93. Percentage of children absent from school due to ill-health

93. Percentage of children absent from school due to ill-health

VERSION

V3.0 - 2026.03 — Existing

INDICATOR CODE

93

TECHNICAL OWNER

PRG-S SBP

INDICATOR TYPE

Country Level Outcome Indicator

INDICATOR CLASSIFICATION

Complementary

INDICATOR SCOPE

Programme specific

APPLICABILITY

The selection of this indicator is also recommended against the following sub-activities in CSPs logframes. Selection of the below sub-activities will NOT trigger the mandatory selection of this indicator:

1. School Meals Programme On Site (SF_ONS)

2. School Meals Programme Take Home Initiatives (SF_THI)

UNIT OF MEASUREMENT & ANALYSIS

Percentage

DEFINITION

The percentage of students absent from school because of ill-health is defined as the overall average percentage of female and male students absent from school every month in WFP assisted schools as compared to the total number of enrolled students.

The following definitions apply to this indicator:

Students: are defined in this context as school-aged children that are enrolled in WFP-assisted schools. School-aged children are children that are old enough to go to primary school. Typically, this age group falls between the ages of 5-19 years old, but the minimum age can differ by country.

Absent because of ill-health: Students not attending school because they are suffering of

any physical or psychological pain or illness. Ill-health in the context of child absenteeism

is any health factor that is making the child too sick to be able to go to school on a specific

day or series of days.

School Feeding: The provision of food (meals, snacks, or take-home incentives conditional

upon school attendance) to children and/or their households through school-based programmes.

RATIONALE

Increased access to education, improved learning outcomes and Improved health (physical & psycho-social) of girls & boys are among the main results expected to be achieved through school feeding interventions as per the WFP school feeding theory of change.

Regular school attendance is a key factor for improved education outcomes, and School-Feeding Programmes serve as an incentive for children to attend school. Ill-health can be a great impediment for children’s attendance, their access to school feeding as well as their ability to learn and grow. In many contexts, WFP provides a complementary package (alone or in coordination with other partners/governments) to school-aged children which could include one or more of the following health interventions: vaccination, deworming, menstrual hygiene, eye testing/eyeglasses, hearing testing/treatment, dental cleaning/testing hear, etc. These interventions alongside the healthy school meals that children receive in school are expected to incentivize children to attend more regularly and thus reduce their absenteeism. This Indicator intends to capture the percentage of children that are absent due to ill-health to better understand some of the linkages between health and absenteeism.

In addition, some aspects of school feeding (e.g., take-home rations) can be designed with conditionality of school participation, mainly attendance, attendance monitoring is prerequisite to receiving the ration.

DATA COLLECTION TOOL

Data can be sourced from either:

1. schools

2. or parents of the students (school-aged children)

The data collection can take place at either level based on the programme implementation and design in each country.

Some countries have advanced absenteeism tracking systems and thus this information would be available at the school level for each student. In cases where data is available at

school, the data is to be collected from school records. Electronic or paper-based records

available at schools or centrally at the ministry of Education.

In the absence of accurate school records, this data can be collected at the household level with the parents of the school-aged children. This module can be integrated with other data collection modules/exercises at the household level in instances of multiple assistance being provided to the same households.

Schools: Data to be collected for all schools once every month. This data is available at schools and WFP must compile this information, store in a safe manner and report on it on annual basis at the end of each school year. SBP is piloting School Connect which is a digital data collection tool that could be used to collect attendance data. For more information or specific support on data collection tools, consult SBP MEAL team.

• The below data collection module can be added to a household survey with the parents of the students. Some pointers in regard to the module:

• It is important to note that the below module needs to be repeated for every child in the household that is attending WFP assisted school benefitting from a School Feeding Programme. in household

• Results from module to be analyzed in two-folds – first by analysis of children absent because of ill-health, second by the average number of days absent which will give a scope to the improvement of deterioration of the situation.

• Results of Q2 are used to generate the results of this indicator. Please refer to the example.

Total number of students absent because of ill-health = Xi= Σ of all respondents to question 2.

Xi = Average annual number of students absent from school due to ill-health in year i

Yi = Total number of students enrolled in school in year i at the beginning of the school year

Average percentage of students absent because of ill-health = Xi / Yi x 100

SAMPLING REQUIREMENTS

1. Schools: Data should be collected from all schools that are part of the Home Grown School Feeding Programme every school semester; Or

2. Parents of students (school-aged children): a representative sample is to be selected covering all children benefiting from the School Feeding Programme.

INDICATOR CALCULATION FOR REPORTING

The percentage of students absent from school because of ill-health is calculated by generating the total annual average percentage of students absent because of ill-health.

Annual average percentage of students absent from school because of ill-health=

(Xi / Yi) x 100%

Where:

Xi = Average annual number of students absent from school due to ill-health in year i

Yi = Total number of students enrolled in school in year i at the beginning of the school year

And:

Xi = (X1 + X2 + X3 + … + Xn) / Yi

Where:

n = Total number of months in year i in which the school was operational

X1 = Average monthly number of students missing school in month 1

…

Xn = Average monthly number of students attending school in month n

And:

X1 = X1.1 + X1.2 + X1.3 + … X1z / Y1

…

Xn = Xn1 + Xn2 + Xn3 + … Xnz / Yn

Where:

X1.1 = Number of students absent from school because of ill-health on day 1 of month 1

X1.2 = Number of students absent from school because of ill-health on day 2 of month 1

…

Xnz = Number of students absent from school because of ill-health on day z of month 1

1z = last day in which school was operational in month 1

Y1 = Total number of students enrolled in school in month 1

…

(Repeat for months 2 – n)

Xn1 = Number of students absent from school because of ill-health on day 1 of month n

Xn2 = Number of students absent from school because of ill-health on day 2 of month n

…

Xnz = Number of students absent from school because of ill-health on day z of month n

z = last day in which school was operational in month n

Yz = Total number of students enrolled in school in month n

Alternatively, if absenteeism is not recorded daily in schools, and/or data collection/access is not possible, the average number of students attending any given month (X1, X2, … Xn), can be captured through a randomized school visit and headcount on a given day of the month.

