| Literature DB >> 34147945 |
Anita A Panjwani1, Regan L Bailey2, Bridgette L Kelleher3.
Abstract
BACKGROUND: Research on the impact of the COVID-19 pandemic on behaviors of children with autism spectrum disorder (ASD) is lacking. AIMS: This study investigates the relationship between COVID-19 and behaviors of children with ASD living in the United States. METHODS AND PROCEDURES: Parents and caregivers (n = 200) across the United States, as proxies for children 2-17 years of age with ASD, participated in an online survey querying changes in overall behavior and 15 specific behaviors during the COVID-19 pandemic. Logistic regression was used to assess the association of a moderate-to-large impact on the child's overall behavior with household income level and food security status. OUTCOMES ANDEntities:
Keywords: Autism spectrum disorder; Behavior; COVID-19; Child; Food supply
Mesh:
Year: 2021 PMID: 34147945 PMCID: PMC8276948 DOI: 10.1016/j.ridd.2021.104002
Source DB: PubMed Journal: Res Dev Disabil ISSN: 0891-4222
Household and child characteristics.
| Total | Impact on Overall Behavior | ||||
|---|---|---|---|---|---|
| None to Small N = 51 | Moderate to Large N = 148 | ||||
| Household characteristics | N = 200 | n (%) | n (%) | n (%) | P–value |
| U.S. Region | 198 | ||||
| Midwest | 56 (28.3) | 18 (35.3) | 38 (25.9) | ||
| Northeast | 43 (21.7) | 7 (13.7) | 36 (24.5) | ||
| South | 54 (27.3) | 17 (33.3) | 37 (25.2) | ||
| West | 45 (22.7) | 9 (17.7) | 36 (24.5) | 0.18 | |
| Shelter regulations | 196 | ||||
| Yes | 151 (77.0) | 39 (78.0) | 112 (76.7) | ||
| No | 39 (19.9) | 11 (22.0) | 28 (19.2) | ||
| Don’t know | 6 (3.1) | 0 (0.0) | 6 (4.1) | 0.76 | |
| Living with spouse/partner | 199 | ||||
| Yes | 149 (74.9) | 44 (86.3) | 105 (71.0) | ||
| No | 50 (25.1) | 7 (13.7) | 43 (29.1) | ||
| Children <18y in home, mean (SD) | 192 | 2.1 (1.0) | 2.3 (1.0) | 2.0 (1.0) | 0.08 |
| Respondent education | 183 | ||||
| High school graduate or less | 17 (9.3) | 3 (6.3) | 14 (10.4) | ||
| Some college/associate degree | 71 (38.8) | 13 (27.1) | 58 (43.0) | ||
| College degree | 45 (24.6) | 16 (33.3) | 29 (21.5) | ||
| Graduate degree or above | 50 (27.3) | 16 (33.3) | 34 (25.2) | 0.12 | |
| Spouse/partner education | 133 | ||||
| High school graduate or less | 19 (14.3) | 4 (9.8) | 15 (16.3) | ||
| Some college/associate degree | 51 (38.4) | 15 (36.6) | 36 (39.1) | ||
| College degree | 30 (22.6) | 8 (19.5) | 22 (23.9) | ||
| Graduate degree or above | 33 (24.8) | 14 (34.2) | 19 (20.7) | 0.38 | |
| Loss of employment reduced pay (either or both caregiver) | 144 | ||||
| Yes | 54 (37.5) | 7 (17.1) | 47 (45.6) | ||
| No | 90 (62.5) | 34 (82.9) | 56 (54.4) | ||
| Receiving food resources | 198 | ||||
| Yes | 71 (35.9) | 12 (23.5) | 59 (40.1) | ||
| No | 127 (64.1) | 39 (76.5) | 88 (59.9) | ||
| Household income (pre-COVID) | 163 | ||||
| <$50K | 75 (46.0) | 11 (26.2) | 64 (52.9) | ||
| $50 K - <$100K | 54 (33.1) | 17 (40.5) | 37 (30.6) | ||
| ≥$100K | 34 (20.9) | 14 (33.3) | 20 (16.5) | ||
| Food Insecurity (post-COVID) | 198 | ||||
| Yes | 119 (60.1) | 18 (36.0) | 101 (68.2) | ||
