Jielu Lin1, Jessica A Kelley-Moore2. 1. National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland. lin.jielu@nih.gov. 2. Department of Sociology, Case Western Reserve University, Cleveland, Ohio.
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.
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.
Authors: Jersey Liang; Benjamin A Shaw; Neal Krause; Joan M Bennett; Erika Kobayashi; Taro Fukaya; Yoko Sugihara Journal: J Gerontol B Psychol Sci Soc Sci Date: 2005-07 Impact factor: 4.077
Authors: Alejandro Álvarez-Bustos; Jose Antonio Carnicero-Carreño; Juan Luis Sanchez-Sanchez; Francisco Javier Garcia-Garcia; Cristina Alonso-Bouzón; Leocadio Rodríguez-Mañas Journal: J Cachexia Sarcopenia Muscle Date: 2021-12-23 Impact factor: 12.910