Full sample (n = 2890) | Propensity score* matched pairs (n = 1010, 505 matched pairs) | |||
---|---|---|---|---|
Group 1 (Lowest) n = 1390 | Group 3 (Highest) n = 1434 | Group 1 (Lowest) n = 505 | Group 3 (Highest) n = 505 | |
*Propensity scores constructed by modelling the odds of living in the lowest neighbourhood tertile (compared with the highest tertile) as a function of age, sex, income (nine categories shown), education (five categories shown), occupation (five categories shown), the interactions of sex with all other covariates, and all two way interactions between income, education, and occupation. For the full sample, distributions of income, education, and occupation differed significantly across groups (p<0.0001 for all three). For the propensity score matched sets, distributions of income, education, and occupation did not differ significantly across groups (p = 0.8 for income; p = 0.3 for education; and p = 0.5 for occupation). | ||||
% Female | 59 | 56 | 58.2 | 57.2 |
Mean age | 72.7 | 72.9 | 72.6 | 72.7 |
Income (% distribution) | ||||
<$5000 | 5.9 | 0.8 | 1.0 | 1.8 |
$5000–$7999 | 11.0 | 2.4 | 5.9 | 4.6 |
$8000–$11999 | 14.8 | 5.3 | 9.9 | 9.5 |
$12000–$15999 | 19.6 | 8.9 | 14.1 | 16.0 |
$16000–$24999 | 20.7 | 14.9 | 25.7 | 24.6 |
$25000–$34999 | 14.0 | 15.3 | 16.4 | 18.2 |
$35,000–$49999 | 4.9 | 14.6 | 9.7 | 10.3 |
⩾$50000 | 4.5 | 28.8 | 10.5 | 8.3 |
Unknown | 4.8 | 9.0 | 6.9 | 6.7 |
Education (% distribution) | ||||
Less than complete high school | 42.0 | 10.6 | 20.0 | 22.4 |
Complete high school | 39.2 | 33.0 | 48.3 | 46.9 |
1–3 years college | 8.9 | 18.1 | 16.4 | 13.5 |
Complete 4 year college | 5.4 | 20.0 | 8.1 | 11.1 |
Graduate school | 4.5 | 18.3 | 7.1 | 6.1 |
Occupation (%distribution) | ||||
Professional/technical/managers | 25.3 | 47.2 | 37.4 | 36.1 |
Sales/clerical/service | 13.9 | 18.3 | 17.6 | 21.4 |
Craftsmen/machine operators/ farming/forestry | 25.0 | 6.4 | 12.9 | 14.9 |
Homemaker | 24.5 | 21.7 | 22.0 | 19.3 |
Other/missing | 11.3 | 6.4 | 10.1 | 8.3 |