HIV Clinical Trial
Official title:
A Cluster Randomized Trial of the Impact of an Intimate Partner Violence and HIV Prevention Intervention on Emotional, Physical and Sexual Abuse, Sexual Risk Behaviors and HIV Incidence in Rakai, Uganda
Intimate partner violence (IPV) is a precursor to and consequence of HIV infection. Few
interventions combining HIV and IPV prevention have been evaluated and none has
significantly decreased both outcomes.
A cluster-randomized trial was conducted in Rakai, Uganda. Four intervention arm clusters
(N=5,339) received an IPV prevention intervention (the Safe Homes and Respect for Everyone
(SHARE) Project), enhanced HIV testing and treatment and routine HIV services provided by
Rakai Health Sciences Program (RHSP). Seven control arm clusters (N=6,112) received standard
of care HIV services alone.
Baseline and two follow-up visits were conducted via the Rakai Community Cohort Study
between 2005 and 2009. Primary outcomes were past year emotional, physical and sexual IPV
and HIV incidence. Secondary outcomes included past year intimate partner rape/forced sex,
number of total and extra-marital sex partners, alcohol use surrounding sex, condom use,
discussion about condom use, partner's disclosure of HIV status and respondent's disclosure
of HIV status. Analysis was by intention-to-treat. Modified Poisson regression was used to
estimate prevalence risk ratios (PRR) to detect the impact of the intervention on IPV and
secondary outcomes. Poisson regression was used to estimate incidence rate ratios (IRR) of
HIV acquisition per 100 person years (py).
Our study had three research aims and related hypotheses.
Aim 1 was to assess the impact of SHARE + RHSP community services on report of victimization
from and perpetration of physical and/or sexual IPV in the past 12 months, compared to the
impact of RHSP community services alone.
Hypothesis 1(a): SHARE intervention will reduce women's reports of IPV victimization in
intervention vs. control arms.
Hypothesis 1(b): SHARE intervention will reduce men's reports of IPV perpetration in
intervention vs. control arms.
Aim 2 was to assess the impact of SHARE + RHSP services on report of sexual risk behaviors
among men and women compared to the impact of RHSP community services alone.
Hypothesis 2(a): SHARE intervention will reduce selected sexual risk behaviors in the
intervention vs. control arms.
Aim 3 was to assess the impact of SHARE + RHSP services on HIV incidence compared to the
impact of RHSP community services alone.
Hypothesis 3(a): Incidence of HIV will be lower in the intervention vs. control arms.
Research Team: Rakai Health Sciences Program Data collection for the proposed dissertation
analysis was done by the research teams and investigators from Rakai Health Sciences Program
(RHSP) which was established in 1988 with a focus on HIV/AIDS research, including evaluation
of health education and condom promotion. Over time activities have increased in nature and
volume and expanded to include laboratory and clinical research, randomized trials of new
prevention strategies, health professional training, expanded community services including
HIV voluntary testing and counseling, provision of HIV antiretroviral therapy (ART), general
and HIV-related medical care, prevention of mother-to-child transmission of HIV (PMTCT), and
family planning services. In 2002, the Rakai Program became an International Center for
Excellence in Research (ICER), sponsored by the National Institute of Allergy and Infectious
Diseases (NIAID). The core of the RHSP is the 18-year community-based longitudinal Rakai
Community Cohort Study (RCCS), within which the RHSP has implemented multiple
interdisciplinary studies. Over 150 peer-reviewed papers have been generated from the RCCS
and its nested studies.
Data Source: Rakai Community Cohort Study All data for the proposed analysis were derived
from the Rakai Community Cohort Study (RCCS) which conducts survey interviews every 12-18
months with all consenting people aged 15-49 in ~5,000 households in 47-50 communities
throughout Rakai. These 47-50 communities represent 7% of the 720 communities situated in
Rakai District. The RCCS includes participants residing in trading centers and agrarian
villages, representative of rural southwestern Uganda. Each RCCS participant receives a
unique, life-long study identification number used to link data over time and between RHSP
studies. RCCS written informed consent forms cover study participation, sample archiving for
future assays including genetic testing, linkage of RCCS data to other RHSP databases, and
permission to re-contact participants for other studies.
