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Systematic literature review of instruments that measure the healthfulness of food and beverages sold in informal food outlets



Informal food outlets, defined as vendors who rarely have access to water and toilets, much less shelter and electricity, are a common component of the food environment, particularly in many non-Western countries. The purpose of this study was to review available instruments that measure the quality and particularly the healthfulness of food and beverages sold within informal food outlets.


PubMed, LILACS, Web of Science, and Scopus databases were used. Articles were included if they reported instruments that measured the availability or type of healthy and unhealthy foods and beverages by informal food outlets, were written in English or Spanish, and published between January 1, 2010, and July 31, 2020. Two trained researchers reviewed the title, abstract and full text of selected articles; discrepancies were solved by two independent researchers. In addition, the list of references for selected articles was reviewed for any additional articles of relevance. The quality of published articles and documents was evaluated using JBI Critical appraisal checklist for analytical cross-sectional studies.


We identified 1078 articles of which 14 were included after applying the selection criteria. Three additional articles were considered after reviewing the references from the selected articles. From the final 17 articles, 13 measurement tools were identified. Most of the instruments were used in low- and middle-income countries (LMIC). Products were classified as healthy/unhealthy or produce/non-produce or processed/unprocessed based on availability and type. Six studies reported psychometric tests, whereas one was tested within the informal food sector.


Few instruments can measure the healthfulness of food and beverages sold in informal food outlets, of which the most valid and reliable have been used to measure formal food outlets as well. Therefore, it is necessary to develop an instrument that manages to measure, specifically, the elements available within an informal one. These actions are extremely important to better understand the food environment that is a central contributor to poor diets that are increasingly associated with the obesity and Non-communicable disease (NCD) pandemic.


The prevalence of nutrition-related non-communicable diseases (NCDs) including obesity, type 2 diabetes, hypertension, and cardiovascular disease, has increased globally, particularly in low- and middle-income countries (LMICs) [1, 2]. Moreover, most LMICs currently face the double burden of malnutrition, with a prevalence of stunting among children 0–59 months of 29.1% [3, 4].

The food environment is described as the availability, affordability, convenience, and desirability of various foods, [5] and has been a focus of increasing research interest. Food environments are hypothesized to partially explain the increase in the prevalence of obesity by providing greater access to unhealthy foods and/or lower access to healthy ones [6]. Several systematic reviews have been published summarizing the evidence on the impact of food environments on the association with nutrition- and health-related outcomes, as well as for methodologies used to measure food environments [7,8,9,10,11,12]. However, most of this research has been conducted in high-income countries, where informal food outlets or street food might not be as prevalent as in LMICs [13].

Informal food outlets are defined as vendors who rarely have access to water, toilets, shelter and electricity [14]. Informal food outlets could include street food vending, mobile food outlets, and open-air markets [15,16,17]. According to a systematic review, daily energy intake from foods consumed from informal food outlets ranged from 13 to 50% in adults, and from 13 to 40% in children in LMICs [18]. This study also documented the wide variety of street foods offered by informal food outlets, including healthy items such as fresh fruits, vegetables, and cooked legumes, but also unhealthy items such as soft drinks, cookies, pastries, deep-fried fish and meats, deep-fried snacks, along with other ultra-processed products. The range of foods offered also spans different processing levels, from minimally processed foods (e.g., fresh fruits), prepared dishes - either in advance or at the moment of purchase (e.g., stews and deep-fried fish), to ultra-processed foods (e.g., soft drinks and candies) [18].

In recent years, there has been an increase in the prevalence of away-from-home eating around the world and within LMICs [19,20,21,22,23,24,25]. Eating away from home has been associated with a high intake of low-quality foods, high in critical nutrients including saturated fat, cholesterol, and sodium [26]. Recently, there is a growing tendency of the food industry to blame street food on the high availability of unhealthy traditional food [27, 28]. However, even though several studies have assessed the nutrient contribution of street foods to dietary intake, [18, 29] evidence about the dietary quality of street food is limited. This might be partly explained by the wide variety of foods offered by informal food vendors and consequently, the complexity of measuring and standardizing such food environments. However, given the fundamental role of dietary intake in the double burden of malnutrition and the potential contribution of informal food options to dietary intake around the world, there is an urgent need for a standardized instrument to assess the dietary quality of street food to characterize it, explore associations with nutrition and health outcomes, and allow comparisons between places and across time. Therefore, the present study aimed to review the available instruments that measured the healthfulness of food and beverages sold within informal food outlets.


