Tobacco use prevalence – disentangling associations between Alaska Native race, low socio-economic status and rural disparities

BACKGROUND: Tobacco use rates are exceptionally high among indigenous people in North America. Alaska Native, low socio-economic status (SES) and rural communities are high-priority populations for Alaska's Tobacco Control program. DESIGN: For the purpose of better informing tobacco control interventions, we conducted a descriptive study to describe high-priority groups using prevalence-based and proportion-based approaches. METHODS: With data from 22,311 adults interviewed for Alaska's 2006–2010 Behavioral Risk Factor Surveillance System (BRFSS), we used stratified analysis and logistic regression models to describe the current use of cigarettes and smokeless tobacco (SLT) (including iq'mik, a unique Alaska Native SLT product) among the 3 populations of interest. RESULTS: “Population segments” were created with combinations of responses for Alaska Native race, SES and community type. We identified the highest prevalence and highest proportion of tobacco users for each type of tobacco by “segment”. For cigarette smoking, while the largest proportion (nearly one-third) of the state's smokers are non-Native, high SES and live in urban settings, this group also has lower smoking prevalence than most other groups. Alaska Native, low SES, rural residents had both high smoking prevalence (48%) and represented a large proportion of the state's smokers (nearly 10%). Patterns were similar for SLT, with non-Native high-SES urban residents making up the largest proportion of users despite lower prevalence, and Alaska Native, low SES, rural residents having high prevalence and making up a large proportion of users. For iq'mik use, Alaska Native people in rural settings were both the highest prevalence and proportion of users. CONCLUSION: While Alaska Native race, low SES status and community of residence can be considered alone when developing tobacco control interventions, creating “population segments” based on combinations of factors may be helpful for tailoring effective tobacco control strategies and messaging. Other countries or states may use a similar approach for describing and prioritizing populations.