| Literature DB >> 34967842 |
Cristiana Mignogna1, Simona Costanzo2, Anwal Ghulam1, Chiara Cerletti2, Maria Benedetta Donati2, Giovanni de Gaetano2, Licia Iacoviello1,2, Marialaura Bonaccio2.
Abstract
The lockdowns resulting from the first wave of the COVID-19 pandemic impacted deeply on all life activities, including diet. We performed a systematic review to investigate changes in food intake, eating behaviours and diet quality during lockdown as compared to before. A literature search was performed using three electronic databases from inception until June 13, 2021. Observational studies evaluating changes in general populations during the COVID-19 pandemic lockdown were eligible. Out of 1,963 studies achieved from the search strategy, 95 met inclusion criteria (85 on adults, 10 on children/adolescents), and the majority were of high quality (72.6%). Most of the studies were web-based surveys using convenience sampling, mainly focused on variations in the consumption of foods and eating behaviours during lockdown, whereas only 15 studies analysed diet quality through dietary indices. On the basis of the definition of a healthful diet as reflected by a traditional Mediterranean diet, an increase in recommended foods such as fruit and vegetables, legumes, cereals and olive oil was observed, although a sharp decrease in fish intake and an increase in dairy products were documented. Accordingly, a reduction in foods that should be eaten less frequently was reported, namely, red and processed meat. However, a higher consumption of unhealthy foods (e.g., snacks and sweets) was also observed. Results indicated improved diet quality in Europe, especially among Mediterranean countries, with the exception of France, while a switching to poor nutrient patterns was observed in Colombia and Saudi Arabia. Analyses of eating behaviours suggest an increase in food intake, number of daily meals and snacking. In conclusion, changes in intake of major food groups, apart from fish intake, were in line with the definition of a traditional Mediterranean diet, indicating a consistent moderate improvement of dietary habits worldwide. This review protocol was registered at https://www.crd.york.ac.uk/prospero/ as CRD42020225292.Entities:
Keywords: COVID-19; confinement; diet quality; dietary changes; eating behaviours; lockdown; pandemic
Year: 2021 PMID: 34967842 PMCID: PMC8755350 DOI: 10.1093/advances/nmab130
Source DB: PubMed Journal: Adv Nutr ISSN: 2161-8313 Impact factor: 8.701
FIGURE 1PRISMA flow diagram of the search procedure. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.
FIGURE 2Percentages of high-quality and peer-reviewed observational studies from general adult populations reporting increased/decreased/unchanged consumption of food groups and beverages during the lockdown following the first wave of the COVID-19 outbreak as compared to before (corresponding number on the related bars). COVID-19, coronavirus disease 2019.
Main findings of included observational studies from general adult populations evaluating changes in consumption of foods and beverages during the lockdown resulting from the first wave of the COVID-19 outbreak[1]
| Main findings | ||||
|---|---|---|---|---|
| First author, year (ref) | Country | Increased | Decreased | Authors’ interpretation |
| European studies | ||||
| Sánchez-Sánchez et al., 2020 ( | Spain | Olive oil, vegetables, fruits, red and processed meat, butter, margarine and cream, carbonated/sugary beverages, alcoholic drinks and wine, legumes, fish or seafood, industrial bakery, nuts, sofrito | Preference for white meat | Despite an increase in Mediterranean diet adherence, the consumption of “unhealthy” food also increased |
| Sánchez et al., 2021 ( | Spain | Sugar-sweetened and alcoholic beverages, and other snacks (44.4%); bakery products (46.2%); red meat (26.4%) | — | No overarching interpretation provided |
| Rodríguez-Pérez et al., 2020 ( | Spain | — | Alcohol (57.3%), fried food (20.3%), fast food (34.9%) | An improvement in dietary behaviors was observed |
| Romeo-Arroyo et al., 2020 ( | Spain | Fruit, vegetables, sweets, milk and dairy products, meat and processed meat, pasta, and bread | Fish (33%), alcoholic beverages | No overarching interpretation provided |
| López-Moreno et al., 2020 ( | Spain | Fast food (25.6%), fresh food (55.7%), alcoholic beverages (18.3%) | — | Mixed effects |
| Bonaccio et al., 2021 ( | Italy | Pizza (31.2%), biscuits (18%), chocolate (18.6%), bread substitutes (11.8%), fruit yogurt (7.7%), water (17.2%) | Breakfast cereals, cereal bars (5.6%), sweet packaged snacks (12.7%), ready-to-heat potatoes and potato croquettes (9.9%), packaged bread (10.9%), fruit drinks (e.g., nectars) (7.9%), savory packaged snacks (12.5%), fish nuggets and sticks (9.4%), reconstituted meat products (11.1%), ready-to-heat vegetables (11.4%), soft drinks (12.3%), croissants (14.2%), instant sauces (11.4%), plant-based meat substitutes (10.2%), plant-based cheese substitutes (10.4%) | About 40% of our population switched to unfavorable eating as reflected by increased UPF intake |
| Cancello et al., 2020 ( | Italy | Snack/appetizers | — | No overarching interpretation provided |
| Cicero et al., 2021 ( | Italy | Bread and bread-like products, pasta, rice, vegetables, fruit, milk and yogurt, simple sugars and sweets, low-fat meat, cured meats, cheeses, eggs, healthy vegetable oils, mixed seed oils, nuts, coffee, alcoholic drinks, dietary supplements (19.2%) | Fish, mussels and shellfish, legumes | A trend towards decreasing diet quality |
| Di Renzo et al., 2020 ( | Italy | Cereals, legumes, red and white meat, fresh vegetables, dairy products, eggs, hot beverages | Fresh fish, fresh fruit, packaging sweets and baked products, baked products, alcohol, junk food (29.8%) | No overarching interpretation provided |
| Ferrante et al., 2021 ( | Italy | Sweets (45.1%), alcohol (17.3%), vegetables (40.3%), legumes (21.9%) whole grains (15.5%) | Processed meat (24.4%) | A meaningful proportion of respondents reported a worsening of eating habits, especially among women |
| Maffoni et al., 2021 ( | Italy | Fruit and vegetables, sweet/desserts | Water, sandwich/pizza | Negative changes in eating behaviors were documented |
| Prete et al., 2021 ( | Italy | Sweets, cakes and pastry products (51%), bread/pasta/rice (30%), fresh fruit (28%), vegetables (27%) | Dried fruit (73%) | Prolonged lockdown promotes unhealthy lifestyle changes |
| Ruggiero et al., 2021 ( | Italy | Fresh vegetables (26.1%), cereals (25.7) fresh fruits (22.8), olive oil (12.6%) legumes (14.9%), white meat (15.1%), soft (12.5%) and hard cheese (10.7%), water (17.9%) | Fresh/frozen fish (23.2%), reconstituted meat products (6.7%) | Higher intake of foods characterizing a Mediterranean dietary pattern, healthier lifestyle and more sustainable food choices |
| Scarmozzino et al., 2020 ( | Italy | Fresh fruit and vegetables (21.2%), sweet food (42.5%), salty snacks (23.5%), milk/yogurt (14.3%), cheese (13.3%), coffee, tea, infusions (29.8%) | Red and processed meat (14.9%), fresh or canned fish (13,7%), alcohol (36.8%) | No overarching interpretation provided |