Informal food outlets

Informal food outlets are defined as vendors who rarely have access to water, toilets, shelter and electricity [14]. Informal food outlets are typified by street food vending that includes ready-to-eat foods or beverages prepared and/or sold in streets and public spaces by vendors or hawkers [15]. These vendors usually use portable booths, food carts, or trucks to sell food items [15]. Informal food outlets also include mobile food outlets that sell food out of a moveable vehicle, such as a truck, cart, trailer, kiosk or stand [16]. Open-air markets refer to those places with few or no permanent structures where buyers and sellers meet periodically and operate either daily or on a regular cycle [17]. Although farmer’s markets have been classified as formal markets by some researchers, [30] we included them in this literature review due to some similarities with the Latin informal food context; for example, some of these farmer’s markets have availability of ready-to-eat food. Farmer’s markets were defined as those that promote local and farm-fresh food [31].

Search strategy

The systematic steps of the Cochrane Handbook for Systematic Reviews of interventions was used in this study [32]. PubMed, Web of Science, Scopus, and LILACS databases and manual scan of reference lists were used to identify potential articles. Articles were included if they reported instruments that measured the availability or type of healthy and unhealthy foods and beverages by informal food outlets. Instruments were included regardless of whether they assessed other aspects such as price, quality, variety, promotion, and placement, were written in English or Spanish, and published from January 1, 2010, to July 31, 2020. Articles were excluded if they: only employed qualitative methodology; reported opinions or attitudes; only measured marketing and advertising of food; reported on results of food environment interventions, only discussed food policies or food promotion; assessed foods sold only in formal stores (e.g., supermarkets, corner stores, grocery stores or convenience stores); measured availability of healthy/unhealthy products through physical distances (e.g., number of healthy/unhealthy products by shelf dimensions/space) or by GPS; or assessed food composition through bromatological analyses. Table 1 describes the databases used and searches terms.

Table 1 Databases and search terms

Data collection process and synthesis of results

All citations were imported into an Excel spreadsheet and duplicates were removed manually. Two trained researchers reviewed and selected articles by title, abstract, and full text (JC and UL). Discrepancies were resolved by two independent researchers (CM and TA). For articles that met the inclusion criteria, data extraction was conducted by four researchers (JC, UL, TA, and CM). A data extraction form was developed and pilot tested on the first 10 selected articles and then refined. All researchers manually abstracted author, year, country, types of outlets, instrument description, healthy/unhealthy or produce/no produce or processed/without processing classification, and psychometrics tests into the extraction form. CM reviewed the information of each of the included articles. This information is presented descriptively in Table 2. Given the nature of our aim, a meta-analysis was not considered.

Quality of studies

The quality of published articles was evaluated using the (JBI) Critical appraisal checklist for analytical cross-sectional studies [53]. This checklist has eight questions that inquiries about inclusion criteria, subjects, and settings, validity and reliability of exposure measurements, standard criteria used for measurement of the condition, confounding factors, strategies to deal with confounding factors, validity and reliability of outcome measurements and appropriate statistical analysis [54]. Answers include yes, no, unclear, and not applicable. Overall appraisal encompasses “include”, “exclude”, and “seek further info”. This approach has been used elsewhere to assess the quality of studies [55]. Quality assessment was conducted by two independent reviewers (CM and UL) (Additional Material 1).


After removing duplicates, the literature search yielded 1078 articles, of which 47 were selected after being reviewed by title and abstract. This set included a total of 14 articles that were identified for a full review. In addition, 3 articles were selected through a manual search of the lists of references in the 14 included articles (Fig. 1).

Fig. 1
figure 1

PRISMA Flow diagram: Identification and selection of studies

In total, 17 studies described 13 instruments to classify how healthy/unhealthy are foods and/or beverages available within the informal food environment. The most common types of outlets considered in these reports were street food vendors, [38, 41, 42, 48, 50] farmers markets, [44, 45, 48, 49] open-air markets, [33,34,35], and mobile food vendors [33, 35, 36, 38, 41,42,43, 45, 46, 50, 52]. Tools included the Obesogenic Environment Study – observational tool for stores (ESAO-S), [33,34,35] different versions of the New Food Classification (NOVA), [36, 38, 39] adapted versions of Nutrition Environment Measures Survey – stores (NEMS-S), [43, 48] tools for farmers markets, [44, 49] standard Audit Forms for farmers markets, [50] the Food Retail Outlet Survey Tool (FROST), [45] assessment tool in US, [46] and audit tools from different countries [41, 42, 51, 52]. Six instruments were used in the Brazilian context [33,34,35,36, 39, 48]. In addition, an adaptation of the NEMS was used in the Mexican context (Mazatlán) [43]. Finally, NOVA classification was used in Mozambique [38, 41] and Tajikistan [42]. NOVA categorizes food and beverages according to food processing: unprocessed or minimally processed, processed culinary ingredients, processed foods and ultra-processed foods and drink products [36, 38, 39]. Further information on measurement tools is described in Table 2 (instrument description).

