In-Depth Vendor Assessment – Food Availability

The In-Depth Vendor Assessment Tool is used to gather detailed information on multiple dimensions of the food environment among market vendors and in other retail outlets. This guidance describes its use for assessing food availability. While the Community and Market Mapping Tool can assess the distribution, number, and type of food outlets^[1] in neighborhoods, and typically the availability of food groups, the In-Depth Vendor Assessment gathers more detailed data on the availability of specific food items. Depending on study design, the tool can enable:

1. Analysis of the diversity of foods available, which can describe the availability of a healthy diet as per food based dietary guidelines (FBDG) or other diet quality indicators;
2. Monitoring of trends in the diversity of foods available over time, if regular follow-ups take place, which could include within-group variety of fruits, vegetables, or other fresh foods that may fluctuate as a result of seasonality;
3. Assessment of the variety of unhealthy and discretionary foods available, locations and outlet-types where they are typically found, and how the availability of these changes over time; and
4. Exploration of possible links between food availability and food purchasing or diet outcomes.

In addition to measuring food availability, this tool can also be used to measure food prices and marketing (see In-Depth Vendor Assessment – Food Costs and Affordability and Food and Beverage Promotion tools for guidance on those dimensions). Guidance on sampling, data collection, and assembling of food lists was informed by In-depth Vendor Assessment and Cost of a Healthy Diet protocols from the Food Environment Toolbox^[2] (Downs, Staromiejska, et al., 2024; A. Herforth et al., 2024).

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[1] In this guidance, “outlet” refers to any retail access point for food, which can include supermarkets, grocery stores, small shops, mini-markets, open-air traditional markets, street stalls or kiosks, mobile vendors, restaurants, or any other formal or informal setting to purchase food. 

[2] The Food Environment Toolbox encompasses a suite of assessments designed to measure different dimensions of the food environment in LMICs. The toolbox is available through the Rutgers University website (https://sites.rutgers.edu/food-environment-Toolbox/), and was funded through the Innovative Methods and Metrics for Agriculture and Nutrition Action (IMMANA) program.

Note on assessment of vendor characteristics and other food environment dimensions, including food safety

The guidance provided here does not include assessment of vendor characteristics, such as opening hours, level of permanence (e.g. type of roof), payment methods accepted, or food safety and hygiene practices.  However, food environment assessment typically includes many of these other dimensions, depending on research objectives. Examples of survey questions to measure food safety, level of permanence vs. informality, adequacy or water access or waste management in markets, among others can be found in the Food Environment Toolbox (Community Mapping Tool for level of permanence, and In-Depth Vendor Assessment for vendor hygiene and food storage practices) (Downs, Staromiejska, et al., 2024). USAID and GAIN have also developed an observational checklist of assessing food safety as part of the EatSafe project (GAIN, 2024).

Rationale

Early FE research focused on measuring food availability as the geo-locations and distribution of different types of outlets, relying on assumptions of what foods were offered by these outlet types and whether this was healthy or unhealthy (Glanz et al., 2023). These analyses remain common, including in research exploring linkages between the food environment and obesity (Caspi et al., 2012; Pineda et al., 2024). However, such categorizations of food outlets can miss the variation in specific product offerings that may exist within outlets of the same type and result in the loss of potentially valuable information due to using a binary classification (Thornton et al., 2020). Use of checklists to assess the availability of specific items consumers find inside outlets has grown and tools such as the Nutrition Environment Measurement Survey for Stores (NEMS-S), which are now prevalent in studies from high-income countries (HICs), have even been adapted in certain low and middle-income countries (LMICs) (Glanz et al., 2023; Lytle & Sokol, 2017). Such measures, as well as those addressing the placement and promotion of food items, among other factors, attempt to describe what is often referred as the “consumer food environment”. 

Previous reviews have not yet drawn firm conclusions regarding the association of within-outlet food availability with food purchasing and diet outcomes, in part due to varied methods and metrics used, though existing evidence is suggestive of an association (Ni Mhurchu et al., 2013). Additionally, most studies to date have taken place in HICs. Some of these have measured the shelf space allocated to certain types of food, for example, finding that greater shelf space dedicated to energy-dense snack foods was positively associated with body mass index among consumers in surrounding areas (Ni Mhurchu et al., 2013; Rose et al., 2009). However, measuring shelf space is time-consuming and considered to have a low feasibility in informal retail settings in LMICs (Ahmed et al., 2021)^[3]. Data on food availability from inventory management systems are also unlikely to be widely accessible.

