Assessment of Adolescent Girl
Nutrition, Dietary Practices,and Roles in Zimbabwe
Mangwe and Tsholotsho Districts
June 2015

Authors
Amelia Reese Masterson, MPH
Research Advisor, Nutrition & Food Security, International Medical Corps
Pamela Murakwani
Team Leader; International Medical Corps Zimbabwe
Zothile Mlobane
Independent Consultant

Acknowledgments
This assessment was made possible through internal International Medical Corps funding, and was further facilitated throughthe Amalima program in Zimbabwe. International Medical Corps would like to recognize the invaluable time and input from thefollowing staff at Headquarters:

Caroline Abla; Director; Nutrition, Food Security & Livelihoods; Washington, DC
Jennifer Burns; Nutrition Advisor; Nutrition, Food Security & Livelihoods; Washington, DC
Shiromi Perera; Technical Advisor; Nutrition, Food Security & Livelihoods; Washington, DC
Meghan Greeley; Reproductive Health Officer; Technical Unit; Washington, DC
Janet Meyers; Deputy Director; Health Policy and Practice; Technical Unit; Washington, DC
Kate Brogan; WASH Advisor; Technical Unit; London, UK
Maya Bahoshy; Social & Behavior Change Officer; London, UK

The team of enumerators and data capturers in Zimbabwe for the their insight, hard work, and dedication: Annabel Tshuma,
Bhekimpilo Sithole, Irene Ncube, Noah Ndlovu, Nonhlanhla Ngwabi, Patricia S. Dube, Qhubani Mpala, Sibukile Moyo, and Themba
Maphosa.
The Ministry of Health and Child Care (MoHCC), Zimbabwe, and the Local Government and Rural District Council offices forapproving this assessment and recognizing the importance of increased knowledge on adolescent girl nutrition and health inZimbabwe.
And finally, we acknowledge the technical support received from the Food and Agriculture Organization (FAO) on the use andinterpretation of the Food Insecurity Experience Scale (FIES), as well as valuable input from Bradley Woodruff (Emory University,
Columbia University) and Kristen Cashin (FANTA) on the current state of research and recommendations on the measurement ofadolescent nutritional status.

All photos were taken by Amelia Reese Masterson during data collection for this assessment, 2015.

CONTENTS
LIST OF ACRONYMS................................................................................................................................................3
EXECUTIVE SUMMARY...........................................................................................................................................3

INTRODUCTION............................................................................................................................................6

1.

Background and Justification............................................................................................................................................. 6
Objectives of the Assessment............................................................................................................................................7

METHODS.......................................................................................................................................................82.

Quantitative Methods........................................................................................................................................................... 8A.

Study Design.............................................................................................................................................................. 8

B.

Sample Design.......................................................................................................................................................... 8

C.

Questionnaire............................................................................................................................................................. 9

D.

Quantitative Data Analysis..................................................................................................................................10

Qualitative Methods.............................................................................................................................................................10

3.

A.

Study Design..............................................................................................................................................................11

B.

Qualitative Data Analysis......................................................................................................................................11
RESULTS (QUANTITATIVE AND QUALITATIVE)................................................................................. 11

Demographics........................................................................................................................................................................11
Pregnancy and Reproductive Health..............................................................................................................................14
Nutrition-Related Knowledge, Beliefs, and Practices................................................................................................. 17
Food Security, Dietary Diversity, and Nutritional Status............................................................................................20
Health and Health Access.................................................................................................................................................22
Water, Sanitation, and Hygiene (WASH)........................................................................................................................24
Adolescent Social/Community Engagement...............................................................................................................25
4. DISCUSSION & RECOMMENDATIONS.......................................................................................................... 25
ANNEX 1. Assessment of Food Insecurity Experience Scale Data in an International Medical Corps Surveyof Adolescent Girls in Zimbabwe in 2015...........................................................................................................34

ABBREVIATIONS
AND ACRONYMS
ANC		
BMI		
CNFA		CSB		DHS		
ENSUREFANTA		FAO		FGD		FIES		GWP		HAZ		IFPRI		KII		KPC		MCHIP		MOE		MOHCCORAP		
PLW		
RSA		
SRH		
TB		
UNFPA		UNICEF
VHW		
VoH		
WASH		WDDS		
WEAI		

Antenatal care
Body mass index
Cultivating New Frontiers in Agriculture
Corn soy blend
Demographic and Health Survey
Enhancing Nutrition and Stepping Up Resilience (World Vision)
Food and Nutrition Technical Assistance III Project
Food and Agriculture Organization
Focus Group Discussion
Food Insecurity Experience Scale
Gallup World Poll
Height-for-age Z score
International Food Policy Research Institute
Key Informant Interview
Knowledge, practice, and coverage
Maternal and Child Health Integrated Program
Ministry of Education
Ministry of Health and Child Care
Organization of Rural Associations for Progress
Pregnant and lactating women
Republic of South Africa
Sexual and Reproductive Health
Tuberculosis
United Nations Population Fund
United Nations Children Fund
Village Health Workers
Voices of the Hungry
Water, Sanitation, and Hygiene
Women’s Dietary Diversity Score
Women’s Empowerment in Agriculture Index

1

EXECUTIVE SUMMARY

Only 36% attended school, and many older girls did notcomplete secondary school due to lack of money for school
fees, pregnancy, long distances, household demands, or
migration for work. School attendance is primarily decided byparents, with some adolescent girls reporting that they makethis decision themselves.

Adolescence is a period of heightened nutritional need,which can be compounded by pregnancy. Based on a needfor information on adolescent girl nutrition in Zimbabwe to
inform service provision for this group, the objectives of thisassessment were to: 1) describe nutrition-related beliefs,
knowledge, and practices among adolescent girls; 2) assess
adolescent girl nutrition, food security, and dietary diversity
status; 3) identify potential risk factors related to poor
adolescent nutritional status; and 4) characterize perspectivesof ‘key influencers’ that contribute to determining adolescentgirl roles and responsibilities surrounding nutrition.

Overall, this assessment found that adolescent girls in Mangwe
and Tsholotsho face multifaceted barriers to good health andnutrition, including limited knowledge, low decision making
power, and poor access to resources.
It is recommended to provide integrated behavior change
activities on sexual and reproductive health, WASH, andnutrition through platforms where adolescent girls spend time:school clubs, sports, Care Groups, religious gatherings, andwater collection points. Incentives to keep older adolescent
girls in school while promoting improved diets and delayed
pregnancy/marriage are recommended, potentially including
peer-to-peer models, income-generating activities contingent
on school attendance, take-home food rations, community
conversations among ‘key influencers’, and mobile phonemessaging. Men and boys should be engaged in efforts to
reduce adolescent pregnancies. Finally, programs addressing
food insecurity alongside ongoing nutritional surveillanceamong adolescent girls are critical.

The assessment utilized both quantitative and qualitative
data collection methods. A cross-sectional assessment was
carried out among adolescent girls 13-19 years (n=692) using
multistage cluster sampling, representative of selectedwards in Mangwe and Tsholotsho districts. The questionnaire
included demographics, dietary beliefs and practices, sexualand reproductive health, health access, food security, dietary
diversity, WASH, community involvement, and anthropometrics.
Data were analyzed in SPSS looking at descriptive statistics,
correlations, and difference in means. Qualitative data werecollected by trained facilitators through focus group discussions
and key informant interviews with adolescent boys, mothers
and fathers of adolescent girls, as well as with adolescent girls.
Qualitative data were analyzed for themes and subthemes
through an iterative process.

This assessments begins to address the gap in knowledge
on adolescent girl nutrition in Zimbabwe, but further researchis needed, including: assessment in other provinces or at
the national level, further assessment to confirm adolescentuse of health services across the Zimbabwe, research on the
nutritional value of indigenous/traditional foods and adolescentpreferences, measurement of anemia status, follow up researchon men’s perspectives and roles/behaviors to determine
best approaches to engage men to prevent unplanned/earlypregnancy, and general research to establish age-appropriate
cutoffs for measurement of adolescent girl nutritional status.

Of surveyed adolescent girls, 47% were food insecure and 66%
had poor dietary diversity, yet rates of stunting and thinness
were under 10% and were correlated with pre-menarche. A
variety of socio-behavioral factors were identified that may
contribute to adolescent girl nutrition status. Adolescent girls
were commonly engaged in food preparation (92%), though
had little food-related decision making power. Mothers were
the primary decision-makers surrounding both food purchases
and preparation. Adolescent girls had low levels of knowledge
on nutrition, particularly nutrition during pregnancy. Only 14%
could correctly identify the five critical handwashing moments,
a risk factor for diarrhea and poor nutritional status. Adolescent
girls’ primary source of health/nutrition information was school(34%), followed by clinics (25%) and community health workers/
volunteers (15%). Another 15% reported that they did notreceive or did not know where they received health/nutrition
information.

1. INTRODUCTIONBACKGROUND AND JUSTIFICATIONUSAID-funded Amalima program (2013-2018) is a fiveyear development project being implemented by CNFA,
International Medical Corps, The Manoff Group, Organization of
Rural Associations for Progress (ORAP), Africare, and Dabane
Trust in two provinces, Matabeleland North and MatabelelandSouth in Zimbabwe. The program is being implemented
across four districts (Tsholotsho in Matabeleland North andBulilima, Mangwe and Gwanda in Matabeleland South) in theseprovinces, with a goal to improve household food and nutrition
security. The four districts are in agro-ecological regions 4 and5, which are prone to low rainfall patterns and consequently
are largely food insecure. Amalima aims to improve household
food and nutrition security through three Strategic Objectives:
1) household access to and availability of food improved, 2)community resilience to shocks improved, and 3) nutritionand health among pregnant and lactating women and boys
and girls under 2 improved. International Medical Corps is thetechnical lead for the third objective, of which the key activities

Pregnancy was common (27%), and 89% of pregnancies wereoutside marriage. Aunts were said to be a major source of
information on pregnancy and contraceptive use. Most of thesample had never been married (97%), and most reported
that they could make their own decision about whether to be
married. The average age at first marriage was 16.6 (SD 1.2).
Reported health-seeking was high, with 97% of adolescent
girls saying they seek assistance when they are sick or have ahealth-related concern. While 43% of adolescent girls said theyseek healthcare for themselves, others pointed to their motheror grandmother as the primary decision-maker on their own
health-seeking.
2

are providing food rations to PLW and children 6-23 months,
and implementing care group activities, community healthclubs, and water and sanitation rehabilitation of health centers.

mothers-in-law, and other adults and peers in an adolescent
girl’s life have an influence on her beliefs, practices, behaviors,and nutrition knowledge. Some of these influencers may be thegatekeepers, providing or denying adolescent girls permission
to engage in certain activities or make certain decisions
pertaining to their health and nutritional wellbeing. It is importantto understand the perspectives and influence of these key
key players in adolescent girls’ lives to understand what may
be driving their behaviors, and therefore, what strategies will
work to improve nutrition and dietary beliefs/practices among
adolescent girls. Adolescent boys – who are schoolmates,
brothers, and boyfriends now, and who will grow up to
become fathers, grandfathers or leaders in the communities
where adolescent girls live – are another important group to
understand. Their perspective, current influence on adolescent
girls, and drivers of their behaviors will help guide strategies toimprove adolescent girl health and nutrition.

This group – PLW and children 6-23 months – represents the‘1000-day window’ of heightened nutritional need from theperiod of conception to a child’s second birthday. However,the pre-‘1000’ day window period is crucial to ensure optimal
nutrition, especially for adolescent girls who have heightened
nutrition needs during this time due to puberty and development.
According to the 2013 Lancet series on maternal and childnutrition, undernutrition during pregnancy, affecting fetal
growth, is a major determinant of stunting and developmentof non-communicable diseases in adulthood.1 In fact, 20% ofchild stunting is attributable to intra-uterine growth restriction(estimated by low birth weight) due to maternal malnutrition.2
This evidence supports the focus on the crucial 1000 day
window period, as well as the importance of intervening earlyin pregnancy, and even before conception. The Lancet series
highlights the need for expansion of interventions aimed ataddressing adolescent girls’ health and nutrition.

While adolescent girls have not been a specific target groupthrough the Amalima program until this point, International
Medical Corps recognizes the need for tailored services foradolescent girls through a life cycle approach that would
ensure good nutritional practices and status throughout theadolescent period and better prepare them going into thecritical 1000 day window period.