| Pfeifer et al., 2021 ( | Croatia | Olive oil (12.4%), vegetables (21.2%), fruit (21.7%), legumes (10.9%), commercial pastries (21.5%), homemade pastries (33.5%) | Red meat (21.9%), soft drinks (25.6%), fish (15.2%), alcohol (27.7%), fast food (54.2%), fried foods (24.1%) | No overarching interpretation provided |
| Mititelu et al., 2021 ( | Romania | Vegetables and fruit (34.2%), meat and meat products (27.1%) | — | Positive changes reflected by increases in homemade food, fruit and vegetables |
| Troka et al., 2021 ( | Albania | Bread (52%), dairy (51%), fruit (73.5%), vegetables (52%), meat (51.1%), sweets (56%), water (70%), homemade baked sweets (65.5%) | — | No overarching interpretation provided |
| Tsigkas et al., 2021 ( | Greece | — | Alcohol (34.3%), junk food (25.5%), snack (18.8%), salt (10.3%) | Significant lifestyle changes |
| Kolokotroni et al., 2021 ( | Cyprus | Fruit, vegetables, olive oil, butter, margarine, or cream, sweet beverages, legumes, fish, milk, yogurt, or cheese, commercial sweets and pastries, nuts, sofrito, caffeinated drinks, infusions/herbal teas | Red meat, whole cereals, alcohol | Though participants reported eating more, their quality of diet did not seem to change |
| Deschasaux-Tanguy et al., 2020 ( | France | Canned vegetables (14.2%), frozen vegetables (14.3%), potatoes (15.3%), legumes (14.5%), cheese (17.8%), sweets and chocolate (21.7%), biscuits and cakes (20.4%), tap water (13%), alcohol (15.4%), tea and herbal tea (19.5%) | Fresh fruit (17.2%), fresh vegetables (17.7%), fish or shellfish (31.3%), fresh red meat (22.4%), sandwiches, pizza and savory pies (17.4%) | The lockdown led, in a substantial part of the population, to unhealthy nutritional behaviors |
| Marty et al., 2020 ( | France | Fruits and vegetables, pulses, whole-grain food, dairy products, fish and seafood, processed meat, sugary food, sugary beverages, alcohol, salt | — | Decrease in the nutritional quality of diet on average, which could be partly explained by changes in food choice motives |
| Constant et al., 2020 ( | France | — | Alcohol (21.1%) | Less than 4 in 10 respondents reported healthy changes over the same period, mostly in relation to better eating habits |
| Rolland et al., 2020 ( | France | Caloric/salty food (28.3%), alcohol (15.4%) | — | Widespread increases in addiction-related habits |
| Steffen et al., 2021 ( | Germany | — | Alcohol (40.2%) | Alcohol consumption was altered in an age-dependent manner |
| Drieskens et al., 2021 ( | Belgium | Sweet or salty snacks (33.2%), sugared-sweetened beverages (9.2%) | Alcohol (17.7%) | No overarching interpretation provided |
| Vandevijvere et al., 2020 ( | Belgium | Fruit and vegetables (15.2% and 11.9%), sweet and salty snacks (33.4%), sugared soft drinks (8.8%) | — | No overarching interpretation provided |
| Błaszczyk-Bębenek et al., 2020 ( | Poland | Salty snacks (31.4%), eggs potatoes, sweets, canned meat, alcohol | Fast food, instant soups, energy drinks | Nutrition behavior did not change during lockdown, nor did it increase the proportion of healthy products in the diet |
| Dobrowolski et al., 2021 ( | Poland | Sweetened and confectionery products (36.2%), fast food and salty snacks (32.4%), alcohol (26.6%) | — | Increase in the consumption of total food and products with high energy density. |
| Drywień et al., 2020 ( | Poland | Whole-grain products, low-fat meat and/or egg, pulses, milk and milk products, confectionary, homemade pastry, ice cream and pudding, alcohol, water | Fruit, fish and seafood, processed meat, fast food, commercial pastry, energy drinks | No overarching interpretation provided |
| Górnicka et al., 2020 ( | Poland | Whole-grain products, low-fat meat and/or egg, pulses, milk and milk products, confectionary, homemade pastry, alcohol, water | Fruit, fish and seafood, processed meat, fast food, commercial pastry, ice cream and pudding, sugar-sweetened beverages, energy drinks | Positive and negative on dietary–lifestyle changes |
| Kowalczuk et al., 2021 ( | Poland | Cereals, fruit, vegetable fats, dairy products, eggs, meat, animal fats, dietary supplements, sweets, water, alcohol | Potatoes, juice, fish, sugar, snacks, soft drinks | No overarching interpretation provided |
| Sidor et al., 2020 ( | Poland | Alcohol (14.6%) | — | A significant percentage of individuals can experience modification of dietary habits, manifested by eating and snacking more |
| Giacalone et al., 2020 ( | Denmark | Commercial and homemade pastries (21.1% and 38.1%), fish (15.8%), alcohol (30.3%), carbonated beverages (21.4%) | Fruit (24.9%), vegetables (19.5%), legumes (9.9%), fast food (25.4%), fried food (17.7%) red meat (12.3%) | Dietary changes during the lockdown reflected pre-existing (un)healthy eating habits |
| Kriaucioniene et al., 2020 ( | Lithuania | Vegetables (18.8%), fruits (22.1%), fried food (20.6%), homemade pastries (37.7%) | Fast food (41.3%), fish and seafood (14.3%), carbonated and sugary drinks (19.4%), commercial pastries (26%), red meat (17.9%), alcohol (15.9%) | Both positive and negative changes in nutrition |
| Poelman et al., 2020 ( | The Netherlands | Sweets and snacks (22.1%) | — | Persistence of dietary routines |
| Buckland et al., 2020 ( | United Kingdom | Fruit (48%), vegetables (49%), high-energy-dense sweet and savory foods (28%) | — | Eating behavior traits that increase susceptibility to increased intake of high-energy-dense sweet and savory foods were observed |
| Coulthard et al., 2021 ( | United Kingdom | High-energy-dense snack foods, fruit and vegetables, alcohol | — | No overarching interpretation provided |
| Robinson et al., 2020 ( | United Kingdom | — | Alcohol (30%) | No overarching interpretation provided |
| Ingram et al., 2020 ( | Scotland | Alcohol (35.4%) | — | No overarching interpretation provided |
| North American studies | ||||
| Lamarche et al., 2021 ( | Canada | Whole grains, greens and beans, refined grains, total vegetables, total dairy, seafood and plant proteins, added sugar, total proteins | Whole fruits, sodium, fatty acids | Improved overall diet quality |
| Bin Zarah et al., 2020 ( | USA | Sweets (43.8%), salty snacks (37.4%) water (35.4%), coffee or tea (31.1%), white rice or pasta (26.8%), alcoholic beverages (23.9% and 15.6%), breakfast cereals (22.3%), potatoes (22.2%), starchy vegetables (21.6%), red and processed meat (20.4% and 20.0%), white bread (19.0%), margarine or butter (16.5%), fruit and vegetable juices (11.7% and 5.3%), sugary beverages (10.6%) | Fruit (33.4%), eggs, chicken, or turkey (31%), nonstarchy vegetables (28.2%), dairy (21.6%), fish and shellfish (16.6%), nut butter (26.0%), nuts or seeds (25.3%), brown rice or whole-grain pasta (15.1%), whole-grain bread (14.1%), oils (10.7%) | No major variation in dietary patterns aside from increases in the consumption of sweets and salty snacks |
| Chenarides et al., 2020 ( | USA | Fresh products, dairy, grains, frozen and canned food, bottled water | Fast food (48%), meat | Food consumption patterns for major food groups seemed to stay the same for the majority of participants |
| Cummings et al., 2021 ( | USA | Added sugar (14%) | — | Little evidence that US adults ate more added sugars as compared with before the pandemic |
