Table 1.
Coefficient of significant spatial variables from logistic regression analysis, case-control analysis and Lasso regression analysis. The bold text indicates the significant variables from at least three out of six models.
| Spatial variable |
Government dataset |
Internet dataset |
||||||
|---|---|---|---|---|---|---|---|---|
| Main category | Sub-category | Variable | Logistic regression | Case-control | Lasso regression | Logistic regression | Case-control | Lasso regression |
| Urban geometry | Building geometry | Building height (sum) | 2.132⁎⁎ | 2.710⁎⁎ | 1.159 | 3.210⁎⁎ | 2.240⁎⁎ | 0.951 |
| Building height (standard deviation) | – | – | – | −2.302⁎⁎ | – | – | ||
| Building density (sum) | – | – | – | – | – | 0.273 | ||
| Building density (standard deviation) | −1.590⁎⁎ | −1.797⁎⁎ | −0.030 | −1.536⁎⁎ | −1.924⁎⁎ | −0.140 | ||
| Sky view factor (sum) | – | – | −0.419 | – | – | −0.234 | ||
| Road network | Street length (average) | −2.304⁎⁎ | – | −0.675 | −2.870⁎⁎ | – | −0.226 | |
| Socio-demographic characteristics | Demographic characteristics | Population density | 0.849⁎⁎ | – | 0.213 | – | – | – |
| Age group: 65+ (male) | 1.007⁎⁎ | – | 0.290 | – | – | – | ||
| Educational characteristics | Highest educational attainment: Sub-degree course | – | – | – | 1.316⁎⁎ | – | 0.100 | |
| Economic characteristics | Economic status: Others | – | – | – | – | – | 0.298 | |
| Occupation: Professionals | – | – | – | −2.543⁎⁎ | −1.669⁎⁎ | – | ||
| Occupation: Service and sales workers | – | – | 0.093 | 1.278⁎ | – | 0.325 | ||
| Occupation: Craft and related workers | – | – | – | −3.459⁎⁎ | – | – | ||
| Occupation: Skilled agricultural and fishery workers; and occupations not classifiable | −2.123⁎⁎ | −3.475⁎⁎ | −0.719 | – | – | – | ||
| Industry: Accommodation and food services | – | – | – | – | – | 0.415 | ||
| Industry: Manufacturing | – | – | – | – | – | −0.049 | ||
| Industry: Public administration, education, human health and social work activities | – | – | – | – | – | −0.183 | ||
| Working location: Another district on Hong Kong Island# | – | – | 0.153 | 0.813⁎⁎ | 1.058⁎⁎ | 0.638 | ||
| Working location: Outside Hong Kong | – | – | – | −1.116⁎⁎ | – | – | ||
| Weekly working hours: 18–34 | – | – | – | – | – | 0.108 | ||
| Weekly working hours: 65 and over | – | 1.458⁎ | – | – | – | – | ||
| Median monthly income from main employment (male) | – | −1.723⁎⁎ | – | – | – | – | ||
| Median monthly income from main employment (female) | – | – | – | – | – | −0.073 | ||
| Household characteristics | Median monthly domestic household income | – | – | – | – | – | −0.732 | |
| Housing characteristics | Tenure of accommodation: Owner-occupier (with mortgage and loan) | – | – | −0.018 | – | – | – | |
| Tenure of accommodation: Owner-occupier (without mortgage and loan) | – | – | – | −1.421⁎⁎ | – | – | ||
| Tenure of accommodation: Sole tenant | – | – | – | – | – | 0.309 | ||
| Tenure of accommodation: Co-tenant | −0.642⁎⁎ | – | – | −0.705⁎ | – | – | ||
| Tenure of accommodation: Provided by employer | – | – | – | −1.229⁎ | – | – | ||
⁎⁎
Significant result with p-value < 0.01.
⁎
Significant result with p-value < 0.05.
#
“Working location: Another district on Hong Kong Island” means the number of persons working on Hong Kong Island, excluding the persons living and working in the same district on Hong Kong Island.