Predictors of HIV risk behaviors among older adults : a multilevel analysis.

HIV;Older adults

Laneshia Rae' McCord

University:University of Louisville

Department:Social Work

关键词: HIV;    Older adults;   

Others  :  https://ir.library.louisville.edu/cgi/viewcontent.cgi?article=1938&context=etd

美国|英语

来源: The Universite of Louisville's Institutional Repository

【 摘 要 】

Over the past thirty years, HIV has become a worldwide epidemic. Given the surge in the rate of sexually transmitted diseases including HIV, this sheds light as a new worry for sexually active older adults, raising questions about risk behaviors among this group. The issues facing older adults are three-fold in that they are 1) not identifying themselves as being at risk; 2) not identifying risk behaviors; and 3) are not largely being identified in the public realm as participating in risk behaviors. For these reasons, understanding both environmental and individual factors and their unique influences on HIV risk behaviors among older adults is very important. A study was undertaken to develop an understanding of the environmental and individual population factors that predict HIV risk behaviors among older adults using population- based data from the Behavioral Risk Factor Surveillance System and eight state level data sources, guided by Andersen's Behavioral Model of Health Utilization (2007). The model investigated the predictive ability of social and environmental factors in addition to individual factors on HIV risk behaviors. Methods: The research design for the study was a multilevel repeated cross-sectional design with a three level nested structure. The software package MLwiN was used to conduct the multilevel analysis using the Deviance Information Criterion (DIC) analytical method to assess the fit of models with Markov chain Monte Carlo (MCMC) estimation. Using a nationally representative sample of 23,950 individuals from 2008 to 2011, nested in 51 states, the trend study allowed for an understanding of the state and individual-level factors that predict participating in HIV risk behaviors. Results: In each step, the model fit improved the DIC statistic. Overall, the results indicated that there were differences between states and their levels of HIV risk behaviors. While HIV risk behaviors decreased from 2008 to 2011, there was significant variation between and within states in the probability of individual HIV risk behaviors. States that had a higher percentage white females, a higher percentage of persons uninsured, a higher percentage of whites with AIDS, a lower percentage of Asians with AIDS, and a lower percentage of Other races with AIDS had a higher probability of individuals participating in HIV risk behaviors. All of the individual predictors of HIV risk behaviors were statistically significant. Conclusion: With the increase in older adults living with HIV or becoming diagnosed or infected later in life, it is paramount that HIV risk behaviors