| Zhang et al., 2021 ( | USA | Alcohol (39.5%) | — | No overarching interpretation provided |
| South American studies | ||||
| Christofaro et al., 2021 ( | Brazil | Vegetables (26.6%), fruits (25.9%) fried foods (18.8%), sweets (42.5%) | — | No overarching interpretation provided |
| Malta et al., 2020 ( | Brazil | Sweets, savory snacks, frozen food, alcoholic beverages (17.6%) | Beans, greens, and vegetables | Worsening of lifestyles and increase in health risk behaviors |
| Tebar et al., 2021 ( | Brazil | Sweetened food (42.6%) | — | No overarching interpretation provided |
| Martínez-Vázquez et al., 2021 ( | Mexico | — | Alcoholic beverages (12.1%) | Positive changes in the quality of diet |
| Pertuz-Cruz et al., 2021 ( | Colombia | Water (36.2%), cereals, legumes, eggs, fats, coffee, sugar and sugar cane and its beverages | Fish, nuts, fast food (33.8%), alcohol (18.1%), fruit and vegetables, snacks | Overall trend toward unhealthier diets |
| Ares et al., 2021 ( | Uruguay | Fruit (16.0%), vegetables and pulses (10.0%), rice/flour-based dishes (2.0%), vitamins and minerals (5.0%), water (3.0%), natural juices (2.0%) | Ultra-processed food (3.0%) | Changes related to both an increase and a decrease in the consumption of healthy foods were observed |
| Huancahuire-Vega et al., 2020 ( | Peru | Vegetables, fruit, legumes, dried fruits/nuts, eggs | Bakery products, meat, snacks, refreshment and fast-food | Increase in healthy eating habits |
| Reyes-Olavarría et al., 2020 ( | Chile | Fruit and vegetables (30.9%) | — | No overarching interpretation provided |
| Asian studies | ||||
| Wang et al., 2020 ( | China | Fruit, vegetables, milk products, snacks | — | Mixed effects |
| Yang et al., 2021 ( | China | Staple food (18.8%), animal products (19.1%), vegetables (25.3%), fruits (27.3%), nuts (26.3%), water (27.1%), snacks (38.2%) | Mushroom (19.1%), dairy (21.4%), legumes (25%) | No overarching interpretation provided |
| Zhu et al., 2021 ( | China | Snacks and drinks, fruits, vegetables, egg, livestock/poultry meat, dairy intake, staple food intake, aquatic products, legumes | — | There was an increase in total food intake by 39% of respondents, especially in snacks and drinks |
| Shrestha et al., 2020 ( | Nepal | — | Alcohol drinking (53.6%) | No overarching interpretation provided |
| Chopra et al., 2020 ( | India | Fruits and vegetables, pulses, egg or meat | Fast food, fried food, junk foods (snacks, sugar sweetened beverages), alcohol | COVID-19 marginally improved the eating behavior |
| Singh et al., 2021 ( | India | — | Junk food (73.8%), regular alcohol intake (46.3%) | Positive lifestyle changes |
| Husain et al., 2020 ( | Kuwait | — | Fast food, fish and seafood, Americano coffee, fruit juice | No overarching interpretation provided |
| Alfawaz et al., 2021 ( | Saudi Arabia | Snacks | Fast food, fresh fruits, vegetables | Lockdown impacted on dietary behaviors in an unhealthy way |
| Aljohani, 2020 ( | Saudi Arabia | Coffee (44.8%) | — | No overarching interpretation provided |
| Mumena, 2020 ( | Saudi Arabia | Fruits, savory snacks, sweets, candies | — | No overarching interpretation provided |
| Radwan et al., 2020 ( | United Arab Emirates | Salty snacks (21.3%), sweet snacks (7.1%) | — | Unhealthy lifestyle changes including diet |
| Cheikh Ismail et al., 2020 ( | United Arab Emirates | Water | Fast food, frozen ready-to-eat meals | Unbalanced food choices |
| Galali, 2021 ( | Iraqi Kurdistan | Fruits, vegetables, homemade pizza and sweets, hot beverages, dairy products and yogurt, legumes, white meat | Processed meat, canned fish, alcoholic intake | Despite an increase in Mediterranean diet adherence, the consumption of “unhealthy” food also increased |
| African studies | ||||
| Matsungo et al., 2020 ( | Zimbabwe | Dark-green leafy vegetables (33.72%), alcohol (46.7%) | Other vegetables (48.5%), other fruits (64.9%), nuts and seeds (45.0%), cereals breads and tubers (41.1%), dairy products (44.9%) | Decrease in dietary diversification, disrupted diet and consumption patterns |
| Oceanian studies | ||||
| Gerritsen et al., 2020 ( | New Zealand | Sweet snacks (41.1%), salty snacks (33.2%), white bread and pasta (26.6%), alcohol (32.8%) sugary drinks (19.8%) | Fruit (20.7%), vegetables (13.3%), legumes (25.9%), whole-meal bread and pasta (24.9%) | Overall shift toward an unhealthy dietary pattern |
| Intercontinental studies | ||||
| Abouzid et al., 2021 ( | Middle East and North Africa (MENA) region | Vegetables, fruits, meat, poultry, carbohydrates, dairy products, eggs, snacks, sugars, water intake | Seafood, fast food, dietary supplements | 30.9% reported an improvement in their eating habits compared with 24.8% reported worsening of their eating habits |
| Ammar et al., 2020 ( | Europe, North-Africa, Western Asia and the Americas | Unhealthy food | Alcohol binge drinking | An unhealthy pattern of food consumption was exhibited |
| Cavagnari et al., 2021 ( | Spain and 11 Latin American countries[ | Vegetables, fried foods, and alcoholic beverages (Argentina, Chile, Costa Rica, Spain, and Uruguay); sweetened drinks, pastry products (Guatemala and Paraguay); baked goods (Paraguay, Argentina and Chile); chocolate (Argentina, and Chile); beer (Spain, Paraguay, Chile, Argentina, and Mexico); wine and distillates (Spain, Paraguay, Chile, Argentina, and Mexico) | — | All the Latin American countries showed a change in their consumption patterns toward less healthy diets |
| Cheikh Ismail et al., 2020 ( | Middle East and North Africa (MENA) region | Water | Fast food | Unhealthy lifestyle changes |
| Janssen et al., 2021 ( | Denmark (DK), Germany (DE), and Slovenia (SI) | Sweet snacks, alcoholic drinks (DE, DK) canned food (DE) | Fruit, vegetables, meat (all countries) Fish and bread (DE, SI) Dairy products (DE, DK) | Diverging trends in all food categories analyzed |
| Molina-Montes et al., 2021 ( | 16 European countries[ | Olive oil, fruits, vegetables, legumes | Fast food, fried food, red meat, soft beverages, alcohol, fish, pastry | Improvement in dietary habits among European population as reflected by an increased adherence to the Mediterranean diet |
| Murphy et al., 2020 ( | New Zealand (NZ), USA, Great Britain (GB), and the Island of Ireland (IOI) | Fruit (GB), vegetables (IOI, GB, NZ), saturated fats (IOI, GB, NZ) | — | No overarching interpretation provided |
| Pišot et al., 2020 ( | Bosnia and Herzegovina, Croatia, Greece, Kosovo, Italy, Serbia, Slovakia, Slovenia, and Spain | — | Unhealthy food (35%), alcohol (36%) | No overarching interpretation provided |
| Papandreou et al., 2020 ( | Spain, Greece | Pastries (69.4% Spain; 62.2% Greece), alcohol (81.2% Spain; 78.9% Greece) | — | No overarching interpretation provided |
Percentages indicate the proportion of subjects reporting increases/decreases in the consumption of a given food. COVID-19, coronavirus disease 2019; ref, reference; UPF, ultra-processed food.
Argentina, Chile, Colombia, Costa Rica, Ecuador, Guatemala, Mexico, Peru, Paraguay, Panama, and Uruguay.
Bosnia and Herzegovina, Croatia, Denmark, Germany, Greece, Ireland, Italy, Lithuania, Montenegro, North Macedonia, Poland, Portugal, Serbia, Slovenia, Spain, and Turkey.
