2ª Calle 20-92, Zona 11 Col. El Mirador 1, 01011 Mobile.:(502) 5202 1982 Home: (502) 2472 8501
Guatemala, Guatemala E-mail: jmatute@bigfoot.com
Jorge Matute, October 2011
Title II Food Security Program 
 SHARE 
 
MYAP 2006-2011 
Final Evaluation Report 
Final Evaluation MYAP 2011 
Executive Summary 
i
Asociación SHARE Guatemala (SHARE) hired the consulting company of JMatute-CIENSA to carry out the 
final evaluation for the Title II Improved Food Security Program (IFSP) (MYAP 2006-2011). 
I.1 Program Background 
SHARE Guatemala is a Guatemalan organization whose mission is to promote participative 
and sustainable development opportunities, as well as provide emergency assistance, so 
that the most vulnerable populations are able to improve their quality of life. SHARE was 
legally established in 1987, and since then has implemented various programs in several of 
the nation’s departments.
Child malnutrition is one of Guatemala’s most serious and chronic problems. In rural areas,
51.8%1
 of children under five suffer from chronic malnutrition. Of these, 64.8%1 live in 
Guatemala’s north-western region. SHARE currently implements the Improved Food Security 
(IFS) Program, a Title II Multi-Year Assistance Program launched on October 1, 2006, and 
officially ending on September 30, 2011. This program aims to promote development 
initiatives, offering various services to improve food security for vulnerable families in rural 
areas in the departments of Huehuetenango and Chimaltenango. 
The general objective of the IFS Program is to improve food security for highly vulnerable 
Guatemalan families in rural areas. 
SHARE Guatemala is certified to manage United States government funding for the 
development of this program. 
The findings of this evaluation show highly positive changes in chronic malnutrition rates in 
children under five. While this evaluation cannot demonstrate the program’s causality, it 
can shed light on the effects it has had on participating communities. It is also worth noting 
that SHARE complimentarily implemented the Emergency Assistance Program (SYAP 2009-
2010). SHARE was awarded additional funding to be implemented throughout 2010 in order 
 
1
 ENSMI 2008-2009. NCHS standards = 51.8% / WHO standards = 49.8% 
Final Evaluation MYAP 2011 
Executive Summary 
ii
to compliment the IFS Program in the face of the deteriorated food security situation and to 
mitigate the effects of intermittent draught and rains throughout these years. 
The calculations for the sample size to be used in this study were based on the parameters described in 
this section, and are also described in this study’s design document. Calculations were made following 
FANTA II instructions. The sample size used in the study was calculated according to estimates of chronic 
malnutrition rates in children under five (children whose height for age falls below minus two standard 
deviations). The calculated sample size was of 1,162 children under five, to be found in a sample of 775 
homes, distributed among 31 communities (or clusters). The sampling design is stratified by the 
geographic location of the communities by municipality, and by the presence of the Program’s 
agricultural and livestock farming interventions. As such, out of a total 15 strata, two clusters 
(communities) were selected from each, using random and PPS sampling (selection probability 
proportional to size). The exception was stratum 10, out of which three clusters were selected (see table 
1). 
Data gathering in the field was carried out using the data collection instruments or ballots agreed to by
the three PVOs in the MYAP consortium. In the field, internal and external quality control methods were 
implemented. The consultant monitored the process internally by including “editors” in the field team. 
The main function of these editors was to review each of the instruments or ballots collected in the field 
while still in the communities. This step helped to catch any errors made by the surveyors, and the few 
inconsistencies were corrected in a timely manner. The rest of the internal monitoring was left to each 
respective supervisor in the three teams of surveyors. SHARE performed the external monitoring with 
the participation of their Monitoring and Evaluation unit, as well as participation of staff from the 
Program’s Health and Nutrition and Agriculture/Livestock initiatives. Community facilitators also closely 
monitored the proceedings. External monitoring also contributed to correcting systematic errors during 
interviews. SHARE staff participation also aided in providing timely translation when necessary. 
Final Evaluation MYAP 2011 
Executive Summary 
iii
Table 1: Sampling Design Strata 
Stratum
#
Health and 
Nutrition 
Intervention2
Agricultural 
Intervention Municipality Department
YES NO YES NO
1
X
X
Santa Barbara
Huehuetenango
2 X X Nenton
3 X X
4 X X San Antonio 
Huista / 
Concepción 
Huista 5
X
X
6 X X Aguacatan
7 X X
8 X X Todos Santos 
Cuchumatan 9
X
X
10 X
X
Chiantla
11 X X San Martin 
Jilotepeque
Chimaltenango
12 X
X
13 X X Tecpan
14 X X
15
X
X
San Juan 
Comalapa
Field surveying resulted in 769 completed interviews. A total of 1,046 children were anthropometrically 
measured, given that every child in each family was evaluated. 
With the exception of the anthropometric indicators used to evaluate the children, all other indicators 
relevant to health, nutrition and agriculture were evaluated in the 769 interviews. The other exception 
pertains to the indicators in the commercial intervention, which were measured using a sub-sample of 
the participants in these activities. The reasoning behind this was that these activities were not 
considered to have population-wide effects. As such, it was decided (with FANTA approval) to measure 
the effects on actual participants from the communities selected for the study. 
 
2 Health and Nutrition interventions are carried out in all of the communities in the program coverage area, while 
agricultural and livestock interventions are carried out in a percentage of the total coverage area. 
Final Evaluation MYAP 2011 
Executive Summary 
iv
The information was entered into the computer using a double data entry method with EPI INFO 
software. This double entry was validated to correct for typing errors until an error-free data base could 
be ensured. Statistical analysis took the sampling design into account, using EPI INFO’s CSAMPLE analysis 
module that performs calculations based on stratification and cluster selection. This analysis required 
the calculation of a variable to weight the observations against the probability of selection. This aided in 
ensuring that all of the observations had a similar probability of selection. 
Final Evaluation MYAP 2011 
Executive Summary 
v
III.A MYAP Indicators 
Table III.A.1 MYAP Indicators and their goals 
Thematic Area Code
3
Indicators
Baseline 
value GOAL
2011 Percentage
(Confidence Interval. 
95%)
Anthropometrics 
in children under 
5 years
1a
Percentage of children aged 6 to 59.99 months with <2.0
SD height for age, NCHS 69% 66%
62.5%
(55.9, 69.0)
1a
Percentage of children aged under 5 with <2.0SD height 
for age, NCHS 64% 61% 57.2%
(51.2, 63.1)
1b Percentage of children aged under 5 with <2.0DS height 
for age, WHO 69% N/A 65.8%
(60.3, 70.2)
2a
Percentage of children aged 0 to 59.99 months with <2.0 
SD weight for age, NCHS 35% 30% 29.1%
( 24.8, 33.5)
2b Percentage of children aged 0 to 59.99 months with <2.0 
SD weight for age, WHO 28% N/A4 22.2% 
(18.7, 25.7)
Anthropometrics 
in children under 
36 months
2a
Percentage of children aged 0 to 35.99 months with <2.0 
SD weight for age, NCHS 35% 28% 26.7%
(21.7, 31.8)
2b Percentage of children aged 0 to 35.99 months with <2.0 
SD weight for age, WHO 27% N/A4 18.7% 
( 15.2, 22.1)
Household dietary 
diversity and food 
scarcity in the 
household 
4
Number of food groups consumed in the household in the 
preceding 24 hours. 
4 
Food 
groups
6
Food 
groups
7.3
Food groups
(7.1, 7.4)
5
Average number of months out of the year with adequate 
provisions of food in the household.
11
months
11
months
11.0 months
(10.8,11.2)
Child feeding 8
Percentage of infants aged 0 to 5.99 months who have 
been exclusively breastfed in the preceding 24 hours. 71% 77% 74.7%
(64.4, 85.0)
Warning signs of 
childhood illness.
18
Percentage of mothers and caregivers with children aged 0 
to 35.99 months who recognize at least two warning signs 
of childhood illness that indicate the need to seek health 
services. 
36% 50%
75.4%
(70.1,80.8)
Maternal health 
and neonatal 
warning signs.
12
Percentage of mothers with children aged 0 to 35.99 
months who recognize at least two warning signs in 
pregnancy that indicate the need to seek health services. 
13% 34%
71.3%
(65.0,77.6)
15
Percentage of mothers with children aged 0 to 35.99 
months who recognize at least two neonatal warning signs 
(<28 days) that indicate the need to seek health services. 
15% 35%
61.1%
(53.8,68.5)
Agricultural and 
livestock farming 
practices
22
Percentage of farmers who adopt at least two improved 
agricultural practices. 18% 23% 30.9% (25.5, 36.3)
23
Percentage of farmers who adopt at least two improved 
livestock practices 9% 14% 42.0% 
(35.5, 58.5)
Income 
improvement 30
Percentage of farmers who adopt at least two improved 
formal marketing practices 17% 22% 86.7%
(71.4, 100)
 
3
Codification of the variables subject to research 
Final Evaluation MYAP 2011 
Executive Summary 
vi
Thematic Area Code
3
Indicators
Baseline 
value GOAL
2011 Percentage
(Confidence Interval. 
95%)
(Not comparable to 
the baseline)
Local capacity 
building 31
Number of communities with functioning early warning 
systems for Food and Nutritional Security 0 84 72*
(48, 93)
* According to SHARE’s monitoring system information the exact number of communities is 91. 
Table III.A.1 illustrates that the populations within SHARE’s MYAP coverage area now present a different 
situation than before the program. The proposed goals have been met, with the exception of the 
exclusive breastfeeding indicator. 
Results that directly affect children’s health: 
A 7% reduction from the baseline in chronic malnutrition rates in children under five (Z < -2SD 
height/age) by NCHS standards (from 69% to 62% (P<0.05)). 
A 5.9% reduction from the baseline in general malnutrition rates in children under five (Z < -2SD 
weight/age) by NCHS standards (from 35% to 29.1% (P<0.05)). 
An 8.3% reduction in general malnutrition rates in children under 36 months (Z < -2SD 
weight/age) by NCHS standards (from 35% in the baseline to 26.7% in the final evaluation). 
Values are based on NCHS standards. It is worth noting that the differences are still in evidence by WHO 
standards. 
Final Evaluation MYAP 2011 
Executive Summary 
vii
Malnutrition in the final and baseline evaluations 
Dietary diversity was clearly increased from the baseline value, from an average consumption of 
four food groups to an average of 7.3 groups, resulting as well in exceeding the established goal 
of six groups (P<0.05). The average number of months with adequate food provisions was 11 
months, a similar value to the baseline and to the proposed goal. 
Recognition of warning signs in pregnant women, neonatal infants and children far exceeded baseline 
values, and as such also exceeded the proposed goals (P<0.05). The percentage of women who acquired 
knowledge of warning signs easily doubled or even quadrupled baseline values, and as such now: 
71.3% of women recognize warning signs in pregnancy; 
61.1% recognize neonatal warning signs, and 
75.4% recognize warning signs of childhood illness. 
Among the women who mentioned recognizing some warning signs in both pregnancy and infants and 
children, a percentage of them (around 50%) also mentioned having suffered at least one warning sign, 
0%
10%
20%
30%
40%
50%
60%
70%
NCHS%
children under
5 with chronic
malnutrition
WHO%
children under
5 with chronic
malnutrition
NCHS%
children under
5 with general
malnutrion
WHO%
children under
5 with general
malnutrition
NCHS%
children under
3 with general
malnutrition
WHO%
children under
3 with general
malnutrition
Baseline
Final
Final Evaluation MYAP 2011 
Executive Summary 
viii
either in pregnancy or with one of their children. It is relevant to note that almost all of them (over 95%) 
sought assistance with qualified service providers (hospitals, health centers/posts, or private clinics). 
Given that the study design and sample size were calculated in order to measure chronic malnutrition as 
the main indicator, the measure of the other indicators was necessarily subject to the sampling 
calculated for the main objective. For most of the indicators, this sample size worked perfectly. 
However, in the case of the exclusive breastfeeding indicator, the target population is children under 6 
months, which constitutes a very small subset of the total population of children under 5. Likewise, the 
sample obtained to measure this indicator was also too small. This resulted in obtaining data with too 
high a margin of error. As such, as perhaps could be expected, the results obtained for exclusive 
breastfeeding do not demonstrate a significant change from the baseline, because of the small sample 
that was obtained. However, the value recorded is significantly higher than the national average in rural 
areas (ENSMI 2008-2009, 60.4%). The recommended age to begin complimentary feeding in children is 6 
months, and the study found that 87.1% of the women surveyed implemented this good practice. 
The microbiological quality of water is important to staying healthy. 
96.5% of families treat their drinking water in some way. Of these, 
93.9% boil their water, 
17.6% filter their water, 
6% use the SODIS method, and 
1.3% use chlorine. 
Agricultural and livestock practices have also improved from the baseline, and these indicators also 
exceeded the proposed goals (P<0.05). 
Now, 30.9% of agricultural farmers implement improved agricultural practices, and 
42% of livestock farmers implement improved practices. 
With regards to the implementation of at least two practices in formal marketing, the baseline found 
that 17% of farmers implemented these measures. Accordingly, a goal of 22% was established for this 
Final Evaluation MYAP 2011 
Executive Summary 
ix
indicator. SHARE developed this initiative with a small number of farmers, around 500 individuals, and 
contemplated a small amount of advocacy among participating populations. As such, the sample for this 
indicator is a sub-sample of the evaluation sample4
 that is nonetheless still representative due to the 
random sampling of communities. In this case, a sample of 43 participants was surveyed, yielding the 
following information regarding the program’s achievements: 
86.7% of those surveyed adopted at least two formal marketing practices 
This percentage among the total participating population is at least 71.4%. 
In the area of Local Capacity Building (Risk Management), SHARE has met the goal of providing 84 
communities with an early warning and alert system for potential food insecurity. The three sentinel 
sites evaluated demonstrate community leaders’ effective performance with regards to risk 
management training, managing the community monitoring bulletin board, use of the respective 
notebook, and use of the rainwater gauge, all relevant to the performance of the Monitoring Systems 
and Early Warning for Food and Nutritional Security. Further, according to SHARE’s monitoring and 
evaluation system, 91 communities are now monitored by 12 sentinel sites. 
 
4
 FANTA and the three PVOs: SHARE, Save the Children, and CRS, agreed in meetings held in July 2011, that the 
measure of this indicator would be carried out using a sub-sample of participants, and not using an entire 
population sample, which was used to measure the other indicators. 
MYAP 2011 Final Evaluation 
I Introduction .............................................................................................................................. 1
I.1 Background of the organization (PVO): .............................................................................. 1
I.2 Justification and study objectives. ...................................................................................... 5
1.3 Program Indicators ............................................................................................................. 6
II Methodology ............................................................................................................................ 7
I. Study design .......................................................................................................................... 7
I.1 Sample Size ...................................................................................................................... 7
Selection of study subjects (children under five) ...................................................................12
I.2 Sampling Design (sample selection) ..............................................................................12
I.3 List of selected clusters / communities .........................................................................14
Clusters M2: Selected and visited community clusters .........................................................14
II. Updating and Adapting the Data Collection Instruments ..................................................15
III. Field Staff Selection and Training. .....................................................................................17
III.1 Field staff selection and integration............................................................................17
III.2 Training and standardization ......................................................................................17
IV. The Field Study ..................................................................................................................19
IV. 1 Field work phase ........................................................................................................19
A. Introductions and requests for community cooperation .............................................19
B. Survey team management ............................................................................................19
C. Linguistic Aspects ..........................................................................................................20
D. Field information management ....................................................................................20
IV.2 Quality control in the field ..........................................................................................21
IV.3 Results of the Evaluation............................................................................................21
IV.3.1. Health and Nutrition and Agriculture and Livestock Interventions ....................................21
IV.3.2. Micro-Business Development Intervention ........................................................................ 23
IV.3.3. Capacity Building (Risk Management) ................................................................................23
V Processing, data analysis and report preparation .............................................................24
III Results ....................................................................................................................................26
III.A MYAP Indicators .......................................................................................................28
Graph 1: Malnutrition in the final and baseline evaluations .........................................3030
III.B 2011 Results. ...............................................................................................................32
III.B.1 Anthropometrics in children under 5 ......................................................................32
Graph 2: Malnutrition prevalence in the study ...............................................................344 
Graph 2a: malnutrition prevalence found in this study, compared to the 2009 ENSMI . 355 
III.B.2 Family dietary diversity and family food scarcity ..................................................366 
Graph 3: Average Dietary Diversity Scores ......................................................................377 
 MYAP 2011 Final Evaluation 
xi
Graph 4: Scarce foods and reasons for scarcity ................................................................. 37
Graph 5: Food group consumed............................................¡Error! Marcador no definido.
III.B.3 Information, education and communication in health and nutrition ...................399 
Graph 6: Information, education and communication in health and nutrition .................40
III.B.4 Child Feeding ..........................................................................................................411 
Graph 7: Child Feeding .....................................................................................................422 
III.B.5 Warning signs in maternal, neonatal and children’s health ..................................423 
Graph 8: Knowledge of warning signs in pregnancy, neonatal and children’s health.....444 
III.B.6 Water Treatment ...................................................................................................455 
III.B.7 Agricultural and Livestock Practices.......................................................................466 
Graph 9: Agricultural and Livestock Practices ..................................................................488 
III.B.8 Income Improvement (Formal Marketing) ..............................................................50
Graph 10: Formal Marketing Practices ............................................................................500 
III.B.9 Capacity Building (Risk Management) ...................................................................511 
IV Conclusions ...........................................................................................................................533 
V Annexes ................................................................................................................................545 
ANNEX 1: III.C Detailed 2011 Results. ................................................................................55
III.C.1 Anthropometrics in children under five: ................................................................556 
III.C.2 Family Dietary Diversity and Family Food Scarcity ................................................599 
III.C.3 Information, education and communication in health and nutrition ...................633 
III.C.4 Child Feeding ..........................................................................................................655 
III.C.5 Warning signs in maternal, neonatal and children’s health ..................................666 
III.C.6 Water treatment ......................................................................................................69
III.C.7 Agricultural and Livestock Practices .........................................................................70
III.B.8 Income Improvement (Formal Marketing) ..............................................................73
III.B.9 Community Risk .......................................................................................................75
ANNEX 2: III.D Design Effect on MYAP 2011 Indicators ......................................................78
 MYAP 2011 Final Evaluation 
xii
COCODES Community Development Councils
CRS Catholic Relief Services
ENSMI National Maternal Child Health Survey
FANTA Food and Nutrition Technical Assistance
CI SHARE Cooperating Institutions
MSPAS Ministry of Public Health and Social Welfare
MYAP Multi Year Assistance Program
NCHS National Center for Health Statistics
Odds Ratio Statistical measure describing the strength of association between
illness and exposure to a factor
WHO World Health Organization
PPS sampling Probability Proportional to Size Sampling
PVO Private Voluntary Organization
IFS Improved Food Security
STC Save the Children
USAID United States Agency for International Development
MYAP 2011 Final Evaluation 
Introduction 
1
Asociación SHARE Guatemala (SHARE) hired the consulting company of JMatute-CIENSA to carry out the 
final evaluation for the Title II Improved Food Security Program (IFSP) (MYAP 2006-2011). The results 
of the study are presented in this document. 
I.1 Background of the organization (PVO): 
SHARE Guatemala is a Guatemalan organization whose mission is to promote 
participative and sustainable development opportunities, as well as provide emergency 
assistance, so that the most vulnerable populations are able to improve their quality of 
life. SHARE was legally established in 1987, and is an international non-profit 
organization without political or religious affiliation, headquartered in Guatemala. 
Over its 24 years of work, SHARE has implemented various programs and projects in 
different regions and departments of Guatemala in order to promote sustainable 
development, focusing on areas with greater vulnerability. One such program currently 
in implementation is the Improved Food Security (IFS) Program, a Title II Multi Year 
Assistance Program (MYAP), approved for implementation from 2006-2011. 
 
