1. Relationship between production diversity of Ethiopian smallholder farming households and anemia
status of pregnant women in USAID-ENGINE project areas
Krista Zillmer, Ashish Pokharel, Robert Houser
Abstract
Introduction:Anemiaamongpregnantwomenis associatedwithhigherriskof mortalityandlow birth
weightof infants.The causesof anemiaare multifacetedandthe policymakershave recognizedthe role
of multisectoralprogramsincorrectinganemiaamongothernutritionalproblems.Evidenceof the
positive association betweenincreasedfarmproductiondiversityandimproveddietquality justifiesthe
implementationof multisectoral programsincountrieslikeEthiopia,whichhashighprevalence of
anemiawith22% of pregnantwomenand17% of womenof reproductive age beinganemic.Cross
cuttingprogramslike ENGINEare implementedalongwithotheragriculturalprogramstoimprove
nutritional outcomes.
Objective:The objectiveof thisstudywasto examine the associationbetweenhouseholdproduction
diversityandthe prevalence of anemiaamongpregnantwomen.The studyexploredthe relationshipof
seasonal cropproductionandlivestockproductionwithanemiaoutcomesand examinedthe hypothesis
that increasedproductiondiversityispositivelyassociatedwithreducedanemiaprevalence among
pregnantwomen.
Methods:Thiscross-sectional studyusedsurveydatafrom4680 pregnantwomen(aged14-50 years) in
Oromiaregionof Ethiopia,where ENGINEprogramisimplemented.Twologisticregressionmodelswere
usedto examine the relationshipbetweenhouseholdproductiondiversityandanemia.The firstmodel
usedtotal productiondiversityforbothseasons.The secondmodel separatedproductiondiversityinto
crop productionscore byseasonand livestockproductionscore.Anemiawasdefinedashaving
hemoglobinlevelsbelow <11mg/DL. Importantvariablessuchaseducation,age,numberof antenatal
care visits,ironsupplementation,andweightstatuswere covariates forinthe model.
Results:Increasedtotal productiondiversitywassignificantlyassociatedwithanemiastatusduringthe
secondseason(Belg),butnotduringseason1(Meher).The resultsfromthe secondmodel using
disaggregatedscoresindicatedthatlivestockproductiondiversityscore wassignificantlycorrelatedwith
the decreasedoddsof anemiastatus.Otherfactorssuch as beingunderweightandmultiple pregnancies
alsohad significantassociationwithincreasedoddsof beinganemic.Yearsof educationseemedtohave
a positive effectondecreasedoddsof beinganemic.
Discussion:While householdproductiondiversityduringthe Belgseasonandhouseholdanimal
productionwere associatedwithreducedoddsof anemiaamongpregnantwomen,furtherevidence is
neededbeforerecommendinginterventionstrategiestoincrease households’productionof animal
source foods.Onits own,animal productionislikelyinsufficienttomake significantreductionsin
anemiaprevalence.Otherfactors,includingmaternalworkload,presence of disease,marketaccess,and
utilizationof healthservicesmustalsobe takenintoconsideration.

2. Introduction
Anemiaisa majorpublichealthconcern,asit isone of the largestnutritional deficienciesinthe world
and the prevalence of anemiaremainshighinmanycountriesof SouthAsiaandsub-SaharanAfrica[1].
Highrates of childand maternal mortalitydue tosevere anemiaisacritical publichealthissue in
pregnantwomen;andlossof productivityandfatigue inadultsandpoorcognitive andphysical growth
of childrenare the adverse economicandsocial impactsof anemia [1].The implicationsof anemiareach
beyondhealthconcernstosocial andeconomicsectorsof societyasanemiaadverselyaffects
productivityinadults [2].Froman economicpointof view,datafromdevelopingcountriesestimatethat
the economiclossesattributedtophysical andcognitive effectsof anemiaamounts to4.05% of the total
GDP [2]. Importantly,anemiaisof particularconcernforpregnantwomenbecause of itsassociation
withhighprevalence andincreasedrisksof maternal andperinatal mortality,low birthweight,and
disease prevalencelaterinlife [3].
Dietarypractices,behavioral practices,educational attainment,womenempowerment,bodyweight,
trimesterof pregnancy,andwealthstatusare associatedwithanemiastatus [4].Oftenan integrated
approach addressing all of these facetsis neededtoreduce the prevalence of anemia.The stakeholders,
bothnationallyandinternationally,have recognizedthe multifacetedcausesof anemiaandare
committedtoreducingthe prevalenceof anemia globally,especiallyamongwomenandchildrenin
developingcountries [5].Inrecentyears,there hasbeenanincreasedfocusonmultisectoralprograms
to tackle thisproblem. Keyareasof focusfor improvingoverall nutritionof womenandchildrenare
throughprograms andinterventionsinagricultural production,healthservicesforwomen,education,
targetedsupplementationof micronutrients,empowerment of women,andotherrelated interventions.
