Life course methods and functional trajectories

It is clear that both protective and adverse risk factors operate throughout life to cause disease and disability. But whether these factors are cumulative, or if their rate of change is particularly important, is still unclear. By understanding the trajectories of risk factors i.e how they operate across life and interact with each other, we can better identify periods in life which are particularly important to cause disease, and where interventions may have the greatest potential for benefit.

Aim
This underpinning theme provides the statistical resource to support all programmes in their analysis of complex longitudinal data
Importance
Knowledge of life course trajectories of subclinical health-related traits are vital to the understanding of the development of disease and morbidity in later life. Repeated measurements of body structure and
function, and of environmental exposures and lifestyle, are collected in longitudinal cohorts such as the
MRC National Survey of Health and Development (NSHD), providing unique opportunities to study effects of exposure across the whole of life. Lifetime patterns of exposure can thus be assessed, and such patterns may be a stronger predictor of later life health and ageing than a single midlife measure.
Further, such data allows for the testing of sensitive periods during the life course during which exposure may have the greatest effect on an outcome, or for assessing whether accumulation of exposure is most relevant. Thus it is possible to identify when in the life course intervention may be most effective.
Methods
Understanding what constitutes a healthy trajectory into old age, and how midlife change is related to later life trajectories are important in order to appropriately manage risk factors in older people. The modelling of trajectories as a repeated outcome measure are standard, but more novel approaches are required to deal with, for example, inter-relationships between different functions. Further, research has focussed on associations with the smooth average long-term changes, with less attention paid to shorter-term fluctuations, variability or the immediate impact of health or social events. We will apply standard and novel statistical methods to these problems
Translational implications
These techniques, applied to specific scientific questions in each of the programmes, has the potential to identify critical or sensitive periods during life which determine disease risk, and where intervention could potentially be the most effective