Appendix G.i 
PROMASA II: Annual Evaluation. 
During the fourth quarter of FY09, the PROMASA program conducted an annual results 
evaluation in order to analyze progress made in the field during the second year of program 
interventions. 
Methodology
The evaluation was conducted using the LQAS1
 methodology with a stratified cluster sample 
comprised of 19 study units per stratum2
 for each sample of interest. The sample was 
established by randomly selecting 19 households participating in the PROMASA program for 
each of the 6 project coverage municipalities. 
In order to evaluate progress made in regards to the SO1, SO2 and SO3 indicators, three 
different study samples were established as follows: 
1. Maternal-child nutrition and health survey: a sample consisting of 19 households with 
children less than 36 months of age per stratum (municipality), in order to measure the 
maternal-child nutrition and health indicators3
. A total of 114 households were 
evaluated. 
2. Exclusive breastfeeding survey: the program then selected 19 households with 
children less than 6 months of age per stratum, in order to evaluate the exclusive 
breastfeeding indicator. A total of 111 households were evaluated. The sample size 
for this indicator was slightly lower due to the fact that there were only 16 children 
less than 6 months of age in the Chajul municipality. 
3. Livelihood survey: in addition, the program established a sample of 19 households per 
stratum in order to evaluate the livelihood indicators4
. A total of 114 households were 
evaluated. 
4. Anthropometric evaluation5
: in order to ensure the quality of the evaluation’s 
anthropometric analysis, the program trained evaluation personnel on standards related 
to measuring children’s weight, height and mid upper arm circumference (MUAC). 
Even though 100% of evaluation personnel were trained on MUAC and weight 
measurements, only 35% ended up trained on height measurement. This situation 
resulted in the need to measure the height per age (chronic malnutrition) and weight 
per height (acute malnutrition) indicators via a representative sample. Using the 
sample framework established for the MYAP baseline study, for which municipalities 
served as the primary stratum, 25 households in each of the 32 communities (located 
in the 6 program coverage municipalities) were randomly selected, in order to ensure 
appropriate representation and validity for the study, for a total of 800 households. 
 
1 Lot Quality Assuring Sampling 
2 Valadez, Joseph. 2003. Assessing Community health Programs, A Trainer’s Guide: Using LQAS for Baseline Surveys 
and Regular Monitoring. TALC: Teaching AIDS at Low Cost, St. Albans, United Kingdom. 
3 Weight per age, height per age prevalence, knowledge of neonatal, pregnancy and childhood danger signs. 4 Adoption of best agricultural production and formal marketing practices, months of adequate supply and diet diversity 
index. 
5 Anthropometric indicators used in this report are defined as follows: a) Acute malnutrition: height for age 
b) Global malnutrition: weight for age, c) Acute malnutrition: weight for height and d) MUAC: mid upper arm 
circumference, used to measure acute malnutrition 
For the global and acute malnutrition indicators evaluated using MUAC, a total of 8,274 
children less than 36 months of age were evaluated, representing 95% of those enrolled in the 
PROMASA program in August of 2009. 
Results 
The results of the PROMASA evaluation for fiscal year 2009 are presented below. 
Anthropometric Indicators 
Charts 1, 2 and 3 present the global, chronic and acute malnutrition prevalence rates by 
gender and NCHS (1978) / WHO (2006) growth standards. It is important to highlight that 
despite the fact that the differences found between the sexes is not significant, boys were 
more affected in all three anthropometric indices. 
Chart 1 
 Global Malnutrition Prevalence per Sex and Classification
September, 2009. SC-MYAP, El Quiché, Guatemala
Female Male Total
Female Male
WAZ (WHO) 33.6% 39.0% 36.4%
Total
WAZ (NCHS) 48.9% 49.5% 49.2%
50.0%
45.0%
40.0%
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
WAZ (NCHS 1978)
WAZ (WHO (2006))
Prevalence
n = 8,274
Chart 2
Chronic Malnutrition Prevalence per Sex and Classification
September, 2009. SC-MYAP, El Quiché, Guatemala
Female Male Total
Male
HAZ (NCHS) 69.6%
Female
74.8% 72.0%
Total
HAZ (WHO) 74.6% 83.3% 78.7%
80.0%
70.0%
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
HAZ (WHO (2006))
HAZ (NCHS 1978)
90.0%
Prevalence
n = 821
Chart 3
 Acute Malnutrition Prevalence per Sex and Classification
September, 2009. SC-MYAP, El Quiché, Guatemala
Female Male Total
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
0.0%
WHZ (WHO (2006))
WHZ (NCHS 1978)
3.5%
Prevalence
n = 821
Female Male
WHZ (NCHS) 1.9% 2.8% 2.4%
Total
WHZ (WHO) 1.7% 3.4% 2.5%
Chart 4 presents the results for acute malnutrition, using the mid-arm circumference 
methodology. The data show that 0.3% (red) of children evaluated require immediate 
attention, 3.9% (yellow) are at risk of developing severe acute malnutrition and should be 
monitored and 95.8% (green) have a normal weight per height. 