Agriculture canimprove nutritionthroughmultiplepathways.Suchpathwaysmayimprove nutritional
statusthroughdirectfoodconsumptionfromhouseholdproductionorincreasedincome through
marketsales.
Historically the majorfocusof agricultural interventionshasbeentoincrease yieldsof majorstaple
crops [6].However,there hasbeenrecentinterestinaddressingnutritional problems likeanemia
throughnutritionsensitiveagriculture[7].Joneset.al state thatincreaseddiversityof productionin
subsistence farminghouseholdshaspositive associationswith increaseddietarydiversityandthus
betterdietquality.However,mostfarminghouseholdsindeveloping countriesare acombinationof
subsistence andmarketorientedwhichmayaddcomplexitytofarmdiversityanddietdiversity
relationship [6].Regardlessof the assumptions,itisclearthatbetterdietarydiversityeitherthrough
increasedproductiondiversityorbyincreasedmarketand economicaccessislikelytoimprove anemia
statusof women.ThisissupportedbyDeClercket.al.whomentionthatincreasedfunctional
agrobiodiversitycanalleviate anemiaandhave directandindirecteffectsonhumanhealthandnutrition
[8].Similarly,evidence fromfourcountries(Bangladesh,Cambodia,Nepal andthe Philippines)
demonstratedincreasedconsumptionof nutrientrichfoodsanda reductioninanemiaprevalence
amongyoungchildreninhouseholdsthattookpart inhomesteadfoodproductionprograms [9].

3. Normally,one of the mainstrategiesforanemiatreatmentisthroughironandfolicacid
supplementation.Widespreadsupplementationof irontopregnantwomenhasbeenrecommendedfor
decadesalthough coverage isusuallyvariable.The problemwiththisstrategyisthe potentialharmful
effectsof ironsupplementationthatmayoccur in malaria-endemicareas.Evidence fromalarge
randomizedcontrolledtrial inPemba,Zanzibarsuggestedthatironsupplementationtoironreplete
childrenmayincrease the riskof malariamortality [10].Thishas highlightedthe needforadietbased
approach to treatanemia. Amongmanysmall farmhouseholds, the mechanismthroughwhichanemia
statusmay be improvedishouseholdagricultural production.Diversificationof householdproduction
has showntoincrease dietarydiversityof the household [6].Presumably,smallholderfarmerswould
consume some portionof theirproducedgoodsaside fromthatwhichissoldinthe market. In a recent
paper,Ruel et.al statedthat so far there islittle evidenceof homesteadfoodproductionprograms
havingan effectonmaternal nutritionalstatus.However,the evidence of womenempowerment
programsand behaviorchange programsonmaternal nutritional status hasbeenshown [11].
In Ethiopia,anemiaisasignificantcontributortomorbiditiesinwomenandchildren. Accordingto the
WHO global database onAnemia,in2006 anemiawasclassifiedas asevere publichealthproblemwith
75.2 % (40.7%-93.1%) of the entire populationestimatedtohave hemoglobinlevels<110gm/L [1]. More
recently,amongwomenof reproductive age,17% were anemic,with13% havingmildanemia,3%with
moderate anemiaand1% withsevere anemia.Amongpregnantwomen,the prevalence isevenhigher
at 22% [12]. Furthermore,anemiaprevalence variedbyareaof residence.There wasahigher
prevalence of anemiainrural women(18%) thanurban(11%) and geographically,the prevalence of
anemiaamongpregnantwomenrangedfrom44% inthe Somali regionto9% inAddisAbaba.This wasa
significantimprovementfrom2006, where 62.7 % of the pregnantwomenand52.7% of non-pregnant
womenwere estimatedtohave anemia[1].
ENGINE (EmpoweringNewGenerationstoImprove NutritionandEconomicOpportunities) isaUSAID-
fundedprogramwhichaimsto improve nutritional statusinEthiopiathroughamulti-sectoral approach
includinghealth,agriculture,andeducation.InterventionssuchasUSAID’sENGINE are implemented in
agriculturally productive areas coupled with existing agriculture interventions such as AGP
(Agricultural GrowthProgram) to improve service delivery and utilization of services through
training and strengthening of the health force and increasing awareness, removing
perceptions and improving knowledge and practices around nutrition and health of mothers
and primary caregivers in Amhara, Oromia, SNNPR and Tigray regions of Ethiopia.Inorderto
assessthe effectivenessof interventionmessagesandactivities,itisnecessarytoassessbaseline
characteristicsanddetermine possible associationsthatexistbetweenthese characteristicsandanemia
status.
