A systematic comparison of additive and interaction approaches to modeling the effects of syndemic problems on HIV outcomes in South Africa.

Journal: Journal of behavioral medicine

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Affiliated Institutions:  Department of Psychiatry, Behavioral Medicine Program, Massachusetts General Hospital, One Bowdoin Square th Floor, Boston, MA, , USA. jlee@mgh.harvard.edu. Department of Psychology, University of Miami, Coral Gables, Florida, USA. Department of Psychiatry, Harvard Medical School, Boston, MA, USA. Department of Public Health, Global Health Section, University of Copenhagen, Copenhagen, Denmark. Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA. Department of Psychology, University of Maryland, College Park, MD, USA. Department of Psychology, Stellenbosch University, Western Cape, Stellenbosch, South Africa. Centre of Excellence in Food Security, University of the Western Cape, Cape Town, South Africa. Division of Neuropsychiatry, Department of Psychiatry and Mental Health, HIV Mental Health Research Unit, Neuroscience Institute, University of Cape Town, Cape Town, South Africa. Department of Psychiatry, Behavioral Medicine Program, Massachusetts General Hospital, One Bowdoin Square th Floor, Boston, MA, , USA.

Abstract summary 

Much of the research on the effects of syndemics on HIV outcomes has utilized an additive approach. However, interaction effects may better account for syndemic synergy than an additive approach, but it remains difficult to specify interaction effects without empirical guidance. We sought to systematically compare additive and interaction effects approaches to modeling the effects of syndemic problems on antiretroviral therapy (ART) using empirically specified interaction terms. Participants were 194 people with HIV (PWH) who received HIV care in Khayelitsha, South Africa. In a series of linear regression models, we examined ten syndemic problems: depression, alcohol use, intimate partner violence (IPV), post-traumatic stress, social anxiety, substance use, food insecurity, poverty, housing instability, and structural barriers to care. Depression, substance use, and food insecurity were selected for interaction terms based on a prior network analysis, which found these problems to be most central. The additive models did not produce statistically significant findings. However, the interaction effects models yielded significant interaction terms in both the full model and a parsimonious model. There was a statistically significant effect of the interaction between depression and food insecurity on ART adherence (b = 0.04, Robust SE = 0.02, 95%CI [0.001-0.08], p = .012). This pattern of results was replicated in the parsimonious model. Findings suggest that when feasible, interaction effects approaches may be a helpful syndemic modeling technique. Results may inform future intervention targets, such as depression and food insecurity, and the importance of addressing both structural and psychosocial syndemic problems.

Authors & Co-authors:  Lee Jasper S JS Bainter Sierra A SA Tsai Alexander C AC Andersen Lena S LS Stanton Amelia M AM Magidson Jessica F JF Kagee Ashraf A May Julian J Joska John A JA O'Cleirigh Conall C Safren Steven A SA

Study Outcome 

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Statistics
Citations :  Aiken, L. S., West, S. G., & Reno, R. R. (1991). Multiple regression: Testing and interpreting interactions. sage.
Authors :  11
Identifiers
Doi : 10.1007/s10865-024-00517-y
SSN : 1573-3521
Study Population
Male,Female
Mesh Terms
Other Terms
ART adherence;Depression;Food insecurity;HIV;Interaction effects;Syndemics
Study Design
Study Approach
Systemic Review
Country of Study
South Africa
Publication Country
United States