| No | 79 (39.9) | 32 (64.0) | 47 (31.8) | ||
| N | n (%) | n (%) | n (%) | ||
| Sex | 197 | ||||
| Male | 150 (76.1) | 43 (84.3) | 107 (73.3) | ||
| Female | 47 (23.9) | 8 (15.7) | 39 (26.7) | 0.11 | |
| Age, mean (SD) | 198 | 7.7 (4.1) | 7.4 (4.4) | 7.9 (4.0) | 0.44 |
| Age of diagnosis, mean (SD) | 193 | 3.7 (2.4) | 3.7 (2.4) | 3.7 (2.4) | 0.96 |
| Race | 195 | ||||
| Non-Hispanic White | 121 (62.1) | 32 (62.8) | 89 (61.8) | ||
| Non-Hispanic Black | 14 (7.2) | 2 (3.9) | 12 (8.3) | ||
| Hispanic or Latino | 27 (13.9) | 7 (13.7) | 20 (13.9) | ||
| Mixed | 19 (9.7) | 7 (13.7) | 12 (8.3) | ||
| Other | 14 (7.2) | 3 (5.9) | 11 (7.6) | 0.71 | |
| Weight status | 103 | ||||
| Underweight | 16 (16.5) | 6 (24.0) | 10 (12.8) | ||
| Healthy weight | 43 (41.8) | 10 (40.0) | 33 (76.7) | ||
| Overweight | 16 (15.5) | 3 (12.0) | 13 (16.7) | ||
| Obese | 27 (26.2) | 6 (24.0) | 22 (28.2) | 0.59 | |
| Educational setting | 166 | ||||
| Attending school in person | 1 (0.6) | 0 (0.0) | 1 (0.8) | ||
| Homeschooled | 12 (7.2) | 2 (5.1) | 10 (7.9) | ||
| Receiving virtual instruction | 104 (62.7) | 26 (66.7) | 78 (61.4) | ||
| Not receiving any instruction | 49 (29.5) | 32 (62.8) | 89 (61.8) | 0.91 | |
Note: Some percentages may not add up to 100 % due to rounding; Fisher’s exact p-value reported where applicable. Bolded values = p<0.05.
Shelter in place or stay at home order from any governing body; p-value for this variable excluded the “don’t know” category.
High school graduate including GED or other equivalent.
Age in years.
P–value for this variable excluded the “attending school in person” category.
Fig. 1Changes in specific child behaviors by level of household income (pre-COVID) and food insecurity (post-COVID).
Associations of moderate-to-large impact of post-COVID-19 regulations on overall behavior among children with ASD with income and food insecurity.a
| Odds Ratio | 95 % CI | P–value | |
|---|---|---|---|
| Model I (N = 163) | |||
| ≥$100K | (ref) | – | – |
| $50 K - >$100K | 1.52 | (0.59, 3.92) | 0.38 |
| <$50K | 4.07 | (1.50, 11.04) | |
| Model II (N = 198) | |||
| No | (ref) | – | – |
| Yes | 3.82 | (1.92, 7.62) | |
| Model III (N = 162) | |||
| ≥$100K | (ref) | – | – |
| $50 K - >$100K | 1.23 | (0.47, 3.25) | 0.67 |
| <$50K | 2.12 | (0.75, 6.03) | 0.16 |
| No | (ref) | – | – |
| Yes | 3.19 | (1.42, 7.18) | |
| Model IV (N = 120) | |||
| Female | (ref) | – | – |
| Male | 2.32 | (0.53, 10.17) | 0.28 |
| 1.07 | (0.93, 1.23) | 0.33 | |
| 0.57 | (0.15, 2.09) | 0.35 | |
| 0.40 | (0.10, 1.66) | 0.17 | |
| 3.46 | (0.84, 14.23) | 0.06 | |
| 0.62 | (0.09, 4.02) | 0.61 | |
| ≥$100K | (ref) | – | – |
| $50 K - >$100K | 1.19 | (0.33, 4.25) | 0.87 |
| <$50K | 3.18 | (0.37, 27.54) | 0.27 |
| No | (ref) | – | – |
| Yes | 3.84 | (1.05, 14.00) |
Bolded values = p<0.05.
Child overall behavior defined as none to small (ref) vs. moderate-to-large; logistic regression models with income prior to COVID-19 and food security post-onset of COVID-19.
Loss of employment or reduced pay for one or both caregivers.
Receiving food resources including, SNAP, WIC, food stamps, mobile meals, food pantry, school meals, meals for elderly, etc.