Chart 4 
Acute Malnutrition Prevalence (%), using the mid-arm circumference (MUAC) methodology
September, 2009. SC-MYAP, El Quiché, Guatemala
100.0%
90.0%
80.0%
70.0%
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0% Yellow Green
0.3% 3.9% 95.8%
Red
MUAC categories
Prevalence
n = 8,274
Chart 5 shows the global malnutrition prevalence rate (%) per age group using the NCHS 
(1978) / WHO (2006) growth standards. Data collected for this indicator demonstrate a well￾known tendency of weight per age beginning to decrease for the age group comprised of 
children between 12 and 24 months of age who, together with the age group comprised of 
children between 24 and 36 months of age, are the most affected (38.6% and 39.3% 
respectively). 
Chart 5
Global Malnutrition Prevalence (WAZ) per Age Group and Measurement Standard
September, 2009. SC-MYAP, El Quiché, Guatemala
60.0%
50.0%
40.0%
Prevalence
30.0%
0.0%
10.0%
20.0%
12 - <24 24 - <36
WHO 16.2%
0 - <6
22.2%
6 - <12
38.6% 39.3% 36.4%
Total
NCHS 6.0% 28.9% 54.9% 51.5% 49.2%
NCHS
WHO (2006)
Age Groups
n = 8,274
ARIs and ADDs 
Chart 6 compares global malnutrition (NCHS 1978 / WHO 2006) prevalence rates together 
with acute respiratory infection (ARI) prevalence and acute diarrheal disease (ADD) 
prevalence, per sex. Data collected show that the population covered by the PROMASA 
program is affected by all three of these prevalent illnesses (ARIs, ADDs and malnutrition), 
which cause great harm to children less than 5 years of age. These prevalence rates are much 
higher than the national averages reported in the 2002 ENSMI study and are similar to data 
reported in the PROMASA FY08 Annual Report. 
Chart 6 
Global Malnutrition Prevalence (WAZ) per Measurement Standard
Acute Respiratory (ARIs) and Diarrheal (ADDs) Infections, per Sex
September, 2009. SC-MYAP, El Quiché, Guatemala
WAZ (WHO), 39.0%
WAZ (NCHS), 49.5%
ARIs, 49.4%
ADDs, 36.1%
WAZ (WHO), 33.6%
WAZ (NCHS), 48.9%
ARIs, 49.9%
ADDs, 35.9%
Female
Male
0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% 45.0% 50.0%
Prevalence n = 8,274
LQAS Analysis 
Chart 7, based on a LQAS decision diagram, presents data on municipal priorities for the 
different PROMASA strategies. The primary results of this analysis are shown below. 
Chajul Cotzal Nebaj Cunen Sacapulas Uspantan
Municipalities
Chart 7 
Program interventions by municipality and priority level, 
Sepember 2009, SC-MYAP, El Quiché, Guatemala
WAZ Prevalence (%) Exclusive Breastfeeding Chilhood Danger Sings
Pregnancy Danger Sings Neonatal Danger Sings Best Agricultural Practices
Best Livestock Practices Formal Marketing Practices
The majority of program interventions require special attention in the Sacapulas municipality. 
The low weight-per-age figures are a concern in all program coverage municipalities. Danger 
sign recognition and exclusive breastfeeding require special attention in 2 of the 6 program 
municipalities. This represents significant progress compared to last year where 4 of the 6 
municipalities were categorized as high priorities for these interventions. 
The adoption of best livestock and agricultural practices should be improved in the Chajul and 
Cotzal municipalities. In addition, formal marketing practices should be strengthened in 
Uspantán. 
Livelihood Indicators 
Charts 8, 9 and 10 presents information regarding the number of months of adequate 
household food provision since the start of the program, distribution per municipality and the 
percentage of households with inadequate food supplies per month. 
