A forgotten population: older adults with newly diagnosed HIV

AIDS Patient Care STDS. 2014 Oct;28(10):530-6. doi: 10.1089/apc.2014.0152. Epub 2014 Sep 11.

Abstract

Limited data are available regarding adults age ≥50 at initial HIV diagnosis. Improved understanding of this group is critical in designing interventions to facilitate earlier diagnosis and linkage to HIV care. We characterize individuals newly diagnosed with HIV, particularly those ≥50 years old, and examine the relationship between age and late diagnosis defined as concurrent HIV and AIDS diagnoses. This is a retrospective study of individuals newly diagnosed with HIV from 2006-2011 at an academic medical center in New York City. Multivariable logistic regression was performed to evaluate the effect of age, gender, race/ethnicity, risk factor, and prior medical visits on late diagnosis. Adults age ≥50 comprised 21.3% of all newly diagnosed individuals. Among these older adults, 70.0% were diagnosed as inpatients and 68.9% concurrent with AIDS, compared to 41.7% and 38.9% of younger adults, respectively. On adjusted analyses, age ≥50 (OR 3.13, 95% CI 1.63, 5.98) and injection drug use (OR 4.4, 95% CI 1.31, 14.75) were positively associated with late diagnosis, whereas female gender was negatively associated with late diagnosis (OR 0.52, 95% CI 0.28, 0.98). Our data suggest that HIV testing efforts targeting older adults are essential to address the unmet needs of this population, including implementation of HIV screening guidelines in primary care settings.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors*
  • Aged
  • Aged, 80 and over
  • Delayed Diagnosis*
  • Early Diagnosis*
  • Female
  • HIV Infections / diagnosis*
  • HIV Infections / epidemiology
  • Health Services Needs and Demand
  • Humans
  • Logistic Models
  • Male
  • Mass Screening / statistics & numerical data*
  • Middle Aged
  • Multivariate Analysis
  • Needs Assessment
  • New York City / epidemiology
  • Population Surveillance
  • Primary Health Care
  • Retrospective Studies
  • Risk Factors
  • Sex Distribution