This should be noted in data notes, to account for possible biases in the data.

DATA ENTRY AND DISAGGREGATION IN CORPORATE SYSTEMS

Values are recorded in the logframe. Each value has a reporting combination which is created based on:

• Sub-activity

• Location

• Beneficiary Group

Follow-up value is reported as:

• Numerator

• Denominator

Optional disaggregation:

• Sex

For baseline and target values, only the overall value is required with sex disaggregation as optional.

BASELINE

Baselines are established only once for the entire CSP.

They remain fixed for the full CSP period unless otherwise specified.

Baselines must be set using data collected within three months before or after the start of the activity.

If no baseline is established within this three‑month window, the first collected value will serve as the baseline.

If a new CSP begins and the activity continues from the previous CSP, the last reported value from the previous CSP becomes the baseline for the new cycle.

TARGET SETTING

Annual targets:

To be determined at the country office level. Based on the context, the indicator should decrease or be maintained compared to the baseline/previous year’s value.

End of CSP target:

To be determined at the country office level. Based on the context, the indicator should decrease or be maintained compared to the baseline/previous year’s value.

FREQUENCY OF DATA COLLECTION

Data should be collected once every school semester with annual data entry into COMET.

INTERPRETATION

It is expected that school feeding incentivizes regular attendance to school, so that schoolchildren can learn and also access school health and nutrition services to be well nourished and healthy. The provision of complementary health interventions at the school level supports children’s attendance and in consequence their learning.

The lower the percentage of students that are absent because of ill-health as compared to the total number of students enrolled each year, the more effective School Feeding Programmes are at keeping children in schools and at increasing access to education and improved learning for schoolchildren.

When interpreting results, always refer to planned versus actuals, and analyse/explain reasons for target shortfalls or surplus, or for meeting targets.

A lower absence rate means that all students enrolled attended school every day, and thus, that the School Feeding Programme could improving and/or maintaining access to education.

To put the indicator into perspective, it is important to triangulate this indicator with overall attendance rates at schools. It will be important also to report on trends from previous years; and on any potential external factors, which may have a positive or negative effect on absenteeism.

REPORTING EXAMPLE(S)

Reporting on this indicator should focus on the percentage of children absent because of ill-health as well as any qualitative data that can be collected on the reasons behind absence.

An example of how to use and report on the indicator is provided below:

As per the table above, the percentage of students that were absent from school because of ill-health was 8% for the school year 2020-2021. Higher absenteeism rates were recorded in January, February and March due to an outbreak of cholera in regions ABC which affected the school children. WFP and partners supported in addressing this outbreak through the provision of clean water and handwashing stations at schools. WFP and UNICEF in February launched a nationwide vaccination campaign targeting school children which helped decrease the outbreak. On average, more boys were absent due to ill-health than girls, WFP is conducting qualitative analysis to understand the reasons behind this. Age differences were also noted with older girls (10-14 years old) more likely to skip school due to ill-health.

INDICATORS COLLECTED & ANALYSED AT THE SAME TIME

This indicator module can be used to collect the percentage of children that are absent because of ill-health, the number of days that they are absent, as well as the primary reason for their absenteeism. The country office can use these data points to expand the information available on ill-health of students and absenteeism. This data can also be triangulated with the attendance data at each school.

On the outcome level, this indicator is complementary with the educational outcomes:

• 21. Enrollment rate

• 22. Attendance rate

• 47. Retention Rate, by grade 

COMPLEMENTARY QUALITATIVE RESEARCH

CO can consider an array of qualitative methods, monitoring techniques and approaches to understand the broader reasons behind absenteeism and its effects on the School Feeding Programmes. CO can design any studies to take into account the effects of health interventions on children (e.g. Key Informant Interviews with school health services or Focus Group Discussions with parents of children). These can help better articulate WFP’s contribution as well as the effects of School Feeding Programmes.

DECISIONS DATA CAN INFORM

This indicator informs various decision-making processes. Below are some suggestions:

• Assessing whether the programme is attaining its desired outcomes

• Using the results to advocate for additional funding

• Identifying schools, regions, or districts that require targeted attention

• Exploring opportunities for future collaboration with other agencies and improving

• School Feeding Programmes

• Identifying additional requirements to support children's health

VISUALIZATION

LIMITATIONS

Several limitations exist for this indicator. It is important to note that while ill-health could be a great barrier to school attendance and learning, many other factors contribute to good school and learning. The link between health and the provision of school feeding relies on the provision of specific complementary health interventions. This indicator is therefore a rough proxy on health results.

Many countries are unable to track reasons behind absenteeism and thus this information cannot be easily obtained for school-aged children. This indicator relies on monthly average and an annual average of monthly averages, therefore, while it provides a valuable general trend/analysis, each average is based on a different set of data points, increasing the risks of disproportionally affecting the final number. This indicator will average fluctuations across the school year and may not accurately represent drastic changes in absenteeism rates.  This indicator will measure the overall percentage of students absent from one month to the other. It is only optional to track the number of days absent and the type of illness.

Additionally, data collection methodology and choice of data collection frequency could affect the representativeness of the results.

FURTHER INFORMATION

For further information and support please contact the HQ SBP MERL team.