Self-Reported Prevalence and Predictors of HIV and Gonorrhea Among Primary Healthcare Attendees: A Cross-Sectional...

Background/Objectives: This study aimed to estimate self-reported prevalence of HIV and gonorrhea among primary healthcare attendees in Riyadh and to identify key demographic, behavioral, and clinical predictors, acknowledging that diagnoses were based on participant self-report rather than laboratory confirmation. Methods: A cross-sectional survey was conducted between March and July 2023 across 48 primary healthcare centers in Riyadh. A total of 14,239 adult participants (aged ≥18 years) completed an electronically administered questionnaire that included self-reported prior diagnoses of HIV and gonorrhea. Multivariable logistic regression models were used to identify independent predictors of self-reported HIV and gonorrhea. Results: The self-reported prevalence of HIV was 2.6% (95% CI: 2.35-2.87%), and gonorrhea was 3.1% (95% CI: 2.83-3.40%). Several factors were independently associated with higher odds of self-reported infection. Younger age (<50 years) increased risk (HIV: AOR = 2.19; gonorrhea: AOR = 1.57), as did female sex (HIV: AOR = 1.67; gonorrhea: AOR = 1.59), higher education (HIV: AOR = 1.29; gonorrhea: AOR = 1.23), married status (HIV: AOR = 1.76; gonorrhea: AOR = 1.49), and insurance coverage (HIV: AOR = 2.01; gonorrhea: AOR = 1.88). Behavioral and clinical factors included smoking (HIV: AOR = 4.79; gonorrhea: AOR = 2.41), hypertension (HIV: AOR = 2.58; gonorrhea: AOR = 1.49), obesity (HIV: AOR = 11.55; gonorrhea: AOR = 9.02), hypercholesterolemia (HIV: AOR = 2.24; gonorrhea: AOR = 2.53), and heart disease (HIV: AOR = 11.31; gonorrhea: AOR = 8.77). The notably high associations for obesity and heart disease should be interpreted with caution, as they may be influenced by detection bias or residual confounding within the healthcare-seeking sample. Conclusions: This study provides key insights into the self-reported burden and predictors of HIV and gonorrhea in Saudi Arabia. While identifying significant demographic and metabolic risk profiles, the high magnitude of certain clinical associations must be interpreted with caution due to potential detection bias and residual confounding. Given the reliance on self-reported data, these findings should be viewed as an epidemiological baseline rather than absolute prevalence. Prioritizing clinical context over statistical values and strengthening integrated, laboratory-based surveillance within primary care will be essential for improving early detection and evidence-based prevention strategies in the region.