Prevalence and risk factors of self-medication with antibiotics in the general population of Tehran-a...

Given the ongoing global threat of antimicrobial resistance (AMR), largely fueled by self-medication with antibiotics (SMA), this study offers important insights from southern Tehran-an underrepresented region in national data-regarding the prevalence and determinants of SMA. We investigated several previously underexplored key factors, including socioeconomic status (SES), education, lifestyle, mental health, and COVID-19 history.

A population-based cross-sectional telephone survey was conducted in three major regions of southern Tehran in 2023, involving 1,311 adult participants who were selected through stratified random sampling with probability proportional to size. A structured composite index was developed using data on lifestyle factors such as body mass index, physical activity, smoking, nutrition, mental and physical health, socioeconomic status, and frequency of SMA.

Of the participants, 50.4% were male and 49.6% female, with an overall SMA prevalence of 21.3% (n = 279). Higher education (AOR = 1.93, 95% CI = 1.25-2.96, p value = 0.003), higher SES (AOR = 3.59, 95% CI = 1.82-6.82, p value < 0.001), basic insurance (AOR = 1.69, 95% CI = 1.10-2.63, p value = 0.019), and a history of uncomplicated COVID-19 infection (AOR = 2.30, 95% CI = 1.44-3.78, p value = 0.001) were significantly associated with increased SMA. In contrast, a healthy lifestyle (AOR = 0.66, p value = 0.033) and good mental health (AOR = 0.31, p value < 0.001) were associated with lower SMA rates.

Our findings primarily suggest that we should focus our public health efforts on specific subpopulations affected by SMA. Community-based antibiotic stewardship programs should use educational and behavioral approaches with an emphasis on mental health and health literacy. Policymakers should also consider whether to modify regulations to prevent the general public from obtaining antibiotics without a prescription. Finally, the findings from a representative sample from southern Tehran illustrate the value of local data in national AMR decision-making and avoiding assumptions.