MYAP 2011 Final Evaluation 
Introduction 
2
IMPROVED FOOD SECURITY PROGRAM BACKGROUND: 
Child malnutrition is one of Guatemala’s most serious and chronic problems. In rural areas, 
51.8%5
 of children under five suffer from chronic malnutrition. Of these, 64.8% live in 
Guatemala’s north-western region. The IFS Program currently in implementation was launched 
on October 1, 2006, and officially ends on September 30, 2011. This program aims to promote 
development initiatives, offering various services to improve food security for vulnerable 
families in rural areas in the departments of Huehuetenango and Chimaltenango. 
GENERAL OBJECTIVE: 
The general objective of the IFS Program is to improve food security for highly vulnerable 
Guatemalan families in rural areas. 
STRATEGIC OBJECTIVES: 
1. Improve the health and nutrition of breastfeeding mothers, children aged 0-36 
months and pregnant women. 
2. Improve family food production, income and resource management. 
3. Strengthen community capacities to manage their own development. 
4. Promote basic community infrastructure. 
From its launch on October 1, 2006 through its end on September 30, 2011, the program 
has sought to improve food security by improving four main axes: 
1. Food access 
2. Food availability 
3. Food utilization 
4. Risk Management 
 
5
 ENSMI 2008-2009. NCHS standards = 51.8% / WHO standards = 49.8% 
MYAP 2011 Final Evaluation 
Introduction 
3
IFS Program Interventions and Services: 
Each of the above mentioned axes entail specific interventions and each intervention 
provides a series of services to the beneficiary population. 
The program has been designed to provide participating families with every possible 
opportunity to improve their food security. The objective population is comprised 
mainly of women, who transfer the benefits of the services they receive directly to their 
families. However, the target population varies in each intervention, depending on the 
nature of the activities therein. 
Geographic Area: 
The program is implemented in seven municipalities in the department of 
Huehuetenango and in three municipalities in the department of Chimaltenango. These 
have been deemed priority municipalities, as they share the following characteristics: 
They are included in the list compiled by the President’s Secretariat for 
Planning and Programming (SEGEPLAN), as one of the 70 secondary priority 
municipalities to receive development aid (2005). 
Their chronic malnutrition indicators are higher than 56.5%. 
Their poverty indicators exceed 57%. 
IFS Implementation: 
The program has been implemented with a self-help strategy. There are differences in 
the working methods of each of the interventions, as well as in the development 
context of each municipality, and even among the target populations. Given these 
unique contexts, the program design devised two different implementation strategies: 
Implementation through Local Partners: 
SHARE partners with local organizations called Cooperating Institutions (CIs). These are 
provided with financing, trainings in technologies and technical assistance. CIs 
implement the IFS Program directly with a specified organizational structure. They 
organize and train the community staff members that then provide direct services to 
participating families. In this process, families are organized into interest groups, who 
then participate in activities designed to strengthen organizational capacities and 
MYAP 2011 Final Evaluation 
Introduction 
4
increase their own capacities for development. The program coordinates closely with 
the Ministry of Public Health and Social Welfare (MSPAS). 
This strategy is applied to the following interventions: 
Food Security Risk Management 
Health and Nutrition 
Food Production 
Food Provision 
Capacity building processes are planned, organized and evaluated in conjunction with 
CIs, following a cascade methodology defined by the general IFS Program strategy: 
From SHARE headquarters to regional offices 
From regional offices to municipal / CI offices 
From municipal/ CI offices to community staff 
From community staff to participating families 
Direct Implementation Model: 
 In this model, each intervention has a specialized technical team responsible for 
strengthening participants’ organization, providing technical assistance, monitoring 
implementation and transferring the required resources for each service. 
This model is applied to the interventions in: 
Sanitation and access infrastructure 
Village Banking 
Micro-business development 
SHARE Guatemala is certified to manage United States government funding for the 
development of this program. 
MYAP 2011 Final Evaluation 
Introduction 
5
I.2 Justification and study objectives 
The program and the results attained therein must be evaluated in the months 
preceding the program’s closure. In addition, it is important to determine the 
effectiveness of the program’s implemented strategies and operative processes, given 
that human development processes are dynamic and influenced by internal and 
external factors. 
1. OBJECTIVES OF THE EVALUATION: 
As part of any planning process, an evaluation responds to the need to place a value on 
attained results and to identify any factors that have hindered the accomplishment of 
proposed objectives, in order to improve future planning. 
Thus, the objective of this study is to evaluate the results obtained by the Improved 
Food Security Program in order to determine the effects and achievements to date. The 
evaluation will focus on evaluating the consistency of the program’s strategic design in 
its approach to improving nutritional status, as well as the progress in attaining the 
proposed goals (its effect and impact indicators). 
Specific Objectives: 
1. Compare the results achieved to the proposed goals and objectives (efficacy). 
SHARE hired an external consulting team to meet the evaluation’s proposed objective, in accordance 
with Food for Peace guidance for Title II program evaluations. This helps to ensure that the results and 
findings of the study are objective and transparent. 
This document presents the findings of the study led by the consulting team. The results presented 
respond to the evaluation’s specific objective, and provide SHARE with valuable information. 
MYAP 2011 Final Evaluation 
Introduction 
6
1.3 Program Indicators 
SHARE presented the following indicators for its approved MYAP, to allow the evaluation to determine 
the scope of the program’s achievements: 
Thematic Area Indicators
Anthropometrics in 
children under 5 years
Percentage of children aged 6 to 59.99 months with <2.0 SD height for age, NCHS
Percentage of children aged 0 to 59.99 months with <2.0 SD height for age, WHO 
Percentage of children aged 0 to 59.99 months with <2.0 SD weight for age, NCHS
Percentage of children aged 0 to 59.99 months with <2.0 SD weight for age, WHO 
Anthropometrics in 
children under 36 
months
Percentage of children aged 0 to 35.99 months with <2.0 SD weight for age, NCHS
Percentage of children aged 0 to 35.99 months with <2.0 SD weight for age, WHO
Household dietary 
diversity and food 
scarcity in the 
household
Number of food groups consumed in the household in the preceding 24 hours. 
Average number of months out of the year with adequate provisions of food in the household.
Child feeding Percentage of infants aged 0 to 5.99 months who have been exclusively breastfed in the 
preceding 24 hours. 
Warning signs of 
childhood illness.
Percentage of mothers and caregivers with children aged 0 to 35.99 months who recognize at 
least two warning signs of childhood illness that indicate the need to seek health services.
Maternal health and 
neonatal warning signs.
Percentage of mothers with children aged 0 to 35.99 months who recognize at least two warning 
signs in pregnancy that indicate the need to seek health services. 
Percentage of mothers with children aged 0 to 35.99 months who recognize at least two neonatal 
warning signs (<28 days) that indicate the need to seek health services. 
Agricultural and 
livestock practices
Percentage of farmers who adopt at least two improved agricultural practices. 
Percentage of farmers who adopt at least two improved livestock practices
Income improvement Percentage of farmers who adopt at least two improved formal marketing practices
Local capacity building Number of communities with functioning early warning systems for Food and Nutritional Security 
This evaluation used the same instruments as those created for the baseline to evaluate the 
achievement of the above indicators. However, for this final evaluation, they were subject to review and 
validation by the three Title II MYAP consortium PVOs, resulting in a very small number of adjustments. 
MYAP 2011 Final Evaluation 
Methodology 
7
This evaluation was implemented in five important phases: 
1. Study design 
2. Updating and adaptation of the instruments used to gather data 
3. Field staff selection and training 
4. Field work and data input 
5. Information analysis and report preparation 
I. Study design
The study design process was carried out by a different consulting team6
. On that occasion, the design 
responded to the needs of all three MYAPs, including Save the Children, SHARE and CRS. The sampling 
design presented then was supervised and approved by FANTA II. This section provides a summary of 
that design. 
I.1 Sample Size 
SAMPLING METHOD 
The recommended sampling method was a combination of stratification and cluster sampling. The 
community sampling frame was stratified by its exposure to agricultural and micro business 
development activities. 
First level of stratification: Geo-political. The 10 participating municipalities in the program. 
Second level of stratification: Farming/agricultural activity in the program. In accordance with a 
meeting on June 10 with FANTA, USAID and the PVOs, the sample must be stratified according to 
agricultural participation. As such, each of the geo-political strata should state: 
o With agricultural activity / Without agricultural activity 
 
6
 Consulting team developed by Jorge Matute; contracted by CRS, SHARE and Save the Children, with the objective 
of designing the sampling of the MYAP final evaluation. The design followed FANTA guidelines, who also reviewed 
and approved the design document. Jorge Matute also prepared the document to design the sampling of the 
baseline in 2007-2008.
MYAP 2011 Final Evaluation 
Methodology 
8
The groups were distributed proportionally among the strata. Sampling within each stratum was 
comprised of three sampling stages. PPS sampling was used in the first stage to select the communities, 
simple or systematic random sampling was used in the second stage to select homes within the 
previously selected communities, and simple random sampling was used to select the family within the 
home in the third stage. 
Cluster sampling in three phases was used to obtain the sample within each of the last level strata 
(municipalities-activities). 
First level of selection: Community. The community-cluster is a population group that 
resides in the same geo-political sector that is also quite homogenous. Community￾clusters refer to communities or human settlements known as villages, places, hamlets, 
towns, cities, etc. Community-clusters were selected using PPS Sampling. Community￾clusters correspond to the statistical concept known as primary clusters. 
Second selection level: Households. Within each of the community-clusters selected, 
random sampling was used to select households. This phase of selection took into 
consideration the only factor for inclusion in the sample: that the household contain 
children younger than five years of age. It is important to note that the field team 
documented the number of homes that comprised the sampling frame for each 
community-cluster, as well as the number of homes visited. 
Third selection level: Families. It was highly probable that a single household contain 
more than one family that met the afore-mentioned inclusion criteria. In such a case, 
one of the families was randomly selected. A family is defined by the concept of 
“nuclear family”, consisting of a mother, a father and their offspring7
. These families 
comprised the sampling units subject to measurement: the mother, father and any 
offspring under five. It was important to document the number of families that 
comprised the sampling frame for each home-cluster in the field. A total of 74 
 
7
 It is important to note that this final evaluation measured the data for a nuclear family, which slightly differed 
from the information used for the baseline, which was that of HOUSEHOLD. (The latter included the nuclear family 
as well as any other family member who eats from the same pot). 
MYAP 2011 Final Evaluation 
Methodology 
9
households contained more than one nuclear family that met the inclusion criteria, and 
as such one family in each of these was randomly selected for the study. 
It must be stressed that the selection process for clusters and sampling units was random. This ensured 
adequate representation as well as the evaluation’s external validity, making it possible to extrapolate 
the data to the population. 
DETERMINING THE SAMPLE SIZE 
In accordance with FANTA’s instructions, this design is an adaptation. As such, it uses the same sample 
size calculations in order to perform estimations (and not to prove the hypotheses). 
The sample size for a study such as this is defined by three basic standard parameters: variance, 
confidence level and the standard error expected in the estimations. 
Given that the sampling design is not simple random, the effects of the design on the variance should be 
added to the preceding parameters. This is known as “Design Effect”. FANTA has suggested using a value 
of “2” as the design effect8
. 
Another factor that influenced the sample size is the condition imposed to consider the total target 
population as finite. Finite is understood to be relatively small. In this case small is taken to mean a total 
population smaller than 5,000. However, for this design and given the populations in question, the 
population was instead considered to be infinite (greater than 5,000), both for the MYAP program as 
well as in the case of each of the three PVOs. As such, it was not necessary to make any adjustments for 
population size. 
The sample size required for the baseline was calculated considering the following: 
Confidence level: this was set at 95% (Z = 1.96). 
P (1-P): The study abided by FANTA’s recommendation of using the value of P (1-P) = 0.25. 
Design effect on sampling. The study used FANTA’s recommended value: 2 
Standard Error. The value selected for standard error was 4%. Given that the above values 
are constants in the equation, the standard error of measurement is what conditions the 
 
8
 Meeting with FANTA-2 and the MYAP PVOs, Guatemala, June 10, 2011 
MYAP 2011 Final Evaluation 
Methodology 
10
sample sizes in the end. In SHARE’s evaluation, sample sizes were calculated with a standard 
error of 4. 
Calculation of sample size in the target population of children under five: 
According to the baseline information, the selected households with children under five were found to 
have an average number of 1.5 children per household. Therefore, in order to find 1,163 children under 
five, it is necessary to visit: 
1,163/1.5 = 775 households with children under five. 
Given that at the time of gathering field data some families could reject being interviewed, or that there 
may be cause to rule out a given survey (or that losses may occur), the loss was considered in the 
calculation of the sample size in order to increase the selection and avoid the need for substitutions that 
could skew the sample, or the need to repeat the selection process. 
THE SELECTION PROCESS IN THE FIELD: 
The following procedure was used to find children under five within the communities: 
a. Household selection. Houses were randomly selected using maps or community 
diagrams. 
b. Case confirmation. Once a household was selected, the first step was to confirm 
that it met the inclusion criteria, which was that a child under five resided within. 
MYAP 2011 Final Evaluation 
Methodology 
11
Upon this confirmation, the team needed to establish whether or not there was 
more than one family with children under five within that household. In the case of 
the presence of two or more families who met this criterion, one of them was 
randomly selected. Once selected, the family was required to give informed consent 
to participate in the study. This whole process led to the possibility that the 
selection process could result in not finding a household with children under five, or 
that a selected family would choose not to participate. This loss was then defined as 
“loss for lack of response”. Given the decision to begin the selection within 
communities with households, the size of the sample to be selected within the 
communities refers to HOUSEHOLDS.
Loss for lack of response: This formula was provided by FANTA, and was used to adjust the necessary 
sample size according to the possibility of data loss in the field, especially due to selection of and visits 
to households without children under 5: 
Where lambda corresponds to the calculated factor as: 
Lambda = the average size of the families X the proportion of people in the target population (under 
five) = -(6 X 0.15) = -0.9 (values provided by FANTA at the June 10 meeting). 
Note: The baseline used a sample size adjusted for calculations of the number of community clusters 
sampled. The final evaluation used a non-adjusted sample size to establish the number of community 
clusters, in keeping with FANTA’s recommendation of making the adjustment within each community 
cluster. Therefore, the study planned to find 42 households in each community-cluster, rather than the 
25 that were used in the baseline. 
MYAP 2011 Final Evaluation 
Methodology 
12
Selection of study subjects (children under five)
Once the sampling unit (household) had been selected, it was likely to find more than one nuclear family 
(mother, father, and children) within it, resulting in more than one family applicable for study in the 
household. This made it necessary to define selection criteria for families. The team was also required to 
document the number of families living in the household and to specify that they formed part of the 
sampling frame of the household-cluster. The same inclusion criteria used in the selection of households 
could also be used for the selection of families within the household. The team need only document the 
situation and to select the family to be studied by performing a drawing among the families with 
children under five. 
 The MYAP Consortium and FANTA agreed that all children under five in a selected nuclear family 
should participate in evaluating Capacities, Attitudes and Practices (CAPs), as well as in anthropometric 
measurements. With regards to the former, the surveyor should ask questions pertaining to the 
expected CAPs and in accordance with the age of the children within the household. For instance, if 
there is a child under six months old, the surveyor should ask the question regarding exclusive 
breastfeeding for that child. If there is also a child aged 14 months, then the surveyor should ask the 
question referring to complimentary feeding for that child. 
I.2 Sampling Design (sample selection) 
The sampling design responds to the need to measure the impact indicator: Prevalence (in %) of children 
with low height for age (chronic malnutrition defined by the z-score: malnourished = Z < -2SD). To this 
end, the evaluation followed a design of stratified cluster sampling in three phases. 
The stratification here took into consideration two characteristics in the population groupings: 
The first consisted of the geo-political division of the country into municipalities. In this case, the 
communities subject to the SHARE evaluation are distributed among two departments and ten 
municipalities: 
o Huehuetenango: San Antonio Huista, Concepcion Huista, Todos Santos, Chiantla, Santa 
Barbara, and Aguacatan 
o Chimaltenango: Tecpan, Comalapa, and San Martin 
MYAP 2011 Final Evaluation 
Methodology 
13
The second consisted of the presence of the agricultural or farming intervention that the 
program implemented in some communities. As such, the groups are divided in two: those with 
the agricultural intervention, and those without9
. 
The conjunction among the geo-political divisions and the presence or absence of the agricultural 
intervention generates the stratification. The following are the strata defined for SHARE: 
Table M1: Strata and number of primary clusters to be sampled. 
Stratum
#
Department Municipality Agricultural 
Activity
Total stratum 
population
(families)
Number of clusters
/communities to be 
sampled 
Proportional 
distribution
Adjusted 
distribution
*
1
Huehuetenango
Santa 
Barbara NO 788 2 2
2 Nenton YES 1,099 3 2
3 NO 194 0 2
4
San Antonio 
Huista / 
Concepción 
Huista
YES 1,056 3 2
5 NO 428 1 2
6 Aguacatan YES 1,056 3 2
7 NO 516 1 2
8 Todos 
Santos 
Cuchumatan
YES 1,066 3 2
9 NO 257 1 2
10 Chiantla NO 1,781 44 3
11
Chimaltenango
San Martin 
Jilotepeque
YES 1,215 3 2
12 NO 471 1 2
13
Tecpán YES 1,118 3 2
14 NO 590 1 2
15 San Juan 
Comalapa NO 1,411 3 2
Total Population: 13,046 31
* Table extracted from the document “Title II Food Security Program Evaluation in Guatemala, MYAP 2006-2011, Final Evaluation Sampling 
Design”
 
