Profile of food and beverage street vendors around private schools in Brazil

ABSTRACT

OBJECTIVE  To describe the socioeconomic profile and activity of street vendors, as well as the profile of food sales, according to industrial processing, in the vicinity of private schools in Brazilian state capitals.

METHODS  Cross-sectional study with street vendors in the immediate vicinity of a national probability sample of Brazilian private schools. Elementary and/or high schools participating in the Food Marketing in Brazilian Schools Study were included. A previously validated questionnaire was applied to characterize workers, infrastructure and food availability. Food was classified according to the NOVA system. Comparisons between macro-regions (North, Northeast, Central-West, Southeast, and South) and sizes of point of sale (smallest: 1–3 items; intermediate: 4–13 items; largest: ≥ 14 items) were evaluated using the Kruskal-Wallis test.

RESULTS  The informal food and beverage trade in the immediate vicinity of 2,180 private schools was mapped, totaling 699 street vendors. There was a predominance of men (57.8%), black people (68.8%), those with completed secondary education (35.8%), and those who worked informally (91.4%), in carts and stalls, due to a lack of opportunity in the formal market (52.5%). The median number of ultra-processed items was about twice that of in natura, minimally processed, or processed foods and preparations based on them (2.17; 95%CI 1.90–2.45). Larger outlets concentrated more ultra-processed foods in all regions, except in the Northeast, where this predominance already occurred in intermediate-sized outlets (3.32; 95%CI 2.88–3.75). The lowest ratio of ultra-processed foods was observed in the South (0.21; 95%CI 0.05–0.37) and the highest in the Northeast (3.32; 95%CI 2.88–3.75).

CONCLUSION  Street vending around Brazilian private schools reflects structural inequalities and expands commercially in the supply of ultra-processed foods to children and adolescents. We recommend its inclusion as an inseparable component in the evaluation of the school food environment, to support policies that reconcile income generation and the promotion of healthy eating.

DESCRIPTORS
Ultra-Processed Foods; Food Environment; Schools; Nutritional Sciences; Informal Sector

RESUMO

OBJETIVO  Descrever o perfil socioeconômico e de atuação dos ambulantes, bem como o perfil de comercialização de alimentos, segundo o processamento industrial, no entorno de escolas privadas nas capitais brasileiras.

MÉTODOS  Estudo transversal com ambulantes no entorno imediato de uma amostra probabilística nacional de escolas privadas brasileiras. Foram incluídas escolas de ensino fundamental e/ou médio, participantes do Estudo Comercialização de Alimentos em Escolas Brasileiras. Aplicou-se questionário previamente validado para caracterizar trabalhador, infraestrutura e disponibilidade de alimentos. Os alimentos foram classificados segundo o sistema NOVA. Comparações entre macrorregiões (Norte, Nordeste, Centro-Oeste, Sudeste e Sul) e portes de ponto de venda (menor: 1–3 itens; intermediário: 4–13 itens; maior: ≥ 14 itens) foram avaliadas pelo teste de Kruskal–Wallis.

RESULTADOS  Foi mapeado o comércio informal de alimentos e bebidas no entorno imediato de 2.180 escolas privadas, totalizando 699 ambulantes. Predominaram homens (57,8%), pessoas negras (68,8%), com ensino médio completo (35,8%) e que subsistiam da informalidade (91,4%), em carrinhos e barracas, por falta de oportunidade no mercado formal (52,5%). A mediana de itens ultraprocessados superou em cerca de duas vezes a de alimentos in natura, minimamente processados ou processados e preparações baseadas neles (2,17; IC95% 1,90–2,45). Pontos comerciais de porte maior concentraram mais ultraprocessados em todas as regiões, exceto no Nordeste, onde essa predominância já ocorria no porte intermediário (3,32; IC95% 2,88–3,75). A menor razão de ultraprocessados foi observada no Sul (0,21; IC95% 0,05–0,37) e a maior, no Nordeste (3,32; IC95% 2,88–3,75).

CONCLUSÃO  O comércio ambulante no entorno de escolas privadas brasileiras reflete desigualdades estruturais e expande-se comercialmente na oferta de ultraprocessados para crianças e adolescentes. Recomenda-se sua inclusão como componente indissociável na avaliação do ambiente alimentar escolar, para subsidiar políticas que conciliam geração de renda e promoção da alimentação saudável.

DESCRITORES
Alimentos Ultraprocessados; Ambiente Alimentar; Escolas; Nutrição em Saúde Pública; Setor Informal

INTRODUCTION

The school food environment is the mediating scenario between students and the food choices that take place in and around the school¹,². Elements such as infrastructure, the availability of nutritional information, and the commercialization of food services — formal and informal — directly influence these choices and students’ food autonomy¹.

Among these services, informal tradesmen (street vendors) are responsible for selling 13%–40% of the food consumed daily by children in low- and middle-income countries³. In Brazil, street vendors are part of everyday school life with ready-made, affordable, and often homemade food⁴. However, their itinerant nature⁵ makes it difficult to evaluate them in research, despite studies highlighting their relevance to understanding food environments²,⁵.

Although they are present with a frequency similar to that of snack bars and corner stores in school surroundings⁶, informal commerce is often neglected in the study of food environments and is pointed out as an important methodological limitation². This limitation is worrying, considering that the availability of food in and around schools has an impact on food and nutritional health and safety¹. Evidence associates the massive presence of street vendors with overweight among children in school⁶ and greater accessibility to poorly nutritious foods that are cheaper than healthy options⁷.

Knowing the characteristics of the informal food trade is therefore essential to support regulatory measures that promote healthy school environments. In addition, it is important to recognize that, in middle- and low-income countries such as Brazil, the sale of street food represents not only affordable food in large cities, but also a livelihood strategy adopted by workers⁸. However, most studies on informal commerce have focused on hygiene and health conditions⁹,¹⁰, neglecting sociodemographic aspects and the dynamics of operation that would allow for a more comprehensive and contextualized view of this component of the food environment.

Given these gaps, the aim of this study was to describe the socio-economic profile and activities of street vendors, as well as the profile of food sales, according to industrial processing, in the vicinity of private schools in Brazilian state capitals.

METHODS

Design and Population

A cross-sectional study of street vendors selling food in the immediate vicinity of private primary and/or secondary schools in the 26 Brazilian state capitals and the Federal District. This analysis is part of the Estudo Comercialização de Alimentos em Escolas Brasileiras (Caeb - Food Marketing in Brazilian Schools Study). Conducted from 2022 to 2024, the main objective was to evaluate aspects related to the marketing of food and beverages in Brazilian private schools, based on information collected from managers of school canteens and street vendors present in the immediate vicinity of the schools¹¹.

The study complied with Resolutions No. 466/2012 and No. 510/2016 of the National Health Council and was approved by the relevant ethics committees in the places where it was carried out, as per opinions 5.531.874; 5.913.835; 5.240.459; 6.942.713; 6.796.515; 5.709.474; 6.179.413; 5.427.066; 6.172.595; 6.002.739; 6.270.770; 4.506.207; 5.446.216; 5.060.837; 5.526.372; 5.959.036 and 6.188.500. All participants signed the consent form.

Sample and Sampling

Given the lack of formal records or registration with regulatory bodies to estimate the number of street vendors around schools in Brazil, the number of schools eligible for the Caeb study was used as a reference, following probabilistic sampling by simple random selection with inverse replacement, detailed in Canuto et al.¹¹ The study included street vendors selling ready-to-eat food and beverages in the immediate vicinity of the schools located at the time of canteen data collection. The immediate surroundings were defined as the school gates, all the sidewalks immediately adjacent to the entrance/exit and on the side sidewalks of the schools, as well as in the immediate block, as long as the point of sale faced the school entrance/exit.

Points of sale within four masonry walls, vending machines, raw food not ready for consumption, organized fairs (farmers’ markets, open-air fairs, street markets), and mobile structures linked to formal businesses were excluded. In schools where there was more than one street vendor, all were invited to take part in the survey. The samples were collected on school days (7am to 4pm)¹¹.