Based on experiences through the Amalima program,International Medical Corps has noted significant numbers ofpregnant teenage girls; however, there are currently no Amalima
activities specifically designed to address the nutritional needsof adolescent girls (beyond the wider program activities, whichadolescent girls may participate in). There are high numbersof young mothers/ teenage pregnancies (with program staff
noting anecdotally girls as young as 14), indicating early sexual
debut, possibility of school drop-out, and increased risk ofmaternal
morbidity
and mortality.
International
MedicalCorps, Burundi

OBJECTIVES OF THE ASSESSMENT
This assessment was conceived to address the knowledge
gaps in adolescent nutrition noted above, and gather a body of
information useful for programming nutrition and related services
for adolescent girls in Zimbabwe. Overall, the assessment aims
to identify, describe and understand adolescent girl dietary
practices and nutritional status and needs in Amalima districts(Mangwe and Tsholotsho) in Zimbabwe, as well as identify
opportunities to reach them with key services.

The Ministry of Health and Child Care (MOHCC) of Zimbabwe
has noted that there is a gap in knowledge, and lack of sufficient
information to guide programming priorities for adolescentnutrition in Zimbabwe. According to the 2012 national census
in Zimbabwe, 41% of the population is below 15 years ofage3. Subsequently, adolescent nutrition is of key priority
for MOHCC, and an absence of tailored nutrition services tomeet the needs of adolescent girls has been highlighted in
Zimbabwe’s National Nutrition Strategy.4 No actors or partners
in Zimbabwe have a strong focus on addressing adolescentnutrition (though the Amalima program and other programs
may be doing so minimally by including adolescents in existing
programs). Furthermore, no information is available to guidestrategies to improve adolescent nutrition in Zimbabwe. Thisgap is reflective of a broader gap in adolescent nutrition
knowledge and programmatic evidence worldwide.

Specifically, this study aims to:
1. Describe nutrition-related beliefs, knowledge, and practices
among adolescent girls (including perspectives from adolescent
girls, adolescent boys, and parents)
2. Assess adolescent girl nutritional, food security, and dietary
diversity status
3. Identify potential risk factors associated with adolescentnutrition-related outcomes (stunting, wasting, dietary diversity,
food security), examining: marital status, education, having
children, employment status, WASH-related factors, sexual/
reproductive health practices, dietary beliefs, dietary practices,
decision-making ability, health seeking behavior
4. Identify perspectives of key influencers (adolescentboys, mothers, fathers and others) on adolescent girl roles,
responsibilities, decision-making/empowerment surrounding
school, health access, marriage, pregnancy, and childcare

In addition to adolescent girls themselves, fathers, mothers,
1. Maternal and Child Nutrition, Executive Summary of The Lancet Maternaland Child Nutrition Series, 2013. (Available at: http://www.thelancet.com/series/
maternal-and-child-nutrition)
2. Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, de Onis M, et al.; theMaternal and Child Nutrition Study Group. Maternal and child undernutrition andoverweight in low-income and middle-income countries. Lancet 2013;371:243–60.
3. ZimStat, Census Results 2012, Zimbabwe National Report. http://www.zimstat.co.zw/dmdocuments/Census/CensusResults2012/National_Report.pdf
4. Zimbabwe National Nutrition Strategy (2014-2018) (Available at: file:///C:/
Users/areese/Downloads/Zimbabwe%20National%20Nutrition%20Strategy.
pdf)

2. METHODSQUANTITATIVE METHODS
A. Study Design
To meet study objectives, we utilized a cross-sectional,3

representative assessment of adolescent girls, ages 13-19 years(inclusive). The study was designed to describe the adolescentgirl population in Mangwe and Tsholotsho districts (Amalimaprogram areas) in terms of nutritional status, diets (including
beliefs and practices), nutrition-related decision-making in thehousehold, and factors affecting nutritional status, and provide
a basis for nutrition program design and services for adolescent
girls. Informed consent was sought among all adolescent girlparticipants.

At stage two, we used purposive sampling to select nine wards
in Mangwe and Tsholotsho on the basis of providing geographic
variation and avoiding security threats associated with ongoing
elections (specifically in Tsholotsho district). At stage three, we
randomly selected villages (clusters) proportional to population
size (pps) within each ward. And at stage four, we used chain
sampling to select adolescent girls, 13-19 years, for study
recruitment. Chain sampling was deemed the most appropriate
method for selection of adolescent girls given the low numbersof adolescent girls per village, lack of household or adolescentgirl listing (i.e. no study frame), distance between households(often kilometers apart due to the rural setting), and limited
time and resources. Informed consent was administered at the
beginning of each interview, emphasizing that participation
was optional and all responses would remain anonymous andconfidential.

B. Sample Design
Table 1. Sample structure for quantitative assessment
District(purposively
selected)

Ward(purposively
selected)

1
4

Mangwe

5
14

15
16
10

Tsholotsho

1215

Village/cluster(selected using pps)

Adolescent girls(selected ‘chain
referral’)Mkhaya24

Mhlotshana

31

Makuzeze

31

Guqukani

34

Patse

27

Bulu

33

Zibanani

34

Bhatanani

32

Matsota

26

Nkedile41

Simelamela

17

Lumawe26

Ross Common

32

Zibalongwe

26

Sontulani

30

Thabani30

Zamani30

Khangela

34

Sizwile28

Dinyane W

26

Kulumausenza

32

Sigogo35

Siyaphambili

33

Sample size for this assessment was calculated based onadequate power to detect prevalence of underweight inadolescent girls, and assuming adolescent girls 13-19 years
made up on average 10% of the populations. Calculations
used 5% precision, a 95% confidence level, a design effect of
1.5 (based on relative homogeneity of the population) and a
90% response rate to reach a target sample size of 718 (and aminimum of 24 clusters, with 30 adolescent girls per cluster).
Table 1 demonstrates the actual sampling structure that wasachieved, based on the sample target.
C. Questionnaire
The questionnaire was developed and pilot tested to assess
adolescent girl demographics, dietary beliefs and practices,
sexual and reproductive health, health access, food insecurity,
dietary diversity, WASH, roles and community involvement,
and anthropometric measurements. Dietary beliefs andpractices were measured using a set of questions developed
by International Medical Corps headquarters and field staff,
with input from a team of nutritionists (including MOHCC staff)
from Zimbabwe, and covered knowledge about the major foodgroups, diets during pregnancy, and adolescent girls’ roles infood purchasing, preparation, and dietary practices in the home.
We used a standard pregnancy and birth history questionnaire
adapted from the MCHIP Knowledge Practices and Coverage
Survey (KPC),5 standard questions on antenatal care (ANC), andstandard contraceptive use questions adapted from the UNFPA
Adolescent Sexual and Reproductive Health Toolkit.6 Self-rated
health was assessed, as well as health-seeking behaviors andaccess. Food security experience was assessed using the FAO
Food Insecurity Experience Scale (FIES)7, which had previously
been translated to isiNdeble and used in Zimbabwe. The FAO
9-Item Women’s Dietary Diversity Score (WDDS)8 was used to

TOTAL 692

The sample for the cross-sectional assessment was selectedusing a multistage cluster sampling approach to select astatistically representative sample within selected wards, whileaccounting for limitations (such as limited time/resource, security
concerns, and lack of household listing or listing of adolescent
girls). At stage one, purposive sampling was used to select two
districts where Amalima is operational and security permits datacollection. We selected one district from each province where
Amalima is operational, Mangwe from Matabeleland South and
Tsholotsho from Matabeleland North, with the aim of gathering
information from each province. Resources did not permit us to
conduct the assessment in more than two districts.

5. USAID, Maternal and Child Health Integrated Program (MCHIP), The
Knowledge, Practices and Coverage Survey (KPC) Resources (Available at:
http://www.mchipngo.net/controllers/link.cfc?method=tools_mande)
6. UNFPA, Save the Children, Adolescent Sexual and Reproductive HealthToolkit for Humanitarian Settings (Available at: http://www.unfpa.org/sites/
default/files/pub-pdf/UNFPA_ASRHtoolkit_english.pdf)
7. Ballard TJ, Kepple AW & Cafiero C (2013). The food insecurity experience
scale: developing a global standard for monitoring hunger worldwide.
Technical Paper. Rome, FAO. (Available at http://www.fao.org/economic/ess/
ess-fs/voices/en/)
8. FAO (2010), Guideline for measuring household and individual dietary
diversity. (Available at: http://www.fao.org/3/a-i1983e.pdf)
4

A. Study Design
A total of eight focus groups (FGD) and three key informant
interviews (KII) (Table 2) were conducted in Mangwe andTsholotsho districts during the month of June 2015, with anaverage of 10 participants per group. All focus groups were
led using detailed facilitator guides developed by the researchteam, and verbal informed consent was sought at the beginningof each FGD or KII. All the facilitators were trained on conducting
focus groups and standard moderation techniques were usedthroughout. Participants were recruited by community leaders,
who were sensitized to the study previously. The Ministry of
Health and Child Care (MOHCC) Provincial Medical Directorates
approved the study and objectives, and the letters of approval
were provided to both MOHCC districts.

assess dietary diversity among adolescent girls. To ourknowledge, there is no dietary diversity score questionnairedeveloped specifically for adolescent girls. We used standard
WASH questions pertaining to adolescents, including
questions on water access, handwashing, and hygiene
during menstruation. Finally, we used an adapted version of
the Women’s Empowerment in Agriculture Index (WEAI)9 to
examine decision-making power in the household. According
to anthropometric measurement recommendations, weightand height were taken twice for each girl who was physicallyable and the average was used for analysis. We used a mix ofSeca and UNICEF height boards (calibrated at the beginningand middle of the study) and Seca scales (calibrated regularly).
D. Quantitative Data Analysis
Data were analyzed for descriptive statistics, correlations(using Pearson’s X2 and Fisher’s Exact Test), and difference inmeans (T-Test). Dietary diversity score was established using
the nine food groups recommended by the FAO for assessing
women’s dietary diversity score. Nutritional status was assessedusing BMI-for-age (thinness) and height-for-age (stunting),
compared to the WHO reference population. Among pregnant
adolescents, nutritional status was not assessed as there areno established mid-upper arm circumference (MUAC) cut-offs
for adolescents. Food security results were sent to staff at the
FAO who performed Rasch Modeling to determine appropriate
cutoffs for the scale in Zimbabwe (see Annex 1).

B. Qualitative Data Analysis
All FGDs and KII were audiotaped by the facilitators, and thentranscribed verbatim, translated, and reviewed by the Study
Coordinator, a nutritionist, and the Research Advisor to identify
major themes. The nutritionist and the Study Coordinator
then went through each transcript and manually coded thepresence of each major theme as well as identifying thequotations exemplifying these themes. The nutritionist andthe Study Coordinator discussed any differences in opinion
on the meaning of any specific passages in the transcripts.
The Research Advisor reviewed these themes and raised any
issues needing clarification. The themes that recurred in eachof the focus groups conducted are presented throughout theresults section, alongside quantitative results.

There are several potential biases related to this assessment
approach. This assessment is intended to assess only
Amalima project areas, Mangwe and Tsholotsho, meaning
the results cannot be extrapolated to adolescents outside ofthese districts. Additionally, we had to exclude areas where
there were elections taking place, and cannot rule-out somedifferences between those in more secure versus insecureareas (though we did conduct the assessment very close toelection areas). Finally, we aimed to address any potentialsocial desirability bias (systematic over-reporting of positive
behaviors or under-reporting of negative behaviors) by hiring
data collectors outside the Amalima program and training themin objective data collection approaches.

3. RESULTS
Table 2. Focus Groups (8) and Key Informant Interviews (3)QUALITATIVE METHODSGroup

MangweTsholotsho

Adolescent girls

1 KII

1 FGD

Adolescent boys

1 FGD, 2 KII

1 FGD

Fathers

1 FGD

1 FGD

Mothers / Mothers-in-law

1 FGD

2 FGDs

DEMOGRAPHICS

Qualitative data collection explored the following topics:
basic demographics and health status, adolescent marriage,adolescent pregnancy, adolescent girl roles in the communityand household, decision-making surrounding food and‘nutritional gatekeepers’ for adolescent girls, time use, risky
behaviors, and access to health services. Fathers, mothers,
mothers-in-law, adolescent boys, and adolescent girls10 were
included in qualitative data collection in order to gain a range of
in-depth perspectives from those who play a role in adolescent
girls’ health and nutrition decisions, beliefs, and practices. We
sought to identify key nutrition ‘gatekeepers’, that is, those
providing adolescent girls with permission to engage in certain
activities or make certain decisions pertaining to their healthand nutritional wellbeing.

