contadores web
Skip to main navigation menu Skip to main content Skip to site footer
##common.pageHeaderLogo.altText##

Health promotion and disease prevention

Vol. 26 No. 3 (2024)

Geospatial approach to study the food environment according to the DASH diet guidelines, an Argentinian experience

DOI
https://doi.org/10.22267/rus.242603.336
Submitted
January 25, 2024
Published
2024-11-18

Abstract

Introduction: The characteristics of the food environment influence food choices. Objective: To design and implement a methodology to explore the characteristics of the food environment in a central neighborhood of Córdoba, Argentina, based on the availability of food stores and following the recommendations of the DASH diet (Dietary Approaches to Stop Hypertension). Materials and Methods: 223 stores were analyzed to determine the type of establishment and the availability of foods based on the mentioned approaches. They were georeferenced using coordinates extracted from the Google Earth platform. Then, stores were classified, constructing a continuous quantitative variable that summarizes information about product sales in each place (DASH score). The thematic mapping and score construction were carried out using QGIS 3.22 software. Results: A high predominance of kiosks, bakeries, and fast-food outlets (59.5%) was observed, while stores selling only fresh food represented 17.4% of the total. Additionally, establishments considered 'unhealthy' were mostly located in the northern part of the Alberdi neighborhood in Córdoba. Conclusions: The proposed approach contributes to the study of food environments as a tool for preventing non-communicable diseases and promoting health.

