| Literature DB >> 35189982 |
Ahmad Syafiq1, Sandra Fikawati2, Syilga Cahya Gemily2.
Abstract
BACKGROUND: One of the impacts of the COVID-19 pandemic was the weakening of the community's economic condition. The weak economy of the community will have an impact on household food security. This study aims to determine food security in the COVID-19 pandemic situation and the impact of the pandemic on food security in urban and semi-urban areas.Entities:
Keywords: COVID-19 pandemic; Food security; Semi-urban area; Urban area
Mesh:
Year: 2022 PMID: 35189982 PMCID: PMC8860285 DOI: 10.1186/s41043-022-00285-y
Source DB: PubMed Journal: J Health Popul Nutr ISSN: 1606-0997 Impact factor: 2.000
Number of respondents by data source and region
| Data source | Region | Total | |
|---|---|---|---|
| Jakarta | Depok | ||
| Social media | 115 (44.6%) | 52 (20.1%) | 167 (32.3%) |
| 143 (55.4%) | 207 (79.9%) | 350 (67.7%) | |
| Total | 258 (100%) | 259 (100%) | 517 (100%) |
Situation of the impact of the pandemic and food security during the pandemic
| Variable | Jakarta | Depok | Total |
|---|---|---|---|
| Affected | 198 (76.7%) | 191 (73.7%) | 389 (75.2%) |
| Less affected | 60 (23.3%) | 68 (26.3%) | 128 (24.8%) |
| Income reduced | 163 (63.2%) | 161 (62.2%) | 324 (62.7%) |
| Can't leave the house | 47 (18.2%) | 46 (17.8%) | 93 (18.0%) |
| Stopped working | 35 (13.6%) | 30 (11.6%) | 65 (12.6%) |
| Expensive price | 12 (4.7%) | 16 (6.2%) | 28 (5.4%) |
| Expensive food prices | 0 (0.0%) | 6 (2.3%) | 6 (1.2%) |
| Others (lack of public transportation) | 1 (0.4%) | 0 (0.0%) | 1 (0.2%) |
| March 2020 | 162 (62.8%) | 177 (68.3%) | 339 (65.6%) |
| April 2020 | 60 (23.3%) | 53 (20.5%) | 113 (21.9%) |
| May 2020 | 1 (0.4%) | 0 (0.0%) | 1 (0.2%) |
| June 2020 | 8 (3.1%) | 3 (1.2%) | 11 (2.1%) |
| July 2020 | 4 (1.6%) | 3 (1.2%) | 7 (1.4%) |
| August 2020 | 3 (1.2%) | 1 (0.4%) | 4 (0.8%) |
| September 2020 | 1 (0.4%) | 0 (0.0%) | 1 (0.2%) |
| October 2020 | 19 (7.4%) | 22 (8.5%) | 41 (7.9%) |
| Yes always | 28 (10.9%) | 21 (8.1%) | 49 (9.5%) |
| Yes, often | 28 (10.9%) | 31 (12.0%) | 59 (11.4%) |
| Yes, sometimes | 131 (50.8%) | 122 (47.1%) | 253 (48.9%) |
| No | 71 (27.5%) | 85 (32.8%) | 156 (30.2%) |
| Expensive food price | 18 (9.6%) | 18 (10.3%) | 36 (10.0%) |
| Decreased income | 152 (81.3%) | 142 (81.6%) | 294 (81.4%) |
| Don't have income | 16 (8.65) | 14 (8.0%) | 30 (8.3%) |
| Severe food insecurity | 45 (17.4%) | 35 (13.5%) | 80 (15.5%) |
| Moderate food insecurity | 77 (29.8%) | 69 (26.6%) | 146 (28.2%) |
| Mild food insecurity | 54 (20.9%) | 56 (21.6%) | 110 (21.3%) |
| Adequate food security | 82 (31.8%) | 99 (38.2%) | 181 (35.0%) |
| Food insecurity at various level | 176 (68.2%) | 160 (61.8%) | 336 (65.0%) |
| Adequate food security | 82 (31.8%) | 99 (38.2%) | 181 (35.0%) |
Food consumption conditions in households experiencing food shortage during a pandemic
| Variable | Jakarta | Depok | Total |
|---|---|---|---|
| Yes | 157 (84.0%) | 146 (83.9%) | 303 (83.9%) |
| No | 30 (16.0%) | 28 (16.1%) | 58 (16.1%) |
| Yes | 168 (89.8%) | 325 (90.2%) | 325 (90.0%) |
| No | 19 (10.2%) | 17 (9.8%) | 36 (10.0%) |
| Yes | 126 (67.4%) | 109 (62.6%) | 235 (65.1%) |
| No | 61 (32.6%) | 65 (37.4%) | 126 (34.9%) |
| Yes | 133 (71.1%) | 127 (73.0%) | 260 (72.0%) |
| No | 54 (28.9%) | 47 (27.0%) | 101 (28.0%) |
| Yes | 129 (69.0%) | 118 (67.8%) | 247 (68.4%) |
| No | 58 (31.0%) | 56 (32.2%) | 114 (31.6%) |
| Yes | 58 (31.0%) | 46 (26.4%) | 104 (28.8%) |
| No | 129 (69.0%) | 128 (73.6%) | 257 (71.2%) |
| Yes | 46 (24.6%) | 37 (21.3%) | 83 (23.0%) |
| No | 141 (75.4%) | 137 (78.7%) | 278 (77.0%) |
| Yes | 28 (15.0%) | 17 (9.8%) | 45 (12.5%) |
| No | 159 (85.0%) | 157 (90.2%) | 316 (87.5%) |
Changes in the diet of vulnerable groups in households during the pandemic
| Variable | Infant | Toddler | Under-five | Pregnant women | Lactating mother |
|---|---|---|---|---|---|
| Yes | 18 (16.2%) | 51 (44.0%) | 138 (43.0%) | 50 (68.5%) | 87 (46.3%) |
| No | 93 (83.8%) | 65 (56.0%) | 183 (57.0%) | 23 (31.5%) | 101 (53.7%) |
| The type of food eaten is reduced | 9 (50.0%) | 35 (68.8%) | 88 (63.8%) | 30 (60.0%) | 54 (62.1%) |
| Reduced amount of food eaten | 7 (38.9%) | 10 (19.6%) | 30 (21.7%) | 9 (18.0%) | 23 (26.4%) |
| Decreased number of meals per day | 1 (5.6%) | 4 (7.8%) | 18 (13.0%) | 11 (22.0%) | 9 (10.3%) |
| Others (unable to buy nutritious food, eat potluck, change brands) | 1 (5.6%) | 2 (3.9%) | 2 (1.4%) | 0 (0.0%) | 1 (1.1%) |
Food groups with reduced consumption reported by pregnant women
| Food groups | Frequency (percentage) |
|---|---|
| Staple food | 3 (10.0%) |
| Protein source food | 7 (23.3%) |
| Fruits | 14 (46.7%) |
| Dairy | 6 (20.0%) |
Multivariate final model
| Variable | OR (95% CI) | |
|---|---|---|
| Impact of the COVID-19 pandemic | < 0.001 | 2.6 (1.6–4.1) |
| Family income during the pandemic | < 0.001 | 4.2 (2.7–6.7) |
| Respondent age | 0.011 | 1.7 (1.1–2.5) |
| Husband's work status | 0.171 | 1.8 (0.8–4.1) |