Research Article
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Can Online Dietitian Be a Novel Trend of Post-Pandemic Era in Turkey?

Year 2022, Volume 13, Issue 3, 415 - 422, 01.07.2022
https://doi.org/10.31067/acusaglik.1038338

Abstract

Purpose: The aim of this study was to investigate weight management-related Google search trends in Turkey prompted by the pandemic. Methods: Keywords were “diet”, “dietitian”, “body mass index”, “exercise”, “calorie”, “weight gain”, “healthy nutrition”, “weight loss”, “fat burning”, “slimming”, “online diet” and “online dietitian”. Data collection and time series analysis were completed using the 4.1.0 version of the R Studio program and its gtrendsR, ggplot2, prophet, dplyr, forecast and ggforce packages. SPSS software version 17 was used for statistical analysis of keyword relative search volumes (RSVs) during the prepandemic, early pandemic and late pandemic periods. Results: The RSV of “dietitian” keyword was significantly higher in the late pandemic period than in the early pandemic period (p< 0.05). “Exercise” and “online diet” keywords had significantly higher RSVs in the early pandemic period than in the prepandemic period (p< 0.05). The search queries for “healthy nutrition” were significantly lower in the late pandemic period than in the prepandemic period (p< 0.05). According to the search volume for the previous 10 years, the predicted search trends of “body mass index”, “exercise”, “healthy nutrition”, “online diet” and “online dietitian” tended to increase depending on the seasonal search profile. Conclusion: A large increase in actual and predicted search queries of “online dietitian” can provide some cues about public tendencies in the postpandemic era in Turkey. Some guidelines, including web-based communication competencies in dietitian-patient relationships and follow-ups of the diet on the online platform, should be published for the postpandemic period by authorities.

