Understanding Ageing. An evaluation of research designs for assessing the interdependence of ageing-related changes

Cross-sectional studies of samples varying widely in age have found moderate to high levels of shared age-related variance among measures of cognitive and physiological capabilities, leading researchers to posit common factors or common causal influences for diverse age-related phenomenon.

The influence of population average changes with age on cross-sectional estimates of association has not been widely appreciated in developmental and ageing research. Covariances among age-related variables in cross-sectional studies are highly confounded in regards to inferences about associations among rates of change within individuals since covariances can result from a number of sources including average population age-related differences (fixed age effects) in addition to initial individual differences and individual differences in rates of ageing (random age effects). Analysis of narrow age-cohort samples may provide a superior analytical basis for testing hypotheses regarding associations between rates of change in cross-sectional studies.

The use of age-heterogeneous cross-sectional designs for evaluating interdependence of ageing-related processes is discouraged since associations will not necessarily reflect individual-level correlated rates of change. Typical cross-sectional studies do not provide sufficient evidence for the interdependence of ageing-related changes and should not serve as the basis for theories and hypotheses of ageing. Reanalyzing existing cross-sectional studies using a sequential narrow-age cohort approach provides a useful alternative for evaluating associations between ageing-related changes. Longitudinal designs, however, provide a much stronger basis for inference regarding associations between rates of ageing within individuals.