All the instruments evaluated the informal food environment through observation. All the tools that examined informal food outlets considered the availability and/or types of food and beverages. ESAO-S, [33,34,35], adaptation of NEMS [43, 48], FROST [45], and audit tools [51, 52] considered other characteristics such as variety, quality, quantity, price, advertising, promotion, and marketing. However, these variables were not used to classify food/beverages as healthy/unhealthy. Finally, instruments such as the adaptation of NEMS [48] and ESAO-S/HFSI [33, 34] created an overall indicator, considering several of the previous characteristics (e.g., variety, quality, price) to classify food/beverage outlets as healthy/unhealthy.

Some instruments included other topics such as tobacco, [45], and outlet characteristics (such as business name, type, and street address) [36, 38, 41, 42, 45, 46, 49, 50, 52]. Some tools measured the informal vending sites around schools [43], and bus stops [41]. Among the available instruments, several differences were found, including the way data was collected (e.g., checklists (availability yes/no), questionnaires).

Some instruments classified available and types of food and beverages as healthy and unhealthy [33,34,35, 43, 45, 46, 48,49,50,51,52] or produce (such as fresh products)/non-produce (such as processed food) [44]. Others used the NOVA classification based on food processing [36, 38, 39]. One instrument used fruit and beverages, homemade or industrial classification [41, 42]. Finally, some authors described the availability of food items as percentages or means, [35, 36, 41, 42, 44,45,46, 50,51,52] some others utilized calculated scores [33, 34, 48, 49]. The psychometric tests of the instruments included inter-rater reliability, [35, 39, 45, 48,49,50] test-retest reliability [35, 39, 45], and content, construct or face validity [35, 39, 45, 49]. Some others only performed pilot testing [44, 46, 48, 49, 51]. Seven studies did not report any psychometric tests [36, 38, 41, 42, 46, 51, 52]. In total, six studies reported psychometric tests either in the formal or informal food outlets, [35, 39, 45, 48,49,50] and one did so in terms of informal outlets only [49].

All the tools classified fruit and vegetables as healthy; however, some tools considered additional products within the healthy category including whole grains (e.g., bread and cereals), [45, 46, 48,49,50] plain/low-fat milk, [45, 48, 50, 51] nuts, [46, 48, 50] roots, and tubers, [48] beans, [48, 51] traditional dishes, [51] fresh meat [48, 49, 51] and fish [45, 51], eggs, [45, 48, 49, 51] reduced/low-fat yogurt, [48] some cheeses, [48, 49] and plain or mineral water [45, 50]. Studies based on NOVA classified unprocessed or minimally processed foods to be healthy, i.e., mainly of natural origin, preferably produced by agroecological methods, and appropriate and supportive of socially and environmentally sustainable food systems. These can include fresh fruits, fresh vegetables, fresh meat, milk, grains, legumes, nuts, teas, coffee, herb infusions, and tap and spring water in addition to fruit and vegetables [36, 38, 39]. A summary of these results is described in Table 2.

Almost all instruments classified processed foods/beverages [46, 48] as unhealthy, these included sweetened beverages, [33,34,35, 43, 49, 51, 52] corn or potato chips, [33,34,35] cream-filled cookies, [33,34,35] packed snacks (salty/fried, sweet, or frozen) [43, 52], non-whole-grain baked sweets, [44] savory items, [44] juice/ciders, [44] sugar-added items, [44] concentrated sweets, [44] refined sweets, [49] salty/fatty fare, [49] alcohol, [49, 51] cooking oils or fats, [51] jam, [51] hazelnut, [51] fried plantain, [51] processed meats, [51] pies, [51] cakes, [51] ice-cream, [51] chocolate, [51] pizza, [51] lasagna, [51] and ketchup [51]. And based on NOVA classification: Unhealthy or ultra-processed food and drink products: such as industrial formulations ready to be consumed, manufactured from five or even more ingredients commonly used in foods [39] (Table 2).

Study quality

Based on the (JBI) Critical Appraisal Checklist for Analytical Cross-Sectional Studies, 9 out of 17 studies did not report if the exposure was measured validly and reliably [36, 38, 41,42,43,44, 46, 51, 52]. Due to the nature of the studies, almost all of them (n = 13) did not include confounding factors. The overall mean rating was “Included” (Additional Material 1).

