Adequate vitamin D status is essential to maintain healthy bones. It is difficult, however, to determine recommended intake levels as vitamin D status does not solely depend on vitamin D consumed from food and supplements. A biomarker for vitamin D status is a person's 25-hydroxyvitamin D (25(OH)D) serum level. From a practical viewpoint, we cannot make public health recommendations using 25(OH)D levels and instead want to make recommendations for vitamin D intake. In our work, we model the association between intake of vitamin D and 25(OH)D serum level. Since we can only obtain noisy measurements of vitamin D intake, we propose a nonlinear measurement error model to describe the dependency of 25(OH)D serum levels on vitamin D intake which accounts for the nuisance day-to-day variance when estimating long-term average intake. Using data from the 2005-2006 National Health and Nutrition Examination Survey (NHANES), we show how the measurement errors depend on vitamin D intake. In the application, we assume that the measurement errors follow a truncated normal distribution with mean and variance depending on usual intake.