Abstract
BACKGROUND: Sexually transmitted infections (STIs) are a major public health problem in developing nations. Identification of risk factors can help in formulating effective strategies against them. The present study was conducted in a tertiary care hospital in North India over 1 year to identify the risk factors associated with STIs. MATERIALS AND METHODS: A questionnaire-based cross-sectional case-control survey was conducted where participants answered questions on demographic details, sexual behavior, and awareness of STIs. Cases were patients with STIs whereas controls were randomly selected from healthy individuals accompanying patients with nonvenereal complaints attending our hospital. RESULTS: There were 106 cases and 64 controls. STI patients had sexual debut 2 years before controls. A higher proportion of STI cases had lower education, multiple sexual partners, lived separately from their partner, had nonregular partners, had protected sex in the last month, had sex under influence of alcohol/illicit drugs, sex in unstructured settings, and engaged in transactional sex, in comparison to controls (P < 0.05). More cases were aware of the symptoms/preventive measures of STIs (P < 0.001). On multivariate analysis, multiple sexual partners, sex under influence of alcohol/illicit drugs with nonregular partner, protected sex in the last month, and knowledge of preventive measures were found to be statistically associated with STIs (P < 0.05). CONCLUSIONS: Our study identifies risk-behavior patterns in patients with STIs, which should be modified to reduce the burden of these diseases. Increasing the knowledge about STIs in these patients can translate into more common condom usage that lends support for strengthening sexual health programs at grass-root levels. LIMITATIONS: The small size of the study population could have led to decreased power of the study to detect differences between cases and controls. The external validity of our results needs to be tested in different population groups involving larger sample sizes.