From Noise to Signal: The Age and Social Patterning of Intra-Individual Variability in Late-Life Health

Despite a long tradition of attending to issues of intra-individual variability in the gerontological literature, large-scale panel studies on late-life health disparities have primarily relied on average health trajectories, relegating intra-individual variability over time to random error terms, or "noise." This article reintegrates the systematic study of intra-individual variability back into standard growth curve modeling and investigates the age and social patterning of intra-individual variability in health trajectories.

Using panel data from the Health and Retirement Study, we estimate multilevel growth curves of functional limitations and cognitive impairment and examine whether intra-individual variability in these two health outcomes varies by age, gender, race/ethnicity, and socioeconomic status, using level-1 residuals extracted from the adjusted growth curve models.

For both outcomes, intra-individual variability increases with age. Racial/ethnic minorities and individuals with lower socioeconomic status tend to have greater intra-individual variability in health. Relying exclusively on average health trajectories may have masked important "signals" of life course health inequality.

The findings contribute to scientific understanding of the source of heterogeneity in late-life health and highlight the need to further investigate specific life course mechanisms that generate the social patterning of intra-individual variability in health status.