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Sources of food ready to consume around the Health Academy Program units: an analysis according to inequality

Abstract

The aim of this study was to spatially examine the distribution of establishments for the acquisition of food that is ready to consume around the Health Academy Program (PAS) in Belo Horizonte, Minas Gerais, Brazil, according to the Municipal Human Development Index (IDH-M).This is an ecological study with the PAS as the unit of analysis. The establishments contained in a circular buffer with a radius of 900 meters from the 77 units of the PAS in operation were evaluated. Address and type of establishment data were obtained from a public list and verified in a virtual audit. Thematic kernel maps were used. A total of 3,050 establishments were identified around the PAS units. Higher densities were observed around units located in the city’s south-central region and in areas with high and very high IDH-M. There was a high density of establishments selling ready-to-consume foods around the PAS units, especially in the wealthier parts of the city. These results are useful in supporting the planning of actions aimed at strengthening the PAS as a promoter of healthy eating environments. Further, it reinforces the need for equitable public policies for supply and regulation, aiming to promote access to adequate and healthy food for all.

Key words:
Food environment; Business; Ultra-processed foods; Health programs; Geographic mapping

Resumo

Objetivou-se analisar espacialmente a distribuição de estabelecimentos de aquisição de alimentos para consumo imediato no entorno do Programa Academia da Saúde (PAS) de Belo Horizonte, Minas Gerais, Brasil, segundo Índice de Desenvolvimento Humano Municipal (IDHM). Estudo ecológico tendo o PAS como unidade de análise. Foram avaliados estabelecimentos de aquisição de alimentos para consumo imediato contidos em buffer circular com raio de 900 metros a partir das 77 unidades do PAS em funcionamento. Endereços e tipos de estabelecimento foram obtidos em lista pública e verificados em auditoria virtual. Mapas de Kernel temático foram elaborados. Identificou-se 3.050 estabelecimentos no entorno das unidades do PAS. Maiores densidades foram observadas na região Centro-sul da cidade e em áreas com IDHM alto e muito alto. Foi elevada a densidade de estabelecimentos comerciais de venda de alimentos para consumo imediato no entorno das unidades do PAS, sobretudo em áreas mais ricas. Os resultados podem subsidiar ações que visem fortalecer o PAS como promotor de ambientes alimentares saudáveis. Ademais, reforça a necessidade de políticas públicas equânimes de abastecimento e regulação visando promover o acesso à alimentação adequada e saudável para todos.

Palavras-chave:
Ambiente alimentar; Comércio; Alimentos ultraprocessados; Programas de saúde; Mapeamento geográfico

Introduction

The expansion of urban centers has led to changes in the population’s lifestyle, such as a reduction in time devoted to eating at home and the consequent search for convenience in preparing meals and consuming food11 Brasil. Ministério da Saúde (MS). Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Guia alimentar para a população brasileira. 2ª ed. Brasília: MS; 2014.. In this sense, the food environment plays an important role in the food choices of individuals and families, and the predominance of establishments selling ready-to-consume foods in a given region may favor the intake of these foods22 Lucan SC, Maroko AR, Seitchik JL, Yoon D, Sperry LE, Schechter CB. Sources of Foods That Are Ready-to-Consume ('Grazing Environments') Versus Requiring Additional Preparation ('Grocery Environments'): Implications for Food-Environment Research and Community Health. J Community Health 2018; 43: 886-895.

3 Black C, Moon G, Baird J.Dietary inequalities: what is the evidence for the effect of the neighbourhood food environment? Health Place 2014; 27:229-242.

4 Morland KB, Evenson KR. Obesity prevalence and the local food environment. Health Place 2009; 15:491-495.
-55 Morland K, Wing S, Diez Roux A. The contextual effect of the local food environment on residents' diets: the atherosclerosis risk in communities study. Am J Public Health 2002; 92:1761-1768.. Among these establishments, restaurants and snack bars stand out for selling mostly ultra-processed foods (UPFs) such as soft drinks, snacks, and fast food66 Bezerra IN, Moreira TMV, Cavalcante JB, Souza AM, Sichieri R. Consumo de alimentos fora do lar no Brasil segundo locais de aquisição. Rev Saude Publica 2017; 51:15..

UPFs are formulated from ingredients extracted from other foods (sugars, oils, proteins, starch, and fibers) and are often added with industrial additives, such as dyes and flavoring, to make them hyperpalatable and increase their consumption77 Monteiro CA, Cannon G, Lawrence M, Louzada MLC, Machado PP. Ultra-processed foods, diet quality, and health using the NOVA classification system. Rome: FAO; 2019.,88 Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, Rauber F, Khandpur N, Cediel G, Neri D, Martinez-Steele E, Baraldi LG, Jaime PC. Ultra-processed foods: what they are and how to identify them. Public Health Nutr 2019; 22:936-941.. Excessive intake of these foods is associated with poorer diet quality, excessive weight gain, the development of obesity, and other chronic non-communicable diseases (NCDs)88 Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, Rauber F, Khandpur N, Cediel G, Neri D, Martinez-Steele E, Baraldi LG, Jaime PC. Ultra-processed foods: what they are and how to identify them. Public Health Nutr 2019; 22:936-941.

9 Campos SF, Santos LC, Lopes MS, Freitas PP, Lopes AC. Consumption of ultra-processed foods and nutritional profile in a health promotion service of primary care. Public Health Nutr 2021; 24(15):5113-5126.

10 Hall KD, Ayuketah A, Brychta R, Cai H, Cassimatis T, Chen KY, Chung ST, Costa E, Courville A, Darcey V, Fletcher LA, Forde CG, Gharib AM, Guo J, Howard R, Joseph PV, McGehee S, Ouwerkerk R, Raisinger K, Rozga I, Stagliano M, Walter M, Walter PJ, Yang S, Zhou M. Ultra-processed diets cause excess calorie intake and weight gain: an inpatient randomized controlled trial of ad libitum food intake. Cell Metab 2019; 30:67-77.

11 Mendonça RD, Lopes AC, Pimenta AM, Gea A, Martinez-Gonzalez MA, Bes-Rastrollo M. Ultra-processed food consumption and the incidence of hypertension in a Mediterranean cohort: the Seguimiento Universidad de Navarra Project. Am J Hypertens 2017; 30:358-366.
-1212 Mendonça RD, Pimenta AM, Gea A, de la Fuente-Arrillaga C, Martinez-Gonzalez MA, Lopes AC, Bes-Rastrollo M. Ultraprocessed food consumption and risk of overweight and obesity: the University of Navarra Follow-Up (SUN) cohort study. Am J Clin Nutr 2016; 104:1433-1440..

