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Weight is more informative than body mass index for predicting post-menopausal breast cancer risk: Prospective Family Study Cohort (ProF-SC).

We considered whether weight is more informative than body mass index = weight/height2 (BMI) when predicting breast cancer risk for post-menopausal women, and if the weight association differs by underlying familial risk. We studied 6,761 women post-menopausal at baseline with a wide range of familial risk from 2,364 families in the Prospective Family Study Cohort (ProF-SC). Participants were followed for on average 11.45 years and there were 416 incident breast cancers. We used Cox regression to estimate risk associations with log-transformed weight and BMI after adjusting for underlying familial risk. We compared model fits using the Akaike Information Criterion (AIC) and nested models using the likelihood ratio test. The AIC for the weight-only model was 6.22 units lower than for the BMI-only model, and the log risk gradient was 23% greater. Adding BMI or height to weight did not improve fit (ΔAIC=0.90 and 0.83, respectively; both P=0.3). Conversely, adding weight to BMI or height gave better fits (ΔAIC=5.32 and 11.64; P=0.007 and 0.0002, respectively). Adding height improved only the BMI model (ΔAIC=5.47; P=0.006). There was no evidence that the BMI or weight associations differed by underlying familial risk (P>0.2). Weight is more informative than BMI for predicting breast cancer risk, consistent with non-adipose as well as adipose tissue being etiologically relevant. The independent but multiplicative associations of weight and familial risk suggest that, in terms of absolute breast cancer risk, the association with weight is more important the greater a woman's underlying familial risk.