11. Minimum diet diversity for women and girls of reproductive age (MDD-W)

11. Minimum diet diversity for women and girls of reproductive age (MDD-W)

VERSION

V5.0 - 2026.03 — Existing

INDICATOR CODE

11

TECHNICAL OWNER

PRG-S Nutrition

INDICATOR TYPE

Country Level Outcome Indicator

INDICATOR CLASSIFICATION

Mandatory

INDICATOR SCOPE

Programme specific

APPLICABILITY

The selection of this indicator is mandatory against the following sub-activities in CSPs logframes. Selection of the below sub-activities will trigger in COMET the mandatory selection of this indicator:

1. Prevention of micronutrient deficiencies (PMD)

2. Prevention of acute malnutrition (PREV)

3. Prevention of stunting (STUN)

4. HIV care & treatment (HIV/TB_C&T)

This indicator is also recommended to be used under Nutrition-Sensitive activities therefore the Nutrition Sensitive Marker should be selected at sub-activity level where relevant.

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. Food assistance for Assets (FFA)

2. Management of moderate acute malnutrition/undernutrition (MAM)

3. General Distribution (GD)

4. Smallholder Agricultural Market Support (SMS)

UNIT OF MEASUREMENT & ANALYSIS

Percentage of women and girls of reproductive age (15-49 years)

DEFINITION

This indicator aims to measure whether women aged 15–49 have consumed at least five out of ten defined food groups in the previous day or night (24‑hour recall). It is a dichotomous indicator, capturing whether minimum dietary diversity for women (MDD‑W) has been met.It is a food group diversity indicator that reflects one key dimension of diet quality – micronutrient adequacy – summarized across 11 micronutrients: vitamin A, thiamine, riboflavin, niacin, vitamin B-6, folate, vitamin B-12, vitamin C, calcium, iron and zinc.

It calculates the percentage of women and girls of reproductive age (15 – 49 years) who reached minimum dietary diversity.Minimum dietary diversity is defined as consumption of 5 or more food groups out of 10 in the last 24 hours.

RATIONALE

The Minimum Dietary Diversity for Women (MDD‑W) indicator is used to assess whether women and adolescent girls of reproductive age (WRA) consume diets that include a sufficient variety of food groups to support adequate micronutrient intake. The percentage of WRA who achieve the minimum threshold of five out of ten food groups serves as a proxy measure of micronutrient adequacy, as dietary diversity is strongly associated with improved intake of essential vitamins and minerals. A higher prevalence of MDD‑W in a population therefore suggests better overall diet quality and a greater likelihood that women are meeting their micronutrient needs.

MDD‑W is needed because women’s micronutrient status is critical to their own health as well as to the health and development of infants during pregnancy and lactation. The indicator supports programme design and decision‑making by identifying populations where dietary diversity is low and where targeted actions are required to improve women’s nutrition. It aligns with global and corporate commitments to reduce undernutrition, strengthen maternal nutrition, and invest in the first 1,000 days, contributing to broader efforts to prevent malnutrition in all its forms.

DATA COLLECTION TOOL

Data source:

A survey conducted among the beneficiary population, such as Post Distribution Monitoring (PDM), is the most common. Representative sample size should be used appropriately.

It is highly recommended that MDD-W is also included in any household assessment, such as Comprehensive Food Security and Vulnerability, Emergency Food Security Assessment, or any other population-based representative survey.

Data collection Tool

The electronic version of the data collection tool for this indicator can be found in Survey Designer in the Nutrition Module Minimum Dietary Diversity for Women (MDD-W)sub-module or by selecting the indicator Minimum diet diversity for women and girls of reproductive age (MDD-W).

SAMPLING REQUIREMENTS

A significant representative sample needs to be generated if a survey is conducted. The following guidance on sample size determination can be adopted for the MDD-W indicator:

• Population size is the number of individuals (i.e., WRA) enrolled in the program at the survey time.  

• Expected prevalence of the indicator: use previous prevalence if available, and if unknown, 50% can be used.  

• Non -response: 10%  

• Design effect: if cluster sampling is done, the design effect needs to be considered. This can be based on previous results and set at 1,5 if no information is available. Take note of guidance on design effect for situations where the design effect needs to be increased or decreased due to the homogeneity of the surveyed population.  

• Confidence interval highly recommended being 95%.

INDICATOR CALCULATION FOR REPORTING

To calculate the indicator:

Scripts in R, STATA and SPSS and sample data are available on Github for the survey version of this indicator.

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

• Country

• Target Group

Recommended disaggregation for reporting outside :

• Selected geographic characteristics (e.g., by province or region, food system typology or by agro-ecological zone);

• Socioeconomic or household characteristics (e.g., urban versus rural households, by wealth quintile, age subgroup, level of education);

• Food insecurity status;

• Decisions regarding appropriate disaggregation will be specific to the survey and context and depend on the objectives, sampling, and sample sizes.

Baseline, target and Follow-up value is reported as one overall score in COMET.

BASELINE

Baselines are set only once, at one of the following points:

1. At the beginning of the CSP, or

2. When the indicator is selected for reporting after the commencement of the CSP; or

3. When a change in target, location and/or modality triggers a new reporting combination (target, location and modality) for an existing indicator.  

