| Literature DB >> 33663623 |
Ali Jafri1, Nonsikelelo Mathe2, Elom K Aglago3, Silvenus O Konyole4, Moussa Ouedraogo5, Keiron Audain6, Urbain Zongo5, Amos K Laar7, Jeffrey Johnson2, Dia Sanou8.
Abstract
OBJECTIVE: To investigate the perceived effects of the coronavirus disease (COVID-19) pandemic lockdown measures on food availability, accessibility, dietary practices and strategies used by participants to cope with these measures.Entities:
Keywords: Accessibility; COVID-19; Coping mechanisms; Food availability; Nutrition security
Mesh:
Year: 2021 PMID: 33663623 PMCID: PMC8007937 DOI: 10.1017/S1368980021000987
Source DB: PubMed Journal: Public Health Nutr ISSN: 1368-9800 Impact factor: 4.022
General characteristics of the study participants (n 1029)
| North Africa | West Africa | East Africa | Southern Africa | Western Europe | North America | Other | Total | |
|---|---|---|---|---|---|---|---|---|
| Total ( | 136 | 251 | 146 | 83 | 172 | 105 | 136 | 1029 |
| Gender (%) | ||||||||
| Female | 63·2 | 37·5 | 49·3 | 78·3 | 53·5 | 62·0 | 51·5 | 52·9 |
| Male | 35·3 | 59·8 | 50·0 | 21·7 | 42·4 | 34·3 | 47·1 | 44·9 |
| Undisclosed | 1·47 | 2·79 | 0·68 | 0 | 4·07 | 3·81 | 1·47 | 2·14 |
| Location (%) | ||||||||
| Rural | 2·21 | 6·37 | 17·1 | 4·82 | 19·8 | 23·8 | 13·2 | 12·2 |
| Suburban | 1·47 | 1·59 | 2·05 | 3·61 | 4·65 | 18·1 | 3·68 | 4·28 |
| Urban | 96·3 | 92·0 | 80·8 | 91·6 | 75·6 | 58·1 | 83·1 | 83·6 |
| Age | ||||||||
| 1st quartile | 27·0 | 30·0 | 28·0 | 28·0 | 28·0 | 33·0 | 30·0 | 29·0 |
| Median | 33·0 | 34·0 | 34·0 | 37·0 | 33·0 | 40·0 | 35·0 | 35·0 |
| 3rd quartile | 40·5 | 41·0 | 42·0 | 42·0 | 40·5 | 48·0 | 40·0 | 42·0 |
| Education (%) | ||||||||
| Primary | 0 | 0·4 | 1·37 | 0 | 0·59 | 0 | 0 | 0·39 |
| Secondary | 3·68 | 4·78 | 4·11 | 9·76 | 11·2 | 11·5 | 5·15 | 6·73 |
| University degree | 31·6 | 27·5 | 50·7 | 53·7 | 42·9 | 47·1 | 39·0 | 39·5 |
| Master or PhD | 64·7 | 67·3 | 43·8 | 36·6 | 45·3 | 41·4 | 55·9 | 53·4 |
| Employment (%) | ||||||||
| Student | 14·0 | 5·98 | 3·42 | 2·41 | 12·8 | 3·81 | 5·15 | 7·19 |
| Employed | 80·2 | 89·6 | 84·3 | 89·2 | 79·1 | 78·1 | 89·7 | 84·7 |
| Retired | 2·21 | 0·4 | 2·05 | 3·61 | 2·33 | 4·76 | 2·21 | 2·14 |
| Unemployed | 1·47 | 3·59 | 7·53 | 4·82 | 5·23 | 7·62 | 2·21 | 4·47 |
| Unemployed due to COVID | 2·21 | 0·4 | 2·74 | 0 | 0·58 | 5·71 | 0·74 | 1·55 |
| Household income in USD | ||||||||
| First quartile | 652·5 | 200 | 200 | 300 | 2000 | 3150 | 420 | 392·5 |
| Median | 1600 | 500 | 590 | 1400 | 3600 | 8250 | 1000 | 1300 |
| Third quartile | 3000 | 1000 | 1500 | 2500 | 8000 | 32 500 | 3000 | 3900 |
