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Alotaibi, M.; Pai, R.R.; Alathur, S.; Chetty, N.; Alhmiedat, T.; Aborokbah, M.; Albalawi, U.; Marie, A.; Bushnag, A.; Kumar, V. Association between Obesity and COVID-19. Encyclopedia. Available online: https://encyclopedia.pub/entry/48492 (accessed on 01 July 2024).
Alotaibi M, Pai RR, Alathur S, Chetty N, Alhmiedat T, Aborokbah M, et al. Association between Obesity and COVID-19. Encyclopedia. Available at: https://encyclopedia.pub/entry/48492. Accessed July 01, 2024.
Alotaibi, Mohammed, Rajesh R. Pai, Sreejith Alathur, Naganna Chetty, Tareq Alhmiedat, Majed Aborokbah, Umar Albalawi, Ashraf Marie, Anas Bushnag, Vishal Kumar. "Association between Obesity and COVID-19" Encyclopedia, https://encyclopedia.pub/entry/48492 (accessed July 01, 2024).
Alotaibi, M., Pai, R.R., Alathur, S., Chetty, N., Alhmiedat, T., Aborokbah, M., Albalawi, U., Marie, A., Bushnag, A., & Kumar, V. (2023, August 25). Association between Obesity and COVID-19. In Encyclopedia. https://encyclopedia.pub/entry/48492
Alotaibi, Mohammed, et al. "Association between Obesity and COVID-19." Encyclopedia. Web. 25 August, 2023.
Association between Obesity and COVID-19
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This entry is adapted from the peer-reviewed paper 10.3390/info14080448

The adoption of emerging technologies in healthcare systems plays a crucial part in anti-obesity initiatives. COVID-19 has intensified the Body Mass Index (BMI) discourses in AI (Artificial Intelligence)-powered social media. However, few studies have reported on the influence of digital content on obesity prevention policies. Understanding the nature and forums of obese metaphors in social media is the first step in policy intervention. 

obesity COVID-19 Twitter social media

1. Introduction

Obesity has become one of the most common chronic diseases in the last two decades as people’s lifestyles have changed worldwide. Obesity is measured using the BMI value, which considers an individual’s mass (weight) and height. The BMI is defined as “the body mass divided by the square of the body height and is universally expressed in units of kg/m2, resulting from mass in kilograms and height in meters” [1].
According to the World Health Organization (WHO) over 1.9 billion people aged 18 and above are overweight, with Asia contributing to around half of all overweight children [2]. Obesity affects over 650 million of these, and approximately 41 million children under the age of five are obese worldwide [2]. In 2016, Obesity Atlas reported that 33.4 percent of females and 24.1 percent of males were overweight or obese [3]. Furthermore, the obesity rate is also very high in some developing countries. For example, for children between the ages of 4 and 8, the prevalence of overweight and obesity in Saudi Arabia is approximately19.2 percent [3].
COVID-19 affects people with poor immune systems more than healthier people [4]. Several studies have found a link between obesity and other chronic conditions such as diabetes and hypertension [5][6][7]. According to these studies, obese children have a higher risk of developing diabetes at a young age. Modern lifestyle, eating habits and less physical activity contributes to obesity especially in children [8]. This implies the necessity of efforts to reduce obesity rates, particularly among children, by raising awareness in the early stages of their lives. As a result, modern technologies such as the Internet of Things, mobile health and social robotics offers excellent and cost-effective solutions to enhance societal understanding.
Modern technologies, intelligent mobile devices, robotics and social networks and the internet has accelerated the design and delivery of healthcare systems, aiding in managing and understanding chronic diseases like obesity and diabetes. This technological revolution established new virtual world with multilingual social networks allowing users to communicate with friends or individuals across geographical, political or economic boundaries. About 3.6 billion internet users use social networks, and these figures are expected to rise as mobile devices and social networks gain attraction [9].
AI technology uses large amounts of raw data as a new area of development and a valuable source of information about people’s perceptions of political decisions or elections. Big data is a concept that describes the massive amount of structured and unstructured information that regularly floods a company [10]. In general, social networks are the most popular sources of big data. The attributes can be collected for each tweet, resulting in a massive volume of data in a short period, with the stream of data increasing sharply second by second. AI technologies help to analyze big data and they assist business decision-makers or governments with forming a picture about the population’s opinions on a social, political or economic issue. The use of natural language processing to analyze healthcare data is prevalent [11]. Twitter data could be analyzed using deep learning techniques [12].

