductve health behavor. As Pongou, Ezzat, and Salomon (26) note, n some tradtonal socetes, educaton would provde the mother wth the capacty to break wth some tradtonal practces and taboos. Educaton promotes modern atttudes, and hence mothers wth hgher levels of educaton are more lkely to seek health care servces from health centers and health professonals. Educated mothers are also more lkely to accept and use famly plannng methods, ncludng contraceptves. Knowledge of famly plannng and health. Educaton enhances mother s knowledge of health, whch s an mportant predctor of chld health outcome (Glewwe, 1999; Webb and Block, 24). Health knowledge can drectly be acqured from formal educaton. Educaton can also facltate the mother s ablty to understand the causaton and preventon methods of llness. It also enhances her knowledge of nutrton and famly plannng. However, Frost, Forste, and Haas (25) revew ndcates that the avalable emprcal evdence on the relatonshp between maternal health knowledge and chld health s nconclusve. Reproductve behavor. Reproductve behavor s another mportant lnk through whch educaton nfluences chld health outcome. In general, educated women have more control over ther reproductve behavor and make conscous decsons for example, on the number of brths and ntervals. Reproductve behavor s proxed by mother s age and selected chld demographc characterstcs. Relevant chld characterstcs nclude age, sex, brth order, and precedng brth nterval. 5 Vast evdence shows that the rsk of chld malnutrton ncreases wth age n developng countres. Webb and Block (24, p. 812) fnd, though, that HAZ and WHZ declne wth age wth 4 Strong postve relatonshp wth nutrtonal status means strong negatve relatonshp wth stuntng and wastng. 5 It should be noted that, not all these demographc varables are responsve to maternal educaton. Therefore, some such as sex and age of chld are ncluded as addtonal control varables. Internatonal Journal of Afrcan Development v.1 n.2 Sprng

12 a postve second dervatve. An explanaton for ths relatonshp s the nutrtonal value of breastfeedng that protects young chldren from the rsk of stuntng or wastng at early age (Pongou, Ezzat, & Salomon, 26) and, potentally, shortage of supplemental food n later months. In addton, some measures of malnutrton, such as stuntng, are results of cumulatve process of nadequate detary ntake and llness. Therefore, younger chldren are at lower rsk (Webb & Block, 24). The ratonale for ncludng gender n the model of chld nutrton s to capture the presence of male-bas n ntra-household allocaton of resources (Behrman, 1997). 6 However, the emprcal evdence supportng ths hypothess remans scarce. Based on a revew of 36 chld nutrton surveys conducted snce 1985 n a number of developng countres, Marcoux (22) fnds no sex dfferences n 227 surveys. In fact, the evdence from Afrca and some other developng countres n Asa and Latn Amerca shows that, when sgnfcant dfferences exst, boys are more lkely to be malnourshed than grls. Brth order measures party whle brth nterval captures the care and support that have been made avalable to the chld. The emprcal evdence on party s mxed. For example, n Inda, Jeyaseelan and Lakshman (1997) fnd that malnutrton s hgher among chldren of hgher brth order (5+). On the other hand, n Ethopa, Grma and Genebo (22) fnd that the rsk of stuntng s hgher among frst brths. However, t s common to fnd that the rsk of malnutrton declnes wth brth nterval (Pongou, Ezzat, & Salomon, 26). Fnally, place of resdence and geographc regons are ncluded as control varables n most specfcatons. It should be noted however that these controls are also nfluenced by maternal educaton. Educaton ncreases moblty and creates more opportuntes n urban than rural areas. Desa and Alva (1998) fnd that n addton to