Table 2 Measurement tools that evaluates “how healthy/unhealthy” are the food and beverages sold within the informal food outlets


The purpose of this literature review was to evaluate available instruments that measure the healthfulness of products sold within the informal food outlets. In total, 17 articles were included and 13 measurement tools were identified. Most of the instruments were used in LMIC and all of them evaluated the food environment through observation. All the tools classified fruit and vegetables as healthy; however, some tools considered additional products within the healthy category. Furthermore, almost all instruments classified ultra-processed foods/beverages as unhealthy. Some instruments used other attributes such as variety, quantity, price, promotion, and advertising to generate a score that allows for classifying how healthy/unhealthy are food outlets. Six out of 13 instruments reported at least one psychometric test.

Studies from high-income countries have shown how inequality is associated with unhealthier food environments; i.e., people from lower-income neighborhoods have higher access to unhealthy products from formal food outlets such as convenience and grocery stores [56, 57]. However, most of this evidence came from the formal food environment. Conversely, a higher percentage of people from LMIC tend to buy products from informal food outlets such as street markets or street food stands [58]. In addition, evidence from LMICs shows that informal food outlets could contribute to > 10% of daily intake in adults and children [18]. The prevalence of food consumption away from home has increased around the world and within the LMICs [19,20,21,22,23,24,25]. Given the variety of products informal food outlets offer, evaluating the healthiness of these is a complex task. Thus, further research is needed to understand the contribution of these products to health outcomes.

Concerning the instruments per se, many differences make comparisons difficult. First of all, there are dissimilarities in the way instruments collect data, for instance, checklist (available yes/not) or questionnaires based on several elements including availability, accessibility, variety, quality, quantity, price, advertising, and/or promotion [43, 45]. Secondly, contrasts in foods/beverages considered healthy, i.e., only fruit and vegetables, or fruit and vegetables and whole grains, plain/low-fat milk, nuts, beans, traditional dishes, fresh meat and fish or eggs, reduced/low fat yogurt and plain or mineral water [45, 46, 48,49,50,51].

The accuracy of instruments assures that tools can be used by multiple researchers, at different times and can measure what is expected to be measured. Within this review, we found that only three tools reported inter-rater reliability, test-retest, and construct/content validity [35, 40, 45]. Nine studies reported at least one psychometric test, [35, 40, 44,45,46, 48,49,50,51] some others reported only pilot testing [44, 46, 48, 49, 51] or no testing [36, 38, 41,42,43, 52]. A systematic review that identified 48 tools to measure the food outlets reported that only 39% of them provided psychometric tests [59]. Given that food/beverages sold within the informal food outlets positively or negatively affect the dietary quality of children and adults, it is extremely important to have reliable and valid instruments to measure what is sold in these places.

There are some challenges when evaluating informal food outlets. This includes differences in the venues, for instance, open-air markets could be classified as informal food outlets in countries such as Brazil, [33] whereas, street vendors are the most common informal food outlet in other countries (Mozambique [38] and Mexico [43]). In addition, there are some elements of the informal food outlets that could hinder the assessment. Among these, are the abuse by the authorities of which they are victims in some contexts, their fear of being identified as not having business permits, and inconsistent hours of the points of sale. One of the most important relates to the itinerant or semi-itinerant vending such as vendors’ fear of being identified as not having business permits, and inconsistent schedules of outlets. Thus, future studies should consider these elements in the selection and/or creation of instruments to generate better quality information.

Although several instruments, mainly from high-income countries, have been used to measure formal food outlets, we found that 7 measurement tools were also used to measure informal food outlets. However, there are some limitations in evaluating a street food stand in the same way as a formal food store (such as a convenience store): 1) there are elements that cannot be present, at least to the same extent, in informal food outlets such as interior and exterior advertising or promotions, [45] 2) there are differences in how formal and informal outlets display food items, [60] and 3) there is proportionally higher availability of prepared food in informal outlets foods compared to formal food stores [58].

Available and/or newly developed tools should consider other aspects such as: 1) allow comparisons between countries at least in terms of the general characteristics of the environment, 2) include other elements such as price, degree of processing, hygiene, 3) include a local adaptation methodology before its implementation [61], 4) consider different contexts, and 5) allow comparisons between the formal and informal food environment. This last point is crucial because some formal food retailers such as “fondas” – family-run stalls or small canteens where food and drinks are sold in the Mexican context may offer products, in a quick-serve fashion and at a low cost, similar to what the informal food outlets could offer (such as in the case of food trucks).

Finally, given the increasing prevalence of NCDs, governments of all parts of the world have implemented a package of strategies including soda tax, the front of package labelling, and school policy regulations [62]. In countries such as Mexico, the food industry claims that products sold within informal food outlets could contribute to the high prevalence of overweight and obesity and not their products [27, 28]. However, this has not been substantiated by scientific research. Based on our results, further research is needed to: 1) characterize the informal food environment, 2) estimate the percentage of ultra-processed foods and basic non-industrialized foods in this environment, 3) understand the main contribution of these outlets to the diet and in the near future, if necessary, 4) to develop interventions to improve food environment aimed at promoting changes in offer and preparation by these outlets.

