| Literature DB >> 35302447 |
Shahram Lotfipour1,2, Nikhil Shah3, Hina Patel4, Soheil Saadat1, Tim Bruckner5, Parvati Singh6, Bharath Chakravarthy1.
Abstract
INTRODUCTION: Our goal in this study was to identify stimulant abuser patients who are at specifically high risk of suicide attempt (SAT), in order to prioritize them in preventive and risk mitigation programs.Entities:
Mesh:
Year: 2022 PMID: 35302447 PMCID: PMC8967467 DOI: 10.5811/westjem.2021.8.51022
Source DB: PubMed Journal: West J Emerg Med ISSN: 1936-900X
Prevalence of stimulant abuse per emergency department visits, according to patients’ characteristics.
| Demographics | Stimulants Abuse | |||
|---|---|---|---|---|
|
| ||||
| No | Yes | |||
|
|
| |||
| Count | Row % | Count | Row % | |
| Age group | ||||
| 0–10 | 1,768,307 | 100.0% | 237 | 0.0% |
| 10–20 | 1,112,735 | 98.7% | 14,267 | 1.3% |
| 20–30 | 1,637,599 | 98.2% | 29,655 | 1.8% |
| 30–40 | 1,300,234 | 98.5% | 19,899 | 1.5% |
| 40–50 | 1,289,198 | 98.6% | 18469 | 1.4% |
| 50–60 | 1,141,177 | 99.0% | 11,613 | 1.0% |
| 60–70 | 712,538 | 99.6% | 2,925 | 0.4% |
| 70–80 | 491,645 | 99.9% | 403 | 0.1% |
| 80–90 | 515,341 | 100.0% | 90 | 0.0% |
| Gender | ||||
| Male | 4,465,778 | 98.6% | 61,998 | 1.4% |
| Female | 5,426,236 | 99.4% | 35,214 | 0.6% |
| Race | ||||
| White | 4,119,855 | 98.9% | 44,413 | 1.1% |
| Black | 1,079,244 | 98.2% | 19,593 | 1.8% |
| Hispanic | 3,515,411 | 99.3% | 25,526 | 0.7% |
| Asian/Pacific | 453,282 | 99.6% | 1,799 | 0.4% |
| Native American | 18,253 | 98.2% | 335 | 1.8% |
| Other | 321,250 | 99.1% | 2,782 | 0.9% |
| Median household income state quartile for patient ZIP Code | ||||
| 1 | 3,087,808 | 98.8% | 38,239 | 1.2% |
| 2 | 2,684,738 | 99.1% | 24,087 | 0.9% |
| 3 | 2,289,600 | 99.2% | 18,698 | 0.8% |
| 4 | 1,702,577 | 99.3% | 11,243 | 0.7% |
Figure 1Association of suicide attempt with stimulant abuse in age-gender groups.
Figure 2Association of suicide attempt with stimulant abuse in racial groups.
Association of suicide attempt with stimulant abuse and different demographic characteristics.
| Variable | Odds ratio | Standard error | Z | P | 95% Confidence interval |
|---|---|---|---|---|---|
| Stimulant abuse | |||||
| Yes (vs No) | 4.18 | .159 | 37.67 | <0.001 | 3.88 – 4.51 |
| Gender | |||||
| Female (vs male) | 1.07 | .017 | 4.59 | <0.001 | 1.04 – 1.11 |
| Age groups | |||||
| 10–20 (vs 0–10) | 92.30 | 14.160 | 29.50 | <0.001 | 68.33 – 124.68 |
| 20–30 (vs 0–10) | 59.45 | 9.11 | 26.67 | <0.001 | 44.04 – 80.27 |
| 30–40 (vs 0–10) | 46.36 | 7.12 | 24.99 | <0.001 | 34.31 – 62.64 |
| 40–50 (vs 0–10) | 41.46 | 6.37 | 24.25 | <0.001 | 30.68 – 56.02 |
| 50–60 (vs 0–10) | 29.70 | 4.57 | 22.02 | <0.001 | 21.96 – 40.16 |
| 60+ (vs 0–10) | 7.89 | 1.23 | 13.25 | <0.001 | 5.82 – 10.72 |
| Race | |||||
| White (vs Black) | 1.89 | .049 | 24.77 | <0.001 | 1.80 – 1.99 |
| Hispanic (vs Black) | 1.07 | .030 | 2.43 | 0.015 | 1.01 – 1.13 |
| Asian/Pacific (vs Black) | 1.18 | .054 | 3.55 | <0.001 | 1.08 – 1.29 |
| Native American (vs Black) | 1.61 | .228 | 3.35 | 0.001 | 1.22 – 2.12 |
| Others (vs Black) | 1.58 | .068 | 10.60 | <0.001 | 1.45 – 1.72 |
| Interactions | |||||
| Stimulant by Female | 1.49 | .080 | 7.36 | <0.001 | 1.34 – 1.65 |
| Model Constant | .0001 | 0.00001 | −63.79 | ||
Pseudo R2 = 0.05 (Standard error adjusted for 4,528,235 clusters).