Simple measures of food diversity that account for between-group and within-group diversity available in outlets may be easier to collect data for and predictive of diet outcomes, under the hypothesis that greater diversity in local food environments may lead to more diverse food purchases. For example, food diversity in local markets, measured using a checklist 25 items across 9 food groups, was positively associated with women’s dietary diversity in rural Ethiopia (Ambikapathi et al., 2019). While studies in urban settings of LMICs are still lacking, the relative ease of collecting this data^[4], the insight it provides into a key dimension of food environments, and its potential influence on food access and healthy diets have informed this guidance’s focus on enumerator observation-based checklists of food item availability in outlets.

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^[3] If there are outlets in the study area where measuring shelf-space may be feasible (e.g. supermarkets, mini-markets, other outlets with aisles and accessible shelves) and research objectives would benefit from this, guidance on doing so is provided by the International Network for Food and Obesity/Non-communicable Diseases (NCDs) Research, Monitoring and Action Support (INFORMAS)

^[4] It should also be pointed out that if users intend to use the In-Depth Vendor Assessment Tool to collect food price data, the additional effort needed to collect availability data on those same items should be marginal, if any at all. This guidance can therefore be read alongside the In-Depth Vendor Assessment – Food Costs and Affordability guidance for additional insights into how availability data gathered can be analyzed, and indicators that can be generated from it.

Type of data

Data are gathered using an observational checklist of food items that enumerators must attempt to locate and record availability (yes/no) for. These food items are typically part of a pre-specified food list that aims to assess the diversity of foods available across and within multiple food groups, however assessments can also be designed allowing enumerators to record all of the items they find within each group, with no pre-specified list^[5]. Food lists are typically organized into food groups, which can be chosen based on those recommended in FBDGs, those that comprise a typical diet, or according to other specific research objectives of the assessment, which may focus on a narrower set of healthy or unhealthy foods.

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^[5] It should also be pointed out that if users intend to use the In-Depth Vendor Assessment Tool to collect food price data, the additional effort needed to collect availability data on those same items should be marginal, if any at all. This guidance can therefore be read alongside the In-Depth Vendor Assessment – Food Costs and Affordability guidance for additional insights into how availability data gathered can be analyzed, and indicators that can be generated from it.

Indicators

Indicators generated from data collected using the In-Depth Vendor Assessment – Food Availability Tool, described individually below, mainly seek to assess the diversity dimension of food availability. In contrast to indicators in the Community and Market Mapping Tool guidance, which draw on food group-level data, the indicators here are more detailed, aiming to assess both diversity across food groups and within food groups.

These indicators are generated from binary (available/not available) food item data gathered at the outlet-level. Therefore, they may not provide insight into how abundant a food or food group might be in the given outlet, which would require different methods of measurement, such as shelf space measurement, inventory databases, or counting stock of individual items (e.g. pieces of fruit or bottles of soda). However, depending on sampling and study design, outlet-level indicators could be aggregated to the community-level to estimate prevalence of outlets selling specific foods (see box on level of analysis below). Similarly, indicators cannot be generated from this data to assess the placement or prominence of food, which may also be key features of the food environments inside of outlets. If the availability of food groups included in the study are affected by seasonality, a one-time, cross-sectional analysis may be limited in the insight it provides. To assess changes, availability needs to be re-measured regularly or at least seasonally. Repeated measurements could also be used to track changes due to economic or climate-related shocks, or in the spread of unhealthy or discretionary foods (such as UPFs) offered in different types of outlets and communities over time.