FIGURE 3Percentages of high-quality and peer-reviewed observational studies from general adult populations reporting increased/decreased/unchanged eating behaviors during the lockdown following the first wave of the COVID-19 outbreak as compared to before (corresponding number on the related bars). COVID-19, coronavirus disease 2019.
Main findings of included observational studies from general adult populations evaluating changes in eating behaviors during the lockdown resulting from the first wave of the COVID-19 outbreak[1]
| Main findings | ||||
|---|---|---|---|---|
| First author, year (ref) | Country | Increased | Decreased | Authors’ interpretation |
| European studies | ||||
| López-Moreno et al., 2020 ( | Spain | Home cooking (73.5%), daily meals (23%), more efficient preparation of food (64.2%) | Food intake (33.3%) | Mixed effects |
| Rodríguez-Pérez et al., 2020 ( | Spain | Cooking (45.7%), snacking (37.6%) | — | Despite an increase in Mediterranean diet adherence, the consumption of “unhealthy” food also increased |
| Sánchez et al., 2021 ( | Spain | Eating continuously (17.9%), ready-to-eat foods (22%) | — | No overarching interpretation provided |
| Sánchez-Sánchez et al., 2020 ( | Spain | Homemade desserts and pastries | — | An improvement in dietary behaviors was observed |
| Bonaccio et al., 2021 ( | Italy | Home cooking (48.6%), number of daily meals (17.6%) | Pre-prepared meals (11.6%) | About 40% of our population switched to unfavorable eating as reflected by increased UPF intake |
| Cancello et al., 2020 ( | Italy | Food intake (42%), dietary supplements (23%) | — | No overarching interpretation provided |
| Di Renzo et al., 2020 ( | Italy | Homemade food, eating (37.4%) | Delivery food | No overarching interpretation provided |
| Maffoni et al., 2021 ( | Italy | Breakfast | Craving or eating between meals | Negative changes in eating behaviors were documented |
| Scacchi et al., 2021 ( | Italy | Food consumption (43.4%), home cooking (55.1%) | — | The Italian lockdown highly affected food choice behaviors, leading to positive and sustainable habits towards food purchase and consumption |
| Scarmozzino et al., 2020 ( | Italy | Eating more (52.9%) | Ready meals | No overarching interpretation provided |
| Ruggiero et al., 2021 ( | Italy | Home cooking (49.3%), number of daily meals (17.8%) | Pre-prepared meals (12.0%), take-away (12.4%) | Higher intake of foods characterizing a Mediterranean dietary pattern, healthier lifestyle, and more sustainable food choices |
| Pfeifer et al., 2021 ( | Croatia | Home cooking (53.8%), snacking (33.9%) | — | Increased diet quality among those cooking more |
| Mititelu et al., 2021 ( | Romania | Amount of food eaten (25.6%), home cooking (77.5%) | — | Positive changes reflected by increases in homemade food, fruit, and vegetables |
| Kolokotroni et al., 2021 ( | Cyprus | Number of daily meals, conviviality | — | Though participants reported eating more, their quality of diet did not seem to change |
| Deschasaux-Tanguy et al., 2020 ( | France | Cooking (40.4%), snacking (21.1%) | — | The lockdown created an opportunity to improve nutritional behaviors, such as cooking homemade meals, increasing consumption of fresh products, and buying food products from local shop and/or farmers |
| Marty et al., 2020 ( | France | Cooking (83.2%), energy intake | — | Decrease in the nutritional quality of diet, on average, which could be partly explained by changes in food choice motives |
| Constant et al., 2020 ( | France | Snacking (24%) | — | Less than 4 in 10 respondents reported healthy changes over the same period, mostly in relation to better eating habits |
| Drieskens et al., 2021 ( | Belgium | — | Food prepared out-of-home (39.7%) | No overarching interpretation provided |
| Błaszczyk-Bębenek et al., 2020 ( | Poland | 5 meals or more (31.1%), snacking (77.9%) | Eating outside or ordering take-away food (51.6%) | Nutrition behavior does not change during lockdown, nor does it increase the proportion of healthy products in the diet |
| Dobrowolski et al., 2021 ( | Poland | Amount of food eaten (48.4%) | Home delivery and take-away (37.8%) | Increase in the consumption of total food and products with high energy density |
| Drywień et al., 2020 ( | Poland | Eating more (35.7%) Homemade meals | Take-away meals | No overarching interpretation provided |
| Górnicka et al., 2020 ( | Poland | Eating more (34.3%), homemade meals | — | Positive and negative on dietary–lifestyle changes |
| Kowalczuk et al., 2021 ( | Poland | Eating more regularly | Diet diversity | No overarching interpretation provided |
| Sidor et al., 2020 ( | Poland | Eating more (43.5%), snacking (51.8%), cooking (62.3%) | — | A significant percentage of individuals can experience modification of dietary habits, manifested by eating and snacking more |
| Giacalone et al., 2020 ( | Denmark | Cooking (29.9%), eating (42.8%) snacking (41.7%) | — | Dietary changes during the lockdown reflected pre-existing (un)healthy eating habits |
| Kriaucioniene et al., 2020 ( | Lithuania | Eating more (49.4%), snacking (45.1%), home cooking (62.1%) | — | Both positive and negative changes in nutrition |
| Poelman et al., 2020 ( | The Netherlands | Eating more (8.9%), meal delivery services (29.5%) | — | Persistence of dietary routines |
| Buckland et al., 2020 ( | United Kingdom | Food intake (48%), snacking (53%), number of meals (31%) | — | Eating behavior traits that increase susceptibility to increased intake of HED sweet and savory foods were observed |
| Coulthard et al., 2021 ( | United Kingdom | Home-prepared food | — | No overarching interpretation provided |
| Herle et al., 2021 ( | United Kingdom | Amount of food eaten (17.3%) | — | One-third of the sample report changes in quantities eaten throughout the first UK lockdown period |
| Robinson et al., 2020 ( | United Kingdom | Large meals/snacks, snacking, drinking | Dieting/fasting, skipping meals | No overarching interpretation provided |
| Robinsonet al., 2020 ( | United Kingdom | Binged on food (49%) | — | No overarching interpretation provided |
| North American studies | ||||
| Lamarche et al., 2021 ( | Canada | — | Meals consumed outside, lunch consumed outside, snacking | Improved overall diet quality |
| Chenarides et al., 2020 ( | USA | Eating more (21%), snacking (41.9%) | Take-out meals (48%), prepped meals | An overwhelming shift away from consumption away from home (e.g., fast food) to snack food consumption |
| South American studies | ||||
| Martínez-Vázquez et al., 2021 ( | Mexico | Homemade foods (28.4%) | — | Positive changes in the quality of diet |
| Pertuz-Cruz et al., 2021 ( | Colombia | Snacking (48%), amount of food eaten (45%), perishable food (50.2%), expenditure on food (71%), home cooking (59.3%) | — | Transition toward unhealthy diets |
| Reyes-Olavarría et al., 2020 ( | Chile | Home cooking (59.6%), eating more (51.3%) | — | No overarching interpretation provided |
| Ares et al., 2021 ( | Uruguay | Eating more homemade food (8.0%) | — | Changes related to both an increase and a decrease in the consumption of healthy foods were observed |
| Ramos-Padilla et al., 2021 ( | Ecuador | Intake of any food (44%), supplement (41.4%), or beverage (31.6%) | — | No overarching interpretation provided |
| Asian studies | ||||
| Yang et al., 2021 ( | China | — | Breakfast frequency (23.6%), midnight snacking (15.8%) | No overarching interpretation provided |
