摘要：A multilevel model (allowing for individual risk factors and geo-graphic context) is developed for jointly modelling cross-sectional di erencesin diabetes prevalence and trends in prevalence, and then adapted to providegeographically disaggregated diabetes prevalence forecasts. This involves aweighted binomial regression applied to US data from the Behavioral RiskFactor Surveillance System (BRFSS) survey, speci cally totals of diagnoseddiabetes cases, and populations at risk. Both cases and populations are dis-aggregated according to survey year (2000 to 2010), individual risk factors(e.g., age, education), and contextual risk factors, namely US census divi-sion and the poverty level of the county of residence. The model includes alinear growth path in decadal time units, and forecasts are obtained by ex-tending the growth path to future years. The trend component of the modelcontrols for interacting inuences (individual and contextual) on changingprevalence. Prevalence growth is found to be highest among younger adults,among males, and among those with high school education. There are alsoregional shifts, with a widening of the US \diabetes belt".