For the survey assessment, 692 adolescent girls age 13-19 years(average age 15.94, SD 1.9) were interviewed in Tsholotsho
and Mangwe districts, with a response rate of 98.5% (10 total
refusals).
Education:
Based on the quantitative assessment, 36% of adolescent
girls reported currently attending school, a number which
is supported by the estimate given by parents during
FGDs that less than half of school-aged girls are currently
attending school. According to survey results, when asked
about the highest education level they had attained, 49%
reported attending some secondary school, while only 14%
had completed secondary school. Parents were the primarydecision-makers on adolescent girl school attendance. Focus
group results identified a few reasons for girls dropping out
Photo: International Medical Corps, Zimbabweof school. Adolescent girl FGD participants agreed that they

9. IFPRI, WEAI Resource Center: http://www.ifpri.org/topic/weai-resourcecenter.
10. Note: husbands of adolescent girls were not included in qualitative datacollection as there were too few to easily form a FGD in a given village.
5

endure long distances to schools, and that only 30 to 40%
complete secondary level, largely due to pregnancies and/orlack of money to pay school fees. Some adolescent girls who
also happen to be household heads, dropped out of schoolas they failed to find a balance between school and homedemands. There were more older girls out of school than
younger girls, as the majority do not complete Form 4 (the final
level in secondary school) or continue into high school.

Most father and mother FGD participants were of the viewthat bread winners, household heads, and guardians makethe decision for adolescents to attend school or not. Most
adolescent girl and boy participants, however, expressed thatthey can also choose to stop going to school without being
influenced by peers or parents.
Marriage and decision-making surrounding marriage:
The majority of adolescent girls (97%) had never been married,
and among those who had been married (n=22), the averageage of marriage was 16.6 years. Twelve of these reported that
their husbands were living with them at the time of this study,
and eight said their husbands were working in the city or aneighboring country (the other two were missing). Adolescent
girls reported that the common age of marriage in theircommunity was 19 years (on average), yet they perceived age
23 as a ‘good age to get married.’ When asked who made thedecision for them to get married, 60% of ever-married girls said
they decided for themselves, followed by parents (20%), mother(10%), and other (10%). When asked about the primary reason
they got married, 55% cited love, 15% said pregnancy, 10% said
‘escape from poverty, and 10% said ‘decision was made for me’
among other reasons. Notably, 5% reported getting married toescape from abuse.

Additionally, during an FGD, parents estimated that about halfof adolescent boys are currently attending school. According toparents, boys become “unmanageable” at this age, which may
contribute to them leaving school. Other reasons include lack ofinterest in school or lack of money for school fees. The fathers
and older women were in agreement to say that the majorityof boys drop out of school between the ages of 14 – 15 years.
Adolescent boys seemed to have more say in whether theyattended school than adolescent girls. Finally, for adolescentboys, there are additional pressures from other older boys who
have dropped out of the school to go drink alcohol or smoke
cigarettes instead of attending school.
Table 3: Demographic characteristics of adolescent girls1
Mangwe & Tsholotsho
N(%) or Mean(SD)Age

15.94 (1.9)

Percent in school

250 (36.2)

Education Level Attained≤ Primary school (grade 1-7)
Some secondary (form 1-4)
Completed secondary (form 4)Some high school (form 5-6)
≥ High school (form 6+)

243 (35.2)
341 (49.4)
99 (14.3)
3 (0.4)4 (0.6)Percent employed56 (8.1)

Occupation
Domestic worker (not in own home)
Agriculture, gardening
Vendor, shopkeeper
Baby sitter
Cook for pre-school
Hairdresser
Other

21 (51.2)
6 (14.6)
6 (14.6)
3 (7.3)2 (4.9)2 (4.9)1 (2.4)

Marital status
Never married
MarriedWidowed660 (96.8)
21 (3.1)
1 (0.1)

Age at first marriage3

16.60 (1.2)

Based on FGDs and interviews, most groups were of the viewthat very few adolescent girls are married, and that the majority
have children outside of marriage. It is stated that it is a common
phenomenon in the village that girls get pregnant from 15 yearsof age.
“Some girls rush into marriage as a way of escaping frompoverty in their homes, and others would be fleeing fromemotional and physical abuse from guardians.”– Adolescent boy from Tsholotsho

2

Perceived common marriage age

19 (2.6)

Perceived ‘good age to get married’

23 (3.8)

Household size

5.92 (2.4)“Most of the girls in this area have kids but are not married.
Some elope with boys to RSA [Republic of South Africa];
cohabit without the knowledge or consent of parents.”– Father from Tsholotsho
The majority of adolescent girls said they decide whom they
desire to get married to. Parents play a vital role in facilitating
the marriage. According to the fathers and older mothers theboy/men’s family initiates the process of asking for the girl’shand in marriage and the two families approve of the union.
The boys were of the view that the boy and the girl concerned
decide whether they would like to get married. Mothers wereunanimous in saying that while the adolescent girl is empowered
to make the decision about whom she marries, there are very
few of them who are married.

1. Numbers may not sum to total due to missing. Valid percents are usedthroughout.
2. Among those who were employed (n=56)
3. Among those ever-married (n=22)“What is surprising is that these girls have the power tochoose whom they wish to be married to, but most of them
are not married still, probably if the parents were responsible
for arranging their marriages, they would all be married.”– Mother From Mangwe“Adolescent boys decide for themselves, they leave homein the morning and the next thing they are spending the day
at the shops. There is nothing you can do once they start
absconding from school, eventually they stop attending
school”- Mother from Tsholotsho

Employment and livelihoods:
Only 8% of the sample was employed, and the most common
type of the employment was domestic work (Table 3). Qualitative
6

data further confirms that the majority of adolescent girls (andboys) were not involved in any livelihood activities. A few wereinvolved in brick molding, and fetching firewood for resale.
Lack of livelihood activities has been cited as a push factor foradolescents relocating to cities and neighboring countries.

“Some parents envy what their neighbor’s children living in
RSA do for them, and in turn influence their children to leave
the country and seek employment”– Father from Tsholotsho“We are consistently chased away from school for the nonpayment of school fees and eventually we stay at home withnothing to look forward to, we have no option but to cross theborder”– Adolescent girl from Mangwe“We don’t have any livelihood activities in this area, no jobs.
What I just think of is to get my axe and get into the bush but
l don’t fetch much from selling firewood and logs for fencing
and roofing”—Adolescent Boy from Mangwe

PREGNANCY AND REPRODUCTIVE HEALTH

Among those adolescents girls who were employed, theassessment found that 31% said they made the decision about
employment themselves, while the others said that any family
member (mother, father, grandparent, or aunt) made thisdecision for them. According to FGDs, most adolescents maketheir own decision to be involved in any livelihood activity. It
was not common for the school-going adolescents to seekjobs or be involved in livelihood activities, but it was common
among adolescents with children. Additionally a large numberof adolescents migrate to neighboring countries where they
were involved in menial jobs such as housekeeping, seasonalcasual labor, and construction sector work.

Just over 27% of the sample had been pregnant; and of these,most (89%) were not married. Antenatal care use (at least 1 visit)
was high among the ever-pregnant (96%). All adolescent girls
were asked who they would turn to for advice if they became(or were) pregnant; 34% (293) said they would turn to an aunt,
followed by health care provider (144, 21%), grandmother (113,16%), and mother (93, 13%).
Among those who had delivered a baby, we asked twoquestions to triangulate responses and ascertain an estimateof low birth weight prevalence. Twenty-four percent reported
that their last baby was “very small” or “smaller than average”
at birth. Further, when asked about birth weight in grams, 13%
reported <2500g (which is classified as low birth weight). If
reported birthweights equal to 2500g were included, thisfigure would rise to 25%.

Migration:
Migration was common among adolescent girls, particularly
older adolescent girls. There were a few motivations identified
for this migration, all related to poverty and the potential
for income generation. Some wards along the border with
Botswana were said to have very few adolescent girls present(notably, in Simelamela, Lumawe and Paste), because girls
were moving to Botswana for employment. The girls are said
to use undesignated entry points into Botswana and also havean advantage of speaking the local languages of Botswana(Tswana and Kalanga).

Table 4: Pregnancy & Birth History
N(%) orMean(SD)

Based on FGDs and interviews, it was revealed that either
relatives, parents/guardians, or adolescents themselves may
make the decision to migrate. Some mentioned that relatives
employed in South Africa inspire adolescents to migrate, andfacilitate the illegal movement of adolescent girls and boys totheir country of employment by providing monetary support.
These adolescents are relocated across the border, some withand some without the consent of parents or guardian. Acrossboth districts, many respondents said that adolescents may
migrate of their own will – including both school-going andnon-school-going girls. For these adolescents, poverty is themain driver, pushing them and their peers out of their villages
to neighboring countries or big cities. They partly blamed theirparents for failing to pay their school fees; as a result they areforced to leave school. This is said to be demotivating andultimately one voluntarily leaves the village to seek casual
employment.
Parents in FGDs reported that they wouldn’t encourage
their children to leave school and seek employment. Someadolescents do migrate to neighboring countries to join theirparents there; however, there are few respondents across
FGDs who felt that parents influence adolescents to migrate toother places for employment purposes.

Ever been pregnant

187 (27.1)

Percent of ever-pregnant who were notmarried167 (89.3)

Currently pregnant

29 (4.2)

ANC use (at least 1 visit) among ever-pregnant

176 (95.7)

ANC services included:
Iron/folic acid supplementationCounseling on mosquito net usage
Deworming treatment
Intermittent, preventive treatment formalariaCounseling on nutrition during pregnancy
Counseling on breastfeeding

108 (60.0)
157 (86.7)

Felt comfortable with the ANC services

178 (98.3)

Reported “very small”/”smaller than average”
birth size

38 (23.8)

Reported LBW (birthweights <2500g)

21 (13.4)

171 (95.0)
66 (36.5)
16 (8.8)
74 (40.9)

Among those who had ever been married or ever been pregnant,120 (60.6%) reported using a condom at last sexual encounter,
while 36.9% did not, and 2.5% refused to answer. Based on
qualitative findings, adolescent girls were more knowledgeable
about “protection” (condom use) than about contraception forthe purpose of limiting or spacing births. Among those thatuse contraception, 87% reported that they normally make the7decision about whether or not to use family planning to space orlimit birth, followed by their mother or grandmother as primarydecision-maker. Only 8% of adolescent girls reported that they
could not make the decision regarding use of family planningeven if they wanted to. Health facilities were the primary sourceof contraception obtained by adolescents, followed by shops/
stores (where many adolescents were said to spend their freetime). During FGDs with mothers, some reported that they
helped ensure their daughters had access to family planning.

men/boys working in neighboring countries as most of thesemen/boys are usually perceived to have a better income andsocial status.
According to parents FGDs the early pregnancies are mostly
blamed on men, namely three groups of men – namely injiva(a local term for men working in neighboring countries), cattle
headers and local non-school going adolescent boys. Men
working in the neighboring countries visit home during themain holidays and are said to lure young girls with gifts andmoney and as a result some school-going girls fall pregnant.
Some mothers reported that in some instances the men
working outside of Zimbabwe elope to neighboring countries
with adolescent girls without the knowledge of their parents or
guardians.

