METHODS: This cross-sectional study utilised data from the Ministry of Health, the Department of Statistics, and the Department of Environment Malaysia. Multilevel logistic regression analysis was employed to examine individual-level factors, including age, sex, ethnicity, nationality, contact history, travel history, and vaccination status. Concurrently, contextual factors were assessed, encompassing district-level determinants such as population density, median household income, urbanisation, the number of health and rural clinics, vaccination rates, fine particulate matter less than 2.5 μm (PM2.5) levels, relative humidity, and temperature, to determine their impact on measles infection risk.
RESULTS: Measles infection was significantly associated with various individual factors. These included age (adjusted odds ratio [aOR], 1.02; 95% confidence interval [CI], 1.02-1.03), ethnicity, non-Malaysian nationality (aOR, 34.53; 95% CI, 8.42- 141.51), prior contact with a measles case (aOR, 2.36; 95% CI, 2.07-2.69), travel history (aOR, 2.30; 95% CI, 1.13-4.70), and vaccination status (aOR, 0.76; 95% CI, 0.72-0.79). Among contextual factors, urbanisation (aOR, 1.56; 95% CI, 1.16- 2.10) and the number of clinics (aOR, 0.98; 95% CI, 0.97-0.99) were significant determinants.
CONCLUSION: This multilevel logistic regression analysis illuminates the complexities of measles transmission, advocating public health interventions tailored to individual and contextual vulnerabilities. The findings highlight the need for a synergistic approach that combines vaccination campaigns, healthcare accessibility improvements, and socioeconomic interventions to effectively combat measles.