References

  • https://covid19.saglik.gov.tr/TR-66935/genel-koronavirus-tablosu.html
  • https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Overweight_and_obesity_-_BMI_statistics
  • Abdelaal M, Roux CW le, Docherty NG. Morbidity and mortality associated with obesity. Ann Transl Med 2017;5. https://doi.org/10.21037/ATM.2017.03.107.
  • Zhou Y, Chi J, Lv W, Wang Y. Obesity and diabetes as high‐risk factors for severe coronavirus disease 2019 (COVID‐19). Diabetes Metab Res Rev 2021;37. https://doi.org/10.1002/DMRR.3377.
  • Chang TH, Chou CC, Chang LY. Effect of obesity and body mass index on coronavirus disease 2019 severity: A systematic review and meta-analysis. Obes Rev 2020;21:e13089–e13089. https://doi.org/10.1111/OBR.13089.
  • Cornejo-Pareja IM, Gómez-Pérez AM, Fernández-García JC, Millan RBS, Luque AA, Hollanda A de, et al. Coronavirus disease 2019 (COVID-19) and obesity. Impact of obesity and its main comorbidities in the evolution of the disease. Eur Eat Disord Rev 2020;28:799–815. https://doi.org/10.1002/ERV.2770.
  • Rychter AM, Zawada A, Ratajczak AE, Dobrowolska A, Krela‐Kaźmierczak I. Should patients with obesity be more afraid of COVID‐19? Obes Rev 2020;21. https://doi.org/10.1111/OBR.13083.
  • Walker MD, Sulyok M. Online behavioural patterns for Coronavirus disease 2019 (COVID-19) in the United Kingdom. Epidemiol Infect 2020;148. https://doi.org/10.1017/S0950268820001193.
  • McCarthy AD, McGoldrick D. Analyzing Public Interest in Metabolic Health-Related Search Terms During COVID-19 Using Google Trends. Cureus 2021;13. https://doi.org/10.7759/CUREUS.15715.
  • Mayasari NR, Ho DKN, Lundy DJ, Skalny A V., Tinkov AA, Teng I-C, et al. Impacts of the COVID-19 Pandemic on Food Security and Diet-Related Lifestyle Behaviors: An Analytical Study of Google Trends-Based Query Volumes. Nutr 2020;12:3103. https://doi.org/10.3390/NU12103103.
  • Ngoc HN, Kriengsinyos W. Impacts of COVID-19 Pandemic and Its Lockdown on Global Eating Behavior: A Google Trends Analysis 2020. https://doi.org/10.20944/PREPRINTS202012.0701.V1.
  • https://trends.google.com. Accession Date: 1 June 2021.
  • Nuti SV, Wayda B, Ranasinghe I, Wang S, Dreyer RP, Chen SI, et al. The Use of Google Trends in Health Care Research : A Systematic Review. PLoS One 2014;9:49. https://doi.org/10.1371/journal.pone.0109583.
  • Massicotte P, Eddelbuettel D. (2021). Package gtrendsR. Version 1.4.8. https://cran.r-project.org/web/packages/gtrendsR/gtrendsR.pdf
  • Wickham H, Chang W, Henry L, Pedersen TL, Takahashi K, Wilke C et al. (2021). Package ggplot2. Version 3.3.5. https://cran.r-project.org/web/packages/ggplot2/ggplot2.pdf
  • Taylor S, Letham B. (2021). Package prophet. Version 1.0. https://cran.r-project.org/web/packages/prophet/prophet.pdf
  • Wickham H, François R, Henry L, Müller K. (2021). Package dplyr. Version 1.0.7. https://cran.r-project.org/web/packages/dplyr/dplyr.pdf
  • Hyndman R, Athanasopoulos G, Bergmeir C, Caceres G, Chhay L, O’Hara-Wild M. et al. (2021). Package forecast. Version 8.15. https://cran.r-project.org/web/packages/forecast/forecast.pdf
  • Pedersen TL. (2021). Package ggforce. Version 0.3.3. https://cran.r-project.org/web/packages/ggforce/ggforce.pdf .
  • Kandula S, Hsu D, Shaman J. Subregional Nowcasts of Seasonal Influenza Using Search Trends. J Med Internet Res 2017;19:e7486. https://doi.org/10.2196/JMIR.7486.
  • He M, Xu J, Sun Z, Wang S, Zhu L, Wang X, et al. Comparison and evaluation of the efficacy of compressed SENSE (CS) and gradient- and spin-echo (GRASE) in breath-hold (BH) magnetic resonance cholangiopancreatography (MRCP). J Magn Reson Imaging 2020;51:824–32. https://doi.org/10.1002/jmri.26863.
  • Donnelly R, Keller H. Challenges Providing Nutrition Care during the COVID-19 Pandemic: Canadian Dietitian Perspectives. J Nutr Heal Aging 2021 255 2021;25:710–1. https://doi.org/10.1007/S12603-020-1585-Z.
  • Naja F, Hamadeh R. Nutrition amid the COVID-19 pandemic: a multi-level framework for action. Eur J Clin Nutr 2020 748 2020;74:1117–21. https://doi.org/10.1038/s41430-020-0634-3.
  • Kutlu N, Ekin M, Alav A, Ceylan Z, Meral R. Covıd-19 Pandemi Sürecinde Bireylerin Beslenme Alışkanlığında Meydana Gelen Değişimin Belirlenmesi Üzerine Bir Araştırma. Int J Soc Polit Econ Res 2021;8:173–87. https://doi.org/10.46291/IJOSPERVOL8ISS1PP173-187.
  • Özden G, Parlar Kiliç S. The Effect of Social Isolation during COVID-19 Pandemic on Nutrition and Exercise Behaviors of Nursing Students. Ecol Food Nutr 2021. https://doi.org/10.1080/03670244.2021.1875456.
  • Lim MA, Pranata R. Sports activities during any pandemic lockdown. Irish J Med Sci (1971 -) 2020 1901. 2020;190:447–51. https://doi.org/10.1007/S11845-020-02300-9.
  • Freyne J, Saunders I, Brindal E, Berkovsky S, Smith G. Factors associated with persistent participation in an online diet intervention. 30th ACM Conference on Human Factors in Computing Systems (CHI '12) 2012:2375–80. https://doi.org/10.1145/2212776.2223805.
  • Beleigoli A, Andrade AQ, Diniz MDF, Ribeiro AL. Personalized Web-Based Weight Loss Behavior Change Program With and Without Dietitian Online Coaching for Adults With Overweight and Obesity: Randomized Controlled Trial. J Med Internet Res 2020;22(11)E17494 Https//WwwJmirOrg/2020/11/E17494 2020;22:e17494. https://doi.org/10.2196/17494.