9
 Stratification agreement between FANTA, Save the Children, CRS and SHARE (MYAP Title II consortium) 
MYAP 2011 Final Evaluation 
Methodology 
14
I.3 List of selected clusters / communities 
Table M2 presents the list of selected clusters that were presented to SHARE in the design document. 
Using this list, SHARE staff reviewed the viability and feasibility of visiting the selected areas, taking into 
account factors such as natural disasters. The evaluation was performed during the rainy season and as 
such some access roads were washed out, were subject to landslides or were at high risk levels. Another 
factor taken into consideration was that of social risk (rejection on the part of the community that could 
pose the risk of violence such as lynching to the group of surveyors working in the field. In the end, 
SHARE made a few changes to the presented list, switching some of the original communities for 
replacement communities. 
Clusters M2: Selected and visited community clusters Dept. Stratum
Municipality
Total Stratum 
Population Selected Cluster / Community
Community 
Visited
Huehuetenango
1 Santa Barbara
788
1 Tintonel YES
2 Cania Pequeño YES
Replacement 
Community 3 Chicol NO
2
Nenton
1,099
4 Chanquejelve YES
5 Subajasun YES
Replacement 
Community 6 Bilil NO
3
194
7 Canquintic YES
8 Tzojbal YES
Replacement 
Community 9 Yalisjau NO
4
San Antonio 
Huista / 
Concepción 
Huista
1,056
10 Canton Union YES
11 Petatan YES
Replacement 
Community 12 Ap NO
5
428
13 Canton Pozo YES
14 Ajul YES
Replacement 
Community 15 El Tablon NO
6
Aguacatan
1,056
16 Rio San Juan Village YES
17 Climentoro Village YES
Replacement 
Community 18 Pichiquil Village NO
7
516
19 Pajuil Pais Village YES
20 La Estancia Village YES
Replacement 
Community 21 La Barranca Village NO
MYAP 2011 Final Evaluation 
Methodology 
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Dept.
Stratum
Municipality
Total Stratum 
Population Selected Cluster / Community
Community 
Visited
8
Todos Santos 
Cuchumatan
1,066
22 Chicoy YES
23 San Martin YES
Replacement 
Community 24 Tres Cruces NO
9
257
25 Las Lajas YES
26 Laguna Seca YES
Replacement 
Community 27 Tuicobch NO
10 Chiantla
1,781
28 El Potrerillo YES
29 La Laguna YES
30 El Calvario YES
Replacement 
Community 31 La Haciendita NO
Chimaltenango
11
San Martin
Jilotepeque
1,215
32 Los Osorios YES
33 Varituc YES
Replacement 
Community 34 Choabajito NO
12
471
35 Estancia La Virgen YES
36 Rosario Conajal YES
Replacement 
Community 37 Choatalun NO
13
Tecpán
1,118
38 Pachichiac YES
39 Pacacay Village YES
Replacement 
Community 40 Pamezul NO
14
590
41 Paraxquin Village YES
42 Xecoxol YES
Replacement 
Community 43 San Vicente NO
15 San Juan 
Comalapa
1,411
44 Simajuleu Village YES
45 Chipoc YES
Replacement 
Community 46 Paxot NO
 The original design document is annexed to this document. 
II. Updating and Adapting the Data Collection Instruments
Because the MYAP is carried out by three organizations (Save the Children, CRS and SHARE), evaluations 
such as the baseline and the current final evaluation are carried out jointly, with the inherent 
differences of each of the PVOs. Doing this in consortium and with joint agreements helps to ensure 
MYAP 2011 Final Evaluation 
Methodology 
16
standardized results. Thus, the data collection instruments were defined from the beginning of the 
MYAP. The baseline evaluation already had validated and widely field tested instruments for gathering 
information. However, as each organization independently implemented its program, the technical staff 
of each organization met to review the baseline instruments and to determine whether to make minor 
changes to the format prior to gathering data for the final evaluation (given the particular information 
needs of each PVO). To the understanding of the consulting team, the changes made did not result in 
any significant variations to the original structure of the instruments. Rather, they maintained their 
quality of standardized instruments for data collection aimed at obtaining information and establishing 
the attainment of the indicators standardized by the MYAP consortium. (For instance, changes consisted 
of providing alternative answers to some of the questions.) 
As such, the consulting team that performed the evaluation already had data collection instruments 
with previously validated and field-tested questions at the time of the field study. 
In order to facilitate data gathering and input, the consultant divided the original instrument into several 
sections or forms, without changing the original questions. This allowed for more efficient data 
collection in the field and data input. 
The following is a complete list of the instruments, and they are also annexed to this document: 
1. Form 1 Cover (filter).docx (one page) 
2. Form 2 Family composition (FORM A).docx (one page)
3. Form 3 Health 0-60 (FORM B).docx (0 a <60 months) (six pages) 
4. Form 4 Health 0-6 (FORM C).docx (0 a <6 months) (two pages)
5. Form 5 Health 6-24 (FORM D).docx (6 a <24 months) (two pages)
6. Form 6 Production (FORM E).docx (six pages)
7. Form 7 Marketing cover (filter-M).docx (one page)
8. Form 8 Marketing family composition (FORM F).docx (one page) 
9. Form 9 Marketing (FORM G).docx (three pages) 
10. Form 10 Anthropometrics (FORM anthropometrics).docx (one page) 
11. Form 11 Risk management (FORM H).docx (one page) 
12. Form 11a Risk management (FORM H1).docx (Community Strengthening)(three pages)
MYAP 2011 Final Evaluation 
Methodology 
17
More detailed information regarding the evaluation instruments is provided in the annex “First Progress 
Report: Training”. 
III. Field Staff Selection and Training.
Whenever undertaking field research, one should keep in mind that some elements have a direct impact 
on the quality of information to be collected, subsequently conditioning the findings. It is therefore 
important to consider staff recruitment or selection, as well as other requirements such as training 
activities and standardization. 
III.1 Field staff selection and integration 
The staff, comprised of 21 members divided into three work groups, was recruited in accordance with 
the following basic characteristics: that they have a mid-level educational degree and previous 
experience. Surveying staff were expected to speak at least one of the Mayan languages of the regions 
to be visited. Another prerequisite was availability in accordance with the timetable in the initially 
drafted work schedule. Lastly, team members were expected to have positive attitudes toward the kind 
of activities that these types of quantitative studies require. 
The method used to document the survey responses in the field was through the instruments or paper 
ballots. As such, each of the three groups of surveyors had one team member identified as the editor. 
The role of the editor was to review and verify each and every one of the instruments completed in the 
field, especially in the communities, in order to ensure that these were properly and completely filled 
out. The editor also needed to verify the presence of the different “forms” in accordance with the 
information collected in each family. 
III.2 Training and standardization 
Training for the Survey Group consisted of a five-day workshop (August 8-12, 2011). Usually, in 
consultancies of a similar nature, the contracting organizations leave training and standardization to the 
consultant. However, in this case both SHARE and Save the Children requested direct participation in 
staff training, and to act in a supervising capacity rather than one of observation (as is usual). This was to 
ensure quality data collection and proper management of the information to be collected. As such and 
following the request of the technical staff for these organizations, the first activities in the training 
workshop were managed by them. There, they presented their programs and especially the questions in 
the instruments concerning health, production and marketing (commercialization). The first two and a 
MYAP 2011 Final Evaluation 
Methodology 
18
half days of the workshop were dedicated to these topics. The remaining time was used for staff 
practice, and to standardize the management of the instruments as well as standardize anthropometrics 
for the staff designated to record weight and height. 
In the practice sessions for completing the instruments, techniques and activities were employed to 
work on direct “face to face” interviews, as this was the method to be used in the field. 
The training workshop was divided into three significant sections: 
Part One: Generalities and knowledge of the topics (managed by SHARE and Save the Children 
technical staff) 
Part Two: Familiarization with the instruments 
Part Three: Practice and standardization 
The second part of the workshop was used to review the data gathering instruments, and instruction 
was provided for the completion of each of the forms. In this way, the survey team could familiarize 
itself with the order and sequence of the questions, and the correct way to record the information 
(codification of the recorded information). 
The third part of the workshop took on the technical aspects of the face to face interview format (in 
pairs and systematically), and incorporated respective practice. This phase had two main purposes: 
a) Instructing the staff on the process of applying the data collection instruments 
b) Evaluating the learning level of each of the workshop participants with regards to proper 
instrument management. Determining the degree to which each of the team members learned 
enabled timely constructive feedback as to the correct application of each of the data gathering 
instruments. 
The final two days of the workshop was used to standardize the basic survey terminology in Mayan 
languages (Quiché, Ixil, Mam, K'aqchikel), and to apply the data collection instruments in these 
languages using the systematized interview. This was repeated until the teams reached a degree of 
standardization similar to the one demonstrated in the application of the instruments in Spanish. 
MYAP 2011 Final Evaluation 
Methodology 
19
The third part of the workshop was also used to practice three activities for the standardization of 
weight and height for children under five10, in order to ensure that the staff was standardized prior to 
taking and recording these anthropometric measurements. In these exercises, Salter brand hanging 
scales in perfect working order were used. These had a weight capacity of 25 kilograms with 
“calibration/sensitivity=0.1kg (100gr)”. These were the same scales to be used in the field, as well as the 
measuring rods to measure children horizontally or vertically. The standardization of these methods was 
evaluated using the Habicht11 method. 
IV. The Field Study 
Upon completion of the training, the consulting team reviewed and defined the field logistics in 
accordance with the evaluation requirements. Field schedules and working routes were established 
according to the selected communities. SHARE helped to establish routes and to convene the clusters to 
be interviewed in advance. 
IV. 1 Field work phase 
Field activities were carried out in accordance with the plans made during the training and logistics 
phase. 
A. Introductions and requests for community cooperation 
Prior to gathering information in each community, each field team sought the support of local 
authorities/leaders. These mainly consisted of SHARE or Save the Children technical staff, institutional 
facilitators, community facilitators, lead mothers, COCODE members and auxiliary mayors. These 
individuals served as facilitators during the field phase and provided guidance within the community, 
served as translators and/or helped contact the community members. 
B. Survey team management 
The field teams began their part of the evaluation on August 13, 2011, arriving in the department of 
Huehuetenango to begin working in SHARE communities. Surveying in Huehuetenango municipalities 
took place from August 14 through August 20. Three field teams worked simultaneously (Groups 1, 2 
and 3), so that three communities were visited per day. On September 4 the teams were transferred to 
 
10 This practice was carried out with aid from the Integrated Attention Centers Program, which facilitated the entry 
of our staff to the center located in zone 13 (see annex 5 for a copy of the letter requesting cooperation). 
11 The purpose of this standardization was to determine the degree of precision and accuracy with which 
participants weighed and measured the children under five. 
MYAP 2011 Final Evaluation 
Methodology 
20
the Chimaltenango communities, where field work began on September 5 in the municipality of Tecpan. 
The work method described above was also used in Chimaltenango. The last community visited was 
Varituc in the municipality of San Martin Jilotepeque on September 8, and that same day the teams 
returned to headquarters. 
C. Linguistic Aspects 
Previous familiarization with the geographic regions and especially linguistic contexts was a determining 
factor in designating each team member to each team. Each team had at least one member who spoke 
one of the four dominant languages for the different regions. Thus there was always at least one 
surveying member of the team who could speak the local language. The field supervisor was responsible 
for finding and placing translators as needed. Hired translators were community members such as 
community facilitators, lead mothers and in some cases technical staff. Prior to using their services, they 
were provided with a brief introduction to ensure their understanding of the instruments to be used. 
Prior to hiring translators the teams explored the community to determine the general language 
preference of the mothers to be surveyed. This included questioning the local authorities. In each 
household, the team introduced itself and asked the surveyed mother her language preference for the 
interview. Each group supervisor was responsible for assigning translators and was careful to note when 
and if they were necessary, staying with the group at all times during the field phase. 
It is important to highlight the collaboration between local SHARE technical staff and the field teams. 
This was instrumental in facilitating community introductions, presenting the field team and explaining 
the reasons for their presence in the communities to the local authorities. SHARE also helped to find 
local community guides and translators. 
D. Field information management 
Within each community, the first step was to select the homes to be visited, according to the total 
number of homes in the community and the determined sample size of 35 homes. In each community, 
the samples were selected by systematic random sampling using the sampling frames (community 
mapping diagrams). Once the surveyors and anthropometrists were established in the community, the 
team supervisor transferred them to the homes assigned by the sampling. 
MYAP 2011 Final Evaluation 
Methodology 
21
All of the information in the field was collected in home visits. Each interview lasted between 45 
minutes and 1.5 hours. This depended on introductions, the number of instruments to be used 
(depending on the number and ages of the children present in the home), and the need for translators. 
In most communities the field staff was supported by local staff, who served as guides and companions. 
This contributed greatly to ensuring more effective field work. 
IV.2 Quality control in the field 
IV.2.1 Internal quality control 
During the field phase, several mechanisms for quality control were applied, including: 
a. Direct supervision in the surveyed homes; the supervisor randomly selected homes to be 
supervised in the course of the field activities. 
b. In depth review of each of the completed questionnaires (editing). This activity was the 
responsibility of the team editors and was done while still in the respective community. 
IV.2.1 External quality control 
Throughout the field work phase SHARE local and headquarters staff supervised the three field teams. 
SHARE headquarters personnel who continually supervised and escorted the teams were: the 
Monitoring and Evaluation Coordinator, the Health and Nutrition Sub-Manager, the Agriculture Sub￾Manager and the Human Development Manager. This is the staff that oversees the implementation of 
the IFS Program, in conjunction with field staff in the various municipalities. SHARE headquarters staff 
supervised the evaluation field work and helped to improve the field teams’ performance by providing 
constructive criticism regarding data collection. 
IV.3 Results of the Evaluation 
IV.3.1. Health and Nutrition and Agriculture and Livestock Farming Interventions 
The results of the evaluation corresponding to the surveys recorded in each community are presented in 
Table M3, in the order that the communities were visited. 
MYAP 2011 Final Evaluation 
Methodology 
22
Table M3. Summary of surveys recorded by community: Health and Nutrition and Agriculture 
and Livestock Farming Interventions. 
Department Community Survey 
team
# of selected 
homes
# of effective 
interviews
Huehuetenango Chanquejelve 2 35 22
Huehuetenango Subajasun 3 35 26
Huehuetenango Canquintic 1 35 25
Huehuetenango Tzojbal 2 35 26
Huehuetenango Canton Union 1 35 21
Huehuetenango Petatán 3 35 25
Huehuetenango Canton Pozo 3 35 25
Huehuetenango Ajul 1 35 28
Huehuetenango Chicoy 2 35 27
Huehuetenango San Martin 3 35 26
Huehuetenango Las Lajas 2 35 23
Huehuetenango Laguna Seca 1 35 29
Huehuetenango El Potrerillo 2 35 28
Huehuetenango La Laguna Paquix 1 35 24
Huehuetenango El Calvario 3 35 28
Huehuetenango Tintonel 1 35 24
Huehuetenango Canjá Chiquito 3 35 16
Huehuetenango Rio San Juan Village 3 35 24
Huehuetenango Pajuil Pais Village 1 35 21
Huehuetenango La Estancia Village 2 35 21
Huehuetenango Climentoro Village 2 35 14
Chimaltenango Pachichiac 1 35 28
Chimaltenango Pacacay 2 35 25
Chimaltenango Paraxquín Village 3 35 24
Chimaltenango Xecoxol 2 35 25
Chimaltenango Simajhuleu Village 3 35 26
Chimaltenango Chipoc 1 35 28
Chimaltenango El Rosario Canajal 1 35 28
Chimaltenango Estancia de la Virgen 3 35 25
Chimaltenango Los Osorios 2 35 25
Chimaltenango Varituc 1,2,3 35 32
It is important to note that, due to the dates and scheduling of the field portion of the study, 
several events took place in and out of the communities that at times limited data collection. 
Some examples include political rallies due to the election year, religious activities (activities 
prior to and during the Day of the Virgin’s Assumption and other religious activities particular to 
MYAP 2011 Final Evaluation 
Methodology 
23
various communities), school activities for Independence Day, activities organized by the Mi 
Familia Progresa [a Guatemalan government program], COCODE meetings, and other 
community events. These events occupied the mothers outside of their homes for the better 
part of the day, delaying anthropometric measurements and interviews. 
It is likewise important to note that suburban communities presented frequent scheduling 
conflicts to the survey scheduling, as it was common to find the women away from their homes 
or unwilling to take the survey. 
IV.3.2. Micro-Business Development Intervention 
The research for this intervention took place among participating groups within the randomly selected 
communities. All community participants in the Micro-Business development intervention were 
convened for this purpose. Coordination and convening of the participants was the responsibility of 
SHARE’s technical teams.
The results of the surveys obtained in each selected community are presented in Table M4, according to 
the order in which the communities were visited during the field study. 
Table M4. Summary of surveys obtained per community, Micro-Business Development 
Intervention. 
Department Community Survey Team # of Marketing Ballots
Huehuetenango Las Lajas 2 14
Huehuetenango La Estancia Village 2 10
Chimaltenango Pacacay 2 10
Chimaltenango Simajhuleu Village 3 10
Chimaltenango Los Osorios 2 5
A total of 5 communities were sampled for this component, and a total of 49 surveys were completed. 
IV.3.3. Capacity Building (Risk Management) 
The Risk Management intervention was evaluated using questionnaires H and H1. The first was applied 
in 31 communities that comprised the sample and the second was used in three communities with 
sentinel sites. It should be noted that the sample of 31 communities included some communities in 
which the intervention was not implemented. 
MYAP 2011 Final Evaluation 
Methodology 
24
The team interviewed community leaders (COCODEs). The field supervisor of each team was responsible 
for coordinating and convening the people to be interviewed, with the support of SHARE technical staff. 
In the case of the communities with sentinel sites, the survey activities were carried out in locations 
specified by the community leaders in order to observe the sites. This included a review of the 
documents that support the intervention and its implementation. Table M5 includes the names of the 
communities in which sentinel site information was compiled. 
Table M5. Summary of surveys completed in Sentinel Sites per community. 
Department Community Survey team Community Bulletin 
Boards
Huehuetenango Chanquejelve 2 1
Chimaltenango Pacacay 2 1
Chimaltenango Los Osorios 2 1
The information compiled with both of these questionnaires provides the answer to the question posed 
by the indicator, “#of communities with functioning monitoring and early warning systems”. 
V Processing, data analysis and report preparation
The data that was collected in the field was entered using EPI INFO version DOS 6.04d software. The 
information was entered using double entry of each of the completed questionnaires or instruments. 
Each of the double entries was performed by a different data entry operative. EPI INFO incorporates a 
function to ensure quality control during input, called CHECK. This function was enabled and thus 
allowed to check for errors such as inadvertent “jumping” between variables, extreme or invalid values 
(for instance, only two codes are accepted for sex: 1 = man and 2 = woman; the software did not allow 
the input of any other number). Once the mutually independent double entry was completed, these 
were compared through a process known as validation (using the software VALIDATE). Any 
discrepancies or errors in the file were identified and were corrected in both input files (the first and 
second). Once the files had been corrected, they were validated again. If errors were found, they were 
again identified and corrected. The process was repeated as many times as necessary until the two files 
were identical (without inconsistencies or errors). 
Anthropometric values were calculated using EPI INFO’s EPINUT module. This software provides Z-scores 
according to NCHS standards. Z-scores according to WHO standards were also calculated using WHO 
ANTHRO software version 3.2.2. It is important to note that upon processing the data, both software 
MYAP 2011 Final Evaluation 
Methodology 
25
programs identified extreme cases or “outliers”. The ANTHRO program eliminates the values for these 
children, while NCHS software requires manual elimination through the consultant’s programming. 
Because there are children under five with extreme measurements in weight or height for their age, and 
because there is rarely a case in which the extreme measurement is for both weight and height, sample 
sizes for anthropometric indicators are not homogenous, nor are the indicators measured by the 
different software programs homogenous, because of their differing standards. 
Once the databases were free of errors, programs were created to construct the indicators (see the 
annexed databases for these programs; they have a PGM extension and are accessible through Word). 
EPI INFO’s CSAMPLE was used for statistical analysis. This program calculates percentages, averages and 
variable measurements (including confidence intervals), considering the sampling design. In this case, 
three variables were considered: STRATUM, CLUSTER and WEIGHTING. 
The strata is the same as is described in the design document, so each survey is easy to locate within its 
corresponding stratum. By the same token the CLUSTER corresponds to primary or community cluster, in
other words, the community. WEIGHTING was calculated taking into consideration probability of 
selection (the same calculations that were made in the baseline): 
 Weighting = 1 / probability of selection 
 Where: 
Probability of selection = Prob. Community selection X Prob. Selecting a home in the 
community 
For the preparation of this report, SHARE and Save the Children were presented with a draft that 
identified the tables of indicators to be reported. 
MYAP 2011 Final Evaluation 
Results 
26
This section details the results of each of the program indicators as measured by the study. The 
information is organized into thematic tables12. The tables present the information for the entire 
population as well as disaggregated by communities with/without the program’s agricultural farming 
interventions. 
The tables present the values for the sample (percentages and averages), as well as the values for the 
population (with a 95% confidence interval). The tables also detail the sample size with which each 
indicator was calculated, and the number of subjects in the sample that meet the indicator. It is 
important to note that due to the fact that the statistical analysis was performed considering the 
sampling design (stratified by cluster), it was necessary to weight each observation against its probability 
of selection. As such, the percentages don’t correspond to a simple division of the number of cases that 
meet the indicator by the sample size. For instance in the case of the indicator: Percentage of children 
under five with chronic malnutrition (Z < -2SD height/age) in communities with the program’s 
agricultural interventions. The finding is 58.1%, though the sample size is 389 children under five, and of 
these 223 meet the indicator of having less than two standard deviations. 
 