Trial Design The SHARE intervention trial used a cluster randomized controlled design where
study regions rather than individuals were selected to receive (or not receive) exposure to
the intervention, with all consenting adults in the community being offered treatment
(intervention). The community-based approach was selected because offering a partner
violence prevention intervention to individuals without involving their intimate partners
would not achieve holistic results. IPV involves both members of the couple and its
prevention must likewise target both.
The SHARE intervention trial was done via the Rakai Community Cohort Study (RCCS) which
operates in ~50 communities which were aggregated into 11 study regions (categorized as
rural or semi-urban) for a prior trial of sexually transmitted disease control and HIV
transmission prevention conducted between 1994 and 1999. A previous FP outreach trial (1999
and 2002) had randomized these communities,35 and the SHARE study built on this prior
randomization whereby the SHARE intervention was implemented in 4 regions (Buyamba, Kabira,
Kalisizo, Katana) of the total 11 RCCS research areas. . For the current trial, four of the
six FP intervention clusters were randomly assigned to the IPV intervention arm.
The process used to select regions for exposure to the SHARE trial built on a previous
cluster randomized trial (CRT) that was conducted between 1999 and 2002 to assess the impact
of family planning outreach via social marketing in Rakai. For the family planning CRT, 5
clusters were randomly selected to receive standard family planning services while 6
clusters were assigned to the intervention arm and received additional family planning
information, counseling, and contraceptive methods from government service providers and
community-based volunteer agents using social marketing and other strategies. Condom use was
promoted in both control and intervention areas. Findings indicated family planning outreach
via social marketing can significantly increase hormonal contraceptive use and decrease
pregnancy rates. No differentials were found, however, in condom use between study arms.
In 2005, 4 of the 6 family planning intervention clusters were randomly assigned to the
intervention arm of the SHARE trial. The remaining 2 family planning intervention clusters,
as well as all 5 family planning control clusters were assigned to the control arm of the
SHARE intervention trial, making a total of 7 control regions in the SHARE trial. The
decision to allocate only 4 communities to intervention was based on budgetary constraints
which precluded a larger number of intervention areas.
RCCS rounds and intervention trial implementation
Data from 2 rounds of the RCCS, R1 and R2, will be analyzed for the proposed study:
R1 = baseline, pre-intervention (Feb 2005-Jun 2006) R2 = post-intervention follow-up (Aug
2006-Apr 2008) R3 = post-intervention follow-up (Jun 2008-Nov 2009)
Baseline interviews were conducted in all 4 intervention and 7 control regions via RCCS
between February 2005 and June 2006. SHARE was rolled out in the 4 intervention regions
between August 2005 and November 2006. SHARE activities were introduced in each intervention
region only after all baseline data collection had been completed for the entire study area.
Because regions are surveyed via RCCS in the same order during each annual/semi-annual
round, we estimate that each intervention community had approximately the same length of
exposure to SHARE before each point of follow-up.
Independent/Dependent Variables and Confounders
Independent (exposure) variables
There are 2 independent variables for the proposed study: RCCS round and arm of the trial
1. RCCS round:
1. Pre-intervention baseline (R1)
2. Post-intervention follow-up time 2 (R2)
3. Post-intervention follow-up time 2 (R3)
2. Arm of trial
1. Intervention arm
2. Control arm
Dependent (outcome) variables
The primary dependent variable is past year experience of IPV (victimization among
women, perpetration among men). Secondary outcome variables include number of
non-marital sexual partners, condom use in the past 6 months, alcohol use at last
sex and HIV incidence. All dependent variables will be determined at baseline,
post-intervention time 1 and time 2.
Confounders Potential confounding variables will be assessed at baseline to
determine comparability between arms. The association between potential
confounders and outcomes of interest will be assessed by univariate analyses, and
potential covariates will include; age, sex (gender), education, marital status,
religion, pregnancy-status, reproductive/fertility preferences, HIV-status, use of
VCT, household socio-economic status. We will also assess the associations between
sexual behaviors and IPV/HIV acquisition.
Intention to Treat An intention to treat approach will be used in which all
participants with evaluable data for each outcome measure will be included in the
analysis by randomization arm. Retention rates will be estimated by arm.
