Carbohydrate nutrition and risk of adiposity-related cancers: results from the Framingham Offspring cohort (1991–2013)

Abstract

AbstractHigher carbohydrate intake, glycaemic index (GI), and glycaemic load (GL) are hypothesised to increase cancer risk through metabolic dysregulation of the glucose-insulin axis and adiposity-related mechanisms, but epidemiological evidence is inconsistent. This prospective cohort study investigates carbohydrate quantity and quality in relation to risk of adiposity-related cancers, which represent the most commonly diagnosed preventable cancers in the USA. In exploratory analyses, associations with three site-specific cancers: breast, prostate and colorectal cancers were also examined. The study sample consisted of 3184 adults from the Framingham Offspring cohort. Dietary data were collected in 1991–1995 using a FFQ along with lifestyle and medical information. From 1991 to 2013, 565 incident adiposity-related cancers, including 124 breast, 157 prostate and sixty-eight colorectal cancers, were identified. Cox proportional hazards models were used to evaluate the role of carbohydrate nutrition in cancer risk. GI and GL were not associated with risk of adiposity-related cancers or any of the site-specific cancers. Total carbohydrate intake was not associated with risk of adiposity-related cancers combined or prostate and colorectal cancers. However, carbohydrate consumption in the highest v. lowest quintile was associated with 41 % lower breast cancer risk (hazard ratio (HR) 0·59; 95 % CI 0·36, 0·97). High-, medium- and low-GI foods were not associated with risk of adiposity-related cancers or prostate and colorectal cancers. In exploratory analyses, low-GI foods, were associated with 49 % lower breast cancer risk (HR 0·51; 95 % CI 0·32, 0·83). In this cohort of Caucasian American adults, associations between carbohydrate nutrition and cancer varied by cancer site. Healthier low-GI carbohydrate foods may prevent adiposity-related cancers among women, but these findings require confirmation in a larger sample.