From Noise to Signal: The Age and Social Patterning of Intra-Individual Variability in Late-Life Health.
| Year of Publication |
2017
|
|---|---|
| Author | |
| Journal |
J Gerontol B Psychol Sci Soc Sci
|
| Volume |
72
|
| Issue |
1
|
| Number of Pages |
168-179
|
| ISSN Number |
1758-5368
|
| 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. |
| Date Published |
2017 Jan
|
| URL |
http://psychsocgerontology.oxfordjournals.org/content/early/2015/08/26/geronb.gbv081.abstract
|
| DOI |
10.1093/geronb/gbv081
|
| Alternate Journal |
J Gerontol B Psychol Sci Soc Sci
|
| PMID |
26320123
|
| PMCID |
PMC5156487
|
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