socoeconomc factors, geographcal controls are mportant lnks through whch the mpact of maternal educaton on chld health outcome s medated. Data and Measurement of Varables The data. Ths study uses two waves of the Ethopa Demographc and Health Survey (EDHS) avalable at the tme of wrtng (Central Statstcal Agency, 21; ORC Macro, 26). The frst survey was completed n 2 and the second survey n 25. The EDHS sample s stratfed, clustered, and collected wth a two-stage probablstc samplng technque based on the lst of enumeraton areas of the 1994 Populaton and Housng Census of Ethopa. Therefore, the descrpton and analyss undertaken n ths study take nto account the nature of the data. 6 Another form of gender based human captal outcome would result from fertlty behavor. Jensen (22) argues that female chldren may have more sblngs than male chldren as a result of son-preferrng dfferental-stoppng behavor n fertlty,.e., on average, females come from a larger famly sze where all chldren are worse off. Therefore, even f there s equal treatment at the household level, there may be unequal outcome at aggregate level. In some tradtonal socetes, son-preferrng behavor would result n nequaltes n nutrtonal outcomes (Tarozz and Mahajan, 27). 16

13 Accordngly, the sample weght, sample strata, and prmary samplng unts are ncluded. At the frst samplng stage n the 2 survey, 539 (138 urban and 41 rural) clusters were selected. In the 25 survey, 54 (145 urban and 395 rural) clusters were selected. The second stage conssted of the selecton of a representatve sample of households and women aged years old n each household. Accordngly, n the 2 survey, 15,367 women from 14,72 households were selected. In the 25 survey, 14,7 women from 14,5 households were selected. In both surveys, women were asked questons about ther chldren, especally for those younger than 5, and anthropometrc measurements (heght and weght) were taken. In the 2 and 25 surveys, the total number of chldren measured and whose mothers were also ntervewed were 9,774 and 4,296, respectvely. Measurement of varables Dependent Varable: Chld Nutrtonal Status. Long-term or chronc malnutrton s measured by heght for age (HAZ), whle short-term or acute malnutrton s measured by weght for heght (WHZ). A chld s deemed stunted f HAZ score s less than 2SD and wasted f WHZ score s less than 2SD. Therefore, the dependent varable s a dchotomous varable that takes 1 f the chld s stunted or wasted, and otherwse. Explanatory Varables. The prmary varables of nterest are maternal educaton and pathway varables. The models are also controlled for geography (place of resdence and regons) and survey year. The varables are measured as follows. The DHS data comple maternal educaton n two dfferent forms: sngle years and hghest level of educaton. For ease of nterpretaton, sx categores are consdered followng the DHS classfcaton. These are: (1) no educaton, (2) ncomplete prmary educaton, (3) complete prmary educaton, (4) ncomplete secondary educaton, (5) complete secondary educaton, and (6) hgher educaton. The correspondng values from the smallest to the hghest educaton category range from -5. Socoeconomc status s measured dfferently n dfferent studes. Frost, Forste, and Haas (25) construct two ndex varables from selected household assets and dwellng characterstcs. However, for ths study the DHS wealth ndex s used because n addton to a number of household assets and dwellng characterstcs, t consders the household s demographc structure. 7 Assets and amentes ncluded n the DHS wealth ndex range from the possesson of tems (e.g., bcycles, cars, rados, sofas, and televsons); dwellng characterstcs, such as type of floorng materal or the level of overcrowdng; household facltes such as source of drnkng water, type of tolet faclty, and type of cookng fuel; and other characterstcs related to wealth status. 7 The pros and cons of the DHS wealth ndex have been noted. On the one hand, the DHS surveys are often mplemented n countres where ncome tself may not be the most relable or even avalable way of measurng socoeconomc status. On the other hand, the ndex s constructed from urban-based socal and economc amentes and may be measurng urbancty nstead of socoeconomc status. Internatonal Journal of Afrcan Development v.1 n.2 Sprng