So far,there is limited evidence on what is the most effective set of approaches to address
stuntingandanemiainEthiopia.The implementationof ENGINEprovidesaunique opportunityto
understandthe effectivenessof suchapproachesand strategies. Thiscrosssectional studyexaminesthe
relationshipof agricultural practices,namelycropproductiondiversity,andprevalence of anemiain
pregnantwomeninENGINEprojectareas.

4. Throughthe ENGINEbirthcohort study,itis expectedthatincreasedutilizationof directnutrition
interventionshasapositive effectonanemiainmothersandtheirinfantsandthatimprovement of
livelihoods through agriculture, coupled with access to directnutrition interventions, will have
positive effects on maternal health outcomes(e.g.anemia).The presentstudyaimedtoinvestigate
the relationshipbetweenhouseholdagricultural productiondiversity,whichincludesbothfoodcrop
productionandlivestockproductproduction,withanemiastatusamongpregnantwomeninthree
differentworedasof the OromiaregioninEthiopia.The studyhypothesizedthatthe production
diversityhasapositive associationinreducinganemiaprevalenceamongpregnantwomen.
Furthermore,the studywill examine the relationshipof seasonal foodcropproductiondiversityon
anemiastatus.
Methods
Data
The presentstudyanalyzedbaselinedatafromthe USAID-ENGINEEthiopiaquasi-experimental
observational birthcohortstudy.Pregnantwomen,ages14-50 were recruitedfromthree woredasfrom
the OromiaregioninEthiopia;and,foreach woreda40 womenwere recruitedfrom39kebeles
(N=4680). Data will be collectedtwice duringpregnancy,atthe birth,andthenevery3 monthsuntil the
childis24 months.The baseline datausedinthisstudy were obtainedthroughsurveysandassessments
administeredtothe pregnantwomen duringthe time of recruitment.All eligible womenwere enrolled
at the kebelelevel (whichisequivalenttothe municipalities) fromthe three woredas(whichis
equivalenttodistricts). Inaddition,the presentstudyuseddatacollectedfrombaseline survey
administeredtothe householdhead.DatawascollectedelectronicallythroughatabletusingaGather
Data software application.
Measurement
Anemia
A binaryvariable foranemiastatuswasusedasthe outcome variable.Anemiaprevalence was
determinedusingthe WorldHealthOrganization(WHO) establishedcutoffpointsforhemoglobin
measuresinpregnantwomen.The subjectisclassifiedasanemicif the measure of hemoglobinisbelow
11mg/dL. Mildanemiaisbetween10-10.9 mg/dL,moderate anemiaisbetween7-9.9mg/dL,and severe
anemiaisbelow7 mg/dL[3].
Production Diversity
Productiondiversityscoreswere calculatedusingasimple countvariablethatrangedfrom0-12. This
includescereals,roots/tubers,legumes,cashcrops,vegetables,fruits,oilseeds,spices,meat,dairy,
poultry,andeggs.Productiondiversitywascalculatedseparatelyforthe 2 seasons.Cropproductionwas
reportedbyeachseason,butlivestockproductionwasnot.Season1includedthe periodfromJuly2012
to December2012 and season2 includedthe periodfromJanuary2013 to June 2013. The assumption
was made that if a householdwasinvolvedinlivestockproduction,it wascontinuousthroughoutthe
year.The meat,dairy,poultry,andeggsscoreswere addedtocrop scoresfor season1 to give the

5. householdproductiondiversityof season1.Likewise,the same animal source scores were added tothe
crop scoresfor season2 to produce a season2 householdproductiondiversityscore.
Demographiccharacteristics
Years of educationwere recodedinto4categories:noformal education(0years),primaryschool-some
or completed(1-5),secondaryschool-some orcompleted(6-9),andhighschool educationorbeyond
(10+). Marital statuswas categorizedinto3groups:marriedand monogamous,marriedand
polygamous,andnotmarried.The notmarriedgroupincludedsingle,cohabitating,separated,divorced,
widowedasa single category. ReligionwascategorizedaseitherMuslim, Christian(Catholic,Orthodox,
Protestant),orother(pagan,traditional religions,orother).
Health characteristics
A binaryvariable wasconstructedforunderweightasanindicatorof nutritional status.Measuresof
weightorBMI are not appropriate foruse inidentifyingundernourishedpregnantwomen,somid-upper
arm circumference (MUAC) wasusedinstead.The average of three MUACmeasurementswasusedin
thisstudy.UnderweightforpregnantwomenwasdefinedashavingaMUAC of lessthan 23 cm. The
antenatal care variable,whichreferstothe numberof antenatal visitsduringpregnancy, wasclassified
as 0, 1, 2, 3, and 4 or more appointmentsattended.Ironsupplementationwascodedasa binary
variable on whetherthe womanreceivedorboughtironsupplementsduringthe currentpregnancy.