2. Impact of Obesity on Those with COVID-19

Researchers reviewed the literature on the impact of obesity on an individual in terms of worsening the COVID-19 pandemic situation. Existing studies have shown that being obese increases the risks of respiratory diseases [13]. The experience with H1N1 influenza revealed that patients with obesity need utmost care in order to control H1N1 flu and similar diseases [14]. Table 1 shows the impact of overweight and obesity on people with the COVID-19 virus.
Table 1. The impact of obesity on COVID-19-associated risks.
Authors Purpose Methodology Outcome Remarks
Popkin et al. (2020) [15] To identify the link between obesity and COVID-19 risk of infection and the medical consequences of infection Meta-analysis of literature on COVID-19 in Chinese and English languages Individuals with obesity are more prone to COVID-19 infection, hospitalization, requiring intensive care, and mortality Obesity increases the risks of COVID-19
Busetto et al. (2020) [16] To evaluate the relationship between the severity of COVID-19 infection and obesity The statistical analysis method is used on hospitalized COVID-19 patients with different age groups and obesity Overweight and obese patients suffering from COVID-19 requires the facilities of ventilation and the intensive care unit than the normal-weight patients Obesity increases the severity of COVID-19 in patients
Gao et al. (2020) [17] To understand whether obesity is a risk factor for COVID-19 severity or not Statistical analysis of hospitalized COVID-19 patients (75 with obesity and 75 without obesity) Obese individuals were classified as severe COVID-19 patients Obesity increases the severity of COVID-19 in patients
Cai et al. (2020) [13] To understand the association between obesity and severity of COVID-19 Statistical analysis was applied to data of consecutively hospitalized COVID-19 patients The severity of COVID-19 in overweight patients was greater than in normal-weight patients
The severity of COVID-19 in obese patients was greater than in overweight patients		 Obesity increases the severity of COVID-19 patients
Nakeshbandi et al. (2020) [18] To illustrate the association between obesity and COVID-19 A retrospective cohort study on hospitalized COVID-19 patients Overweight and obese people had a higher mortality risk than normal-weight people.
Overweight and obese people were more likely to require intubation than normal-weight people.
Obesity raises the risk of mortality in males		 Obesity increases COVID-19′s associated risks
Nagy et al. (2023) [19] To understand the impact of obesity on COVID-19 patients Observational study on hospitalized COVID-19 infected Obesity is found as the most significant risk factor for COVID-19 patients Obesity increases COVID-19′s associated risks
Guo et al. (2023) [20] To identify the impact of obesity on respiratory tract immunity for COVID-19 infected Examined the ventilated COVID-19 infected patients with obese and non-obese The strength of the nasal immune cells of obese children is reduced Blunted tissue immune responses in obese patients
People with obesity are more vulnerable to the consequences of COVID-19. The mortality rate of obese patients with COVID-19 was greater than that of those who had COVID-19 but were not obese [15]. COVID-19 attacks irrespective of the age of the target but its impact is most severe in older, overweight, and obese people than in young and normal-weight individuals [16][17]. COVID-19 also attacks irrespective of gender, but the mortality risks are greater for male patients than for female patients [18].