Variables

Socio-economic Characteristics of Street Vendors

We analyzed the street vendors’ socio-economic (gender, age, race/skin color, schooling, main source of income, length of time in the informal trade, and motivation for working informally) and performance (location, physical structure — as shown in the Chart —, selling elsewhere, working shifts, days of work, relationship with school management, registration with public bodies, and impediment to activity) characteristics.

Chart
Characteristics used to identify the physical structure of street vendors when collecting data for the Caeb national survey.

Structure	Characterization
Cart	Those means of sale that have wheels for locomotion, but are not motorized, with or without a cover.
Private car	Those means of commerce that take place inside or with the immediate support of an ordinary motorized passenger car without identifying logos or specific modifications for the sale of food.
Stalls	Those means of sale that are covered with a canvas structure or other material and do not have wheels and/or motors.
Food Truck	Means of commerce that have wheels and are motorized, usually cars modified to sell food. They can have a metal roof and a more elaborate structure.
Stand	Means of commerce that do not have a roof, wheels, or a motor. Simple means of sale, easy to dismantle and transport.
Styrofoam	Those means of commerce that consist of selling the contents in a Styrofoam or polyethylene thermal box. They can be supported on wheels or not.
Other	Those means of sale that do not fit in with any of the above.

Food and Beverages Sold

To characterize the marketing profile of street vendors, three dimensions of food and beverages were assessed: availability, variety, and quality. Availability was recorded for 58 foods and beverages¹¹. The list included: (a) In natura, minimally processed, or processed foods and preparations based on these foods (AIMPP): mineral water, coconut water, natural fruit juice, 100% natural juice, coffee, natural tea, milk shaken with fruit, fresh fruit, dried or dehydrated fruit, plain fruit salad, açaí without sugar or syrup, roasted or boiled corn, culinary preparation cake, fruit or vegetable-based jam, culinary preparation cookie, pão de queijo (Brazilian cheese bread), tapioca without ultra-processed filling, pizza without ultra-processed filling, baked salty snack without ultra-processed filling, fried salty snack without ultra-processed filling, sandwich without ultra-processed filling, hamburger without ultra-processed meat, sweet peanuts, skewers, popcorn made with natural grain and regional preparations; (b) Ultra-processed foods and preparations based on these foods (AUPP): fruit nectar, soft drink, ready-to-drink tea, dairy drink, soy-based drink, regular soda, zero/light/diet soda, energy drink, isotonic, fruit salad with toppings, açaí with sugar or syrup, açaí with toppings, cereal bar, breakfast cereal, ultra-processed cake, candy with ultra-processed ingredient, chocolate/candy, treat, popsicle or ice cream, sweet cookie with or without filling, packet snack/chips/biscuit/salty cracker, frozen or ready mix pão de queijo, tapioca with ultra-processed filling, pizza with ultra-processed filling, baked snack with ultra-processed filling, fried snack with ultra-processed filling, sandwich with ultra-processed filling, hamburger with ultra-processed meat, ultra-processed popcorn, packet sweet popcorn, and churros; and (c) alcoholic beverages.

Variety was classified according to the sum of the options available at the point of sale, considering the different flavors, brands and sizes for each food or beverage.

For quality, the foods and beverages were organized according to the characteristics of industrial processing (NOVA system): AIMPP and AUPP¹². Alcoholic beverages were indicated as “unclassified” and traditional foods, when mentioned, were recorded as “regional preparations” or “other food” with a detailed description¹¹.

Two indicators of relative proportion between food groups were used. The percentage of foods was calculated by dividing the total AIMPP or AUPP available by the total variety of items sold (from both groups) at the point of sale. The result of the division was multiplied by 100. The ratio between AUPP and AIMPP resulted from dividing the total AUPP available by the total AIMPP available. A ratio > 1 indicates the relative advantage of the availability of AUPP compared to that of AIMPP. A ratio < 1 indicates that AUPPs are marketed less than AIMPPs¹².

Data Analysis

The data was processed in Microsoft 365 Excel and analyzed in the Statistical Package for the Social Science (SPSS), version 21.0. Descriptive analyses included measures of central tendency and dispersion, frequencies and 95% confidence intervals. The Kruskal-Wallis test was used to compare the differences between independent groups — Brazilian macro-regions (North, Northeast, Central-West, Southeast, and South) and point of sale sizes (smallest, intermediate, largest) — due to the violation of normality assumptions (p < 0.05 in the Kolmogorov-Smirnov and Shapiro-Wilk tests).

As street vending does not have management indicators (annual turnover, number of customers, stock management), the size stratification was operationalized by generating tertiles of the variety of food and drink available. A 5% significance level was used for all the association analyses.

RESULTS

Informal businesses were mapped around the 2,180 schools included in the larger study, totaling 699 street vendors. No street vendors were found at the time of the visit to the schools in Cuiabá (MT), Fortaleza (CE), Florianópolis (SC), Goiânia (GO), and Vitória (ES).

Most street vendors were male, aged between 45 and 59, black, and had completed high school. Regional differences were revealed: there was a predominance of females in the Northeast (52.6%), a lower age group in the Central-West and Northeast, and only in the South (50.0%) and Southeast (50.3%) was the majority white, but with a high percentage of blacks considering the Brazilian racial structure. Informal trade was the main source of income for these workers (91.4%), with a higher frequency in the Northeast (97.7%). The most frequent time spent working informally was between 2 and 5 years (35.2%) and the lack of opportunities in the formal market (52.5%) was pointed out as the predominant reason for informal food and drink sales in Brazil (Table 1).

Table 1
Sociodemographic characterization of street vendors around private primary and secondary schools in the Comercialização de Alimentos em Escolas Brasileiras (Food Marketing in Brazilian Schools) study, according to Brazilian macro-region. Brazil, 2022–2024.

