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A comparison of two population-based household surveys in Uganda for assessment of violence against youth

  • Dustin W. Currie ,

    Roles Conceptualization, Formal analysis, Methodology, Writing – original draft

    pif7@cdc.gov

    Affiliations Division of Global HIV & Tuberculosis, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America, Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

  • Rose Apondi,

    Roles Conceptualization, Data curation, Methodology, Writing – review & editing

    Affiliation Division of Global HIV & Tuberculosis, Centers for Disease Control and Prevention, Kampala, Uganda

  • Christine A. West,

    Roles Conceptualization, Funding acquisition, Project administration, Supervision, Writing – review & editing

    Affiliation Division of Global HIV & Tuberculosis, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

  • Samuel Biraro,

    Roles Data curation, Project administration, Writing – review & editing

    Affiliation ICAP at Columbia University, Kampala, Uganda

  • Lydia N. Wasula,

    Roles Conceptualization, Data curation, Project administration, Writing – review & editing

    Affiliation Uganda Ministry of Gender, Labour, and Social Development, Kampala, Uganda

  • Pragna Patel,

    Roles Conceptualization, Methodology, Resources, Writing – review & editing

    Affiliation Division of Global HIV & Tuberculosis, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

  • Jennifer Hegle,

    Roles Conceptualization, Methodology, Resources, Writing – review & editing

    Affiliation Division of Global HIV & Tuberculosis, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

  • Ashleigh Howard,

    Roles Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Resources, Writing – review & editing

    Current address: Division of Global Health Protection, Centers for Disease Control and Prevention, Kinshasa, Democratic Republic of the Congo

    Affiliations Division of Violence Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America, Strategic Innovative Solutions, LLC, Clearwater, Florida, United States of America

  • Regina Benevides de Barros,

    Roles Conceptualization, Methodology, Resources, Writing – review & editing

    Affiliation Division of Global HIV & Tuberculosis, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

  • Tonji Durant,

    Roles Conceptualization, Resources, Writing – review & editing

    Affiliation Division of Global HIV & Tuberculosis, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

  • Laura F. Chiang,

    Roles Data curation, Methodology, Writing – review & editing

    Affiliation Division of Violence Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

  • Andrew C. Voetsch,

    Roles Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing

    Affiliation Division of Global HIV & Tuberculosis, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

  • Greta M. Massetti

    Roles Conceptualization, Methodology, Supervision, Writing – review & editing

    Affiliation Division of Violence Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

Abstract

Violence is associated with health-risk behaviors, potentially contributing to gender-related HIV incidence disparities in sub-Saharan Africa. Previous research has demonstrated that violence, gender, and HIV are linked via complex mechanisms that may be direct, such as through forced sex, or indirect, such as an inability to negotiate safe sex. Accurately estimating violence prevalence and its association with HIV is critical in monitoring programmatic efforts to reduce both violence and HIV. We compared prevalence estimates of violence in youth aged 15–24 years from two Ugandan population-based cross-sectional household surveys (Uganda Violence Against Children Survey 2015 [VACS] and Uganda Population-based HIV Impact Assessment 2016–2017 [UPHIA]), stratified by gender. UPHIA violence estimates were consistently lower than VACS estimates, including lifetime physical violence, recent intimate partner physical violence, and lifetime sexual violence, likely reflecting underestimation of violence in UPHIA. Multiple factors likely contributed to these differences, including the survey objectives, interviewer training, and questionnaire structure. VACS may be better suited to estimate distal determinants of HIV acquisition for youth (including experience of violence) than UPHIA, which is crucial for monitoring progress toward HIV epidemic control.

Introduction

Violence against children (ages 14 years and under) and youth (ages 15–24 years) [1], defined by the World Health Organization as “the intentional use of physical force or power, threatened or actual, against oneself, another person, or a group or community, that either results in or has a high likelihood of resulting in injury, death, psychological harm, maldevelopment, or deprivation” [2], is a significant public health issue: over one billion children are affected each year globally [3]. Individuals who experience violence face wide-ranging consequences, including poor physical and mental health, decreased education and employment opportunities, higher likelihood of drinking alcohol or using drugs in general and before sex, initiating intercourse at an earlier age, having intercourse with multiple partners or strangers, having a sexually transmitted infection, and experiencing suicidal ideation [46].

