Geographical variation of food discourse on Twitter and its correlation with the obesity rate in Argentina.
Obesity is a significant health problem due to its increasing prevalence and impact on health. Social networks have proven to be a valid source for studying population health-related phenomena. This study aimed to evaluate the spatial distribution of food indicators constructed from food-re...
| Autores principales: | , , , , , , |
|---|---|
| Formato: | Artículo revista |
| Lenguaje: | Español |
| Publicado: |
Universidad Nacional Córdoba. Facultad de Ciencias Médicas. Secretaria de Ciencia y Tecnología
2023
|
| Materias: | |
| Acceso en línea: | https://revistas.unc.edu.ar/index.php/med/article/view/42655 |
| Aporte de: |
| id |
I10-R327-article-42655 |
|---|---|
| record_format |
ojs |
| institution |
Universidad Nacional de Córdoba |
| institution_str |
I-10 |
| repository_str |
R-327 |
| container_title_str |
Revista de la Facultad de Ciencias Médicas de Córdoba |
| language |
Español |
| format |
Artículo revista |
| topic |
obesity social networks food Obesidad Redes sociales Alimentos |
| spellingShingle |
obesity social networks food Obesidad Redes sociales Alimentos Haluszka, E Díaz Oroz , EB Pastore, AC Peralta Sparacino, V Zonghetti, R Aballay, LR Niclis , C Geographical variation of food discourse on Twitter and its correlation with the obesity rate in Argentina. |
| topic_facet |
obesity social networks food Obesidad Redes sociales Alimentos |
| author |
Haluszka, E Díaz Oroz , EB Pastore, AC Peralta Sparacino, V Zonghetti, R Aballay, LR Niclis , C |
| author_facet |
Haluszka, E Díaz Oroz , EB Pastore, AC Peralta Sparacino, V Zonghetti, R Aballay, LR Niclis , C |
| author_sort |
Haluszka, E |
| title |
Geographical variation of food discourse on Twitter and its correlation with the obesity rate in Argentina. |
| title_short |
Geographical variation of food discourse on Twitter and its correlation with the obesity rate in Argentina. |
| title_full |
Geographical variation of food discourse on Twitter and its correlation with the obesity rate in Argentina. |
| title_fullStr |
Geographical variation of food discourse on Twitter and its correlation with the obesity rate in Argentina. |
| title_full_unstemmed |
Geographical variation of food discourse on Twitter and its correlation with the obesity rate in Argentina. |
| title_sort |
geographical variation of food discourse on twitter and its correlation with the obesity rate in argentina. |
| description |
Obesity is a significant health problem due to its increasing prevalence and impact on health. Social networks have proven to be a valid source for studying population health-related phenomena. This study aimed to evaluate the spatial distribution of food indicators constructed from food-related content posted on the social network Twitter and to compare it with the geographical variation at a provincial level of the prevalence of obesity in the adult population of Argentina.
An ecological study was conducted using the data from the 2018 National Risk Factor Survey (to calculate weighted obesity prevalence rates) and 6023548 geo-referenced tweets collected during 2021-2022. Food indicators (rate of tweets with food-related content, frequency of mention of food and food groups, and nutrient density index (NDI, the higher the value, the better the nutritional quality of the food mentioned) were constructed from the tweets for each province. Maps were produced and the correlation between food indicators and the prevalence of total obesity, by sex and age group, at the provincial level was estimated. In addition, the Moran Autocorrelation Index was calculated to detect spatial patterns of the variables studied.
The distribution of obesity prevalence, food tweet rate and NDI showed a non-random spatial distribution (p<0.05). The frequency of mention of some foods considered 'healthy' (cucumber, grapefruit, orange, mushroom, artichoke, tuna, beef, strawberry) was inversely correlated with the prevalence of obesity at the provincial level, while the mention of some foods considered 'unhealthy' (sweetbread, semi-hard cheese, chocolate, black pudding, hamburgers, candy) was positively correlated. In some cases, these results varied by gender and age group. Finally, higher food mentions in tweets were associated with better average NDI at the provincial level (p=0.04).