References

  1. Galante M, Konfino J, Ondarsuhu D, Goldberg L, O’Donnell V, Begue C, et al. Principales resultados de la tercera Encuesta Nacional de Factores de Riesgo de enfermedades no transmisibles en Argentina. Rev Argent Salud Pública [Internet]. 2015; 6(24):22-29. Available from: https://www.rasp.msal.gov.ar/index.php/rasp/article/view/214
  2. Secretaría de Gobierno de Salud. 4ta Encuesta Nacional de Factores de Riesgo: Principales Resultados. Buenos Aires (ARG); 2019. Available from: https://new.globalphysicalactivityobservatory.com/new%20anexos/ARGENTINA/0000001444cnt-4ta-encuesta-nacional-factores-riesgo_2019_principales-resultados.pdf
  3. Troncoso-Pantoja C, Monsalve-Reyes C, Alarcón-Riveros MA. Ambientes alimentarios y su rol en la seguridad alimentaria y la malnutrición por exceso. Medisur [Internet]. 2022; 20(6):1200-1210. Available from: http://scielo.sld.cu/scielo.php?script=sci_arttext&pid=S1727-897X2022000601200&lng=es
  4. Gaglioti AH, Xu J, Rollins L, Baltrus P, O'Connell LK, Cooper DL, et al. Neighborhood environmental health and premature death from cardiovascular disease. Prev Chronic Dis [Internet]. 2018; 15:170220. DOI: 10.5888/pcd15.170220
  5. Mackenbach JD, Nelissen KGM, Dijkstra SC, Poelman MP, Daams JG, Leijssen JB, et al. A systematic review on socioeconomic differences in the association between the food environment and dietary behaviors. Nutrients [Internet]. 2019; 11(9):2215. DOI: 10.3390/nu11092215
  6. Ly C, Essman M, Zimmer C, Ng SW. Developing an index to estimate the association between the food environment and CVD mortality rates. Health Place [Internet]. 2020; 66:102469. DOI: 10.1016/j.healthplace.2020.102469
  7. Papas MA, Alberg AJ, Ewing R, Helzlsouer KJ, Gary TL, Klassen AC. The built environment and obesity. Epidemiol Rev [Internet]. 2007; 29(1):129-143. DOI: 10.1093/epirev/mxm009
  8. Booth KM, Pinkston MM, Poston WSC. Obesity and the built environment. J Am Diet Assoc [Internet]. 2005; 105(5):110-117. DOI: 10.1016/j.jada.2005.02.045
  9. Granheim SI, Opheim E, Terragni L, Torheim LE, Thurston M. Mapping the digital food environment: a scoping review protocol. BMJ Open [Internet]. 2020; 10(4):e036241. DOI: 10.1136/bmjopen-2019-036241
  10. National Heart, Lung, and Blood Institute (NHLBI). Living with the DASH Eating Plan. 2021. Available from: https://www.nhlbi.nih.gov/education/dash/living-with-dash
  11. De Grande P, Salvia A. Estratificación y desigualdad social (total país), 2010 [Internet]. Observatorio de la deuda social, Argentina; 2021. Available from: https://mapa.poblaciones.org/map/97801
  12. Boito ME, Michelazzo C. Patrimonio, identidad y espectáculo: una aproximación a las tensiones que conforman el espacio barrial de Alberdi, Córdoba, durante la última década. II Jornadas de Sociología de la Universidad Nacional de Cuyo y Pre ALAS Mendoza. Balances y desafíos de una década larga (2001-2015): aportes y debate desde la sociología. Mendoza (ARG): Universidad Nacional del Cuyo; 2015. Available from: http://hdl.handle.net/11086/5953
  13. Instituto Superior de Estudios Pedagógicos [ISEP]. Alberdi, escenario clave para estudiar la ciudad de Córdoba. Ministerio de Educación de la Provincia de Córdoba; 2018. Available from: http://isep-cba.edu.ar/web/2018/09/21/alberdi-escenario-clave-para-estudiar-la-ciudad-de-cordoba
  14. Glanz K, Sallis JF, Saelens BE, Frank LD. Healthy nutrition environments: concepts and measures. Am J Health Promot [Internet]. 2005;19(5):330-3. DOI: 10.4278/0890-1171-19.5.330
  15. Getchell WS, Svetkey LP, Appel LJ, Moore TJ, Bray GA, Obarzanek E. Summary of the Dietary Approaches to Stop Hypertension (DASH) Randomized Clinical Trial. Curr Treat Options Cardiovasc Med [Internet]. 1999; 1(4):295-298. DOI: 10.1007/s11936-999-0024-6
  16. Navarro A, Muñoz SE, Lantieri MJ, Fabro EA, Eynard AR. Composition of saturated and unsaturated fatty acids of foods frequently consumed in Argentina. Arch Latinoam Nutr [Internet]. 1997; 47(3):276-281. Available from: https://www.alanrevista.org/ediciones/1997/3/art-15
  17. Zhou B, Perel P, Mensah GA, Ezzati M. Global epidemiology, health burden and effective interventions for elevated blood pressure and hypertension. Nat Rev Cardiol [Internet]. 2021; 18(11):785-802. DOI: 10.1038/s41569-021-00559-8
  18. Asociación Argentina de Dietistas y Nutricionistas Dietistas. Nuevas guías alimentarias para la población argentina. 2016. Available from: https://aadynd.org.ar/diaeta/seccion.php?n=60
  19. Ministerio de Salud de Argentina. 2° Encuesta Nacional de Nutrición y Salud. Indicadores priorizados. 2019. Available from: https://bancos.salud.gob.ar/recurso/2deg-encuesta-nacional-de-nutricion-y-salud-indicadores-priorizados
  20. Marchiori GN. Impacto de los lípidos dietarios y séricos sobre biomarcadores inflamatorios y protrombóticos y el desarrollo de aterosclerosis en hipertensión arterial [Tesis doctoral]. Córdoba (ARG): Universidad Nacional de Córdoba; 2021. Available from: https://rdu.unc.edu.ar/bitstream/handle/11086/20667/MARCHIORI%20CC.pdf?sequence=1
  21. Baraquet ML, Del Rosso S, Oberto MG, Defagó MD, Perovic NR. Cardiometabolic risk, biomarkers of low-grade subclinical inflammation and flavonoid intake: a cross-sectional study in Argentina. PharmaNutrition [Internet]. 2022; 20:100297. DOI: 10.1016/j.phanu.2022.100297
  22. Aballay LR. La obesidad en Córdoba: Estudio de su prevalencia e identificación de factores de riesgo [Tesis doctoral]. Córdoba (ARG): Universidad Nacional de Córdoba; 2013. Available from: https://repositoriosdigitales.mincyt.gob.ar/vufind/Record/RDUUNC_819f54ca293f11e2ffcec2cfaa738eeb