Limitation and strengths

This study identified potential instruments that can be used to evaluate informal food outlets. We conducted a systematic literature review using four different databases; however, we did not search the “gray literature.” Therefore, we could have potentially missed some information. We used available definitions for informal food outlets; however, there may be alternative forms of informal food outlets in different regions of the world that we did not fully capture. Some studies were included despite not having a perfect quality assessment, so caution should be taken when these instruments are used to assess the healthfulness of informal food outlets.


Although we found 13 instruments that have been developed or adapted to measure how healthy are food/beverages available at informal food outlets, only three performed inter-rater reliability, test-retest reliability, and validity, of which they were not used to exclusively measure informal food outlets. There are many drawbacks to measuring informal food outlets in the same way as formal food outlets. Therefore, it is necessary to develop an instrument that measures the elements specific to the informal food environment.

Additional research in this area is urgently needed to better understand a key aspect of the food environment that may be a central contributor to poor diets that are increasingly associated with the obesity and Non-communicable disease (NCD) pandemic.

Registration and protocol

There is no available registration number. This protocol was reviewed and approved by the Ethical Board of the National Institute of Public Health Mexico (Number: CI 1684). This systematic literature review followed PRISMA guidelines (Additional Material 2) [63].

Availability of data and materials

All data generated or analyzed during this study are included in this published article.



Food Retail Outlet Survey Tool


Fruit and vegetables


Global Positioning System


Healthy food store index


Low- and middle-income countries


New Food Classification


Non-communicable diseases


Nutrition Environment Measures Survey – stores


Nutrition Environment Measures Survey – restaurants


Obesogenic Environment Study – observational tool for stores


United States of America


  1. Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al. Global burden of cardiovascular diseases and risk factors, 1990-2019: update from the GBD 2019 study. J Am Coll Cardiol. 2020;76(25):2982–3021.

    PubMed  PubMed Central  Article  Google Scholar 

  2. Collaborators GBDRF. Global burden of 87 risk factors in 204 countries and territories, 1990-2019: a systematic analysis for the global burden of disease study 2019. Lancet. 2020;396(10258):1223–49.

    Article  Google Scholar 

  3. Ssentongo P, Ssentongo AE, Ba DM, Ericson JE, Na M, Gao X, et al. Global, regional and national epidemiology and prevalence of child stunting, wasting and underweight in low- and middle-income countries, 2006-2018. Sci Rep. 2021;11(1):5204.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  4. Popkin BM, Corvalan C, Grummer-Strawn LM. Dynamics of the double burden of malnutrition and the changing nutrition reality. Lancet. 2020;395(10217):65–74.

    PubMed  Article  Google Scholar 

  5. Herforth A, Ahmed S. The food environment, its effects on dietary consumption, and potential for measurement within agriculture-nutrition interventions. Food Security. 2015;7(3):505–20.

    Article  Google Scholar 

  6. Black JL, Macinko J. Neighborhoods and obesity. Nutr Rev. 2008;66(1):2–20.

    PubMed  Article  Google Scholar 

  7. Feng J, Glass TA, Curriero FC, Stewart WF, Schwartz BS. The built environment and obesity: a systematic review of the epidemiologic evidence. Health Place. 2010;16(2):175–90.

    PubMed  Article  Google Scholar 

  8. Cobb LK, Appel LJ, Franco M, Jones-Smith JC, Nur A, Anderson CA. The relationship of the local food environment with obesity: a systematic review of methods, study quality, and results. Obesity (Silver Spring). 2015;23(7):1331–44.

    Article  Google Scholar 

  9. Gamba RJ, Schuchter J, Rutt C, Seto EY. Measuring the food environment and its effects on obesity in the United States: a systematic review of methods and results. J Community Health. 2015;40(3):464–75.

    PubMed  Article  Google Scholar 

  10. Mackenbach JD, Nelissen KGM, Dijkstra SC, Poelman MP, Daams JG, Leijssen JB, et al. A systematic review on socioeconomic differences in the association between the food environment and dietary behaviors. Nutrients. 2019;11(9).

  11. Wilkins E, Radley D, Morris M, Hobbs M, Christensen A, Marwa WL, et al. A systematic review employing the GeoFERN framework to examine methods, reporting quality and associations between the retail food environment and obesity. Health Place. 2019;57:186–99.

    PubMed  Article  Google Scholar 

  12. Lytle LA, Sokol RL. Measures of the food environment: a systematic review of the field, 2007-2015. Health Place. 2017;44:18–34.

