[Report] A cycle of invisibility: how older people are overlooked in data and research

Historically, policy-makers and researchers have treated old age as a single, homogeneous stage beginning at State Pension age, consistent with the life-course model comprising periods of education, work and retirement.

At the same time, the tendency to judge success primarily through economic indicators such as GDP, productivity and labour market participation has resulted in retirement being framed as a period of dependency, with the significant non-market contributions of older people entirely overlooked.

Older people are widely excluded from clinical trials despite being the population most likely to use many medications, medical devices and health care interventions. In one study of non-small cell lung cancer trials, people aged 75 and over made up just 7% of trial participants but 43% of the population living with the disease.

Sometimes, it is not that the data does not exist but rather that it isn’t reported. It is not uncommon to see national survey data (see National and commercial data) reported for people ‘aged 65 and over’ – that is all 11 million of them in one huge, undifferentiated group.

In contrast, good data – that is representative, complete, accurate and sufficiently granular – paints a detailed picture of the population and subgroups within it.

Only with good-quality, representative data can we move beyond assumptions and make informed decisions about policy, services, investment and product design that genuinely meet the needs of our whole population.