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Self-Management Model fails to Predict Quality of Life for People Living with Dual Diagnosis of HIV and Diabetes

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Abstract

The objective of this study was to test a self-management model for self-management in people living with HIV and type 2 diabetes (PLWH + T2DM). We conducted a predictive, longitudinal study of data from a national research cohort of PLWH using lag analysis to test short- and long-term health outcomes for PLWH + T2DM. We used a dataset from the Center for AIDS Research (CFAR) Network of Integrated Clinic Systems (CNICS), a nation-wide research network of 8 clinics that serves PLWH. Patient-reported outcomes, collected at clinic visit, included depression, adherence, CD4 cell count, and health-related quality of life (HRQoL). We computed summary statistics to describe the sample. Using lag analysis, we then modeled the three variables of adherence, CD4 count, and HRQoL as a function of their predecessors in our conceptual model. In the final model, an increase of in medication adherence corresponded to a small increase in HRQoL. An increase in CD4 count corresponded to a small increase in HRQoL. An increase in lagged depression was associated with a small decrease in HRQoL. The model was not sufficient to predict short- or long-term outcomes in PLWH + T2DM. Although depression had a moderate impact, the final model was not clinically significant. For people with a dual diagnosis of HIV and T2DM, variables other than those traditionally addressed in self-management interventions may be more important.

Resumen

El objetivo de este estudio era evaluar un modelo de autocontrol para el autocontrol en aquellas personas que viven con VIH y diabetes de tipo 2 (PLWH + T2DM). Llevamos a cabo un estudio predictivo y longitudinal de la información proveniente de un estudio nacional de una población base de PLWH usando un análisis de retraso para evaluar los resultados en la salud a corto y largo plazo para PLWH + T2DM. Utilizamos un conjunto de datos del Center for AIDS Research [Instituto para la Investigación del SIDA] (CFAR) Network of Integrated Clinic Systems [Red de Sistemas de Clínicas Integradas] (CNICS), una red de investigación nacional que cuenta con ocho clínicas al servicio de PLWH. Los resultados que los pacientes reportaron, recolectados en una visita médica, incluyen depresión, adherencia, conteo de células CD4 y la calidad de vida relacionado con la salud (HRQoL). Calculamos el resumen estadístico para describir la muestra. Utilizando análisis de retraso, modelamos luego las tres variables de adherencia, conteo de células CD4 y el HRQoL como función de su antecesor en nuestro modelo conceptual. En el modelo final, un aumento en la adherencia al medicamento correspondió a un aumento en el HRQoL. Un aumento en el conteo de células CD4 correspondió a un aumento en el HRQoL. Se asoció un aumento de depresión retardada con una disminución en el HRQoL. El modelo no fue suficiente como para predecir resultados a corto o largo plazo en PLWH + T2DM. A pesar de que la depresión tenía un impacto moderado, el modelo final no fue clínicamente significativo. Para aquellas personas con un diagnóstico doble de VIH y T2DM, otras variables, además de las que se abordan tradicionalmente en las intervenciones de autocontrol, podrían ser más importantes.

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Data Availability

Data is part of the Center for AIDS Research Network of Integrated Clinical system.

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Acknowledgements

Heidi Crane, PhD, Chris Mathews, Ken Mayer for their assistance with the CNICS research cohort

Funding

National Institutes of Health, National Institute of Nursing Research (Grant No. R15NR017579). CNICS is an NIH funded program (Grant No. R24 AI067039) made possible by the National Institute of Allergy and Infectious Diseases (NIAID). The CFAR sites involved in CNICS include the University of Alabama at Birmingham (Grant No. P30 AI027767), University of Washington (Grant No. P30 AI027757), University of California San Diego (Grant No. P30 AI036214), University of California San Francisco (Grant No. P30 AI027763), Case Western Reserve University (Grant No. P30 AI036219), Johns Hopkins University (Grant No. P30 AI094189, Grant No. U01 DA036935), Fenway Health/Harvard (Grant No. P30 AI060354), and the University of North Carolina at Chapel Hill (Grant No. P30 AI50410).

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Authors and Affiliations

  1. The University of Texas at Austin, Austin, USA

    Julie Ann Zuñiga, Dong Eun Jang, Chelsi West Ohueri & Alexandra A. García

  2. Worcester Polytechnic Institute, Worcester, USA

    Adam Sales

  3. University of Alabama, Tuscaloosa, USA

    Greer Burkholder

  4. Johns Hopkins Medical, Baltimore, USA

    Richard Moore

  5. University of North Carolina, Chapel Hill, USA

    Thibaut Davy-Méndez

  6. University of California, San Francisco, USA

    Katerina Christopoulos

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  1. Julie Ann Zuñiga
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All authors had a significant part of the manuscript in writing, reviewing it, and revising its intellectual and technical content.

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Correspondence to Julie Ann Zuñiga.

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Zuñiga, J.A., Sales, A., Jang, D.E. et al. Self-Management Model fails to Predict Quality of Life for People Living with Dual Diagnosis of HIV and Diabetes. AIDS Behav 26, 488–495 (2022). https://doi.org/10.1007/s10461-021-03405-7

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