| Shrestha et al., 2020 ( | Nepal | Quality of diet (67.6%) | Alcohol drinking (53.6%) | No overarching interpretation provided |
| Husain et al., 2020 ( | Kuwait | Late-night snack or meal, freshly made main meal, home cooking, skipping breakfast | Number of meals, main meal from a restaurant | Unhealthy meal patterns were detected |
| Al-Domi et al., 2021 ( | Jordan | Food intake or supplements containing antioxidants (46.0%), breakfast (69.4%), lunch (89.8%), dinner (54.0%) | — | Significant negative changes in healthy nutritional behavior |
| Alhusseini et al., 2020 ( | Saudi Arabia | Home-cooked meals | Take-away or delivered food | No overarching interpretation provided |
| Aljohani, 2020 ( | Saudi Arabia | Food intake (63%), after dinner snacking (47.9%) | — | No overarching interpretation provided |
| Radwan et al., 2020 ( | United Arab Emirates | Food intake (31.8%), cooked food (84.4%) | — | Unhealthy lifestyle changes including diet |
| Cheikh Ismail et al., 2020 ( | United Arab Emirates | Homemade meals, daily meals, breakfast | Frozen ready-to-eat meals, skipping meals, eating outside | Unbalanced food choices |
| Galali, 2021 ( | Iraqi Kurdistan | Home cooking | Delivered food products | An improvement in dietary behaviors was observed |
| Oceanian studies | ||||
| Curtis et al., 2021 ( | Australia | Energy from alcohol | Energy from protein | Small dietary changes were observed |
| Phillipou et al., 2020 ( | Australia | Binge eating (34.6%), food restriction (27.6%) | — | Potential adverse health consequences because of increased binge eating and restricting behaviors |
| Gerritsen et al., 2020 ( | New Zealand | Cooking hot meals, baking | — | Overall shift toward an unhealthy dietary pattern |
| Intercontinental studies | ||||
| Ammar et al., 2020 ( | Europe, North Africa, Western Asia, and the Americas | Snacking, number of meals | Alcohol binge drinking | An unhealthy pattern of food consumption was exhibited |
| Cheikh Ismail et al., 2020 ( | Middle East and North Africa (MENA) region | Daily meals, homemade meals (97.2%), breakfast (71.2%) | Frozen ready-to-eat meals (7.5%), eating outside, skipping meals (45.1%) | Unhealthy lifestyle changes |
| Dou et al., 2021 ( | China and USA | Home cooking, eating more | Ready-to-eat food, delivery food | Better nutrition from increased time spent on meal planning and preparing at home |
| Janssen et al., 2021 ( | Denmark (DK), Germany (DE), and Slovenia (SI) | Ready-made meals (DE, DK) | Ready-made meals (SI) | Diverging trends in all food categories analyzed |
| Molina-Montes et al., 2021 ( | 16 European countries[ | Frequency of cooking and snacking, homemade pastry | — | An increase in overall dietary quality and more engagement in home cooking |
| Murphy et al., 2020 ( | New Zealand, USA, Great Britain (GB), and the Island of Ireland (IOI) | Fresh ingredients for dinner (IOI and GB), baking | Ready-made dinner (not in the USA), take-away | No overarching interpretation provided |
| Pišot et al., 2020 ( | Bosnia and Herzegovina, Croatia, Greece, Kosovo, Italy, Serbia, Slovakia, Slovenia, and Spain | Regular meals (44%), larger meal sizes (29%) | — | No overarching interpretation provided |
| Papandreou et al., 2020 ( | Spain, Greece | Snacking (34.1% Spain; 40.8% Greece) | Amount of food eaten (74.3% Spain; 63.1% Greece) | No overarching interpretation provided |
COVID-19, coronavirus disease 2019; HED, high-energy-dense; ref, reference; UPF, ultra-processed food.
Bosnia and Herzegovina, Croatia, Denmark, Germany, Greece, Ireland, Italy, Lithuania, Montenegro, North Macedonia, Poland, Portugal, Serbia, Slovenia, Spain, and Turkey.
Main findings of included observational studies from general adult populations evaluating changes in overall diet quality during the lockdown resulting from the first wave of the COVID-19 outbreak[1]
| First author, year (ref) | Country | Main findings | Authors’ interpretation |
|---|---|---|---|
| Rodríguez-Pérez et al., 2020 ( | Spain | MEDAS increased from 6.53 ± 2 (before lockdown) to 7.34 ± 1.93 (during lockdown) | Adherence to Mediterranean diet increased significantly during the lockdown |
| Sánchez-Sánchez et al., 2020 ( | Spain | High adherence (MEDAS ≥9) increased from 4.7% (before lockdown) to 8% (during lockdown) | Mediterranean diet adherence slightly increases during lockdown, although consumption of “unhealthy” food also increases |
| Bonaccio et al., 2021 ( | Italy | Average UPF score was −0.28 ± 4.07 | Slight decrease in the consumption of UPF |
| Cicero et al., 2021 ( | Italy | DQI reduced from 42.4 ± 4.1 to 37.8 ± 4.7 | A trend towards decreasing diet quality |
| Ruggiero et al., 2021 ( | Italy | Average MDP score was 0.5 ± 2.2 | A slight improvement in diet quality at a population level during the lockdown |
| Pfeifer et al., 2021 ( | Croatia | MEDAS increased from 5.02 ± 1.97 (before lockdown) to 5.85 ± 2.04 (during lockdown) | Increased diet quality among those cooking more |
| Kolokotroni et al., 2021 ( | Cyprus | MEDAS increased by 1 unit (median 6, IQR 3) during lockdown | Increased adherence to Mediterranean diet (31.9%) |
| Deschasaux-Tanguy et al., 2020 ( | France | AHEI-2010 decreased by 3% during lockdown UPF decreased by 1% during lockdown | The lockdown led, in a substantial part of the population, to unhealthy nutritional behaviours. |
| Marty et al., 2020 ( | France | sPNNS-GS2 decreased from 1.2 ± 2.5 (before lockdown) to 0.8 ± 2.8 (during lockdown) | The lockdown period in France was related to a decrease in nutritional quality of diet, on average |
| Lamarche et al., 2021 ( | Canada | HEI-2015 increased by 1.1 points (95% CI: 0.6, 1.5) | Diet quality has slightly improved during the COVID-19-related early lockdown |
| Pertuz-Cruz et al., 2021 ( | Colombia | Change toward a westernized-like dietary pattern | Transition toward unhealthy diets |
| Martínez-Vázquez et al., 2021 ( | Mexico | Median DQI increased from −1 (before lockdown) to 2 (during lockdown) | DQI was higher during lockdown in all groups |
| Alhusseini et al., 2020 ( | Saudi Arabia | Food-quality score decreased from 16.46 ± 2.84 (before lockdown) to 16.39 ± 2.79 (during lockdown); food quantity score increased from 14.62 ± 2.71 (before lockdown) to 15.70 ± 2.66 (during lockdown) | The quality and the quantity of the food was compromised |
| Ammar et al., 2020 ( | Europe, North Africa, Western Asia, and the Americas | Total diet score 4.4% higher during lockdown than before* | Isolation alters eating behaviors in a health-compromising direction |
| Molina-Montes et al., 2021 ( | 16 European countries[ | MEDAS score increased from 5.23 ± 2.06 (before lockdown) to 6.15 ± 2.06 (during lockdown) | A significantly higher adherence to the Mediterranean diet during the lockdown was observed across all countries |
Values in the main findings’ column are means ± SDs. *Measured through the Short Diet Behaviours Questionnaire for Lockdowns (higher values indicating a decrease in diet quality). AHEI-2010, Alternate Healthy Eating Index–2010 score; COVID-19, coronavirus disease 2019; DQI, Dietary Quality Index; HEI-2015, Healthy Eating Index–2015; MEDAS, PREDIMED (PREvención con DIeta MEDiterránea) Mediterranean Diet Adherence Screener; ref, reference; sPNNS-GS2, Simplified Programme National Nutrition Santé—guidelines score 2; UPF, ultra-processed food.