14 Mother s health-seekng behavor s an ndex varable constructed from utlzaton of selected preventve health care servces. It s constructed by prncpal component analyss from four related varables ncluded n the EDHS (Table 3). These are: (1) receved prenatal servces from a health professonal or a traned brth attendant; (2) delvered a baby at a health center (hosptal, clnc, others); (3) have used contraceptve; and (4) receved tetanus njecton before brth. Smlarly, maternal knowledge of famly plannng and health s an ndex varable constructed by prncpal component analyss from selected varables avalable n the 2 and 25 EDHS. Health knowledge s measured by knowledge of oral rehydraton therapy,.e., f the woman heard of or used oral rehydraton therapy. Famly plannng knowledge s measured by knowledge of ovulaton cycle,.e., f the woman knows when durng her ovulaton cycle she can get pregnant. Addtonal factors ncluded n the knowledge ndex are proxes of famly plannng nformaton from rado, TV, newspaper, and frequences of readng newspaper, lstenng to rado, and watchng TV (Table 3). Reproductve behavor s proxed by maternal age and selected chld characterstcs such as age, sex of chld, brth order, and brth nterval. Chld age s n months and maternal age s n years. Both are n logs. The remanng namely, sex of chld, brth order, and precedng brth ntervals are dummy varables. Table 3. Factor Analyses of Health-Seekng Behavor and Knowledge Indces Sample Mean Factor Loadngs Varable α Health-Seekng Behavor Index Delvered a baby n modern health faclty Receved prenatal from a health professonal Receved tetanus njecton before brth Used contraceptve Knowledge Index Has heard of oral rehydraton therapy Knows when n ovulaton cycle can get pregnant Frequency of readng newspaper Frequency of lstenng to rado Frequency of watchng TV Heard of famly plannng from rado Heard of famly plannng from TV Read about famly plannng from newspaper Source: EDHS 2 and 25 (Central Statstcal Authorty and ORC Macro, 21, 26) Note: α s a relablty coeffcent or Cronbach s alpha. It s greater than.7 n both cases, whch s wthn acceptable range. 18

15 Fnally, Table 4 presents descrptve statstcs of the model s varables ncluded n the regressons, excludng control dummy varables for place of resdence and geographc regons. Table 4. Descrptve Statstcs of Model Varables Varables 2 EDHS 25 EDHS Mn Max Mean SD Mn Max Mean SD Heght for age (HAZ) z-score Weght for heght (WHZ) z-score Stunted (HAZ<-2SD=1) (b) Wasted (WHZ<-2SD=1) (b) Maternal educaton Wealth ndex Health ndex Knowledge ndex Chld: Gender (Male=1) (b) Chld: age (months & n logs) Chld: age squared Chld: Brth order >3 (b) Chld: Brth nterval > 2years (b) Mother: age (years & n logs) Mother: age squared Source: 2 and 25 EDHS (Central Statstcal Authorty and ORC Macro, 21, 26). Note: (b )= bnary ndcators; Mn = mnmum value; Max = maxmum value; and SD = standard devatons. 