Sub-Saharan Africa has among the highest global prevalence rates of violence against children, youth and women [3,7]. The Sub-Saharan Africa region also has the highest global prevalence and incidence of HIV; 64% of all people living with HIV live in sub-Saharan Africa [8]. Women and girls account for 63% of all new HIV infections in the region, which rises to 86% in the 15–19 year old age group [9]. In Uganda, an estimated 22% of women aged 15 to 49 had experienced some form of sexual violence in their lifetime [10], and an estimated 7.6% of females aged 15 to 64 were living with HIV [11]. Previous studies have suggested an association between violence and HIV risk, through direct mechanisms such as forced sex or indirect mechanisms such as an inability to negotiate safe sex [1214]. Gender and violence are often intertwined, and the higher incidence of HIV among 15–24 year old females compared to their male peers in some countries likely reflect gender-related drivers of HIV infection, including violence [12,1416].

National household surveys funded by the US President’s Emergency Plan for AIDS Relief in sub-Saharan Africa have been designed to estimate the prevalence of violence in relation to sexual risk behaviors and HIV status. Violence Against Children and Youth Surveys (VACS; https://www.cdc.gov/violenceprevention/childabuseandneglect/vacs/) are designed to estimate childhood, lifetime, and past-12-month violence prevalence in children and youth aged 13–24 years and include modules assessing sexual behaviors and HIV risk [17]. Population-based HIV Impact Assessments (PHIAs; https://phia.icap.columbia.edu/) are designed to estimate HIV-related outcomes and in most countries included a violence module during the first round of surveys; most countries use an abbreviated version to allow for inclusion of other priority issues.

The Uganda PHIA 2016–2017 (UPHIA) used the full violence module and thus is aligned more closely with the Uganda VACS (2015). UPHIA eligibility criteria were adapted to be comparable with VACS criteria, by restricting violence module eligibility to youth and by modeling the sampling approach after VACS [11]. Therefore, UPHIA served as a “proof of concept”, allowing determination of whether an HIV-focused survey with biomarker data collection resulted in comparable violence prevalence data to VACS. The purpose of this report is to compare violence prevalence estimates generated by VACS and UPHIA. Understanding comparability of violence prevalence estimates in an HIV-focused survey and a violence-focused survey has implications for ongoing surveillance of violence against youth and HIV.

Methods

Detailed descriptions of the VACS [17,18] and UPHIA [11] survey designs have been published previously. Briefly, both were population-based household surveys using a three-stage sampling approach, in which enumeration areas (EAs), limited geographic areas designated by national statistical authorities, were selected within regional strata in Uganda, and households were randomly selected within EAs. A single eligible respondent per household was selected randomly to participate in the survey (for VACS) or the violence module (for UPHIA). For both surveys, a referral mechanism was in place to put respondents in contact with a social welfare officer if further assistance was needed for a violence-related issue. National weights in both surveys were used to generate estimates that accounted for sample selection probabilities and were adjusted for nonresponse and noncoverage. Both surveys were approved by the CDC Institutional Review Board (Protocols #6538 [Uganda VACS] and #6830 [UPHIA]), and the Uganda National Council for Science and Technology.

Tables 1 and 2 summarize key differences between the two surveys. While the overarching strategy was similar, there were differences in primary objectives, survey methods and sampling (Table 1), and in questionnaire structure and content (Table 2). Both surveys were designed to generate nationally representative estimates of primary outcomes, and separated EAs such that only males or only females were eligible for either the violence module (UPHIA) or the whole questionnaire (Uganda VACS) within an EA (Table 1). Both surveys were completed via face-to-face interviews with trained interviewers but given the difference in the objectives of the two surveys, there were some differences in interviewer training. There were differences in how experience of violence questions were asked, with UPHIA generally using more parent questions and skip patterns, and Uganda VACS asking about experiences of different types of violence via different perpetrators separately (Table 2).

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Table 1. Methods and sampling structure of Uganda Population-based HIV Impact Assessment (UPHIA 2016–2017) and Uganda Violence Against Children Survey (VACS 2015).

https://doi.org/10.1371/journal.pone.0260986.t001

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Table 2. Wording and response options of comparable violence questionnaire items between Uganda Violence Against Children Survey (VACS 2015) and Uganda Population-based HIV Impact Assessment (UPHIA 2016–2017)*.

https://doi.org/10.1371/journal.pone.0260986.t002

Weighted prevalence estimates and 95% confidence intervals (CI) were calculated stratified by gender, accounting for the complex sampling design of each survey. Comparisons between UPHIA and VACS were restricted to individuals aged 15–24 years so that comparisons included identical age groups. Two proportion z-tests were used to calculate p-values comparing prevalence estimates between VACS and UPHIA, with statistical significance determined at p<0.05. Analyses were completed using SAS 9.4.