Chart 8 
Months of Adequate Household Food Provisions, (MAHFP)
SC-MYAP, El Quiché, Guatemala
8.00 2009
(n=114)
IC (9.4;9.6)
2008
(n=214)
IC (9.6;10.4)
BL
(n=799)
IC (10.8;11.0)
Months (Avg.) 10.83 10.03 9.50 
11.00
1 .00 0
Of Months
Average 
Number 
9.00
Chart 9
 Months of Adequate Food Provisions, per Municipality
SC-MYAP, El Quiché, Guatemala
- Chajul Cotzal Nebaj Cunén Sacapulas Uspantán
2009 10.32 9.32 9.21 10.42 9.68 7.89
2008 9.90 9.20 11.70 9.50 10.60 10.50 
BL 10.70 10.40 11.10 11.20 10.90 10.20 
12.00
10.00
Average 
Number of
Months
8.00
6.00
4.00
2.00
Municipalities
The data show that families participating in the PROMASA program continue to suffer food 
provision problems during months characterized by food shortages (July to November). This 
period was especially harsh in 2009 as a result the drought. As a result, the number of months 
of adequate food provisions decreased for all municipalities. Corn, beans and sugar were the 
foods most often reported to be in short supply (See Chart 11). 
Chart 10 
 Percentage of households that reported inadequate food provisions, per month
SC-MYAP, El Quiché, Guatemala
60.0%
50.0%
Percentage
Of 
Families 40.0%
30.0%
20.0%
10.0%
Charts 12 and 13 present information regarding the diet diversity score (HDDS) for 
households participating in the PROMASA program. This index has remained unchanged 
since the start of the program. The questions asked of participants to determine the diet 
diversity score can be further investigated in order to evaluate the consumption of specific 
foods or food groups. The program’s family garden activity is a common intervention whose 
objective is to increase the consumption of vegetables rich in Vitamin A. 
0.0%
Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug
2008 56.0% 33.4% 18.6% 8.6% 19.0% 23.1% 29.8% 15.4% 16.7% 33.2% 48.4% 48.6%
2009 36.3% 37.6% 29.4% 21.1% 16.5% 8.8% 6.7% 12.3% 13.0% 17.4% 27.4% 29.5%
Months
Chart 11
 Percentage of households that reported food scarcity, per type of food
SC-MYAP, El Quiché, Guatemala
Corn
Beans
Sugar
Foods Vegetables
Rice
Meat
Herbs
Eggs
Oil
Other
0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0%
Percentage of Households
Other Oil Eggs Herbs Meat Rice Vegetables Sugar Beans Corn
2009 2.9% 6.9% 8.6% 13.1% 13.2% 13.3% 16.2% 18.7% 58.2% 63.3%
2008 5.2% 9.8% 11.8% 13.6% 24.4% 28.0% 28.2% 36.7% 52.1% 64.4%
2.00
2.50
3.00
3.50
4.00
4.50
5.00
Average
Chart 12 
Household Diet Diversity Score (HDDS)
September 2009, SC-MYAP, El Quiché, Guatemala
Average 4.57 4.72 4.64 
LB
(n=799)
IC (4.50;4.65)
2008
(n=214)
IC (4.38;5.06)
2009
(n=114)
IC (4.6;4.7)
Chart 14 presents data on the percentage of producers that have adopted best practices related 
to agriculture, livestock and marketing. It is important to mention that these indicators were 
not measured in FY08 as not enough time had passed to determine whether practices 
promoted by PROMASA had been adopted or not. The chart also presents results for these 
indicators at baseline. 
2.00
2.50
3.00
3.50
4.00
4.50
5.00
5.50
6.00
Average
Municipalities
Chart 13
Household Diet Diversity Score (HDDS), per Municipality
SC-MYAP, El Quiché, Guatemala
BL 4.60 4.70 4.60 4.70 4.50 4.50 
2008 4.40 5.50 4.70 4.60 4.20 5.50 
2009 4.74 4.53 3.63 5.37 4.32 5.63 
Chajul Cotzal Nebaj Cunén Sacapulas Uspantán
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
Porcentage
Municipalities
Chart 14 
Porcentage of producers that have adopted 
at least two best practices, per municipality 
September, 2009 SC-MYAP, El Quiché, Guatemala
Agriculture (60.7% : 78.9%) 11.5% 69.8%
Livestock (34.5% : 52.5%) 12.0% 43.5%
Marketing (7.0% : 20.5%) 15.4% 13.7%
LB 2009