Analysis Plans The proposed statistical analysis will follow four key steps.
Step 1 - Establish baseline comparability
First, the characteristics of study participants will be assessed at
pre-intervention (baseline) in both the control and intervention regions.
Comparability of the two arms at baseline is important for designing final
statistical analysis models capable of adjusting for any differences and assessing
the impact of the intervention with minimal or no confounding. Pre-intervention
data on outcome variables, socio-demographic and covariates will be analyzed,
using descriptive statistics and graphics to display in the control and
intervention communities. Exploratory analysis will include frequencies for
dichotomous and categorical variables, using X2 and Fisher's exact tests for
differences in proportions. Continuous variables will be assessed by means and
medians using t-tests and Wilcoxon rank test.
Step 2 - Investigate associations between intervention exposure and
primary/secondary outcomes
The second analytic step will be to investigate the associations between
intervention exposure and the primary and secondary outcomes (past year IPV,
condom use, alcohol use with sex, number of non-marital partners and HIV
incidence) using univariate regression analyses. Covariates (characteristics or
behaviors) found to be correlated with outcomes of interest in the univariate
models at the p<0.15 significance levels will be included in subsequent
multivariate models.
Step 3 - Construct adjusted multivariate models
Adjusted multivariate regression models will be constructed for outcomes found to
be significantly predicted by intervention exposure. Details are provided in the
subsequent section on data modeling and power calculations for the 3 aims of the
proposed dissertation research.
Proposed Data Modeling and Power Calculations by Research Aim
AIM 1 - Intimate Partner Violence Outcome To assess the impact of SHARE + RHSP
community services on report of victimization from and perpetration of physical
and/or sexual IPV in the past 12 months, compared to the impact of RHSP community
services alone.
Statistical Modeling for Aim 1
The measures of past year experience of IPV will be analyzed separately for
physical and sexual IPV and both will be modeled categorically. Three categories
of physical violence will be used: (1) None (referent); (2) Moderate physical IPV;
(3) Severe physical IPV. Two categories of sexual violence will be used: (1) None
(referent); (1) Any sexual violence. Participants who report any experience
(victimization or perpetration) of physical or sexual IPV in the past 12 month
will be counted as having experienced the outcome.
The proportion of each type of IPV will be tabulated by follow-up visit, and
unadjusted differences between trial arms will be assessed using χ2 and Fisher's
exact tests. The proportion of each type of IPV will be calculated separately for
men (perpetration) and women (victimization). Behavior changes will be evaluated
from baseline to follow-up (i.e. the second post-trial follow-up) by which time
individuals in intervention regions had been exposed to the SHARE intervention for
more than one year.
Linear regression models will be fitted to estimate the marginal distributions of
repeated outcomes to compare the within-individual behavior changes in relation to
exposure or non-exposure to the intervention. The following equation will be used
where Yit denotes the absence/presence of each type of IPV for every unit i at
each time t.
Yit = β0 + β1G + β2T + β3(G×T) + β4X1... + βkXk +εit
Covariates included in the multivariate models will be characteristics or
behaviors found to be correlated with IPV outcomes in univariate analyses at
p<0.15. Models will also adjust for any statistically significant lack of
comparability between the trial arms at baseline. Statistical inference for
individual covariates will be based on the Wald statistic, and model fit assessed
by the log likelihood ratio test (LRT).
The difference between follow-up and baseline measures of IPV will be calculated
separately for intervention and control regions and the difference in changes will
be assessed under the null hypothesis that there is no DiD: (IPV-IntFup -
IPV-IntB) = (IPV-CF - IPV-Cb). The statistical significance of the interaction
coefficient, β3, will be obtained using the Wald statistic, and model fit assessed
by the log likelihood ratio test (LRT). All hypothesis tests will be two sided
with significance levels of 0.05.
Behavioral variables found to have changed significantly during the post-trial
follow-up will be further analyzed through repeated fitting of the linear model
analyses stratifying by age group, type of community (rural vs. urban), and other
important variables to investigate if behavior changes are associated with
specific characteristics of individuals or populations.