Firstpregnancyisa binaryvariable of whetherawomanis pregnantwithherfirstchildorhas had
previouspregnancies.
Regression Model
LogisticregressionwasperformedusingStataCorp2013, StataICRelease 13 software topredictanemia
statusfrom householdproductiondiversityscoresfromeachseason.The model wasrunseparatelyfor
the productiondiversityscorescorrespondingwiththe twogrowingseasons.Onlythe householdsthat
completedboththe cropand livestocksurveyswere includedinthe model (n=4628).Additional
covariateswere addedtothe model,whichincludematernal age,education,numberof previous
pregnancies,antenatalcare attendance,nutritionalstatus,andironsupplementation.The regression
model wasadjustedforclusteringatthe kebelelevel.A secondmodel wasperformedusing
disaggregatedproductiondiversityscoreswhichseparatedcropproductionfromanimal production.The
modelswere testedformisspecificationproblemsandgoodnessof fitusingthe Statalinktestand
Hosmer’sandLemeshowgoodness-of-fit.

6. Results
Demographicand Health Characteristics
The majorityof the womenwere betweenthe agesof
20-29 (57%) and mostof the womenwere ina
monogamousmarriage (96%) (Table 1).The women
were primarilyMuslim(67%) andhadlow educational
attainment(mean:2.3years).The demographicand
healthdatafrom the sample alsosuggeststhathealth
servicesandhealthcare knowledgewaspooramong
the pregnantwomeninthe sample.Thisassumption
isbasedon the findingsthata large proportionof
womenare underweight(41%) anddidnot attend
any antenatal care appointmentsduringpregnancy
(49%).Moreover,a significantproportionof the
womendidnottake antenatal ironsupplementation
tabletsduringpregnancy(83%).
AnemiaStatus
Overall,the prevalence of anemiaamongthe
pregnantwomeninthe sample was12.39%. Among
the womenwithanemia,the majorityof anemic
womenhadmildanemiaat68.91%, whereasa
smallerpercentage havingmoderate orsevere
anemiaat 29.88% and 1.21% respectively.The
prevalence of anemiaincreasedasthe age group
increasedwhereasanemiaprevalence decreased
withincrease ineducation(Table 2). The prevalence
of anemiawashigherin Muslimwomencomparedto
those practicingotherreligions.The prevalence of
anemiawashigherin womenin polygamous
marriage,althoughthe numberof womeninthis
groupwas low inthe sample.Similarly,the
prevalence of anemiawashigherinunderweight
womenandwomenwhohave hadprevious
pregnancies.Surprisingly,the prevalence of anemia
was higherinwomenwhohadironsupplementation.
Perhapsironsupplementswere onlygiventowomen
screenedforlow ironor hemoglobinconcentration
Table 1:Demographic and Health Characteristics
Mean +/-
SE
Percent
Age
26.4 +/-
0.11
Age Group
14-19 9.87
20-29 56.6
30-39 31.84
40-50 1.69
Marital Status
Married-
monogamous
96.2
Married-
polygamous
1.5
Not married1 2.3
Religion
Muslim 67.26
Christian 32.67
Other 0.06
Years of Education
2.28 +/-
0.14
Educational Attainment
0 yrs 55.24
1-5 yrs 27.12
6-9 yrs 13.7
10+ yrs 3.96
Woreda
Woliso 33.33
Goma 33.35
Tiro Afeta 33.31
Underweight3
Yes 40.8
No 59.2
Firstpregnancy
Yes 16.94
No 83.06
Antenatal Appointments
0 49.38
1 21.4
2 17.79
3 8.57
4+ 2.86
Received Iron
Supplements
Yes 17.01
No 82.99
Note: 1 Includesresponsesfor single, cohabitating,
separated, divorced, andwidowed. 2 Religion:Christian
includes Orthodox, Catholic, and Protestant;other
includes traditional andother religions. 3Underweight
classifiedas a MUACscore of <23 cm

7. and therefore,thisresultwouldbe expected.However,little wasknownaboutthe policiesandpractices
inthe studycommunitiesfordistributingironsupplementstopregnantwomen.