Table 5. Sexual and Reproductive Health Indicators
N(%) orMean(SD)
Have not yet reached menarche

147 (21.2)

Avg. age at menarche (n=540)

14.27 (1.15)

Ever heard of contraception (including protection)

534 (77.4)

Currently using method to delay/avoid pregnancy

203 (29.5)

Contraceptive methods used
Female sterilization
IUD
Injectables
Implants
Pill
CondomOther (combinations of the above, abstinence)

1 (0.5)1 (0.5)52 (25.6)
20 (9.9)32 (15.8)
85 (41.9)
12 (5.9)

Where obtained contraception
Health facility
Store
Family/friend
Boyfriend
Other (CHW, pharmacy, boyfriend, school,
natural)

159 (78.3)
27 (13.3)
5 (2.5)4 (2.0)8 (3.9)Used a condom at last sexual encounter1

120 (60.6)

Mangwe and Tsholotsho districts attract adolescent boys
from other districts, such as Binga, Nkayi and Lupane, whoare employed as cattle herders while in transit to neighboring
countries or simply for long term seasonal-casual labor.
During FGDs, fathers tended to blame this group of people forimpregnating adolescent girls and failing to marry them.
“The highly mobile cattle headers are also to blame for thehigh numbers of girls with kids yet unmarried. This group ofmen waits for school girls after school and walk them to theirvillages, they are to blame for all these kids without fathers in
our village. One boy can be responsible for impregnating fourgirls” – Father from Tsholotsho
The cattle herders are said to be mobile, and once they
impregnate a girl they either relocate to another area or move toSouth Africa depending on how much money they would havesaved. Either way, they are said not to take any responsibility
for the child. Lastly the non-school-going local boys weresaid to be partly to blame for adolescent pregnancies. Someadolescent boys interviewed mentioned that they cannot marrybecause they are unemployed and as such cannot afford tolook after the adolescent girl. The very few married adolescent
girls were married to older men.
Early pregnancy and decision-making:
Our survey results do not show high rates of early marriage,
but rather early pregnancy. FGD participants reported thatmost adolescent pregnancies are unplanned, hence theytend to be concealed till very late (month of pregnancy not
specified); however, most girls sought advice either from thehealth care center, health workers, aunt, sister-in-law, mother,or grandmother after they got pregnant. It was stated by anumber of female FGD participants (adolescent girls and young
mothers) that at times girls are pushed into marriage due tofactors such as poverty and emotional abuse from guardians(i.e. next of kin who care for adolescent girls if parents areaway).

1. Denominator is 197 (some refused to answer, and if girl was unmarried/
never been pregnant we did not ask this question)“For family planning services the majority of the mothers takethem to the clinic so as to avoid unplanned and unwanted
babies.”– Mother from Mangwe
FGDs further confirmed much of the survey assessment
findings, with respondents reporting that it was more common
for adolescent girls to become pregnant outside of marriage.
In fact, according to the older women and men, more thanhalf of adolescent girls are pregnant or have children. Older
women observed most girls start to have children at the age of
15 years to 16 years while the community felt that the good age
for a woman to start having children is between 20 to 25 years.
Most parents felt that moral decadence and technology are themajor causes for these early pregnancies. The social platforms
like WhatsApp and Facebook have made it easy for girls tocommunicate in real time and thus get engaged in unguided
relationships. Some girls are lured into sexual relationships with“We don’t plan for pregnancy, it’s something that just happens
unexpectedly, a girl will just tell you that they skipped theirmonthly periods and that’s it and l can’t do much about it as lam also still being looked after by my parents.”– Adolescent boy from Tsholotsho

8

NUTRITION-RELATED KNOWLEDGE, BELIEFS, AND
PRACTICES

the recommended diet citing poverty and limited income topurchase food as reasons why they cannot consume nutritious
food. It also appears that locally available nutritious foods –such as millet, Mopani worms, and wild fruits – are looked down
upon and only consumed among those of low socio-economic
status.

Less than 1% of girls were the primary food purchaser forthe household, and only 28% reported that they can decide
what they personally consume. Most commonly, the head ofhousehold (mother, aunt, uncle, grandparent, or father) makes
food purchases for the family or sends food from outside thecountry. Only 5% of adolescent girls reported that they decide
what food is purchased for the household, and 14% decide what
is prepared for daily meals. Mothers were the primary decisionmakers on what is prepared for daily meals (40%), followed by
grandmother/grandfather, adolescent girls, and then aunts/
uncles. Almost half of girls reported that they could not makethe decision about what to prepare for daily meals even if theywanted to. Mothers and grandparents were also the primarydecision makers regarding minor household expenditures,such as food for daily consumption or household needs (36%
and 23%, respectively). Fathers play very little role in deciding
what food is prepared at mealtime, or what food is purchasedfor daily consumption; this is likely because fathers were often
absent.

Table 6: Nutrition Knowledge, Beliefs and Practices
N(%) orMean(SD)
Primary source of health/nutrition information
SchoolClinicCHW/CHV
Care GroupOther
Did not receive/DK

237 (34.3)
173 (25.1)
102 (14.8)
39 (5.7)
36 (5.2)
103 (14.9)

Knowledge of food groups
None
Poor
Fair
Good

91 (13.2)
257 (37.1)
195 (28.2)
149 (21.5)

Knowledge of diet during pregnancy (correct response)
Knowledge of “4-star diet”1 during pregnancy₁

Qualitative findings confirmed the above, and revealed further
that decisions at homesteads are centralized and girls havelittle autonomy on deciding on their diet. Decisions on dietwere also informed by the availability of resources to buy food.
In cases where food insecurity was critical, choices on dietwere limited to what was available to the family. Most families
relied on remittances from South Africa and Botswana this also
had a bearing on their diet. The family member who purchases
the food for the family makes the decision on what to buy forthe family (mothers, in many cases). The adolescents eat whatis available, and the same applies to married adolescents wholive with in-laws.

Poor (0-1)
Medium (2-3)
Good (4)“We don’t have money so at the end of the day money forfood becomes a determinant. Also food availability is adeterminant, for example around this season there are very
limited choices but soon after harvest we normally have plentyof choices”– Adolescent Boy from Mangwe

520 (75.1)
239 (34.7)
378 (54.6)
72 (10.4)

Who is prioritized at mealtime (top 4)
All eat at same time
Grandparents
ChildrenMother371 (53.6)
100 (14.5)
94 (13.6)
37 (5.4)

Adolescent girl is primary meal preparer in household

327 (47.3)

Adolescent girl often/always prepares householdmeals

632 (91.7)

1. The “4-star diet” is promoted in Zimbabwe among pregnant women. It
consists of: grains & staples, legumes, vegetables and fruit, and animal
source foods.

“Millet porridge mixed with pounded Mopani worms does
not look appetizing at all, l doubt it tastes good and besides
grinded millet tastes bad such that even dogs can’t eat it,what‘s more a human being.”– Adolescent mother from Mangwe

When asked whether certain family members are prioritized
during mealtime, 53% of girls reported that no one in the family
is prioritized, 14% said grandparents, and 13% said children,
while other responses varied. Generally, it seems male family
members are not prioritized in terms of receiving food before
other family members.

Adolescent girls receive most of their information on health or
nutrition from their schools, local health clinics, or community
health workers/outreach workers (Figure 1). Fifteen percent
of adolescent girls, however, said that they did not receive
any health or nutrition information, highlighting the need forincreased health/nutrition education targetting this age group.
Of the 15% who did not receive any health/nutrition information,
the majority (85%) were not attending school and 80% were notparticipating in any group or community activity on a regularbasis. This indicates the need to target this group throughspecific activities designed to reach them where they are,primarily at the homestead (as this group was not found to belargely employed).

FGD respondents confirmed that adolescent girls eat what thewhole family eats, there is no specific diet for them (whether
married or unmarried). An adolescent girl’s diet may change
after she is married, either improving or becoming poorer
depending on the financial status of the in-laws. The majorityof families all eat at the same time, and in instances where
fruits and snacks are available, one women’s FGD reported
that those were reserved for children. Adolescent girls
overwhelmingly agreed that the diet does not change whenan adolescent girl becomes pregnant. They continue with theirnormal diet. Adolescent girls with children have knowledge on
the recommended diet during pregnancy; however few follow
9Figure 1. Primary sources of health & nutrition information
reported by adolescent girls

PRIMARY SOURCE OF HEALTH/NUTRITION INFORMATION
Did not receive / DK

School15%
Other

Care Group

34%

5%
6%

Community healthworker / volunteer

15%

25%
ClinicAdolescent time use:
Parents and peers have an influence on how the adolescents
spend their time at home and around the community.
Qualitative findings revealed that adolescents were generally
either at school or at home, while the data collection team also
observed adolescents going to church on Sundays. The nonschool going adolescents are expected to carry out householdchores such as fetching water, working in the fields, and otherdomestic chores. Those who are married are expected to do
more household chores per cultural norms. In cases where themarried adolescent girl lives with in-laws, she is expected to
do most of the work at home, even when pregnant. There are
specific roles for adolescent boys such as gathering firewood,clearing fields and watering livestock. After they finish doing
chores, some boys spend their time at the shops, watching TV,
and dancing to loud music till late while others play local soccer.
‘The shops’ (centrally located stores in a village or villages withbasic supplies, bars, food, and meeting places) were said tohave become a convergence zone for adolescents (typicallyafter school), and parents expressed dissatisfaction as theyfelt that this is where relationships among adolescents aredeveloped.
After household chores are completed, it is up to the adolescentgirl how she spends her free time. School-going adolescents
often read their books, while the non-school going roam aroundthe village with peers. One adolescent boy, when asked how
girls spend their time, commented that they are concerned withstaying clean and therefore roam around the village aimlessly,
not wanting to get dirty. Time-use also depends on the time of
the year, during the rainy season, girls spend most of their timein the field, ploughing and cultivating. At harvest time married or
unmarried girls spend most of their time in the fields harvesting
and fetching water.

FOOD SECURITY, DIETARY DIVERSITY, AND NUTRITIONALSTATUSWith 47.1% (324) adolescent girls found to be food insecure(moderate plus severe), food insecurity was found to be asignificant issue. The scale used, the Food Insecurity Experience
Scale (FIES), was developed by FAO as an experience-based
metric of severity of food insecurity that relies on an individual’s
direct responses to 8 questions regarding their access toadequate food over the past year.11 Event-based cues wereused to help adolescent girls recall this time period.

“During this time of the year, this area experiences water
shortage; hence girls spend more time queuing at theborehole to fetch water for domestic use and watering of
livestock. Queuing can take up to 4 hours and the girls canvisit the borehole three times a day.”– Mother from Mangwe

11. Ballard, T.J., Kepple, A.W. & Cafiero, C. 2013. The food insecurity experience
scale: developing a global standard for monitoring hunger worldwide. TechnicalPaper. Rome, FAO. (available at http://www.fao.org/economic/ess/ess-fs/voices/
en/).
10

or post menarche. Interestingly, we found that of thoseadolescents who were pre-menarche, 17.7% were stunted (HAZ<-2 SD), while among those who were post-menarche only 2.3%
were stunted. The correlation between menarche and stunting
was significant (p<.001), but should be interpreted with caution
due to the smaller sample size.

Figure 2. Percent food insecurity among adolescent girls

15.7%

Severe food insecurity
Moderate food insecurity

31.4%

Figure 3. Food Security Status by Level of Dietary Diversity(n=690)19%

Marginal food security
Food secure

33.9%
0

5

10

15

20

25

30

35

food secure40

food insecure

248
210

Dietary diversity score was 3.17 (SD 1.09) on average, with aslightly higher score in Mangwe compared to Tsholotsho.
Dietary diversity score does not vary by age or marital status.
Dietary diversity was measured using the 9-Item Women’s
Dietary Diversity Score (WDDS). According to recent FAO
validation study examining different options for analyzing the
9-Item WDDS scale data, a threshold of 5 or more food groups
consumed during the previous day is used as a positive indicator,
demonstrating greater probability of meeting micronutrient
needs. Consuming less than 5 food groups, however, does notindicate ‘poor’ dietary diversity. Rather, poor dietary diversity
is indicated by consuming 3 or fewer food groups during thepast 24 hours. Among our sample, the prevalence of good
dietary diversity is 11.2%, and poor dietary diversity is 66.4%.
Poor dietary diversity was slightly higher in Tsholotsho (70.3%)
compared to Mangwe (63.3%).