| COVID-19 security measures | ||||||||
| Travel ban (%) | 97·8 | 94·4 | 85·6 | 100 | 83·7 | 74·3 | 70·6 | 87·1 |
| Lockdown (%) | 81·6 | 80·1 | 86·3 | 81·9 | 14·0 | 12·4 | 33·8 | 57·2 |
| Social distancing (%) | 94·9 | 96·4 | 96·6 | 95·2 | 98·8 | 100 | 98·5 | 97·2 |
| Home confinement (%) | 95·6 | 49·4 | 51·4 | 89·2 | 77·3 | 56·2 | 69·9 | 67·1 |
| Closed fast-foods (%) | 80·2 | 57·0 | 48·6 | 72·3 | 73·3 | 58·1 | 53·7 | 62·5 |
| Closed supermarkets (%) | 7·35 | 37·9 | 6·85 | 12·1 | 4·65 | 5·71 | 14·7 | 15·5 |
Relative frequencies of respondents who stockpiled food during the COVID-19 pandemic during April and May 2020
| North Africa | West Africa | East Africa | Southern Africa | Western Europe | North America | Other | Total | |
|---|---|---|---|---|---|---|---|---|
| Total ( | 136 | 251 | 146 | 83 | 172 | 105 | 136 | 1029 |
| Purchased more food due to COVID-19 (%) | 41·9 | 71·3 | 67·1 | 61·5 | 61·1 | 76·2 | 55·2 | 62·7 |
| Stockpiled cereals (%) | 50·7 | 77·7 | 74·7 | 39·8 | 40·1 | 56·2 | 57·4 | 59·5 |
| Stockpiled meat (%) | 29·4 | 42·2 | 36·3 | 45·8 | 22·7 | 43·8 | 36·0 | 36·1 |
| Stockpiled dairy (%) | 18·4 | 45·4 | 16·4 | 14·5 | 8·72 | 20·0 | 30·9 | 24·6 |
| Stockpiled legumes (%) | 43·4 | 55·0 | 69·2 | 37·4 | 35·5 | 48·6 | 44·9 | 48·8 |
| Stockpiled fruits (%) | 15·4 | 20·3 | 23·3 | 22·9 | 7·6 | 30·5 | 19·1 | 19·1 |
| Stockpiled vegetables (%) | 21·3 | 42·2 | 29·5 | 33·7 | 14·0 | 37·1 | 30·9 | 30·2 |
| Stockpiled canned products (%) | 35·3 | 39·8 | 16·4 | 41·0 | 44·8 | 66·7 | 33·8 | 38·8 |
| Stockpiled sweets (%) | 19·1 | 18·7 | 13·7 | 15·7 | 14·5 | 24·8 | 19·9 | 17·9 |
Relative frequency of people having experienced increasing prices in certain food groups, alcohol and cigarettes during the COVID-19 pandemic
| North Africa | West Africa | East Africa | Southern Africa | Western Europe | North America | Other | Total | |
|---|---|---|---|---|---|---|---|---|
| Total ( | 136 | 251 | 146 | 83 | 172 | 105 | 136 | 1029 |
| Cereals (%) | 24·3 | 61·4 | 77·4 | 54·2 | 25·0 | 28·6 | 50·7 | 47·3 |
| Dairy (%) | 8·82 | 37·5 | 45·9 | 50·6 | 19·8 | 41·9 | 41·9 | 34·0 |
| Fruits and veggies (%) | 43·4 | 62·6 | 65·8 | 62·7 | 29·7 | 32·4 | 58·8 | 51·4 |
| Meats (%) | 27·2 | 53·4 | 50·0 | 62·7 | 24·4 | 61·9 | 47·1 | 45·4 |
| Legumes (%) | 28·7 | 52·2 | 67·1 | 47·0 | 16·9 | 18·1 | 40·4 | 39·8 |
| Oils and fats (%) | 14·0 | 39·8 | 52·1 | 54·2 | 14·0 | 18·1 | 34·6 | 32·1 |
| Sweets (%) | 9·56 | 36·3 | 50·7 | 51·8 | 14·0 | 12·4 | 39·0 | 30·2 |
| Alcohol (%) | 12·3 | 11·7 | 15·7 | 25·0 | 7·38 | 11·1 | 23·0 | 12·8 |