    PubMed  Article  Google Scholar 

  13. Turner C, Aggarwal A, Walls H, Herforth A, Drewnowski A, Coates J, et al. Concepts and critical perspectives for food environment research: a global framework with implications for action in low- and middle-income countries. Global Food Security. 2018;18:93–101.

    Article  Google Scholar 

  14. Skinner C. Informal Food Retail in Africa: A Review of Evidence. 2016. In: consuming urban poverty project working paper No2 [internet]. African Centre for Cities, University of Cape Town.

  15. Fellows P, Hilmi M. Selling street and snack foods: FAO diversification booklet 18; 2012.

    Google Scholar 

  16. Mobile Food Retail. Encouraging healthier mobile food retailers to operate in underserved areas: CDC. Available from:

  17. Cherono I, Jakinda D. Peri-urban food traders’ preferences for open-air market and managment attributes in Nairobi, Kenya: 5th International Conference of AAAE; 2016 [Available from:

  18. Steyn NP, McHiza Z, Hill J, Davids YD, Venter I, Hinrichsen E, et al. Nutritional contribution of street foods to the diet of people in developing countries: a systematic review. Public Health Nutr. 2014;17(6):1363–74.

    PubMed  Article  Google Scholar 

  19. Claro RM, Baraldi LG, Martins AP, Bandoni DH, Levy RB. Trends in spending on eating away from home in Brazil, 2002-2003 to 2008-2009. Cad Saude Publica. 2014;30(7):1418–26.

    PubMed  Article  Google Scholar 

  20. INEGI. Encuesta Nacional de Ingresos y Gastos de los Hogares (ENIGH) 2018 [Available from:

  21. INEGI. Encuesta Nacional de Ingresos y Gastos de los Hogares (ENIGH)2016. Available from:

  22. Wellard-Cole L, Davies A, Chen J, Jung J, Bente KB, Kay J, et al. The contribution of foods prepared outside the home to the diets of 18- to 30-year-old Australians: the MYMeals study. Nutrients. 2021;13(6).

  23. Todd JE. Changes in consumption of food away from home and intakes of energy and other nutrients among US working-age adults, 2005-2014. Public Health Nutr. 2017;20(18):3238–46.

    PubMed  Article  Google Scholar 

  24. Orfanos P, Naska A, Trichopoulos D, Slimani N, Ferrari P, van Bakel M, et al. Eating out of home and its correlates in 10 European countries. The European prospective investigation into Cancer and nutrition (EPIC) study. Public Health Nutr. 2007;10(12):1515–25.

    PubMed  Article  Google Scholar 

  25. Adams J, Goffe L, Brown T, Lake AA, Summerbell C, White M, et al. Frequency and socio-demographic correlates of eating meals out and take-away meals at home: cross-sectional analysis of the UK national diet and nutrition survey, waves 1-4 (2008-12). Int J Behav Nutr Phys Act. 2015;12:51.

    PubMed  PubMed Central  Article  Google Scholar 

  26. Wellard-Cole L, Davies A, Allman-Farinelli M. Contribution of foods prepared away from home to intakes of energy and nutrients of public health concern in adults: a systematic review. Crit Rev Food Sci Nutr. 2021;1-12.

  27. El poder del consumidor. Exceso de mentiras en los argumentos de la industria. Mito 4: Los antojitos causan obesidad 2021 [Available from:

  28. Sánchez I. Comer en la calle en México: entre orgullo y sentimiento de culpa 2018 [Available from:

  29. Oguntona CR, Kanye O. Contribution of street foods to nutrient intakes by Nigerian adolescents. Nutr Health. 1995;10(2):165–71.

    CAS  PubMed  Article  Google Scholar 

  30. Downs SM, Ahmed S, Fanzo J, Herforth A. Food environment typology: advancing an expanded definition, framework, and methodological approach for improved characterization of wild, cultivated, and built food environments toward sustainable diets. Foods. 2020;9(4).

  31. Guderson M, Wysocki J. A funtional evaluation of business models in fresh produce in the United States. In: Postharvest handling a system approach. USA: Food Science and Technology; 2009. p. 129–52.

    Chapter  Google Scholar 

  32. Higgins J, Green S. Handbook for systematic reviews of interventions version 5.1.0: The Cochrane Collaboration; 2011 [Available from:

  33. Costa BVL, Menezes MC, Oliveira CDL, Mingoti SA, Jaime PC, Caiaffa WT, et al. Does access to healthy food vary according to socioeconomic status and to food store type? An ecologic study. BMC Public Health. 2019;19(1):775.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. Duran AC, Diez Roux AV, Latorre Mdo R, Jaime PC. Neighborhood socioeconomic characteristics and differences in the availability of healthy food stores and restaurants in Sao Paulo. Brazil Health Place. 2013;23:39–47.