3. Impact of COVID-19 on Development of Obesity

The COVID-19 pandemic spread to most of the world by March 2020. The association between COVID-19 and obesity is not restricted to BMI but is rather a complex relationship with different levels of obesity [21]. Quarantine, isolation, lockdown, and border sealing are the standard measures adopted to contain the COVID-19 pandemic by the governing authorities of an individual nation. The COVID-19 control measures change an individual’s lifestyle and eating habits and this can lead to overweight and obesity [22]. The availability of processed food lacking in nutrients was prevalent at the beginning of the pandemic as transportation and other facilities were blocked due to lockdowns in different counties [15][23]. High levels of consumption of non-nutrients and processed food could increase the risks of overweight and obesity [16][23]. Table 2 shows the relationship between COVID-19 and obesity development.
Table 2. The impact of COVID-19 on obesity.
Authors Purpose Results
Abbas et al. (2020) [24] To understand the mutual effects between COVID-19 and obesity Obesity increased during the COVID-19 pandemic.
Obesity is riskier for COVID-19 patients
Mattioli et al. (2020) [22] To understand how the COVID-19 pandemic affected the risk of becoming obese COVID-19 control measures induced stress, anxiety and anger.
Stress changes lifestyle and results in obesity
Stavridou et al. (2021) [25] To evaluate obesity among people of different ages during the COVID-19 pandemic The emergence of COVID-19 disrupted the activities of individuals.
Increased food intake and reduced physical work are leading to obesity
Dohet et al. (2021) [23] To understand obesity during the COVID-19 pandemic COVID-19-induced lockdown resulted in changes in lifestyle, mental health, and weight, leading to obesity
The COVID-19 control measures, such as lockdowns, disrupted individuals’ activities [25]. This disruption of normal activities induced stress, anxiety, anger, and depression. Stress makes individuals eat more and it reduces physical activity, leading to increased overweight and obesity [22][24]. Specifically, the lockdowns resulted in lifestyle changes, mental health issues, and increased weight and obesity in people [21]. In general, the COVID-19 pandemic is increasing obesity by disturbing the normal activities of people.