Power Calculations for Aim 1 Data on the impact of SHARE + RHSP community services
on past year IPV will be analyzed to present (1) the percent change (reduction or
increase) or lack thereof of reports of the IPV outcome in both groups
(intervention and control) from baseline to follow-up; (2) the difference in the
percent change of the IPV outcome between intervention and control groups.
For Aim 1, power estimates were calculated to assess the study's power to measure
percent change (reduction or increase) of IPV from baseline to follow-up, assuming
there will be comparability in the percentages reported pre-intervention in both
arms. Thus, study power estimates were calculated for the primary outcome of past
year IPV based on (1) the set sample size for each round of data collection, (2)
baseline prevalence of each type (physical and sexual) of IPV (3) assumptions
regarding the expected magnitude of decline in each type of IPV that might result
from the SHARE intervention combined with RHSP HIV prevention activities.
Two sets of power calculations were used for physical IPV (moderate and severe
combined) and sexual IPV. The sample size is fixed as per Table 3. STATA 1059 was
used to estimate power to detect a minimum percent reduction, assuming a two-sided
α = 0.05 with an approximate intervention population of 3,500 and an approximate
control population of 11,100 at both time points. Baseline prevalence of different
IPV types are based on RCCS data suggesting 20% of women experienced physical IPV
and 14.5% experienced sexual IPV during the year before the survey. It is thus
estimated that the study has 80% power to detect as little as a 7% reduction in
the proportion of individuals reporting physical IPV and as little as a 16%
reduction in the proportion of individuals reporting sexual IPV in both arms
between baseline and follow-up.
AIM 2 - Sexual Risk Behavior Outcomes To assess the impact of SHARE + RHSP
community services on report of sexual risk behaviors, including non-marital
partnerships in the past year, condom use over the past 6 months and use of
alcohol before sex among men and women compared to the impact of RHSP community
services alone.
Statistical Modeling for Aim 2 The three measures of past year sexual risk
behaviors will be analyzed separately for non-marital partnerships, condom use in
the past 6 months, and alcohol use at last sex. All outcomes will be modeled
categorically.
Non-marital partners Number of non-marital sex partners in the past year will be
modeled as a categorical outcome: (1) no non-marital partner (referent); (2) one
non-marital partner; (3) two or more non-marital partners.
Condom use in the past 6 months Condom in the past 6 months will be modeled
categorically as: (1) no condom use (referent); (2) inconsistent use; and (3)
consistent use.
Alcohol use at last sex Alcohol use at last sex will be modeled categorically as:
(1) no alcohol use at last sex (referent); (2) any alcohol use at last sex.
The proportion of each type of sexual risk behavior reported will be tabulated by
follow-up visit, and unadjusted differences between trial arms will be assessed
using χ2 and Fisher's exact tests. The proportion of each type of IPV will be
calculated separately for men and women and behavior changes will be evaluated
from baseline to follow-up.
Linear regression models will be fitted to estimate the marginal distributions of
repeated outcomes67 to compare the within-individual behavior changes in relation
to exposure or non-exposure to the intervention. The following equation will be
used where Yit denotes the absence/presence of each type of sexual risk behavior
for every unit i at each time t: Yit = β0 + β1G + β2T + β3(G×T) + β4X1... + βkXk
+εit The remainder of the description of statistical methods for Aim 2 is
identical to that of Aim 1.
Power Calculations for Aim 2 Estimates were calculated to assess the study's power
to measure percent change (reduction or increase) of each sexual risk behavior
from baseline to follow-up, assuming comparability at baseline in in both arms.
Again, study power estimates were calculated were based on (1) the set sample size
for each round of data collection and (2) baseline prevalence, derived from Rakai
data, of each type of sexual risk behavior. Three sets of power estimates were
calculated.
Non-marital partners: Rakai data indicated approximately 61% of men and 10% of
women had more than one non-marital sex partner in the past year,49 the proposed
analysis has 80% power to detect as small as a 3% reduction in men and an 11%
reduction in women from time one to time two in each arm.
Condom use: Data on condom use in the last six months was not available. But it is
estimated that 6.5% of men and 3% of women consistently used condom use in the
past year. 49 Based on these findings, it is estimated that the proposed analysis
has the power to detects as small as 15% increase in consistent condom use among
women and as small as a 23% increase in consistent condom use among men.
