We propose a set of analyses that examine the antecedents, correlates, and consequences of change in biological measures and health. Specifically, we will examine three questions. 1) What individual and environmental factors contribute to our understanding of downstream health and survival? We will focus on links between health and stressful experience, SES, psychosocial vulnerability and emotional well- being. 2) What factors predict change in bioindicators? We will examine demographic and psychosocial factors along with environmental exposures to determine how prior experience is associated with change in biomarkers. We will focus on the effects of socioeconomic status (SES), emotional well-being, and chronic and acute stressors. We will examine change across the full array of biomarkers;a particularly innovative analysis will examine the connection between stressful experience and telomere attrition. 3) Do changes in bioindicators predict health outcomes and survival? We will use a life course framework to explore how change in bioindicators and trajectories of prior experience and exposures are associated with subsequent health, physical and cognitive function, and survival. Of particular interest are several high-profile bioindicators (telomere length, 5-HTTLPR genotype, and inflammatory markers), new data on factors that may modify these associations (trauma, caregiving, sleep quality, chronic pain, and optimism), and gene-environment interactions. We request funding for two data collection activities in order to enrich previously-collected data: A second round of in-home functional assessments in 2010;and selected assays of frozen biospecimens. Specifically, we will: 1) Obtain interviewer-measured markers of health and function collected in the home. The household protocol of the 2006 biomarker study included measures of grip strength, timed walks, chair stands, blood pressure, and lung capacity. We propose to collect these data for the survivors of the 2006 study by supplementing the longitudinal survey planned for 2010. These assessments will be added to the public use data set. 2) We will perform assays (5-HTTLPR, homocysteine, folate, ICAM-1, e-selectin, and high sensitivity C-reactive protein) of frozen round 1 blood specimens to """"""""backfill"""""""" the round 1 data to the round 2 standard. The results of these assays will be added to the publicly released data. The work builds on a foundation of two decades of health and psychosocial data, two rounds of biomarker collection, and an interdisciplinary research team with an established record of productive collaboration.
The proposed data collection and analysis will help researchers understand how and why environmental factors - such as individuals'socioeconomic status and the type and extent of life challenges that they face - influence health and survival at the older ages. A central focus is to understand the role of different biological mechanisms, including cardiovascular and metabolic function, immune response, and genetic influences, that underlie the linkages between the social environment and downstream health. The findings have implications for identifying the strongest predictors of population health and for expanding clinicians'focus beyond conventional risk factors of cardiovascular disease.
|Lin, Yu-Hsuan; Jen, Min-Hua; Chien, Kuo-Liong (2017) Association between life-course socioeconomic position and inflammatory biomarkers in older age: a nationally representative cohort study in Taiwan. BMC Geriatr 17:201|
|Glei, Dana A; Goldman, Noreen; Ryff, Carol D et al. (2017) Can we determine whether physical limitations are more prevalent in the US than in countries with comparable life expectancy? SSM Popul Health 3:808-813|
|Cornman, Jennifer C; Glei, Dana A; Goldman, Noreen et al. (2016) Cohort Profile: The Social Environment and Biomarkers of Aging Study (SEBAS) in Taiwan. Int J Epidemiol 45:54-63|
|Glei, Dana A; Goldman, Noreen; Risques, Rosa Ana et al. (2016) Predicting Survival from Telomere Length versus Conventional Predictors: A Multinational Population-Based Cohort Study. PLoS One 11:e0152486|
|Goldman, Noreen; Glei, Dana A (2015) Quantifying the value of biomarkers for predicting mortality. Ann Epidemiol 25:901-6.e1-4|
|Cornman, Jennifer C; Glei, Dana A; Goldman, Noreen et al. (2015) Socioeconomic status and biological markers of health: an examination of adults in the United States and Taiwan. J Aging Health 27:75-102|
|Wu, I-Chien; Hsiung, Chao A; Chang, I-Shou et al. (2015) Personal mastery, multisystem physiological dysregulation and risk of functional decline in older adults: A prospective study in Taiwan. Geriatr Gerontol Int 15:707-14|
|Vasunilashorn, Sarinnapha; Lynch, Scott M; Glei, Dana A et al. (2015) Exposure to stressors and trajectories of perceived stress among older adults. J Gerontol B Psychol Sci Soc Sci 70:329-37|
|Glei, Dana A; Goldman, Noreen; Weinstein, Maxine et al. (2015) Shorter Ends, Faster End? Leukocyte Telomere Length and Mortality Among Older Taiwanese. J Gerontol A Biol Sci Med Sci 70:1490-8|
|Lagona, Francesco; Jdanov, Dmitri; Shkolnikova, Maria (2014) Latent time-varying factors in longitudinal analysis: a linear mixed hidden Markov model for heart rates. Stat Med 33:4116-34|
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