Table 2: Anemia status across demographic and health characteristics
(n=)
Hemoglobin (g/dL)
mean +/- SE
Anemia Prevalence (%)
Age Group
14-19 (461) 12.67 +/- .07 9.98
20-29 (2644) 12.49 +/- .05 11.81
30-39 (1489) 12.35 +/- .06 13.65
40-50 (78) 12.08 +/- .27 20.51
Marital Status
Married-monogamous (4495) 12.46 +/- 0.5 12.27
Married-polygamous (69) 12.34 +/- .18 18.84
Not married (108) 12.43 +/- .14 12.04
Religion
Muslim(3146) 12.33 +/- 0.6 15
Christian (1523) 12.73 +/- .05 6.96
Other (3) 12.70 +/- .39 0
Years of Education
0 (2577) 12.34 +/-.06 14.49
1-5 (1270) 12.57 +/-.05 10.33
6-9 (640) 12.63 +/-.06 9.06
10+ (185) 12.75 +/- .10 8.1
Woreda
Woliso (1556) 12.56 +/-.04 10.73
Goma (1561) 12.15 +/-.09 18.24
Tiro Afeta (1555) 12.66 +/-.06 8.11
Underweight(MUAC)
Yes (1905) 12.31 +/-.06 14.98
No (2767) 12.56+/-.05 10.56
Firsttime pregnant
Yes (791) 12.76+/-.06 8.09
No (3881) 12.40 +/-.05 13.24
Antenatal appointments
0 (2305) 12.49+/-.06 12.29
1 (1000) 12.40 +/-.05 12.3
2 (831) 12.40+/-.07 12.53
3 (402) 12.47 +/-.07 13.97
4+ (132) 12.70+/-.13 7.58
Received Iron Supplements
Yes (797) 12.35 +/- .06 13.84

8. No (3875) 12.48 +/- .05 12.06
HouseholdProduction
The percentage of householdsinproduction of cereals,rootsandtubers,legumes, vegetables,and oil
seeds(rapeseed,flax,safflower,etc.) were higherforseason2than season1 (Table 3). Thismeansmore
householdsparticipate inproductionof cereals,roots,legumes,vegetables,and oilseeds inseason2
comparedto season1. On the otherhand,the percentage of householdsin productionforfruitsand
spiceswere higherinseason1than season2, whichmeansthathouseholdsproduce fewerfruitsand
spicesinseason2 whencomparedtoseason1.The productionof cashcrops remained similarforboth
the seasons.Equal livestockproductiondiversityscoresformeat,dairy,poultry,andeggswere assigned
to bothseasonsas livestockproductionisnotdirectlydependentuponseason.
Table 3: Percentage of households in production
n= 4391 Season 1 Season 2
Cash Crops 63.56 63.43
Eggs 33.4 33.4
Poultry 31.51 31.51
Cereals 31.22 56.62
Fruits 26.58 18.65
Vegetables 19.27 24.05
Dairy 14.34 14.34
Roots/Tubers 9.52 31.41
Legume 6.15 15.08
Oil Seeds 3.35 10.73
Spices 1.66 0.27
Meat 0.17 0.17
LogisticRegression
The resultsfromthe firstmodel indicatesthatinthe secondseasonforeveryone pointincrease in
productiondiversitythe oddsof beinganemiadecreasesby7%, all else equal (Table4a).Inbothseasons
beingunderweightincreasesthe oddsof beinganemic.Forseason1 the oddsof beinganemicincreases
by 44% and for season2 the odds increasesby42%.Similarly,the resultsindicatethatwomenwhoare
not intheirfirstpregnancyhave higheroddsof beinganemicthanthe womenintheirfirstpregnancy.
The model predictsthatthe oddsof havinganemiadecreaseswithincreasingyearsof educationwitha
28% decrease in1-5 yearsof educationand32% decrease in6-9 yearsof educationwhencomparedto0
yearsof education,all elseequal.

9. Table 4a: Logistic Regression predicting anemia from production diversity and several covariates
Season 1 Season 2
n=4628 Adjusted
Odds Ratio
95%
Confidence
Interval
Adjusted
Odds Ratio
95%
Confidence
Interval
Production Diversity
Score
1.02 0.95,1.09 0.93* 0.88, 0.98
Iron
Supplementation
No reference
Yes 1.13 0.82,1.55 1.09 0.80, 1.48
Antenatal
Appointments
0 reference
1 1.00 0.79, 1.27 1.01 0.80, 1.28
2 1.00 0.78, 1.27 1.03 0.81, 1.30
3 1.14 0.81, 1.60 1.15 0.82, 1.60
4+ 0.59 0.31, 1.13 0.58 0.30, 1.10
Underweight
No reference
Yes 1.44*** 1.19, 1.75 1.42*** 1.17, 1.73
Firsttime pregnant
Yes reference
No 1.46* 1.01, 2.13 1.52* 1.04, 2.21
Age 1.00 0.98, 1.03 1.01 0.98, 1.03
Years of Education
0 reference
1-5 0.72* 0.56, 0.93 0.74* 0.58, 0.95
6-9 0.68* 0.47,0.99 0.70 0.48, 1.01
10+ 0.63 0.35, 1.12 0.63 0.35, 1.13

10. Significance atthe levelof 0.05*, 0.01**, 0.001***
The individual effectof independentvariablesonthe likelihoodof beinganemiccanbe examined
throughcrude odds ratio(showninTable 4b).Crude oddsratio of the “underweight”variableishigher
whencomparedto the adjustedoddsratio of the same variable. Similarly,the crude ORof the “first
time pregnancy”variable ishigherand statisticallysignificant ata higherlevelwhencomparedtothe
adjustedOR. Likewise,the crude oddsratioof the “years of education”variablesare alsodifferentand
statisticallysignificantata muchhigherlevel.
