| Literature DB >> 33105965 |
Kevin Kc Hung1,2,3, Joseph H Walline1, Emily Ying Yang Chan1,2,3,4, Zhe Huang2,3, Eugene Siu Kai Lo2,3, Eng Kiong Yeoh3, Colin A Graham1,2,3.
Abstract
BACKGROUND: As health systems across the world respond to the coronavirus disease 2019 (COVID-19), there is rising concern that patients without COVID-19 are not receiving timely emergency care, resulting in avoidable deaths. This study examined patterns of self-reported health service utilization, their socio-demographic determinants and association with avoidable deaths during the COVID-19 outbreak.Entities:
Keywords: Access to Healthcare; Fear of Infection; Health Seeking Behavior
Mesh:
Year: 2022 PMID: 33105965 PMCID: PMC9309937 DOI: 10.34172/ijhpm.2020.183
Source DB: PubMed Journal: Int J Health Policy Manag ISSN: 2322-5939
Respondent Characteristics and Health Service Avoidance
|
|
|
|
|
| |
| Gender | |||||
| Male | 356 (46.5%) | 80 (22.5%) | <0.001 | 0.460 (0.323-0.655) | <0.001 |
| Female | 409 (53.5%) | 152 (37.2%) | 1 | ||
| Age group | |||||
| 18-24 | 71 (9.3%) | 21 (29.6%) | 0.080 | ||
| 25-44 | 248 (32.4%) | 89 (35.9%) | |||
| 45-64 | 303 (39.6%) | 88 (29.1%) | |||
| 65 or older | 143 (18.7%) | 34 (23.8%) | |||
| Marital status | |||||
| Non-married | 304 (39.9%) | 82 (27.0%) | 0.090 | 0.692 (0.483-0.991) | 0.044 |
| Married | 459 (60.1%) | 150 (32.8%) | 1 | ||
| Education level | |||||
| Primary level or below | 61 (8.0%) | 9 (14.8%) | 0.002 | 0.328 (0.149-0.721) | 0.005 |
| Secondary | 330 (43.3%) | 91 (27.7%) | 0.651 (0.455-0.933) | ||
| Tertiary level | 371 (48.7%) | 131 (35.3%) | 1 | ||
| Profession | |||||
| White collar | 341 (45.2%) | 120 (35.2%) | 0.040 | ||
| Blue collar (including services or sales) | 128 (17.0%) | 31 (24.2%) | |||
| Homemaker | 93 (12.3%) | 30 (32.3%) | |||
| Student | 47 (6.2%) | 15 (31.9%) | |||
| Unemployed or retired | 145 (19.2%) | 33 (22.8%) | |||
| Religion | |||||
| No religion | 509 (67.2%) | 150 (29.5%) | 0.390 | ||
| Any | 249 (32.8%) | 81 (32.5%) | |||
| Chronic disease | |||||
| No | 624 (81.6%) | 191 (30.7%) | 0.713 | ||
| Yes | 141 (18.4%) | 41 (29.1%) | |||
| Flu vaccine in the past 12 months | |||||
| No | 560 (73.5%) | 164 (29.3%) | 0.252 | ||
| Yes | 202 (26.5%) | 68 (33.7%) | |||
| Household income (monthly HK$) | |||||
| <2000-7999 | 66 (9.2%) | 13 (19.7%) | 0.135 | ||
| 8000-19 999 | 100 (13.9%) | 27 (26.7%) | |||
| 20 000-39 999 | 191 (26.6%) | 65 (34.0%) | |||
| 40 000 or more | 360 (50.2%) | 114 (31.7%) | |||
| Residential district | |||||
| Hong Kong Island | 147 (19.2%) | 57 (38.8%) | 0.046 | 1.659 (1.059-2.599) | 0.069 |
| Kowloon | 231 (30.2%) | 67 (29.0%) | 1.020 (0.688-1.512) | ||
| New territories | 387 (50.6%) | 108 (28.0%) | 1 | ||
| Housing type | |||||
| Public housing | 219 (28.6%) | 62 (28.4%) | 0.054 | ||
| Subsidized housing | 108 (14.2%) | 24 (22.2%) | |||
| Private housing | 435 (57.2%) | 146 (33.6%) | |||
| Household members younger than 15 or older than 59 | |||||
| No | 264 (34.8%) | 72 (27.3%) | 0.179 | ||
| Yes | 495 (65.2%) | 158 (32.0%) | |||
| Having a very high risk of contracting COVID-19 in year 2020 | |||||
| Disagree or totally disagree | 332 (44.1%) | 86 (25.9%) | 0.025 | ||
| Neutral | 286 (38.0%) | 103 (36.0%) | |||
| Agree or totally agree | 136 (17.9%) | 41 (30.4%) | |||
| Effect of COVID-19 on your physical health | |||||
| Small or very small effect | 192 (25.3%) | 39 (20.3%) | 0.002 | 0.655 (0.398-1.078) | 0.097 |
| Neutral | 173 (22.8%) | 59 (34.1%) | 1.167 (0.752-1.811) | ||
| Large or very large effect | 394 (51.8%) | 133 (33.8%) | 1 | ||
| Effect of COVID-19 on your mental health | |||||
| Small or very small effect | 193 (25.3%) | 38 (19.7%) | <0.001 | 0.524 (0.313-0.878) | 0.047 |
| Neutral | 213 (27.9%) | 65 (30.5%) | 0.788 (0.514-1.178) | ||
| Large or very large effect | 358 (46.8%) | 129 (36.1%) | 1 | ||
| Enough knowledge to deal with COVID-19 outbreak to protect personal health | |||||
| Lacking or very lacking | 95 (12.4%) | 24 (25.3%) | 0.015 | 0.962 (0.546-1.694) | 0.082 |
| Neutral | 304 (39.7%) | 110 (36.3%) | 1.469 (1.020-2.116) | ||
| Sufficient or very sufficient | 366 (47.9%) | 98 (26.8%) | 1 | ||
Abbreviations: OR, odds ratio; COVID-19, coronavirus disease 2019.
a Based on the response to the question: ‘Have you avoided medical consultation since January 2020?’ (missing response to this question was excluded from subsequent analyses).
b Chi square tests.
c Binary logistic regression analysis including all listed variables.
Reported Changes to Utilisation of Various Healthcare Services
|
|
|
| |
| Visiting private general practitioners | 21 (2.7%) | 505 (66.1%) | 238 (31.2%) |
| Visiting public general out-patient clinics | 17 (2.2%) | 546 (71.7%) | 199 (26.1%) |
| Visiting hospital EDs | 17 (2.2%) | 554 (72.6%) | 192 (25.2%) |
| Admission to public hospitals (if advised by a physician) | 21 (2.7%) | 611 (80.0%) | 132 (17.3%) |
| Admission to private hospitals (if advised by a physician) | 23 (3.0%) | 629 (82.2%) | 113 (14.8%) |
Abbreviation: ED, emergency department.