Refining HIV Risk: The Modifying Effects of Youth, Gender and Education among People Who Inject Drugs in Poland

<div><p>Objective</p><p>The goal of this study was to examine specific factors placing young (aged <30) women who inject drugs at higher risk for HIV, and to establish the need for targeted interventions within this population.</p><p>Methods</p><p>A national cross-sectional sero-survey was conducted in 2004–2005 in six regions in Poland. A snowball sample of ever-injectors was recruited from drug treatment facilities and the surrounding community. Log-binomial regression was used to estimate adjusted prevalence ratios (PRs).</p><p>Results</p><p>A total of 491 injection drug users younger than 30 were recruited, of whom 159 were women and 332 were men. The prevalence of HIV was 16.4% and 9.6% among women and men, respectively. In multivariate analysis, young female injectors whose education terminated at the primary level were more likely to be HIV-positive compared to males with a similar level of education (PR = 3.34, 95% CI = 1.86–6.00) and more highly educated women (PR = 4.16, 95% CI = 2.21–7.82).</p><p>Conclusions</p><p>This study confirms an elevated risk of HIV among under-educated young women. Suggestions for specific interventions to reduce HIV transmission are presented. Additional research is needed to quantify the differential distribution of risk behaviors which amplify their likelihood of transmission.</p></div

Unadjusted prevalence ratios (PR) calculated in univariate analyses and adjusted prevalence ratios (APR) estimated in log-binomial model fitted for young (<30) PWID, with 95% confidence intervals (CI).

*<p>The final log-binomial model used to estimate APRs included the following terms: Gender (females vs. males), Education (primary vs. more than primary sch.), IDU initiation (<5 years ago vs. ≥5 years ago), Needle sharing (ever vs. never), Sex with PWID (ever vs. never), Cohabiting with spouse/partner (yes vs. no) and an interaction term between Gender and Education. Due to significant interaction between Gender and Education, the effect of Gender is presented separately for lower (primary school) and better educated (more than primary school) study participants, just as effect of Education is presented separately for females and males.</p

Injection risk behaviors of young (<30) female compared to young male PWID.

*<p>when injecting with borrowed needles/syringes.</p>**<p>when injecting with new needles/syringes.</p

Sociodemographic characteristics of young (<30) female compared to young male PWID in a cross-sectional study conducted in Poland, 2004–2005.

*<p>in-patient = in-patient treatment facilities and programs; out-patient = community-based programs serving PWID and surrounding community.</p>**<p>may be in more than one category.</p

HIV prevalence with 95% confidence intervals stratified by gender and age, in a cross-sectional study conducted in Poland, 2004–2005.

<p>Of the 748 respondents to the original survey, 137 (18.3%) had a positive test result for HIV. Upon age stratification, females in younger age groups tended to have a higher level of HIV infection compared to males. Overall, HIV prevalence among females and males aged <30 years (analyzed subset of the original dataset) was 16.4% and 9.6%, respectively. Among those ≥30 years, the relative proportions were reversed: HIV prevalence was 21.4% among females and 33.5% among males.</p

Summary of recruitment process.

<p>Case-control study of tick-borne encephalitis risk factors, Poland, January–December 2009.</p

Estimates of population attributable fraction.

<p>Selected risk factors and 95% confidence intervals, TBE case-control study, Poland, January–December 2009. * indicates statistically significant effects (p<0.05).</p

Description of variables used in the analysis, national case-control study of TBE risk factors, Poland, January–December 2009.

<p>Description of variables used in the analysis, national case-control study of TBE risk factors, Poland, January–December 2009.</p

Interaction between time spent in mixed forest and collecting forest foods.

<p>Odds ratios and 95% confidence intervals, TBE case-control study, Poland, January–December 2009.</p

Univariate and multivariate association between studied variables and the TBE risk among inhabitants of non-endemic areas, results from conditional logistic regression, Poland, 2009.

*<p>p-value for the likelihood ratio (LR) chi-square test computed for the univariate statistics; Note: for ordinal variables this approximates a test for trend;</p>†<p>calculated from local currency (PLN) as at January-December 2009;</p>‡<p>the denominator for percentages were non-missing observations; OR - odds ratio from univariate analyses; aOR - adjusted odds ratio for variables retained in the final multivariate model; CI – confidence interval.</p