Variables	Brazil (n = 699)	North Region (n = 98)	Northeast (n = 255)	Central-West Region (n = 75)	Southeast (n = 161)	South region (n = 110)	p value
	% (95%CI)	% (95%CI)	% (95%CI)	% (95%CI)	% (95%CI)	% (95%CI)
Sex
Female	42.2 (38.5–45.9)	44.9 (34.9–54.9)	52.6 (46.4–58.7)	33.3 (22.4–44.3)	32.3 (25.0–39.6)	36.4 (27.2–45.5)	< 0.001a
Male	57.8 (54.1–61.5)	55.1 (45.1–65.1)	45.5 (41.3–53.6)	66.7 (55.8–77.6)	67.7 (60.4–75.0)	63.6 (54.5–72.8)	< 0.001a
Age group
18 to 24 years	8.2 (6.1–10.2)	2.0 (0–4.9)	11.4 (7.5–15.3)	17.3 (8.6–26.1)	4.4 (1.2–7.5)	5.5 (1.1–9.8)	< 0.001a
25 to 34 years	17.6 (14.8–20.4)	14.3 (7.2–21.3)	25.5 (20.1–30.9)	24.0 (14.1–33.9)	7.5 (3.4–11.6)	12.7 (6.4–19.1)	< 0.001a
35 to 44 years	27.6 (24.3–30.9)	32.7 (23.2–42.1)	25.1 (19.7–30.5)	22.7 (13.0–32.4)	30.4 (23.3–37.6)	28.2 (19.6–30.7)	0.459
45 to 59 years	35.2 (31.6–38.7)	39.8 (30.0–49.7)	29.0 (23.4–34.6)	22.7 (13.0–32.4)	42.2 (34.5–50.0)	43.6 (34.2–53.1)	0.002a
≥ 60 years	11.4 (9.1–13.8)	11.2 (4.9–17.6)	9.0 (5.5–12.6)	13.3 (5.5–21.2)	15.5 (9.9–21.2)	10.0 (4.3–15.7)	0.329
Race/color
White	29.3 (25.9–32.7)	4.1 (0.1–8.1)	20.0 (15.1–24.9)	18.7 (9.6–27.7)	50.3 (42.5–58.1)	50.0 (40.5–59.5)	< 0.001a
Black	24.6 (21.4–27.8)	37.8 (28.0–47.5)	24.3 (19.0–29.6)	13.3 (5.5–21.2)	24.2 (17.5–30.9)	21.8 (14.0–29.7)	0.005a
Brown	44.2 (40.5–47.9)	56.1 (46.1–66.1)	54.5 (48.4–60.7)	62.7 (51.5–73.9)	23.6 (17.0–30.2)	27.3 (18.8–35.7)	< 0.001a
Yellow	0.9 (0.1–1.5)	1.0 (0–3.1)	1.2 (0–2.5)	2.7 (0–6.4)	0	0	0.235
Indigenous	0.6 (0–1.1)	1.0 (0–3.1)	0	2.7 (0–6.4)	0	0.9 (0–2.7)	0.068
Black (black and brown)	68.8 (65.4–72.3)	93.9 (89.1–98.7)	78.8 (73.8–83.9)	76.0 (66.1–85.9)	47.8 (40.0–55.6)	49.1 (39.6–59.6)	< 0.001a
Schooling
Incomplete primary education	16.2 (13.4–18.9)	18.4 (10.6–26.2)	14.9 (10.5–19.3)	6.7 (0.9–12.4)	19.9 (13.7–26.1)	18.2 (10.9–25.5)	0.107
Complete elementary school	29.2 (25.8–32.6)	30.6 (21.3–40.0)	24.7 (19.4–30.0)	24.0 (14.1–33.9)	34.1 (26.8–41.6)	34.6 (25.5–43.6)	0.136
Incomplete secondary education	14.3 (11.7–16.9)	16.3 (8.9–23.8)	20.0 (15.1–24.9)	9.3 (2.6–16.1)	10.6 (5.8–15.4)	8.2 (3.0–13.4)	0.008a
Complete high school	35.8 (32.2–39.3)	27.6 (18.6–36.6)	35.7 (29.8–41.6)	52.0 (40.4–63.6)	31.7 (24.4–38.9)	38.2 (29.0–47.4)	0.012a
Higher education	4.6 (3.0–6.1)	7.1 (2.0–12.3)	4.7 (2.1–7.3)	8.0 (1.7–14.3)	3.7 (0.8–6.7)	0.9 (0–2.7)	0.129
Main source of income
Working as a street vendor	91.4 (89.3–93.5)	89.8 (83.7–95.9)	97.7 (95.8–99.5)	90.7 (83.9–97.4)	85.7 (80.3–91.2)	87.3 (81.0–93.6)	< 0.001a
Retirement or pension	3.4 (2.1–4.8)	2.0 (0–4.9)	0.8 (0–1.9)	2.7 (0–6.4)	9.3 (4.8–13.9)	2.7 (0–5.8)	< 0.001a
Other source of incomeb	5.2 (3.5–6.8)	8.2 (2.7–13.7)	1.6 (0–3.1)	6.7 (0.9–12.4)	5.0 (1.6–8.4)	10.0 (4.3–15.7)	0.007
Time as a street vendor
< 2 years	24.5 (21.3–27.7)	26.5 (17.6–35.4)	23.9 (18.7–29.2)	38.7 (27.4–50.0)	11.8 (6.8–16.8)	32.7 (23.8–41.6)	< 0.001a
Between 2 and 5 years	35.2 (31.6–38–7)	35.7 (26.1–45.4)	40.8 (34.7–46.9)	24.0 (14.1–33.9)	31.7 (24.4–38.9)	34.6 (25.5–43.6)	0.075
Between 5 and 10 years	23.3 (20.2–26.5)	31.6 (22.3–41.0)	21.6 (16.5–26.7)	21.3 (11.8–30.6)	22.4 (15.9–28.9)	22.7 (14.8–30.7)	0.344
More than 10 years	17.0 (14.2–19.8)	6.1 (1.3–11.0)	13.7 (9.5–18.0)	16.0 (7.5–24.5)	34.2 (26.8–41.6)	10.0 (4.3–15.7)	< 0.001a
Motivation for informal selling
Likes it and identifies with it	16.5 (13.7–19.2)	9.2 (3.4–15.0)	18.4 (13.6–23.0)	17.3 (8.6–26.1)	14.3 (8.8–19.8)	20.9 (13.2–28.6)	0.155
Lack of qualifications	12.6 (10.1–15.1)	20.4 (12.3–28.5)	10.6 (6.8–14–4)	9.3 (2.6–16.1)	11.8 (6.8–16.8)	13.6 (7.1–20.2)	0.122
Lack of opportunity in the formal market	52.5 (48.8–56.2)	62.2 (52.5–72.0)	53.7 (47.6–59.9)	48.0 (36.4–59.6)	52.8 (45.0–60.1)	43.6 (34.2–53.1)	0.093
Family business	14.2 (11.6–16.8)	4.1 (0.1–8.1)	15.3 (10.9–19.7)	21.3 (11.8–30.8)	14.3 (8.8–19.8)	15.5 (8.6–22.3)	0.019a
Other motivationc	4.3 (2.8–5.8)	4.1 (0.1–8.1)	2.0 (0.3–3.7)	4.0 (0–8.5)	6.8 (2.9–10.8)	6.4 (1.7–11.0)	0.132

• 95%CI: 95% confidence interval.
• ^aKruskal-Wallis test. The significance level is 0.05.
• ^bOther types mentioned: working as a non-street vendor, security guard, janitor, general service assistant, supermarket attendant, teacher, nanny, seamstress, mechanic, construction worker, and artist.
• ^cOther motivations mentioned: supplementing income, flexible working hours, health limitations for other jobs.

Regarding the characteristics of their operations, by macro-region (Table 2), 59.8% of street vendors were located in the school block; carts were the most used structure in all regions, followed by stalls, which predominated in the Northeast (36.5%). Most street vendors worked exclusively around schools, except in the South (20.0%). Most street vendors were informal, with 82.1% not registered with public bodies. Formalization was more frequent in the South (29.1%), and the Southeast had the highest number of MEI/CNPJs (4.4%). Despite this, 89.7% had never been impeded and, when they had, they were conducted by civil agents in the South (16.4%) and by public agents in the Southeast (9.3%), North (4.1%), and Northeast (3.9%). Schools, in turn, did not interfere with the presence of these vendors.

Table 2
Characterization of the activities of street vendors around private primary and secondary schools in the Comercialização de Alimentos em Escolas Brasileiras (Food Marketing in Brazilian Schools) study, by Brazilian macro-region. Brazil, 2022 to 2024.