Twitter speeches could serve as a proxy indicator of dietary habits and their analysis would be useful for studying unfavourable health indicators at the population level. |
| publisher |
Universidad Nacional Córdoba. Facultad de Ciencias Médicas. Secretaria de Ciencia y Tecnología |
| publishDate |
2023 |
| url |
https://revistas.unc.edu.ar/index.php/med/article/view/42655 |
| work_keys_str_mv |
AT haluszkae geographicalvariationoffooddiscourseontwitteranditscorrelationwiththeobesityrateinargentina AT diazorozeb geographicalvariationoffooddiscourseontwitteranditscorrelationwiththeobesityrateinargentina AT pastoreac geographicalvariationoffooddiscourseontwitteranditscorrelationwiththeobesityrateinargentina AT peraltasparacinov geographicalvariationoffooddiscourseontwitteranditscorrelationwiththeobesityrateinargentina AT zonghettir geographicalvariationoffooddiscourseontwitteranditscorrelationwiththeobesityrateinargentina AT aballaylr geographicalvariationoffooddiscourseontwitteranditscorrelationwiththeobesityrateinargentina AT niclisc geographicalvariationoffooddiscourseontwitteranditscorrelationwiththeobesityrateinargentina AT haluszkae variaciongeograficadelosdiscursossobrealimentacionentwitterysucorrelacionconlatasadeobesidadenargentina AT diazorozeb variaciongeograficadelosdiscursossobrealimentacionentwitterysucorrelacionconlatasadeobesidadenargentina AT pastoreac variaciongeograficadelosdiscursossobrealimentacionentwitterysucorrelacionconlatasadeobesidadenargentina AT peraltasparacinov variaciongeograficadelosdiscursossobrealimentacionentwitterysucorrelacionconlatasadeobesidadenargentina AT zonghettir variaciongeograficadelosdiscursossobrealimentacionentwitterysucorrelacionconlatasadeobesidadenargentina AT aballaylr variaciongeograficadelosdiscursossobrealimentacionentwitterysucorrelacionconlatasadeobesidadenargentina AT niclisc variaciongeograficadelosdiscursossobrealimentacionentwitterysucorrelacionconlatasadeobesidadenargentina |
| first_indexed |
2024-09-03T21:04:42Z |
| last_indexed |
2024-09-03T21:04:42Z |
| _version_ |
1809210390605725696 |
| spelling |
I10-R327-article-426552023-10-19T21:20:19Z Geographical variation of food discourse on Twitter and its correlation with the obesity rate in Argentina. Variación geográfica de los discursos sobre alimentación en Twitter y su correlación con la tasa de obesidad en Argentina Haluszka, E Díaz Oroz , EB Pastore, AC Peralta Sparacino, V Zonghetti, R Aballay, LR Niclis , C obesity Twitter social networks food Obesidad Twitter Redes sociales Alimentos Obesity is a significant health problem due to its increasing prevalence and impact on health. Social networks have proven to be a valid source for studying population health-related phenomena. This study aimed to evaluate the spatial distribution of food indicators constructed from food-related content posted on the social network Twitter and to compare it with the geographical variation at a provincial level of the prevalence of obesity in the adult population of Argentina. An ecological study was conducted using the data from the 2018 National Risk Factor Survey (to calculate weighted obesity prevalence rates) and 6023548 geo-referenced tweets collected during 2021-2022. Food indicators (rate of tweets with food-related content, frequency of mention of food and food groups, and nutrient density index (NDI, the higher the value, the better the nutritional quality of the food mentioned) were constructed from the tweets for each province. Maps were produced and the correlation between food indicators and the prevalence of total obesity, by sex and age group, at the provincial level was estimated. In addition, the Moran Autocorrelation Index was calculated to detect spatial patterns of the variables studied. The distribution of obesity prevalence, food