Sample indicator Sample Size Number of 
Cases
%
Percentage of children aged 0 to 59.99 with <2.0 SD height/age, 
NCHS 389 223 57.2%
The operation of 223 divided by 389, equals 57.3%, and not 58.1%. The reason for this is because the 
58.1% is calculated taking into consideration the sampling design, while the value of 57.3% does not 
consider the sampling design. As such, the latter is a skewed value (by analysis). 
The results are in five different sections of the document: 
III.A MYAP Indicators This section presents a summary table with the results of the main 
program indicators. The values are shown in contrast with regards to goals and values found in the 
baseline. 
 
12 The tables gather all of the indicators of a particular theme. 
MYAP 2011 Final Evaluation 
Results 
27
III.B 2011 Results Tables present summarized indicators, as well as a narrative of the main findings 
(discussion of the results). 
III.C Detailed 2011 Results The results of the indicators are presented in detail, for the total as well 
as disaggregated population (populations with/without the agricultural component). The tables include 
sample sizes as well as confidence intervals. This section is annexed to this document (Annex 1). 
III.D Design Effect This is detailed in Annex 2, in which the sampling design effect of each of the 
main indicators is presented. 
III.E 2011 Results by Municipality This section presents the results of the indicators disaggregated 
by municipality. This sections IS NOT PRESENTED as a part of this report, rather it is an attached 
document that contains the EPI INFO analysis outputs. This disaggregation was requested by SHARE, for 
use of the information for programming purposes. 
Confidence Intervals 
The tables present confidence intervals, which provide the values between which we find the value 
estimated for the total population. In other words, the percentages presented in the tables correspond 
to the value obtained from the sample, which is also the value for the population. However, this value 
doesn’t necessarily correspond to the value in the total population. Rather, the population value is 
calculated with error and is therefore presented as an interval. This interval presents the lowest and 
highest values, between which the values for the population can be found. For example, the Percentage 
of children aged 0 to 59.99 months with <2.0 SD weight for age, NCHS, is 29.1% for the sample, and in 
the total population may be as low as 24.8% or as high as 33.5%. 
Percentage of children aged 0 to 59.99 months with <2.0 SD 
weight for age, NCHS
29.1%
( 24.8, 33.5)
MYAP 2011 Final Evaluation 
Results 
28
III.A MYAP Indicators 
Table III.A.1 MYAP indicators and their goals 
Thematic Area Code
13 Indicators Baseline 
value GOAL
2011 Percentage
(Confidence Interval. 
95%)
Anthropometrics 
in children under 
5 years
1a
Percentage of children aged 6 to 59.99 months with <2.0 
SD height for age, NCHS 69% 66% 62.5%
(55.9, 69.0)
1a
Percentage of children aged under 5 with <2.0SD height 
for age, NCHS 64% 61% 57.2%
(51.2, 63.1)
1b Percentage of children aged 0 to 59.99 months with <2.0 
SD height for age, WHO 69% N/A14 65.8%
(60.3, 70.2)
2a
Percentage of children aged 0 to 59.99 months with <2.0 
SD weight for age, NCHS 35% 30% 29.1%
( 24.8, 33.5)
2b Percentage of children aged 0 to 59.99 months with <2.0 
SD weight for age, WHO 28% N/A4 22.2% 
(18.7, 25.7)
Anthropometrics 
in children under 
36 months
2a
Percentage of children aged 0 to 35.99 months with <2.0 
SD weight for age, NCHS 35% 28% 26.7%
(21.7, 31.8)
2b Percentage of children aged 0 to 35.99 months with <2.0 
SD weight for age, WHO 27% N/A4 18.7% 
( 15.2, 22.1)
Household dietary 
diversity and food 
scarcity in the 
household 
4
Number of food groups consumed in the household in the 
preceding 24 hours. 
4 
Food 
groups
6
Food 
groups
7.3
Food groups
(7.1, 7.4)
5
Average number of months out of the year with adequate 
provisions of food in the household.
11
months
11
months
11.0 months
(10.8,11.2)
Child feeding 8
Percentage of infants aged 0 to 5.99 months who have 
been exclusively breastfed in the preceding 24 hours. 71% 77% 74.7%
(64.4, 85.0)
Warning signs of 
childhood illness. 18
Percentage of mothers and caregivers with children aged 0 
to 35.99 months who recognize at least two warning signs 
of childhood illness that indicate the need to seek health 
services. 
36% 50%
75.4%
(70.1,80.8)
Maternal health 
and neonatal 
warning signs.
12
Percentage of mothers with children aged 0 to 35.99 
months who recognize at least two warning signs in 
pregnancy that indicate the need to seek health services. 
13% 34%
71.3%
(65.0,77.6)
15
Percentage of mothers with children aged 0 to 35.99 
months who recognize at least two neonatal warning signs 
(<28 days) that indicate the need to seek health services. 
15% 35%
61.1%
(53.8,68.5)
Agricultural and 
livestock farming 
practices
22
Percentage of farmers who adopt at least two improved 
agricultural practices. 18% 23% 30.9% (25.5, 36.3)
23
Percentage of farmers who adopt at least two improved 
livestock practices 9% 14% 42.0% 
(35.5, 58.5)
Income 
improvement 30
Percentage of farmers who adopt at least two improved 
formal marketing practices 17% 22%
86.7%
(71.4, 100)
(Not comparable to 
the baseline)
 
13 Codification of the variables subject to research 
14 Note: In anthropometric indicators, the ascribed goals correspond only to the values estimated in NCHS 
standards, and not WHO standards. 
MYAP 2011 Final Evaluation 
Results 
29
Thematic Area Code
13 Indicators Baseline 
value GOAL
2011 Percentage
(Confidence Interval. 
95%)
Local capacity 
building 31
Number of communities with functioning early warning 
systems for Food and Nutritional Security 0 84 72*
(48, 93)
* According to SHARE monitoring information, the exact amount is 91 communities. 
III.A.1 MYAP Indicators and their Goals 
Main Findings: 
Table III.A.1 illustrates that the populations who are in the implementation area of SHARE’s MYAP 
now present a different situation than before the program, as most of the indicators demonstrate 
an improvement. Childhood indicators are particularly highlighted: reduced rates of chronic 
malnutrition in children under five (height for age at less than two standard deviations), from 69% to 
62.5% (P<0.05), and in children aged 6 to 59.99 months (height for age at less than two standard 
deviations) from 69% to 62.5%, and reduced rates of general malnutrition in children under 36 
months (weight for age at less than two standard deviations) from 35% to 26.7% (P<0.05). This 
demonstrates that the established goals for the reduction of chronic and general malnutrition rates 
were met. 
MYAP 2011 Final Evaluation 
Results 
30
Graph 1: Malnutrition in the final and baseline evaluations 
 Dietary diversity was clearly increased from the baseline value, from an average consumption of four 
food groups to an average of 7.3 groups, exceeding the established goal of six groups (P<0.05). 
Knowledge of warning signs in pregnancy, neonatal infants and children greatly exceeded the values 
found in the baseline, and as such also exceeded the goals (P<0.05). The percentage of women who 
acquired knowledge of warning signs easily doubled or even quadrupled baseline values, and as such 
now 71.3% of women recognize warning signs in pregnancy, 61.1% recognize neonatal warning signs, 
and 75.4% recognize warning signs of childhood illness. 
74% of infants younger than 6 months were exclusively breastfed, while in the baseline, that value was 
71%. However, due to having such a small sample to measure this indicator, it was not possible to 
establish a change of sufficient statistical significance from the baseline. Therefore it was also impossible 
to evaluate whether the indicator goal was met. Regardless, among the populations where SHARE 
works, the percentage of infants younger than 6 months who were exclusively breastfed is significantly 
higher than the ENSMI 2008-2009 findings for rural areas (60.4%). 
0%
10%
20%
30%
40%
50%
60%
70%
NCHS%
children under
5 with chronic
malnutrition
WHO%
children under
5 with chronic
malnutrition
NCHS%
children under
5 with general
malnutrion
WHO%
children under
5 with general
malnutrition
NCHS%
children under
3 with general
malnutrition
WHO%
children under
3 with general
malnutrition
Baseline
Final
MYAP 2011 Final Evaluation 
Results 
31
Agricultural and livestock practices have also improved from the baseline, and these indicators also 
exceeded the proposed goals (P<0.05). Now, 30.9% of agricultural farmers implement improved 
agricultural practices, and 42% of livestock farmers implement improved practices. 
 With regards to the implementation of at least two practices in formal marketing, at the time of the 
baseline 17% of farmers implemented these measures. Accordingly, a goal of 22% was established for 
this indicator. SHARE developed this initiative with a small number of farmers, around 500 individuals, 
and contemplated a small amount of advocacy among participating populations. Given this, the 
indicator does not adequately demonstrate the effort and accomplishments of these participants. The 
sample for this indicator is a sub-sample of the evaluation sample15, which is nonetheless representative 
due to the random sampling of communities. In this case, a sample of 43 participants was surveyed, 
showing that the program has accomplished that 86.7% of those surveyed adopted at least two formal 
marketing practices, and that the rate among the total participating population is at least 71.4%. 
 
15 FANTA and the three PVOs: SHARE, Save the Children and CRS, agreed in meetings held in July 2011, that the 
measure of this indicator would be carried out using a sub-sample of participants, and not using the populational 
sampling used to measure the other indicators. 
MYAP 2011 Final Evaluation 
Results 
32
III.B 2011 Results 
III.B.1 Anthropometrics in children under 5
The sample size of children under 5 was 1,046. Because some of these presented extreme values in their 
weight and/or height measurements in relation to their age or the relationship between them, these 
were identified as outliers. The software programs flag these values, and the ANTHRO program 
eliminates them. For this reason, the total sample size is less than 1,046 children, and the indicators 
present different sample sizes, depending on the outlying measurement. 
Table III.B.1a Anthropometrics in children under 5
Results
Indicator
Code Name
Anthropometrics according to NCHS standards
1a
Percentage of children of 0 to 59.99 months with chronic malnutrition (Z < -2SD 
height/age)
57.2%
1a
Percentage of children of 6 to 59.99 months with chronic malnutrition (Z < -2SD 
height/age)
62.5%
1a1 Average Z score for height/age in children of 0 to 59.99 moths. -2.16 SD
1a1 Average Z score for height/age in children of 6 to 59.99 months. -2.28 SD
2a Percentage of children under 5 with general malnutrition (Z < -2SD weight/age) 29.1%
2a1 Average Z score for weight/age in children under five -1.37 SD
Anthropometrics according to WHO standards
1b Percentage of children under 5 with chronic malnutrition (Z < -2SD height/age) 65.8%
1b1 Average Z score for height/age in children under five -2.35 SD
2b Percentage of children under 5 with general malnutrition (Z < -2SD weight/age) 22.2% 
2b1 Average Z score for weight/age in children under five -1.21 SD
Table III.B.1b Anthropometrics in children under 5 years 
by age group Results
Indicator
0 to < 36
months
36 months to < 60 
Code Name months
Anthropometrics according to NCHS standards
1a
Percentage of children under 5 with chronic malnutrition (Z < 
-2SD height/age)
50.5% 68.9%
1a1 Average Z score for height/age in children under five -2.00 SD -2.44 SD
2a Percentage of children under 5 with general malnutrition (Z < 
-2SD weight/age)
26.7% 33.4% 
MYAP 2011 Final Evaluation 
Results 
33
III.B.1 Anthropometrics in children under five years 
Main Findings: 
Tables III.B.1a and III.B.1b (see Annex 1) show that chronic and general malnutrition rates are 
comparable among children in communities with agricultural interventions and those in communities 
without agricultural interventions (in accordance with NCHS standards), with chronic malnutrition at 
62% and general malnutrition at 29%. However, acute malnutrition is lower in communities with the 
agricultural intervention than in communities without the agricultural intervention. It is also noteworthy 
that according to WHO standards, there was likewise no statistical difference in malnutrition rates 
among these strata (with or without agricultural intervention). The differences between the two 
systems for malnutrition classification are significant because the WHO system gives higher values than 
the NCHS system. 
2a1 Average Z score for weight/age in children under five -1.22 SD -1.62 SD
Anthropometrics according to WHO standards
1b
Percentage of children under 5 with chronic malnutrition (Z < 
-2SD height/age)
60.0% 75.9% 
1b1 Average Z score for height/age in children under five -2.22 SD -2.57 SD
2b Percentage of children under 5 with general malnutrition (Z < 
-2SD weight/age)
18.7% 28.3%
2b1 Average Z score for weight/age in children under five -1.03 SD -1.52 SD
MYAP 2011 Final Evaluation 
Results 
34
It is important to highlight the low numbers of children with severe acute malnutrition (lower than or 
equal to three standard deviations), being only a total of 5 cases according to NCHS standards and 16 
according to WHO standards. 
Graph 2: Malnutrition prevalence in the study 
The National Survey for Maternal/Children’s Health for 2008-2009 (ENSMI) presented malnutrition 
results in accordance with WHO standards (for children aged 3 to 59 months). In the specific areas of 
Chimaltenango and Huehuetenango, the results for chronic malnutrition were 61.2% and 69.5% 
respectively, and 14.5% and 20.8% for general malnutrition respectively. These values coincide with the 
values found by this study in the evaluated populations. The ENSMI also presents national values for 
chronic and general malnutrition in accordance with WHO as well as NCHS standards, and it is worth 
noting that the population in this evaluation presents much higher values than those found by the 
ENSMI for national levels (see Graph 2a). 
Tables III.B.1b and III.C.1b (Annex 1) also show a series of important differences in terms of malnutrition 
rates by age group in accordance with NCHS standards. In this case, the rates of chronic malnutrition are
lower in younger children (under 36 months), with a rate of 50.5%, while the older group (over 36 
months) presented a rate of 68.9%. This is a statistically significant difference (P < 0.05) that 
demonstrates that children older than 36 months are 2.1 times more likely (odds ratio) to suffer from 
malnutrition than children under 36 months. This observation is consistent with the values that are 
supported by the average Z score. 
0% 20% 40% 60% 80%
Chronic NCHS
Chronic WHO
General NCHS
General WHO
36 months to < 60
months
0 to < 36 months
Under 5 years
MYAP 2011 Final Evaluation 
Results 
35
Graph 2a: Malnutrition prevalence found in this study, compared to the 2009 ENSMI 
Likewise, these results show that lower acute malnutrition rates are found in younger age groups (0.5% 
as compared to 3.9% on older children (P < 0.05). The probability of finding children with acute 
malnutrition is 8.2 times more likely (odds ratio) in children who are over 36 months. 
The results in this same table show that rates of malnutrition found in accordance with WHO 
anthropometric standards were lower (P<0.05) for the age group of 0 to < 6 months, a finding that is 
consistent with each of the Z score measures, respectively. 
Table III.C.1c (Annex 1) presents the results of the data analysis by sex. According to the results found in 
accordance with NCHS standards, no difference is found between the sexes. However, using WHO 
standards for the analysis results in a significant difference in the rates of chronic malnutrition, where 
boys/girls present a higher value than girls (68.5% compared to 62.7%, P < 0.05). Boys/girls are 1.3 times 
more likely (odds ratio) than girls to suffer from malnutrition. This finding is unusual, and it is difficult to 
find an explanation. 
0% 10% 20% 30% 40% 50% 60% 70% 80%
Chronic NCHS
Chronic WHO
General NCHS
General WHO
36 months to < 60 months
0 to < 36 months
Under 5 years
ENSMI 2009 National
ENSMI 2009 Hue
ENSMI 2009 Chim
MYAP 2011 Final Evaluation 
Results 
36
III.B.2 Family dietary diversity and family food scarcity 
Due to the relevance of food production to this theme, the results are presented disaggregated by the 
presence or absence of the agricultural intervention. 
Table III.B.2 Family Dietary 
Diversity
Family Food Scarcity Results
Indicator Population WITH 
Agricultural 
Interventions
Population WITHOUT 
Agricultural Interventions
Total 
Population Code Name
Family Dietary Diversity
4
Average Dietary Diversity Score
(average number of groups 
consumed)
7.5 groups 7.0 groups 7.3 groups
4a Percentage of families who ate from 
the group:
4a3 C: Vegetables 48.0% 42.2% 44.8%
4a4 D: Fruits 71.9% 67.5% 69.5%
4a6 F: Eggs 66.8% 54.5% 60.0%
4a8 H: Legumes / leguminous plants / 
dried fruits
78.9% 71.3% 74.7%
Family Food Scarcity
5
Average number of months with 
adequate food provisioning in the 
home
11.1 months 10.9 months 11.0 months
5a Foods that became scarce:
5a1 A: Corn 32.8% 29.3% 30.9%
5a2 B: Beans 26.9% 23.3% 24.9%
5b Reasons for food scarcity:
5b1 A: Lack of money 29.7% 35.0% 32.7%
5b2 B: Lack of employment 26.4% 27.6% 27.0%
5b5 E: There were no crops 13.6% 15.2% 14.5%
5b6 F: The harvest was lost 9.2% 5.5% 7.2%
6
Average Reduced Severity Index16
"What did you do for food during 
the months of scarcity"
1.7 points 1.8 points 1.7 points
6a What was done for food during the 
months of scarcity:
6a2 B: Sold animals 14.6% 14.2% 14.4%
6a4 D: Borrowed 13.6% 17.2% 15.6%
6a6
F: Someone in the family went 
elsewhere for work
21.5% 21.3% 21.4%
 
