Background: Allergic rhinitis (AR) is characterized by the occurrence of at least 2 symptoms of nasal itching, nasal blockage, rhinorrhea, and sneezing, when not afflicted with a cold or flu, with defined atopic sensitization demonstrated by skin prick test or specific IgE responses. Besides the detriment to standard of living and economic burden of AR, both multicentre and single-cohort studies have observed an increase in AR prevalence in Asia over time. Methods: In total, 12 872 individuals, with mean age 22.1 years (SD = 4.8), were recruited from universities in Singapore and Malaysia. Each participant provided epidemiological data based on an investigator-administered questionnaire adapted from the validated International Study of Allergies and Asthma in Childhood (ISAAC) protocol, and atopy status was determined using a skin prick test (SPT) performed by qualified staff. AR was diagnosed according to Allergic Rhinitis and its Impact on Asthma (ARIA) guidelines and a positive SPT result. Results: Sensitization (determined by SPT) to either Blomia tropicalis or Dermatophagoides pteronyssinus was prevalent in 66.5% of the cohort. Current rhinitis (manifesting ≥2 rhinitis symptoms, within the past 12 months) was observed in 48.9% of our population, while AR, which included atopy status, was estimated at 39.4%. Sneezing and rhinorrhea were the most common symptoms among AR cases. AR prevalence decreased with increasing age (OR: 0.979; 95% CI: 0.969-0.989), while male gender (OR: 2.053; 95% CI: 1.839-2.294), and a parental history of allergic diseases (OR: 2.750; 95% CI: 2.284-3.316) were significant risk factors for AR. Upon adjustment for age, gender, and parental history, housing type (OR: 0.632; 95% CI: 0.543-0.736) and income level (>$6000 vs <$2000; OR: 2.461; 95% CI: 2.058-2.947) remained as significant risk factors for AR, while ever having kept a pet (OR: 1.167; 95% CI: 1.025-1.328) emerged as a risk factor. Conflicting results were obtained for indicators of sedentary lifestyle: frequent physical activity (OR: 1.394; 95% CI: 1.150-1.694) and increased duration spent using the TV/computer (OR: 1.224; 95% CI: 1.006-1.489) both increased the risk of AR. Lastly, we used the Quality of Diet based on Glycaemic Index Score (QDGIS) to assess the Glycaemic Index (GI) level of overall diet. We identified lower GI level of overall diet as a protective factor against AR manifestation (OR: 0.682; 95% CI: 0.577-0.807). Conclusion: While the previously established non-modifiable risk factors for AR were present in our study population, the identification of modifiable risk factors, such as TV/computer usage, and dietary habits, opens a new area for research, both in the areas of gene-environment interaction, and management of AR.