Nutritional knowledge and immunity-boosting food consumption patterns before and after the COVID-19 pandemic lockdown periods in Osun State, Nigeria

Folorunso, A A; Olu-Lawal, Fareedah; Omoniyi, Saheed

doi:10.1177/02601060221122153

Cited by 2 publications

(5 citation statements)

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“…As previous studies showed, an increase in the nutrition knowledge level is related to an increase in the consumption of essential food groups, such as grains, dairy, meats, beans, and so on ( 54 , 55 ). Especially during the COVID-19 pandemic, nutritional knowledge was significantly associated with the consumption of healthy foods to ensure a robust immune system ( 56 ). A healthy eating project in Poland suggested that increasing individuals’ nutrition knowledge was an important target to improve their lifestyles and dietary quality throughout the whole lifespan ( 57 ).…”

Section: Discussionmentioning

confidence: 99%

Deep neural network for prediction of diet quality among doctors and nurses in North China during the COVID-19 pandemic

Wang,

Chu,

et al. 2023

Front. Public Health

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ObjectiveThe COVID-19 pandemic has placed unprecedented pressure on front-line healthcare workers, leading to poor health status, especially diet quality. This study aimed to develop a diet quality prediction model and determine the predictive effects of personality traits, socioeconomic status, lifestyles, and individual and working conditions on diet quality among doctors and nurses during the COVID-19 pandemic.MethodsA total of 5,013 doctors and nurses from thirty-nine COVID-19 designated hospitals provided valid responses in north China in 2022. Participants’ data related to social-demographic characteristics, lifestyles, sleep quality, personality traits, burnout, work-related conflicts, and diet quality were collected with questionnaires. Deep Neural Network (DNN) was applied to develop a diet quality prediction model among doctors and nurses during the COVID-19 pandemic.ResultsThe mean score of diet quality was 46.14 ± 15.08; specifically, the mean scores for variety, adequacy, moderation, and overall balance were 14.33 ± 3.65, 17.99 ± 5.73, 9.41 ± 7.33, and 4.41 ± 2.98, respectively. The current study developed a DNN model with a 21–30–28-1 network framework for diet quality prediction. The DNN model achieved high prediction efficacy, and values of R2, MAE, MSE, and RMSE were 0.928, 0.048, 0.004, and 0.065, respectively. Among doctors and nurses in north China, the top five predictors in the diet quality prediction model were BMI, poor sleep quality, work–family conflict, negative emotional eating, and nutrition knowledge.ConclusionDuring the COVID-19 pandemic, poor diet quality is prevalent among doctors and nurses in north China. Machine learning models can provide an automated identification mechanism for the prediction of diet quality. This study suggests that integrated interventions can be a promising approach to improving diet quality among doctors and nurses, particularly weight management, sleep quality improvement, work-family balance, decreased emotional eating, and increased nutrition knowledge.

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Section: Discussionmentioning

confidence: 99%

Deep neural network for prediction of diet quality among doctors and nurses in North China during the COVID-19 pandemic

Wang,

Chu,

et al. 2023

Front. Public Health

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“…Many studies suggest that the pandemic affected negatively food consumption patterns and diets, especially during the period of lockdown [48,53]. However, other studies posit that attention to health and healthy diets, especially those presumed to boost the immune system, increased during the pandemic [59,60,67,72]. Further studies deal with food (in)security during the pandemic [66,94,112].…”

Section: Agriculture Subsectors and Food Chain Stagesmentioning

confidence: 99%

“…This, as well as the reduction in physical activity/exercise especially during the lockdown [53], caused an increase in the prevalence of non-communicable diseases. However, there was, at the same time, an increase in attention to and interest in health [59,60,72]. For that, some scholars suggest that the pandemic improved nutritional knowledge [59,120].…”

Section: Impacts On Food Security and Nutritionmentioning

confidence: 99%

“…However, there was, at the same time, an increase in attention to and interest in health [59,60,72]. For that, some scholars suggest that the pandemic improved nutritional knowledge [59,120]. Saah et al [120] found that "Health knowledge has improved due to COVID-19 in terms of access to health information and increased understanding of health issues.…”