Variables	Brazil (n = 699)	North Region (n = 98)	Northeast region (n = 255)		Central-West Region (n = 75)	Southeast region (n = 161)	South region (n = 110)	p value
	% (95%CI)	% (95%CI)	% (95%CI)		% (95%CI)	% (95%CI)	% (95%CI)
Location
In front of or at the gate	40.2 (36.6–43.8)	23.5 (14.9–32.0)		25.1 (19.7–30.5)	74.7 (64.6–84.7)	66.5 (59.1–73.8)	28.2 (19.6–36.7)	< 0.001*
Block	59.8 (56.2–63.4)	76.5 (68.0–85.1)		74.9 (69.5–80.3)	25.3 (15.3–35.4)	33.5 (26.2–40.9)	71.8 (63.3–80.4)	< 0.001*
Structure
Cart	40.8 (37.1–44.4)	52.0 (42.0–62.1)		30.2 (24.5–35.9)	34.7 (23.6–45.7)	57.1 (49.4–64.9)	35.5 (26.4–44.5)	< 0.001*
Private car	6.6 (4.7–8.4)	3.1 (0–6.5)		6.3 (3.3–9.3)	9.3 (2.6–16.1)	5.0 (1.6–8.4)	10.9 (5.0–16.8)	0.138
Stall	20.3 (17.3–23.3)	12.2 (5.6–18.9)		36.5 (30.5–42.4)	14.7 (6.5–22.9)	14.9 (9.4–20.5)	1.8 (0–4.4)	< 0.001*
Food truck	3.6 (2.2–5.0)	3.1 (0–6.5)		1.6 (0–3.1)	13.3 (5.5–21.2)	2.5 (0.1–4.9)	3.6 (0.1–7.2)	< 0.001*
Bench or table	8.4 (6.4–10.5)	19.4 (11.4–27.4)		6.3 (3.3–9.3)	13.3 (5.5–21.2)	7.5 (3.4–11.6)	1.8 (0–4.4)	< 0.001*
Styrofoam or thermal box	15.9 (13.2–18.6)	9.2 (3.4–15.0)		18.0 (13.3–22.8)	9.3 (2.6–16.1)	11.2 (6.3–16.1)	28.2 (19.6–36.7)	< 0.001*
Other type**	4.4 (2.9–6.0)	1.0 (0–3.1)		1.2 (0–2.5)	5.3 (0.1–10.5)	1.9 (0–4.0)	18.2 (10.9–25.5)	< 0.001*
Food sold elsewhere
Yes	35.3 (31.8–38.9)	51.0 (41.0–61.1)		6.3 (3.3–9.3)	33.3 (22.4–44.3)	42.2 (34.5–50.0)	80.0 (72.4–87.6)	< 0.001*
No	64.7 (61.1–68.2)	49.0 (38.9–59.1)		93.7 (90.7–96.7)	66.7 (55.8–77.6)	57.8 (50.1–65.5)	20.0 (12.4–27.6)	< 0.001*
Work shift
Morning	86.7 (84.2–89.2)	74.5 (65.7–83.3)		92.9 (89.8–96.1)	86.7 (78.8–94.5)	93.8 (90.0–97.6)	72.7 (64.3–81.2)	< 0.001*
Late	94.7 (93.0–96.4)	86.7 (77.4–92.0)		96.1 (93.7–98.5)	92.0 (85.7–98.3)	98.1 (96.0–100)	92.3 (94.2–100)	< 0.001*
Night	29.0 (25.7–32.4)	28.6 (19.5–37.7)		25.1 (19.7–30.5)	10.7 (3.5–17.8)	38.5 (30.9–46.1)	37.3 (28.1–46.5)	< 0.001*
Working days
Monday	91.0 (88.9–93.1)	91.8 (86.3–97.4)		97.7 (95.8–99.5)	92.0 (85.7–98.3)	89.4 (84.6–94.2)	76.4 (68.3–84.4)	< 0.001*
Tuesday	93.4 (91.6–92.3)	98.0 (95.1–100)		98.8 (97.5–100)	97.3 (93.6–100)	92.6 (88.5–96.7)	75.5 (67.3–83.6)	< 0.001*
Wednesday	92.6 (90.6–94.5)	98.0 (95.1–100)		98.0 (96.3–99.8)	96.0 (91.5–100)	90.7 (86.2–95.2)	75.5 (67.3–83.6)	< 0.001*
Thursday	93.6 (91.7–95.4)	98.0 (95.1–100)		98.8 (97.5–100)	96.0 (91.5–100)	92.6 (88.5–96.7)	77.3 (69.3–85.2)	< 0.001*
Friday	92.6 (90.6–94.5)	93.9 (89.1–98.7)		98.8 (97.5–100)	94.7 (89.5–99.9)	92.6 (88.5–96.7)	75.5 (67.3–83.6)	< 0.001*
Saturday	33.2 (29.7–36.7)	20.4 (12.3–28.5)		33.7 (27.9–39.6)	17.3 (8.6–26.1)	41.0 (33.3–48.7)	42.7 (33.3–52.1)	< 0.001*
Registration with public authorities
No registration	82.1 (79.3–85.0)	72.5 (63.5–81.5)		89.4 (85.6–93.2)	88.0 (80.5–95.5)	82.0 (76.0–88.0)	70.0 (61.3–78.7)	< 0.001*
Has a permit, license, or other registration	16.6 (13.8–19.4)	27.6 (18.6–36.6)		10.2 (6.5–13.9)	12.0 (4.5–19.5)	13.7 (8.3–19.0)	29.1 (20.5–37.7)	< 0.001*
MEI/CNPJ registration	1.3 (0.5–2.1)	0		0.4 (0–1.2)	0	4.4 (1.2–7.5)	0.9 (0–2.7)	0.003*
Impediment
No impediment	89.7 (87.4–92.0)	89.8 (83.7–95.9)		93.3 (90.3–96.4)	93.3 (87.6–99.1)	88.2 (83.2–93.2)	80.9 (73.5–88.4)	0.006*
Prevented by a public officiala	4.7 (3.1–6.3)	4.1 (0.1–8.1)		3.9 (1.5–6.3)	1.3 (0–4.0)	9.3 (4.8–13.6)	2.7 (0–5.8)	0.028*
Prevented by civilian agentb	5.6 (3.9–7.3)	6.1 (1.3–11.0)		2.8 (0.7–4.8)	5.3 (0.1–10.5)	2.5 (0.1–4.9)	16.4 (9.3–23.4)	< 0.001*
Interference from school
Yesc	0.9 (0.2–1.5)	2.0 (0–4.9)		0	1.3 (0–4.0)	0.6 (0–1.9)	1.8 (0–4.4)	0.257
No	99.1 (98.5–99.8)	98.0 (95.1–100)		100	98.7 (96.0–100)	99.4 (98.2–100)	98.2 (95.7–100)	0.257

• 95%CI: 95% confidence interval.
• *Kruskal-Wallis test. The significance level is 0.05.
• **Other types mentioned: wheelbarrow, bicycle, oven, barbecue grill, box, basket, hanger, and tray.
• ^aPublic authorities mentioned: town hall inspectors and police.
• ^bCivil agents mentioned: formal traders, other street vendors, school management, parents, residents. The variable “place of production of culinary preparations” was not described because there were only 6 responses (3 “at the street vendor’s house”; 1 “by suppliers”; 2 “at the place of sale”).
• ^cThe following were mentioned as items suggested by the school for sale by the street vendor: “baked snacks” 2 times; “salty and sweet popcorn” 3 times; “sweets and candies “ 1 time; “natural fruit or pulp juice” 1 time; “homemade cake” 1 time; “soft drinks and industrialized juices” 1 time; and as items prohibited by the school for sale by the street vendor: “alcoholic drink” 3 times; “cigarette” 3 times; “sweets and candies” 2 times; “ice cream” 1 time; “water” 2 times; “soda and industrialized juices” 3 times; “energy drink or isotonic” 2 times.

Table 3 shows the frequency of foods and drinks audited by macro-region. The most common AIMPP in Brazil were: mineral water (55.2%), coffee (12.2%), baked cake (11.6%), ultra-processed fried snacks without filling (10.6%), and popcorn with natural kernels (10.2%). Mineral water was the majority in all regions, followed by baked goods in the North (29.6%), coffee in the Northeast (18.4%), fresh fruit in the Central-West (12.0%), and popcorn in the Southeast (19.9%) and South (8.2%). Traditional foods, representative of regional culture, were rarely found in Brazilian street vending.

Table 3
Frequency of food and beverages sold by street vendors around private primary and secondary schools in the Comercialização de Alimentos em Escolas Brasileiras (Food Marketing in Brazilian Schools) study, by Brazilian macro-region. Brazil, 2022 to 2024.