Despite evidence presented by international studies, national research that describes the distribution of establishments that primarily sell UPFs is scarce, especially in the vicinity of health services1313 Turner C, Kalamatianou S, Drewnowski A, Kulkarni B, Kinra S, Kadiyala S. Food environment research in low-and middle-income countries: a systematic scoping review. Adv Nutr 2020; 11:387-397.. In the realm of public health promotion services, such as the Health Academy Program (PAS), no studies have been identified. However, PAS is usually located in areas with health and economic vulnerability, which lack studies on the food environment.

PAS is a point of attention in the Unified Health System (SUS), which seeks to promote health and control of NCDs based on changes in people’s lifestyles and the development of healthy territories1414 Brasil. Ministério da Saúde (MS). Portaria nº 719, de 7 de abril de 2011. Institui o Programa Academia da Saúde no âmbito do Sistema Único de Saúde. 2011. Diário Oficial da União; 2011.. To this end, it is guided by the principles of integrality, intersectoriality, popular participation, interdisciplinarity, intergenerationality, and territoriality1515 Brasil. Ministério da Saúde (MS). Portaria nº 2.681, de 7 de novembro de 2013. Redefine o Programa Academia da Saúde no âmbito do Sistema Único de Saúde. 2013. Diário Oficial da União; 2013.. In Belo Horizonte-MG, the municipality in which this work was carried out, and the activities offered by the program, include bodily and physical activities, the production of care, and healthy ways of living. Adequate and healthy food, integrative and complementary practices, education in health, artistic and cultural practices, and social mobilization are promoted among other initiatives1414 Brasil. Ministério da Saúde (MS). Portaria nº 719, de 7 de abril de 2011. Institui o Programa Academia da Saúde no âmbito do Sistema Único de Saúde. 2011. Diário Oficial da União; 2011.,1616 Belo Horizonte. Prefeitura de Belo Horizonte. Academia da Cidade: Saúde e equilíbrio mais próximo do cidadão [Internet]. 2021 [acessado 2022 fev 1]. Disponível em: https://prefeitura.pbh.gov.br/saude/informacoes/atencao-a-saude/promocao-da-saude/academia-da-cidade.
https://prefeitura.pbh.gov.br/saude/info...
,1717 Lopes ACS, Ferreira AD, Mendonça RD, Dias MAS, Rodrigues RCLC, Santos LC. Estratégia de promoção à saúde: programa academia da cidade de Belo Horizonte. Rev Bras Ativ Fis Saude 2016; 21:381-386..

The influence of the food environment on food choices and its repercussions for the health of the population, as well as the importance of environments favorable to health, underscore the need to characterize the food environment, especially in the surroundings of health services, such as the PAS, aiming to attain the intersectoriality of policies. In this sense, this study aimed to spatially analyze the distribution of establishments selling ready-to-consume foods in the surroundings of the PAS in Belo Horizonte, Minas Gerais, Brazil, according to the Municipal Human Development Index (IDH-M).

Methods

Design and location of the study

An ecological study was developed from data on establishments selling ready-to-consume foods in the city of Belo Horizonte, Minas Gerais. This metropolis is the sixth most populous city in Brazil, with a population projection for 20181818 Instituto Brasileiro de Geografia e Estatística (IBGE). IBGE divulga as Estimativas de População dos municípios para 2018 [Internet]. 2018 [acessado 2022 fev 1]. Disponível em: https://censos.ibge.gov.br/agencia-sala-de-imprensa/2013-agencia-de-noticias/releases/22374-ibge-divulga-as-estimativas-de-populacao-dos-municipios-para-2018.
https://censos.ibge.gov.br/agencia-sala-...
of more than 2.5 million inhabitants in a 331 km² area subdivided into nine administrative regions1919 Instituto Brasileiro de Geografia e Estatística (IBGE). Belo Horizonte [Internet]. 2010 [acessado 2022 fev 1]. Disponível em: https://cidades.ibge.gov.br/brasil/mg/belo-horizonte/panorama.
https://cidades.ibge.gov.br/brasil/mg/be...
and 277 Human Development Units (HDUs).

HDUs are units of analysis with fairly homogeneous socioeconomic characteristics, resulting from the aggregation of census sectors with similar characteristics. They have a maximum area value of 19.91 km² and a minimum of 0.01 km², with an average value of 1.19 km². The features and spatial distribution of these areas are not homogeneous, and respect the junction of limits of census sectors selected for each unit. HDUs were created for AtlasBR in a partnership between the United Nations Development Program (UNDP), the João Pinheiro Foundation (FJP), and the Institute for Applied Economic Research (IPEA)2020 Plataforma Atlas do Desenvolvimento Humano no Brasil (AtlasBR) [Internet]. [acessado 2020 Jul 11]. Disponível em: www.atlasbrasil.org.br.
www.atlasbrasil.org.br...
. For the city of Belo Horizonte, the data were gathered from the 2000 and 2010 demographic censuses by the Brazilian Institute of Geography and Statistics (IBGE) and include demographic and socioeconomic indicators. In this study, only data from 2010 were used, as they are closer to the year in which the data were collected.

Among the data provided by HDUs, the IDH-M was also calculated for 2010. The components of IDH-M are longevity, education and income. The index ranges from 0 to 1, and the closer to 1, the greater the human development2020 Plataforma Atlas do Desenvolvimento Humano no Brasil (AtlasBR) [Internet]. [acessado 2020 Jul 11]. Disponível em: www.atlasbrasil.org.br.
www.atlasbrasil.org.br...
. According to the AtlasBR criteria for the composition and classification of the index, Belo Horizonte has an IDH-M ranging from medium (0.617-0.699) to high (0.700-0.799) and very high (0.800-0.955)2020 Plataforma Atlas do Desenvolvimento Humano no Brasil (AtlasBR) [Internet]. [acessado 2020 Jul 11]. Disponível em: www.atlasbrasil.org.br.
www.atlasbrasil.org.br...
.

Study sample and database

Establishments selling ready-to-consume foods located in a 900-meter radius around the 77 PAS units, operating in the municipality in January 2018, were investigated. These PAS units serve approximately 19,000 users and are distributed throughout the municipality’s nine administrative regions1616 Belo Horizonte. Prefeitura de Belo Horizonte. Academia da Cidade: Saúde e equilíbrio mais próximo do cidadão [Internet]. 2021 [acessado 2022 fev 1]. Disponível em: https://prefeitura.pbh.gov.br/saude/informacoes/atencao-a-saude/promocao-da-saude/academia-da-cidade.
https://prefeitura.pbh.gov.br/saude/info...
.

