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Articles

The Influence of Relationship Power Dynamics on HIV Testing in Rural Malawi

Pages 347-359 | Published online: 26 Mar 2014
 

Abstract

Using the theory of gender and power (TGP) and data from the Tsogolo la Thanzi (TLT) study, we examined how relationship power shapes young people's decisions to test for HIV in rural Malawi (N=932), a high-HIV prevalence setting undergoing rapid expansions in testing services. We used generalized estimating equations (GEE) to examine associations among five constructs of relationship power (socioeconomic inequalities, relationship dominance, relationship violence, relationship unity, and mistrust), perceived risk, and receiving an HIV test over a 16-month period. The results indicate that young Malawians are testing for HIV at relatively high rates, repeatedly, and not just during pregnancy. Over the study period, 47.3% of respondents received at least one HIV test outside of TLT (range: 0–4). The GEE analysis revealed that men and women with higher levels of relationship unity were less likely to test for HIV. For men, being a victim of sexual coercion was an additional barrier to testing. Women's testing decisions were more strongly influenced by perceptions of a partner's risk for HIV than their own, whereas men relied more on self-assessments. The results highlight that testing decisions are deeply embedded within the relationship context, which should be considered in future HIV testing interventions.

Acknowledgments

An earlier version of this manuscript was presented at the Annual Meeting of the American Public Health Association (APHA) on October 30, 2012, in San Francisco, CA. We are grateful to Sheana Bull, Sara Yeatman, Jean Scandlyn, Jennifer Harman, Torsten Neilands, Lynae Darbes, and several anonymous reviewers for their valuable feedback on earlier versions of this manuscript.

Notes

1Refer to http://projects.pop.psu.edu/tlt for more information about the TLT data set, to request data access, and for replication files.

Note. Unity: 1 = Strongly disagree; 2 = Disagree; 3 = Agree; 4 = Strongly agree. Higher scores indicate more unity. Unity scores were created by taking the mean across all unity items.

*Chi-square and ANOVA differences for gender were significant at p < 0.05.

a Adjusted models control for all predictor variables, marital status, age, education, household goods index, relationship duration, previous testing through the TLT, previous testing outside of TLT, and antenatal care testing (women only). Time-varying predictors include perceived risk, marital status, and the testing control variables. Unity scores ranged from 1 to 4, with higher values indicating more unity.

p < 0.10. *p < 0.05. **p < 0.01.

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