Variablesb	Brazil (n = 699)	Northern region (n = 98)	Northeast region (n = 255)	Central-West Region (n = 75)	Southeast region (n = 161)	South region (n = 110)	p value
	% (95%CI)	% (95%CI)	% (95%CI)	% (95%CI)	% (95%CI)	% (95%CI)
	In natura, minimally processed, or processed foods and culinary preparations based on these foods (AIMPP)
Mineral water	55.2 (51.5–58.9)	59.2 (49.3–69.1)	86.3 (82.0–90.5)	40.0 (28.7–51.4)	31.1 (23.8–38.3)	25.5 (17.2–33.7)	< 0.001a
Coffee	12.2 (9.7–14.6)	17.4 (9.7–25.0)	18.4 (13.6–23.2)	5.3 (0.1–10.6)	10.6 (5.8–15.4)	0	< 0.001a
Culinary prearation cake	11.6 (9.2–14.0)	29.6 (20.4–38.8)	16.9 (12.2–21.5)	5.3 (0.1–10.5)	1.9 (0–4.0)	1.8 (0–4.4)	< 0.001a
Natural fruit juice	11.3 (9.0–13.7)	21.4 (13.2–29.7)	16.9 (12.2–21.5)	6.7 (0.9–12.4)	4.4 (1.2–7.5)	2.7 (0–5.8)	< 0.001a
Ultra-processed fried snacks without filling	10.6 (8.3–12.9)	20.4 (12.3–17.1)	16.1 (11.5–20.6)	6.7 (0.9–12.4)	4.4 (1.2–7.5)	0.9 (0–2.7)	< 0.001a
Popcorn with natural kernels	10.2 (7.9–12.4)	17.4 (9.7–25.0)	2.0 (0.3–3.7)	10.7 (3.5–17.8)	19.9 (13.7–26.1)	8.2 (3.0–13.4)	< 0.001a
Ultra-processed baked snack without filling	8.9 (6.8–11.0)	19.4 (11.4–27.4)	13.3 (9.1–17.5)	4.0 (0–8.5)	3.7 (0.8–6.7)	0	< 0.001a
Coconut water	8.6 (6.5–10.7)	9.2 (3.4–15.0)	12.6 (8.5–16.6)	2.7 (0–6.4)	6.8 (2.9–10.8)	5.5 (1.1–9.8)	0.033a
Sweet peanut	7.2 (5.2–9.1)	10.2 (4.1–16.3)	6.7 (3.6–9.8)	9.3 (2.6–16.7)	8.1 (3.8–12.3)	2.7 (0–5.8)	0.245
Churros	6.3 (4.5–8.1)	11.2 (4.9–17.6)	2.4 (0.5–4.2)	10.7 (3.5–17.8)	9.3 (4.8–13.9)	3.6 (0.1–7.2)	0.002a
Fruit or vegetable jam	5.0 (3.4–6.6)	1.0 (0–3.1)	5.5 (2.7–8.3)	5.3 (0.1–10.5)	9.3 (4.8–13.9)	0.9 (0–2.7)	0.009a
100% natural juice in carton, can, or bottle	5.0 (3.4–6.6)	6.1 (1.3–11.0)	7.1 (3.9–10.2)	4.0 (0–8.5)	5.0 (1.6–8.4)	0	0.076
Ultra-processed meatless burger	4.6 (3.0–6.1)	9.2 (3.4–15.0)	7.8 (4.5–11.2)	1.3 (0–4.0)	1.2 (0–3.0)	0	< 0.001a
Skewers	4.2 (2.7–5.6)	6.1 (1.3–11.0)	1.6 (0–3.1)	2.7 (0–6.4)	9.3 (4.8–13.9)	1.8 (0–4.4)	0.001a
Culinary preparation cookie	3.7 (2.3–5.1)	1.0 (0–3.1)	8.2 (4.8–11.6)	2.7 (0–6.4)	1.2 (0–3.0)	0	< 0.001a
Fresh fruit	3.6 (2.2–5.0)	2.0 (0–4.9)	1.2 (0–2.5)	12.0 (4.5–19.5)	2.5 (0.1–4.9)	6.4 (1.7–11.0)	< 0.001a
Roasted/cooked corn	3.3 (2.0–4.6)	2.0 (0–4.9)	2.4 (0.5–4.2)	0	6.8 (2.9–10.8)	3.6 (0.1–7.2)	0.039a
Plain fruit salad	2.4 (1.3–3.6)	11.2 (4.9–17.6)	1.6 (0–3.1)	0	0.6 (0–1.9)	0.9 (0–2.7)	< 0.001a
Ultra-processed foods and culinary preparations based on these foods (AUPP)							p value
Regular soft drink	46.2 (42.5–49.9)	65.3 (55.7–74.9)	72.9 (67.5–78.4)	26.7 (16.4–36.9)	30.4 (23.3–37.6)	3.6 (0.1–7.2)	< 0.001a
Sweets	29.6 (26.2–33.0)	23.5 (14.9–32.0)	45.9 (39.7–52.0)	24.0 (14.1–33.9)	23.6 (17.0–30.2)	10.0 (4.3–15.7)	< 0.001a
Packet snacks	21.5 (18.4–24.5)	27.6 (18.6–36.6)	36.1 (30.1–42.0)	4.0 (0–8.5)	17.4 (11.5–23.3)	0	< 0.001a
Packet popcorn	19.0 (16.1–21.9)	19.4 (11.4–27.4)	35.7 (29.8–41.6)	6.7 (0.9–12.4)	6.8 (2.9–10.8)	6.4 (1.7–11.0)	< 0.001a
Chocolate/candy	17.2 (14.4–20.0)	13.3 (6.4–20.1)	28.2 (22.7–33.8)	8.0 (1.7–14.3)	16.2 (10.4–21.9)	2.7 (0–5.8)	< 0.001a
Popsicle or ice cream	16.6 (13.8–19.4)	33.7 (24.2–43.2)	21.6 (16.5–26.7)	17.3 (8.6–26.1)	5.6 (2.0–9.2)	5.5 (1.1–9.8)	< 0.001a
Baked snack with ultra-processed filling	10.4 (8.2–12.7)	33.7 (24.2–43.2)	10.2 (6.5–13.9)	9.3 (2.6–16.7)	4.4 (1.2–7.5)	0	< 0.001a
Ultra-processed sweet cookie	8.7 (6.6–10.8)	11.2 (4.9–17.6)	12.6 (8.5–16.6)	0	11.2 (6.3–16.1)	0	< 0.001a
Deep-fried snack with ultra-processed filling	7.7 (5.7–9.7)	23.5 (14.9–32.0)	9.0 (5.5–12.6)	5.3 (0.1–10.5)	2.5 (0.1–4.9)	0	< 0.001a
Soft drinks	6.7 (4.9–8.6)	18.4 (10.6–26.2)	3.5 (1.3–5.8)	1.3 (0–4.0)	9.9 (5.3–14.6)	2.7 (0–5.8)	< 0.001a
Sandwich with ultra-processed filling	6.6 (4.7–8.4)	24.5 (15.8–33.2)	6.3 (3.3–9.3)	1.3 (0–4.0)	0	4.6 (0.6–8.5)	< 0.001a
Zero soda	5.6 (3.9–7.3)	4.1 (0.1–8.1)	5.5 (2.7–8.3)	4.0 (0–8.5)	9.9 (5.3–14.6)	1.8 (0–4.4)	0.049a
Cereal bar	4.2 (2.7–5.6)	10.2 (4.1–16.3)	2.0 (0.3–3.7)	0	8.7 (4.3–13.1)	0	< 0.001a
Fruit nectar in a carton, can, or bottle	4.0 (2.6–5.5)	6.1 (1.3–11.0)	3.9 (1.5–6.3)	4.0 (0–8.5)	4.4 (1.2–7.5)	1.8 (0–4.4)	0.634
Açaí with toppings	3.7 (2.3–5.1)	8.2 (2.7–13.7)	2.0 (0.3–3.7)	13.3 (5.5–21.2)	1.9 (0–4.0)	0	< 0.001a
Sweets with ultra-processed ingredients	3.2 (1.9–4.4)	1.0 (0–3.1)	3.1 (1.0–5.3)	2.7 (0–6.4)	4.4 (1.2–7.5)	3.6 (0.1–7.2)	0.671
Energy drink	2.7 (1.5–3.9)	1.0 (0–3.1)	4.3 (1.8–6.8)	2.7 (0–6.4)	3.1 (0.4–5.8)	0	0.154
Pizza with ultra-processed filling	2.0 (1.0–3.0)	8.2 (2.7–13.7)	1.2 (0–2.5)	4.0 (0–8.5)	0	0	< 0.001a
Alcoholic drink							p value
Alcoholic drink	3.6 (2.2–5.0)	1.0 (0–3.1)	7.5 (4.2–10.7)	0	3.1 (0.4–5.8)	0	< 0.001a

• 95%CI: 95% confidence interval.
• ^aKruskal-Wallis test. The significance level is 0.05.
• ^bFoods that did not reach 1.0% of the minimum limit of the 95%CI for Brazil have been hidden from the table.

The most frequent AUPPs were: regular soft drinks (46.2%), sweets (29.6%), packet snacks (21.5%), industrialized popcorn (19.0%), and chocolate/candy (17.2%). Soft drinks were predominant in four regions, except in the South (3.6%), where sweets stood out (10.0%). The Northeast had the highest frequency of street vendors selling alcoholic beverages around schools (7.5%) (Table 3).