Information on establishments that sell ready-to-consume foods in the municipality was obtained from the register of the Municipal Secretary of Social Assistance, Food Security and Citizenship (SMASAC). The following were considered establishments that sell ready-to-consume foods: bakeries and confectioneries; convenience stores; restaurants and equivalents; bars; snack bars; and tea, juice houses, and equivalents. The complete list of subclasses of establishments classified as places that sell ready-to-consume foods can be found in Chart 1.

Chart 1
Investigated subclasses of establishments selling ready-to-consume foods according to the Brazilian Institute of Geography and Statistics.

All establishments in the database were georeferenced in a semi-automated way by a trained team through a Google Maps Application Programming Interface (API) in which the addresses of establishments were entered to obtain their respective geographic coordinates in latitude and longitude format. Non-processed establishments were manually georeferenced using Google Maps. In the event of the impossibility of georeferencing due to inconsistencies in the addresses, an additional search was carried out in Open Street Map2121 Open Street Map [Internet]. [acessado 2020 jul 11]. Disponível em: https://www.opnestreetmap.org.
https://www.opnestreetmap.org...
to obtain the latitude and longitude. Establishments not located after this stage were classified as impossible to georeference and excluded from the study.

Google Maps offers geographic coordinates in latitude and longitude format, decimal degrees, and in the WGS84 datum, requiring their conversion to the UTM projection in SIRGAS 2000 datum. This conversion was made using the geographic calculator from the National Institute for Space Research (INPE)2222 Brasil. Instituto Nacional de Pesquisas Espaciais. Calculadora Geográfica [Internet]. [acessado 2020 jul 11]. Disponível em: http://www.dpi.inpe.br/calcula.
http://www.dpi.inpe.br/calcula...
, and the location given in the UTM projection was compared to the original address from a Google Maps link produced by the geographic calculator.

The location of the PAS units, as well as other databases with data related to the urban fabric of the municipality, was accessed through the geoportal available on the Belo Horizonte City Hall website2323 Prefeitura de Belo Horizonte. BH Map - Visualizador [Internet]. [acessado 2020 jul 11]. Disponível em: http://bhmap.pbh.gov.br/v2/mapa/idebhgeo.
http://bhmap.pbh.gov.br/v2/mapa/idebhgeo...
.

From the georeferencing of the PAS units, circular buffers were built with a 900-meter radius around each one, a distance corresponding to approximately ten minutes of walking; that is, a distance considered walkable. Establishments selling ready-to-consume foods within these buffers (n=6,467) were selected for the next stages of the study.

After selecting the establishments, a virtual audit was carried out to confirm the existence of the establishment and whether it was intended for selling ready-to-consume foods. Other eligible establishments appear in the search areas but are not listed in the database; these were also identified (n=244). To perform a virtual audit, the addresses of the establishments were entered into the tool, which enabled us to obtain a panoramic view of the environment with a range of 360° horizontally and 290° vertically. The existence and type of establishment and the year of image capture by Street View were checked, prioritizing images captured in 2018, the same year as the database. To classify the establishments that sell ready-to-consume foods as existing, the façade, signs, and characteristics of the interior of the stores (when possible) that identified them as belonging to this category were analyzed. This entire process was carried out by a trained team using the Street View tool on Google Maps (Google Inc. 2019).

The existence of establishments located inside shopping malls, galleries and district/municipal/central markets was verified by checking the list of establishments available on the website of the relevant location. In the event that this information was unavailable, the establishment was considered non-existent. Places with no indication of becoming a commercial establishment (e.g., residences and vacant lots), as well as establishments whose virtual audit was impossible due to location (e.g., streets without Street View image capture), were deemed non-existent. Also, establishments inside private institutions do not have images registered on Street View and street food services due to the absence of a fixed sales address.

After the virtual audit of 6,467 establishments, those considered non-existent (n=2,932; 43.3%) and those that were not considered establishments that sell ready-to-consume foods (n=729; 10.8%) were excluded (Figure 1).

Figure 1
Study flowchart.

Data analysis

The distribution frequencies of the PAS units and establishments that sell ready-to-consume foods by IDH-M category were shown as a percentage with 95% confidence intervals (95%CI). Differences were examined from 95%CI analysis.

In parallel, a kernel density map and thematic map were created, representing the distribution of the number of establishments by HDU and their respective IDH-M to guide the spatial analysis. The kernel density map considers the distribution of georeferenced addresses by interpolating points from a nucleus, enabling the identification of hotspots; that is, areas of greater concentration in the analyzed territory. Classes were created to identify the strata of the IDH-M in the thematic map according to the data used by the Atlas of Human Development in Brazil, segmented into three classes2424 Plataforma Atlas do Desenvolvimento Humano no Brasil (ATLASBR). Consulta por tabelas, utilizando indicadores de população, educação e renda por unidade de desenvolvimento humano, dados do censo demográfico de 2000 e 2010 [Internet]. [acessado 2021 jun 10]. Disponível em: http://www.atlasbrasil.org.br/consulta/planilha.
http://www.atlasbrasil.org.br/consulta/p...
. The classification method adopted for dividing the intervals of the kernel density map analysis categories, and for dividing the class intervals by the number of establishments, was the natural breaks segmented into five classes. This method is useful for mapping data values that are not evenly distributed. Classes established by natural breaks are rooted in natural groupings inherent in the data, and limits are set where there are fairly large differences in data values2525 ESRI. ArcGIS for Power BI. Tipos de Classificação [Internet]. [acessado 2020 jul 11]. Disponível em: https://doc.arcgis.com/pt-br/power-bi/design/classification-types.htm.
https://doc.arcgis.com/pt-br/power-bi/de...
.

Georeferencing, treatment, the spatialization of data, and the elaboration of maps were performed using Microsoft Excel, ArcGis 10.5 and Quantum Gis 3.10.9 software. The statistical analyses were performed in the program STATA/SE, version 14.0 (Stata Corp, College Station, TX, USA).

Results

Among the 77 PAS units analyzed, 41.6% [95%CI: 30.9-53.1] were in areas with a high IDH-M, 37.7% [95%CI: 27.4-49.2], very high, and a 20.8% [95%CI: 13.0-31.5] medium, with no significant differences between the frequency of PAS units and the IDH-M categories (Table 1).

Table 1
Frequency of units of the Health Academy Program (PAS) by category, based on the Municipal Human Development Index (IDH-M). Belo Horizonte, 2018.

A total of 3,050 establishments that sell ready-to-consume foods in the surroundings of the PAS were analyzed. Stratifying them by the IDH-M category revealed that the highest prevalence of these establishments was in areas with very high (58.8 [95%CI: 57.1-60.6]) and high (32.7 [95%CI]: 31.1-34.4]) IDH-M compared to areas with medium IDH-M (8.4 [95%CI: 7.5-9.4]) (Table 2).

