| Literature DB >> 33053656 |
Noor Rohmah Mayasari1, Dang Khanh Ngan Ho1, David J Lundy2, Anatoly V Skalny3, Alexey A Tinkov3,4, I-Chun Teng1, Meng-Chieh Wu1, Amelia Faradina1, Afrah Zaki Mahdi Mohammed1, Ji Min Park1, Yi Jing Ngu1, Sabrina Aliné1, Naila Maya Shofia5, Jung-Su Chang1,6,7,8.
Abstract
The severe acute respiratory syndrome coronavirus (SARS-CoV)-2 disease (COVID)-19 is having profound effects on the global economy and food trade. Limited data are available on how this pandemic is affecting our dietary and lifestyle-related behaviors at the global level. Google Trends was used to obtain worldwide relative search volumes (RSVs) covering a timeframe from before the COVID-19 pandemic 1 June 2019 to 27 April 2020. Spearman's rank-order correlation coefficients were used to measure relationships between daily confirmed cases and aforementioned RSVs between 31 December 2019 and 15 April 2020. RSV curves showed increased interest in multiple keywords related to dietary and lifestyle behaviors during the COVID-19 lockdown period in March and April 2020. Spearman's correlation analysis showed that the strongest variables in each keyword category were (1) food security (food shortage: r = 0.749, food bank: r = 0.660, and free food: r = 0.555; all p < 0.001), (2) dietary behaviors (delivery: r = 0.780, restaurant: r = -0.731, take-away: r = 0.731, and food-delivery: r = 0.693; all p < 0.001), (3) outdoor-related behaviors (resort: r = -0.922, hotel: r = -0.913, cinema: r = -0.844, park: r = -0.827, fitness: r = -0.817, gym: r = -0.811; plant: r = 0.749, sunbathing: r = 0.668, and online: r = 0.670; all p < 0.001), and (4) immune-related nutrients/herbs/foods (vitamin C: r = 0.802, vitamin A: r = 0.780, zinc: r = 0.781, immune: r = 0.739, vitamin E: r = 0.707, garlic: r = 0.667, omega-3 fatty acid: r = -0.633, vitamin D: r = 0.549, and turmeric: r = 0.545; all p < 0.001). Restricted movement has affected peoples' dietary and lifestyle behaviors as people tend to search for immune-boosting nutrients/herbs and have replaced outdoor activities with sedentary indoor behaviors.Entities:
Keywords: COVID-19; Google Trends; diet; food security; lifestyle behavior; nutrition
Mesh:
Substances:
Year: 2020 PMID: 33053656 PMCID: PMC7601866 DOI: 10.3390/nu12103103
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
Figure 1Global trend curves and heat map for nutrient and herb-related search terms. (A) Global trend curves for coronavirus-related search terms, cumulative confirmed coronavirus cases, (B) food insecurity RSV curves. (C–F) Indicates food insecurity interest heat map covering from 31 December 2019 to 25 April 2020: (C) Food bank, (D) Free food, (E) Free meal, (F) Food shortage. (C–F) The left line indicates the top five searched countries and the right line indicated the top five rising queries related search term. RSV: relative search volumes.
Figure 2Global trend curves for dietary and lifestyle behavior-related search terms from 1 June 2019 to 27 April 2020. (A) Dietary behavior, (B) Lifestyle: indoor behavior, (C,D) Lifestyle: outdoor behavior. RSV: relative search volumes.
Figure 3Global trend curves and heat map for nutrient and herb-related search terms. (A, B) RSV curves for nutrient and herb-related search terms. (C–H) Indicates nutrient and herb-related search terms interest heat map covering from 31 December 2019 to 25 April 2020: (C) Vitamin C, (D) Vitamin D, (E) Zinc, (F) Garlic, (G) Turmeric, (H) Herb. (C–H) The left line indicates the top five searched countries and the right line indicated the top five rising queries related search term. RSV: relative search volumes.
Figure 4Global network correlations between daily conformed COVID-19 cases and diet-related lifestyle behavior search terms. The size of the nodes represents the strength of the correlation between the daily confirmed COVID-19 cases and diet-related lifestyle behavior search terms denoted as relative search volumes (RSVs). Each path represents a correlation, and the wider and less transparent the path, the stronger the correlation between the two variables. Blue indicates a positive correlation, while red represents a negative correlation.