Table 4b: Crude Odds ratios of variables predictinganemia
n=4628 Crude
Odds Ratio
95%
Confidence
Interval
Season 1 Production
Diversity Score
1.03 0.96,1.09
Season 2 Production
Diversity Score
0.93* 0.88, 0.99
Iron
Supplementation
No reference
Yes 1.16 0.87,1.55
Antenatal
Appointments
0 reference
1 0.99 0.78, 1.27
2 1.01 0.81, 1.27
3 1.15 0.86, 1.53
4+ 0.58 0.30, 1.14
Underweight
No reference
Yes 1.49*** 1.22, 1.81
Firsttime pregnant
Yes reference

11. No 1.73*** 1.32, 2.28
Age 1.02** 1.00, 1.04
Years of Education
0 reference
1-5 0.68*** 0.53, 0.85
6-9 0.59** 0.41,0.84
10+ 0.52* 0.31, 0.88
Significance atthe levelof 0.05*, 0.01**, 0.001***
The secondmodel examinedthe individual effectsof cropproductiondiversityscoresof the two
seasonsandanimal productiondiversityscores (Table5).The secondmodel predictsthatforone unit
increase inSeason1 crop productiondiversityscore the oddsof beinganemicincreasesby11%.Not
surprisingly,one unitincrease inthe animal productiondiversityreducesthe oddsof beinganemicby
14% all else equal.Similartothe firstmodel underweight,firsttime pregnancy,andeducationyearsare
significantpredictorsof anemia.The oddsof beinganemicincreasedby44% if the woman was
underweight,all elseequal.Likewise,the oddsof beinganemicincreasedby46% if the woman was
underweight,all elseequal.Finally,the oddsof beinganemicdecreasesby24% if the education was
between1-5yearscomparedto 0 years of education,all else equal.
Table 5: Logistic Regression predicting anemia using disaggregated scores
n=4628
Adjusted Odds
Ratio
95% Confidence
Interval
Crop Production Score (season 1) 1.11* 1.02, 1.20
Crop Production Score (season 2) 0.97 0.90, 1.05
Animal Production
Score 0.86* 0.76, 0.97
Iron
Supplementation
No reference
Yes 1.08 0.78, 1.47
Antenatal
Appointments
0 reference

12. 1 1.02 0.81, 1.29
2 1.03 0.82, 1.31
3 1.14 0.82, 1.59
4+ 0.59 0.31, 1.12
Underweight
No reference
Yes 1.44*** 1.19, 1.74
Firsttime pregnant
Yes reference
No 1.46* 1.00, 2.14
Age 1.00 0.98, 1.03
Years of Education
0 reference
1-5 0.76* 0.59, 0.97
6-9 0.72 0.49, 1.04
10+ 0.66 0.37, 1.19
Significance atthe levelof 0.05*, 0.01**, 0.001***
Discussion
Model 1
Season1 in the surveyreferstohouseholdproductionduringthe monthsof July2012 to December
2012 and season2 referstoJanuary 2013 to June 2013. In Ethiopia,there are twomaincrop seasons:
Meherand Belg.Season1 mostcloselycorrespondswiththe monthsof the Meher(September-
November) andseason2correspondstothe Belg (March–May). In the studyworedas,September
throughNovemberistime forharvestingandMarch throughMay is time forlandpreparation.However
thisisapplicable forcropsonly.There isno specificharvestingtime forfruitsandvegetables.The Meher
isthe mainseasonwhere 90-95% of the total cereal outputinEthiopiaisproduced [13].While the
Meheris the mostimportantseasonintermsof the quantityof cerealsproduced,smallholderfarmers
are the onlyproducerscultivatingcropsduringthe Belgandsoit has relevance andimportance tothe
studypopulation [14].

