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

Abstract

Objectives: 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.

Method: 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.

Results: 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.

Discussion: 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.

Keywords: Health disparities; Intra-individual variability; Multilevel growth curves; Residuals.

Figure 1.

Hypothesized age-based patterns of intra-individual variability in health.

Figure 2.

Normal quantile plot of level-1 residuals in adjusted health trajectories.