| Literature DB >> 25377274 |
Anna Hayden, Kanna Hayashi, Huiru Dong, Michael-John Milloy, Thomas Kerr, Julio S G Montaner, Evan Wood1.
Abstract
BACKGROUND: Illicit drug use is a well-established risk factor for morbidity and mortality. However, few studies have examined the impact of different drug use patterns on mortality among polysubstance using populations. This study aimed to identify drug-specific patterns of mortality among a cohort of polysubstance using persons who inject drugs (PWIDs).Entities:
Mesh:
Year: 2014 PMID: 25377274 PMCID: PMC4246520 DOI: 10.1186/1471-2458-14-1153
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Baseline demographics of the study population stratified by daily cocaine injection in the past 6 months (n = 2330)
| Characteristic | Total (%) | Daily cocaine injection | |||
|---|---|---|---|---|---|
| Yes (%) | No (%) | Odds ratio (95% CI) |
| ||
| ( | ( | ( | |||
|
| |||||
| Positive | 640 (27.5) | 212 (29.1) | 426 (26.8) | 1.12 (0.92 – 1.36) | 0.247 |
| Negative | 1688 (72.5) | 515 (70.7) | 1161 (73.1) | ||
|
| |||||
| Male | 1550 (66.5) | 444 (61.0) | 1098 (69.1) | 0.70 (0.58 – 0.84) | <0.001 |
| Female | 780 (33.5) | 284 (39.0) | 490 (30.9) | ||
|
| |||||
| Caucasian | 1424 (61.1) | 413 (56.7) | 1001 (63.0) | 0.77 (0.64 – 0.92) | 0.004 |
| Other | 906 (38.9) | 315 (43.3) | 587 (37.0) | ||
|
| |||||
| Yes | 1637 (70.3) | 556 (76.4) | 1072 (67.5) | 1.62 (1.32 – 1.99) | <0.001 |
| No | 677 (29.1) | 163 (22.4) | 509 (32.1) | ||
|
| |||||
| Per 10 year older | 37.3 (14.3) | 35.3 (13.4) | 38.4 (14.1) | 0.76 (0.69 – 0.83) | <0.001 |
|
| |||||
| Per 10 year longer | 14.4 (18.0) | 14.1 (16.3) | 14.6 (18.8) | 0.91 (0.84 – 0.99) | 0.033 |
|
| |||||
| Yes | 550 (23.6) | 179 (24.6) | 368 (23.2) | 1.10 (0.88 – 1.33) | 0.450 |
| No | 1775 (76.2) | 547 (75.1) | 1217 (76.6) | ||
|
| |||||
| Yes | 901 (38.7) | 345 (47.4) | 555 (35.0) | 1.68 (1.40 – 2.00) | <0.001 |
| No | 1424 (61.1) | 383 (52.6) | 1033 (65.1) | ||
|
| |||||
| Yes | 97 (4.2) | 30 (4.1) | 66 (4.2) | 0.99 (0.64 – 1.54) | 0.969 |
| No | 2230 (95.7) | 697 (95.7) | 1520 (95.7) | ||
|
| |||||
| Yes | 51 (2.2) | 7 (1.0) | 44 (2.8) | 0.34 (0.15 – 0.76) | 0.006 |
| No | 2274 (97.6) | 721 (99.0) | 1542 (97.1) | ||
|
| |||||
| Yes | 7 (0.3) | 1 (0.1) | 6 (0.4) | 0.36 (0.04 – 3.02) | 0.445† |
| 2322 (99.7) | 727 (99.9) | 1581 (99.6) | |||
|
| |||||
| Yes | 560 (24.0) | 137 (18.8) | 420 (26.5) | 0.65 (0.52 – 0.80) | <0.001 |
| No | 1767 (75.8) | 589 (80.9) | 1167 (73.5) | ||
|
| |||||
| Yes | 288 (12.4) | 216 (29.7) | 71 (4.5) | 9.01 (6.77 – 12.00) | <0.001 |
| No | 2038 (87.5) | 512 (70.3) | 1516 (95.5) | ||
*Refers to activities in the six months prior to interview. IQR = Interquartile range. †Fisher’s Exact Test.
Univariate and multivariate Cox proportional hazard regression analyses of the time to all-cause death among people who inject drugs in Vancouver, Canada (n = 2330)
| Unadjusted hazard ratio (HR) | Adjusted † hazard ratio (AHR) | |||||
|---|---|---|---|---|---|---|
| Variable | HR | (95% CI) |
| AHR | (95% CI) |
|
|
| 0.98 | 0.77 – 1.25 | 0.854 | 1.00 | 0.78 – 1.28 | 0.979 |
|
| 0.75 | 0.60 – 0.95 | 0.018 | 0.92 | 0.71 – 1.19 | 0.502 |
|
| 1.12 | 0.51 – 2.44 | 0.779 | 1.44 | 0.68 – 3.07 | 0.340 |
|
| 1.41 | 1.12 – 1.78 | 0.003 | 1.36 | 1.06 – 1.76 | 0.017 |
|
| 0.39 | 0.10 – 1.54 | 0.177 | 0.41 | 0.10 – 1.72 | 0.224 |
|
| 1.13 | 0.29 – 4.50 | 0.859 | 0.94 | 0.13 – 6.88 | 0.949 |
|
| 0.91 | 0.74 – 1.12 | 0.358 | 0.83 | 0.67 – 1.04 | 0.099 |
|
| 1.02 | 0.69 – 1.52 | 0.917 | 0.98 | 0.62 – 1.56 | 0.944 |
*Refers to activities in the six months prior to interview. †Model was adjusted for HIV serostatus, age, and unstable housing.