13. Resultsfromlogisticregressionshowedthatthe relationshipbetweenproductiondiversityandthe odds
of anemiawere significantforseason2 (i.e.Belg) butnotforseason1 (i.e.Meher).The higher
percentage of populationinvolvedinproductionof cereals,roots/tubers,andlegumesinseason2may
be explainedbya large numberof smallholderfarminghouseholdsproducingcropsinBelgseason,but
witha lowertotal quantityof output.
Duringthe Meher season,farmersmaychoose tospecialize inaparticulartype of crop and produce a
large volume of thiscropto sell inthe market.Householdproductionmayleadtoimprovednutritional
statusthroughmultiple pathways,the primarypathwaysbeingdirect consumptionof foodsproducedby
the householdorbyincreasedincome throughmarketsales,whichallow the householdtopurchase
otherfoods [15]. Productiondiversityatthe householdlevel isone waytoincrease dietarydiversityand
adequate micronutrientintake,includingiron-richfoods.However,householdproductioncannot
replace the abundance of agricultural goodsinthe marketplace.Perhapsduringthe Meherseason,
there isan abundance of diverse foodsavailableatthe marketand itis more beneficial forspecializeina
particularcrop and sell alarge quantityof it to generate income forpurchase of othergoods.Duringthe
smallerharvestseason,perhapsitisbeneficial tothendiversifythe typesof cropsandlivestock
produced. Previousstudiessupportthispatternastheyshow that poorhouseholdsaimtofulfill their
caloricrequirementsfirstthroughproductionandgreaterdietarydiversityisachievedonly through
purchasingpowerfrom greaterincome [16].
Model 2
Whentotal productiondiversityisdisaggregatedintoseparate cropproductiondiversityandanimal
productiondiversityscore,the resultssuggestthatproductionof animal source foodsisthe maindriver
that reducesoddsof womenhavinganemia.The model showedthathouseholdanimal production
significantlyreducedthe oddsof the anemiainthe pregnantwoman,butthe same effectwasnot
observedforthe crop scores(Table 5).Therefore,animal productionmore thancropdiversitydrivesthe
reductioninoddsof anemia.Thismakessense because animalproductsare richersourcesof ironand
containthe most bioavailable form. While householdproductionof animal source foodsisone strategy
to improve ironintake,itmaynotbe sufficientonitsowntomeetthe highironneedsof a pregnant
women.Thus,interventionsshouldalsoincorporate strategiestoimprove use of antenatal care,
coverage of ironsupplementation,andpromote female education,whichwasalsoa predictorof anemia
status.As previouslyshown,utilizationof antenatal care andiron-supplementationcoverage are low
amongthe studypopulation(Table1).
It has beennotedthatinareas where cereals are the predominantsource of energy inthe dietand
where disease burdenishigh,evenstrategiestopromote productionof animal source foodsislikely to
be insufficientforimprovinganemiastatusinpregnantwomen [17].Furthermore,thereisinsufficient
evidence todetermine whetherpromotionof animal source foodsisaneffectivemeanstoalleviate
problemsof undernutritionasthere islittleknownaboutpotential negativeimpactsonfactorslike
maternal time andworkload,maternal income,andthe riskof concomitantly promotingzoonosis [18].
Other determinants ofiron status

14. Prenatal ironsupplementationhelpstoreduce irondeficiencyanemiaamongwomen.However,inour
modelsthe effectsof ironsupplementationwasnon-significantanditincreasedthe oddsof being
anemic,all else equal.The possible explanationforthisobservationmightbe thatsupplementation
mightonlybe giventopregnantwomenwhowere extremelyanemic.Thus,supplementation mayhave
changedtheirstatus fromseverelyormoderatelydeficienttomildlydeficient.Since thisstudyused
anemiastatusas a binary“yes”or “no” variable,it wasnotpossible toexamine thesesubtleties.
Furthermore, inmalariaendemicareaslike Ethiopiaironsupplementationcanincrease the riskof
infection.Introductionof highironquantitiesinthe bodycausesa spike incirculatingironinthe blood,
whichcan be usedby the malarial parasite.Therefore,itisimportant tominimize the amountof free
ironin the bloodsothat it cannotbe utilizedbyparasites.Consumptionof ironinsmallerdosesthrough
foodbasedapproachis perhapsa safermethodtoimprove ironstatusinplaceslike Ethiopia.In
Ethiopia, anemiasupplementationmightbe usedforthe treatmentof severe anemia.