100
55
POOR

55

NORMAL/MODERATE

22
GOOD

LEVEL OF DIETARY DIVERSITY

Table 7: Food Security, Dietary Diversity, and Nutritional
StatusComparing mean dietary diversity score across levels of foodinsecurity (Figure 3), we find that greater food insecurity is
statistically significantly correlated with lower dietary diversity(Pearson X2 28.14, p<.001). This indicates food insecurity may becontributing to poor dietary diversity among adolescent girls.
The majority (96%) of respondents said that yesterday (therecall period for the dietary diversity scale) was not a holiday
or unique day in any way, indicating that the data is not biased
by unusual food consumption. Survey interviews were carriedout on every day of the work, thus avoiding bias related to dayof the week.
Height-for-age Z score (HAZ) less than -2 standard deviations
was used to classify girls as stunted, and a Z score less than -3
indicates severe stunting, using the WHO reference population
for girls 13-19 years of age.10 We found stunting rates to be at
6.7% and severe stunting at 1% in this population (excluding
pregnant adolescents, and any adolescent girls in their 19th
year, as there is no internationally established cutoff for these
populations).

All
n=692

Mangwen=406

Tsholotsho
n=286

N(%) orMean(SD)

N(%) orMean(SD)

N(%) orMean(SD)

Food Security1
Food secure
Marginal food security
Moderate food insecurity
Severe food insecurity

233 (33.9)
131 (19.0)
216 (31.4)
108 (15.7)

101 (25.1)
81 (20.1)
146 (36.3)
74 (18.4)

132 (46.2)
50 (17.5)
70 (24.5)
34 (11.9)

Women’s Dietary Diversity
Score (Average)2

3.17 (1.09)

3.23 (1.14)

3.08 (1.02)

Women’s Dietary Diversity
Good (≥5 food groups)
Poor (≤3 food groups)

77 (11.2)
458 (66.4)

56 (13.9)257 (63.6)

21 (7.3)
201 (70.3)

Stunting (HAZ <-2 SD)3

40 (6.7)

19 (5.4)

21 (8.5)

Severe stunting (HAZ<-3SD) 3

6 (1.0)1 (0.3)5 (2.0)Thinness (BMI/age Z <-2) 3

36 (6.0)

26 (7.4)

10 (4.0)

Severe thinness (BMI/age Z<-3) 35 (0.8)4 (1.1)1 (0.4)

All percents are column percents.
1. From the FAO Food Insecurity Experience Scale (FIES) tested for use in
Ndebele language in Zimbabwe
2. Based on the 9-Item FAO Women’s Dietary Diversity Score (WDDS). A dietis more likely to meet micronutrient needs at ≥5 food groups. Poor dietary
diversity is defined at ≤3 food groups consumed.
3. Only among non-pregnant adolescents 13-19 years as there areestablished cutoffs for this group (n=599)

Thinness, measured by BMI-for-age Z score less than -2
standard deviations using the WHO reference population,12 was
at 6%, and 0.8% were found to be severely thin (BMI-for-age Z<-3) (Table 7). Previous research has shown that menarche (orpuberty) may be an opportunity for catch-up growth. Thus, we
explored whether stunting was higher in those pre-menarche

HEALTH AND HEALTH ACCESS
Adolescent girls were asked about key health indicators andhealth seeking behaviors, as well as their perspective on andcomfort level with the health services they received (Table 8).
We asked adolescent girls about several risky behaviors.

12. Woodruff BA and Duffield A (2002). Anthropometric assessment of
nutritional status in adolescent populations in humanitarian emergencies.
European Journal of Clinical Nutrition, 56:1108-1118.
11others said that their mother (24%), grandmother (20%), or
aunt (4%) typically decides this for them. Very few adolescent
girls reported that their father or brother decides when or ifthey should seek healthcare for themselves. And, most (78%)
said if they wanted to make their own decisions about seeking
healthcare they could some or most of the time.
Most FGD participants believed that adolescents between theages of 13 to 15 were healthy, while those over 15 with children
were said to be showing signs of poor health. Parents felt thatthe poor health was due to poverty and diseases, and did not
attribute it to malnutrition of any kind.
Table 8: Health Status & Health Access by District
All

MangweTsholotsho

N(%) orMean(SD)

N(%) orMean(SD)

N(%) orMean(SD)

81 (11.7)
369 (53.6)
212 (30.8)
26 (3.8)

59 (14.6)
199 (49.3)
131 (32.4)
15 (3.7)

22 (7.7)
170 (59.9)
81 (28.5)
11 (3.9)

Diarrhea in past 2
weeks

55 (7.9)

28 (7.0)27 (9.5)

Ever taken deworming
medication

85 (12.3)

45 (11.2)

40 (14.0)

667 (96.8)

393 (97.3)

274 (96.1)

666 (98.5)
6 (0.9)396 (98.0)
2 (0.5)270 (94.4)
4 (1.4)2 (0.3)5 (0.3)1 (0.3)0

1 (0.4)5 (1.7)

Respondent felt comfortable seeking healthservices

658 (97.3)

381 (96.5)

277 (98.6)

Healthcare services
met respondent’s
needs as an adolescent

658 (97.1)

384 (96.5)

274 (97.9)

Health status
Self-rated health
Excellent
Good
Acceptable / fair
Poor

Health seeking behavior
Seeks assistance whensick or have health-related need
Where health assistance sought
Health facility
Faith/Traditional
healerFriend or relative
Other (village healthworker, home-based
care)

Most girls (97.2%) reported that they never drink alcohol, andthe questionnaire did not include smoking as this was said tobe very uncommon during the pilot test. (Findings regarding
condom use at last sexual encounter are reported in the
reproductive health section.)
Most adolescent girls said they seek healthcare when sickor having a health-related issue. Among those who said they
do not seek healthcare, reasons given were primarily lack ofneed, a feeling that she could take care of herself, or distance.
Similarly, the majority (97.3%) said they feel comfortable seeking
health services as an adolescent, and that the services meettheir needs. Among those who said they were uncomfortable(2.4%) or felt the health services did not meet their needs (2.7%),
the following reasons were given: nurse attitude (nurses weresaid to be ‘mean’, aloof, rude, or accusing the girls of ‘loose
morals’), slow service/long lines, hesitancy to go accompanied
by parents, lack of medications or corruption in distribution.

“It is difficult to say with certainty because it is difficult todistinguish between actual malnutrition and a disease. Lack offood exacerbates disease states and at the end of the day its
combined disease and malnutrition. Reasons for lack of foodrange from difficult economy, limited rainfall to laziness.”– Mother from Mangwe
Mothers have great influence when it comes to health accessfor school attending adolescent girls. Mothers accompany theadolescent girls to health care centers for health attention,
while adolescents with children make their own decision toseek medical attention. Married adolescent girls living with inlaws stated that they make their own decision to seek healthadvice for themselves and for their children.

While many adolescent girls (43%) said they typically decide
about seeking healthcare for themselves for any reason,
12

WATER, SANITATION, AND HYGIENE (WASH)

ADOLESCENT SOCIAL/COMMUNITY ENGAGEMENTWASH indicators, such as handwashing with soap, diarrhea
prevalence, and drinking water source and treatment havebeen shown to be predictors in nutritional status. Among
those adolescent girls who had reached menarche (n=540),
the majority (83%) reported that they bathe more often during
menstruation (while one respondent said that bathing the fullbody was considered taboo during menstruation). Girls haveaccess to products to manage menstruation (92%), but some(7%) were using found items (such as rags or leaves) rather
than purchased sanitary products. While most girls keep goingto school during menstruation, about 12% do not. This could
potentially be related to poor sanitation at school or lack ofaccess to sanitary products, though this was not included in thequestionnaire.

We asked adolescent girls about their social or community
engagement, and specifically the types of activities they engage
in socially. Forty-three percent (295) said they are engaged insome type of group or community activity on a regular basis.
The most common group activity for girls to be engaged inwas sports (41%), primarily associated with schools. This wasfollowed by school clubs, religious gatherings, Care Groups,
and youth groups (see Figure 4.)
Figure 4. Adolescent girl involvement in group/social activities
ADOLESCENT GIRL GROUP / SOCIAL ACTIVITIES
Other

4

Volunteer Work

1

Care Groups

13

SportsTable 9: Water and Sanitation indicators among
adolescent girls

41

School Clubs

17

Religious Gatherings

15

Youth Groups

N(%) or Mean(SD)7Community Health Clubs

20

Main source of drinking water
Piped water, into home
Piped water, public tap
Tubewell or borehole
Dug well (protected)
Dug well (unprotected)
Surface water
Digging into a dry river bed
Irrigation canal

10 (1.4)
10 (1.4)457 (66.2)
83 (12.0)
34 (4.9)90 (13.0)
5 (0.7)1 (0.1)

Number(%) of girls who collect water

604 (87.5)

Avg. liters per day carried by girls (n=604)

31.6 (29.15)

Avg. time to get water for girls (n=604)≤ 30 minutes
31-60 minutes
1-3 hours

323 (66.7)
118 (24.4)
38 (7.9)

Family has a latrine

413 (60.0)

No. of Respondents who identified the 5 criticalhandwashing moments

94 (13.6)

Respondent bathes more often during menstruation

452 (83.5)

Respondent has access to products to manage
menstruation

499 (92.1)

Respondent continues to go to school during
menstruation

283 (88.2)1

5

10

15

25

20

30

35

40

45

PERCENT

4. DISCUSSION &RECOMMENDATIONSThis assessment identified a variety of socio-behavioral andother factors that may contribute to adolescent girl nutritional
status and practices in Zimbabwe. Adolescent girls in Mangwe
and Tsholotsho were commonly engaged in food preparation,
though had little food-related decision making power and low
levels of knowledge surrounding general nutrition, particularly
nutrition during pregnancy. Many experience food insecurity,
and related, poor dietary diversity, indicating their diets areunlikely to meet micronutrient adequacy. The overall women’s
dietary diversity score for adolescent girls in our sample was
3.2, which is corroborated by the dietary diversity score (3.1)
found by a recent Title II Food for Peace baseline survey inAmalima and ENSURE program areas.13
Pregnancy among unmarried adolescent girls is common, andonly about 29.5% of girls are using some type of contraception,
indicating more work is needed to increase both knowledge
and use of contraception for delaying/avoiding pregnancy or
spacing births. Due to heightened nutritional needs in this age
group, pregnancy poses additional risks. In addition, although
60.6% of married/sexually active adolescent girls reported
condom use at last sexual encounter, continued promotionof condom use for protection against sexually transmitted
infections (STIs) is important.

1. Low response rate 173 missing in error

Finally, respondents reported that menstruating women in
their communities are prohibited from the following activities:
gathering wild fruits (4%), herding cattle (5%), milk consumption(8%), farming (10%), cooking (12%), sexual activity (33%), religious
activities (54%), and in some cases other activities such as
meeting/gathering, handshaking with men, salty food, touching
glasses, bathing the whole body (only bathing limbs permitted),and milking the cattle.

A variety of ‘key influencers’ or ‘gatekeepers’ were identified.
As mentioned, the aunt was identified as a major source of
information for adolescent girls on pregnancy, and contraceptiveuse, and may have influence over nutrition or food-related
decisions depending on household structure. The mother
13. USAID, Baseline Study of Title II Development Food Assistance Programs
in Zimbabwe, 201413

was identified as the primary decision-maker surrounding
both food purchases and food preparation. Adolescent
girls commonly decide for themselves about seeking healthservices, and many identified their mothers or grandmothers as
key influencers in health-seeking decisions. Decision-making
on school attendance, on the other hand, is mixed. Adolescent
girls identified either their parents or themselves as the primarydecision-makers; however, during FGDS parents said theyusually make this decision, while some adolescents (boys andgirls) said they can make this decision for themselves. This
indicates a need to involve parents in any programs intending
to incentivize adolescent girl school attendance.

growth in adolescence, namely: “the large variability in timing,
expression and duration of pubertal growth and somaticdevelopment, and the relationship between the measurement
error and the increase in growth observed within a defined time
period.”10
According to the Zimbabwe DHS, prevalence of thinness
among adolescent girls 15-19 years was 13.5%.16 Our study
found a 6% prevalence of thinness among adolescent girls
13-19 years, which is below the national average from 2010-11.
While this assessment was powered to look at undernutrition inadolescent girls, this finding should be interpreted with caution
due to the reduced sample size for this statistic, and should not
be extrapolated beyond the districts represented by this study.