16 "Severity Index" known as the Coping Strategies Index (CSI). This index has been studied to a greater degree in Africa and was 
created by the World Food Program (WFP) Assisted Refugees in Western Tanzania. The index is presented in a document 
drafted by several organizations in 200816, and is defined as the sum of considered adaptations (or strategies used to confront 
food crises). In Guatemala, JMatute-CIENSA has calculated the index for UNICEF and World Vision. The index has a scale of 0-20 
points, where “0” means that no strategy was employed and “20” is the maximum severity having employed all of the checked 
strategies. 
MYAP 2011 Final Evaluation 
Results 
37
III.B.2 Family Dietary Diversity and Family Food Scarcity 
Main Findings: 
Tables III.B.2 and III.C.2 (Annex 1) demonstrate that the populations with agricultural interventions have 
a higher dietary diversity score, as compared to populations without agricultural interventions (7.5 
points versus 7.0 points respectively, P<0.05). 99.9% of the families consume cereals, and a similarly 
high 97.8% consume sugar or honey. The foods that follow in terms of consumption rates are fats or oils 
(79.3%), legumes or leguminous plants (74.7%) and fruits (69.5%). The least consumed foods are fish 
and seafood (3%), followed by milk and dairy products (21.7%). It is worth highlighting that the 
population with agricultural interventions demonstrated a significantly higher consumption of the 
vegetable, egg and legume food groups, than the populations without the agricultural intervention. 
Therefore, this may be considered one of the program’s effects. 
Graph 3: Average Dietary Diversity Scores Graph 4: Food Groups Consumed 
It may also be noted that the number of months of the year in which adequate food provisions may be 
counted on is eleven. However, out of the 769 surveyed homes, 437 mentioned having had adequate 
provisions for 12 months of the year (56.8%17). Thus, 332 homes reported at least one month of scarcity, 
and it was the month of July that was reported as the month with the most significant scarcity (143 out 
of the 332 that reported scarcity). 
 
17 Non-weighted value
6.7
6.8
6.9
7
7.1
7.2
7.3
7.4
7.5
7.6
With
Agriculture
Without
Agriculture
Group Total
Average
MYAP 2011 Final Evaluation 
Results 
38
 
The food that is most reported as scarce is corn (30.9%), followed by beans (24.9%) and sugar (22.5%). 
The main reasons given by families who report food scarcity is “lack of money” (32.7%) and “lack of 
employment” (27.0%). It is also important to note, however, that the reasons “no crops” or “the harvest 
was lost” jointly added up to 22.8%. 
Graph 5: Scarce foods and reasons for scarcity 
The severity index quantifies the adaptations the family had to make in order to overcome the food 
crisis caused by food scarcity. In this case, the calculated index is on a 0 to 20 point scale, where “0” 
means the families felt no need to adapt, and “20” means that they employed all of the means 
considered in the study. The results show an average of 1.7 points, with which we may conclude that the 
studied population did not have very pressing needs of adaptation in the last year. This in turn is 
explained by the fact that, as previously mentioned, the majority of homes had adequate food 
provisions for 12 months of that year. It is also important to note that this study found that the families 
with the most severe food insecurity, whose children posed the greatest malnutrition problems, were 
supported by additional resources (including food, supplements, medical services, fowl, etc.). These 
were provided with additional funds in the context of a Single Year Assistance Program for Acute 
Malnutrition Recovery and Agricultural Reactivation. Further, not all of the possible adaptation 
mechanisms were measured, which means that this index does not adequately demonstrate this 
population’s food insecurity. The most employed adaptation mechanism was “seeking work in another 
area” (21.4%), followed by “borrowing” (15.6%), and “the sale of animals” (14.4%). Significantly, 3.6% 
0% 5% 10% 15% 20% 25% 30% 35% 40%
Corn
Beans
Lack of money
Lack of employment
There were no crops
Harvest was lost
Total Without Agriculture With Agriculture
MYAP 2011 Final Evaluation 
Results 
39
families mentioned that their children had to work (Annex 1), which may be interpreted as a sign of the 
magnitude of the crisis the family faced, given the strong campaign against child labor. 
III.B.3 Information, education and communication in health and nutrition
 
Table III.B.3 Information, education and communication in health and nutrition
Code Name of the Indicator Results
7
Percentage of women who confirm having received health and nutrition counseling in 
the preceding month
63.4%
7a
Percentage of women who confirm having received counseling from MSPAS staff and/or
from the IFS Program 
62.0%
Women received counseling from:
7a1 A: MSPAS health staff 21.6%
7a2 B: IFS Program community staff 50.6%
7b Topics dealt with in the counseling sessions:
7b1 A: Children’s health 49.7%
7b4 D: Food and nutrition 53.8%
7b5 E: Household hygiene 36.1%
7c Ways that messages or counseling were transmitted:
7c1 A: Counseling 26.9%
7c2 B: Educational meetings and/or demonstrations 54.8%
MYAP 2011 Final Evaluation 
Results 
40
III.B.3 Information, education and communication in health and nutrition 
Main Findings: 
63.4% of the women confirmed having received health and nutrition counseling in the last month. It is 
evident that having received said counseling was unrelated to the disaggregation factor of whether or 
not a population participated in agricultural interventions (see Table III.C.3 in Annex 1). This makes it 
clear that the health and nutrition intervention was implemented equally among both populations, 
which was to be expected. 
There is a relatively high percentage of women who confirm having received counseling from qualified 
staff from either the MSPAS or the IFS Program, the latter having been the source of the majority 
(50.6%). The main counseling topics were “nutrition and feeding” (53.8%) and “children’s health” 
(49.7%). 
The main method employed for the transmission of these topics was through educational meetings 
and/or demonstrations (54.8%).
Graph 6: Information, education and communication in health and nutrition 
0%
10%
20%
30%
40%
50%
60%
70%
MYAP 2011 Final Evaluation 
Results 
41
III.B.4 Child Feeding
 
Table III.B.4 Child Feeding
Code Indicator Results
Breastfeeding in infants under 6 months
8
Percentage of infants from 0 to < 6 months that were exclusively breastfed in the 
preceding 24 hours 
74.7%
Feeding in children aged 6 to 24 months
9
Percentage of women with children aged 6 to < 24 months who have breastfed their 
children
94.8%
9a
Percentage of women with children aged 6 to < 24 months who are breastfeeding their 
children
79.6%
10
Percentage of mothers or caregivers of children aged 6 to < 24 months who know 
about and practice good weaning / complimentary feeding practices (having started 
complimentary feeding when the child was six months old)
87.1%
10a Average age at which children aged 6 to < 24 months started complimentary feeding 6.6
months
III.B.4 Child Feeding 
Main Findings: 
The study found that 74.7% of infants are exclusively breastfed among the surveyed population in 
SHARE’s IFS Program. The rate for the total population could be as low as 64.4% and as high as 85% 
(confidence interval). The rate of exclusive breastfeeding found is significantly higher than the national 
average for rural populations (ENSMI 2009, 60.4%). With regards to general breastfeeding, with or 
without complimentary feeding in infants under 6 months, ENSMI reports rates of 96.6% for rural 
populations, which coincides with the rates found in this evaluation (97.8%). 
94.8% of children between the ages of 6 and 24 months have been breastfed, and the percentage of this 
population currently being breastfed is 79.6%. In other words, almost 20% of children between the ages 
of 6 and 24 months are no longer being breastfed. 
The recommended age to begin complimentary feeding in infants is 6 months. The study found that 
87.1% of the women surveyed implement this practice with their children. The average age at which 
mothers began this practice was 6.6 months. 
MYAP 2011 Final Evaluation 
Results 
42
Graph 7: Child Feeding 
III.B.5 Warning signs in maternal, neonatal and children’s health
 
Table III.B.5 Warning signs in maternal, neonatal and children’s health
Results
Code Indicator
12 Percentage of women who recognize at least two warning signs in pregnancy 71.3%
13 Percentage of women who had warning signs in pregnancy 
Of those who mentioned recognizing at least one warning sign
43.7%
14 Percentage of women who sought counseling or treatment because of a warning sign during pregnancy 90.4%
14a Where the counseling was sought
14a1 Hospital, Health Center/Post, Private Clinic 86.8%
14a2 MSPAS Health promotion convergence center, midwife 37.4%
15 Percentage of women who recognize at least two neonatal or newborn danger signs (under 28 days) 61.1%
16
Percentage of women who confirm having had a newborn with danger signs
Of those who mention recognizing at least one sign
46.7%
0% 20% 40% 60% 80% 100%
Exclusive breastfeeding < 6 months
Breastfeeding < 6 months
Have been breastfed 6-24 months
Being breastfed 6-24 months
Began complimentary feeding at 6
months
MYAP 2011 Final Evaluation 
Results 
43
Table III.B.5 Warning signs in maternal, neonatal and children’s health
Results
Code Indicator
17 Percentage of women who confirm seeking treatment when their newborn demonstrated danger signs 96.2%
17a Where they sought treatment
17a1 Hospital, Health Center/Post, Private Clinic 87.6%
17a2 MSPAS Health promotion convergence center, midwife 20.9%
18
Percentage of women who recognize at least two warning signs that indicate that the child needs 
medical treatment when ill 
75.4%
19
Percentage of mothers who confirm that one of their children has shown warning signs during illness 
Of those who mention recognizing at least one sign
75.3%
20
Percentage of women who confirm having sought treatment when their child demonstrated warning 
signs
98.7%
20a Where they sought treatment
20a1 Hospital, Health Center/Post, Private Clinic 90.9%
20a2 MSPAS Health promotion convergence center, midwife 18.1%
III.B.5 Warning signs in maternal, neonatal and children’s health
Main Findings: 
The study found that 71.3% of women recognize at least two warning signs in pregnancy. Of those who 
recognize at least one sign, 43.7% mentioned having experienced one of the signs, and of them, 90.4% 
sought help (either counseling or treatment). A high percentage (86.8%) of these women sought 
assistance with qualified personnel (a hospital, health center/post or private clinic), and 37.4% sought 
assistance locally (in a convergence center, with a health promoter or with a midwife). 
The study also found that 61.1% of women recognize at least two warning signs in neonatal infant 
health. Of those who recognize at least one, 46.7% confirmed having witnessed a warning sign in their 
newborn, and almost all of these (96.2%) sought assistance. Of these, 87.6% sought assistance with 
qualified personnel (a hospital, health center/post or private clinic), while 20.9% sought assistance 
locally (in a convergence center, with a health promoter or with a midwife). 
Of the women surveyed, 75.4% recognize at least two warning signs when their child is ill. Of those who 
recognize at least one sign, 75.3% mentioned having witnessed a warning sign in their child, and of 
them, nearly all sought help (98.7%), seeking assistance mainly with qualified personnel (90.9%), while 
only 18.1% sought assistance locally. 
MYAP 2011 Final Evaluation 
Results 
44
Graph 8: Knowledge of warning signs in pregnancy, neonatal and children’s health 
0% 20% 40% 60% 80% 100%
Sought assistance locally
Sought assistance with qualified personnel
Experienced a warning sign in pregnancy
Recognizes at least two warning signs in
pregnancy
Sought assistance locally
Sought assistance with qualified personnel
Witnessed a warning sign in their newborn
Recognizes at least two warning signs in
neonatal health
Sought assistance locally
Sought assistance with qualified personnel
Witnessed a warning sign in their child
Recognizes at least two warning signs in
children's health
MYAP 2011 Final Evaluation 
Results 
45
III.B.6 Water Treatment
 
