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Zeng C, Qiao S, Li X, Yang X, Shen Z, Zhou Y. Differential relationships of stress and HIV disclosure by gender: a person centered longitudinal study. BMC Public Health 2021; 21:263. [PMID: 33530986 PMCID: PMC7852186 DOI: 10.1186/s12889-021-10291-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Accepted: 01/20/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Existing literature mostly consider HIV disclosure as a static event and investigate its relationship with stress using a cross-sectional design. It is unclear about the dynamic changes of HIV disclosure levels (defined as the number of disclosure targets) and how stress may influence these changes. This study explored different disclosure levels using a person-centered longitudinal approach, examined whether stress could predict these disclosure levels, and investigated if this relationship differed by gender among people living with HIV (PLWH). METHODS Data were derived from a prospective cohort study conducted from November 2016 to January 2018 in Guangxi, China. Four hundred forty-four PLWH were included. Participants were assessed on perceived stress, sociodemographic characteristics, and number of HIV disclosure targets at baseline, 6-month, and 12-month follow-ups. Growth mixture modeling was used to characterize disclosure levels based on the changes of disclosure target number. Multinomial logistic regression was used to predict disclosure levels with baseline stress after adjusting for covariates. The interaction effect of stress by gender was examined. Adjusted odds ratio (AOR) with its 95% confidence interval were reported to show the strength of association. RESULTS: Three levels of disclosure were characterized as "Low levels of disclosure" (Level One), "Increased levels of disclosure" (Level Two), and "High levels of disclosure" (Level Three). Accordingly, 355 (81.2%), 28 (6.4%), and 64 (12.4%) of PLWH were categorized respectively under low, increased, and high levels of disclosure. The interaction of baseline stress by gender was significant in differentiating Level One from Three (AOR = 0.85 [0.74 ~ 0.99]) while it was not significant between Level One and Two (AOR = 0.96 [0.81 ~ 1.15]). Compared to female, male PLWH with higher baseline stress had lower probability to have consistent high disclosure levels over time. PLWH who were married/cohabited had lower probability of being classified into consistent high levels of disclosure than low level (AOR = 0.43 [0.19 ~ 0.94]). CONCLUSIONS There was gender difference in the relationship between stress and levels of HIV disclosure. To promote HIV disclosure, gender tailored interventions should be employed to help PLWH cope with stress.
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Affiliation(s)
- Chengbo Zeng
- South Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
- UofSC Big Data Health Science Center, University of South Carolina, Columbia, SC, USA.
- Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
| | - Shan Qiao
- South Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
- UofSC Big Data Health Science Center, University of South Carolina, Columbia, SC, USA
- Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Xiaoming Li
- South Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
- UofSC Big Data Health Science Center, University of South Carolina, Columbia, SC, USA
- Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Xueying Yang
- South Carolina SmartState Center for Healthcare Quality, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
- UofSC Big Data Health Science Center, University of South Carolina, Columbia, SC, USA
- Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA
| | - Zhiyong Shen
- Guangxi Center for Disease Prevention and Control, Nanning, Guangxi, China
| | - Yuejiao Zhou
- Guangxi Center for Disease Prevention and Control, Nanning, Guangxi, China
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