Baselines remain fixed for the entire CSP period and are not recalculated annually, unless applicable above.

Baseline value is reported as one overall score.

TARGET SETTING

Annual targets:

The proportion of Women and Girls of Reproductive Age (15-49 years) who reached Minimum Dietary Diversity for Women (MDD-W) has increased compared to the previous year’s value. See comment end of CSP target. If uncertain, it’s recommended to target an increase of 10%.

End of CSP target:

The target at the end of the CSP is to increase the MDD-W value compared to the baseline. Only general guidance can be provided for setting targets for Minimum Dietary Diversity for Women (MDD-W), as it is not possible to recommend universal targets.

Note: Setting targets is not an exact science. It is rare that a specific, single value is the only acceptable expected value for an indicator target. An acceptable range is usually used. Targets should be ambitious, but achievable given the programme’s inputs and timeframe.

The percentage of increase should therefore be determined based on local context; baseline value; type of intervention implemented and its theory of change or impact pathway; scientific evidence on the impact of this type of intervention, if available; timeframe and season (especially relevant to MDD-W); ongoing interventions in the same area and/or events that may affect the desired outcome.

Target value is reported as one overall score

FREQUENCY OF DATA COLLECTION

Data must be collected at least twice per year in the same season. Ensure that the baseline data was collected at the beginning of the programme. If required by the programme data can be collected across each season. This ensures a fuller understanding of seasonal patterns in diets and serves as an important baseline if repeat measurements occur in different seasons.

For years when a baseline is conducted, only one follow up is required.

INTERPRETATION

An increase in MDD‑W indicates that a higher proportion of women of reproductive age are consuming more diverse diets, suggesting improved micronutrient adequacy and better overall diet quality. A decrease or consistently low levels signals potential challenges in women’s access to or use of diverse foods, which may stem from food insecurity, market constraints, seasonal changes, or gaps in programme design or messaging.

When interpreting results, consider context: seasonal trends, food prices, and programme coverage can all influence dietary diversity. Combining MDD‑W with other indicators (e.g., food security or market data) helps clarify whether changes reflect access constraints, knowledge gaps, or broader environmental or economic factors.

REPORTING EXAMPLE(S)

The proportion of women and girls who achieved the minimum diet diversity was 40%. A higher prevalence of women and girls who reached the minimum diet diversity was found in the Metropolitan region, while the lowest percentage was obtained in the desert region indicating nutritional deficiencies among the interviewed women.

INDICATORS COLLECTED & ANALYSED AT THE SAME TIME

The following indicators may be reported along with this indicator:

Individual level indicators:

• 10. Minimum Acceptable Diet (MAD)

• 8. Proportion of target population who participate in an adequate number of distributions (adherence)

• 7. Proportion of eligible people reached by nutrition preventive programme (coverage)

Household level indicators:

• 1. Food Consumption Score (FCS)

• 3. Reduced Coping Strategies Index (rCSI)

• 4. Livelihood Coping Strategies - Food Security (LCS-FS)

• 5. Livelihood Coping Strategies - Essential Needs (LCS-EN)

• 6. Economic Capacity to Meet Essential Needs (ECMEN)

COMPLEMENTARY QUALITATIVE RESEARCH

Qualitative approaches should be used, including Focus Group Discussions to complement quantitative data to establish reasons for the performance of the indicator. Qualitative data can, in addition, inform required actions and recommendations for improvement.

For guidance on collecting complimentary qualitative data to complement quantitative data for this indicator, please refer to this qualitative methodological noteand guide.

DECISIONS DATA CAN INFORM

MDD‑W data helps WFP identify women and girls most at risk of inadequate diets and prioritize geographic areas where low dietary diversity is most prevalent. This enables more effective targeting of nutrition interventions toward populations with the greatest nutritional vulnerabilities.

The indicator also guides programme design and refinement by highlighting specific dietary gaps. For example, if certain food groups are consistently under‑consumed, WFP can tailor interventions such as nutrition education, social and behaviour change communication, or efforts to enhance availability and accessibility of targeted food groups to address these gaps.

An increase in the proportion of women achieving MDD‑W reflects an improvement in diet quality. Conversely, no change, failure to meet targets, or a decline should prompt a review of the context and an assessment of programme appropriateness, effectiveness, and delivery to identify and address underlying barriers.

VISUALIZATION

Figure 1: Percent of WRA achieving MDD-W during the previous day or night, by region

LIMITATIONS

While data are collected from individual women, the indicator cannot be used to infer diet quality for an individual, as it is based on a single recall period over one day and night (24-hours) and does not reflect day-to-day variability for individual intakes. The correct use and interpretation of MDD-W are at the population level, i.e., for groups of WRA. Therefore, it should not be used for screening or targeting women.

FURTHER INFORMATION

Nutrition Monitoring & Evaluation Guidelines 2023 | WFPgo

WFP Guidance Minimum Dietary Diversity – Women 2022

Survey Designer

List based questionnaire – xlsform / enketo

Open recall questionnaire – xlsform / enketo

Scripts in R, STATA and SPSS and sample data are available on Github for calculating this indicator.