There is increasing evidence that health and development in adult life is influenced or “programmed” by factors, including nutrition, operating during foetal life and infancy. Early nutrition in a variety of animal species, including primates, has been demonstrated to influence later outcomes, including the likelihood of cardiovascular disease, learning and behaviour problems and longevity (see supplementary data).

Evidence of programming in humans has, until recently, come largely from historical observational studies that showed associations between small size in early life and adult disease risk (see supplementary data). These cohorts were constructed from available health records. They by necessity relied on indirect measures of maternal and infant nutrition and often lacked detailed data on potential confounding variables. Many cohorts enrolled people who were born in the first half of the 20^th century, and it is possible that the nature and size of any associations are different in contemporary populations. Thus, although these studies have generated considerable interest they have been unable to examine direct associations with diet or establish whether associations are causal and cannot, therefore, be used to inform infant feeding recommendations. This has led to a greater emphasis on the need for RCTs to test early nutritional interventions and prospective observational cohorts.

RCTs are generally accepted as methodologically the best approach for informing health policy. They can equalise unknown as well as known confounding factors and so can demonstrate causation; they permit estimation of effect size and so can be used to assess likely economic benefits; and they can, if adequately powered, measure expected adverse effects and thus address safety. Nevertheless, in the context of nutritional programming of disease later in life, they have certain limitations. For example, some trials cannot be performed because they would be unethical (eg, breast feeding versus formula feeding). In addition, although certain …