Table III.B.6 Water Treatment
Results Code Indicator
21
Percentage of families that practice some form of water treatment (boiling, chlorinating, filtering or 
using the SODIS method)
96.5%
Percentage of families who treat by:
21a Boiling 93.9%
21b Filtering 17.6%
III.B.6 Water Treatment 
Main Findings: 
The microbiological qualities of water are important to staying healthy. It has been demonstrated that 
when water is contaminated by pathogens associated with diarrhea, children’s nutritional health bears a 
significant negative impact. This is even more exacerbated when the pathogen is something as virulent 
as, for instance, cholera, which could be fatal. This is even more of a risk among vulnerable populations 
who are living in poverty and with poor nutritional health. Over the past few years in Guatemala, the 
Nutritional Institute for Central America and Panama (INCAP) has studied the relationship between 
diarrhea episodes in children and nutritional states, demonstrating how even non-severe diarrhea 
episodes that are frequently repeated over long periods of time can negatively affect children and their 
nutritional states. As one of the main vectors for these pathogens is contaminated water, it is very 
important to ensure that household drinking water is treated prior to consumption. This study found 
that 96.5% of families treat their water. Of these, 93.9% boil it, 17.6% filter it, 6% use the SODIS method, 
and 1.3% use chlorine (see Annex 1). 
MYAP 2011 Final Evaluation 
Results 
46
III.B.7 Agricultural and Livestock Practices
A total of 769 homes were selected, visited and then surveyed. Of this total, some of the families do not 
practice agricultural or livestock farming. Therefore, the sample sizes shown in this section are smaller 
than in previous sections. 
Table III.B.7 Agricultural and Livestock Practices
Results
Indicator Population 
WITH 
Agricultural 
Interventions
Population 
WITHOUT 
Agricultural 
Interventions 
Total 
Code Name Population
Agricultural Practices
Evaluated only among families who practice 
agriculture
22
Percentage of farmers who adopt at least two 
improved agricultural practices 41.1% 22.4% 30.9%
22a Adopted agricultural practices:
22a1
Percentage of farmers who adopt good storage 
practice (silos) 20.5% 21.3% 21.0%
22a3
Percentage of farmers who adopt the practice of 
organic fertilization 33.5% 25.0% 28.9%
22a4
Percentage of farmers who adopt the practice of crop 
diversification 36.1% 16.7% 25.6%
22a5
Percentage of farmers who adopt the practice of fruit 
tree management 43.9% 23.0% 32.6%
Livestock practices
Evaluated only among families who employ livestock 
practices
23
Percentage of farmers who adopt improved livestock 
practices (with fowl)
Meets the following two: 23a1 and 23b1
49.7% 34.9% 42.0% 
23a1
Percentage of farmers who enclose their livestock 
(fowl) 74.2% 64.4% 69.1%
23b1 Percentage of farmers who care for their livestock:
Fowl vaccinations 63.0% 51.6% 57.4%
24 Percentage of families who consume at least one food 
provided by their animal husbandry (fowl) 95.0% 88.3% 91.4 %
25
Percentage of farmers who sell at least one of the 
foods produced by their animal husbandry (fowl) 68.1% 70.7% 69.5%
Farming information, education and communication (considering 
individuals with agricultural and/or livestock practices )
26
Percentage of people who have received 
agricultural/livestock farming counseling 42.0% 15.8% 27.6%
27 Frequency of counseling:
27a Once a month 74.4% 50.7% 66.9%
28
The counseling received in the past year has been 
about:
28a Agricultural farming improvement 88.8% 81.0% 86.3%
28d Livestock farming improvement 89.6% 81.6% 87.1%
29
Who have provided the counseling in most recent 
years:
29a Organizations in support of farming or 84.7% 70.0% 80.0%
MYAP 2011 Final Evaluation 
Results 
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Table III.B.7 Agricultural and Livestock Practices
Results
Indicator Population 
WITH 
Agricultural 
Interventions
Population 
WITHOUT 
Agricultural 
Interventions 
Total 
Code Name Population
commercialization 
III.B.7 Agricultural and Livestock Practices 
Main Findings: 
Given that the majority of communities in SHARE’s coverage area practice agricultural farming, good 
practices are to be expected even areas without the agricultural and productive component of SHARE’s 
program. This is clear in Tables III.B.7 and III.C.7 (see Annex 1), as they show that good practice is found 
both in areas that benefit from the agricultural component as well as in areas that did not. The same is 
true for education in agricultural and livestock topics. However, the benefits of the program in areas 
with agricultural and productive interventions is clear, as the percentage of farmers who have adopted 
at least two improved agricultural practices is significantly higher in communities with the interventions 
(41.1%) than in communities without the interventions (22.4%). This is due to the positive reception 
and implementation of the practices introduced by the program. A farmer who lives in communities 
with the agricultural intervention is 2.42 times more likely (odds ratio) to adopt improved agricultural 
practices than one who lives in a community without the intervention. This reflects the high adoption 
rates of two of the introduced practices. One is crop diversification, for which the rate of farmers is 
much higher (P<0.05) in communities with the agricultural intervention (36.1%) than in those without 
(16.7%). The other is adoption of fruit tree management, for which the rate of adoption is 43.9% among 
communities with the intervention compared to 23% in communities without the intervention. 
MYAP 2011 Final Evaluation 
Results 
48
Graph 9: Agricultural and Livestock Practices 
Livestock practices are limited in people who have adopted an animal for the purpose of raising it. In this 
case, SHARE has promoted and motivated people to raise fowl. Therefore, this is the type of animal 
husbandry in practice among all of the families. Of this total, less than half (218) live in the communities 
in which SHARE has developed livestock farming activities. The study found that 49.7% of those who 
own fowl and who live in communities where the farming intervention is implemented have adopted 
two good practices: enclosure of their animals (fowl), and caring for them (vaccinations). These rates are 
significantly lower (P<0.05) in areas where the farming interventions are not implemented, as only 34% 
in these latter communities have adopted these practices. A farmer who breeds fowl and lives in a 
community where the program implements the farming interventions is 1.84 times more likely (odds 
ratio) to implement these two practices than one who lives in a community without farming 
interventions. The adoption of both practices is important, not only because they help to ensure 
productivity, but also because they maintain a cleaner and healthier home environment. 
Adoption of the improved practices is a reflection of the educational processes involved in the program. 
The rates of people who have received agricultural and livestock farming counseling is significantly 
higher (P<0.05) in communities that have participated in the program’s farming interventions, compared 
to rates in areas where the farming interventions were not implemented. It is further important to note 
that this counseling is more frequent in areas where the farming intervention is implemented. The 
0% 10% 20% 30% 40% 50% 60% 70% 80% 90%100%
Adopt at least two improved agricultural practices
Adopt storage practices
Adopt organic fertilization
Adopt crop diversification
Adopt fruit tree management
Adopt good livestock practices
Enclose their animals
Care for their animals
Consume animal husbandry products
Sell animal husbandry products
Total Without Agriculture With Agriculture
MYAP 2011 Final Evaluation 
Results 
49
majority of the farmers (88.8%) confirm that this counseling has been provided by organizations that 
support farming and commercialization, such as SHARE. Lastly, it is worth mentioning that, because the 
sampling for this study was based on the total population, and not on participants, it is highly probable 
that the indicators are not met by 100% because of the farmers surveyed who do not participate in the 
program. 
III.B.8 Income Improvement (Formal Marketing)
The data for this table was obtained through a sub-sampling of the original sample. This was achieved by 
evaluating all of the participants in marketing or income improvement activities that were found within 
the five communities selected for this study. 
 
Table III.B.8 Income Improvement (Formal Marketing)
Code Indicator Results
30
Percentage of farmers who adopt two formal marketing processes
(ind30a1 and/or Ind30a2) 86.7%
30b
Percentage of farmers who adopt two formal marketing processes
(ind30a1 and Ind30a2) 86.7%
Formal marketing practices employed:
30a1
Percentage of farmers who calculate production and/or commercialization 99.0%
30a2 Percentage of farmers who record production and/or commercialization 86.7%
30b1 
Percentage of farmers who calculate production and commercialization 99.0%
31
Percentage of farmers that receive institutional technical assistance for formal 
marketing 97.2%
31a Types of businesses run by the farmers:
31a1 Agricultural 100%
31a2 Livestock 2.8%
31b Family business 3.5%
32
Percentage of farmers who implement production and/or commercialization 
planning 96.5%
32b Percentage of farmers who implement production and commercialization planning 85.4%
Places where their products are sold:
32a1 Communal Market 12.7%
32a2 Municipal Market 12.7%
32a3
Regional market, Guatemala City wholesaler, middleman, export market 86.6%
MYAP 2011 Final Evaluation 
Results 
50
Table III.B.8 Income Improvement (Formal Marketing)
Code Indicator Results
33
Percentage of farmers who express having had problems that affected his or her 
business 72.0%
33a Type of problem:
33a1 Lack of marketing or advising 38.3%
33a2 Lack of money, capital or raw materials 33.5%
III.B.8 Income Improvement 
Main Findings: 
Unlike the previously reported indicators that were evaluated among the general population, the 
income improvement indicator was evaluated with a small sample of participants in marketing 
intervention. Thus, a total of 49 people were surveyed. The study found that 100% of these individuals 
had an agricultural type of business, and very few of them (5%) had other types of businesses. 
In terms of activities related to income improvement, 86.7% of those surveyed had adopted two formal 
marketing practices. These were “calculating production and commercialization” and “recording 
production and commercialization”. 85.4% implement production and commercialization planning. Most 
of these (86.6%) sell their products in markets outside of their communities, seeking larger markets 
(regional markets, wholesalers in Guatemala City and export markets). 
72% of these farmers stated that they had had some kind of problem that had affected their business, 
including a lack in marketing/counseling (38.3%) and lack of capital / raw materials (33.5%). 
Graph 10: Formal Marketing Practices 
75% 80% 85% 90% 95% 100%
Adopt two formal marketing practices
Calculate production/commercialization
Record production / commercialization
Receive technical assistance
Implement production/commercialization…
MYAP 2011 Final Evaluation 
Results 
51
III.B.9 Capacity Building (Risk Management)
Within its commitments, one of SHARE’s goals is to ensure that 84 of the communities that participate 
in the IFS Program have an early warning and alert system for potential food insecurity. In order to 
gauge the scope of this goal, the units analyzed are the communities rather than the women, men and 
children that have been evaluated for the other indicators. The sample of 31 communities visited is 
representative of the total number of communities in SHARE’s IFS Program. 
SHARE has implemented the methodology of sentinel sites in the risk mitigation intervention. One 
sentinel site located in a community reflects the food and nutritional security status of the other 
communities it covers. SHARE has implemented a total of 12 sentinel sites. Thus, a total of 84 
communities should be covered in accordance with the goal of these 12 sentinel sites. However, the IFS 
Program monitoring and evaluation system registers that 91 communities are covered by the 12 sentinel 
sites18. In order to evaluate the results, the consultant calculated the average number of communities 
that should be covered per sentinel site, being 84/12 = 7 communities per sentinel site; and 
subsequently calculated the same average within the sampled communities. 
SHARE’s progress in building local capacities (risk management) is examined in detail with the results of 
the indicators described below. 
Indicators and respective results: 
Number of communities that have participated in risk management activities, per active 
sentinel site
Table III.b.9a (Annex 1), shows that three sentinel sites were found in the 31 sampled 
communities and their function was verified and confirmed. Additionally, Table III.b.9 (Annex 1) 
shows that 18 communities have received trainings regarding community risk management. 
This is equal to 58.1% of the communities visited, and considering the confidence interval this 
rate may be as low as 39% or as high as 75%. 
Of the 31 communities evaluated, 18 have participated in risk management through sentinel 
site coverage. This information yields a calculated average of communities covered per sentinel 
site: 18 / 3 = 6. Considering the confidence interval of 95%, this means that there are 4 to 7.75 
communities covered per sentinel site. Based on the confidence interval, it may be concluded 
 
18 Information provided by SHARE directly to the consultant 
MYAP 2011 Final Evaluation 
Results 
52
that SHARE has met its goal of having an average of 7 communities covered per sentinel site, 
which translates to meeting the goal of 84 communities covered program-wide. The estimated 
total value based on sampled communities is 72, with a confidence interval ranging from 48 to 
93 communities. This interval includes the target value. Further, SHARE’s monitoring system 
reports a total of 91 communities covered. 
Number of communities that have participated in activities related to an early warning and 
alert system for potential food insecurity. 
Table III.b.9 (Annex 1) shows that 13 communities have participated in activities related to an 
early warning and alert system for potential food insecurity. This means 41.9% of the 
communities visited and 72% of communities that have been covered by sentinel sites. This 
reflects the communities’ acceptance, awareness and ownership of the early warning and alert 
system for potential food insecurity. 
III.B.9 Capacity Building (Risk Management) 
Main Findings: 
SHARE has met the goal of providing 84 communities with an early warning and alert system for 
potential food insecurity. The three sentinel sites evaluated demonstrate community leaders’ effective 
performance with regards to risk management training, managing the community monitoring bulletin 
board, use of the respective notebook, and use of the rainwater gauge, all relevant to the performance 
of the Monitoring Systems and Early Warning for Food and Nutritional Security. Further, according to 
SHARE’s monitoring and evaluation system19, 91 communities are now monitored by 12 sentinel sites. 
 
19 Verbal information provided by SHARE to the consultant. 
MYAP 2011 Final Evaluation 
Conclusions 
53
Based on the findings here presented, the study has drawn the following conclusions: 
1. This study demonstrates that SHARE has performed well in terms of meeting the goals 
of its various interventions. 
2. There has been a significant improvement in the nutrition and health indicators for the 
communities in which the IFS Program was implemented, as compared to the baseline 
findings, with the exception of the exclusive breastfeeding indicator. Among them, the 
following stand out: 
a. Reduction of chronic malnutrition in children under five by 6.8%.
b. Reduction of general malnutrition in children under 36 months by 8.3% 
c. Improvements in the recognition of warning signs in pregnancy, neonatal and 
children’s health
d. Adoption of improved health and nutrition practices 
e. Increased family dietary diversity 
3. In the communities where SHARE implements its agricultural and livestock farming 
interventions, there was a significant increase in the adoption of good agricultural and 
livestock farming practices as compared to the baseline findings. This could explain the 
increase in family dietary diversity and in maintaining a reduced incidence of months of 
food scarcity. 
4. At the community level, risk management has been implemented in the number of 
communities established in the indicator goal. In these communities, the COCODEs 
confirm being knowledgeable in the topic of Disaster Risk Management, and Project 
Profiles. They also confirm having the necessary tools to manage community projects. 
MYAP 2011 Final Evaluation 
Annexes 
54
1. Design effects on MYAP 2011 Indicators 
Databases (annexed documents) 
2. Folder with the original EPI INFO databases (REC Files) 
3. Folder with the EPI INFO databases that contain the indicators (REC files), as well as the programs with which they were constructed 
(PGM files) 
MYAP 2011 Final Evaluation 
Annex 1 
55
ANNEX 1: III.C Detailed 2011 Results. 
III.C.1 Anthropometrics in children under five:
Table III.C.1a Anthropometrics in children under five
Results
Indicator
Population WITH the 
agricultural intervention
Population WITHOUT the 
agricultural intervention Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Anthropometrics according to NCHS standards
1a
Percentage of children under 5 with chronic malnutrition (Z 
< -2SD height/age)
389
(223)
58.1% 
(49.9, 66.4)
645
(375)
56.4%
(48.0, 64.8)
1034
(598)
57.2% 
(51.2, 63.1)
1a
Percentage of children of 6 to 59.99 moths with < -2.0 SD 
height/age) NCHS
342
(217)
64.9%
(54.3, 75.5)
587
(367)
60.6%
(52.6, 68.7)
929
(584)
62.5% 
(55.9, 69.0)
1a1
Average Z score for height/age in children under five 389 -2.22 SD 
(-2.41, -2.03)
645 -2.11 SD
(-2.29, -1.93)
1034 -2.16 SD
(-2.29, -2.03)
1a1
Average Z score for height/age in children of 6 to 59.99 
months
342 -2.36 DE 
(-2.59, -2.12)
587 -2.22 DE
(-2.39, -2.06)
929 -2.28 DE
(-2.42, -2.14)
2a
Percentage of children under 5 with general malnutrition 
(Z < -2SD weight/age)
389 
(107)
27.5% 
(20.0, 35.0)
647 
(202)
30.4% 
(25.4, 35.4)
1036 
(309)
29.1%
( 24.8, 33.5)
2a1
Average Z score for weight/age in children under five 389 -1.32 SD
(-1.44, -1.20)
647 -1.40 SD 
( -1.57, -1.23)
1036 -1.37 SD
(-1.47, -1.26)
3a
Percentage of children under 5 with acute malnutrition (Z < 
-2SD weight/height 
387 
(1)
0.3%
(0.0, 0.9)
645
(17)
2.86% 
(0.1, 5.7)
1032
(18)
1.7% 
(0.1, 3.3)
3a1
Average Z score for weight/height in children under five 387 0.09 SD
(-0.16, 0.34)
645 -0.11 SD
(-0.25, 0.03)
1032 -0.02 SD 
(-0.16, 0.01)
Anthropometrics according to WHO standards
1b
Percentage of children under 5 with chronic malnutrition (Z 
< -2SD height/age)
389
(264)
69.3%
(62.1, 76.5)
648
(422)
62.9%
(55.1, 70.9)
1037
(686)
65.8%
(60.3, 70.2)
1b1
Average Z score for height/age in children under five 389 -2.38 SD
(-2.60, -2.16)
648 -2.32 SD
(-2.51, -2.13)
1037 -2.35 SD
(-2.49, -2.20)
MYAP 2011 Final Evaluation 
Annex 1 
56
Table III.C.1a Anthropometrics in children under five
Results
Indicator
Population WITH the 
agricultural intervention
Population WITHOUT the 
agricultural intervention Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
2b
Percentage of children under 5 with general malnutrition 
(Z < -2SD weight/age)
391
(80)
20.4% 
(15.2, 25.7)
648
(158)
23.6%
(18.8, 28.3)
1039 
(238)
22.2% 
(18.7, 25.7)
2b1
Average Z score for weight/age in children under five 391 -1.17 SD
(-1.36, -0.98)
648 -1.24 SD
(-1.41, -1.06)
1039 -1.21 SD
(-1.34, -1.08)
3b
Percentage of children under 5 with acute malnutrition (Z < 
-2SD weight/height 
389
(4)
1.2% 
(0.0, 3.4)
648
(18)
3.0%
(0.2, 5.8)
1037 
(22)
2.2% 
(0.2, 4.1)
3b1
Average Z score for weight/height in children under five 389 0.32 SD 
(-0.10, 0.73)
648 0.13 SD
(-0.01, 0.28)
1037 0.22 SD
(-0.26, 0.62)
Table III.C.1b Anthropometrics in children under five by age 
groups
Results
Indicator
0 to < 36 months 36 months to < 60 months
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Anthropometrics according to NCHS standards
1a
Percentage of children under 5 with chronic malnutrition (Z < -2SD 
height/age)
670
(347)
50.5%
(44.8, 56.2)
370
(254)
68.9%
(60.8, 76.9)
1a1
Average Z score for height/age in children under five
670 -2.00 SD
(-2.14, -1.86)
370 -2.44
(-2.62, -2.27)
2a
Percentage of children under 5 with general malnutrition (Z < -2SD 
weight/age)
673
(194)
26.7%
(21.7, 31.8)
369
(117)
33.4%
(25.6, 41.2)
2a1
Average Z score for weight/age in children under five
673 -1.22 SD
(-1.33, -1.11)
369 -1.62 SD
(-1.77, -1.46)
3a Percentage of children under 5 with acute malnutrition (Z < -2SD 669 0.5% 369 3.9%
MYAP 2011 Final Evaluation 
Annex 1 
57
Table III.C.1b Anthropometrics in children under five by age 
groups
Results
Indicator
0 to < 36 months 36 months to < 60 months
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
weight/height (6) (0.0, 1.0) (12) (0.0, 8.0)
3a1
Average Z score for weight/height in children under five
669 0.09 SD
(-0.05, 0.23)
369 -0.22 SD
(-0.40, -0.03)
Anthropometrics according to WHO standards
1b
Percentage of children under 5 with chronic malnutrition (Z < -2SD 
height/age)
674
(412)
60.0% 
(54.6, 65.5)
369
(278)
75.9% 
(68.4, 83.3)
1b1
Average Z score for height/age in children under five
674 -2.22 SD
(-2.40, -2.03)
369 -2.57 SD
(-2.74, 2.40)
2b
Percentage of children under 5 with general malnutrition (Z < -2SD 
weight/age)
676
(137)
18.7% 
( 15.2, 22.1)
369 
(101)
28.3%
(20.9, 35.8)
2b1
Average Z score for weight/age in children under five
676 -1.03 SD
(-1.17, -0.90)
369 -1.52 SD
(-1.69, -1.35)
3b
Percentage of children under 5 with acute malnutrition (Z < -2SD 
weight/height 
674
(9)
1.0% 
(0.0, 2.0)
369 
(13)
4.2%
(0.0, 8.5)
3b1
Average Z score for weight/height in children under five
674 0.32 SD
(0.12, 0.51)
369 0.04 SD
(-0.23, 0.31)
MYAP 2011 Final Evaluation 
Annex 1 
58
Table III.C.1c Anthropometrics in children under five by sex
Results
Indicator
Boys/Girls Girls
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Anthropometrics according to NCHS standards
1a
Percentage of children under 5 with chronic malnutrition (Z < -2SD 
height/age)
520
(301)
59.1%
(51.5, 66.8)
520
(300)
55.0%
(49.6, 60.4)
1a1
Average Z score for height/age in children under five
520 -2.13 SD
(-2.27, -1.99)
520 -2.18 SD
(-2.33, -2.03)
2a
Percentage of children under 5 with general malnutrition (Z < -2SD 
weight/age)
521
(148)
27.3% 
(21.7, 32.8)
521
(163)
30.9%
(26.5, 35.3)
2a1
Average Z score for weight/age in children under five
521 -1.32 SD
(-1.47, -1.17)
521 -1.41 SD
(-1.50, -1.31)
3a
Percentage of children under 5 with acute malnutrition (Z < -2SD 
weight/height 
520
(6)
1.0% 
(0.0, 2.2)
518
(12)
2.4%
(0.0, 4.9)
3a1
Average Z score for weight/height in children under five
520 0.01 SD
(-0.16, 0.17)
518 -0.05 SD
(-0.20, 0.11)
Anthropometrics according to WHO standards
1b
Percentage of children under 5 with chronic malnutrition (Z < -2SD 
height/age)
524
(352)
68.5% 
(62.1, 74.9)
519
(338)
62.7%
(57.6, 67.9)
1b1
Average Z score for height/age in children under five
524 -2.35 SD
(-2.54, -2.17)
519 -2.33 SD
(-2.48, -2.18)
2b
Percentage of children under 5 with general malnutrition (Z < -2SD 
weight/age)
524
(119)
21.5% 
(16.7, 26.4) 521 (119) 22.7% 
(18.6, 26.7)
2b1
Average Z score for weight/age in children under five
524 -1.18 SD
(-1.38, -0.98)
521 -1.23 SD
(-1.33, -1.13)
3b
Percentage of children under 5 with acute malnutrition (Z < -2SD 
weight/height 
524
(10)
1.9% 
(0.0, 4.0) 519 (12) 2.4% 
(0.0, 4.9)
3b1
Average Z score for weight/height in children under five
524 0.24 SD
(-0.05, 0.53)
519 0.19 SD
(0.03, 0.36)
MYAP 2011 Final Evaluation 
Annex 1 
59
III.C.2 Family Dietary Diversity and Family Food Scarcity
 