Table 2
Frequency of establishments selling ready-to-eat foods by category, based on the Municipal Human Development Index (IDH-M). Belo Horizonte, 2018.

Figure 2 shows the Kernel Density Map with the spatial distribution of the establishments. Darker shades represent zones with the highest concentration of establishments that sell ready-to-consume foods; this intensity diminishes as the density of establishments decreases. The South-Central region is an area with the highest concentration of establishments, but areas with a high density of establishments have also been observed between the North and Venda Nova, West, Northeast, and Barreiro regions.

Figure 2
Kernel Density Map of establishments selling ready-to-consume foods. Belo Horizonte, 2018.

Areas with the highest density of establishments selling ready-to-consume foods were those with very high IDH-M and an emphasis on the South-Central, Northwest, East, West and Pampulha regions. In the Venda Nova and Barreiro regions, the highest density of establishments was concentrated in regions with a high IDH-M (Figure 3).

Figure 3
Location of establishments according to Municipal Human Development Index (IDH-M). Belo Horizonte, 2018.

Discussion

Establishments selling ready-to-consume foods were not distributed in a similar way around the PAS units in Belo Horizonte-MG, with a greater density of establishments in the central and richest parts of the city; that is, those with the highest IDH-M. However, concentrations of these establishments have also been seen in less affluent regions.

As expected, a greater concentration of establishments that sell ready-to-consume foods was identified, with the predominant sale of ready-to-eat foods in the south-central region. This is the main region for commerce, leisure, and services in the city, with a higher concentration of offices, companies, diversified markets, bus stations, cultural spaces, and the movement of people. In addition, it is the wealthiest and most densely populated region in terms of municipalities1616 Belo Horizonte. Prefeitura de Belo Horizonte. Academia da Cidade: Saúde e equilíbrio mais próximo do cidadão [Internet]. 2021 [acessado 2022 fev 1]. Disponível em: https://prefeitura.pbh.gov.br/saude/informacoes/atencao-a-saude/promocao-da-saude/academia-da-cidade.
https://prefeitura.pbh.gov.br/saude/info...
.

The concentrated distribution of food acquisition establishments in central and more affluent parts of cities has been described in other studies, with peculiarities between high- and middle-income countries2626 Lopes MS, Caiaffa WT, Andrade ACS, Carmo AS, Barber S, Mendes LL, Friche AAL. Spatial inequalities of retail food stores may determine availability of healthful food choices in a Brazilian metropolis. Public Health Nutr 2021; 1-12.

27 Assis MM, Leite MA, Carmo ASD, Andrade ACS, Pessoa MC, Pereira Netto M, Cândido APC, Mendes LL. Food environment, social deprivation and obesity among students from Brazilian public schools. Public Health Nutr 2019; 22(11):1920-1927.
-2828 Almeida LFF, Novaes TG, Pessoa MC, Carmo AS, Mendes LL, Ribeiro AQ. Socioeconomic Disparities in the Community Food Environment of a Medium-Sized City of Brazil. J Am Coll Nutr 2021; 40(3):253-260.. In the US, a high-income country, the concentration of establishments seems associated with the type of establishment and the healthiness of the foods sold. For example, establishments selling predominantly healthy foods, such as supermarkets, are mostly located in the richest neighborhoods when compared to the most vulnerable, racially, or economically segregated residents. The opposite seems to happen with unhealthy establishments, such as fast food or convenience stores, which tend to be more prevalent in the most vulnerable areas2929 Gosliner W, Brown DM, Sun BC, Woodward-Lopez G, Crawford PB. Availability, quality and price of produce in low-income neighbourhood food stores in California raise equity issues. Public Health Nutr 2018; 21(9):1639-1648.

30 Rimkus L, Isgor Z, Ohri-Vachaspati P, Zenk SN, Powell LM, Barker DC, Chaloupka FJ. Disparities in the Availability and Price of Low-Fat and Higher-Fat Milk in US Food Stores by Community Characteristics. J Acad Nutr Diet 2015; 115(12):1975-1985.

31 Ohri-Vachaspati P, DeWeese RS, Acciai F, DeLia D, Tulloch D, Tong D, Lorts C, Yedidia M. Healthy Food Access in Low-Income High-Minority Communities: A Longitudinal Assessment-2009-2017. Int J Environ Res Public Health 2019; 16(13):2354.

32 Hallum SH, Hughey SM, Wende ME, Stowe EW, Kaczynski AT. Healthy and unhealthy food environments are linked with neighbourhood socio-economic disadvantage: an innovative geospatial approach to understanding food access inequities. Public Health Nutr 2020; 23(17):3190-3196.
-3333 Bower KM, Thorpe Jr RJ, Rohde C, Gaskin DJ. The intersection of neighborhood racial segregation, poverty, and urbanicity and its impact on food store availability in the United States. Prev Med 2014; 58:33-39..

However, in Brazil, there seems to be a greater availability of commercial establishments in more affluent areas, regardless of type2828 Almeida LFF, Novaes TG, Pessoa MC, Carmo AS, Mendes LL, Ribeiro AQ. Socioeconomic Disparities in the Community Food Environment of a Medium-Sized City of Brazil. J Am Coll Nutr 2021; 40(3):253-260.,3434 Fortes MF, Borges CA, Miranda WC, Jaime PC. Mapeando as desigualdades socioeconômicas na distribuição do comércio varejista local. Segur Aliment Nutr 2018; 25(3):45-58.. Thus, wealthier parts of cities have a greater number of establishments that sell food, whether healthy or not, as suggested by studies carried out in three cities in the country’s Southeast macroregion.

The first, an ecological study that characterized the community food environment according to the socioeconomic status of the census sectors in Viçosa-MG, showed that the average number of food outlets, regardless of type, increased according to the income of the census sector2828 Almeida LFF, Novaes TG, Pessoa MC, Carmo AS, Mendes LL, Ribeiro AQ. Socioeconomic Disparities in the Community Food Environment of a Medium-Sized City of Brazil. J Am Coll Nutr 2021; 40(3):253-260., with agglomeration in the central part of the city. Studies conducted in Jundiaí-SP and Belo Hori zonte-MG also indicated such inequality in the distribution of establishments. The study carried out in Jundiai, for example, revealed that in areas with better sociodemographic indicators, there were higher concentrations of establishments, such as bakeries2626 Lopes MS, Caiaffa WT, Andrade ACS, Carmo AS, Barber S, Mendes LL, Friche AAL. Spatial inequalities of retail food stores may determine availability of healthful food choices in a Brazilian metropolis. Public Health Nutr 2021; 1-12.,3434 Fortes MF, Borges CA, Miranda WC, Jaime PC. Mapeando as desigualdades socioeconômicas na distribuição do comércio varejista local. Segur Aliment Nutr 2018; 25(3):45-58..

