| Literature DB >> 32532050 |
Evan Su Wei Shang1,2, Eugene Siu Kai Lo1, Zhe Huang1,2, Kevin Kei Ching Hung1,3, Emily Ying Yang Chan1,2,3,4.
Abstract
Although much of the health emergency and disaster risk management (Health-EDRM) literature evaluates methods to protect health assets and mitigate health risks from disasters, there is a lack of research into those who have taken high-risk behaviour during extreme events. The study's main objective is to examine the association between engaging in high-risk behaviour and factors including sociodemographic characteristics, disaster risk perception and household preparedness during a super typhoon. A computerized randomized digit dialling cross-sectional household survey was conducted in Hong Kong, an urban metropolis, two weeks after the landing of Typhoon Mangkhut. Telephone interviews were conducted in Cantonese with adult residents. The response rate was 23.8% and the sample was representative of the Hong Kong population. Multivariable logistic regressions of 521 respondents adjusted with age and gender found education, income, risk perception and disaster preparedness were insignificantly associated with risk-taking behaviour during typhoons. This suggests that other factors may be involved in driving this behaviour, such as a general tendency to underestimate risk or sensation seeking. Further Health-EDRM research into risk-taking and sensation seeking behaviour during extreme events is needed to identify policy measures.Entities:
Keywords: Health-EDRM; cyclone; hurricane; natural disaster; risk-taking behaviour; sensation seeking; strong wind levels; typhoon; urban
Mesh:
Year: 2020 PMID: 32532050 PMCID: PMC7312186 DOI: 10.3390/ijerph17114150
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1The recruitment details in the telephone survey.
Descriptive table of the study population.
| Characteristics | Go Outdoor for Emergency/Work Reasons ( | Go Outdoor for Non-Essential Reasons ( | Did Not Go Outdoor ( | ||
|---|---|---|---|---|---|
| Gender | Male | 9 (42.9%) | 38 (61.3%) | 174 (39.7%) | 0.006 |
| Female | 12 (57.1%) | 24 (38.7%) | 264 (60.3%) | ||
| Age | 18–24 | 2 (9.5%) | 14 (22.6%) | 47 (10.7%) | 0.078 |
| 25–44 | 9 (42.9%) | 18 (29.0%) | 127 (29.0%) | ||
| 45–64 | 9 (42.9%) | 24 (38.7%) | 191 (43.6%) | ||
| ≥65 | 1 (4.8%) | 6 (9.7%) | 73 (16.7%) | ||
| Education attainment | Primary or below | 2 (10.0%) | 5 (8.1%) | 49 (11.3%) | 0.407 |
| Secondary | 7 (35.0%) | 18 (29.0%) | 170 (39.2%) | ||
| Post-secondary | 11 (55.0%) | 39 (62.9%) | 215 (49.5%) | ||
| Marital status | Single | 8 (38.1%) | 28 (45.2%) | 176 (40.2%) | 0.734 |
| Married | 13 (61.9%) | 34 (54.8%) | 262 (59.8%) | ||
| Income | <2000–9999 | 0 (0.0%) | 5 (8.9%) | 40 (9.9%) | 0.462 |
| 10,000–19,999 | 2 (10.5%) | 5 (8.9%) | 66 (16.3%) | ||
| 20,000–39,999 | 6 (31.6%) | 21 (37.5%) | 133 (32.9%) | ||
| ≥40,000 | 11 (57.9%) | 25 (44.6%) | 165 (40.8%) | ||
| Occupation | Manager/Professional/Clerk | 9 (45.0%) | 24 (41.4%) | 151 (35.4%) | |
| Sales & Services | 5 (25.0%) | 2 (3.4%) | 35 (8.2%) | ||
| Craft related/ Machinery labour | 0 (0.0%) | 5 (8.6%) | 20 (4.7%) | 0.033 | |
| Elementary occupation | 3 (15.0%) | 3 (5.2%) | 23 (5.4%) | ||
| Housewives/Students | 1 (5.0%) | 14 (24.1%) | 115 (26.9%) | ||
| Unemployed/Retired | 2 (10.0%) | 10 (17.2%) | 83 (19.4%) | ||
| Chronic disease | Yes | 4 (19.0%) | 10 (16.7%) | 77 (17.7%) | 0.965 |
| No | 17 (81.0%) | 50 (83.3%) | 357 (82.3%) | ||
| Routinely work during typhoon signal no.8 | Yes | 15 (83.3%) | 4 (9.3%) | 35 (13.4%) | <0.001 |
| No | 3 (16.7%) | 39 (90.7%) | 227 (86.6%) | ||
| Occupation involving mainly outdoor work | Yes | 3 (17.6%) | 10 (23.3%) | 43 (16.8%) | 0.591 |
| No | 14 (82.4%) | 33 (76.7%) | 213 (83.2%) | ||
| Channel of obtaining weather information | Television | 12 (57.1%) | 26 (41.9%) | 236 (53.9%) | 0.015 |
| Radio | 0 (0.0%) | 6 (9.7%) | 24 (5.5%) | ||
| Website/Smartphone platform | 6 (28.6%) | 28 (45.2%) | 168 (38.4%) | ||
| Newspaper or others | 3 (14.3%) | 2 (3.2%) | 10 (2.3%) | ||
| Disaster preparation immediately prior to the typhoon | No | 0 (0.0%) | 4 (6.5%) | 28 (6.4%) | 0.489 |
| Yes | 21 (100.0%) | 58 (93.5%) | 410 (93.6%) | ||
Chi-square comparison and multivariable logistic regressions of the associating factors towards non-essential RBDT.
