Prediction of measured weight from self‐reported weight was not improved after stratification by body mass index

Objective:

Self‐reported weight may underestimate measured weight. Researchers have tried to reduce the error using statistical models to predict weight from self‐reported weight. We investigate whether deriving equations within separate BMI categories improves the prediction of weight compared with an equation derived regardless of an individual's BMI.

Design and Methods:

The analysis included self‐reported and measured data from 20,536 individuals participating in the EPIC‐Norfolk study. In a derivation set (n = 15,381) two approaches were used to predict weight from self‐reported weight: (1) using a linear regression model with measured weight as outcome and self‐reported weight and age as predictors, and (2) using the same model fit separately within 3 strata defined by BMI (< 25, 25‐30, ≥30 kg m^?2). The performance of these approaches was assessed in a validation set (n = 5,155). Measured weight was compared to self‐reported weight and predicted weight.

Results:

Self‐reported weight underestimated measured weight (P < 0.0001): mean difference ?1.2 ± 3.1 kg (men), ?1.3 ± 2.5 kg (women). Underestimation was greater in obese participants (P < 0.0001). Predicted weight using approach 1 was not significantly different from measured weight (P < 0.05). However, in individuals with BMI < 25 kg m^?2, weight was overestimated in men (0.90 ± 3.87 kg) and women (0.57 ± 2.06 kg), but underestimated in overweight (?0.29 ± 3.58, ?0.20 ± 2.62 kg) and obese (?1.46 ± 5.05 kg, ?0.73 ± 3.54 kg) men and women.

Conclusions:

Using separate prediction equations in strata of BMI did not further improve prediction of weight. In conclusion, predicted weight was closer to measured weight compared with self‐reported weight, but using equations derived in strata of BMI did not further improve the prediction and are not recommended for prediction of weight.