    PubMed  Article  Google Scholar 

  35. Duran AC, Lock K, Latorre Mdo R, Jaime PC. Evaluating the use of in-store measures in retail food stores and restaurants in Brazil. Rev Saude Publica. 2015;49.

  36. Leite FH, Oliveira MA, Cremm EC, Abreu DS, Maron LR, Martins PA. Availability of processed foods in the perimeter of public schools in urban areas. J Pediatr. 2012;88(4):328–34.

    Article  Google Scholar 

  37. Monteiro CA, Levy RB, Claro RM, Castro IR, Cannon G. A new classification of foods based on the extent and purpose of their processing. Cad Saude Publica. 2010;26(11):2039–49.

    PubMed  Article  Google Scholar 

  38. Gelormini M, Damasceno A, Lopes SA, Malo S, Chongole C, Muholove P, et al. Street food environment in Maputo (STOOD map): a cross-sectional study in Mozambique. JMIR Res Protoc. 2015;4(3):e98.

    PubMed  PubMed Central  Article  Google Scholar 

  39. Monteiro C, Cannon G, Levy R, Moubarac J-C, Jaime P, Martins AP. NOVA: the star shines bright. World Nutrition. 2016;7:28–38.

    Google Scholar 

  40. Borges CA, Jaime PC. Development and evaluation of food environment audit instrument: AUDITNOVA. Rev Saude Publica. 2019;53:91.

    PubMed  Article  Google Scholar 

  41. Sousa S, Gelormini M, Damasceno A, Lopes SA, Malo S, Chongole C, et al. Street food in Maputo, Mozambique: availability and nutritional value of homemade foods. Nutr Health. 2019;25(1):37–46.

    PubMed  Article  Google Scholar 

  42. Albuquerque G, Morais I, Gelormini M, Casal S, Damasceno A, Pinho O, et al. Street food in Dushanbe, Tajikistan: availability and nutritional value. Br J Nutr. 2019;122(9):1052–61.

    CAS  PubMed  Article  Google Scholar 

  43. Bridle-Fitzpatrick S. Food deserts or food swamps?: a mixed-methods study of local food environments in a Mexican city. Soc Sci Med. 2015;142:202–13.

    PubMed  Article  Google Scholar 

  44. Lucan SC, Maroko AR, Sanon O, Frias R, Schechter CB. Urban farmers' markets: accessibility, offerings, and produce variety, quality, and price compared to nearby stores. Appetite. 2015;90:23–30.

    PubMed  PubMed Central  Article  Google Scholar 

  45. Hosler AS, Dharssi A. Reliability of a survey tool for measuring consumer nutrition environment in urban food stores. J Public Health Manag Pract. 2011;17(5):E1–8.

    PubMed  Article  Google Scholar 

  46. Lucan SC, Varona M, Maroko AR, Bumol J, Torrens L, Wylie-Rosett J. Assessing mobile food vendors (a.k.a. street food vendors)--methods, challenges, and lessons learned for future food-environment research. Public Health. 2013;127(8):766–76.

    CAS  PubMed  Article  Google Scholar 

  47. Lucan SC, Maroko AR, Bumol J, Varona M, Torrens L, Schechter CB. Mobile food vendors in urban neighborhoods-implications for diet and diet-related health by weather and season. Health Place. 2014;27:171–5.

    PubMed  PubMed Central  Article  Google Scholar 

  48. Martins PA, Cremm EC, Leite FH, Maron LR, Scagliusi FB, Oliveira MA. Validation of an adapted version of the nutrition environment measurement tool for stores (NEMS-S) in an urban area of Brazil. J Nutr Educ Behav. 2013;45(6):785–92.

    PubMed  Article  Google Scholar 

  49. Byker Shanks C, Jilcott Pitts S, Gustafson A. Development and validation of a Farmers' market audit tool in rural and urban communities. Health Promot Pract. 2015;16(6):859–66.

    PubMed  PubMed Central  Article  Google Scholar 

  50. Lucan SC, Maroko AR, Patel AN, Gjonbalaj I, Elbel B, Schechter CB. Healthful and less-healthful foods and drinks from storefront and non-storefront businesses: implications for 'food deserts', 'food swamps' and food-source disparities. Public Health Nutr. 2020;23(8):1428–39.

    PubMed  PubMed Central  Article  Google Scholar 

  51. Green MA, Pradeilles R, Laar A, Osei-Kwasi H, Bricas N, Coleman N, et al. Investigating foods and beverages sold and advertised in deprived urban neighbourhoods in Ghana and Kenya: a cross-sectional study. BMJ Open. 2020;10(6):e035680.