Bosnia and Herzegovina, Croatia, Denmark, Germany, Greece, Ireland, Italy, Lithuania, Montenegro, North Macedonia, Poland, Portugal, Serbia, Slovenia, Spain, and Turkey.
Main findings of included observational studies from general populations of children and adolescents evaluating changes in diet during the lockdown resulting from the first wave of the COVID-19 outbreak[1]
| Main findings | ||||
|---|---|---|---|---|
| First author, year (ref) | Country | Increased | Decreased | Authors’ interpretation |
| Medrano et al., 2020 ( | Spain | KIDMED increased from 5.9 ± 1.8 to 6.4 ± 1.5 | — | KIDMED score increased, although the prevalence of children with a high adherence to the Mediterranean diet was not significantly improved |
| Aguilar-Martínez et al., 2021 ( | Spain | Fruit, vegetables, cereals, dairy products, eggs, fresh food, number of meals (28.4%), snacking between meals (56.4%), amount of food eaten | Legumes, meat, fish, sweets and pastries (39.3%), convenience foods (49.2%), soft drinks (49.8%), convenience food, packaged food, regularity of meal hours | Changes towards less healthy eating were also related to students’ socioeconomic position |
| Segre et al., 2021 ( | Italy | Amount of food eaten (57.3%); junk food; snacks; sweets | — | Important changes in dietary habits |
| Mastorci et al., 2021 ( | Italy | KIDMED increased from 6.1 ± 2.6 to 6.5 ± 2.5 | — | Increased adherence to the Mediterranean diet |
| Androutsos et al., 2021 ( | Greece | Fruits and fresh fruit juices, vegetables, dairy products, pasta, sweets, total snacks | Fast food | Unfavorable changes in children's and adolescents’ lifestyle behaviors during the first COVID-19 lockdown |
| Philippe et al., 2021 ( | France | Midafternoon snack increased (15%), fruit juice and soda, chips, salty biscuits, candy, chocolate, ice cream, pastries, cake, sweet cookies, cream dessert, milks, yogurt, cheese, quark, fresh and dried fruits, nuts | Compote, fruits in syrup | No overarching interpretation provided |
| Jia et al., 2020 ( | China | Wheat products, other staple foods, preserved vegetables, tea | Rice, meat, poultry, fresh vegetables, fresh fruit, soybean products, dairy products, sugar-sweetened beverages | Compensatory eating patterns deserve further investigation for a full evaluation of the effects of the lockdown on dietary patterns and quality |
| Al Hourani et al., 2021 ( | Jordan | Milk and milk products, cooked and raw vegetables, fruit, bread and grains, carbonated beverages | — | Increased food consumption |
| Bahatheg, 2021 ( | Saudi Arabia, Britain, and Turkey | Fruit, chocolate, sweets, cakes, biscuits, and cupcakes, frozen food (pizza, nuggets, and pies), soft drinks, sweetened juices, juice blends and fruit juice | — | Nutritional system of the Turkish and British children was better than that of Saudi children during the lockdown |
| Ruiz-Roso et al., 2020 ( | Italy, Spain, Brazil, Chile, Colombia | Legumes, vegetables, fruit, fried food, sweet food | Fast food | Overall diet quality did not increase |
Values in the main findings’ column are means ± SDs. COVID-19, coronavirus disease 2019; KIDMED, Mediterranean Diet Quality Index for children and teenagers; ref, reference.
Descriptive characteristics of included observational studies from general populations analyzing changes in food intake, eating behaviors, and diet quality during nationwide lockdowns resulting from the first wave of the COVID-19 pandemic[1]
| First author, year (ref) | Country | Nationwide lockdown timeline (length in days) | Survey period | Study design | Data collection | Dietary assessment | Sample size | Age (mean ± SD), y |
|---|---|---|---|---|---|---|---|---|
| Aguilar-Martínez et al., 2021 ( | Spain | March 14/May 9, 2020 (56) | June–July 2020 | Cross-sectional/retrospective | Web-based survey on DESK cohort participants | Changes by food quantity and frequency of eating behaviors | 303 | 16.4 ± 1.11 |
| López-Moreno et al., 2020 ( | Spain | March 14/May 9, 2020 (56) | May 28–June 21, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 675 | 39.1 ± 12.9 |
| Medrano et al., 2020 ( | Spain | March 14/May 9, 2020 (56) | September–December 2019/March–April 2020 | Longitudinal | Web-based survey | KIDMED | 106 | 12.0 ± 2.6 |
| Rodríguez-Pérez et al., 2020 ( | Spain | March 14/May 9, 2020 (56) | From March 20, 2020, for 3 wk | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown MEDAS (score 0–14) | 7514 | ≥18 |
| Romeo-Arroyo et al., 2020 ( | Spain | March 14/May 9, 2020 (56) | Last week of April 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 600 | 42.6 ± 12.2 |
| Sánchez-Sánchez et al., 2020 ( | Spain | March 14/May 9, 2020 (56) | May 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown MEDAS (score 0–14) | 1065 | 38.7 ± 12.4 |
| Sánchez et al., 2021 ( | Spain | March 14/May 9, 2020 (56) | May 26–June 20, 2020 | Cross-sectional/retrospective | Computer-assisted telephone interviews on a representative sample | Eating more/less/the same | 1000 | 51 ± 18 |
| Bonaccio et al., 2021 ( | Italy | March 9/May 18, 2020 (70) | May–September 2020 | Cross-sectional/retrospective | Telephone-based survey (Moli-LOCK cohort) and web-based survey on convenience sample (ALTRISCOVID-19 cohort) | Eating more/less/the same | 2992 | 57.9 ± 15.3 |
| Cancello et al., 2020 ( | Italy | March 9/May 18, 2020 (70) | April 15–May 4, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 490 | ≥18 |
| Cicero et al., 2021 ( | Italy | March 9/May 18, 2020 (70) | February-April 2020 and after the quarantine | Cohort study; longitudinal | Telephone-based survey | Daily/weekly frequency before and during lockdown; DQI | 359 | 64.6 ± 13.3 |
| Di Renzo et al., 2020 ( | Italy | March 9/May 18, 2020 (70) | April 5–24, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 3533 | 40.0 ± 13.5 |
| Ferrante et al., 2021 ( | Italy | March 9/May 18, 2020 (70) | April 21–June 7, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 7847 | 48.6 ± 13.9 |
| Maffoni et al., 2021 ( | Italy | March 9/May 18, 2020 (70) | April 30–May 10, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Dietary recommendations | 1304 | ≥18 |
| Mastorci et al., 2021 ( | Italy | March 9/May 18, 2020 (70) | September-October 2019/April 2020 | Longitudinal | Web-based survey | KIDMED | 1289 | 12.5 ± 1.2 |
| Prete et al., 2021 ( | Italy | March 9/May 18, 2020 (70) | 22 April–3 May, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 604 | 29.8 ± 10.4 |
| Ruggiero et al., 2021 ( | Italy | March 9/May 18, 2020 (70) | May–September 2020 | Cross-sectional/retrospective | Telephone-based survey (Moli-LOCK cohort) and web-based survey on convenience sample (ALTRISCOVID-19 cohort) | Eating more/less/the same | 3161 | 57.7 ± 15.4 |
| Scacchi et al., 2021 ( | Italy | March 9/May 18, 2020 (70) | May 6–31, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 1865 | Median 29 (IQR 16.0) |
| Scarmozzino et al., 2020 ( | Italy | March 9/May 18, 2020 (70) | April 3–15, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 1932 | NA |
| Segre et al., 2021 ( | Italy | March 9/May 18, 2020 (70) | May 18–June 7, 2020 | Cross-sectional/retrospective | Online interview | Eating more/less/the same | 82 | 6–14 |
| Pfeifer et al., 2021 ( | Croatia | March 18/April 19, 2020 (32) | April 7–May 4, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown MEDAS (score 0–14) | 4281 | ≥18 |