Table 4 shows the average frequency of food sold according to the size of the street vendor. There was a predominance of AIMPP at smaller points of sale (selling one to three items) and of AUPP at larger street vendors (selling 14 or more items), except in the Northeast, where AUPP predominated at intermediate sizes (selling four to 13 items). In the South, there was no significant difference between AIMPP and AUPP by size. Analysis of the AUPP/AIMPP ratio revealed that AUPP quantitatively outnumbered AIMPP in intermediate and larger sales points, except for intermediate street vendors in the Southeast (0.64; 95%CI 0.27–1.01; p < 0.001) and South (0.45; 95%CI 0.07–0.84; p = 0.001). On average, intermediate-sized street vendors sold twice as many AUPPs (2.07; 95%CI 1.72–2.41; p < 0.001) as AIMPPs, while the ratio doubled among larger vendors (4.09; 95%CI 3.46–4.72; p < 0.001).

Table 4
Indicators of food and beverages sold by street vendors around private primary and secondary schools in the Comercialização de Alimentos em Escolas Brasileiras (Food Marketing in Brazilian Schools) study, according to the size of the street vendor and the Brazilian macro-region. Brazil, 2022 to 2024.

	Smaller (n = 204)		Intermediate size (n = 254)		Largest (n = 241)		p value
	Mean (95%CI)	Median (Interquartile range)	Mean (95%CI)	Median (interquartile range)	Mean (95%CI)	Median (interquartile range)
Percentage (%) of AIMPP marketed
Brazil (n = 699)	82.7 (77.6–87.7)	100 (0)	43.1 (38.6–47.5)	33.3 (53)	28.6 (26.1–31.2)	25.0 (26)	< 0.001a
Northern region (n = 98)	93.3 (74.9–100)	100 (17)	44.5 (32.6–56.4)	29.1 (73)	31.9 (25.9–37.8)	31.3 (37)	0.003a
Northeast region (n = 255)	78.1 (64.4–91.9)	100 (46)	28.4 (24.2–32.5)	25.0 (24)	29.8 (26.4–33.2)	25.9 (26)	< 0.001a
Central-West region (n = 75)	89.6 (77.2–100)	100 (0)	52.7 (36.1–69.3)	50.0 (92)	26.9 (16.5–37.2)	20.1 (41)	< 0.001a
@@Southeast region (n = 161)	93.6 (87.9–99.3)	100 (0)	55.9 (45.0–66.7)	55.6 (84)	21.5 (17.0–26.0)	22.0 (18)	< 0.001a
Southern region (n = 110)	71.2 (60.8–81.7)	100 (100)	58.0 (42.6–73.3)	66.7 (100)	28.6 (0–100)	7.2 (79)	0.085
Percentage (%) of AUPP marketed
Brazil (n = 699)	17.3 (12.3–33.4)	0 (0)	56.8 (52.4–61.2)	66.7 (53)	69.7 (67.2–72.3)	73.3 (29)	< 0.001a
Northern region (n = 98)	6.7 (0–25.2)	0 (17)	55.5 (43.6–67.4)	71.0 (73)	68.0 (62.0–73.9)	68.8 (37)	0.003a
Northeast region (n = 255)	21.9 (8.1–35.7)	0 (46)	71.3 (67.1–75.5)	75.0 (25)	67.3 (63.9–70.7)	69.4 (28)	< 0.001a
Central-West region (n = 75)	10.4 (0–22.8)	0 (0)	47.3 (30.7–63.9)	50.0 (92)	73.2 (62.8–83.5)	79.9 (41)	< 0.001a
Southeast region (n = 161)	6.4 (0.7–12.1)	0 (0)	44.2 (33.3–55.0)	44.4 (84)	77.7 (73.2–82.2)	78.1 (16)	< 0.001a
Southern region (n = 110)	28.8 (18.3–39.2)	0 (100)	42.1 (26.6–57.5)	33.3 (100)	71.4 (0–100)	92.9 (79)	0.085
AUPP/AIMPP ratio
Brazil (n = 699)	0.04 (0.01–0.07)	0 (0)	2.07 (1.72–2.41)	1.00 (3)	4.09 (3.46–4.72)	2.60 (4)	< 0.001a
Northern region (n = 98)	0.10 (0–0.38)	0 (0)	2.44 (1.42–3.45)	0.90 (4)	1.94 (1.41–2.47)	1.60 (3)	0.028a
Northeast region (n = 255)	0.14 (0–0.29)	0 (0)	3.43 (2.84–4.02)	2.70 (4)	4.06 (3.34–4.77)	2.60 (4)	< 0.001a
Central-West region (n = 75)	0.04 (0–0.13)	0 (0)	1.19 (0.19–2.20)	0 (1)	5.24 (2.91–7.56)	3.25 (9)	< 0.001a
Southeast region (n = 161)	0.01 (0–0.04)	0 (0)	0.64 (0.27–1.01)	0 (1)	6.72 (4.03–9.42)	3.40 (6)	< 0.001a
Southern region (n = 110)	0.03 (0–0.07)	0 (0)	0.45 (0.07–0.84)	0 (1)	1.50 (0–6.27)	0 (5)	0.001a

• AUPP: ultra-processed foods and culinary preparations based on these foods; AIMPP: in natura, minimally processed, or processed foods and culinary preparations based on these foods; 95%CI: 95% confidence interval.
• Note: the size tertiles were determined according to the variety of food and beverages available in the street vending trade, as follows: 1st tercile: smallest size of 1 to 3 items; 2nd tercile: intermediate size of 4 to 13 items and; 3rd tercile: largest size of 14 or more items.
• ^aKruskal-Wallis test. The significance level is 0.05.

DISCUSSION

This study, a pioneer in describing the informal food trade, based on an audit around a representative sample of Brazilian private schools, revealed a profile of middle-aged black men with low levels of education. The simultaneous marketing of AIMPP and AUPP was also observed, with regional and size variations, in which AUPP tends to stand out in the larger sizes.

The profile differs from that of women traditionally associated with street food sales, although it remains predominantly black¹³. The significant proportion of black street vendors reflects the racial division of labor as one of the manifestations of the structural racism that limits the access, progress, and maintenance of black people in the formal market¹⁶. This phenomenon is particularly evident in the South and Southeast, where the proportion of black street vendors significantly exceeds their representation in the ethnic-racial profile of the population (27.4% and 49.3%, respectively)¹⁷.

The most cited periods of entry into informality coincided with milestones in the country’s economic and social crisis — the recession that began in 2017 and the Covid-19 pandemic (2020–2022) — marked by record layoffs and the withdrawal of labor and social security rights¹⁸,¹⁹. These findings are in line with the theory of subsistence entrepreneurship²⁰, which characterizes informality as a compulsory option in the face of a shortage of opportunities in the formal market or the failure to meet basic survival needs. Studies corroborate that informal commerce is the main source of income for street vendors, promoting economic empowerment and poverty reduction in marginalized populations due to the low requirement for qualifications and start-up capital²¹.

However, Brazilian academic production on street food often neglects discussions on race/skin color and socioeconomic motivations, limiting itself to the sanitary approach²². Even when describing workers, studies tend to restrict themselves to the variables of gender and schooling — the latter often associated with a supposed lack of qualification for good food handling practices, without contextualizing structural inequalities in access to education or considering other knowledge and social determinants²²,²³. The predominant approach limits the possibility of integrated interventions, restricting them to the health field, and compromises the advancement of knowledge necessary for urban management and the formulation of inclusive public policies⁹,¹⁰.

As for location, the proximity of street vendors to school gates reinforces their relevance to studies on the school food environment¹. International research indicates that adolescents choose food for the convenience of minimal travel and low prices²⁴ and that public policies in some countries limit the activities of street vendors in the vicinity of schools²¹. In Brazil, the lack of explicit mention of informal vending in the regulatory frameworks for the school environment represents a regulatory gap²⁵.