It is hypothesized that the diversity of activities in the central and wealthier areas of Brazilian municipalities, and the addition of better connected streets, favor the sale of ready-to-eat foods, thus being an alternative for workers who seek quick meals and live close to their workplace, as well as those who use services and trades in the region. It is believed that the same could happen with users of PAS units located in these regions. However, on the other hand, this hypothesis might not be confirmed in countries such as the US, not only because of their peculiarities and the planning of cities but also because of cultural aspects that affect the population’s food consumption. Another aspect that may contribute to the difference in the outcomes between these countries is the classification of establishments as healthy and unhealthy. For example, while in the US, supermarkets are considered healthy food establishments; in Brazil, in many regions, they are considered to be mixed2626 Lopes MS, Caiaffa WT, Andrade ACS, Carmo AS, Barber S, Mendes LL, Friche AAL. Spatial inequalities of retail food stores may determine availability of healthful food choices in a Brazilian metropolis. Public Health Nutr 2021; 1-12..

Additionally, in Brazil, it is necessary to underline that the consumption of food outside the home has been growing, accounting for a rising share of food costs3535 Instituto Brasileiro de Geografia e Estatística (IBGE). Diretoria de Pesquisas, coordenação de trabalho e rendimento. Pesquisa de Orçamentos Familiares (POF) 2017-2018 Primeiros resultados [Internet]. 2019 [acessado 2021 jun 10]. Disponível em: https://biblioteca.ibge.gov.br/visualizacao/livros/liv101670.pdf.
https://biblioteca.ibge.gov.br/visualiza...
. Changes in the job market, with a greater number of family members outside their homes throughout the day and more time spent commuting, are important factors that drive this process66 Bezerra IN, Moreira TMV, Cavalcante JB, Souza AM, Sichieri R. Consumo de alimentos fora do lar no Brasil segundo locais de aquisição. Rev Saude Publica 2017; 51:15..

A study carried out with data from the 2008-2009 Family Budget Survey concluded that restaurants and snack bars are the most frequent places to purchase ready-to-consume foods, with snack bars being predominantly places to buy UPFs66 Bezerra IN, Moreira TMV, Cavalcante JB, Souza AM, Sichieri R. Consumo de alimentos fora do lar no Brasil segundo locais de aquisição. Rev Saude Publica 2017; 51:15.,88 Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, Rauber F, Khandpur N, Cediel G, Neri D, Martinez-Steele E, Baraldi LG, Jaime PC. Ultra-processed foods: what they are and how to identify them. Public Health Nutr 2019; 22:936-941.. In these establishments, the most consumed foods are beer (51.0%), distilled beverages (44.1%), fried and baked snacks (40.1%), and other non-alcoholic beverages (40.1%), followed by ice cream/popsicles (37.2%), chips (32.7%), stuffed cakes (32.6%), and soft drinks (31.1%)3737 Martins AP, Levy RB, Claro RM, Moubarac JC, Monteiro CA. Increased contribution of ultra-processed food products in the Brazilian diet (1987-2009). Rev Saude Publica 2013; 47(4):656-665.. However, the consumption of these foods may vary according to income, and a higher income is related to greater consumption of vegetables and soft drinks. On the other hand, a lower income is associated with the predominant consumption of UPFs like ham, yogurt, chips, and pizza3636 Brasil. Ministério da Saúde (MS). Política Nacional de Promoção da Saúde. Brasília: MS; 2013..

This scenario is far from the primary objectives of the PAS, since the program is one of the main health promotion strategies proposed by the Plan to Tackle NCDs and the National Policy for Health Promotion3636 Brasil. Ministério da Saúde (MS). Política Nacional de Promoção da Saúde. Brasília: MS; 2013.. Furthermore, avoiding UPF consumption is recommended by the Dietary Guidelines for the Brazilian Population as part of the golden rule for an adequate and healthy diet, one of the guidelines of the National Food and Nutrition Policy11 Brasil. Ministério da Saúde (MS). Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Guia alimentar para a população brasileira. 2ª ed. Brasília: MS; 2014.. The high density of UPF-purchasing establishments can make it difficult for PAS users and the population residing in their territories to adhere to an adequate and healthy diet. This leads to a negative impact on food choices and favoring the replacement of traditional eating habits by the excessive consumption of UPFs3737 Martins AP, Levy RB, Claro RM, Moubarac JC, Monteiro CA. Increased contribution of ultra-processed food products in the Brazilian diet (1987-2009). Rev Saude Publica 2013; 47(4):656-665.,3838 Menezes MC, Costa BV, Oliveira CD, Lopes AC. Local food environment and fruit and vegetable consumption: An ecological study. Prev Med Rep 2016; 5:13-20., which is associated with the development of obesity and other NCDs88 Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, Rauber F, Khandpur N, Cediel G, Neri D, Martinez-Steele E, Baraldi LG, Jaime PC. Ultra-processed foods: what they are and how to identify them. Public Health Nutr 2019; 22:936-941.,3939 Hall KD. Did the Food Environment Cause the Obesity Epidemic? Obesity (Silver Spring) 2018; 26(1):11-13.,4040 Swinburn BA, Sacks G, Hall KD, McPherson K, Finegood DT, Moodie ML, Gortmaker SL. The global obesity pandemic: shaped by global drivers and local environments. Lancet 2011; 378(9793):804-814..

Notwithstanding, restaurants - also categorized as establishments that sell ready-to-consume foods - can offer both healthy and unhealthy foods. Restaurants that provide a wide variety of culinary preparations are considered good alternatives for individuals who cannot routinely eat at home11 Brasil. Ministério da Saúde (MS). Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Guia alimentar para a população brasileira. 2ª ed. Brasília: MS; 2014.. However, meals eaten in commercial restaurants can also result in higher consumption of sugars, sweets, oils and fats4141 Bandoni DH, Canella DS, Levy RB, Jaime PC. Eating out or in from home: analyzing the quality of meal according eating locations. Rev Nutr 2013; 26(6):25-32..

Although in smaller concentrations, in this study, we observed a high density of establishments that sell ready-to-consume foods in peripheral parts of the city, such as in the West, Venda Nova, and Northwest regions. This may indicate the expansion of new commercial centers, driven by the process of organization and population growth. In addition, the location of PAS units, as recommended by Ordinance 2684/2013, should favor regions with greater health vulnerability and that concentrate a large number of people in order to help build healthy environments that serve more individuals4242 Freitas PP, Menezes MC, Lopes ACS. Consumer food environment and overweight. Nutrition 2019; 66:108-114.,4343 Menezes MC, Diez Roux AV, Souza Lopes AC. Fruit and vegetable intake: Influence of perceived food environment and self-efficacy. Appetite 2018; 127:249-256..