References

  1. Ferrera, L. Focus on Body Mass Index and Health Research; Nova Science Publishers: New York, NY, USA, 2006.
  2. WHO. World Health Organization. 2021. Available online: http://www.who.int/home (accessed on 3 August 2023).
  3. Worldobesity. World Obesity Federation|Data. 2018. Available online: https://www.worldobesity.org/data/ (accessed on 21 May 2018).
  4. Chetty, N.; Alathur, S.; Kumar, V. 2019-nCoV disease control and rehabilitation: Insights from twitter analytics. In Proceedings of the 2020 5th International Conference on Computing, Communication and Security (ICCCS), Patna, India, 14–16 October 2020; pp. 1–4.
  5. Nguyen, N.; Nguyen, X.; Lane, J.; Wang, P. Relationship between Obesity and Diabetes in a US Adult Population: Findings from the National Health and Nutrition Examination Survey, 1999–2006. Obes. Surg. 2010, 21, 351–355.
  6. Eckel, R.; Kahn, S.; Ferrannini, E.; Goldfine, A.; Nathan, D.; Schwartz, M.; Smith, R.; Smith, S. Obesity and Type 2 Diabetes: What Can Be Unified and What Needs to Be Individualized? Diabetes Care 2011, 34, 424–1430.
  7. Rossner, S. Obesity and type 2 diabetes. Pract. Diabetes Int. 2001, 18, 263–264.
  8. Al Dhaifallah, A.; Mwanri, L.; Aljoudi, A. Childhood obesity in Saudi Arabia: Opportunities and challenges. Saudi J. Obes. 2015, 3, 2–7.
  9. Statista. Most Used Social Media 2020. Statista. 2020. Available online: https://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/ (accessed on 1 November 2020).
  10. Buyya, R. Big Data; Morgan Kaufmann Publisher: Burlington, VT, Canada, 2016.
  11. Elbattah, M.; Arnaud, É.; Gignon, M.; Dequen, G. The Role of Text Analytics in Healthcare: A Review of Recent Developments and Applications. Healthinf 2021, 5, 825–832.
  12. Ainapure, B.S.; Pise, R.N.; Reddy, P.; Appasani, B.; Srinivasulu, A.; Khan, M.S.; Bizon, N. Sentiment Analysis of COVID-19 Tweets Using Deep Learning and Lexicon-Based Approaches. Sustainability 2023, 15, 2573.
  13. Cai, Q.; Chen, F.; Wang, T.; Luo, F.; Liu, X.; Wu, Q.; He, Q.; Wang, Z.; Liu, Y.; Liu, L.; et al. Obesity and COVID-19 severity in a designated hospital in Shenzhen, China. Diabetes Care 2020, 43, 1392–1398.
  14. Dietz, W.; Santos-Burgoa, C. Obesity and its implications for COVID-19 mortality. Obesity 2020, 28, 1005.
  15. Popkin, B.M.; Du, S.; Green, W.D.; Beck, M.A.; Algaith, T.; Herbst, C.H.; Alsukait, R.F.; Alluhidan, M.; Alazemi, N.; Shekar, M. Individuals with obesity and COVID-19: A global perspective on the epidemiology and biological relationships. Obes. Rev. 2020, 21, e13128.
  16. Busetto, L.; Bettini, S.; Fabris, R.; Serra, R.; Pra, C.D.; Maffei, P.; Rossato, M.; Fioretto, P.; Vettor, R. Obesity and COVID-19: An Italian snapshot. Obesity 2020, 28, 1600–1605.
  17. Gao, F.; Zheng, K.I.; Wang, X.-B.; Sun, Q.-F.; Pan, K.-H.; Wang, T.-Y.; Chen, Y.-P.; Targher, G.; Byrne, C.D.; George, J.; et al. Obesity is a risk factor for greater COVID-19 severity. Diabetes Care 2020, 43, e72–e74.
  18. Nakeshbandi, M.; Maini, R.; Daniel, P.; Rosengarten, S.; Parmar, P.; Wilson, C.; Kim, J.M.; Oommen, A.; Mecklenburg, M.; Salvani, J.; et al. The impact of obesity on COVID-19 complications: A retrospective cohort study. Int. J. Obes. 2020, 44, 1832–1837.
  19. Nagy, É.; Cseh, V.; Barcs, I.; Ludwig, E. The Impact of Comorbidities and Obesity on the Severity and Outcome of COVID-19 in Hospitalized Patients—A Retrospective Study in a Hungarian Hospital. Int. J. Environ. Res. Public Health 2023, 20, 1372.
  20. Guo, S.A.; Bowyer, G.S.; Ferdinand, J.R.; Maes, M.; Tuong, Z.K.; Gillman, E.; Liao, M.; Lindeboom, R.G.H.; Yoshida, M.; Worlock, K.; et al. Obesity is associated with attenuated tissue immunity in COVID-19. Am. J. Respir. Crit. Care Med. 2023, 207, 566–576.
  21. Dohet, F.; Loap, S.; Menzel, A.; Iddir, M.; Dadoun, F.; Bohn, T.; Samouda, H. Obesity considerations during the COVID-19 outbreak. Int. J. Vitam. Nutr. Res. 2021.
  22. Mattioli, A.V.; Pinti, M.; Farinetti, A.; Nasi, M. Obesity risk during collective quarantine for the COVID-19 epidemic. Obes. Med. 2020, 20, 100263.
  23. Pries, A.M.; Ferguson, E.L.; Sharma, N.; Upadhyay, A.; Filteau, S. Exploratory analysis of nutritional quality and metrics of snack consumption among Nepali children during the complementary feeding period. Nutrients 2019, 11, 2962.
  24. Abbas, A.M.; Fathy, S.K.; Fawzy, A.T.; Salem, A.S.; Shawky, M.S. The mutual effects of COVID-19 and obesity. Obes. Med. 2020, 19, 100250.
  25. Stavridou, A.; Kapsali, E.; Panagouli, E.; Thirios, A.; Polychronis, K.; Bacopoulou, F.; Psaltopoulou, T.; Tsolia, M.; Sergentanis, T.N.; Tsitsika, A. Obesity in Children and Adolescents during COVID-19 Pandemic. Children 2021, 8, 135.
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Subjects: Health Care Sciences & Services
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Mohammed Alotaibi
,
Rajesh R. Pai
,
Sreejith Alathur
,
Naganna Chetty
,
Tareq Alhmiedat
,
Majed Aborokbah
,
Umar Albalawi
,
Ashraf Marie
,
Anas Bushnag
,
Vishal Kumar
View Times: 181
Revisions: 2 times (View History)
Update Date: 28 Aug 2023
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