5. Results and Dscusson The multvarate analyss results are based on the estmaton of the varous specfcatons of Equaton (3). As ndcated earler, the dependent varable s a dchotomous varable. Therefore, the models are estmated usng logstc regresson. The logstc regresson model fts the log odds or logts by a lnear functon of the explanatory varables as follows: logt(p ) ln[ p ] x'β, where p s the probablty that the chld s stunted or wasted condtonal on x, whch s a vector of p explanatory varables ncluded n Equaton (3); ln[ ] s the log odds of the outcome; and α and β are the parameters to be estmated. Maternal Educaton and Chronc Malnutrton Table 5 reports the log odds of varous specfcatons of chronc malnutrton, stuntng. Model 1 s the baselne model wth only maternal educaton ncluded as a prmary explanatory varable after controllng for survey year. 8 Model 2 adds geographc controls (place of resdence and regons) to Model 1. Models 3 6 each add a pathway varable to the baselne model after 1 p 1 p 8 The pooled (2 and 25) data are used n all models. Therefore, all are controlled for by a survey year dummy. Internatonal Journal of Afrcan Development v.1 n.2 Sprng

16 controllng for place of resdence, regons, and survey year. In ths row, Model 3 s the socoeconomc status model; Model 4 s the health-seekng behavor model; Model 5 s the knowledge model; and Model 6 s the reproductve behavor model. Fnally, Model 7 presents the full model wth all the prmary explanatory varables and control varables ncluded. Maternal educaton s sgnfcant n the baselne model (Model 1), where t s controlled only for survey year. Model 2 shows that the addton of geographc controls to the baselne model reduces the educaton effect whle the sgnfcance of the educaton varable remans unchanged. Models 3 6 show that, except for the health-seekng behavor, all other pathways (socoeconomc status, knowledge, and reproductve behavor) are sgnfcant, and the educaton effect s sgnfcant but lower n absolute value when compared to the baselne model. However, n the full model (Model 7), maternal educaton, socoeconomc status and some reproductve behavor varables are sgnfcant. The declne n the sgnfcance of some of the pathway varables could be due to multcollnearty ether wth maternal educaton or socoeconomc status or both. The top row of Table 5 shows that the log odds assocated wth maternal educaton declne from.27 to.16 n absolute value. It appears that each level of educaton decreases the relatve probablty of stuntng by 24% ( = [1-exp (log odds)]*1) n the baselne model. 9 The mpact declnes to 15% n the full model (see also Table 7). Therefore, the declne n the drect effect of educaton from 24% to 15% means that the pathways and geographc controls explaned only about 38% of the educaton effect. Referrng to the full model (Table 5, Model 7), the mportant predctors of stuntng are, therefore, maternal educaton, socoeconomc status, and reproductve behavor. Socoeconomc status s the most mportant predctor of stuntng as demonstrated by the magntude of the coeffcent (log odds) and ts sgnfcance. The lkelhood of stuntng also ncreases wth chld age at a decreasng rate and ncreases wth maternal age at a decreasng rate. Smlar to earler fndngs n Afrca and other developng countres (e.g., Marcoux, 22), but n contrast to other studes on Ethopa (e.g., Grma and Genebo, 22), the male dummy s sgnfcant, mplyng that male chldren are more lkely to be stunted than females. 9 For a unt ncrease n the j th regressor, the dervaton and nterpretaton s as follows: exp( x' β) ncreases to p exp( x' β β j) exp( x' β) *exp(β j). Hence the odds rato [ 1 p ] ncreases by a multple exp(β ) j. Thus, for example, the logt slope parameter of.1 means a unt ncrease n the regressor multples the ntal odds rato by exp(.1) = 1.15, whch s a proportonate ncrease of.15 tmes the ntal odds rato. Therefore, the relatve probablty of beng stunted ncreases or decreases (dependng on the sgn of the coeffcent n the logt model) by 1.5 percent (Cameron and Trved, 25, p. 47). 2