In this context, intersectoral policies are indispensable. That said, the main policies observed in different countries are related to the provision of nutritional information on menus, which are important but insufficient4444 McGuffin LE, Wallace JM, McCrorie TA, Price RK, Pourshahidi LK, Livingstone MB. Family eating out-of-home: a review of nutrition and health policies. Proc Nutr Soc 2013; 72(1):126-139.. According to the World Health Organization (WHO), governments need to engage in proactive measures to encourage the sectors responsible for the food supply to recognize issues and to act responsibly to contribute to better consumer choices4545 World Health Organization (WHO). Global action plan for the prevention and control of noncommunicable diseases 2013-2020 [Internet]. 2013 [acessado 2021 jun 10]. Disponível em: https://apps.who.int/iris/handle/10665/94384.
https://apps.who.int/iris/handle/10665/9...
. Strategies include regulating advertising, subsidizing healthy foods, and increasing the supply of healthier foods in establishments that sell ready-to-consume foods.

Previous evidence that indicates limited access to establishments that sell fruits, vegetables, food, and nutritional security equipment2828 Almeida LFF, Novaes TG, Pessoa MC, Carmo AS, Mendes LL, Ribeiro AQ. Socioeconomic Disparities in the Community Food Environment of a Medium-Sized City of Brazil. J Am Coll Nutr 2021; 40(3):253-260.,3131 Ohri-Vachaspati P, DeWeese RS, Acciai F, DeLia D, Tulloch D, Tong D, Lorts C, Yedidia M. Healthy Food Access in Low-Income High-Minority Communities: A Longitudinal Assessment-2009-2017. Int J Environ Res Public Health 2019; 16(13):2354.,4646 Duran AC, Diez Roux AV, Latorre MR, 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. in PAS territory - in addition to the high availability of establishments that sell ready-to-eat food, as shown in this study - points to a double health risk for the population. In addition to the low number of establishments that sell healthy foods in PAS areas, the low variety of fruits and vegetables hinders the consumption of these foods, in addition to being associated with the monotony of food consumption and being overweight4242 Freitas PP, Menezes MC, Lopes ACS. Consumer food environment and overweight. Nutrition 2019; 66:108-114.,4343 Menezes MC, Diez Roux AV, Souza Lopes AC. Fruit and vegetable intake: Influence of perceived food environment and self-efficacy. Appetite 2018; 127:249-256.,4747 Mendonça RD, Lopes MS, Freitas PP, Campos SF, Menezes MC, Lopes ACS. Monotony in the consumption of fruits and vegetables and food environment characteristics. Rev Saude Publica 2019; 53(63):1-12..

One limitation of this study is the information bias imposed by the use of secondary data and the failure to conduct an on-site audit of the establishments. Virtual audits are a good alternative to reduce the risk of such bias given the difficulties in carrying out an on-site validation due to the municipality’s large territorial extension. In addition, the virtual audit has a lower cost, a relevant aspect in the national scenario of a lack of funding for research4848 Malta DC, Reis AACD, Jaime PC, Morais Neto OL, Silva MMAD, Akerman M. Brazil's Unified Health System and the National Health Promotion Policy: prospects, results, progress and challenges in times of crisis. Cien Saude Colet 2018; 23(6):1799-1809.,4949 Silva AGD, Teixeira RA, Prates EJS, Malta DC. Monitoring and projection of targets for risk and protection factors for coping with noncommunicable diseases in Brazilian capitals. Cien Saude Colet 2021; 26(4):1193-1206.. The choice of not including informal food services such as street vendors and food trucks, and establishments located on private property, serving as potential food stores for immediate consumption, may have limited the characterization of the community environment of the investigated territories.

Another limitation refers to the Street View capture tool, which can record the environmental image on a certain date that is not necessarily the same as the date in the database. Notwithstanding, in this study, the analysis of images captured in 2018 was prioritized, the same period of data registration in the municipality’s database. Finally, the lack of information on the type of food sold within commercial establishments and other information on the consumer’s food environment restricted some conclusions, highlighting the need to carry out future surveys with this objective. Another limitation was the lack of temporal correspondence between data relating to commercial establishments and the IDH-M. That said, at the time of this investigation, there were no reliable data with temporal correspondence for such analysis, since it was only in 2021 that a new demographic census started in the country, which is still ongoing.

A strength of this study is that it characterizes the food environment of the community related to the acquisition of ready-to-consume foods in the territories of all units of PAS in a Brazilian metropolis, which is unprecedented in the Brazilian literature. The characterization of the food environment in PAS territory can assist with the implementation of health promotion, as well as food and nutrition policies, that aim to advance health-friendly food environments, in addition to food and nutrition education for the community that uses these health services. Furthermore, carrying out this investigation has the potential to help monitor strategies that foster adequate and healthy eating and combat NCDs, such as obesity4848 Malta DC, Reis AACD, Jaime PC, Morais Neto OL, Silva MMAD, Akerman M. Brazil's Unified Health System and the National Health Promotion Policy: prospects, results, progress and challenges in times of crisis. Cien Saude Colet 2018; 23(6):1799-1809.,4949 Silva AGD, Teixeira RA, Prates EJS, Malta DC. Monitoring and projection of targets for risk and protection factors for coping with noncommunicable diseases in Brazilian capitals. Cien Saude Colet 2021; 26(4):1193-1206..

Conclusion

Mapping establishments that sell ready-to-consume foods around the PAS units in Belo Horizonte-MG made it possible to verify socioeconomic inequality in their distribution. The densities of establishments were higher in areas with higher IDH-M; however, concentrations were also observed in less affluent regions. These results reinforce the need for more equitable food and health regulation and supply policies, which consider the singularities of the development of each part of the city. Therefore, actions should promote access to healthy food for all and protect the population against excessive exposure to UPFs, especially in the city’s central zones and peripheral areas with consolidated subcenters.

Acknowledgments

We thank the Prefeitura Municipal de Belo Horizonte for making the database available, and the entire team of researchers from GIN/UFMG-CNPq for their collaboration in the georeferencing and virtual audit of the database.