  23. García SM, Fantuzzi G, Angelini J, Bourgeois M, Elgart J, Etchegoyen G, et al. Food Intake of an Adult Population in Two Cities in the Province of Buenos Aires: Its Adequacy to Nutritional Recommendations. Actual Nutr [Internet]. 2018; 19(2):38-43. Available from: https://ri.conicet.gov.ar/bitstream/handle/11336/91085/CONICET_Digital_Nro.deb85d31-ba97-4f0d-bcb7-c9f91f248a02_A.pdf?sequence=2
  24. Creel JS, Sharkey JR, McIntosh A, Anding J, Huber JC Jr. Availability of healthier options in traditional and nontraditional rural fast-food outlets. BMC Public Health [Internet]. 2008; 8(1):395. DOI: 10.1186/1471-2458-8-395
  25. Hattori A, An R, Sturm R. Neighborhood food outlets, diet, and obesity among California adults, 2007 and 2009. Prev Chronic Dis [Internet]. 2013; 10:120123. DOI: 10.5888/pcd10.120123
  26. Colozza D, Avendano M. Urbanisation, dietary change and traditional food practices in Indonesia: a longitudinal analysis. Soc Sci Med [Internet]. 2019; 233:103-112. DOI: 10.1016/j.socscimed.2019.06.007
  27. Leone AF, Rigby S, Betterley C, Park S, Kurtz H, Johnson MA, et al. Store type and demographic influence on the availability and price of healthful foods, Leon County, Florida, 2008. Prev Chronic Dis [Internet]. 2011; 8(6):A140. Available from: https://pubmed.ncbi.nlm.nih.gov/22005633
  28. Bilal U, Díez J, Alfayate S, Gullón P, Del Cura I, Escobar F, et al. Population cardiovascular health and urban environments: the Heart Healthy Hoods exploratory study in Madrid, Spain. BMC Med Res Methodol [Internet]. 2016; 16(1):104. DOI: 10.1186/s12874-016-0213-4
  29. Díez J, Conde P, Sandin M, Urtasun M, López R, Carrero JL, et al. Understanding the local food environment: A participatory photovoice project in a low-income area in Madrid, Spain. Health Place [Internet]. 2017; 43:95-103. DOI: 10.1016/j.healthplace.2016.11.012
  30. Beaulac J, Kristjansson E, Cummins S. A systematic review of food deserts, 1966-2007. Prev Chronic Dis [Internet]. 2009; 6(3):A105. Available from: https://pubmed.ncbi.nlm.nih.gov/19527577
  31. Alcocer-García O, Campos-Alanís J. The convenience store format as a mean of proximity of services and supply in urban areas. Quivera [Internet]. 2014; 16(2):63-84. Available from: https://www.redalyc.org/pdf/401/40136960004.pdf
  32. Walker RE, Keane CR, Burke JG. Disparities and access to healthy food in the United States: A review of food deserts literature. Health Place [Internet]. 2010; 16(5):876-884. DOI: 10.1016/j.healthplace.2010.04.013
  33. Hilmers A, Hilmers DC, Dave J. Neighborhood disparities in access to healthy foods and their effects on environmental justice. Am J Public Health [Internet]. 2012; 102(9):1644-1654. DOI: 10.2105/AJPH.2012.300865
  34. Ghosh-Dastidar B, Cohen D, Hunter G, Zenk SN, Huang C, Beckman R, et al. Distance to store, food prices, and obesity in urban food deserts. Am J Prev Med [Internet]. 2014; 47(5):587-595. DOI: 10.1016/j.amepre.2014.07.005
  35. Cooksey-Stowers K, Schwartz MB, Brownell KD. Food swamps predict obesity rates better than food deserts in the United States. Int J Environ Res Public Health [Internet]. 2017; 14(11):1366. DOI: 10.3390/ijerph14111366
  36. Liese AD, Weis KE, Pluto D, Smith E, Lawson A. Food store types, availability, and cost of foods in a rural environment. J Am Diet Assoc [Internet]. 2007; 107(11):1916-1923. DOI: 10.1016/j.jada.2007.08.012
  37. Courtemanche C, Carden A. Supersizing supercenters? The impact of Walmart Supercenters on body mass index and obesity. J Urban Econ [Internet]. 2011; 69(2):165-181. DOI: 10.1016/j.jue.2010.09.005
  38. Trinh H, Dhar B, Simioni M, de Haan S, Thanh Huynh TT, Huynh TV. Supermarkets and household food acquisition patterns in Vietnam in relation to population demographics and socioeconomic strata: insights from public data. Front Sustain Food Syst [Internet]. 2020; 4(15):1-12. DOI: 10.3389/fsufs.2020.00015
  39. Honório OS, Pessoa MC, Gratão LHA, Rocha LL, de Castro IRR, Canella DS, et al. Social inequalities in the surrounding areas of food deserts and food swamps in a Brazilian metropolis. Int J Equity Health [Internet]. 2021; 20(1):168. DOI: 10.1186/s12939-021-01501-7
  40. Fagundes Grilo M, de Menezes C, Duran AC. Food swamps in Campinas, Brazil. Cien Saude Colet [Internet]. 2022; 27(7):2717-2728. DOI: 10.1590/1413-81232022277.17772021en
  41. Begué C, Goldberg L, King A, Odonnell V, Piaggio LR, Rolón MI. ¿Cuán disponibles están las opciones saludables?: estudio descriptivo de entornos alimentarios de universidades argentinas. Rev Argent Salud Pública [Internet]. 2019; 10(41):37-45. Available from: https://rasp.msal.gov.ar/index.php/rasp/article/view/105
  42. Elorriaga N, Moyano DL, López MV, Cavallo AS, Gutierrez L, Panaggio CB, et al. Urban retail food environments: relative availability and prominence of exhibition of healthy vs. unhealthy foods at supermarkets in Buenos Aires, Argentina. Int J Environ Res Public Health [Internet]. 2021; 18(3):944. DOI: 10.3390/ijerph18030944
  43. Bertoni AG, Foy CG, Hunter JC, Quandt SA, Vitolins MZ, Whitt-Glover MC. A multilevel assessment of barriers to adoption of Dietary Approaches to Stop Hypertension (DASH) among African Americans of low socioeconomic status. JHCPU [Internet]. 2011; 22(4):1205-1220. DOI: 10.1353/hpu.2011.0142
  44. Young CM, Batch BC, Svetkey LP. Effect of socioeconomic status on food availability and cost of the Dietary Approaches to Stop Hypertension (DASH) dietary pattern. J Clin Hypertens [Internet]. 2008; 10(8):603-611. DOI: 10.1111/j.1751-7176.2008.08199.x
  45. Instituto Nacional de Estadística y Censos de Argentina. Índices de precios al consumidor (IPC). Ínformes Técnicos vol. 7 no. 264, 2023 [Internet]. Buenos Aires (ARG): INDEC; 2023. Available from: https://www.indec.gob.ar/uploads/informesdeprensa/ipc_12_23EA48BE000C.pdf

Downloads

Download data is not yet available.