The validity of self-reported height and weight in 4808 EPIC–Oxford participants was assessed by comparing them with measured values. The study found high Spearman rank correlations (r > 0.9, P < 0.0001) between self-reported and measured height, weight, and BMI. Men overestimated their height by an average of 1.23 cm, while women overestimated by 0.60 cm. Women underestimated their weight by an average of 1.40 kg, while men underestimated by 1.85 kg. Using standard BMI categories, 22.4% of men and 18.0% of women were misclassified based on self-reported data. After correcting self-reported values with predictive equations, misclassification decreased to 15.2% in men and 13.8% in women. Self-reported height and weight data are valid for identifying relationships in epidemiological studies. However, systematic errors exist, with men overestimating height more than women and heavier individuals overestimating height more. Weight underestimation was more pronounced in heavier individuals. BMI was underestimated in most categories, with the greatest underestimation in the obese category. Misclassification of BMI categories was higher in obese individuals and older participants. Correcting self-reported values using predictive equations improved BMI accuracy. The study highlights the importance of using measured values in representative samples to enhance the accuracy of BMI estimates in epidemiological analyses.The validity of self-reported height and weight in 4808 EPIC–Oxford participants was assessed by comparing them with measured values. The study found high Spearman rank correlations (r > 0.9, P < 0.0001) between self-reported and measured height, weight, and BMI. Men overestimated their height by an average of 1.23 cm, while women overestimated by 0.60 cm. Women underestimated their weight by an average of 1.40 kg, while men underestimated by 1.85 kg. Using standard BMI categories, 22.4% of men and 18.0% of women were misclassified based on self-reported data. After correcting self-reported values with predictive equations, misclassification decreased to 15.2% in men and 13.8% in women. Self-reported height and weight data are valid for identifying relationships in epidemiological studies. However, systematic errors exist, with men overestimating height more than women and heavier individuals overestimating height more. Weight underestimation was more pronounced in heavier individuals. BMI was underestimated in most categories, with the greatest underestimation in the obese category. Misclassification of BMI categories was higher in obese individuals and older participants. Correcting self-reported values using predictive equations improved BMI accuracy. The study highlights the importance of using measured values in representative samples to enhance the accuracy of BMI estimates in epidemiological analyses.