Referências

  • 1
    Brasil. Ministério da Saúde (MS). Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Guia alimentar para a população brasileira. 2ª ed. Brasília: MS; 2014.
  • 2
    Lucan SC, Maroko AR, Seitchik JL, Yoon D, Sperry LE, Schechter CB. Sources of Foods That Are Ready-to-Consume ('Grazing Environments') Versus Requiring Additional Preparation ('Grocery Environments'): Implications for Food-Environment Research and Community Health. J Community Health 2018; 43: 886-895.
  • 3
    Black C, Moon G, Baird J.Dietary inequalities: what is the evidence for the effect of the neighbourhood food environment? Health Place 2014; 27:229-242.
  • 4
    Morland KB, Evenson KR. Obesity prevalence and the local food environment. Health Place 2009; 15:491-495.
  • 5
    Morland K, Wing S, Diez Roux A. The contextual effect of the local food environment on residents' diets: the atherosclerosis risk in communities study. Am J Public Health 2002; 92:1761-1768.
  • 6
    Bezerra IN, Moreira TMV, Cavalcante JB, Souza AM, Sichieri R. Consumo de alimentos fora do lar no Brasil segundo locais de aquisição. Rev Saude Publica 2017; 51:15.
  • 7
    Monteiro CA, Cannon G, Lawrence M, Louzada MLC, Machado PP. Ultra-processed foods, diet quality, and health using the NOVA classification system. Rome: FAO; 2019.
  • 8
    Monteiro CA, Cannon G, Levy RB, Moubarac JC, Louzada ML, Rauber F, Khandpur N, Cediel G, Neri D, Martinez-Steele E, Baraldi LG, Jaime PC. Ultra-processed foods: what they are and how to identify them. Public Health Nutr 2019; 22:936-941.
  • 9
    Campos SF, Santos LC, Lopes MS, Freitas PP, Lopes AC. Consumption of ultra-processed foods and nutritional profile in a health promotion service of primary care. Public Health Nutr 2021; 24(15):5113-5126.
  • 10
    Hall KD, Ayuketah A, Brychta R, Cai H, Cassimatis T, Chen KY, Chung ST, Costa E, Courville A, Darcey V, Fletcher LA, Forde CG, Gharib AM, Guo J, Howard R, Joseph PV, McGehee S, Ouwerkerk R, Raisinger K, Rozga I, Stagliano M, Walter M, Walter PJ, Yang S, Zhou M. Ultra-processed diets cause excess calorie intake and weight gain: an inpatient randomized controlled trial of ad libitum food intake. Cell Metab 2019; 30:67-77.
  • 11
    Mendonça RD, Lopes AC, Pimenta AM, Gea A, Martinez-Gonzalez MA, Bes-Rastrollo M. Ultra-processed food consumption and the incidence of hypertension in a Mediterranean cohort: the Seguimiento Universidad de Navarra Project. Am J Hypertens 2017; 30:358-366.
  • 12
    Mendonça RD, Pimenta AM, Gea A, de la Fuente-Arrillaga C, Martinez-Gonzalez MA, Lopes AC, Bes-Rastrollo M. Ultraprocessed food consumption and risk of overweight and obesity: the University of Navarra Follow-Up (SUN) cohort study. Am J Clin Nutr 2016; 104:1433-1440.
  • 13
    Turner C, Kalamatianou S, Drewnowski A, Kulkarni B, Kinra S, Kadiyala S. Food environment research in low-and middle-income countries: a systematic scoping review. Adv Nutr 2020; 11:387-397.
  • 14
    Brasil. Ministério da Saúde (MS). Portaria nº 719, de 7 de abril de 2011. Institui o Programa Academia da Saúde no âmbito do Sistema Único de Saúde. 2011. Diário Oficial da União; 2011.
  • 15
    Brasil. Ministério da Saúde (MS). Portaria nº 2.681, de 7 de novembro de 2013. Redefine o Programa Academia da Saúde no âmbito do Sistema Único de Saúde. 2013. Diário Oficial da União; 2013.
  • 16
    Belo Horizonte. Prefeitura de Belo Horizonte. Academia da Cidade: Saúde e equilíbrio mais próximo do cidadão [Internet]. 2021 [acessado 2022 fev 1]. Disponível em: https://prefeitura.pbh.gov.br/saude/informacoes/atencao-a-saude/promocao-da-saude/academia-da-cidade
    » https://prefeitura.pbh.gov.br/saude/informacoes/atencao-a-saude/promocao-da-saude/academia-da-cidade
  • 17
    Lopes ACS, Ferreira AD, Mendonça RD, Dias MAS, Rodrigues RCLC, Santos LC. Estratégia de promoção à saúde: programa academia da cidade de Belo Horizonte. Rev Bras Ativ Fis Saude 2016; 21:381-386.
  • 18
    Instituto Brasileiro de Geografia e Estatística (IBGE). IBGE divulga as Estimativas de População dos municípios para 2018 [Internet]. 2018 [acessado 2022 fev 1]. Disponível em: https://censos.ibge.gov.br/agencia-sala-de-imprensa/2013-agencia-de-noticias/releases/22374-ibge-divulga-as-estimativas-de-populacao-dos-municipios-para-2018
    » https://censos.ibge.gov.br/agencia-sala-de-imprensa/2013-agencia-de-noticias/releases/22374-ibge-divulga-as-estimativas-de-populacao-dos-municipios-para-2018
  • 19
    Instituto Brasileiro de Geografia e Estatística (IBGE). Belo Horizonte [Internet]. 2010 [acessado 2022 fev 1]. Disponível em: https://cidades.ibge.gov.br/brasil/mg/belo-horizonte/panorama
    » https://cidades.ibge.gov.br/brasil/mg/belo-horizonte/panorama
  • 20
    Plataforma Atlas do Desenvolvimento Humano no Brasil (AtlasBR) [Internet]. [acessado 2020 Jul 11]. Disponível em: www.atlasbrasil.org.br
    » www.atlasbrasil.org.br
  • 21
    Open Street Map [Internet]. [acessado 2020 jul 11]. Disponível em: https://www.opnestreetmap.org
    » https://www.opnestreetmap.org
  • 22
    Brasil. Instituto Nacional de Pesquisas Espaciais. Calculadora Geográfica [Internet]. [acessado 2020 jul 11]. Disponível em: http://www.dpi.inpe.br/calcula
    » http://www.dpi.inpe.br/calcula
  • 23
    Prefeitura de Belo Horizonte. BH Map - Visualizador [Internet]. [acessado 2020 jul 11]. Disponível em: http://bhmap.pbh.gov.br/v2/mapa/idebhgeo
    » http://bhmap.pbh.gov.br/v2/mapa/idebhgeo
  • 24
    Plataforma Atlas do Desenvolvimento Humano no Brasil (ATLASBR). Consulta por tabelas, utilizando indicadores de população, educação e renda por unidade de desenvolvimento humano, dados do censo demográfico de 2000 e 2010 [Internet]. [acessado 2021 jun 10]. Disponível em: http://www.atlasbrasil.org.br/consulta/planilha
    » http://www.atlasbrasil.org.br/consulta/planilha
  • 25