The numberof antenatal visitsalsofailedtoshow anystatistical significance inbothof the models.This
mightbe explainedbythe factthat only2.86 percentof the total womenincludedinthe modelhadthe
recommended4or more antenatal visitsandonly8.6% of the total womenhad3 antenatal visits.About
50% of the total womeninthe sample didn’thave anyantenatal visits.Hence,pooror non-existing
antenatal care mightexplainnon-significantassociationwithanemiastatus.
Both models showed thatunderweightwasstronglycorrelatedwithanemia.Thisisintuitiveas energy
and nutrientdeprivation oftenleadstounderweight. Often,whenapersonisunderweighttheir
consumptionof micronutrientslike ironare verylow. Inthissample,only about15 % of all underweight
womenwere anemic, butthe oddsof beinganemicincreasedsignificantly whenthe motherswere
underweightwhencomparedtonotbeing underweight.If mothershave adequatesourcesof ironin
theirdiettheymaynot be anemicevenif theyare underweight because of caloricdeprivation. This
mightexplainthe findingsinthissamplethat despite beingunderweight, about85% of mothers were
not anemic. The lowprevalenceof anemiaamongunderweightwomencouldbe explainedbycommon
dietarypracticesinEthiopia.Unlike moststaple foods,Ethiopia’smajorgrain,teff,isagood source of
iron.Furtherstudiesusingdietaryintakedatacanexamine these consumption patternsinorderto
betterexplainthe relationshipbetweenunderweightandanemia.
The study showedasignificantassociationof likelihoodof beinganemicandmultigravida(i.e.pregnancy
more than one time).Pregnancyincreasesthe requirementsforironinthe bodyandoftenmultiple
pregnanciesdepletethe ironstoresinthe women’sbody,especiallyif theyare closelyspaced.Hence,
the studynaturallyfindsthatwomenwhoare not intheirfirstpregnancyare more likelytobe anemic.
Study LimitationsandFutureWork
To performthisanalysisthe assumptionwasmade thatproducinghouseholdsconsumedsomeportion
of the foodtheyproduced.Determiningthe relationshiphouseholdproductiondiversityanddiversityof
the dietwouldhave establishedamore directlinkbetweenproductionanddietaryhabitsandthe effect
on nutritional status,butsurveydatawere notsufficienttocalculate dietarydiversityscores.However,

15. ina studyof 4 countriesincludingIndonesia,Kenya,Malawi,andEthiopia,householdproduction
diversitywasassociatedwithanincrease inhouseholddietarydiversity [19].And,dietarydiversityisa
goodindicatorof micronutrientstatusof bothchildrenandwomenina diverse samplingof developing
countries [20,21]. Therefore,itisplausible forhouseholdproductiondiversitytoimpactanemiastatus.
The study didnotcontrol for purchasingpowerof the householdsdue tolimitationsof the income data.
Usually,householdswithsufficienteconomicaccessare able to purchase higherqualityanddiverse
nutritious foodsare purchasedfromthe market.Furthermore,the distance tothe local marketmight
playan importantrole inthe purchasingof highervalue fooditemslikemeatproducts,fruitsand
vegetables.Hence,thisstudyrecommendscontrollingforthese factorsinfuture.
There islimitedevidence onthe role of householdproductiondiversityinhealthof pregnantwomen.
Thisstudycontributestothe bodyof knowledgeof agriculture tonutritionpathways. The resultsfrom
our studyshowthat furtherinvestigationneedstobe carriedout inorderto examine the effectof
agricultural outputsonhealthoutcomeslikeanemia.Thisstudy,alongwithfuture studiesonhousehold
productionhabits canhelpexplainthe pathwaysandmechanismof how agriculture andnutritionare
related.
The resultsof thisstudycan alsobe usedby policymakersforprogrammaticpurposes. Resultsindicate
that a focus on improvingthe production of livestockandtheirproducts islikelytoimprove health
outcomesof the mothers. The studysuggeststhatthe improved productionof itemslike eggs,milk,and
meatmay translate into consumption bythe household andconsequently improve healthof the
mothers. Furthermore, these resultssupportthe needforimprovementsin complementary health
interventionssuchas female educationand accesstobasic healthcare facilities. Communityhealth
outreachprograms that provide counselingandservicestopregnantwomen canbe initiated toimprove
coverage of servicessuchas antenatal care appointmentsanddistributionof ironandfolicacid
supplements. Promotionof healthybirthspacingcanhelpreduce anemiainwomenbyproviding
enoughtime toreplenishironstoresbefore herneeds are increasedagainduringpregnancy. Finally,
investmentsineducationof adolescentgirlsandwomenislikelytoimprove healthandnutritionof
mothers andtheirfamilies.Improvededucation,especiallyamongfemales,hasexternal benefitsto
societysuchas povertyreduction,income,andhigherstandardof living.
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