| Literature DB >> 31697736 |
Lauren Dayton1, Rachel E Gicquelais2, Karin Tobin1, Melissa Davey-Rothwell1, Oluwaseun Falade-Nwulia3, Xiangrong Kong4, Michael Fingerhood5,6, Abenaa A Jones1, Carl Latkin1.
Abstract
BACKGROUND: Fatal opioid overdose is a pressing public health concern in the United States. Addressing barriers and augmenting facilitators to take-home naloxone (THN) access and administration could expand program reach in preventing fatal overdoses.Entities:
Mesh:
Substances:
Year: 2019 PMID: 31697736 PMCID: PMC6837378 DOI: 10.1371/journal.pone.0224686
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.752
Bivariate correlates of access and administration of take-home naloxone (THN) among people who use opioids in Baltimore, MD, USA.
| THN Access | THN Administration | |||||
|---|---|---|---|---|---|---|
| No (n = 197) | Yes (n = 380) | No (n = 177) | Yes (n = 168) | |||
| Age (years) | ||||||
| 40–49 | 47 (23%) | 94 (25%) | 0.003 | 50 (28%) | 35 (21%) | <0.001 |
| 50–55 | 48 (24%) | 97 (25%) | 49 (28%) | 36 (21%) | ||
| 56+ | 61 (31%) | 70 (18%) | 41 (23%) | 24 (14%) | ||
| Male | 136 (69%) | 244 (64%) | 0.246 | 110 (62%) | 114 (68%) | 0.267 |
| High school/GED+ | 106 (54%) | 248 (65%) | 0.007 | 107 (60%) | 115 (68%) | 0.121 |
| Homeless (past 6 mos.) | 83 (42%) | 187 (49%) | 0.106 | 69 (39%) | 105 (63%) | <0.001 |
| Carry THN Often/Always | --- | --- | 30 (17%) | 77 (46%) | <0.001 | |
| Injected (past 12 mos.) | 107 (54%) | 256 (67%) | 0.002 | 100 (56%) | 136 (81%) | <0.001 |
| Ever overdosed | 99 (50%) | 281 (74%) | <0.001 | 131 (74%) | 131 (78%) | 0.389 |
| No. of overdoses witnessed | ||||||
| 0 | 38 (19%) | 35 (9%) | 0.001 | --- | --- | |
| 1 to 2 | 52 (27%) | 78 (20%) | 58 (33%) | 20 (12%) | <0.001 | |
| 3 to 4 | 41 (21%) | 94 (25%) | 55 (31%) | 39 (23%) | ||
| 5 to 9 | 28 (14%) | 67 (18%) | 28 (16%) | 39 (23%) | ||
| 10 + | 38 (19%) | 106 (28%) | 36 (20%) | 70 (42%) | ||
| >50% of heroin supply has fentanyl | 99 (50%) | 228 (60%) | 0.025 | 97 (55%) | 112 (67%) | 0.024 |
| Perception of insufficient overdose training | 143 (73%) | 185 (49%) | <0.001 | 105 (59%) | 58 (35%) | <0.001 |
| Perception that Narcan recipient will become aggressive | 74 (38%) | 77 (20%) | <0.001 | 48 (27%) | 22 (13%) | 0.001 |
| Perception that police will threaten people at overdose scene | 109 (55%) | 184 (48%) | 0.115 | 82 (46%) | 85 (51%) | 0.428 |
| Medication-Assisted Treatment | 82 (42%) | 281 (74%) | <0.001 | 135 (76%) | 120 (71%) | 0.306 |
| Currently have health insurance coverage | 175 (89%) | 354 (93%) | 0.074 | 167 (94%) | 154 (92%) | 0.327 |
---variable not included in the model
Multivariable model of correlates of access and administration take-home naloxone (THN) among people who use opioids in Baltimore, MD, USA.
| THN Access | THN Administration | |||
|---|---|---|---|---|
| aOR (95% CI) | aOR (95% CI) | |||
| Age | ||||
| 40–49 | 0.86 (0.48–1.55) | 0.612 | 0.55 (0.28–1.07) | 0.080 |
| 50–55 | 1.00 (0.55–1.81) | 0.992 | 0.75 (0.36–1.54) | 0.429 |
| 56+ | 0.70 (0.38–1.29) | 0.258 | 0.66 (0.31–1.40) | 0.276 |
| Male | 0.78 (0.50–1.19) | 0.249 | 0.96 (0.55–1.70) | 0.901 |
| High school/GED+ | 1.68 (1.13–2.50) | 0.010 | 1.37 (0.80–2.36) | 0.254 |
| Homeless | --- | --- | 1.82 (1.08–3.07) | 0.024 |
| Carry THN Often/Always | --- | --- | 3.47 (1.99–6.06) | < .001 |
| Injected in past 12mo | --- | --- | 2.61 (1.43–4.76) | 0.002 |
| Ever overdosed | 2.68 (1.79–4.01) | <0.001 | 0.61 (0.33–1.12) | 0.110 |
| No. of overdoses witnessed | ||||
| 3–4 | --- | --- | 2.02 (0.98–4.16) | 0.057 |
| 5–9 | --- | --- | 5.18 (2.22–12.07) | < .001 |
| 10+ | --- | --- | 5.73 (2.79–11.75) | < .001 |
| Perception of insufficient overdose training | 0.43 (0.28–0.68) | <0.001 | 0.56 (0.32–0.96) | 0.034 |
| Perception that Narcan recipient will become aggressive | 0.55 (0.35–0.85) | 0.007 | 0.54 (0.28–1.04) | 0.064 |
| Perception that police will threaten people at overdose scene | 0.68 (0.46–1.00) | 0.052 | --- | --- |
| Medication-Assisted Treatment | 3.87 (2.59–5.78) | <0.001 | --- | --- |
---variable not included in the model