17 Table 5. Logstc Estmates of Chld Stuntng (pooled sample) Varable Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Maternal educaton -.27** -.23** -.19** -.23** -.17** -.23** -.16** (-7.41) (-5.46) (-4.31) (-4.7) (-3.56) (-5.44) (-2.65) Socoeconomc status -.28** (2.96) -.37** (-3.4) Health-seekng behavor -.4 (-1.38) -.5 (-1.6) Knowledge -.8** (-2.7) -.4 (-.8) Reproductve behavor.9.17** Chld: gender (Male=1) (1.94) (2.89) Chld: age (ln) 3.86** (11.18) 3.85** (9.51) Chld: age squared -.52** -.5** (-9.34) (-7.4) Chld: brth order > 3.28** (3.58).12 (1.23) Chld: brth nterval > years (-1.34) (-1.38) Mother: age (ln) 7.76** (2.63) 6.87* (2.9) Mother: age squared -1.21** -1.7** (-2.78) (-2.21) Resdence: (Urban=1) (-.35) (1.15) (-.5) (.18) -(.49) (1.33) Survey year: (25=1) -.19** -.18** -.16** ** (-3.6) (-2.97) (-2.62) (-1.49) -(2.84) (-3.36) (-1.12) ** -.43* -.53** -.53** ** -18.2** Constant (3.38) (-2.7) (-2.24) (-2.67) (-2.78) (-3.94) (-3.29) Regonal varaton? a Yes Yes Yes Yes Yes Yes No b Pseudo R square Log Lkelhood -9,74-9,632-9,62-6,484-9,556-8,844-5,681 LRCh2 186** 331** 355** 245** 343** 1,99** 1,764** # of observatons 12,463 12,463 12,463 8,572 12,35 12,463 8,498 Note: t-statstcs n parentheses; * and ** denote sgnfcance at 5% and 1% level, respectvely; a regonal varaton refers to the 11 geographc regons wth Adds Ababa as a reference category; b no varaton for most regons except for Dre, Dawa, and Gambella regons, where they are found better than the reference category. The place of resdence dummy (urban = 1) s nsgnfcant n all models. The result s expected n multvarate settng due to the fact that the urban advantage s captured by other better measures of urban-based socal and economc amentes (Fotso, 26). However, some regons (Tgray, Afar, Amhara, Oromya, Somal, and SNNP) are found sgnfcantly dfferent from the reference regon, Adds Ababa (Model 2). A chld from one of these regons s more lkely to be stunted when compared to a chld from the reference regon, Adds Ababa. The regonal varaton obtaned n Models 2 6 could be due to dfferences n the level of urbanzaton. Internatonal Journal of Afrcan Development v.1 n.2 Sprng

18 Fnally, the dscusson n Secton 3 suggested sgnfcant changes n stuntng occurred over tme. However, the results of the full model n Table 5 show that the survey year dummy s nsgnfcant, suggestng the absence of dfference between 2 and 25 when other factors are consdered. Thus, the observed change n stuntng over tme s attrbutable to changes n other factors ncludng maternal educaton, socoeconomc status and reproductve behavor. Table 6. Logstc Estmates of Chld Wastng (pooled sample) Varable Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Maternal educaton -.23** (-4.5) -(1.88) (-.87) (-1.48) (-1.21) (-1.9) (-.98) Socoeconomc status -.42** -.41** (-3.1) (-2.63) Health-seekng behavor (-1.26) (-.79) Knowledge (-.77) (.58) Reproductve behavor.14.2* Chld: gender (Male=1) (1.81) (2.35) Chld: age (ln) 3.13** 3.44** (6.11) (5.21) Chld: age squared -.59** -.64** (-6.64) (-5.39) Chld: brth order > (1.11) (-.25) Chld: brth nterval > * (1.55) (2.8) Mother: age (ln) (1.57) (1.54) Mother: age squared (-1.56) (-1.54) Resdence: (Urban=1) -.56** * -.52* -.54** -.1 (-2.83) (-.45) (-2.7) (-2.43) (-2.63) (-.4) Survey year: (25=1) (.16) (-.79) (-.78) (-.82) (-.76) (-.67) (-.51) Regonal varaton? a Yes Yes Yes Yes Yes Yes N Pseudo R square Log lkelhood -4,82-4,79-4,78-3,518-4,756-4,669-3,399 LRCh2 33.3** 94.6** 113.7** 75.4** 94.9** 342** 284** # of observatons 12,637 12,637 12,637 9,61 8,66 12,637 8,585 Note: t-statstcs n parentheses; * and ** denote sgnfcance at 5% and 1% level, respectvely; a regonal varaton refers to the 11 geographc regons wth Adds Ababa as a reference category; b no varaton for all regons except for Somal Regon where the lkelhood of chld wastng s found larger than the reference category. Maternal Educaton and Acute Malnutrton Table 6 reports logstc regresson results of acute malnutrton, wastng. The presentaton n Table 6 follows the same approach used earler n Table 5. Therefore, the frst row n Table