Adolescent girls were largely unable to name the five key
handwashing moments, which is a risk factor for diarrheal
disease. Only 8% of adolescent girls, however, reported having
diarrhea in the past two weeks. Most households whereadolescents were residing get their water from a borehole,and about 87% of adolescent girls are involved in fetching andcarrying water regularly, with distances typically less than 30
minutes away, but sometimes reaching 1-3 hours of walking.
Most girls reported being able to bathe more often during
menstruation, and most had the products they needed to manage
menstruation, though some were using found items rather thansanitary products from a store. A previous assessment carriedout by International Medical Corps found that a major reason forgirls using found items was embarrassment to ask for sanitary
products. Because over 12% of menstruating girls reported notgoing to school during menstruation, further inquiry is neededat the school level to find out if any barriers exist (lack of clean
latrines, running water, sanitary supplies) to menstruating girls
attending school.

RECOMMENDATIONSWorldwide, interventions for adolescent nutrition need to bescaled up.17 The following program and policy recommendations
are based on the findings of this assessment, and aim to respondthe unique nutrition and health-related needs of adolescent
girls in Mangwe and Tsholotsho districts of Zimbabwe (thoughmany of the lessons here may be applicable to other districts
as well).
I. Integrated behavior change promotion on SRH, WASH,
and Nutrition through school and other platforms: Based on
findings of high pregnancy rates (particularly outside marriage),poor knowledge of proper hygiene and sanitation, and poor
dietary diversity, integrated programming for adolescent girls(and potentially boys) is recommended where possible.
Below are some suggested approaches and considerations:

Stunting was lower than expected among this population. This
could be related to the reduced sample size for this measure(n=599), as currently pregnant adolescents and those in their
19th year were excluded due to lack of established cutoffs
for these populations. Alternatively, this could be related topotential catch-up growth during adolescence. Researchshows that there could be an opportunity for catch-up growthin adolescence related to growth during puberty, yet this isunder-studied.14,15 To explore the possibility of catch-up growthin our population, we looked at stunting by menarche status.
Interestingly, we found significantly higher rates of stunting
among those adolescents who were pre-menarche, comparedto those who were post-menarche (X2 35.29, p<.001). Stunting
in children age 48-59 months (just before their fifth birthday) isa. Integration of WASH, Nutrition, and SRH education canoccur through school classrooms, school clubs, youth clubs,
etc. – places where education is already ongoingb. It is important to provide age-sensitive SRH information,
including fertility awareness, sex education and contraception.
Promotion of birth spacing and delayed pregnancy can go
hand-in-hand with good nutrition massaging.
c. WASH and nutrition are inextricably linked, and it makes
sense to integrate behavior change promotion on theseareas. Because so few girls could identify the five criticalhandwashing moments, this could be one key behavior
promoted through schools, as well as discussing diarrheal
disease and the impact on nutritional status.

26% according to the Zimbabwe DHS,11 so the rate of stunting
we found in pre-menarche adolescents (17.7%) is only slightly
lower in comparison. The correlation between menarche andstunting is significant, yet should be interpreted with caution as
the sample size is small. More research is needed to determine
if stage of puberty is related to stunting among adolescent girls
in general, and specifically in Zimbabwe. Previous research has
noted the difficulties associated with measuring catch-up

d. Behavior change programs should promote both general
hygiene and menstrual hygiene as part of outreach, linking
WASH and SRH. This is particularly needed in schools, where
about 12% of girls do not attend during menstruation (thoughreasons for lack of attendance during menstruation should
be explored first).
e. Ensure nutrition is added to the current health curriculaand activities promoted in schools. This includes education

14. Coly AN, Milet J, Diallo A, et al. (2006). Preschool Stunting, Adolescent
Migration, Catch-Up Growth and Adult Height in Young Senegalese Men and
Women of Rural Origin. J Nutr 136: 2412-2420.
15. Largo RH (1993). The Physical Status: The Use and Interpretation of
Anthropometry in Adolescence. Horm Res 39(suppl 3);41-48.

16. Demographic and Health Surveys (DHS), Zimbabwe, 2010-2011.
17. Save the Children (2015) Adolescent Nutrition: Policy and programming in
SUN+ countries
14

on the importance of proper diet, diet diversity, frequency ofmeals per day, and diet during pregnancy.

female head of household). Such interventions could have apositive effect on both adolescent girl nutrition and household
nutrition.

f. School gardens are a hands-on way to both teach girls
about dietary diversity, and provide them with foods to takehome and include in their diets.

V. Contraception promotion and education should beincorporated into adolescent programming: Pregnancy rates
are high (27%), with the majority of ever-pregnant adolescents
being unmarried, indicating unintentional pregnancies may becommon. Overall contraceptive use was 29.5% and condom use
at last sexual encounter was around 60%, indicating room for
improvement. Due to awareness surrounding STIs, particularly
surrounding HIV as Zimbabwe has one of the highest
prevalence rates in the world (16.7% in adults 15-49), adolescent
girls seemed to have more knowledge about ‘protection’ than
the importance of family planning and birth spacing for theirown health and the health of their babies. In addition to lack ofknowledge, a previous International Medical Corps assessment
found that adolescent girls in Tsholotsho district faced thefollowing barriers to accessing contraceptives: fear of society’s
perceptions, distance to nearest services, shortages, and lackof information or knowledge. Based on these barriers, it isrecommended to increase targeted contraception promotion,
education, and access among adolescent girls, as well as men
and boys. Below are some potential platforms:

II. Meet adolescents where they are: This report identifies
venues where adolescent girls spend their time. In order toreach this group, interventions should target behavior change
promotion, services, and activities through existing social
mechanisms. These include: sports groups or events, schools
and school clubs, religious gatherings (church youth groups),
Care Groups (for pregnant adolescents and adolescentmothers), and other peer groups. Boreholes should beconsidered as most adolescent girls fetch water. Additionally, forthose adolescents (primarily older adolescent girls) who spend
most of their time in the home or in domestic work in another
home, a peer group model (such as Care Groups) that meetsin the community and is targeted specifically for adolescent
girls should be considered. Finally, because mothers andgrandparents were identified as the primary decision-makers onfood expenditure and preparation, and aunts were identified as
an influential group on information surrounding pregnancy andcontraceptive use, a session for these individuals on important
nutrition, contraception, and pregnancy-related information foradolescent girls is another recommended route to reachingadolescent girls.

a. Introduce contraception education and behavior change
to existing programs that adolescents participate in, such as:
Care Groups, Community Health Clubs, religious activities,
and school activities (clubs, peer groups, sports).

III. Promote good diets during pregnancy: Adolescent girls
have very little knowledge about dietary requirements andrecommended changes during pregnancy, and may havevery little say in decisions surrounding their own diets (unlessthey are the female head of household). Zimbabwe alreadypromotes the “4-star diet” for pregnant women,18 and it isrecommended that this (along with messages on increasing
consumption) are incorporated into programs teaching
nutrition to adolescents and ‘key influencers’ (such as mothers,
grandmothers, and aunts) so that those making food purchaseand preparation decisions are aware of the recommended
diet during pregnancy. In addition, ANC nutrition counseling
was found lacking (only 60% reported receiving counselingon nutrition during ANC sessions). It is recommended that the“4-star diet” is promoted through ANC nutrition counseling forevery mother.

b. Work with ‘key influencers’ identified through thisassessment to introduce important contraception andnutrition messages for adolescent girls. This could include
working with aunts and mothers to facilitate conversations
with adolescent girls about delaying marriage, delaying
pregnancy, birth spacing, and recognizing the importance ofcontraceptive use if sexually active, as well as sources toobtain contraceptives.
c. Utilize mobile phones to distribute information oncontraceptive use, access, and the benefits of delayed
pregnancy and birth spacing. Adolescent girls were reported
to use Facebook and WhatsApp regularly.
d. Establish maternity homes near clinics for women waiting
to deliver where nutrition education could be provided
on optimal health actions, and healthy spacing of babies
utilizing family planning could be introduced.

IV. Interventions targeting nutritional improvement during
meal preparation: Adolescent girls play a key role in foodpreparation in the household, with 47% being the primary foode. Work with men and boys to engage them on issues ofcontraception, including exploring whether and how fathers
support unmarried, pregnant adolescent girls. (This will
require further study for program planning purposes).

preparers, and 92% preparing food often. Girls, however, havelittle say in what food is prepared and almost no say in foodpurchases. Mothers are primary decision-makers on what is
prepared for meals, followed by grandparent, and then theadolescent girl. For this reason, programs targeting behavior
change surrounding recipes and meal preparation (such as
Care Groups, and potentially Community Health Clubs or a
Positive Deviance/Hearth approach) are best placed if theytarget both the adolescent girl and her mother (or the primary

f. Explore working with local shops, pharmacies, and healthclinics to provide contraceptive methods that girls areinterested in using. This includes training health facility staff
in adolescent-friendly services.
VI. Creative solutions for targeting older adolescent girls(14-19 years) are needed: Older adolescent girls are often
incentivized to drop out of school after Form 4 (secondary

18. The 4 star diet can be found in this promotional flyer by UNICEF: http://www.
unicef.org/nutrition/files/Brochure_maternal_nutrition.pdf
15

education) due to lack of funds for school fees, the need forincome, demanding household chores, pregnancy, marriage, or
migration for work. Adolescent girl respondents also agreed thatthey endure long distances to reach school. Some adolescenthousehold heads drop out to take care of household demands.
Many older adolescents take up domestic work outside theirown homes, and many migrate for work. Early marriage is nota big issue in the population, but pregnancy is common. This isa hard-to-reach population, and programs must be creative intargeting approaches for older adolescents both to incentivize
school attendance, delay pregnancy and marriage, andpromote good nutrition. Potential program platforms include:

adolescent girls, by giving them an income-generating
activity at home and encouraging them to stay in the area.
Such livelihood activities could contribute not only to theadolescent girl’s wellbeing, but also to her family’s wellbeing.
Community norms may be at play here as well, and whenplanning this activity consideration should be taken to workwith parents of adolescent girls, and the relatives abroad (ifpossible) who are said to support girls to migrate before they
complete school.
d. ‘Community conversations’: As part of the same study,
the Population Council found that “in communities that were
engaged in conversations about the value of educating girls
and the harms of child marriage, girls 12–14 year were twothirds less likely to be married at endline than were girls inthat age range at baseline (adjusted odds ratio 0.37, 95%
confidence interval 0.18–0.76).”13 When planning ‘community
conversations’ it is important to include all ‘key influencers’
who adolescent girls identified through this assessment (seeTable 10).

a. Peer-to-peer models: Peer groups – based at schoolfor school-going girls or using the existing Care Group or
Community Health Club model – can be used to promote
adoption of healthy behaviors related to contraceptive use,
WASH, and nutrition. This is a good opportunity to discuss
the culture of unplanned pregnancies, as related to thetransient male populations or the need to migrate for work.
This would also provide a forum to discuss the consequencesof engaging in unprotected sex. Peers can provide condoms
through this platform, and encourage the use of other formsof contraception for delaying/avoiding pregnancy. Suchgroups can also provide links to clinics and other services
available to adolescent girls. Other organizations havesuccessfully implemented such peer-to-peer groups in theform of ‘Community Clubs’ or ‘Safe Spaces’ for adolescent
girls (see Mercy Corps programs in Niger19), and in Zimbabwe
this could build upon existing Community Health Club or
Care Group models.

