| Literature DB >> 35527741 |
Kritthika Gonella1, Sudeepti Pramod Nayak1, Meenakshi Garg1, Namratha Pai Kotebagilu2.
Abstract
Background: /Entities:
Keywords: COVID-19; Gooseberry; Middle-aged adults; Neem; Young-aged adults
Year: 2022 PMID: 35527741 PMCID: PMC9069973 DOI: 10.1016/j.cegh.2022.101056
Source DB: PubMed Journal: Clin Epidemiol Glob Health ISSN: 2213-3984
Personal and sociodemographic details of the participants.
| Variables | Frequency (n = 218) | Percentage |
|---|---|---|
| Gender | ||
| - Male | 85 | 38.99% |
| - Female | 133 | 61.01% |
| Age | ||
| - Young Adult (20–35 years) | 138 | 63.3% |
| - Middle-aged Adult (36–55 years) | 80 | 36.7% |
| Religion | ||
| - Hindu | 194 | 89% |
| - Muslim | 7 | 3.2% |
| - Christian | 10 | 4.6% |
| - Others | 7 | 3.2% |
| Marital Status | ||
| - Married | 97 | 44.5% |
| - Unmarried | 119 | 54.6% |
| - Widowed | 2 | 0.9% |
| Type of family | ||
| - Nuclear | 168 | 77.1% |
| - Joint | 38 | 17.4% |
| - Extended | 12 | 5.5% |
| Locality | ||
| - Urban | 187 | 85.8% |
| - Rural | 31 | 14.2% |
| - North | 17 | 7.8% |
| - South | 174 | 79.8% |
| - East | 3 | 1.4% |
| - West | 24 | 11% |
| Educational qualification of the participant | ||
| - Professional degree, post-graduate and above | 106 | 48.62% |
| - B.A. or B.Sc. degree | 101 | 46.33% |
| - Intermediate or past high school diploma | 11 | 5.05% |
| Occupation of the participant | ||
| - Profession | 94 | 43.11% |
| - Semi profession | 24 | 11% |
| - Clerical, shop owner, -farmer | 13 | 5.96% |
| - Skilled worker | 1 | 0.46% |
| - Semiskilled worker | 1 | 0.46% |
| - Unemployed | 85 | 38.99% |
| Monthly income of the participant | ||
| - ≥ 78,063 | 46 | 21.1% |
| - 39,033–78,062 | 41 | 18.8% |
| - 29,200–39,032 | 11 | 5% |
| - 19,516–29,199 | 25 | 11.5% |
| - 11,708–19,515 | 12 | 5.5% |
| - 3,908–11,707 | 3 | 1.4% |
| - ≤ 3,907 | 3 | 1.4% |
| - Not applicable | 77 | 35.3% |
| SES category | ||
| - Upper Lower | 8 | 3.67% |
| - Lower Middle | 20 | 9.17% |
| - Upper Middle | 76 | 34.86% |
| - Upper | 114 | 52.29% |
| If the lockdown or pandemic affected one's job | ||
| - Yes | 58 | 26.61% |
| - No | 160 | 73.39% |
Variation in Food Consumption Scores between young and middle-aged adults.
| Time period | Age group | N | FCS | p-value |
|---|---|---|---|---|
| Median (Q1, Q3) | ||||
| Pre COVID | Young-aged adults | 138 (63.3%) | 55.25 (27.125, 77.75) | 0.001*** |
| Middle-aged adults | 80 (36.69%) | 32 (22.5, 66.5) | ||
| During COVID | Young-aged adults | 138 (63.3%) | 57.25 (30.375, 79.25) | <0.001*** |
| Middle-aged adults | 80 (36.69%) | 32 (21.375, 61.875) |
*** indicates significance level at 0.1%.
Linear regression model for food consumption scores.
| Model | Unstandardized Coefficients | p-value | 95% Confidence Interval | ||
|---|---|---|---|---|---|
| B | Std. Error | Lower Bound | Upper Bound | ||
| (Constant) | 45.365 | 9.745 | <0.001 | 26.57 | 64.15 |
| Job status | 13.78 | 4.2 | 0.001*** | 5.49 | 22.06 |
| Age group | −13.88 | 3.7 | <0.001*** | −21.37 | −6.39 |
*** indicates significance level at 0.1%.
Comparison of various immune-boosting food during the two points.
| Consumption of immune boosters | Pre COVID | During COVID | p-value | |
|---|---|---|---|---|
| Aloe Vera | Yes | 36 (16.51%) | 45 (20.64%) | 0.11 |
| No | 182 (83.49%) | 173 (79.36%) | ||
| Condiments | Yes | 170 (77.98%) | 193 (88.53%) | 0.011** |
| No | 48 (22.02%) | 25 (11.47%) | ||
| Dark green leafy vegetables | Yes | 177 (81.19%) | 187 (85.78%) | 0.12 |
| No | 41 (18.81%) | 31 (14.22%) | ||
| Fruit | Yes | 181 (83.03%) | 195 (89.45%) | 0.02* |
| No | 37 (16.97%) | 23 (10.55%) | ||
| Gooseberries | Yes | 86 (39.45%) | 109 (50%) | <0.001*** |
| No | 132 (60.55%) | 209 (50%) | ||
| Honey | Yes | 123 (56.42%) | 138 (63.3%) | 0.03* |
| No | 95 (43.58%) | 80 (36.7%) | ||
| Neem | Yes | 55 (25.23%) | 71 (32.57%) | 0.015* |
| No | 163 (74.77%) | 147 (67.43%) | ||
| Spices | Yes | 175 (80.28%) | 191 (87.61%) | 0.017* |
| No | 43 (19.72%) | 27 (12.39%) |
*, **, *** indicates significance levels at 5%, 1% and 0.1% respectively.