Most epidemiological data suggest a protective role for fruits and vegetables in the prevention of several common epithelial cancers, including digestive and major non-digestive neoplasms. The relation between frequency of consumption of vegetables and fruit and cancer and myocardial infarction risk was analysed using data from a series of case-control studies conducted in Italy. For digestive tract cancer, population attributable risks for low intake of vegetables and fruit ranged between 15 and 40%. A selected number of antioxidants showed a significant inverse relation with breast and colorectal cancer risk, although the main components responsible for the favourable effect of a diet rich in vegetables and fruit remain undefined. Fish tends to be another favourable indicator of reduced cancer risk. In contrast, subjects reporting frequent red meat intake showed a relative risk consistently above unity for several common neoplasms. Whole grain food intake was consistently related to reduced risk of several types of cancer, particularly of the upper digestive tract neoplasms. Epidemiological evidence of the relation between fiber and colorectal cancer indicated a possible protections. In contrast, refined grain intake was associated to increased risk of different types of cancer, pointing to a potential role of insulin-like growth factor 1 (IGF-1). A low risk diet for cardiovascular disease includes high consumption of fish, vegetables and fruit, and hence rich in ascorbic acid and other antioxidants, thus sharing several aspects with a favourable diet for cancer.
In this paper we present the R implementation of a GLIM macro which fits age-period-cohort model following Osmond and Gardner. In addition to the estimates of the corresponding model, owing to the programming capability of R as an object oriented language, methods for printing, plotting and summarizing the results are provided. Furthermore, the researcher has fully access to the output of the main function (apc) which returns all the models fitted within the function. It is so possible to critically evaluate the goodness of fit of the resulting model