tweet rate and NDI showed a non-random spatial distribution (p<0.05). The frequency of mention of some foods considered 'healthy' (cucumber, grapefruit, orange, mushroom, artichoke, tuna, beef, strawberry) was inversely correlated with the prevalence of obesity at the provincial level, while the mention of some foods considered 'unhealthy' (sweetbread, semi-hard cheese, chocolate, black pudding, hamburgers, candy) was positively correlated. In some cases, these results varied by gender and age group. Finally, higher food mentions in tweets were associated with better average NDI at the provincial level (p=0.04). Twitter speeches could serve as a proxy indicator of dietary habits and their analysis would be useful for studying unfavourable health indicators at the population level. La obesidad representa un problema sanitario de gran relevancia debido a su creciente prevalencia y su impacto en la salud. Las redes sociales han demostrado ser una fuente válida de información para el estudio de fenómenos relacionados con la salud de las poblaciones. El objetivo de este trabajo fue evaluar la distribución espacial de indicadores alimentarios construidos a partir del contenido relacionado a alimentos publicado en la red social Twitter y compararla con la variación geográfica a nivel provincial de la prevalencia de obesidad en la población adulta argentina. Se realizó un estudio ecológico, utilizando datos de la Encuesta Nacional de Factores de Riesgo 2018 (para calcular tasas de prevalencia de obesidad ponderadas) y 6023548 de tweets georreferenciados recolectados durante 2021-2022. A partir de los tweets se construyeron indicadores alimentarios (tasa de tweets con contenidos relacionados a alimentos, frecuencia de mención de alimentos y grupos de alimentos, e índice de densidad de nutrientes -IDN, a mayor valor, mejor calidad nutricional de los alimentos mencionados-) para cada provincia. Se elaboraron mapas y se estimó la correlación entre los indicadores alimentarios y la prevalencia de obesidad total, por sexo y grupo etario, a nivel provincial. Además, se calculó el Índice de autocorrelación de Moran, para detectar patrones espaciales de las variables estudiadas. La distribución de la prevalencia de obesidad, la tasa de tweets alimentarios y el IDN, presentaron una distribución espacial no aleatoria (p<0,05). La frecuencia de mención de algunos alimentos considerados ‘saludables’ (pepino, pomelo, naranja, champiñón, alcaucil, atún, carne de vaca, frutilla) se correlacionó inversamente con la prevalencia de obesidad a nivel provincial, mientras que la mención de algunos alimentos considerados ‘poco saludables’ (molleja, queso semiduro, chocolate, morcilla, hamburguesas, golosinas) presentaron una correlación positiva. En algunos casos, estos resultados variaron según sexo y grupo etario. Por último, una mayor mención de alimentos en tweets, se asoció con mejor IDN promedio a nivel provincial (p=0,04). Los discursos en Twitter, podrían servir como indicador proxy de hábitos alimentarios y su análisis sería de utilidad para el estudio de indicadores de salud desfavorables a nivel poblacional. Universidad Nacional Córdoba. Facultad de Ciencias Médicas. Secretaria de Ciencia y Tecnología 2023-10-19 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unc.edu.ar/index.php/med/article/view/42655 Revista de la Facultad de Ciencias Médicas de Córdoba.; Vol. 80 (2023): Suplemento JIC XXIV Revista de la Facultad de Ciencias Médicas de Córdoba; Vol. 80 (2023): Suplemento JIC XXIV Revista da Faculdade de Ciências Médicas de Córdoba; v. 80 (2023): Suplemento JIC XXIV 1853-0605 0014-6722 spa https://revistas.unc.edu.ar/index.php/med/article/view/42655/42856 Derechos de autor 2023 Universidad Nacional de Córdoba http://creativecommons.org/licenses/by-nc/4.0 |