Although the predominant structures (carts and stalls) allow for mobility, a consistent pattern of daily location was observed. The literature recognizes a broad typology of structures in terms of mobility, legality and appropriation of urban resources and spaces¹⁴, as demonstrated by Ambikapathi et al.¹³ in Tanzania, when differentiating between semi-formal vendors (who maintained their location) and informal vendors (on foot, by bicycle or cart). In Brazil, like other sectors of informal commerce²⁶, street food vendors are predominantly semi-formal in terms of their mobility, on the fringes of legality.

The higher proportion of formalized street vendors in the South and Southeast may indicate an appropriation of the neoliberal discourse of entrepreneurship and individual effort, which, in practice, intensifies the job insecurity of this vulnerable group⁸,¹⁶. This is a phenomenon that requires monitoring in future studies on food marketing, with a view to analyzing the repercussions on the Brazilian labor market.

Our results differ from scientific studies which associate the lack of licensing with episodes of state repression¹⁴. In Ghana, 63.9% of the street vendors studied did not even apply for a work permit for fear of reprisals such as threats of eviction and legal action¹⁵. In the Brazilian context, it is suggested that the greater cultural acceptance of street food may explain the less conflictual scenario found. Even so, even with formal authorizations, there is ongoing political negotiation to avoid abrupt removals in the urban setting²⁶. Although zoning measures in areas with a shortage of formal commerce are proposed²⁰, spatial reordering policies can result in the sanitization of public spaces and the marginalization of street vendors at the behest of civil agents who hold social and economic power¹⁴, especially when considering their sociodemographic profile. This study provides the first systematic characterization of this previously invisible population.

There was an increase in the sales of AUPP as the size of the street vendors grew, with regional variations. This finding can be explained, in part, by the low operational complexity and reduced working capital required for this trade, which tends to favor the prioritization of these products. But also, because of the methodology used to classify size, since the greater diversity of foods sold is related to the AUPP offer.

The adoption of the NOVA system in this study was based on its indication as a viable standardization in the face of the greatest divergence in studies that analyze the informal food environment: the concept of healthiness⁵. According to the evaluation of food consumption in Brazil (2008–2018), although consumption of ultra-processed foods has increased, there has been a reduction among the population with a higher income²⁷. This may explain, at least in part, the lower supply of AUPP among street vendors in the South, where the capitals with the highest per capita income in the country are located (Florianópolis and Porto Alegre)²⁸.

Street vending around private schools showed coexistence between AIMPP and AUPP, a pattern also observed in public schools⁴. In these schools, couscous, tapioca, natural sandwiches, root vegetable-based snacks, and soft drinks were identified, even when the street vendors were classified as healthy⁴. In the present study, although the offer of AUPP predominated, traditional foods were recorded in the Northeast (abará, acarajé, arroz doce, biscoitinho de goma, bolinho de estudante, canjica, couscous, and mungunzá) and North (vatapá, tacacá, and cascalho amazonense). These findings corroborate Baker et al.²⁹ on the potential of street vendors to preserve food culture in lower-income countries. On the other hand, the global spread of AUPP plays a commercial and value transition role as an appropriation strategy for replacing traditional foods with snacks in the Brazilian diet²⁷. Public policies are needed that consider the impact of AUPPs on both public health and the dissolution of food traditions.

Street vending has a dual influence by preserving culture and spreading AUPPs, but the coexistence of healthy and unhealthy options has not been enough to offset the competitive impact of AUPPs³,⁷. International⁶ and national⁴ studies have shown that proximity to street vendors increases adolescents’ exposure to unhealthy products, including alcoholic beverages — illegal for minors, but sold in school surroundings in the Northeast, North, and Southeast regions. There is a need to regulate the informal trade around schools, considering its dual relevance as a source of income and a low-cost food alternative for vulnerable populations, especially in the North and Northeast, and restrictive measures that aggravate the food insecurity of street vendors, their families and customers are contraindicated²¹.

The analysis revealed that intermediate-sized street vendors in the Northeast and larger ones in all the macro-regions are diffusers of AUPP in the school environment. Although they typically start out small due to the lack of investment capital and social protection²⁰, the low investment requirement for AUPP favors commercial expansion — especially in the Northeast. However, in the Southeast and South, as in the USA³⁰, street vendors with more schooling and alternative income adopt healthier practices. Therefore, street vendors of all sizes should be included in actions to reduce students’ exposure to unhealthy foods.

This study has an inherent limitation of information bias, mitigated by standardized training for the national territory, local and regional supervision of fieldwork. Another limitation is the link between the collection of street vendors and the collection of canteens, which were carried out according to the availability of the canteen owners, which may have underestimated the population of street vendors given the itinerant nature of informal commercial activity. However, this is the first nationwide study of informal commerce and provides an important snapshot of this reality. Despite the focus on the school environment, the results may represent the Brazilian informal trade, given the expected low variation of informal food marketing activity in other urban spaces. In the dynamic context of the informal food environment, the collection of primary data from street vendors, who are absent from records and registers, consolidates the relevance of the study.

Furthermore, the use of the variety of food sold to define the size of the points of sale can be considered a methodological innovation, especially in informal settings, where management information is scarce or non-existent. However, this methodology has limitations when it comes to interpreting our findings, since the greater diversity of foods sold is strongly associated with the offer of AUPPs, since they have a greater variety of presentations, flavors and brands, broadening the assortment available. This limitation should be considered in future studies using this methodology. Finally, this study makes an unprecedented contribution to the characterization of the informal food trade in Brazil, highlighting structural inequalities, with historical roots in the ethnic-racial and regional dimensions, and the dominance of AUPP in the school environment. The results reinforce the need to include informal trade as an inseparable component in the evaluation of the school food environment, given its socioeconomic and cultural relevance.

Future research should deepen our understanding of the profile and dynamics of informal workers, recognizing their potential as agents for transforming food systems. From a political point of view, it is essential that governments incorporate the informal food environment into food and nutrition security strategies in low- and middle-income countries. Public policies must integrate street vendors, reconciling income generation and the promotion of healthy eating, empowering them to promote cultural preservation and access to healthy food in the reality of urban public space.