19 demonstrates how the effect of educaton on wastng changes as a new pathway varable s added to the baselne model. The comparson of results n Table 5 and Table 6 would show the dfferences and common features of models of chronc and acute malnutrton. Frst, n Table 6, maternal educaton s nsgnfcant n all except the baselne model. Second, both educaton and the two pathway varables of health-seekng behavor and knowledge are also nsgnfcant as shown n models 4 and 5. However, smlar to the chronc malnutrton case, socoeconomc status and selected reproductve behavor varables are sgnfcantly related to acute malnutrton. In addton, geographc and survey year controls are found to have a smlar pattern. Robustness Tests: Alternatve Sample Domans Tables 7 and 8 report logstc regresson results of the full models of stuntng and wastng, respectvely, based on alternatve sample domans. The estmatons are based on a dsaggregated data by survey year and place of resdence. Each table ncorporates four models. The frst two models are for each survey year: 2 and 25. The thrd and the fourth models are for rural and urban chldren, respectvely. Table 7. Logstc Estmates of Chld Stuntng by Survey Year and Place of Resdence 2 25 Rural Urban Maternal educaton -.14 (-1.76) -.18 (-2.4)* -.21 (-2.73)** -.7 (-.63) Socoeconomc status -.37 (-2.74)** -.48 (-2.33)* -.36 (-2.6)** -.61 (-2.71)** Health-seekng behavor -.5 (-1.35) -.6 (-.98) -.3 (-.73) -.13 (-1.98) * Knowledge -.5 (-.8) -.1 (-.2) -.5 (-.95). (-.2) Reproductve behavor Chld: gender (Male=1).16 (2.42) *.19 (1.8).23 (3.75)** -.38 (-1.92) Chld: age (ln) 3.7 (7.46) ** 4.27 (6.84) ** 4.3 (9.94)** 1.91 (1.55) Chld: age squared -.47 (-5.71)** -.58 (-5.42)** -.53 (-7.68)** -.19 (-.93) Chld: brth order >3.8 (.63).26 (1.59).16 (1.66) -.8 (-.19) Chld: brth nterval > (-1.68).2 (.17) -.9 (-1.11) -.23 (-1.8) Mother: age (ln) 1.35 (2.61) ** (-.52) 5.89 (1.76) (1.27) Mother: age squared (-2.69)**.34 (.41) -.93 (-1.89) (-1.26) Resdence: (Urban=1).36 (1.4).26 (1.2) Survey year: (25=1) (-.84) -.37 (-1.67) Constant (-3.58)** (-.21) (-2.95)** (-1.48)** Regonal Varaton? No No Yes Yes Pseudo R square Log Lkelhood -4,14-1,654-5,79-55 LRCh2 1, , # of Observatons 5,971 2,527 6,6 1,45 Note: t-stat n parenthess; * and ** denote sgnfcance at 5% and 1% level, respectvely; pooled data s used for rural and urban models; urban regons (Adds Ababa, Dre Dawa, and Harar) are excluded n the rural model and the reference category n the rural model s Tgray; the reference category for regonal dummes n all other models s Adds Ababa. Internatonal Journal of Afrcan Development v.1 n.2 Sprng

20 The results n Table 7 are generally smlar to the results n Table 5. Accordngly, socoeconomc status s sgnfcant n all cases. Educaton retans ts sgnfcance n two of the four cases. Health-seekng behavor and knowledge are nsgnfcant n most cases. However, healthseekng behavor appears sgnfcant n the urban model. Lkewse, the results n Table 8 are smlar to those of Table 6. In most cases maternal educaton and ts pathways are nsgnfcant. Table 8. Logstc Estmates of Chld Wastng by Survey Year and Resdence 2 25 Rural Urban Maternal educaton.3 (.36) -.35 (-2.33)* -.15 (-1.48).9 (.51) Socoeconomc status -.34 (-1.82) -.63 (-1.88) -.41 (-2.5)* -.35 (-1.31) Health-seekng -.1 (-.21) -.8 (-.93) -.3 (-.61) -.9 (-.9) Knowledge -.4 (-.62).15 (1.54).3 (.4) -.1 (-.11) Reproductve behavor Chld: gender (Male=1).18 (1.72).26 (1.71).19 (2.6)*.45 (1.31) Chld: age (ln) 4.46 (6.6)** 1.75 (1.62) 3.4 (4.93)** 4.4 (2.5)* Chld: age squared -.81 (-6.21)** -.34 (-1.74) -.63 (-5.1)** -.78 (-2.4)* Chld: brth order >3.3 (.21) -.7 (-.29) -.7 (-.51).26 (.56) Chld: brth nterval >2.45 (3.48)** -.33 (-1.66).24 (2.8)*.21 (.51) Mother: age (ln) 2.37 (.39) (2.27)* 9.63 (1.82) (-.52) Mother: age squared -.35 (-.39) -3.9 (-2.26)* -1.4 (-1.81) 1.55 (.48) Resdence (Urban=1) -.12 (-.36).2 (.35) Survey year (25=1) -.4 (-.37) -.15 (-.28) Constant (-1.17) -4.4 (-2.58)** (-2.57)** (.33) Regonal varaton? No No Yes Yes Pseudo R square Log lkelhood -2, , # of observatons 6,58 2,527 6,682 1,454 Note: t-stat n parenthess; * and ** denote sgnfcance at 5% and 1% level, respectvely; pooled data s used for rural and urban models; urban regons (Adds Ababa, Dre Dawa, and Harar) are excluded n the rural model and the reference category n the rural model s Tgray; the reference category for regonal dummes n all other models s Adds Ababa. 6. Dscusson Table 9 summarzes the results and compares the effect of maternal educaton on chld nutrtonal status by model type and measure of malnutrton. The log odds effects of educaton n Table 9 are obtaned from the frst rows n the prevous tables (Tables 5 8). The mpact of each level of educaton on the relatve probablty of beng stunted or wasted s calculated accordngly,.e., (1-exp(log odds)). 24

21 Table 9. The Effect of Maternal Educaton and Pathway Varables on Stuntng and Wastng by Model Type Chronc Malnutrton (Stuntng) Acute Malnutrton (Wastng) 1-exp Educaton Pathway 1-exp Pathway log (log sgnfcantvarable log (log Educaton varable Model Type odds odds)? sgnfcant? odds odds) sgnfcant? sgnfcant? Baselne Yes _ Yes _ Geographc Yes Yes No Yes SES Yes Yes No Yes Health-seekng Yes No No No Knowledge Yes Yes No No Reproductve Yes Yes No Yes Full model Natonal Yes Yes a No Yes a Rural sample Yes Yes a No Yes a Urban sample No Yes No No 2 sample No Yes No No 25 sample Yes Yes Yes No Note: SES s socoeconomc status; a some pathways only (mostly SES). Table 9 ndcates that the maxmum effect of maternal educaton on stuntng and wastng s observed n the baselne model. It s 24% for stuntng and 2% for wastng. In the full model, the effect declnes to 15% for stuntng and 11% for wastng. The table also shows that maternal educaton and ts pathways are more relevant n explanng stuntng than wastng. Except for the baselne model, maternal educaton s not sgnfcant n all other models of wastng. Another mportant observaton s that the drect effect of maternal educaton s larger n the rural than urban areas. Each level of maternal educaton n the rural sample reduces the relatve probablty of stuntng by 19%. However, t s not sgnfcant n the urban areas. Socoeconomc status s the most mportant factor of all pathways n medatng the mpact of maternal educaton on chld nutrtonal status. It s sgnfcant n all sample categores of stuntng and n the natonal and rural models of wastng. 1 The results mply that polces and programs ntended to reduce chld malnutrton and hence chld mortalty would prmarly focus on targetng the varous key elements of socoeconomc status. Socoeconomc status n ths study s measured by the DHS wealth ndex. Unfortunately, ts specfc msgvngs would make t less amenable to polcy. Frst, the key elements from whch the DHS wealth ndex s constructed are predomnantly urban based. Therefore, the ndex could smply be measurng urbancty. Second, dfferent elements contrbute to the ndex dfferently. Therefore, the ndvdual part of the ndex that essentally s drvng the mpact on chld health needs further study. Overall, the results obtaned for chronc and acute chld malnutrton are n lne wth earler related studes on other countres, ncludng Frost, Forste, and Haas (25) for Bolva, and Webb 1 The mnmum level of statstcal sgnfcance employed n ths study s 5%. However, socoeconomc status s sgnfcant at the 1% level n the 2 and 25 samples. All other pathways are very far from that value (Table 7). Internatonal Journal of Afrcan Development v.1 n.2 Sprng