Table III.C.2 Family Dietary Diversity and
Family Food Scarcity
Results
Indicator
Populations WITH 
Agricultural Interventions
Populations WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Family Dietary Diversity
4
Average Dietary Diversity Score
(average number of groups consumed)
295 7.5 groups
(7.3, 7.7)
474 7.0 groups
(6.8, 7.3)
769 7.3 groups
(7.1, 7.4)
4a Percentage of families who ate from the group:
4a1 A: Cereals
295
(295)
100%
(-)
474
(473)
99.9%
(99.3, 100)
769
(768)
99.9%
(99.9, 100)
4a2 B: Roots and tubers
295
(174)
58.7%
(54.5, 62.7)
474
(277)
58.7%
(48.6, 68.9)
769
(451)
58.7%
(52.3, 64.6)
4a3 C: Vegetables
295
(133)
48.0%
(42.0, 54.0)
474
(202)
42.2%
(37.0, 47.5)
769
(335)
44.8%
(40.9, 48.7)
4a4 D: Fruits
295
(206)
71.9%
(66.7, 77.1)
474
(312)
67.5%
(63.1, 72.0)
769
(518)
69.5%
(66.2, 72.8)
4a5 E: Meat, chicken and offal
295
(136)
41.5%
(34.5, 48.4)
474
(213)
40.3%
(33.4, 47.3)
769
(349)
40.8%
(35.9, 45.8)
4a6 F: Eggs
295
(194)
66.8%
(56.0, 77.5)
474
(267)
54.5%
(47.3, 61.7)
769
(461)
60.0%
(53.4, 66.6)
MYAP 2011 Final Evaluation 
Annex 1 
60
Table III.C.2 Family Dietary Diversity and
Family Food Scarcity
Results
Indicator
Populations WITH 
Agricultural Interventions
Populations WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
4a7 G: Fish and seafood
295
(13)
4.5%
(2.1, 7.0)
474
(13)
1.8%
(0.9, 2.7)
769
(26)
3.0%
(1.8, 4.2)
4a8 H: Legumes / leguminous plants / dried fruits
295
(234)
78.9%
(73.9, 83.9)
474
(348)
71.3%
(66.7, 75.9)
769
(582)
74.7%
(71.2, 78.2)
4a9 I: Milk or dairy products
295
(69)
23.1%
(16.1, 30.1)
474
(99)
20.6%
(13.8, 27.4)
769
(168)
21.7%
(16.9, 26.5)
4a10 J: Oils / fats 295
(229)
82.3%
(74.1, 90.4)
474
(353)
77.0%
(69.6, 84.9)
769
(582)
79.3%
(73.8, 84.9)
4a11 K: Sugar / honey 295
(288)
98.1%
(96.3, 100)
474
(452)
97.5%
(95.8, 99.2)
769
(740)
97.8%
(96.6, 99.0)
4a12 L: Various foods
295
(233)
76.6%
(72.4, 80.7)
474
(355)
72.3%
(66.7, 77.9)
769
(588)
74.2%
(70.6, 77.8)
Family food scarcity
5
Average number of months with adequate food 
provisioning in the home 295 11.1 months
(10.8,11.4) 474 10.9 months
(10.6,11.2) 769 11.0 months
(10.8,11.2)
5a
Foods that became scarce :
5a1 A: Corn
295
(98)
32.8%
(25.6,40.1)
474
(149)
29.3%
(21.6,36.9)
769
(247)
30.9%
(25.6,36.1)
5a2 B: Beans
295
(82)
26.9%
(22.8,31.1)
474
(135)
23.3%
(14.9,31.7)
769
(217)
24.9%
(19.9,29.9)
5a3 C: Produce
295
(16)
5.5%
(0.6,10.3)
474
(55)
10.5%
(5.7,15.3)
769
(71)
8.3%
(4.7,11.8)
5a4 D: Greens 295 1.5% 474 4.8% 769 3.4%
MYAP 2011 Final Evaluation 
Annex 1 
61
Table III.C.2 Family Dietary Diversity and
Family Food Scarcity
Results
Indicator
Populations WITH 
Agricultural Interventions
Populations WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
(6) (0.0,3.6) (26) (3.2,6.5) (32) (1.9,4.8)
5a5 E: Sugar
295
(59)
19.9%
(12.5,27.3)
474
(117)
24.5%
(16.5,32.6)
769
(176)
22.5%
(16.8,28.2)
5a6 F: Oil
295
(15)
6.4%
(3.5,9.3)
474
(24)
5.7%
(2.3,9.0)
769
(39)
6.0%
(3.8,8.2)
5a7 G: Rice
295
(33)
12.0%
(10.1,14.0)
474
(71)
15.2%
(11.2,19.1)
769
(104)
13.8%
(11.3,16.2)
5a8 H: Eggs
295
(22)
6.01%
(1.4,10.7)
474
(26)
5.9%
(4.0,7.9)
769
(48)
6.0%
(3.6,8.3)
5a9 I: Meat
295
(37)
11.6%
(6.6,16.6)
474
(71)
16.2%
(9.5,22.9)
769
(108)
14.2%
(9.7,18.6)
5a10 J: Other
295
(13)
4.6%
(2.3,7.0)
474
(34)
8.0%
(3.8,12.3)
769
(47)
6.5%
(3.9,9.1)
5b Reasons for food scarcity:
5b1 A: Lack of money
295
(87)
29.7%
(26.3,33.1)
474
(173)
35.0%
(25.2,44.9)
769
(260)
32.7%
(27.0,38.4)
5b2 B: Lack of employment
295
(76)
26.4%
(18.1,34.7)
474
(131)
27.6%
(18.9,36.3)
769
(207)
27.0%
(20.9,33.1)
5b3 C: Large family
295
(9)
2.8%
(0.0,6.0)
474
(12)
2.4%
(0.6,4.1)
769
(21)
2.6%
(0.9,4.3)
5b4 D: Distant market/ food supply store 295
(3)
1.5%
(0.0,3.2)
474
(5)
1.2%
(0.2,2.2)
769
(8)
1.4%
(0.4,2.3)
5b5 E: There were no crops
295
(45)
13.6%
(8.2,19.0)
474
(83)
15.2%
(12.4,18.0)
769
(128)
14.5%
(11.6,17.4)
MYAP 2011 Final Evaluation 
Annex 1 
62
Table III.C.2 Family Dietary Diversity and
Family Food Scarcity
Results
Indicator
Populations WITH 
Agricultural Interventions
Populations WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
5b6 F: The harvest was lost
295
(25)
9.2%
(3.8,14.6)
474
(25)
5.5%
(2.9,8.1)
769
(50)
7.2%
(4.4,10.0)
5b7 G: Food too expensive
295
(6)
1.5%
(0.0,3.5)
474
(25)
4.7%
(1.8,7.5)
769
(31)
3.2%
(1.3,5.2)
5b8 H: Other
295
(5)
1.2%
(0.0,3.0)
474
(5)
1.3%
(0.0,2.5)
769
(10)
1.2%
(0.1,2.3)
6
Average Reduced Severity Index20
"What did you do for food during the months of 
scarcity"
295 1.7 points
(1.4,2.0) 474 1.8 points
(1.4,2.2) 769 1.7 points
(1.5,2.0)
6a What was done for food in the months of scarcity
6a1 A: Sold an item
295
(13)
3.5%
(0.9,6.1)
474
(34)
5.8%
(0.9,10.7)
769
(47)
4.7%
(1.8,7.7)
6a2 B: Sold animals
295
(37)
14.6%
(11.7,17.4)
474
(60)
14.2%
(9.0,19.4)
769
(97)
14.4%
(11.2,17.5)
6a3 C: Sold land
295
(2)
0.4%
(0.0,1.0)
474
(1)
0.0%
(0.0,0.1)
769
(3)
0.2%
(0.0,0.5)
6a4 D: Borrowed
295
(40)
13.6%
(9.4,17.7)
474
(83)
17.2%
(12.0,22.3)
769
(123)
15.6%
(12.0,19.1)
6a5 E: Some of the children had to work
295
(11)
4.3%
(1.4,7.1)
474
(17)
3.1%
(1.0,5.1)
769
(28)
3.6%
(1.9,5.3)
 
20 "Severity Index" known as the Coping Strategies Index (CSI). This index has been studied to a greater degree in Africa and was created by the World Food Program (WFP) 
Assisted Refugees in Western Tanzania. The index is presented in a document drafted by several organizations in 200820, and is defined as the sum of considered adaptations (or 
strategies used to confront food crises). In Guatemala, JMatute-CIENSA has calculated the index for UNICEF and World Vision. The index has a scale of 0-20 points, where “0” 
means that no strategy was employed and “20” is the maximum severity having employed all of the checked strategies. 
MYAP 2011 Final Evaluation 
Annex 1 
63
Table III.C.2 Family Dietary Diversity and
Family Food Scarcity
Results
Indicator
Populations WITH 
Agricultural Interventions
Populations WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
6a6 F: Someone in the family went elsewhere for work
295
(64)
21.5%
(14.0,29.0)
474
(125)
21.3%
(14.9,27.6)
769
(189)
21.4%
(16.5,26.2)
6a7 G: Reduced the number of daily meals
295
(15)
4.0%
(1.5,6.5)
474
(21)
5.4%
(2.6,8.2)
769
(36)
4.8%
(2.8,6.8)
6a8 H: Other
295
(14)
4.3%
(0.0,9.5)
474
(17)
5.2%
(0.9,9.4)
769
(31)
4.8%
(1.4,8.1)
III.C.3 Information, education and communication in health and nutrition
 
Table III.C.3 Information, education and communication 
in health and nutrition
Results
Indicator
Population WITH Agricultural 
Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
7
Percentage of women who confirm having received health 
and nutrition counseling in the preceding month
295
(171)
57.7%
(51.7, 63.7)
474
(315)
68.1%
(55.0, 81.1)
769
(486)
63.4%
(55.7, 71.2)
7a
Percentage of women who confirm having received 
counseling from MSPAS staff and/or from the IFS Program 
295
(167)
56.7%
(51.5, 61.8)
474
(308)
66.4%
(53.7, 79.1)
769
(475)
62.0%
(54.7, 69.4)
Women received counseling from:
7a1 A: MSPAS health staff 295 17.4% 474 25.0% 769 21.6%
MYAP 2011 Final Evaluation 
Annex 1 
64
Table III.C.3 Information, education and communication 
in health and nutrition
Results
Indicator
Population WITH Agricultural 
Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
(54) (11.1, 23.8) (96) (17.6, 32.4) (150) (16.5, 26.8)
7a2 B: IFS Program community staff
295
(138)
48.2%
(45.0, 62.6)
474
(253)
52.5%
(42.3, 62.6)
769
(391)
50.6%
(44.9, 56.3)
7a3 C: Families, neighbors or others
295
(14)
4.1%
(0.0, 8.3)
474
(24)
6.0%
(1.1, 10.9)
769
(38)
5.2%
(1.8, 8.6)
7b Topics dealt with in the counseling sessions:
7b1 A: Children’s health 295
(137)
44.0%
(35.0, 53.0)
474
(241)
54.3%
(42.6, 66.0)
769
(378)
49.7%
(41.9, 57.5)
7b2 B: Healthy pregnancy
295
(24)
8.8%
(3.3, 14.3)
474
(42)
10.2%
(3.9, 16.5)
769
(66)
9.6%
(5.3, 13.8)
7b3 C: Newborn health
295
(27)
8.8%
(4.1, 13.4)
474
(60)
13.5%
(9.3, 17.8)
769
(87)
11.4%
(8.2,14.6)
7b4 D: Food and nutrition
295
(141)
47.6%
(39.8, 55.4)
474
(264)
58.9%
(48.3, 69.5)
769
(405)
53.8%
(46.8, 60.9)
7b5 E: Household hygiene
295
(99)
35.7%
(31.7, 39.7)
474
(166)
36.4%
(27.1, 45.8)
769
(265)
36.1%
(30.6, 41.6)
7b6 D: Water treatment and care
295
(44)
15.8%
(11.6, 20.0)
474
(95)
21.3%
(12.4, 30.2)
769
(139)
18.8%
(13.6, 24.1)
7c Ways that messages or counseling were transmitted:
7c1 A: Counseling
295
(59)
15.8%
(5.0, 26.7)
474
(152)
35.9%
(24.2, 47.6)
769
(211)
26.9%
(18.1, 35.7)
7c2 B: Educational meetings and/or demonstrations
295
(153)
52.2%
(44.5, 60.0)
474
(265)
56.8%
(46.2, 67.5)
769
(418)
54.8%
(47.9, 61.6)
MYAP 2011 Final Evaluation 
Annex 1 
65
Table III.C.3 Information, education and communication 
in health and nutrition
Results
Indicator
Population WITH Agricultural 
Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
7c3 C: Home visits
295
(24)
8.6%
(5.5, 11.7)
474
(35)
6.1%
(1.6, 10.6)
769
(59)
7.2%
(4.3, 10.1)
7c4
D: Public media (radio, posters, fliers, billboards, TV, 
loudspeaker)
295
(33)
10.0%
(2.9, 17.1)
474
(47)
9.6%
(2.0, 17.3)
769
(80)
9.8%
(4.5, 15.1)
III.C.4 Child Feeding
 
Table III.C.4 Child feeding
Results
Indicator
Population WITH 
Agricultural Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Breastfeeding in infants under 6 months
8
Percentage of infants from 0 to < 6 months that were 
exclusively breastfed in the preceding 24 hours 
47
(36)
80.2%
(67.1, 93.3)
59
(41)
68.9%
(54.9, 83.0)
106
(77)
74.7%
(64.4, 85.0)
8a
Percentage of women with infants aged 0 to < 6 months who 
are breastfeeding
47
(47)
100%
(-)
59
(58)
95.5%
(86.4, 100)
106
(105)
97.8%
(93.4, 100)
Feeding in children aged 6 to 24 months
9
Percentage of women with children aged 6 to < 24 months 
who have breastfed their children
108
(104)
94.4%
(90.5, 98.2)
242
(231)
95.0%
(91.2, 98.8)
350
(335)
94.8%
(92.0,98.0)
9a
Percentage of women with children aged 6 to < 24 months 
who are breastfeeding their children
108
(95)
85.8%
(78.5, 93.0)
242
(188)
76.0%
(70.6, 81.4)
350
(283)
79.6%
(75.4, 83.8)
10
Percentage of mothers or caregivers of children aged 6 to < 
24 months who know about and practice good weaning / 
108
(99)
91.7%
(88.0, 95.4)
242
(206)
84.4%
(79.9, 88.9)
350
(305)
87.1%
(83.8, 90.3)
MYAP 2011 Final Evaluation 
Annex 1 
66
Table III.C.4 Child feeding
Results
Indicator
Population WITH 
Agricultural Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
complimentary feeding practices (having started 
complimentary feeding when the child was six months old) 
10a
Average age in which children aged 6 to < 24 months started 
complimentary feeding 105 6.5 months
(6.4, 6.6) 232 6.6 months
(6.3, 6.8) 337 6.6 months
(6.4, 6.8)
III.C.5 Warning signs in maternal, neonatal and children’s health 
 