| Mititelu et al., 2021 ( | Romania | March 25/May 12, 2020 (48) | July 8–26, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 805 | ≥20 |
| Troka et al., 2021 ( | Albania | March 13/June 1, 2020 (80) | March–May 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 325 | NA |
| Androutsos et al., 2021 ( | Greece | March 23/May 4, 2020 (42) | April 30–May 24, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 397 | 7.8 ± 4.1 |
| Tsigkas et al., 2021 ( | Greece | March 23/May 4, 2020 (42) | April 13–30, 2020 | Cross-sectional/retrospective | Telephone-based survey | Eating more/less/the same | 1014 | ≥35 |
| Kolokotroni et al., 2021 ( | Cyprus | March 24/April 13, 2020 (20) | April 10–May 12, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown MEDAS (score 0–14) | 745 | 39 (median) |
| Deschasaux-Tanguy et al., 2020 ( | France | March 17/May 11, 2020 (55) | April–May 2020 | Cohort study; longitudinal | Web-based survey | Web-based 24h dietary records;AHEI-2010 score and UPF (% food weight) | 9372 | 52.1 ± 16.6 |
| Marty et al., 2020 ( | France | March 17/May 11, 2020 (55) | End of April 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency and amount before and during lockdown sPNNS-GS2 (score −17 to 11.5) to assess compliance to French dietary recommendations | 938 | 38.7 ± 11.6 |
| Constant et al., 2020 ( | France | March 17/May 11, 2020 (55) | April 8–20, 2020 | Cross-sectional/retrospective | Web-based survey among panelists from the Arcade Research Institute | Eating more/less/the same | 4005 | ≥18 |
| Philippe et al., 2021 ( | France | March 17/May 11, 2020 (55) | April 30–May 10, 2020 | Retrospective | Web-based survey among panelists from a French agency | Daily/weekly frequency before and during lockdown | 498 | 7.3 ± 2.2 |
| Rolland et al., 2020 ( | France | March 17/May 11, 2020 (55) | March 25–30, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 11,391 | ≥16 |
| Steffen et al., 2021 ( | Germany | March 22/April 20 to May 11, 2020 (29 to 50) | March–April 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 2067 | 25.6 ± 10.6 |
| Drieskens et al., 2021 ( | Belgium | March 18/May 4, 2020 (47) | April 16–23, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 28,029 | ≥18 |
| Vandevijvere et al., 2020 ( | Belgium | March 18/May 4, 2020 (47) | March–May 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 8640 | ≥18 |
| Błaszczyk-Bębenek et al., 2020 ( | Poland | March 13/April 11, 2020 (29) | April–May 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 312 | 41.1 ± 13.0 |
| Dobrowolski et al., 2021 ( | Poland | March 13/April 11, 2020 (29) | NA | Cross-sectional/retrospective | Computer-assisted web interview on convenience sample | Eating more/less/the same | 183 | 33 ± 11 |
| Drywień et al., 2021 ( | Poland | March 13/April 11, 2020 (29) | April–May 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 1769 women | ≥18 |
| Górnicka et al., 2020 ( | Poland | March 13/April 11, 2020 (29) | April 30–May 23, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 2381 | ≥18 |
| Kowalczuk et al., 2021 ( | Poland | March 13/April 11, 2020 (29) | March 20–May 30, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 926 | ≥18 |
| Sidor et al., 2020 ( | Poland | March 13/April 11, 2020 (29) | April 17–May 1, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 1097 | 27.7 ± 9.0 |
| Giacalone et al., 2020 ( | Denmark | March 12/April 13, 2020 (33) | April 24–May 5, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 2462 | ≥18 |
| Kriaucioniene et al., 2020 ( | Lithuania | March 16/June 18, 2020 (94) | From April 14, 2020 for 2 wk | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 2447 | ≥18 |
| Poelman et al., 2020 ( | The Netherlands | March 15/April 6, 2020 (22) | April 22–28, 2020 | Cross-sectional/retrospective | Web-based survey on a representative sample of adults | Eating more/less/the same | 1030 | 49.9 ± 17.0 |
| Buckland et al., 2020 ( | United Kingdom | March 23/July 13, 2020 (98 to 112) | May 15–June 27, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Changes by frequency of intake | 588 | 33.4 ± 12.6 |
| Coulthard et al., 2021 ( | United Kingdom | March 23/July 13, 2020 (98 to 112) | April 22–May 22, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 620 | 39.9 ± 13.9 |
| Herle et al., 2021 ( | United Kingdom | March 23/July 13, 2020 (98 to 112) | March 28–June 4, 2020 | Longitudinal | Web-based survey on convenience sample | Eating more/less/the same | 22,374 | ≥18 |
| Robinson et al., 2020 ( | United Kingdom | March 23/July 13, 2020 (98 to 112) | April 19–22, 2020 | Cross-sectional/retrospective | Web-based survey among Prolific Researcher panelists | Changes by frequency of intake | 723 | 30.7 ± 9.6 |
| Robinson et al., 2020 ( | United Kingdom | March 23/July 13, 2020 (98 to 112) | April 28–May 22, 2020 | Cross-sectional/retrospective | Web-based survey among Prolific Researcher panelists | Changes by frequency of intake | 2002 | 34.7 ± 12.3 |
| Ingram et al., 2020 ( | Scotland | March 23/June 29, 2020 (98) | March–May 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample among Prolific Academic users | Eating more/less/the same | 399 | 32.4 ± 11.4 |
| Bin Zarah et al., 2020 ( | USA | March–June, 2020 (20 to 89) | April–June 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 3133 | ≥18 |
| Cummings et al., 2021 ( | USA | March–June, 2020 (20 to 89) | March 2020 | Comparison with a similar cohort recruited in February 2019 | Web-based survey on convenience sample | Palatable Eating Motives Scale;National Cancer Institute's Dietary Screener Questionnaire;Modified Yale Food Addiction Scale 2.0 | 868 | ≥18 |
| Chenarides et al., 2020 ( | USA | March–June, 2020 (20 to 89) | May 13–30, 2020 | Cross-sectional/retrospective | Web-based survey | Eating more/less/the same | 861 | 53 ± 18 |
| Zhang et al., 2021 ( | USA | March–June, 2020 (20 to 89) | May/June 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 1276 | 45 ± 17 |
| Lamarche et al., 2021 ( | Canada | March 17/May 18, 2020 (58 to 61) | June 2019 and February 2020 (before lockdown)April 15–May 12, 2020 (during lockdown) | Open cohort study; longitudinal | Web-based survey | Web-based 24-h dietary recallHEI-2015 (score 0–100) | 853 | ≥18 |
| Christofaro et al., 2021 ( | Brazil | March 17/May 20, 2020 (21 to 47) | May 5–17, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 1874 | ≥18 |
| Malta et al., 2020 ( | Brazil | March 17/May 20, 2020 (21 to 47) | April 24–May 24, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown; self-rated changes for alcohol consumption | 45,161 | ≥18 |
| Tebar et al., 2021 ( | Brazil | March 17/May 20, 2020 (21 to 47) | May 5–17, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 1897 | 37.9 ± 13.3 |
| Martínez-Vázquez et al., 2021 ( | Mexico | March 23/June 1, 2020 (70) | April 13–May 16, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown; DQI | 8289 | ≥18 |
| Pertuz-Cruz et al., 2021 ( | Colombia | March 25/June 30, 2020 (97) | April 6–May 22, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 2745 | ≥18 |
| Ramos-Padilla et al., 2021 ( | Ecuador | March 16–31, 2020 (15) | June–July 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 9522 | 18–69 |
| Ares et al., 2021 ( | Uruguay | No restrictions | March 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 1725 | ≥18 |
| Huancahuire-Vega et al., 2020 ( | Peru | March 16/June 30, 2020 (106) | July 16–August 31, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 1176 | ≥18 |