Table 10: Key influencing groups and areas of influenceb. Take-home food rations to incentivize high school
attendance: While take-home rations have been used largely
in primary school settings to incentivize girl attendance, thismay be a good incentive for adolescent girl attendance
during secondary or high school as well, particularly in
the Zimbabwe setting where lack of funds for school fees,
poverty, and need for employment or help at the homestead
are common reasons for adolescent girls dropping out
of school. Parents, primarily, were said to decide whether
adolescent girls attend school, and such an incentive may
help change parents’ minds as well.
c. Income generating activities associated with schools/
school clubs: Recent research in sub-Saharan Africa by the
Population Council shows one model particularly effective
in delaying marriage among adolescent girls and keeping
them in school longer. This model included a conditional
economic transfer of a goat or chicken for families who keep
adolescent girls unmarried and in school. They found that“in communities where girls were offered two chickens forevery year they remained unmarried and in school, girls aged
15–17 years were half as likely to be married at endline thanwere girls in that age range at baseline (adjusted odds ratio
0.50, 95% confidence interval 0.29–0.83).” 20 This approach
could also help address the migration patterns among older

Key Influencing GroupArea

Schools, Clinics,
Community health workers

Health/nutrition information

Aunt

Pregnancy, contraception

MotherFood preparation and purchase,
health seeking behavior, school
attendance

FatherFood purchase, school attendance

Head of household

Food purchase

Self

Marriage, sometimes school
attendance, sometimes healthseeking behavior

Grandmother

Health-seeking behavior, sometimes
food preparation

Shops, shopkeepers(a place where adolescent girls
spend time)

Boreholes(a place where adolescent girls
spend time)e. Mobile phone platforms: Girls were said to use mobile
phones, particularly WhatsApp and Facebook, as a main modeof communication. These platforms should be considered whenplanning adolescent-specific activities as a tool for organizing,
messaging, and sending reminders/cues for action.
VII. Establish ‘Safe Spaces’ for all ages of adolescent girls:
Establish safe and welcoming spaces where adolescent girls
are free to come together. Provide information and activities
related to the key behaviors and practices identified in thisreport that may be resulting in poor health/nutrition. There is amodel for’ Safe Spaces’ in the Girl-Centered Program Design:
A Toolkit to Develop, Strengthen and Expand Adolescent Girls
Programs.21

19. Mercy Corps model in Niger: http://reliefweb.int/report/niger/nigerien-girlsfind-place-discuss-marriage-health-nutrition
20. “New Research from the Population Council Shows Child Marriage Can Be
Delays.” http://www.popcouncil.org/news/new-research-from-the-populationcouncil-shows-child-marriage-can-be-delaye

21. Girl-Centered Program Design: A Toolkit to Develop, Strengthen and Expand Adolescent Girls Programs (Available at: http://www.popcouncil.org/research/girl-centered-program-design-a-toolkit-to-develop-strengthen-and-expand-ado)16

herders, local non-school-going adolescent boys, and men
returning home during the holidays from work cross-border.
Although we did not interview husbands of adolescent girls,
this group should be considered as well. Working with these
populations to ensure they have both contraception knowledge
and access to contraceptives may help prevent adolescentpregnancy.

VIII. Nutritional Surveillance: There is a need to expand andenhance nutritional surveillance to collect information on the
nutrition situation of all adolescent girls (from as young asage 10 up to 19 years). This could include collecting data onadolescents through routine government-led data collection. If
adolescent girl nutritional status goes unmeasured, then it is notpossible to know if it is being addressed. New approachedsand
technologies for data collection among adolescents could beconsidered, including: cell phone platforms, utilizing the CHW
workforce, or using peer leaders to collect and report data.
The approach must be culturally appropriate, and seek theadvice of traditional and village leaders to help design the datacollection system.

XII. Policy Recommendation:a. First, further studies in other provinces or at the national
level are needed to confirm and expand upon results fromthis study. This assessment cannot be extrapolated to alarger population; however, these findings can contributetoward informing MOHCC, NGOs, and other key partners
on the most common health and nutrition issues affecting
adolescents and designing practical, relevant activities toeffectively reach adolescents.

IX. Link girls to vocational centers: More research is neededon what vocational activities girls and their families consider
useful. This information could be used to develop or linkadolescent girls to centers where they are offered training on
a particular skill, one which they envision providing them anincome in the future. Examples include sewing, agriculturalactivities, livestock, first aid, and others.

b. The MOHCC’s National Nutrition strategy has prioritizedadolescent nutrition (key Result Area 1 of the strategy), but
acknowledges that there are no specific adolescent nutrition
programs in Zimbabwe. This assessment can be used tosupport the development of new programs or approaches
to target adolescent nutrition (pending findings from further
research).

X. Address food insecurity, which is linked to dietary diversity:
Two potential approaches were identified for addressing foodinsecurity, which was found to be high in this population:c. Findings from this assessment should be shared with the
Ministry of Education, a key player in reaching adolescents
due to the school platform. The MoE should be included inany discussion of strategy for reaching adolescent girls, as
it is important to meet girls where they already are. Many
girls identified schools, school clubs, and school-related
sports activities are places where they gather, spend time,or receive health/nutrition information.

a. Work with the private sector to improve access to nutrientrich local foods (animal-source foods, fruits, vegetables),considering micronutrient supplements and fortification to
improve the diets of adolescent girls if found to be effective
through further research. Private sector participants toconsider include input dealers, especially those of improved
seeds. A voucher scheme (below) could be linked to thisapproach, by providing access to agricultural inputs (e.g.
improved seeds, vegetables, farm tools, etc.) or a hen/chicken. The latter are easier to tend by both girls and theirparents.

d. It is recommended that any strategy to address adolescentnutrition include ministry-level interventions aimed ataddressing the issue of food insecurity, which is highly
prevalent and is related to poor dietary diversity in this age
group.

b. Consider providing conditional vouchers as part ofother interventions. Criteria should be established andbeneficiaries sensitized on criteria for qualification andtimelines. Cash vouchers grant greater flexibility; thus a
combination of vouchers and working with the private sector
should be considered. Commodities selected for conditionalvouchers must be available in local communities.

e. As adolescent nutrition strategy is developed, it isimportant to remember the ‘key influencers’ who adolescent
girls identified in different areas, and work with them as well.
(See Table 10)
XIII. Recommendations for Follow-On Research:

Interventions targeting availability of and access to food mustgo hand-in-hand with behavior change promotion. Poor dietary
diversity and food insecurity are highly correlated, indicating
food availability and access are an issue in achieving variety
in the diet. For this reason, any behavior change interventions
aimed at improving dietary diversity should go alongsideinterventions that practically address food insecurity among
adolescent girls and their families. Dietary diversity interventions
can include keyhole gardening (focusing on increasing dietdiversity), animal husbandry (chickens, small ruminants, etc.), or
school gardening. (Also see Recommendation VI).

a. Further assessment in other provinces or at the national
level is needed to confirm findings and represent other partsof Zimbabwe.
b. More research is needed to confirm if adolescents acrossthe Zimbabwe are using health services, or if this was morecommon among our sample alone. This should include
both discussion with the MOHCC, health service providers,and assessment among adolescents. It should also include
questions regarding who is paying or making payment
decisions surrounding healthcare use. If the majority ofadolescent girls across Zimbabwe are using health services,then this is an opportunity through which to reach them withother nutrition services.

XI. Working with men and boys: Based on qualitative findings,
several groups of men and boys stood out as key groups totarget in reducing adolescent pregnancy. These include: cattle17

c. More research is needed on indigenous or traditional
foods, to identify which are nutrient rich, available toadolescent girls, and liked by adolescent girls, as well as
barriers to eating certain nutrient-rich indigenous/traditional
foods.
d. Future assessment of adolescent nutrition in Zimbabwe
should include measurement of anemia status, as thisis a common issue facing adolescent girls worldwide.
Deworming treatment use in our sample was low, and islargely absent (9%) at ANC visits. Future research could
examine the links between deworming and anemia in thispopulation, as deworming has been found to be a safe andeffective intervention that can be administered at the schoollevel or through ANC for adolescent girls.22
e. Research is needed on men’s perspectives, roles, andbehaviors to determine best approaches to engaging men
to prevent early marriage/pregnancy.
f. Overall, further research is needed to establish ageappropriate cutoffs for measurement of adolescent nutrition.
Additionally, establishing more appropriate adolescentreference populations by region or country is recommended
to enable more accurate calculation of adolescent nutritional
status.

22. WHO, School-based deworming at a glance, March 2003.
18

ANNEX 1: Assessment of Food
Insecurity Experience Scale Data in an
International Medical Corps Survey ofAdolescent Girls in Zimbabwe in 2015

would not be correct and are not reported here.
Missing responses to the FIES questions were rare. Only
7 cases (1.0 percent) had any missing responses, and 4 ofthose missed only a single question. Two respondents missed
all 8 FIES questions. No item was missed by more than 2 ofthe respondents who gave valid answers to any of the FIES
questions. This low proportion of missing responses indicatesthat the questions were not unreasonably sensitive or difficult
to answer. The seven cases with missing responses wereomitted from all analyses here. For substantive use, those with
only a single missing response could be included, with their raw
score calculated as the sum of valid responses (i.e., effectively
imputing “no” to missing responses. The remaining 3 cases
should probably be omitted from analyses of food insecurity.

Mark Nord, Voices of the Hungry, FAO
August 6, 2015
The Food Insecurity Experience Scale (FIES) was included
in a survey of adolescent girls (ages 13-19) in Zimbabwe,conducted by International Medical Corps in 2015. The survey
was conducted in two Districts (Mangwe and Tsholotsho) andfocused on adolescent health and nutrition. The Voices ofthe Hungry (VoH) project of the United Nationals Food andAgriculture Organization (FAO) was asked to assess the qualityof the FIES data and provide guidance for food security statusclassification.

COMPARISON DATA
I compared psychometric statistics of the International
Medical Corps data with GWP 2014 data for Zimbabwe, fora subsample of those data interviewed in Ndebele, and fora subsample of those data for females ages 15 to 20. (TheInternational Medical Corps survey included girls 13 to 19.
GWP does not survey individuals younger than 15. I included
age 20 in the comparison subsample to get enough cases foreven marginally reliable results.) The two subsamples were
too small for reliable psychometric statistics, but provide someindication as to whether differences between the International
Medical Corps and GWP data may be related to language ofadministration or to unique characteristics of young womenand girls.

The assessment includes two parts:• Assessment of the quality of the FIES measure in theInternational Medical Corps data for use within the survey(and, by extension, the potential usefulness of the samemeasure in future surveys of similar populations)• Assessment of the comparability of FIES-based results in
the International Medical Corps data with national and global
results from other surveys using the same instrument.
Psychometric statistical methods based on the Rasch
measurement model are the main basis of the assessment. I
provide brief descriptions of the statistics reported, but readers
who are not familiar with these statistical methods may wantto consult the VoH report, Introduction to item response
theory applied to food security measurement: Basic Concepts,
Parameters and Statistics, available at http://www.fao.org/3/ai3946e.pdf for further information on the statistics.

QUALITY OF THE FIES MEASURE IN THE
INTERNATIONAL MEDICAL CORPS DATA FOR USE
WITHIN THE SURVEY
Here, I report statistics that assess the consistency of the datawith assumptions of the Rasch measurement model, and I reporta statistic indicating the reliability of the measure. The extent towhich data are consistent with assumptions of the Rasch modelis important, as those assumptions justify the use of raw scoreas an ordinal indicator of severity of food insecurity. The validityof the respondent parameter as an interval-level measure ofseverity also relies on the data meeting model assumptions.

QUESTIONNAIRE
The questionnaire was the standard Food Insecurity Experience
Survey Module for Individuals, FIESM-I (i.e., referenced to theindividual respondent, not to the household as a whole). Allinterviews were conducted in the Ndebele language, using
the Gallup World Poll (GWP) 2014 translation. Questions werereferenced to the 12 months prior to the survey.

Item “infit” statistics assess the important Rasch-model
assumption that all items discriminate equally (i.e., are havethe same strength of association with the latent trait of foodinsecurity). Infit is an information-weighted chi-square-typestatistic that compares the observed responses to the item tothe expected responses given item severities as estimated in
the model and the raw score of the respondent. The expectedvalue is 1.0 for all items. Higher values indicate weakerassociation with the latent trait (i.e., higher chi square). Values
between 0.8 and 1.2 are generally considered to indicate goodconsistency with the model assumption of equal discrimination,and 0.7 to 1.3 indicate acceptable consistency for positive
contribution to the measure.

DATA AND MISSING RESPONSES
Data were provided to VoH for 692 girls. Of these, 45 werein households in which more than one girl was interviewed.
Separate analyses were conducted including all cases
and including only one case per household. Results were
essentially identical, and only the all-cases analysis is reported
here.
The sample design was complex, and sampling weights were
not available in the data provided to VoH. The psychometricanalysis is, in general, not sensitive to weighting, but prevalence
estimates for the target population based on unweighted data

The infit statistics for these data are unusually good in myexperience of food security measurement. The highest is 1.07
19

and the lowest 0.84 (Table 1). The sample is rather small for adefinitive psychometric assessment, but the lack of statisticalpower is as likely to overstate as to understate model-fit
problems.