Alcohol use at last sex: Previous Rakai findings suggest that 75.5% of men and 37%
of women drink alcohol before sex. Based on these findings, it is estimated that
the proposed analysis has the power to detect as small as 2% and 5% decrease in
alcohol use with sex among men and women, respectively.
AIM 3 - HIV Incidence Outcome To assess the impact of SHARE + RHSP community
services on HIV incidence. Statistical Modeling for Aim 3
For Aim 3, data from all 3 rounds of RCCS will be analyzed. Person years (PY) of
exposure will be cumulated from baseline to the last negative HIV result if the
person remained negative, or to the midpoint of the interval between the last
negative tests and first positive tests for seroconverters. HIV incidence will be
estimated per 100 PY. The primary analysis will be intention-to-treat, using a log
link and Poisson distribution to estimate the incidence rate ratios (IRR) of HIV
acquisition. Random effects models will be used to account for intra-region
correlation. All models will be adjusted by study region. In univariate analyses
we will assess covariates associated with HIV acquisition at p<0.15 to determine
potential confounders for inclusion in multivariate models. Models will also
adjust for any statistically significant baseline differences between
randomization arms.
Potential covariates include terms for sex, age, sexual risk behaviors, and
community baseline prevalence of HIV. Homogeneity of the treatment effect in men
and women will be assessed by testing for a sex by treatment interaction. Results
of these models will be used to estimate the number of HIV infections prevented by
the intervention over a ~4.5 period per 100 participants.
Power Calculations for Aim 3 Assuming 75% annual retention and two follow up
intervals post-intervention, we estimate we will have ~4,753 PY of exposure in the
intervention group and ~16,969 PY of exposure in the control group. The power to
detect minimal IRRs with this person time was estimated using STATA 1059 assuming
a two sided α =0.05 and an HIV incidence estimate of 1.5/100 PY among women and
1.4/100 PY among men. The study has 80% power to detect a 36% lower HIV incidence
in intervention compared to control communities over time of follow-up.
ETHICAL CONSIDERATIONS Several steps were taken by the RHSP to ensure the safety
and confidentiality of all research participants. Because this is secondary data
analysis, the main risk is breach of confidentiality if participant records,
interviews or lab results are revealed to third parties. Informed consent
documents are retained in locked filing cabinets and store rooms, accessible only
to senior investigators or designated staff. All questionnaires and samples are
identified by pre-printed study ID numbers, and names are removed. All
questionnaires are stored in secure, locked facilities in the field station in
Kalisizo and permanent stores in Entebbe. Only designated staff members have
access to these records. All computerized data bases contain study ID numbers and
the lists linking study numbers to names is kept separately in a password
protected computer accessible only to senior data managers. Files of lab results
are maintained in a separate safe computer file, with study ID numbers, and
contain no personal identifiers.
The RCCS interviews for this study were conducted in the respondents' homes or at
a central location (referred to as a "hub"). Interviews were done in complete
privacy in the language of Luganda by experienced same-sex interviewers using
structured questionnaires. Recognizing that research on IPV raises important
ethical and methodological challenges beyond those posed by general population
health research, RHSP investigators followed recommendations developed by the WHO
regarding the safe and ethical conduct of domestic violence research.
IRB approval for the original study data was granted under two studies "Rakai
Community Cohort Study" and "Assessing the impact of community-based intervention
designed to reduce levels physical and sexual domestic violence in Rakai District,
Uganda." The "Rakai Community Cohort Study" received IRB approval from WIRB (WIRB
PRO#20031318) and the study "Assessing the impact of community-based intervention
designed to reduce levels physical and sexual domestic violence in Rakai District,
Uganda" received approval from the IRB of the World Health Organization
(WHO.A55085). Both studies also received ethical approval from the Uganda Virus
Research Institute's Science Ethics Committee and the Ugandan National Council of
Science and Technology. Ethical approval for the proposed secondary analysis was
received by WIRB as a sub study to the ongoing Rakai Community Cohort study (WIRB
PRO#20031318). All enrollment and data collection has ended.
;
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