Market food diversity index (MFDI)

These indicators mirror the measurement of diet diversity by estimating the number of food groups available in an outlet. Similar to those indicators, food groups assessed can be chosen to represent those that would achieve micronutrient adequacy or some standard of diet quality if consumed. For example, the Market Food Diversity Index (MFDI), included within the USAID Advancing Nutrition Guidelines for Market-based Food Environment Assessments, measures the availability of the 29 food groups included in the Diet Quality Questionnaire (DQQ) in open-air traditional markets (USAID Advancing Nutrition, 2023). Food group diversity scores like MFDI can also base their scoring on the availability of food groups included in other diet indicators, such as the Global Diet Quality Score (GDQS) or minimum dietary diversity for women (MDD-W)^[6].

Within-group count of unique foods

These indicators assess the variety of food items available within food groups, which may provide additional insight beyond food group diversity. For example, depending on research objectives, it may be important to distinguish between outlets that offer any green leafy vegetables at all (and potentially just one) versus outlets that have a large number of different leafy vegetables. Measuring within-group diversity is relevant for food groups where FBDGs encourage variety in daily consumption, but may also be relevant for measuring within-group diversity of unhealthy or discretionary foods, to understand the variety of these offered in different types of outlets and locations.

Healthy food availability indicators

Many indicators to measure the overall healthfulness of vendor offerings have been utilized in high-income countries (e.g. the Nutrient Environment Measures Survey for Stores (NEMS-S) and the Healthy Food Availability Index (HFAI)) (Franco et al., 2008; Glanz et al., 2007). However, these often seek to account for shelf-space and prominence of placement of healthy and unhealthy items, which is not included within the In-Depth Vendor Assessment Tool. Development and adaptation of such indicators typically requires classification of foods as healthy or unhealthy as well, which may be complex (see box on classification below).

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^[6] Diversity scores like MFDI are typically calculated as a sum of all the food groups in the benchmark basket that are present (e.g. a score of 29 using DQQ indicates that all DQQ food groups are present). In the case of DQQ and GDQS, MFDI scores may be calculated separately for healthy food groups and food groups to limit.

A note on level of analysis for availability indicators

These availability indicators can be calculated for individual food outlets, but policymakers and other data users may also like to aggregate measures over a neighborhood or other geographic delineation. This can be done by taking the median indicator value of all sampled outlets within the area, or, by establishing a cut-off threshold value for the indicator and calculating percent of outlets below or above it (Martins et al., 2013). For example, the count of unique vegetables available can be measured in 16 outlets in a neighborhood, and the median may be 4. There may also be interest in whether outlets offer at least 3 different vegetables (e.g. if FBDG require daily consumption of at least three vegetables). Depending on the distribution, the percentage of outlets with 3 unique vegetables or more can be calculated. If sampling is random and sample sizes are sufficient to be representative at the neighborhood level, findings can be generalized to the full population of outlets^[7].

When analyzing how availability indicators affect food purchases or diets, different approaches are also available for linking food outlets and outlets with consumers. Options for defining the boundaries of a household’s food environment include, but are not limited to:

1. all outlets in the same census tract (or other administrative division) as a household (taking the median of the indicator values from all sampled outlets in this area);
2. only the closest outlet to the household; and
3. all outlets within a specified distance of the household (taking the median of the indicator values from all sampled outlets in this buffer).

These approaches may yield different findings, as each is likely to link a different set of outlets to individual households, therefore changing the denominator of indicators. Approaches 2 and 3 may be less appropriate than Approach 1 when sampled outlets for In-Depth Vendor Assessment are only a small percentage of the total number of outlets present at cluster level or are not randomly sampled. In these scenarios, the nearest sampled outlet to a household may not be the outlet that is actually nearest, and sampled outlets within the specified buffer of households may not be adequate to accurately reflect the food environment in that area. However, Approach 1 will also have limitations for households that reside on or near administrative borders.

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^[7] Note that in the case of Community and Market Mapping, data is actually collected from all outlets in the study area, however, due to these potentially large sample sizes, it may be difficult to include lengthier questionnaires that assess the availability of individual food items. It is therefore the recommended approach to first conduct a Community and Market Mapping exercise and an In-Depth Vendor Assessment only among a sub-sample.