International Medical Corps data is also higher than in eitherof the GWP subsamples (.71 for respondents interviewed
in Ndebele and .69 for females ages 15-20.) For a further
comparison, in the 2014 GWP data for about 147 countries, themean Rasch reliability (the equally-weighted variant) was 0.74.
In general, higher reliability indicates response patterns thatare more consistent with the severity-order of the items. We
expect that if a respondent says “yes” to an item, she will also
say “yes” to all items that are less severe, and if she says “no” toan item, she will also say “no” to all items that are more severe.
It is not expected that this pattern will be absolute—only
probabilistic. The extent to which this pattern predominates
increases the dispersion of item parameters, which, in turn,increases the dispersion of respondent parameters relative tomeasurement error and, thus, increases reliability. In practicalterms, high reliability indicates that respondents understoodquestions consistently, responded thoughtfully, that responses
were recorded accurately, and that the way food insecurity isexperienced and described in the sample is consistent acrossrespondents.

Outfit statistics are also very good. Outfit is similar to infit except
that, since it is not information-weighted, it is very sensitive to
unexpected outliers. Such outliers may indicate idiosyncratic
conditions, careless responses, or incorrect coding of
responses. No such problems are suggested by these outfit
statistics.
The second model assumption to be tested is conditional
independence of items. The Rasch model assumes that
responses to any two items are correlated only because of theirmutual association with the underlying latent trait. In practicalterms, this means that we do not want two questions thatask about essentially the same behavior or condition causedby food insecurity. Conditional independence is assessedby comparing observed correlations among items with thecorrelations expected given item and raw-score parameters
and the distribution of cases across raw scores. I have notshown the conditional correlation matrix, but note that theconditional correlation between HEALTY and FEWFOODS is
marginally high enough to be of concern (r=.41). These two items
have shown conditional correlations in several other datasets,
and it is readily apparent why this could be the case, as theyboth reflect similar expressions of reduced diet diversity. In the
GWP Zimbabwe data, however, the conditional correlation is
only .26 (analysis not shown). While this is the highest inter-item
conditional correlation in those data, it is far below the levelat which it would be considered problematic. The conditionalcorrelation for these two items was .29 in the GWP Ndebele
subsample, and .37 in the GWP “females 15-20” subsample.
These statistics are not very reliable given the small sample
sizes, but may suggest that the marginally high correlation in
the International Medical Corps data may be typical of young
women and girls. In a future administration, it may be worthwhile
to examine the translations of these two items to see if they
can be tweaked to refer to more distinct conditions. However,for use in the current International Medical Corps data, any
distortions caused by this conditional correlation will be smallenough to not be worrisome.

In summary, raw score on the FIES in the International Medical
Corps data can be used with confidence as a valid ordinalmeasure of severity of food insecurity. Statistics for respondents
by raw score are presented in Table 2. Food security status aspresented in Table 2 will be fairly consistent with severity levels
indicated for Zimbabwe and other countries in the forthcoming
VoH report on the 2014 GWP survey data. The severity
parameters in Table 2 can be used as an interval-level measureof severity of food insecurity in analyses such as regression andcorrelation that require an interval-level measure. (Raw scoreis ordinal, but not interval, and is not suitable for regression
or correlation analysis.) An alternative, if food insecurity is
an independent variable, is to use a set of dummy variables
to indicate either raw score or raw-score-based categories.
This allows for a more flexible fit, since associations of many
outcomes with food insecurity may not be linear.

COMPARABILITY OF FIES-BASED RESULTS IN THE
INTERNATIONAL MEDICAL CORPS DATA WITH
NATIONAL AND GLOBAL RESULTS FROM OTHERSURVEYS USING THE SAME INSTRUMENT
Methods to assess the extent to which the measured severityof food insecurity of individuals and the prevalence of foodinsecurity at specified levels of severity in the International
Medical Corps survey are comparable with corresponding
statistics from other surveys using the same instrument are
based on the following assumptions:Finally, we examine the Rasch reliability statistic as anindication of overall model fit. Rasch reliability is, conceptually,
the proportion of total variance of severity of food insecurity
in the sample (actually, in the sample omitting raw scores
0 and 8) that is accounted for by the measure (i.e., by thedifference in raw scores of respondents). Rasch reliability of
the International Medical Corps data was .74. A second versionof Rasch reliability, useful for comparing across surveys using
the same scale, weights all raw scores equally rather than by
the number of cases in each raw score. This variant of Raschreliability for the International Medical Corps scale is .73. (Thislatter measure is used within the VoH project to compare model
fit across countries, since the “true” Rasch reliability is affectedboth by model fit and by the distribution of cases across raw
scores.) For a measure of 8 items, .74 indicates reasonably
good reliability, and is slightly better than the reliability for the
GWP 2014 Zimbabwe data (.72). Higher reliability is expected
in a more homogeneous population, but the reliability in the

1. The corresponding items in the various surveys areintended to register the same objective conditions.
2. The same objective conditions are expected to indicate
similar levels of severity of food insecurity in all populations.
3. In principle, this would result in the same difference inseverity of each pair of items in all surveys.
4. However, in practice, the severity of items that are intended
to mean the same thing may differ somewhat among surveys
due to differences in nuance of translation and differences in
how food insecurity is experienced and managed in different
20cultures. Furthermore, the severity of one or more items may
differ substantially between any two surveys for the same
reasons.

With this in mind, I compared the International Medical Corps
scale with the scale based on the GWP 2014 Zimbabwe data.
Figure 1 shows the comparison of item parameters after two
iterations in which first WORRIED and then SKIPPED MEALS
were specified as unique. The greater severity of WORRIED in
the International Medical Corps survey indicates that girls in thatsurvey were less likely to report this condition than respondents
in the GWP Zimbabwe survey, given their responses to otheritems. The opposite is true for SKIPPED MEALS. With these
two items unique, the correlation among the remaining (i.e.,common) item parameters was .94 (analysis not shown), andthe standard deviation of the parameters for the common items
was 1.37 times as high for the International Medical Corps
survey as for the GWP survey (analysis not shown). The higher
standard deviation indicates higher average item discrimination
and, thus, moderately better model fit.

5. The extent of consistency of responses to items relative totheir severity may differ from survey to survey. Inconsistencyof response patterns introduces statistical noise, which
affects the dispersion of items (measured by differences inthe standard deviation of item severity parameters.)
6. And (a technical detail), Rasch-based scales areindeterminate with respect to location, meaning that they
have no natural zero point. (I.e., they are interval measures,
but not ratio measures.) Thus, adding or subtracting a
constant to all item parameters leaves the scale unchanged.
Given these assumptions, scales from two surveys areadjusted to a common metric (usually the metric of one of thetwo surveys—or, in the VoH project, the metric of the global
standard, which is based on results from about 147 countries)
using the following general protocol:

The differences between these scales are somewhat larger thanI expect for a subpopulation. To explore two possible reasonsfor the differences, I compared the International Medical Corps
scale with scales calculated for two subpopulations in the GWP
that would more nearly resemble the International Medical
Corps sample: those interviewed in Ndebele, and females ages
15-20 (analyses not shown). Scales from both GWP subsamples
were somewhat more consistent with the International Medical
Corps scale than was the overall Zimbabwe GWP sample (abit more-so for the females ages 15-20.) But the improvements
were not dramatic. It may also be the case that the inclusionof 13- and 14-year-olds in the International Medical Corps
could explain part of the difference, although I did not test thishypothesis.

1. Item parameters of the second scale are adjusted by a linear
transformation calculated to equate the mean and standard
deviation of item parameters to those of the first scale. The
additive constant is unimportant given point 6 above. The
multiplicative constant in the linear transform adjusts forthe difference in dispersion of items, which (point 5 above)is assumed to reflect differences in the extent of statisticalnoise in the two surveys. This difference does have meaning
and importance as it reflects differences in average item
discrimination, which, in turn affects adjusted measurement
error in a later process.

Table 1. Item parameters and fit statistics, Zimbabwe IMC
survey of adolescent girls

2. Adjusted item parameters for scale 2 are compared with theparameters for scale 1, typically using a scatterplot.
3. If an item is obviously an outlier in terms of difference
between the surveys, that item is declared “unique,” and steps
1 and 2 are repeated with the linear transformation recalculated
to equate the mean and standard deviation of the remaining(“common”) items in the two scales. This iteration is repeated
if necessary until the remaining common items are within
acceptable limits of being equal.
4. The respondent parameters are then adjusted by the same
linear transformation as in the final iteration and the respondent
error is adjusted by the multiplicative constant in that linear
transform. These adjusted respondent parameters and errors
are then on the same metric as scale 1 and provide the bridgefor comparing severity of respondents and prevalence rates
between the two surveys.
Note that “unique” items are retained within each scale forcalculating raw score, but they are not used to adjust thetwo scales to a common metric, since they are considered torepresent different objective conditions.
In addition to the possible interest in establishing equivalenceof the scale across surveys, it is also of interest to know how
consistently the scale “works” across subpopulations within acountry. Stability across subpopulations is a desirable property
in a measure.

Item1

Severity
parameter

Error

Infit

OutfitWorried food would run out

-0.16

0.144

1.07

1.22

Could not afford healthynutritious meals

-1.61

0.158

0.99

0.84

Ate only a few kinds of food

-1.57

0.157

0.96

01.21

Skipped meals

-0.55

0.146

0.97

0.97

Ate less than should

-0.48

0.145

0.84

0.89

Household ran out of food

0.83

0.148

1.01

1.06

Hungry and did not eat

0.32

0.144

0.96

0.97

Did not eat for whole day

3.22

0.225

1.05

1.34

Mean

0.00

Standard deviation

1.55

N²

344

I also adjusted the International Medical Corps data to the
VoH global standard, which provided the food security
classifications in Table 2. Similar adjustment for the overall
Zimbabwe GWP data indicates that for those data, raw score 4
should be considered marginally secure (or marginally insecure,depending on your labeling preference) rather than moderately
food insecure. Thus, raw scores at this level are not directlycomparable between the International Medical Corps and GWP
21

Zimbabwe data, but classifications are nearly comparable if therange for moderate food insecurity is specified as 5-7 for the
GWP data and 4-7 for the International Medical Corps data.
In both cases, raw score 8 is a good proxy for severe foodinsecurity. (This information is provided in case research using
the two data sources is contemplated after release of the GWP
data.)

Figure 1
COMPARISON OF ITEM SEVERITY PARAMETERS, ZIMBABWE
ADOLESCENT GIRLS (IMC) VERSUS ZIMBABWE GALLUP WORLDPOLL 2014 (GWP)
3Whole day2

Notes:
1Full wording of each question included additional detail, areminder of the 12-month reference period, and the specificationthat the behavior or condition occurred “because there was notenough money or other resources to get food.”1
Ran out of food0-1

Measurement Provisional food security
error1status²

03

-2.32

1.50

1

-2.50

1.12

2

-1.53

0.89

3

-0.80

0.82

4

-0.14

0.81

5

0.55

0.86

6

1.40

1.00

7

2.71

1.32

83

3.78

1.66

Few kinds food

Healthy-3-3-2

Equivalent item

Table 2. Respondent parameters and measurement errors in
the Zimbabwe IMC survey of adolescent girls
Severity
parameter

HungrySkipped meals-2²Respondents who responded “no” to all 8 questions (n=233)
or “yes” to all 8 questions (n=108) were omitted from thepsychometric analysis. They will be included in substantive
analysis, classified as being very food secure and very
food insecure, respectively, but their responses provide no
information about the relative severity of items.

Raw
score

WorriedAte less

Food secure
Marginally food secure/marginally food insecure

Moderately food insecure

Severly food insecure

Notes:
1Measurement error can be thought of as the standard
deviation (around the severity parameter—which is the mean
severity within the raw score) of true severity of food insecurityof respondents represented by the sampled individual.
²Provisional food security status is based on the thresholds
used by the Voices of the Hungry project to classify respondents
in the Gallup World Poll. Those thresholds are used withprobabilistic assessment to estimate national prevalence rates
after adjusting each country’s scale to the global standard. The
raw-score assignment indicated here most nearly approximates
the prevalence rates calculated by adjusting the IMC scale to
the global standard for 2014.
3Severity parameters and measurement error cannot becalculated for raw scores 0 and 8 using the conditional maximum
likelihood methods used in this analysis. Rough approximations
presented here are based on pseudo-raw-scores of 0.5 and
7.5.

22

-1

0
1
Severity parameter, GWP

Unique item

2

Equal severity

3