Year 2022, Volume 13, Issue 3, 415 - 422, 01.07.2022
https://doi.org/10.31067/acusaglik.1038338

Abstract

References

  • https://covid19.saglik.gov.tr/TR-66935/genel-koronavirus-tablosu.html
  • https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Overweight_and_obesity_-_BMI_statistics
  • Abdelaal M, Roux CW le, Docherty NG. Morbidity and mortality associated with obesity. Ann Transl Med 2017;5. https://doi.org/10.21037/ATM.2017.03.107.
  • Zhou Y, Chi J, Lv W, Wang Y. Obesity and diabetes as high‐risk factors for severe coronavirus disease 2019 (COVID‐19). Diabetes Metab Res Rev 2021;37. https://doi.org/10.1002/DMRR.3377.
  • Chang TH, Chou CC, Chang LY. Effect of obesity and body mass index on coronavirus disease 2019 severity: A systematic review and meta-analysis. Obes Rev 2020;21:e13089–e13089. https://doi.org/10.1111/OBR.13089.
  • Cornejo-Pareja IM, Gómez-Pérez AM, Fernández-García JC, Millan RBS, Luque AA, Hollanda A de, et al. Coronavirus disease 2019 (COVID-19) and obesity. Impact of obesity and its main comorbidities in the evolution of the disease. Eur Eat Disord Rev 2020;28:799–815. https://doi.org/10.1002/ERV.2770.
  • Rychter AM, Zawada A, Ratajczak AE, Dobrowolska A, Krela‐Kaźmierczak I. Should patients with obesity be more afraid of COVID‐19? Obes Rev 2020;21. https://doi.org/10.1111/OBR.13083.
  • Walker MD, Sulyok M. Online behavioural patterns for Coronavirus disease 2019 (COVID-19) in the United Kingdom. Epidemiol Infect 2020;148. https://doi.org/10.1017/S0950268820001193.
  • McCarthy AD, McGoldrick D. Analyzing Public Interest in Metabolic Health-Related Search Terms During COVID-19 Using Google Trends. Cureus 2021;13. https://doi.org/10.7759/CUREUS.15715.
  • Mayasari NR, Ho DKN, Lundy DJ, Skalny A V., Tinkov AA, Teng I-C, et al. Impacts of the COVID-19 Pandemic on Food Security and Diet-Related Lifestyle Behaviors: An Analytical Study of Google Trends-Based Query Volumes. Nutr 2020;12:3103. https://doi.org/10.3390/NU12103103.
  • Ngoc HN, Kriengsinyos W. Impacts of COVID-19 Pandemic and Its Lockdown on Global Eating Behavior: A Google Trends Analysis 2020. https://doi.org/10.20944/PREPRINTS202012.0701.V1.
  • https://trends.google.com. Accession Date: 1 June 2021.
  • Nuti SV, Wayda B, Ranasinghe I, Wang S, Dreyer RP, Chen SI, et al. The Use of Google Trends in Health Care Research : A Systematic Review. PLoS One 2014;9:49. https://doi.org/10.1371/journal.pone.0109583.
  • Massicotte P, Eddelbuettel D. (2021). Package gtrendsR. Version 1.4.8. https://cran.r-project.org/web/packages/gtrendsR/gtrendsR.pdf
  • Wickham H, Chang W, Henry L, Pedersen TL, Takahashi K, Wilke C et al. (2021). Package ggplot2. Version 3.3.5. https://cran.r-project.org/web/packages/ggplot2/ggplot2.pdf
  • Taylor S, Letham B. (2021). Package prophet. Version 1.0. https://cran.r-project.org/web/packages/prophet/prophet.pdf
  • Wickham H, François R, Henry L, Müller K. (2021). Package dplyr. Version 1.0.7. https://cran.r-project.org/web/packages/dplyr/dplyr.pdf
  • Hyndman R, Athanasopoulos G, Bergmeir C, Caceres G, Chhay L, O’Hara-Wild M. et al. (2021). Package forecast. Version 8.15. https://cran.r-project.org/web/packages/forecast/forecast.pdf
  • Pedersen TL. (2021). Package ggforce. Version 0.3.3. https://cran.r-project.org/web/packages/ggforce/ggforce.pdf .
  • Kandula S, Hsu D, Shaman J. Subregional Nowcasts of Seasonal Influenza Using Search Trends. J Med Internet Res 2017;19:e7486. https://doi.org/10.2196/JMIR.7486.
  • He M, Xu J, Sun Z, Wang S, Zhu L, Wang X, et al. Comparison and evaluation of the efficacy of compressed SENSE (CS) and gradient- and spin-echo (GRASE) in breath-hold (BH) magnetic resonance cholangiopancreatography (MRCP). J Magn Reson Imaging 2020;51:824–32. https://doi.org/10.1002/jmri.26863.
  • Donnelly R, Keller H. Challenges Providing Nutrition Care during the COVID-19 Pandemic: Canadian Dietitian Perspectives. J Nutr Heal Aging 2021 255 2021;25:710–1. https://doi.org/10.1007/S12603-020-1585-Z.
  • Naja F, Hamadeh R. Nutrition amid the COVID-19 pandemic: a multi-level framework for action. Eur J Clin Nutr 2020 748 2020;74:1117–21. https://doi.org/10.1038/s41430-020-0634-3.
  • Kutlu N, Ekin M, Alav A, Ceylan Z, Meral R. Covıd-19 Pandemi Sürecinde Bireylerin Beslenme Alışkanlığında Meydana Gelen Değişimin Belirlenmesi Üzerine Bir Araştırma. Int J Soc Polit Econ Res 2021;8:173–87. https://doi.org/10.46291/IJOSPERVOL8ISS1PP173-187.
  • Özden G, Parlar Kiliç S. The Effect of Social Isolation during COVID-19 Pandemic on Nutrition and Exercise Behaviors of Nursing Students. Ecol Food Nutr 2021. https://doi.org/10.1080/03670244.2021.1875456.
  • Lim MA, Pranata R. Sports activities during any pandemic lockdown. Irish J Med Sci (1971 -) 2020 1901. 2020;190:447–51. https://doi.org/10.1007/S11845-020-02300-9.
  • Freyne J, Saunders I, Brindal E, Berkovsky S, Smith G. Factors associated with persistent participation in an online diet intervention. 30th ACM Conference on Human Factors in Computing Systems (CHI '12) 2012:2375–80. https://doi.org/10.1145/2212776.2223805.
  • Beleigoli A, Andrade AQ, Diniz MDF, Ribeiro AL. Personalized Web-Based Weight Loss Behavior Change Program With and Without Dietitian Online Coaching for Adults With Overweight and Obesity: Randomized Controlled Trial. J Med Internet Res 2020;22(11)E17494 Https//WwwJmirOrg/2020/11/E17494 2020;22:e17494. https://doi.org/10.2196/17494.

