Age-Old Stories: Increasing the Visibility of Older Individuals Past and Present

With its deep-time perspective and global reach, archaeology is a powerful tool for challenging negative stereotypes of old age. Over 11 million (18.6%) people in the UK are aged over 65 and caring for an ageing population is a pressing challenge of the 21st century. Ageism, however, remains the most commonly experienced form of prejudice in Europe, with over 1 million older people going more than a month without speaking to friends, neighbours or family. This loneliness epidemic is a major public health concern impacting mental and physical wellbeing, with estimated associated healthcare costs in excess of £6,000 per person per decade. These statistics make stark reading for both healthcare professionals and economists, and have led to the launch of a nationwide ‘Tacking Loneliness Network Action Plan’.
The low social status of older adults in industrialised societies is tied to their relative market value as contributors to capitalist economies. By developing an ‘archaeology of ageing’, Age-Old Stories will challenge this position. Children, who can be aged quite precisely by the developmental stages of their bones and teeth, are now a common feature of archaeological narratives about the past. Older adults on the other hand remain invisible, not least because age-at-death estimates on skeletal remains become less accurate as people age and are not sufficiently refined to examine this diverse group of individuals.
As the first large-scale bioarchaeological study focusing on ‘older adults’ (i.e. individuals identified as 40/45/50+ years by traditional osteoarchaeological methods), Age-Old Stories has three principal aims:

to increase the accuracy of bioarchaeological methods (aDNA, proteomics, osteology, histology) for ageing ‘older adults’ 
to combine biomolecular techniques with funerary archaeology to understand the diet, health, mobility and social status of older adults in a range of pre-industrial societies across Europe
to use this research...