| Literature DB >> 29282091 |
Rafael Alves Guimarães1,2, Vivianne de Oliveira Landgraf de Castro3, Sandra Maria do Valle Leone de Oliveira3, Andréa Cristina Stabile3, Ana Rita Coimbra Motta-Castro3,4, Megmar Aparecida Dos Santos Carneiro1, Lyriane Apolinário Araujo1, Karlla Antonieta Amorim Caetano2, Marcos André de Matos2, Sheila Araujo Teles5.
Abstract
BACKGROUND: The aim of this study was to compare sociodemographic characteristics, patterns of drug use, and risky sexual behaviour among female and male users of crack cocaine.Entities:
Keywords: Crack cocaine users; Gender; Sexual risky behaviours; Syphilis
Mesh:
Substances:
Year: 2017 PMID: 29282091 PMCID: PMC5745789 DOI: 10.1186/s12888-017-1569-7
Source DB: PubMed Journal: BMC Psychiatry ISSN: 1471-244X Impact factor: 3.630
Characteristics of crack users in Central Brazil, by gender
| Variables | Total | Men | Female |
|
|---|---|---|---|---|
| Sociodemographic characteristics ( | ||||
| Age (years), median (IQR)a | 30.0 (12.0) | 31.43 (8.9) | 30.60 (8.4) | 0.506 |
| Low educationb , | 570 (62.0) | 484 (61.8) | 86 (63.2) | 0.753 |
| Single marital status, | 713 (77.6) | 612 (78.3) | 101 (74.3) | 0.302 |
| Non-white race/ethnicity, | 637 (69.3) | 541 (69.1) | 96 (70.6) | 0.727 |
| History of homelessnessc, | 161 (17.5) | 133 (17.0) | 28 (20.6) | 0.308 |
| Previous incarcerationd ( | 458 (49.8) | 415 (53.0) | 43 (31.6) |
|
| Pattern of crack/similar and psychoactive substances use ( | ||||
| Age at first illicit drug use, median (IQR)a | 16 (6) | 16 (5) | 18 (9) |
|
| Duration of crack/similar use (months), median (IQR)a | 24.0 (52.0) | 24.0 (52.0) | 36.0 (50.7) | 0.589 |
| Daily crack consumption, | 551 (60.0) | 455 (58.1) | 96 (70.6) |
|
| Sharing of pipec, | 645 (70.2) | 547 (70.0) | 98 (72.0) | 0.612 |
| Smoking mixed crack and tobaccoc, | 377 (41.1) | 334 (42.7) | 43 (31.9) |
|
| Smoking mixed crack and marijuanac, | 397 (43.2) | 350 (44.7) | 47 (34.8) |
|
| Alcoholc , | 676 (73.6) | 581 (74.2) | 95 (69.9) | 0.288 |
| Marijuanac, | 586 (63.8) | 516 (65.9) | 70 (51.5) |
|
| Intranasal cocainec, | 503 (54.7) | 442 (56.4) | 61 (44.9) |
|
| Injecting drugsd, | 93 (10.1) | 77 (9.8) | 16 (11.9) | 0.473 |
| Sexual behaviours | ||||
| Homosexual orientation ( | 98 (12.0) | 82 (11.9) | 16 (12.6) | 0.833 |
| Sexual violenced ( | 115 (12.6) | 64 (8.2) | 51 (38.1) |
|
| Exchanging sex for money and/or drugsc ( | 177 (20.6) | 122 (16.8) | 55 (42.0) |
|
| Number of sexual partners ( | 3.0 (4.0) | 3.0 (2.0) | 4.0 (9.0) |
|
| Any unprotected sexual intercourse with steady partnerc ( | 431 (83.5) | 346 (83.0) | 85 (85.9) | 0.487 |
| Any unprotected sexual intercourse with casual partnerc ( | 301 (59.1) | 259 (56.5) | 42 (59.2) | 0.951 |
| Any unprotected anal intercoursec ( | 311 (66.0) | 272 (64.9) | 39 (75.0) | 0.148 |
| STIe historyc ( | 258 (28.6) | 224 (29.1) | 34 (25.6) | 0.406 |
| Syphilis prevalence (+)f ( | 109 (11.9) | 72 (9.2) | 37 (27.2) |
|
aInterquartile range
bDefined as elementary and middle schools (completed or not)
cPrevious six months
dLifetime
eSexually transmitted infections
fELISA positivity
gPearson’s chi-squared (qualitative variables) or Wilcoxon–Mann–Whitney (quantitative variables)
Fig. 1Results of chi-squared automatic interaction detector (CHAID) model for previous prison and pattern of drug use in crack users in Central Brazil
Fig. 2Results of chi-squared automatic interaction detector (CHAID) model sexual risk and syphilis prevalence in crack users in Central Brazil