Obesity and its Risk Associations in Older Mexicans Living with HIV

It is expected that by 2020, older adults living with HIV (OALHV) represents more than 50% of the population living with HIV worldwide [1,2]. It should be mentioned that some of them have aged with HIV and others have acquired the infection only in old age. In addition, OALHIV have a high risk for developing chronic diseases associated with age, but that occur earlier among people living with HIV, unlike those without the infection [3-5]. HIV infection causes premature aging and this seems to be caused by chronic immune activation as well as numerical loss and dysfunction of CD4+ cells. Others biological similarities between aging and HIV infection include DNA damage, loss of DNA repair capacity and altered mechanisms of apoptosis of immune system cells [6]. The increase in life expectancy and survival caused by advances in the treatment of HIV infection, resulted in an increase in the prevalence of some chronic diseases included obesity [7,8]. Thus, a 2-year longitudinal study of 116 participants was conducted to determine the prevalence of obesity and its risk associations in OALHIV. The participants were adults over 50 years of age living with HIV and attending an HIV clinic in a university hospital in the city of Guadalajara in Mexico. Recruitment occurred between January 2015 and January 2017. All participants underwent a geriatric evaluation with which the diagnoses of geriatric syndromes were obtained. In accordance with convention, we defined obesity as BMI ≥ 30 kg/m2. Correlates variables included age, sex, CD4+ count and some geriatrics syndromes. Frailty was defined according to phenotype proposed by Fried [5]. Depression was assessed using the Geriatric Depression Scale [3]. CD4+ T-lymphocyte count (CD4+) was measured by flow cytometry (BD FACSCalibur™). Multivariate logistic regression analyses were created to identify the socio-demographic and health correlates of obesity. The final model included sex, and the CD4 count, age at the time of HIV diagnosis and the presence of symptoms of depression were included as confounding variables. All statistical tests were performed using 95% Confidence Intervals (CI) at the 0.05 level. Statistical analyses were conducted using the Stata statistical package for Windows® (Stata Corp., Texas, IL., v. 14).