| Factors | χ2 Test | Logistic Regression | ||||
|---|---|---|---|---|---|---|
| Stayed Indoor | Non-essential RBDT | OR (95% CI) | ||||
| Gender a | Male | 174 (39.7%) | 38 (61.3%) | 0.001 | Ref. | |
| Female | 264 (60.3%) | 24 (38.7%) | 0.435 (0.248–0.761) | 0.004 | ||
| Age a | 18–24 | 47 (10.7%) | 14 (22.6%) | 0.041 | Ref. | |
| 25–44 | 127 (29.0%) | 18 (29.0%) | 0.573 (0.260–1.263) | 0.167 | ||
| 45–64 | 191 (43.6%) | 24 (38.7%) | 0.527 (0.248–1.118) | 0.095 | ||
| ≥65 | 73 (16.7%) | 6 (9.7%) | 0.297 (0.106–0.833) | 0.021 | ||
| Education attainment b | Primary or below | 49 (11.3%) | 5 (8.1%) | 0.144 | Ref. | |
| Secondary | 170 (39.2%) | 18 (29.0%) | 0.799 (0.269–2.374) | 0.687 | ||
| Post-secondary | 215 (49.5%) | 39 (62.9%) | 1.110 (0.363–3.392) | 0.854 | ||
| Income b | <2000–9999 | 40 (9.9%) | 5 (8.9%) | 0.517 | Ref. | |
| 10,000–19,999 | 66 (16.3%) | 5 (8.9%) | 0.465 (0.120–1.796) | 0.267 | ||
| 20,000–39,999 | 133 (32.9%) | 21 (37.5%) | 0.897 (0.28–2.784) | 0.851 | ||
| ≥40,000 | 165 (40.98 | 25 (44.6%) | 0.821 (0.264–2.555) | 0.733 | ||
| Perceived Hong Kong to be susceptible to disasters b | No | 35 (8.0%) | 4 (6.5%) | 0.669 | Ref. | |
| Yes | 402 (92.0%) | 58 (93.5%) | 1.474 (0.494–4.398) | 0.486 | ||
| Perceived impact of Typhoon Mangkhut compared to expectations b | Less than expected | 118 (27.1%) | 16 (25.8%) | 0.919 | Ref. | |
| Same as expected | 235 (54.0%) | 33 (53.2%) | 0.919 (0.477–1.773) | 0.802 | ||
| Larger than expected | 82 (18.9%) | 13 (21.0%) | 1.032 (0.462–2.303) | 0.940 | ||
| Concerned for the safety of oneself and family members b | No | 159 (36.3%) | 17 (27.4%) | 0.171 | Ref. | |
| Yes | 279 (63.7%) | 45 (72.6%) | 1.585 (0.860–2.922) | 0.140 | ||
| Practiced disaster preparedness immediately prior to the typhoon b | No | 28 (6.4%) | 4 (6.5%) | 0.986 | Ref. | |
| Yes | 410 (93.6%) | 58 (93.5%) | 1.077 (0.355–3.264) | 0.896 | ||
| Preparedness: routine food reserves b | No | 81 (18.5%) | 7 (11.3%) | 0.163 | Ref. | |
| Yes | 357 (81.5%) | 55 (88.7%) | 1.663 (0.717–3.857) | 0.236 | ||
| Preparedness: routine potable water reserves b | No | 223 (50.9%) | 32 (51.6%) | 0.918 | Ref. | |
| Yes | 215 (49.1%) | 30 (48.4%) | 0.842 (0.484–1.463) | 0.541 | ||
| Preparedness: food reserves specifically for Typhoon Mangkhut b | No | 137 (31.3%) | 25 (40.3%) | 0.154 | Ref. | |
| Yes | 301 (68.7%) | 37 (59.7%) | 0.666 (0.378–1.174) | 0.160 | ||
| Preparedness: potable water reserves specifically for Typhoon Mangkhut b | No | 272 (62.1%) | 39 (62.9%) | 0.903 | Ref. | |
| Yes | 166 (37.9%) | 23 (37.1%) | 0.894 (0.506–1.581) | 0.700 | ||
a is the multivariable regression of age and gender; b is the logistic regression adjusted with age and gender.