Reports from nutritional epidemiology studies lack reliability if based solely on self-reported dietary consumption estimates. Consumption biomarkers are available for some components of diet. These can be collected in subsets of study cohorts, along with corresponding self-report assessments. Linear regression of (log-transformed) biomarker values on corresponding self-report values and other pertinent study subject characteristics yields calibration equations for dietary consumption, from which calibrated consumption estimates can be calculated throughout study cohorts. Nutritional epidemiology disease association studies of enhanced reliability can be expected from analyses that relate disease risk to calibrated consumption estimates. Applications to the study of energy and protein consumption in relation to cardiovascular diseases, type 2 diabetes, and cancer in the Women's Health Initiative will be briefly summarized. Also, challenges related to variables that may either mediate or confound associations of interest will be described, along with the need for longitudinal biomarker and self-report data, and the need for additional nutritional biomarker development.