Tool and indicator validation

Similar tools as that described have been tested in urban, peri-urban, and rural settings of India and Cambodia as part of the development of the Food Environment Toolbox, and by USAID Advancing Nutrition in Honduras, Liberia, Nigeria, and Timor-Leste (Downs et al., 2025; Downs, Warne, et al., 2024). These pilot experiences did not formally assess validity or reliability, but gauged feasibility based on field experiences of enumerators and refined the tools accordingly.  The adapted NEMS-S for urban Brazil did test for inter-rater reliability, finding that enumerators were able to identify food groups and count foods within food groups with a high level of consistency (Martins et al., 2013). The original NEMS-S (as well as a version designed for restaurants) were also found to have high inter-rater reliability, test-retest reliability, in addition to face and discriminant validity (Glanz et al., 2007; Saelens et al., 2007). These tools included measurement of prices and shelf space, which are not required for measurement of diversity-based indicators, but results are promising that checklists of food item availability (yes/no) can be measured accurately. Future studies are encouraged to include reliability assessment.

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Sampling and data collection considerations

Sampling procedures should address selection of communities (the primary sampling unit) and food outlets within the communities. If including wet markets or farmers markets, researchers must also select these and decide how to sample individual vendors within these markets. For researchers interested in school food environments, primary sampling units may instead consist of schools and their surrounding geographic areas; this may also apply to other types of institutional food environments.

Selection of communities can be random or purposive. A random sample could be drawn from all urban and peri-urban areas of interest, while a purposive sample could focus on specific areas of interest – such as those where a program is being planned or areas of contrasting income levels. The definition of “community” may vary by setting, and may often consist of smaller geographic areas than those delineated by the lowest administrative units, especially in densely populated urban areas.

Due to the length of questionnaires and density of vendors in urban areas, it is not likely feasible to conduct In-Depth Vendor Assessment among all vendors in the study area, so additional sampling procedures are needed at this level. Formative information gathering in the study area with key informants and community members may help to identify specific outlet types that are most frequently used by the target population (e.g. wet markets, small retail shops, or mobile vendors), or are the most common access points for specific food groups of research interest. For example, if a study is interested in fruit and vegetable consumption and formative research indicates that 90% of purchases are from wet markets, data collection may take place exclusively in wet markets, seeking to sample all of such markets in the study area of interest. If only half of fruit and vegetable purchases are from wet markets and the remaining share is from specialty fruit and vegetable stalls or small retail shops, sampling could also include a certain percentage of those outlets.

A sampling frame, or complete listing of vendors in the study area, can be attained from the Community and Market Mapping Tool if a census has been previously carried out, or if local government maintains registries of vendors (though these may not include all informal vendors). Census and In-Depth Vendor Assessment can be carried out simultaneously by programming survey software to randomly select a specified percentage of outlets identified in the census for immediate in-depth assessment. If it is not possible to carry out a census and no public registries are available, other methods such as random-walk sampling can be used to select vendors for inclusion in the assessment, though these are not probability-based samples (Milligan et al., 2004).

If wet markets, farmers markets, or other multi-vendor outlets are included in the assessment, sampling of vendors in these locations can use one of two approaches: 1) the market is treated as a single location and enumerators seek to locate each food item on this list by examining all vendors’ offerings; 2) the enumerator samples only a sub-set of market vendors in the data collection and limits data collection to that sub-sample of vendors. The second method may be appropriate if there is reasonable uniformity in the range of food items offered by vendors (e.g. fruit vendors offer the same 4-5 fruits, grain vendors offer the same varieties of grains, etc.); this method may also allow the enumerator to gather additional information on vendor characteristics and include short interviews with those vendors on other aspects of the food environment if desired. This vendor-specific information is more difficult to attain through the first method, however that approach may be more appropriate if capturing the full range of food items available requires visiting a large number of vendors in the market.

If the second approach is used, it is recommended to stratify sampling of vendors by the food groups they specialize in, adhering to food group classifications included in FBDG, the Healthy Diet Basket (HDB), DQQ, or GDQS. While vendors may have a specialization in a certain type of food (e.g. legumes), it is not uncommon for them to offer other groups as well (e.g. grains or vegetables) – enumerators should include all items offered by the vendors in the data collection. Limiting data collection to a pre-specified food list is likely the most feasible option, but enumerators could conduct an open audit of all items as well. Open audits could be particularly useful to inform diet surveys, which may require information about the range of foods offered by local vendors.