| Reyes-Olavarría et al., 2020 ( | Chile | Partial lockdowns | May–June 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 700 | Median 31 (18–62) |
| Jia et al., 2020 ( | China | January 23/April 8, 2020 (76) | May 9–12, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Self-recall food consumption before and during lockdown | 10,082 | 19.8 ± 2.3 (15–28) |
| Wang et al., 2020 ( | China | January 23/April 8, 2020 (76) | March–April 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Weekly frequency and amount before and during lockdown | 2289 | 27.8 ± 12.0 |
| Yang et al., 2021 ( | China | January 23/April 8, 2020 (76) | February 23–March 4, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 2702 | 37.3 ± 12.0 |
| Zhu et al., 2021 ( | China | January 23/April 8, 2020 (76) | March 29–April 5, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 889 | 31.8 ± 11.4 |
| Chopra et al., 2020 ( | India | March 25/June 7, 2020 (74) | August 15–30, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 995 | 33.3 ± 14.5 |
| Singh et al., 2021 ( | India | March 25/June 7, 2020 (74) | May 11–20, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 1008 | 24 (median) |
| Shrestha et al., 2020 ( | Nepal | March 24/July 21, 2020 (120) | March 30/July 31, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 667 | ≥18 |
| Husain et al., 2020 ( | Kuwait | March 14–29, 2020 (15) | March–April 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 415 | 38.5 ± 12.7 |
| Alfawaz et al., 2021 ( | Saudi Arabia | March 9/June 21, 2020 (84 to 104) | May 11–June 6, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 1965 | 35.2 ± 13.1 |
| Alhusseini et al., 2020 ( | Saudi Arabia | March 9/June 21, 2020 (84 to 104) | May 5–15, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency;Food Quality score (score 5–25)Food Quantity score (score 0–24) | 2706 | ≥18 |
| Aljohani, 2020 ( | Saudi Arabia | March 9/June 21, 2020 (84 to 104) | April–June 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 782 | ≥16 |
| Mumena, 2020 ( | Saudi Arabia | March 9/June 21, 2020 (84 to 104) | April 13–22, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during curfew | 879 | 35.8 ± 12.1 |
| Radwan et al., 2020 ( | United Arab Emirates | March 26/April 17, 2020 (22) | May 5–18, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 2060 | ≥18 |
| Cheikh Ismail et al., 2020 ( | United Arab Emirates | March 26/April 17, 2020 (22) | April–May 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 1012 | ≥18 |
| Al-Domi et al., 2021 ( | Jordan | March 18/April 30, 2020 (43) | March and April 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Self-rated | 4473 | ≥18 |
| Al Hourani et al., 2021 ( | Jordan | March 18/April 30, 2020 (43) | June 15–30, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 447 | 6–17 |
| Galali, 2021 ( | Iraqi Kurdistan | March 22/April 11, 2020 (20) | June 1–14, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 2137 | NA |
| Matsungo et al., 2020 ( | Zimbabwe | March 30/May 2, 2020 (33) | May 11–25, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 507 | 31–40 |
| Curtis et al., 2021 ( | Australia | March 23/May 15, 2020 (52) | February 2020/ April 2020 | Cohort study/longitudinal | Web-based survey | Dietary Questionnaire for Epidemiological Studies | 64 | 41.3 ± 5.8 |
| Phillipou et al., 2020 ( | Australia | March 23/May 15, 2020 (52) | From April 1, 2020 for 1 wk | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 5289 | 40.6 ± 13.7 |
| Gerritsen et al., 2020 ( | New Zealand | March 26/May 14, 2020 (49) | April 24–May 13, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 3028 | 44.3 ± 14.0 |
| Abouzid et al., 2021 ( | Middle East and North Africa (MENA) region | March–June, 2020 (varying by regions) | August–September 4, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 5896 | ≥18 |
| Ammar et al., 2020 ( | Europe, North-Africa, Western Asia, and the Americas | Varying by country | April 6–11, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Dietary behaviours before and during lockdown by the use of the SDBQ-L (score 0–15; the highest the worst) | 1047 | ≥18 |
| Bahatheg, 2021 ( | Saudi Arabia, Britain, and Turkey | Varying by country | NA | Cross-sectional/retrospective | Web-based survey on convenience sample | Self-rated | 330 | 4–7 |
| Cavagnari et al., 2021 ( | Spain and 11 Latin American countries[ | Varying by country | April 15–May 4, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 10,552 | Median 33( |
| Cheikh Ismail et al., 2020 ( | Middle East and North Africa (MENA) region | March–June, 2020 (varying by regions) | April 15–29, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown | 2970 | ≥18 |
| Dou et al., 2021 ( | China and USA | Varying by country | April 17–27, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 1547 in the USA; 1732 in China | Median 41 ( |
| Janssen et al., 2021 ( | Denmark, Germany, and Slovenia | Varying by country | April 22–May 6, 2020 | Cross-sectional/retrospective | Web-based survey among consumer panel agencies with quota sampling | Daily/weekly frequency before and during lockdown | 2680 | 54.9 ± 14.1 (Denmark)48.9 ± 16.0 (Germany)44.1 ± 13.5 (Slovenia) |
| Molina-Montes et al., 2021 ( | 16 European countries[ | Varying by country | March 20–May 5, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency before and during lockdown MEDAS (score 0–14) | 36,185 | ≥18 |
| Papandreou et al., 2020 ( | Spain, Greece | Spain: March 14/May 9, 2020 (56) Greece: March 23/May 4, 2020 (42) | April–May 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 1002 (Spain) 839 (Greece) | 46.1 ± 13.3 (Spain) 42.4 ± 11.7 (Greece) |
| Pišot et al., 2020 ( | Bosnia and Herzegovina, Croatia, Greece, Kosovo, Italy, Serbia, Slovakia, Slovenia, and Spain | Varying by country | April 15–May 3, 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Eating more/less/the same | 4108 | 32.0 ± 13.2 |
| Ruíz-Roso et al., 2020 ( | Italy, Spain, Brazil, Chile, Colombia | Varying by country | April-May 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Self-recall food consumption before and during lockdown by using a modified version of the National School Health Survey—PeNSE questionnaire | 820 | 10–19 |
| Murphy et al., 2020 ( | New Zealand,USA, Great Britain, and the Island of Ireland | Varying by country | May-June 2020 | Cross-sectional/retrospective | Web-based survey on convenience sample | Daily/weekly frequency and portions before and during lockdown | 2360 | ≥18 |
AHEI-2010, Alternate Healthy Eating Index–2010 score; ALTRISCOVID-19, Analysis of Long Term Risk of COVID-19; COVID-19, coronavirus disease 2019; DQI, Dietary Quality Index; HEI-2015, Healthy Eating Index-2015; KIDMED, Mediterranean Diet Quality Index for children and teenagers; MEDAS, PREDIMED (PREvención con DIeta MEDiterránea) Mediterranean Diet Adherence Screener; NA, not available; ref, reference; SDBQ-L, Short Diet Behaviours Questionnaire for Lockdowns; sPNNS-GS2, Simplified Programme National Nutrition Santé—guidelines score 2; UPF, ultra-processed food.
Argentina, Chile, Colombia, Costa Rica, Ecuador, Guatemala, Mexico, Peru, Paraguay, Panama, and Uruguay.
Bosnia and Herzegovina, Croatia, Denmark, Germany, Greece, Ireland, Italy, Lithuania, Montenegro, North Macedonia, Poland, Portugal, Serbia, Slovenia, Spain, and Turkey.