Section: Impacts On Food Security and Nutritionmentioning

confidence: 99%

“…Davis et al [95] Mali (1) Adjognon et al [83] Nigeria (31) Abay et al [79]; Adebayo and Oluwamayowa [80]; Adenubi et al [81]; Adewopo et al [82]; Agbawodikeizu et al [84]; Amare et al [86]; Balana et al [48]; Bamidele and Amole [91]; Bamidele et al [49]; Bamiwuye et al [55]; Chiemela et al [92]; Ekoh et al [101]; Folayan et al [102]; Folayan et al [58]; Folorunso et al [59]; Igwe et al [130]; Iheme et al [61]; Ilesanmi et al [106]; Inegbedion [107]; Lamontagne et al [63]; Liverpool-Tasie et al [111]; Obayelu et al [117] Agyei et al [85]-Benin, Botswana, Burkina Faso, Burundi, Cabo Verde, Cameroon, Chad, DRC, Ethiopia, Ghana, Guinea, Ivory Coast, Liberia, Malawi, Mali, Mauritania, Morocco, Namibia, Niger, Nigeria, Rwanda, Senegal, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, Togo, Tunisia, Uganda, Zambia, and Zimbabwe; Andrieu et al [87]-Burkina Faso, Colombia, and France; Dasgupta and Robinson [57]-Armenia, Cambodia, Chad, Djibouti, Ethiopia, Kenya, Malawi, Mali, Nigeria, South Africa, and Uganda; de Boef et al [96]-Ethiopia, Myanmar, Nigeria, and Uganda; Gligorić et al [60]-Australia, Brazil, Canada, Denmark, Egypt, France, Germany, Italy, Indonesia, India, Japan, Kenya, Mexico, Nigeria, Sweden, Spain, United Kingdom, and the United States; Kasim et al [110]-Guyana and Nigeria; Wrabel et al [78]-Bangladesh, DRC, Ethiopia, India, Jordan, Kenya, Malawi, Myanmar, Nepal, Nigeria, Pakistan, Philippines, Somalia, South Sudan, Tanzania, Uganda and Yemen; Egger et al [100]-Bangladesh, Burkina Faso, Colombia, Ghana, Kenya, Nepal, Philippines, Rwanda and Sierra Leone; Mertens and Peñalvo…”

Section: Liberia (1)mentioning

confidence: 99%

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Impacts of the COVID-19 Pandemic on Agri-Food Systems in West Africa

El Bilali,

Dambo,

Nanema

et al. 2023

Sustainability

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A growing body of evidence suggests that the COVID-19 pandemic affected not only the functioning of food supply chains but also the performance and outcomes of agri-food systems. In this context, this paper analyses the scholarly literature dealing with the impacts of the pandemic on West African agriculture and food systems. A search carried out on the Web of Science in March 2023 returned 176 records and 87 eligible documents were included in the systematic review. The bibliometric analysis suggests a decreasing interest in the research field. Moreover, a large share of the eligible articles are authored by researchers based outside West Africa. There is a research gap, especially in Cabo Verde, Ivory Coast, Gambia, Guinea, Guinea-Bissau, Mauritania, Niger and Togo. Studies focus on the crop production subsector and consumption stage. The pandemic affected all four dimensions/pillars of food security (viz. availability, access, utilisation/use, and stability). However, most of the analysed documents focus on food access (economic accessibility and physical accessibility). Moreover, COVID-19 affected all the dimensions of agri-food systems (viz. environmental, economic, social, and political) but the analysed articles focus on the pandemic’s socio-economic impacts, especially those relating to food security and health. The promotion of research on the impacts of the pandemic on agri-food systems in West Africa is paramount to designing the evidence-based policies needed to improve the preparedness of the region for current and future crises and shocks.

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Nutritional knowledge and immunity-boosting food consumption patterns before and after the COVID-19 pandemic lockdown periods in Osun State, Nigeria

Cited by 2 publications

References 5 publications

Deep neural network for prediction of diet quality among doctors and nurses in North China during the COVID-19 pandemic

Deep neural network for prediction of diet quality among doctors and nurses in North China during the COVID-19 pandemic

Impacts of the COVID-19 Pandemic on Agri-Food Systems in West Africa

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