Results

Demographic characteristics of the two groups were comparable after weighting (Table 3). Slightly over half of participants were female (UPHIA, 51.3%; VACS, 52.6%), with similar mean age distributions (UPHIA males, 19.1 years; VACS males, 18.9 years; UPHIA females, 19.2 years; VACS females, 19.4 years). Fewer male than female participants had been married or lived with someone like they were married (UPHIA males, 19.3%; VACS males, 19.5%; UPHIA females, 45.2%; VACS females, 46.9%) and had been previously told they were HIV-positive (UPHIA males, 0.1%; VACS males, 0.3%; UPHIA females, 1.6%; VACS females, 1.7%). None of the sex-specific differences between UPHIA and VACS presented in Table 3 were statistically significant (p>0.05).

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Table 3. Weighted demographic characteristics and self-reported HIV status of Uganda VACS 2015 and UPHIA 2016–17 participants, by gender.

https://doi.org/10.1371/journal.pone.0260986.t003

Lifetime prevalence of physical violence was significantly higher in VACS than UPHIA for both males (VACS, 77.1%; UPHIA, 32.0%; p<0.0001; Fig 1) and females (VACS, 67.0%; UPHIA, 26.0% p<0.0001; Fig 2). Similarly, past-year prevalence of physical intimate partner violence was significantly higher in VACS for females (VACS, 14.7%; UPHIA, 7.8%; p<0.0001) and males (VACS, 4.4%; UPHIA, 1.6%; p = 0.003).

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Fig 1. Lifetime and past-12-month prevalence of sexual and physical violence in males aged 15–24 years in Uganda Population-based HIV Impact Assessment (UPHIA 2016–2017) and Uganda Violence Against Children Survey (VACS 2015).

Violence domains include lifetime physical violence, physical intimate partner violence (IPV) in the past 12 months, and lifetime sexual violence. Asterisks (*) indicate significantly higher prevalence in VACS than UPHIA (p<0.05). Daggers () indicate significantly higher prevalence in UHPIA than VACS (p<0.05).

https://doi.org/10.1371/journal.pone.0260986.g001

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Fig 2. Lifetime and past-12-month prevalence of sexual and physical violence in females aged 15–24 years in Uganda Population-based HIV Impact Assessment (UPHIA 2016–2017) and Uganda Violence Against Children Survey (VACS 2015).

Violence domains include lifetime physical violence, physical intimate partner violence (IPV) in the past 12 months, and lifetime sexual violence. Asterisks (*) indicate significantly higher prevalence in VACS than UPHIA (p<0.05). Daggers () indicate significantly higher prevalence in UHPIA than VACS (p<0.05).

https://doi.org/10.1371/journal.pone.0260986.g002

Prevalence estimates of sexual violence between UPHIA and VACS were more comparable, but some differences in estimates emerged. For females, lifetime sexual violence was significantly higher in VACS (48.6%) than UPHIA (36.2%; p<0.001), as was unwanted sexual touching (VACS: 35.5%; UPHIA: 26.0%; p<0.0001) and attempted forced sex (VACS: 25.0%; UPHIA: 19.5%; p = 0.01). Meanwhile, being pressured to have sex was significantly higher in UPHIA (10.0%) than in VACS (6.6%; p = 0.006). For males, lifetime sexual violence was significantly higher in VACS (26.3%) than UPHIA (22.6%; p = 0.03), while forced sex was significantly higher in UPHIA (7.1%) than in VACS (3.1%; p<0.0001).

Discussion

Compared to VACS, UPHIA generated significantly lower prevalence estimates of lifetime physical violence, any lifetime sexual violence, and past-12-month intimate partner violence among both males and females. The differences between survey findings were more consistent for physical violence. Findings were mixed in domain-specific sexual abuse analyses; among males, lifetime reports of having been physically forced to have sex were higher in UPHIA, and among females, being pressured into having sex was higher in UPHIA while unwanted sexual touching and attempted forced sex were higher in VACS. Since underreporting is much more likely in violence data collection than overreporting [19], the overall findings suggest that UPHIA likely underestimated the burden of violence against youth, particularly physical violence, in Uganda [19,20].