Details

Primary Language English
Subjects Health Care Sciences and Services, Nutrition and Dietetics
Journal Section Research Article
Authors

Elif GÜNALAN> (Primary Author)
İSTANBUL SAĞLIK VE TEKNOLOJİ ÜNİVERSİTESİ
0000-0002-3644-5066
Türkiye


Özge ÇONAK>
ISTANBUL GELISIM UNIVERSITY, ACADEMY OF HEALTH SCIENCES, DEPARTMENT OF HEALTH MANAGEMENT
0000-0001-5381-4022
Türkiye

Publication Date July 1, 2022
Application Date December 20, 2021
Acceptance Date March 19, 2022
Published in Issue Year 2022, Volume 13, Issue 3

Cite

EndNote %0 Acıbadem Üniversitesi Sağlık Bilimleri Dergisi Can Online Dietitian Be a Novel Trend of Post-Pandemic Era in Turkey? %A Elif Günalan , Özge Çonak %T Can Online Dietitian Be a Novel Trend of Post-Pandemic Era in Turkey? %D 2022 %J Acıbadem Üniversitesi Sağlık Bilimleri Dergisi %P 1309-470X-1309-5994 %V 13 %N 3 %R doi: 10.31067/acusaglik.1038338 %U 10.31067/acusaglik.1038338