    PubMed  PubMed Central  Article  Google Scholar 

  52. Valdez Z, Dean WR, Sharkey JR. Mobile and home-based vendors' contributions to the retail food environment in rural South Texas Mexican-origin settlements. Appetite. 2012;59(2):212–7.

    PubMed  PubMed Central  Article  Google Scholar 

  53. Moola S, Munn Z, Tufanaru C, Aromataris E, Sears K, Sfetcu R, Currie M, Qureshi R, Mattis P, Lisy K, Mu P-F. Chapter 7: Systematic reviews of etiology and risk. 2017. In: Joanna Briggs institute Reviewe’s manual [internet]. The Joanna Briggs institute. Available from:

  54. Pethrick H, Nowell L, Paolucci EO, Lorenzetti L, Jacobsen M, Clancy T, et al. Peer mentoring in medical residency education: a systematic review. Can Med Educ J. 2020;11(6):e128–e37.

    PubMed  PubMed Central  Google Scholar 

  55. Giraud A, Stephens CM, Boylan GB, Walsh BH. The impact of perinatal inflammation on the electroencephalogram in preterm infants: a systematic review. Pediatr Res. 2022.

  56. Franco M, Diez Roux AV, Glass TA, Caballero B, Brancati FL. Neighborhood characteristics and availability of healthy foods in Baltimore. Am J Prev Med. 2008;35(6):561–7.

    PubMed  PubMed Central  Article  Google Scholar 

  57. Black C, Moon G, Baird J. Dietary inequalities: what is the evidence for the effect of the neighbourhood food environment? Health Place. 2014;27:229–42.

    PubMed  Article  Google Scholar 

  58. Rosales Chavez JB, Bruening M, Ohri-Vachaspati P, Lee RE, Jehn M. Street food stand availability, density, and distribution across income levels in Mexico City. Int J Environ Res Public Health. 2021;18(8).

  59. Ohri-Vachaspati P, Leviton LC. Measuring food environments: a guide to available instruments. Am J Health Promot. 2010;24(6):410–26.

    PubMed  Article  Google Scholar 

  60. Glanz K, Sallis JF, Saelens BE, Frank LD. Nutrition environment measures survey in stores (NEMS-S): development and evaluation. Am J Prev Med. 2007;32(4):282–9.

    PubMed  Article  Google Scholar 

  61. Moayyed H, Kelly B, Feng X, Flood V. Evaluation of a 'healthiness' rating system for food outlet types in Australian residential communities. Nutr Diet. 2017;74(1):29–35.

    PubMed  Article  Google Scholar 

  62. Popkin BM, Barquera S, Corvalan C, Hofman KJ, Monteiro C, Ng SW, et al. Towards unified and impactful policies to reduce ultra-processed food consumption and promote healthier eating. Lancet Diabetes Endocrinol. 2021;9(7):462–70.

    PubMed  PubMed Central  Article  Google Scholar 

  63. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;372:n71.

    PubMed  PubMed Central  Article  Google Scholar 

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We would like to acknowledge the contribution of Ana Isabel Rodríguez from the Public Health Master’s program at the National Institute of Public Health, Mexico.

Authors' contributions

Conceptualization CM, SB; Formal analysis CM, MP, UL, JCH, TA; Funding acquisition SB; Investigation CM; Methodology CM and MP; Project administration CM; Resources SB; Software CM; Supervision MP and SB; Validation MP and SB; Visualization MP and SB; Witting-Original draft CM, UL, JCH, TA; Writing-Review and editing SB, MP, MM, TH, AG, TA, UL, JCH, CG, CM. The author(s) read and approved the final manuscript.


This study was supported by Bloomberg Philanthropies (project number 43003) and the CONACYT-PRONASE-SALUD study (project number 2256, CI:1767). The funders had no role in the study design, data collection, and analysis, decision to publish, or preparation of the manuscript.

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Correspondence to Simón Barquera.

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The study was reviewed and approved by the Instituto Nacional de Salud Publica’s institutional review board. Methods were carried out in accordance with relevant guidelines and regulations.

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Supplementary Information

Additional file 1: Additional Material 1

. JBI Critical appraisal checklist for analytical cross-sectional studies

Additional file 2.

PRISMA 2020 Checklist.

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Medina, C., Piña-Pozas, M., Aburto, T.C. et al. Systematic literature review of instruments that measure the healthfulness of food and beverages sold in informal food outlets. Int J Behav Nutr Phys Act 19, 89 (2022).

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  • Food environment
  • Measurements
  • Informal food outlets
  • Literature review
  • Street food