Assembling a pre-specified food list

Deciding on which food items to assess availability for is another key step in planning the assessment and will depend on study objectives. If researchers are interested in access to foods that make up a healthy diet, it is important to include a range of food items from within the various food groups recommended as part of a healthy diet. If study objectives are focused on a narrower set of food groups, the food list could instead be limited to items in those groups. If repeated assessments will be carried out, food lists may also seek to capture availability of seasonal items.

Researchers may also be interested in assessing how availability of unhealthy foods influences food purchases and diets, so may choose to include commonly consumed discretionary foods in the list. For packaged items, food lists may also include examples of common brands to aid enumerators.

Assembling a food list should also consider whether any other dimensions of the food environment will be assessed in addition to availability, particularly food prices. For the assessment of cost of a healthy diet (CoHD) (see In-Depth Vendor Assessment Tool – Food Costs and Affordability), it is recommended to include foods that are both low-cost and commonly consumed within each food group. The table below provides a guideline for researchers interested in estimating the cost of the Healthy Diet Basket, which is a food basket developed to represent the commonalities of FBDGs around the world for global monitoring (A. W. Herforth et al., 2025).

While the Healthy Diet Basket requires only 1-3 items to be selected in each group, spatial variation in CoHD estimates across different urban areas and over time may be better captured if more items are monitored, as different items may be selected as the “low-cost items” included in CoHD in different areas and different times.

Healthy Diet Basket food group	Sub-category of food group	# of items to include in food list
Starchy staple foods		12
Vegetables		9 – 12
Also including:	Dark leafy green vegetables	2 – 3
	Vitamin-A rich orange vegetables and tubers	2 – 3
Fruit		6 – 10
Also including:	Vitamin-A rich orange fruits	2 – 3
Animal-source foods		10 – 12
Also including:	Milk and dairy products	1 – 2
	Fish and seafood	1 – 2
	Eggs	1 – 2
	Meat	1 – 2
Legumes, nuts, and seeds		5 – 6
Also including:	Legumes	2
	Nuts and seeds	1 – 2
Oils and fats		3 – 4

Food groups and items included in the list can be adapted to other target food baskets as well, including national food based dietary guidelines, DQQ, or GDQS.

Other data sources

Secondary data sources	Pros	Cons	Indicators
Vendor inventories	Inventories managed electronically by vendors can be a low-cost source of large quantities of data, and may even include historical data to examine trends	These may only be managed by large formal food vendors, such as supermarket chains, and may not be easily accessible	Food group diversity (e.g. MFDI) Within-group count of unique foods

Illustrative research using these tools and indicators in urban settings 

What are possible research questions you could ask that link diets and food environments?

• How much diversity of fruits, vegetables, and other healthy food groups (between and within-groups) is available in urban and peri-urban neighborhoods and how does this vary by socio-economic background of neighborhoods (e.g. income level) or other contextual factors?
• How does the variety of fruits, vegetables, and other healthy food groups change over time?
• Which types of food outlets and neighborhoods offer the greatest variety of unhealthy foods?
• Is diversity of healthy foods in local food environments associated with improved diet outcomes? (requires data on diet quality)

Resources related to In-Depth Vendor Assessment-Food Availability

• USAID Advancing Nutrition. 2023. “Guidelines for Market-Based Food Environment Assessments. Instruction Manual.” Arlington, VA. See Assessment 3 – Market Food Diversity Index
• IMMANA. 2023. “The Food Environment Toolbox: In-Depth Vendor Assessment Tool.” Note that this resource includes guidance for assessing a range of other food environment characteristics as well, including food promotion, vendor hygiene and food storage practices, and food labeling
• Ni Mhurchu, C., S. Vandevijvere, W. Waterlander, L. E. Thornton, B. Kelly, A. J. Cameron, W. Snowdon, and B. Swinburn. 2013. “Monitoring the Availability of Healthy and Unhealthy Foods and Non-Alcoholic Beverages in Community and Consumer Retail Food Environments Globally.” Obesity Reviews. https://doi.org/10.1111/obr.12080

References