Table III.C.5 Warning signs in maternal, neonatal and 
children’s health Results
Indicator
Population WITH Agricultural 
Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
12
Percentage of women who recognize at least two warning signs 
in pregnancy
295
(208)
67.7%
(56.6,78.7)
474
(341)
74.2%
(67.6,80.7)
769
(549)
71.3%
(65.0,77.6)
13
Percentage of women who had warning signs in pregnancy 
Of those who mentioned recognizing at least one warning sign
227
(111)
47.5%
(38.6,56.6)
379
(167)
41.0%
(33.9,48.1)
606
(278)
43.7%
(38.0,49.4)
14
Percentage of women who sought counseling or treatment 
because of a warning sign during pregnancy 
111
(100)
85.5%
(69.1,100)
167
(156)
94.6%
(91.0,98.2)
278
(256)
90.4%
(82.2,98.7)
14a Where the counseling was sought
14a1 Hospital, Health Center/Post, Private Clinic
100
(82)
84.7%
(74.2,95.1)
156
(131)
88.5%
(83.4,93.5)
256
(213)
86.8%
(81.4,92.2)
14a2 MSPAS Health promotion convergence center, midwife
100
(41)
37.2%
(13.3,61.0)
156
(58)
37.5%
(27.6,47.4)
256
(99)
37.4%
(25.5,49.2)
14a3 Other 100 2.4%
(0.0,5.4)
156 3.6%
(0.0,8.1)
256 3.1%
(0.2,5.9)
MYAP 2011 Final Evaluation 
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Table III.C.5 Warning signs in maternal, neonatal and 
children’s health Results
Indicator
Population WITH Agricultural 
Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
(3) (5) (8)
15
Percentage of women who recognize at least two neonatal or 
newborn danger signs (under 28 days)
295
(189)
58.8%
(44.9,72.6)
474
(293)
63.0%
(56.5,69.5)
769
(482)
61.1%
(53.8,68.5)
16
Percentage of women who confirm having had a newborn with 
danger signs
Of those who mention recognizing at least one sign
221
(108)
47.3%
(38.8,55.9)
347
(156)
46.2%
(40.4,52.1)
568
(264)
46.7%
(41.7,51.7)
17
Percentage of women who confirm seeking treatment when 
their newborn demonstrated danger signs
108
(104)
95.1%
(89.7,100)
156
(149)
97.0%
(94.9,99.2
264
(253)
96.2%
(93.5,98.9)
17a Where they sought treatment
17a1 Hospital, Health Center/Post, Private Clinic 104
(90)
88.2%
(83.2,88.2)
149
(127)
87.1%
(81.6,92.6)
253
(217)
87.6%
(83.9,91.2)
17a2 MSPAS Health promotion convergence center, midwife
104
(26)
21.0%
(14.6,27.3)
149
(31)
20.9%
(13.6,28.2)
253
(57)
20.9%
(16.0,25.9)
17a3 Other
104
(7)
5.4%
(0.8,10.0)
149
(13)
5.4%
(0.7,10.2)
253
(20)
5.4%
(2.1,8.8)
18
Percentage of women who recognize at least two warning signs 
that indicate that the child needs medical treatment when ill
295
(224)
75.6%
(68.0,83.3)
474
(363)
75.2%
(67.9,82.6)
769
(587)
75.4%
(70.1,80.8)
19
Percentage of mothers who confirm that one of their children 
has shown warning signs during illness 
Of those who mention recognizing at least one sign
252
(181)
74.1%
(69.5,78.6)
416
(311)
76.2%
(72.0,80.4)
668
(492)
75.3%
(72.0,80.4)
20
Percentage of women who confirm having sought treatment 
when their child demonstrated warning signs
181
(177)
97.2%
(94.5,99.9)
311
(309)
99.8%
(99.4,100)
492
(486)
98.7%
(97.4,100)
20a Where they sought treatment
20a1 Hospital, Health Center/Post, Private Clinic 177
(150)
86.4%
(78.1,94.8)
309
(280)
94.2%
(91.1,97.2)
486
(430)
90.9%
(87.1,94.7)
20a2 MSPAS Health promotion convergence center, midwife 177 20.7% 309 16.1% 486 18.1%
MYAP 2011 Final Evaluation 
Annex 1 
68
Table III.C.5 Warning signs in maternal, neonatal and 
children’s health Results
Indicator
Population WITH Agricultural 
Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
(43) (12.1,29.3) (50) (10.9,21.3) (93) (13.4,22.7)
20a3 Other
177
(17)
8.5%
(1.7,15.4)
309
(21)
5.6%
(1.2,10.0)
486
(38)
6.8%
(3.0,10.7)
MYAP 2011 Final Evaluation 
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III.C.6 Water treatment
 
Table III.C.6 Water treatment
Results
Indicator
Population WITH Agricultural 
Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample 
Size 
(# of 
cases)
%
(95% CI)
Sample 
Size 
(# of cases)
%
(95% CI)
21
Percentage of families that practice some form of water 
treatment (boiling, chlorinating, filtering or using the SODIS 
method)
295
(286)
97.1%
(95.1,99.1)
474
(452)
96.0%
(94.0,98.1)
769
(738)
96.5%
(95.0,98.0)
Percentage of families who treat by:
21a Boiling
295
(277)
92.3%
(89.4,95.1)
474
(449)
95.2%
(93.0,97.3)
769
(726)
93.9%
(92.1,95.7)
21b Filtering
295
(44)
16.8%
(11.8,21.2)
474
(85)
18.2%
(11.7,24.7)
769
(129)
17.6%
(13.4,21.8)
21c Chlorinating
295
(2)
0.5%
(0.0,1.3)
474
(13)
1.9%
(0.4,3.3)
769
(15)
1.3%
(0.4,2.2)
21d SODIS
295
(19)
9.3%
(1.5,17.1)
474
(15)
3.3%
(1.3,5.2)
769
(34)
6.0%
(2.1,9.8)
MYAP 2011 Final Evaluation 
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70
III.C.7 Agricultural and Livestock Practices
Table III.C.7 Agricultural and Livestock Practices
Results
Indicator
Population WITH Agricultural 
Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Agricultural Practices
Evaluated only among families who practice agriculture 
22
Percentage of farmers who adopt at least two improved 
agricultural practices
262 
(101)
41.1% 
(35.9, 46.2)
415 
(93)
22.4% 
(14.1, 30.6)
677 
(194)
30.9% 
(25.5, 36.3)
22a Adopted agricultural practices:
22a1
Percentage of farmers who adopt good storage practice 
(silos)
262
(57)
20.5%
(10.5, 30.5)
415
(78)
21.3%
(11.3, 31.4)
677
(135)
21.0%
(13.8, 28.1)
22a3
Percentage of farmers who adopt the practice of organic 
fertilization 
262
(86)
33.5%
(27.3, 39.6)
415
(100)
25.0%
(16.1, 33.9)
677
(186)
28.9%
(23.3, 34.5)
22a4
Percentage of farmers who adopt the practice of crop 
diversification
262
(85)
36.1%
(29.2, 42.9)
415
(67)
16.7%
(8.8, 24.8)
677
(152)
25.6%
(19.8, 31.5)
22a5
Percentage of farmers who adopt the practice of fruit tree 
management
262
(107)
43.9%
(30.1, 57.7)
415
(92)
23.0%
(16.1, 29.3)
677
(199)
32.6%
(25.3, 39.9)
Livestock practices
Evaluated only among families who employ livestock practices
23
Percentage of farmers who adopt improved livestock 
practices (with fowl)
Meets the following two: 23a1 and 23b1
218
(116)
49.7%
(38.5, 60.9)
330
(117)
34.9%
(26.2, 43.6)
548
(233)
42.0% 
(35.5, 58.5)
23a1
Percentage of farmers who enclose their livestock (fowl) 218
(161)
74.2%
(66.7, 81.7)
300
(200)
64.4%
(54.5, 74.2)
548
(361)
69.1%
(63.3, 74.8)
23b1
Percentage of farmers who care for their livestock:
Fowl vaccinations
218
(149)
63.0%
(52.8, 74.6)
330
(181)
51.6%
(43.1, 60.0)
548
(330)
57.4
(50.6, 64.1)
24 Percentage of families who consume at least one food 225 95.0% 362 88.3% 587 91.4%
MYAP 2011 Final Evaluation 
Annex 1 
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Table III.C.7 Agricultural and Livestock Practices
Results
Indicator
Population WITH Agricultural 
Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
provided by their animal husbandry (fowl) (217) (90.9, 99.1) (325) (83.5, 93.1) (542) (88.2, 94.6)
25
Percentage of farmers who sell at least one of the foods 
produced by their animal husbandry (fowl)
225
(154)
68.1%
(60.1, 76.2)
362
(265)
70.7%
(59.1, 82.2)
587
(419)
69.5%
(62.2, 76.7)
Farming information, education and communication (considering individuals with agricultural and/or livestock practices )
26
Percentage of people who have received 
agricultural/livestock farming counseling 
294
(112)
42.0%
(35.0, 48.9)
468
(83)
15.8%
(8.4, 23.3)
762
(195)
27.6%
(21.7, 33.3)
27 Frequency of counseling:
27a Once a month
112
(78)
74.4%
(64.5, 84.3)
83
(42)
50.7%
(24.6, 66.7)
195
(120)
66.9%
(57.1, 76.7)
27b
At least once every two months
112
(10)
7.4%
(4.7, 9.7)
83
(14)
14.5%
(1.4, 27.5)
195
(24)
9.6%
(4.6, 14.6)
27c Every three months
112
(6)
4.2%
(0.0, 4.2)
83
(2)
2.1%
(0.0, 7.9)
195
(8)
3.5%
(0.0, 7.9)
27d Less than every three months
112
(8)
7.9%
(2.9, 12.9)
83
(16)
16.9%
(7.3, 26.5)
195
(24)
10.8%
(6.7, 14.8)
28 The counseling received in the past year has been about:
28a
Agricultural farming improvement 112
(96)
88.8%
(81.3, 96.1)
83
(70)
81.0%
(65.7, 96.3)
195
(166)
86.3%
(79.2, 93.4)
28b
Business improvement 112
(6)
3.8%
(0.0, 8.6)
83
(10)
10.5%
(4.2, 16.9)
195
(16)
5.9%
(1.9, 10.0)
28c
Guidance to generate more money 112
(2)
1.8%
(0.0, 5.6)
83
(3)
2.1%
(0.0, 6.5)
195
(5)
1.9%
(0.0, 4.5)
28d
Livestock farming improvement 112
(99)
89.6%
(83.6, 95.6)
83
(67)
81.6%
(73.0, 90.2)
195
(166)
87.1%
(82.2, 91.9)
MYAP 2011 Final Evaluation 
Annex 1 
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Table III.C.7 Agricultural and Livestock Practices
Results
Indicator
Population WITH Agricultural 
Interventions
Population WITHOUT 
Agricultural Interventions Total Population
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
Sample Size 
(# of cases)
%
(95% CI)
29 Who have provided the counseling in most recent years:
29a
Organizations in support of farming or commercialization 112
(88)
84.7%
(68.2, 100)
83
(61)
70.0%
(44.3, 95.6)
195
(149)
80.0%
(65.6, 94.5)
29b
Relatives or neighbors 112
(9)
4.9%
(0.0, 11.9)
83
(10)
15.3%
(5.5, 25.2)
195
(19)
8.2%
(1.9, 14.4)
29c
Mass media (Radio, TV, print, loudspeakers) 112
(0)
0%
(-)
83
(0)
0%
(-)
195
(0)
0%
(-)
29d
Technical operatives or local promoters 112
(26)
21.3%
(13.5, 29.1)
83
(20)
21.8%
(16.2, 27.5)
195
(46)
21.5%
(15.8, 27.1)
MYAP 2011 Final Evaluation 
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III.B.8 Income Improvement (Formal Marketing)
 
Table III.B.8 Income Improvement (Formal Marketing)
Results
Indicator
Code Name
Sample Size 
(# of cases)
%
(95% CI)
30
Percentage of farmers who adopt at least two formal marketing processes
(ind30a1 and/or Ind30a2)
49
(44)
86.7%
(71.4, 100)
30b
Percentage of farmers who adopt at least two formal marketing processes
(ind30b1 and Ind30a2)
49
(44)
86.7%
(71.4, 100)
Formal marketing practices employed:
30a1
Percentage of farmers who calculate production and/or commercialization 49
(48)
99.0%
(96.7, 100)
30a2
Percentage of farmers who record production and/or commercialization 49
(44)
86.7%
(71.4, 100)
30b1 
Percentage of farmers who calculate production and commercialization 49
(48)
99.0%
(96.7, 100)
31
Percentage of farmers that receive institutional technical assistance for formal marketing 49
(47)
97.2%
(91.6, 100)
31a Types of businesses run by the farmers:
31a1
Agricultural 49
(49)
100%
(-)
31a2
Livestock 49
(2)
2.8%
(0.0, 8.4)
31b
Family business 49
(2)
3.5%
(0.0, 7.9)
32
Percentage of farmers who implement production and/or commercialization planning 49
(47)
96.5%
(92.1, 100)
32b
Percentage of farmers who implement production and commercialization planning 49
(42)
85.4%
(73.9, 96.9)
MYAP 2011 Final Evaluation 
Annex 1 
74
Table III.B.8 Income Improvement (Formal Marketing)
Results
Indicator
Code Name
Sample Size 
(# of cases)
%
(95% CI)
Places where their products are sold:
32a1
Communal Market 49
(7)
12.7%
(0.0, 29.3)
32a2
Municipal Market 49
(8)
12.7%
(0.0, 30.6)
32a3
Regional market, Guatemala City wholesaler, middleman, export market 49
(42)
86.6%
(66.5, 100)
33
Percentage of farmers who express having had problems that affected his or her business 49
(38)
72.0%
(41.7, 100)
33a Type of problem:
33a1
Lack of marketing or advising 38
(16)
38.3%
(2.7, 74.0)
33a2
Lack of money, capital or raw materials 38
(13)
33.5%
(0.5, 66.4)
33a3
Lack of appropriate monitoring of operational records or lack of organization on the part of the farmers 38
(0)
0%
(-)
MYAP 2011 Final Evaluation 
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III.B.9 Community Risk
 
Table III.B.9 Community Risk
Results
Sample Size = 31
Indicator
Code Name Number of Cases %
34 Percentage of communities in which one of its leaders were trained regarding community risk management 18 58.1%
34a Percentage of communities that have a community plan for risk management 7 22.6%
34b Percentage of communities that have participated in activities related to a monitoring and warning system or Sentinel Site for 
food scarcity
13 41.9%
34c Percentage of communities that are knowledgeable about early warning systems or Sentinel Sites 12 38.7%
34d Percentage of communities with a community Sentinel Site 
(COCODE confirms that there is an information table for the Sentinel Site and/or verified the existence of the table)
8 25.8%
34e Percentage of communities with a device to read the amount of rainfall in the community 4 12.9%
34e1 Percentage of communities that have a sheet or notebook to record daily rainfall 4 12.9%
Table III.B.9a Community Risk (Sentinel Sites)
Information obtained at the Sentinel Sites
Indicator
Results
Sample Size = 3
Number of cases
Number of communities in which the COCODE has received training regarding risk management 3
Number of communities in which the COCODE has received training regarding COCODE functions 3
Number of communities in which the COCODE has received training regarding risk factors of food and nutritional 
insecurity
3
Number of communities in which the COCODE has received training regarding risk of disaster 3
Number of communities in which the COCODE has received training regarding program profiles 3
Number of communities in which the COCODE has received training regarding food and nutritional security 1
Number of communities in which the COCODE has received training regarding program management 3
Number of communities that have a community risk management plan (the document was verified) 1
MYAP 2011 Final Evaluation 
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76
Table III.B.9a Community Risk (Sentinel Sites)
Information obtained at the Sentinel Sites
Indicator
Results
Sample Size = 3
Number of cases
Topics in which the community is most active
Children’s health, children’s malnutrition, 
food security 
Children’s education 
Animal disease (including birds) 
Environment: household hygiene (waste 
management)
Monitoring corn prices
Program management
Received training materials 3
The topics that the communities found most interesting or important 
Program management
Disaster Risk
Environment
COCODE functions
Monitoring of bird disease
Health and nutrition
Have raised resources at the municipal level to meet their needs 3
Have implemented some program to the benefit of their community
3
Multi-purpose room, classrooms, highway 
retaining wall 
Have participated in some activity or training related to monitoring and warning systems or Sentinel Sites for food 
scarcity
3
The members of the community participate in monitoring and warning systems or Sentinel Sites for food scarcity 3
Recognize a community monitoring board 3
Verification (by observation) of an existing community monitoring board 3
Verification (by observation) of a community notebook 2
Know how to use the colored happy face stickers 3
Know what the early warning system and Sentinel Site are for 3
MYAP 2011 Final Evaluation 
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Table III.B.9a Community Risk (Sentinel Sites)
Information obtained at the Sentinel Sites
Indicator
Results
Sample Size = 3
Number of cases
Have the community Sentinel Site monitoring board (verified by observation) 2
Have a notebook to record the Sentinel Site information 2
Know what a rain gauge is 3
Have a rain gauge installed 3
Have a sheet or notebook to record daily rainfall 3
MYAP 2011 Final Evaluation 
Annex 2 
78
ANNEX 2: III.D Design Effect on MYAP 2011 Indicators 
Thematic Area Cod. Indicators Design Effect
Anthropometrics 
in children under 
5 years
1a
Percentage of children under 5 with chronic malnutrition 
(Z < -2SD height/age), NCHS 3.866
1b Percentage of children under 5 with chronic 
malnutrition (Z < -2SD height/age), WHO 3.558
2a
Percentage of children under 5 with general malnutrition 
(Z < -2SD weight/age), NCHS 2.485
2b
Percentage of children under 5 with general 
malnutrition (Z < -2SD weight/age), WHO 1.931
Anthropometrics 
in children under 
36 months
2a
Percentage of children under 36 months with general 
malnutrition (Z < -2SD weight/age), NCHS 2.299
2b Percentage of children under 36 months with general 
malnutrition (Z < -2SD weight/age), WHO 1.377
Household dietary 
diversity and food 
scarcity in the 
household 
4 Average score in dietary diversity 1.408
5
Average number of months out of the year with 
adequate provisions of food in the household. 1.913
Child feeding 8
Percentage of infants aged 0 to 5.99 months who have 
been exclusively breastfed in the preceding 24 hours. 1.547
Warning signs in 
maternal, 
neonatal and 
children’s health 
12
Percentage of mothers with children aged 0 to 35.99 
months who recognize at least two warning signs in 
pregnancy that indicate the need to seek health services. 
3.880
15
Percentage of mothers with children aged 0 to 35.99 
months who recognize at least two neonatal warning 
signs that indicate the need to seek health services. 
4.565
18
Percentage of mothers and caregivers with children aged 
0 to 35.99 months who recognize at least two warning 
signs of childhood illness that indicate the need to seek 
health services. 
3.059
Agricultural and 
livestock practices
22
Percentage of farmers who adopt at least two improved 
agricultural practices. 2.431
23
Percentage of farmers who adopt at least two improved 
livestock practices 2.448
Income 
improvement
30 Percentage of farmers who adopt at least two improved
formal marketing practices 2.589