Spearman’s correlation coefficients of dietary and lifestyle behavior-related search terms and daily confirmed COVID-19 cases, cumulative COVID-19 cases, and coronavirus Google Trends search terms, 31 December 2019 to 25 April 2020.
| Search Query | Spearman’s Correlation | |||||
|---|---|---|---|---|---|---|
| COVID-19 | COVID-19 | “Coronavirus” Google Trend Search Volume | ||||
| r | r | r | ||||
| Food security | ||||||
| Food bank | 0.679 | <0.001 | 0.674 | <0.001 | 0.625 | <0.001 |
| Free food | 0.583 | <0.001 | 0.564 | <0.001 | 0.437 | <0.001 |
| Free meal | 0.347 | <0.001 | 0.327 | 0.000 | 0.183 | 0.048 |
| Food shortage | 0.768 | <0.001 | 0.828 | <0.001 | 0.885 | <0.001 |
| Dietary behavior | ||||||
| Restaurant | −0.733 | <0.001 | −0.776 | <0.001 | −0.744 | <0.001 |
| Delivery | 0.770 | <0.001 | 0.714 | <0.001 | 0.642 | <0.001 |
| Food delivery | 0.686 | <0.001 | 0.662 | <0.001 | 0.602 | <0.001 |
| Take away | 0.726 | <0.001 | 0.727 | <0.001 | 0.639 | <0.001 |
| Lifestyle: indoor behavior | ||||||
| Recipe | 0.591 | <0.001 | 0.573 | <0.001 | 0.398 | <0.001 |
| Cuisine | 0.314 | 0.001 | 0.303 | 0.001 | −0.032 | 0.734 |
| Cake | 0.514 | <0.001 | 0.478 | <0.001 | 0.169 | 0.068 |
| Netflix | 0.585 | <0.001 | 0.553 | <0.001 | 0.504 | <0.001 |
| Nintendo | 0.570 | <0.001 | 0.567 | <0.001 | 0.481 | <0.001 |
| Lifestyle: outdoor behavior | ||||||
| Cinema | −0.844 | <0.001 | −0.883 | <0.001 | −0.780 | <0.001 |
| Hotel | −0.913 | <0.001 | −0.943 | <0.001 | −0.864 | <0.001 |
| Resort | −0.922 | <0.001 | −0.937 | <0.001 | −0.878 | <0.001 |
| Park | −0.827 | <0.001 | −0.820 | <0.001 | −0.768 | <0.001 |
| Gym | −0.811 | <0.001 | −0.832 | <0.001 | −0.610 | <0.001 |
| Exercise | 0.599 | <0.001 | 0.622 | <0.001 | 0.376 | <0.001 |
| Outdoor | 0.575 | <0.001 | 0.611 | <0.001 | 0.355 | <0.001 |
| Workout | 0.540 | <0.001 | 0.551 | <0.001 | 0.394 | <0.001 |
| Yoga | 0.309 | 0.001 | 0.289 | 0.002 | 0.151 | 0.105 |
| Sunbathing | 0.668 | <0.001 | 0.649 | <0.001 | 0.513 | <0.001 |
| Cycling | 0.194 | 0.036 | 0.255 | 0.006 | −0.095 | 0.310 |
| Fitness | −0.817 | <0.001 | −0.838 | <0.001 | −0.608 | <0.001 |
| Aerobics | 0.050 | 0.592 | 0.038 | 0.688 | −0.174 | 0.060 |
| Plant | 0.749 | <0.001 | 0.844 | <0.001 | 0.567 | <0.001 |
| Flower | 0.581 | <0.001 | 0.567 | <0.001 | 0.185 | 0.045 |
| Immune-related nutrients/herbs | ||||||
| Vitamins | 0.752 | <0.001 | 0.800 | <0.001 | 0.913 | <0.001 |
| Vitamin A | 0.780 | <0.001 | 0.813 | <0.001 | 0.741 | <0.001 |
| Vitamin B | 0.707 | <0.001 | 0.745 | <0.001 | 0.644 | <0.001 |
| Vitamin C | 0.802 | <0.001 | 0.827 | <0.001 | 0.957 | <0.001 |
| Vitamin D | 0.549 | <0.001 | 0.594 | <0.001 | 0.705 | <0.001 |
| Vitamin E | −0.102 | 0.276 | −0.004 | 0.966 | −0.044 | 0.637 |
| Zinc | 0.781 | <0.001 | 0.817 | <0.001 | 0.857 | <0.001 |
| Iron | 0.175 | 0.060 | 0.198 | 0.032 | −0.110 | 0.239 |
| Selenium | −0.205 | 0.027 | −0.162 | 0.081 | −0.194 | 0.036 |
| Omega 3 | −0.633 | <0.001 | −0.598 | <0.001 | −0.594 | <0.001 |
| Turmeric | 0.545 | <0.001 | 0.573 | <0.001 | 0.409 | <0.001 |
| Garlic | 0.667 | <0.001 | 0.654 | <0.001 | 0.472 | <0.001 |
| Ginger | 0.484 | <0.001 | 0.487 | <0.001 | 0.350 | <0.001 |
| Onion | 0.471 | <0.001 | 0.435 | <0.001 | 0.209 | 0.024 |
| Herbs | 0.480 | <0.001 | 0.537 | <0.001 | 0.264 | 0.004 |