REFERENCES

• ¹ Food and Agriculture Organization. School food and nutrition framework. Rome: FAO; 2019 [cited 2025 Jul 16]. Available from: https://openknowledge.fao.org/items/679d1e4a-a5e0-4eba-9758-e76dd7cf376b
  » https://openknowledge.fao.org/items/679d1e4a-a5e0-4eba-9758-e76dd7cf376b
• ² 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):532. https://doi.org/10.3390/foods9040532
  » https://doi.org/10.3390/foods9040532
• ³ 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):1363-1374. https://doi.org/10.1017/S1368980013001158
  » https://doi.org/10.1017/S1368980013001158
• ⁴ França FCO, Zandonadi RP, Santana IAS, Silva ICR, Akutsu RCCA. Food and Consumers' Environment Inside and around Federal Public Schools in Bahia, Brazil. Nutrients. 2024;16(2):1-15. https://doi.org/10.3390/nu16020201
  » https://doi.org/10.3390/nu16020201
• ⁵ Medina C, Piña-Pozas M, Aburto TC, Chavira J, López U, Moreno M, 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. 2022;19(89):1-14. https://doi.org/10.1186/s12966-022-01320-1
  » https://doi.org/10.1186/s12966-022-01320-1
• ⁶ Barrera LH, Rothenberg SJ, Barquera S, Cifuentes E. The toxic food environment around elementary schools and childhood obesity in Mexican cities. Am J Prev Med. 2016;51(2):264-270. https://doi.org/10.1016/j.amepre.2016.02.021
  » https://doi.org/10.1016/j.amepre.2016.02.021
• ⁷ Henriques P, Alvarenga CRT, Ferreira DM, Dias PC, Soares DSB, Barbosa RMS, et al. Food environment surrounding public and private schools: An opportunity or challenge for healthy eating? Cien Saude Colet. 2021;26(8):3135-3145. https://doi.org/10.1590/1413-81232021268.04672020
  » https://doi.org/10.1590/1413-81232021268.04672020
• ⁸ Secco AC, Kovaleski DF. Do empreendedor de si mesmo à medicalização da performance: reflexões sobre a flexibilização no mundo do trabalho. Cien Saude Colet. 2022;27(5):1911-1918. https://doi.org/10.1590/1413-81232022275.09572021
  » https://doi.org/10.1590/1413-81232022275.09572021
• ⁹ Bellia C, Bacarella S, Ingrassia M. Interactions between street food and food safety topics in the scientific literature: a bibliometric analysis with science mapping. Foods. 2022;11(6):789. https://doi.org/10.3390/foods11060789
  » https://doi.org/10.3390/foods11060789
• ¹⁰ Contreras CPA, Cardoso RCV, Silva LNN, Cuello REG. Street food, food safety, and regulation: What is the Panorama in Colombia?: A review. J Food Prot. 2020;83(8):1345-1358. https://doi.org/10.4315/JFP-19-526
  » https://doi.org/10.4315/JFP-19-526
• ¹¹ Canuto R, Clark SGF, Borges LD, Castro Junior PCP, Tavares LF, Cardoso LO, et al. Aspectos metodológicos do estudo Comercialização de Alimentos em Escolas Brasileiras. Cad Saude Publica. 2025;41(5):e00167624. https://doi.org/10.1590/0102-311XPT167624
  » https://doi.org/10.1590/0102-311XPT167624
• ¹² Tavares LF, Perez PMP, Passos MEA, Castro Junior PCP, Franco AS, Cardoso LO, Castro IRR. Development and application of healthiness indicators for commercial establishments that sell foods for immediate consumption. Foods. 2021;10(6):1434. https://doi.org/10.3390/foods10061434
  » https://doi.org/10.3390/foods10061434
• ¹³ Ambikapathi R, Shively G, Leyna G, Mosha D, Mangara A, Patl CL, et al. Informal food environment is associated with household vegetable purchase patterns and dietary intake in the DECIDE study: Empirical evidence from food vendor mapping in peri-urban Dar es Salaam, Tanzania. Glob Food Sec. 2021;28:100474. https://doi.org/10.1016/j.gfs.2020.100474
  » https://doi.org/10.1016/j.gfs.2020.100474
• ¹⁴ Peimani N, Kamalipour H. Informal street vending: a systematic review. Land (Basel). 2022;11(6):829. https://doi.org/10.3390/land11060829
  » https://doi.org/10.3390/land11060829
• ¹⁵ Anaafo D, Nutsugbodo RY, Agyepong E, Anane GK, Mensah BA, Bata PD. Place making decisions among informal street food vendors in Sunyani, Ghana. Cities. 2024;154:105328. https://doi.org/10.1016/j.cities.2024.105328
  » https://doi.org/10.1016/j.cities.2024.105328
• ¹⁶ Alves LD. A divisão racial do trabalho como um ordenamento do racismo estrutural. Rev Katálysis. 2022;25(2):212-21. https://doi.org/10.1590/1982-0259.2022.e84641
  » https://doi.org/10.1590/1982-0259.2022.e84641
• ¹⁷ Instituto Brasileiro de Geografia e Estatística. Censo demográfico 2022: características da população e dos domicílios. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2025 [cited 2025 Jul 16]. Available from: https://biblioteca.ibge.gov.br/visualizacao/livros/liv102192.pdf
  » https://biblioteca.ibge.gov.br/visualizacao/livros/liv102192.pdf
• ¹⁸ Instituto Brasileiro de Geografia e Estatística. Síntese de indicadores sociais: uma análise das condições de vida da população brasileira. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística; 2022 [cited 2025 Jul 16]. Available from: https://biblioteca.ibge.gov.br/visualizacao/livros/liv101979.pdf
  » https://biblioteca.ibge.gov.br/visualizacao/livros/liv101979.pdf
• ¹⁹ Santos KOB, Fernandes RCP, Almeida MMC, Miranda SS, Mise YF, Lima MAG. Labor, health and vulnerability in the COVID-19 pandemic. Cad Saude Publica. 2021;36(12):e00178320. https://doi.org/10.1590/0102-311X00178320
  » https://doi.org/10.1590/0102-311X00178320
• ²⁰ Engidaw AE, Ning J, Kebad MA, Mulaw SG, MandefroTA, WondaTA, et al. Determining the push factors to involve in street vending activities and their challenges: in the case of Ethiopia. J Innov Entrep. 2024;13(42):1-21. https://doi.org/10.1186/s13731-024-00397-1
  » https://doi.org/10.1186/s13731-024-00397-1
• ²¹ Chavez JBR, 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):1-17. https://doi.org/10.3390/ijerph18083953
  » https://doi.org/10.3390/ijerph18083953
• ²² Cintra P, Góis EM, Brunharo MSM, Moreira DOS. Boas práticas de manipulação no comércio ambulante de alimentos em campus universitário da Grande Dourados, MS. Higi Aliment. 2017;31(266/267):27-30.
• ²³ Cortese RDM, Veiros MB, Feldman C, Cavalli SB. Food safety and hygiene practices of vendors during the chain of street food production in Florianopolis, Brazil: a cross-sectional study. Food Control. 2016;62:178-186. https://doi.org/10.1016/j.foodcont.2015.10.027
  » https://doi.org/10.1016/j.foodcont.2015.10.027
• ²⁴ Kelly C, Callaghan M, Gabhainn SN. 'It's hard to make good choices and it costs more': adolescents' perception of the external school food environment. Nutrients. 2021;13(4):1043. https://doi.org/10.3390/nu13041043
  » https://doi.org/10.3390/nu13041043
• ²⁵ Kurihayashi AY, Palombo CNT, Duarte LS, Fujimori E. Food commercialization in schools: analysis of the regulatory process in Brazil. Rev Nutr. 2022;35:e210094. https://doi.org/10.1590/1678-9865202235E210094
  » https://doi.org/10.1590/1678-9865202235E210094
• ²⁶ Cuvi J. The politics of field destruction and the survival of São Paulo's street vendors. Soc Probl. 2016;63(3):395-412. https://doi.org/10.1093/socpro/spw013
  » https://doi.org/10.1093/socpro/spw013
• ²⁷ Louzada MLC, Cruz GL, Silva KAAN, Grassi AGF, Andrade GC, Rauber F, et al. Consumo de alimentos ultraprocessados no Brasil: distribuição e evolução temporal 2008-2018. Rev Saude Publica. 2023;57:12. https://doi.org/10.11606/s1518-8787.2023057004744
  » https://doi.org/10.11606/s1518-8787.2023057004744
• ²⁸ Neri MC. Mapa da riqueza no Brasil. FGV Social; 2023 [cited 2025 Jul 16]. Available from: https://cps.fgv.br/riqueza
  » https://cps.fgv.br/riqueza
• ²⁹ Baker P, Machado P, Santos T, Sievert K, Backholer K, Hadjikakou M, et al. Ultra-processed foods and the nutrition transition: global, regional and national trends, food systems transformations and political economy drivers. Obes Rev. 2020;21(12):e13126. https://doi.org/10.1111/obr.13126
  » https://doi.org/10.1111/obr.13126
• ³⁰ Reznar MM, Brennecke K, Eathorne J, Gittelsohn J. A cross-sectional description of mobile food vendors and the foods they serve: potential partners in delivering healthier food-away-from-home choices. BMC Public Health. 2019;19(1):744. https://doi.org/10.1186/s12889-019-7075-8
  » https://doi.org/10.1186/s12889-019-7075-8

• Data Availability:
  The data are available on request via the Caeb Study data access form (link: https://forms.gle/MVZrLrnVNdbuP5Xu6).
• Funding:
  Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes - financial code 001). Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq - process 442851/2019-7). ACT Health Promotion. Instituto Brasileiro de Defesa do Consumidor (Idec). Ibirapitanga Institute.

Edited by

• Associate Editor:
  Tonantzin Ribeiro Gonçalves https://orcid.org/0000-0003-0249-3358

Data availability

The data are available on request via the Caeb Study data access form (link: https://forms.gle/MVZrLrnVNdbuP5Xu6).

Publication Dates

• Publication in this collection
  20 Mar 2026
• Date of issue
  2026

History

• Received
  18 July 2025
• Accepted
  11 Jan 2026