| Cigarettes (%) | 6·56 | 4·04 | 9·8 | 25·0 | 4·7 | 4·94 | 6·90 | 6·00 |
Fig. 1Relative frequency of people whose food acquisition has been affected by price increases during COVID-19
Aspects of food insecurity experienced by the study participants and coping mechanisms adopted during the COVID-19 pandemic
| North Africa | West Africa | East Africa | Southern Africa | Western Europe | North America | Other | Total | |
|---|---|---|---|---|---|---|---|---|
| Total ( | 136 | 251 | 146 | 83 | 172 | 105 | 136 | 1029 |
| Aspects of food insecurity | ||||||||
| Difficulty accessing drinking water (%) | 1·47 | 11·6 | 19·9 | 8·43 | 1·16 | 4·76 | 14·0 | 9·04 |
| Lesser variety of food (%) | 19·1 | 41·0 | 63·7 | 61·5 | 56·4 | 74·3 | 52·2 | 50·4 |
| Food of less quality (%) | 10·3 | 29·1 | 51·4 | 26·5 | 20·9 | 38·1 | 37·5 | 30·2 |
| Lesser quantity of food (%) | 8·82 | 35·9 | 61·6 | 51·8 | 40·7 | 49·5 | 33·8 | 39·2 |
| Subject to food rationing (%) | 6·62 | 14·3 | 19·2 | 27·7 | 7·56 | 7·62 | 16·9 | 13·6 |
| Food less accessible (%) | 16·2 | 23·9 | 39·0 | 15·7 | 12·8 | 25·7 | 20·6 | 22·3 |
| Not having any food all day (%) | 5·47 | 9·56 | 24·7 | 4·82 | 2·33 | 9·52 | 11·0 | 9·79 |
| Eating less frequently (%) | 19·5 | 23·1 | 45·9 | 31·3 | 11·1 | 29·5 | 26·5 | 25·7 |
| Coping mechanisms | ||||||||
| Relying on less preferred food (%) | 28·9 | 40·2 | 67·1 | 67·5 | 43·6 | 65·7 | 48·5 | 49·2 |
| Borrowing food (%) | 12·5 | 14·3 | 32·9 | 16·9 | 13·4 | 12·4 | 17·7 | 17·0 |
| Food credit (%) | 10·9 | 13·9 | 36·3 | 18·1 | 4·65 | 19·1 | 14·7 | 16·2 |
| Reducing portion sizes (%) | 19·5 | 28·3 | 50·7 | 34·9 | 19·8 | 31·4 | 31·6 | 30·3 |
| Adults restricting themselves (%) | 7·03 | 23·1 | 42·5 | 18·1 | 5·81 | 10·5 | 19·1 | 18·7 |
| Reducing number of meals (%) | 19·5 | 23·1 | 45·9 | 31·3 | 11·1 | 29·5 | 26·5 | 25·7 |
| Food aid (%) | 3·91 | 8·76 | 18·5 | 6·02 | 4·65 | 9·52 | 5·88 | 8·33 |
Vulnerable groups whose diets have been affected by COVID-19 restrictions
| North Africa | West Africa | East Africa | Southern Africa | Western Europe | North America | Other | Total | |
|---|---|---|---|---|---|---|---|---|
| Total ( | 136 | 251 | 146 | 83 | 172 | 105 | 136 | 1029 |
| Infants | 4·41 | 8·37 | 18·5 | 7·23 | 0·58 | 5·71 | 11·8 | 8·07 |
| Children | 0·15 | 15·9 | 35·6 | 15·7 | 2·91 | 6·67 | 18·4 | 14·5 |
| Pregnant women | 5·88 | 13·2 | 32·2 | 13·3 | 1·16 | 3·81 | 16·2 | 12·3 |
| Breastfeeding women | 2·94 | 12·4 | 30·1 | 9·64 | 0·58 | 3·81 | 13·2 | 10·7 |
| Elderly | 9·56 | 15·9 | 37·0 | 19·3 | 6·98 | 10·5 | 23·5 | 17·3 |
| People with NCDs | 10·3 | 19·9 | 41·1 | 24·1 | 11·1 | 15·2 | 21·3 | 20·2 |