| Literature DB >> 32556260 |
Marcella Alsan1,2,3, Stefanie Stantcheva3,4, David Yang3,4, David Cutler3,4.
Abstract
Importance: Data from the coronavirus disease 2019 (COVID-19) pandemic in the US show large differences in hospitalizations and mortality across race and geography. However, there are limited data on health information, beliefs, and behaviors that might indicate different exposure to risk. Objective: To determine the association of sociodemographic characteristics with reported incidence, knowledge, and behavior regarding COVID-19 among US adults. Design, Setting, and Participants: A US national survey study was conducted from March 29 to April 13, 2020, to measure differences in knowledge, beliefs, and behavior about COVID-19. The survey oversampled COVID-19 hotspot areas. The survey was conducted electronically. The criteria for inclusion were age 18 years or older and residence in the US. Data analysis was performed in April 2020. Main Outcomes and Measures: The main outcomes were incidence, knowledge, and behaviors related to COVID-19 as measured by survey response.Entities:
Mesh:
Year: 2020 PMID: 32556260 PMCID: PMC7303811 DOI: 10.1001/jamanetworkopen.2020.12403
Source DB: PubMed Journal: JAMA Netw Open ISSN: 2574-3805
Demographic Characteristics: Survey Sample vs US Census
| Characteristic | Survey sample, participants, No. (%) | US population, % | ||
|---|---|---|---|---|
| Inside hotspot | Outside hotspot | Total (N = 5198) | ||
| Sex | ||||
| Male | 487 (45) | 1849 (45) | 2336 (45) | 48 |
| Female | 591 (55) | 2259 (55) | 2850 (55) | 52 |
| Age, y | ||||
| 18-29 | 240 (22) | 813 (20) | 1053 (20) | 27 |
| 30-39 | 254 (23) | 599 (14) | 853 (16) | 19 |
| 40-49 | 194 (18) | 514 (12) | 708 (14) | 21 |
| 50-59 | 133 (12) | 722 (18) | 855 (16) | 20 |
| 60-69 | 133 (12) | 828 (20) | 961 (18) | 14 |
| Race/ethnicity | ||||
| White | 775 (72) | 2984 (73) | 3759 (72) | 77 |
| Black or African American | 178 (16) | 652 (16) | 830 (16) | 13 |
| Hispanic | 129 (12) | 480 (12) | 609 (12) | 18 |
| Annual gross household income | ||||
| <$25 000 | 188 (17) | 941 (23) | 1129 (22) | 19 |
| $25 000-$49 999 | 199 (18) | 850 (21) | 1049 (20) | 21 |
| $50 0000-$74 999 | 165 (15) | 758 (18) | 923 (18) | 17 |
| $75 000-$99 999 | 162 (15) | 576 (14) | 738 (14) | 12 |
| ≥$100 000 | 368 (34) | 991 (24) | 1359 (26) | 30 |
| Employment status | ||||
| Employed | 685 (63) | 2083 (51) | 2768 (53) | 48 |
| Unemployed | 127 (12) | 624 (15) | 751 (14) | 2 |
| College degree | 674 (62) | 1987 (48) | 2661 (51) | 32 |
The table shows summary statistics of demographic characteristics of survey respondents alongside data from the US as a whole (the fifth column). The source for the fifth column is the US Census Bureau and Current Population Survey, 2018.
The following areas were considered hotspots: New York, New York; New Orleans, Louisiana; Detroit, Michigan; and Seattle, Washington. Residence in a hotspot was coded as a binary variable, which was equal to 1 if the respondent lived in any of the 4 hotspot areas, or 0 otherwise.
Survey Summary Statistics of Major Outcomes: Full Sample and by Hotspot
| Variable | Participants, No. (%) | ||
|---|---|---|---|
| Total (N = 5198) | Inside hotspot (n = 1082) | Outside hotspot (n = 4116) | |
| Knowledge about spread | |||
| Through respiratory droplets | 4339 (86.0) | 875 (83.0) | 3464 (86.0) |
| Through close contact | 3932 (78.0) | 801 (76.0) | 3131 (78.0) |
| Through a contaminated surface | 4215 (83.0) | 853 (81.0) | 3362 (84.0) |
| Spread without showing symptoms | 4778 (94.0) | 978 (93.0) | 3800 (95.0) |
| Through unprotected sex | 553 (10.9) | 145 (13.7) | 408 (10.2) |
| The virus is a hoax | 257 (5.1) | 86 (8.2) | 171 (4.3) |
| Knowledge about symptoms | |||
| Fever | 4758 (94.0) | 972 (92.0) | 3786 (94.0) |
| Cough | 4770 (94.0) | 968 (92.0) | 3802 (95.0) |
| Difficulty in breathing | 4681 (92.0) | 951 (90.0) | 3730 (93.0) |
| All 3 symptoms | 4404 (87.0) | 887 (84.0) | 3517 (88.0) |
| Any other symptoms reported | 512 (10.0) | 131 (12.0) | 381 (9.0) |
| Reports COVID-19 infection | |||
| Self | 214 (4.0) | 74 (7.0) | 140 (3.0) |
| Other | 1208 (23.0) | 434 (40.0) | 774 (19.0) |
| Subjective likelihood, mean (SD), score | |||
| Likelihood of getting sick from COVID-19 in next month, score 0-10 | 3.9 (2.5) | 4.1 (2.5) | 3.9 (2.5) |
| No. of community members likely to get sick from COVID-19 in next month, score 0-100 | 37.6 (30.2) | 46.7 (30.5) | 35.2 (29.7) |
| Behaviors, mean (SD), No. of times | |||
| Handwashing in last 24 h | 13.2 (13.5) | 13.0 (13.0) | 13.2 (13.6) |
| Left home in 3 d | 2.5 (4.0) | 2.8 (4.6) | 2.4 (3.8) |
| Frequent hospital use | 675 (13.0) | 180 (17.0) | 495 (12.0) |
| Ease of accessing testing, mean (SD), score 0-10 | 4.2 (2.9) | 4.3 (3.1) | 4.2 (2.9) |
Abbreviation: COVID-19, coronavirus disease 2019.
No. is the number eligible to answer. A small number of people did not answer each question.
0 = extremely difficult; 10 = extremely easy.
Figure 1. Association of Demographic Characteristics, Socioeconomic Status, Geographic Location, and Political Orientation With the Probability of Having Coronavirus Disease 2019 (COVID-19) or Knowing Someone Who Does
Figure 2. Factors Associated With Knowledge About the Symptoms and Spread of Coronavirus Disease 2019 (COVID-19)
Figure 3. Factors Associated With Handwashing and Leaving the House