Methodological differences between the two surveys likely contributed to these differences. VACS was designed specifically to estimate violence prevalence, while UPHIA was designed primarily to estimate HIV-related outcomes with an additional module to measure violence as a secondary aim. Adding a violence module to a larger survey focused on other health issues may result in underestimation of violence [21]. This can be attributed to confidentiality concerns, survey fatigue, and discomfort with the nature of questions related to violence when compared to other survey items [19]. Additionally, interviewer selection and training related to violence data collection are crucial; respondent willingness to disclose violence may be affected by the rapport established between the interviewer and respondent [2123]. Interviewers may exhibit implicit biases, either perceived or real, that could result in underreporting. Although substantial interviewer training was conducted for data collectors in both UPHIA and VACS, the VACS interviewer selection and training focused more specifically on strategies to facilitate disclosure and assess violence in the targeted age group [24].

The content and structure of the questionnaire also likely contributed to differences in prevalence across the surveys. For physical violence, the VACS questionnaire repeats stem questions for each of the four categories of perpetrators (intimate partners, peers, parents/caregivers/other adult relatives, and adults in the community) to anchor the responses to different types of relationships and facilitate recall. UPHIA asked one question about physical violence from any perpetrator and followed affirmative answers with a question about the perpetrator. Given the normalization of many forms of violence, without orienting respondents to the possible perpetrator, they may not consider certain acts to be violent (e.g., violence perpetrated by a peer or a caregiver) [25]. The respondent may think of only the most salient relationships in their life rather than thinking about all of the types of relationships addressed in the VACS questionnaire. Conversely, UPHIA provided additional clarification to the respondent regarding examples of being pressured into sex, which was the only violence domain more frequently reported in UPHIA than VACS among females. Previous research has demonstrated that using multiple behaviorally specific questions about violence generates higher prevalence estimates than broader, aggregate questions [25]. Our findings suggest that the structure of violence questionnaires, specificity of questions, and design of parent questions and skip patterns may be critical in avoiding under-reporting of violence. Table 2 demonstrates that the structure of the UPHIA questionnaire for physical violence was much different than the VACS, while they were more similar for sexual violence; underestimates for physical violence in UPHIA were also more pronounced than for sexual violence.

PHIAs provide valid and reliable information on important indicators of HIV epidemic control, including incidence, prevalence, and progress toward Joint United Nations Programme on HIV/AIDS 95-95-95 targets (95% of HIV-positive individuals are aware of their HIV status; of these, 95% are receiving antiretroviral therapy; and of these, 95% have achieved viral load suppression) in countries with generalized HIV epidemics. However, our findings suggest that enhancing the VACS to include key laboratory outcomes relating to HIV (e.g. HIV testing, incidence testing, and viral load testing) rather than incorporating additional violence data collection into HIV-focused PHIAs, may be a better approach to understand the prevalence of violence in youth and the relationship between violence and HIV. This approach has been implemented to varying degrees in several recent VACS, which also included rapid HIV testing (in Botswana, Côte d’Ivoire, Lesotho, Kenya, Namibia, Zimbabwe, and Mozambique); the violence module of PHIA has been removed for all countries as of 2019. UPHIA’s violence module represented an attempt to incorporate lessons learned from VACS surveys to estimate violence prevalence in an HIV-focused survey; however, many violence-related outcomes were underestimated in UPHIA. Generating reliable violence estimates in an HIV-focused survey may be possible, given the similar findings in some of the similarly worded sexual violence questions between VACS and UPHIA. However, this would likely require further changes to questionnaire structure (further increasing interview length), as well as additional specialized training for data collectors in facilitating violence disclosure. VACS and PHIA have different primary objectives, and VACS may be better suited to estimate distal determinants of HIV acquisition for youth (including experience of violence), since they can focus more of the interview time as well as the recruiting and training of the interviewers on these topics.

Acknowledgments

We thank the Uganda Ministry of Health and Ministry of Gender, Labour, and Social Development for their leadership in carrying out each of the surveys, the many staff who collected data for both surveys, and the participants of both surveys for sharing personal details of their lives with survey staff, and without whom none of this work would be possible.

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