    ESRI. ArcGIS for Power BI. Tipos de Classificação [Internet]. [acessado 2020 jul 11]. Disponível em: https://doc.arcgis.com/pt-br/power-bi/design/classification-types.htm
    » https://doc.arcgis.com/pt-br/power-bi/design/classification-types.htm
  • 26
    Lopes MS, Caiaffa WT, Andrade ACS, Carmo AS, Barber S, Mendes LL, Friche AAL. Spatial inequalities of retail food stores may determine availability of healthful food choices in a Brazilian metropolis. Public Health Nutr 2021; 1-12.
  • 27
    Assis MM, Leite MA, Carmo ASD, Andrade ACS, Pessoa MC, Pereira Netto M, Cândido APC, Mendes LL. Food environment, social deprivation and obesity among students from Brazilian public schools. Public Health Nutr 2019; 22(11):1920-1927.
  • 28
    Almeida LFF, Novaes TG, Pessoa MC, Carmo AS, Mendes LL, Ribeiro AQ. Socioeconomic Disparities in the Community Food Environment of a Medium-Sized City of Brazil. J Am Coll Nutr 2021; 40(3):253-260.
  • 29
    Gosliner W, Brown DM, Sun BC, Woodward-Lopez G, Crawford PB. Availability, quality and price of produce in low-income neighbourhood food stores in California raise equity issues. Public Health Nutr 2018; 21(9):1639-1648.
  • 30
    Rimkus L, Isgor Z, Ohri-Vachaspati P, Zenk SN, Powell LM, Barker DC, Chaloupka FJ. Disparities in the Availability and Price of Low-Fat and Higher-Fat Milk in US Food Stores by Community Characteristics. J Acad Nutr Diet 2015; 115(12):1975-1985.
  • 31
    Ohri-Vachaspati P, DeWeese RS, Acciai F, DeLia D, Tulloch D, Tong D, Lorts C, Yedidia M. Healthy Food Access in Low-Income High-Minority Communities: A Longitudinal Assessment-2009-2017. Int J Environ Res Public Health 2019; 16(13):2354.
  • 32
    Hallum SH, Hughey SM, Wende ME, Stowe EW, Kaczynski AT. Healthy and unhealthy food environments are linked with neighbourhood socio-economic disadvantage: an innovative geospatial approach to understanding food access inequities. Public Health Nutr 2020; 23(17):3190-3196.
  • 33
    Bower KM, Thorpe Jr RJ, Rohde C, Gaskin DJ. The intersection of neighborhood racial segregation, poverty, and urbanicity and its impact on food store availability in the United States. Prev Med 2014; 58:33-39.
  • 34
    Fortes MF, Borges CA, Miranda WC, Jaime PC. Mapeando as desigualdades socioeconômicas na distribuição do comércio varejista local. Segur Aliment Nutr 2018; 25(3):45-58.
  • 35
    Instituto Brasileiro de Geografia e Estatística (IBGE). Diretoria de Pesquisas, coordenação de trabalho e rendimento. Pesquisa de Orçamentos Familiares (POF) 2017-2018 Primeiros resultados [Internet]. 2019 [acessado 2021 jun 10]. Disponível em: https://biblioteca.ibge.gov.br/visualizacao/livros/liv101670.pdf
    » https://biblioteca.ibge.gov.br/visualizacao/livros/liv101670.pdf
  • 36
    Brasil. Ministério da Saúde (MS). Política Nacional de Promoção da Saúde. Brasília: MS; 2013.
  • 37
    Martins AP, Levy RB, Claro RM, Moubarac JC, Monteiro CA. Increased contribution of ultra-processed food products in the Brazilian diet (1987-2009). Rev Saude Publica 2013; 47(4):656-665.
  • 38
    Menezes MC, Costa BV, Oliveira CD, Lopes AC. Local food environment and fruit and vegetable consumption: An ecological study. Prev Med Rep 2016; 5:13-20.
  • 39
    Hall KD. Did the Food Environment Cause the Obesity Epidemic? Obesity (Silver Spring) 2018; 26(1):11-13.
  • 40
    Swinburn BA, Sacks G, Hall KD, McPherson K, Finegood DT, Moodie ML, Gortmaker SL. The global obesity pandemic: shaped by global drivers and local environments. Lancet 2011; 378(9793):804-814.
  • 41
    Bandoni DH, Canella DS, Levy RB, Jaime PC. Eating out or in from home: analyzing the quality of meal according eating locations. Rev Nutr 2013; 26(6):25-32.
  • 42
    Freitas PP, Menezes MC, Lopes ACS. Consumer food environment and overweight. Nutrition 2019; 66:108-114.
  • 43
    Menezes MC, Diez Roux AV, Souza Lopes AC. Fruit and vegetable intake: Influence of perceived food environment and self-efficacy. Appetite 2018; 127:249-256.
  • 44
    McGuffin LE, Wallace JM, McCrorie TA, Price RK, Pourshahidi LK, Livingstone MB. Family eating out-of-home: a review of nutrition and health policies. Proc Nutr Soc 2013; 72(1):126-139.
  • 45
    World Health Organization (WHO). Global action plan for the prevention and control of noncommunicable diseases 2013-2020 [Internet]. 2013 [acessado 2021 jun 10]. Disponível em: https://apps.who.int/iris/handle/10665/94384
    » https://apps.who.int/iris/handle/10665/94384
  • 46
    Duran AC, Diez Roux AV, Latorre MR, 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.
  • 47
    Mendonça RD, Lopes MS, Freitas PP, Campos SF, Menezes MC, Lopes ACS. Monotony in the consumption of fruits and vegetables and food environment characteristics. Rev Saude Publica 2019; 53(63):1-12.
  • 48
    Malta DC, Reis AACD, Jaime PC, Morais Neto OL, Silva MMAD, Akerman M. Brazil's Unified Health System and the National Health Promotion Policy: prospects, results, progress and challenges in times of crisis. Cien Saude Colet 2018; 23(6):1799-1809.
  • 49
    Silva AGD, Teixeira RA, Prates EJS, Malta DC. Monitoring and projection of targets for risk and protection factors for coping with noncommunicable diseases in Brazilian capitals. Cien Saude Colet 2021; 26(4):1193-1206.
  • Funding

    Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) - Research productivity scholarship ACS Lopes and Programa Institucional de Bolsas de Iniciação Científica (PIBIC); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) - Finance Code 001.

Edited by

Chief editors:

Romeu Gomes, Antônio Augusto Moura da Silva

Publication Dates

  • Publication in this collection
    22 July 2022
  • Date of issue
    Aug 2022

History

  • Received
    06 Oct 2021
  • Accepted
    26 Apr 2022
  • Published
    28 Apr 2022
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