The purpose of Project 4 is to collect comprehensive biological assessments, paralleling those obtained on the existing MIDUS II sample, on a new refresher sample of 800 individuals (aged 25-54) recruited from the Project 1 refresher samples. Approximately 650 respondents will be from the national probability sample (N = 2,100), while 150 will be from the new African American sample in Milwaukee, Wl (N=500). These additions will increase the size of the existing biomarker sample (N = 1,255) by about 65% (62% for RDD, 75% for Milwaukee). Participants will travel to one of three clinical research centers (University of California, Los Angeles;University of Wisconsin, Madison;Georgetown University, Washington, DC) for an overnight stay. Data to will be collected across four biological systems: neuroendocrine, inflammatory, cardiovascular, and musculoskeletal. A laboratory study will include measures of blood pressure, heart-rate variability, respiratory rate, and salivary cortisol before, during and after various challenges (cognitive and orthostatic). In response to prior concerns about innovation, we have added an expanded cytokine panel, metabolic profiling, and insulin-like growth factor (IGF-1), all of which will be assessed in the new refresher biomarker sample as well as the MIDUS 11 biomarker sample (using stored specimens). Key rationales for augmenting the biomarker sample are to: (a) establish baseline biomarkers for young adults aged 25-34 who are missing from the current sample because biomarkers were added at the 2 wave of MIDUS;(b) afford tests of period effects, linked to the economic recession, in biomarker levels (e.g., cortisol, catecholamines, inflammation, blood pressure, waist-hip ratio;glucose and lipid regulation);and (c) expand the size of the biomarker sample (Refresher + MIDUS II) needed for cross-project analyses investigating the interplay between sociodemographic and psychosocial factors in predicting biomarker levels. Many hypotheses will be pursued, but overarching predictions are that major economic upheaval can be consequential for biological regulation, with such effects likely moderated by sociodemographic status variables (e.g., income, education) as well as by psychosocial factors (e.g., quality of social relationships, well-being). Because this P01 will also include longitudinal follow-up for survey (Project 1) and cognitive (Project 3) assessments of the existing sample, a further aim will be to begin analyses that investigate biological systems (assessed at MIDUS II) as mediators of relationships between prior psychosocial factors (MIDUS I &II) and unfolding profiles of morbidity and mortality (MIDUS III).
The societal significance of the proposed research is that MIDUS will advance knowledge of how sociodemographic and psychosocial factors in early and middle adulthood contribute to, or protect against, risk in multiple biological systems that influence later life morbidity and mortality. Because many psychosocial factors are modifiable, they serve as important targets for prevention and positive health promotion in the U.S. population.
|Wiley, Joshua F; Gruenewald, Tara L; Karlamangla, Arun S et al. (2016) Modeling Multisystem Physiological Dysregulation. Psychosom Med 78:290-301|
|Stephan, Yannick; Sutin, Angelina R; Terracciano, Antonio (2016) Feeling older and risk of hospitalization: Evidence from three longitudinal cohorts. Health Psychol 35:634-7|
|Lee, Pai-Lin (2016) Control beliefs level and change as predictors of subjective memory complaints. Aging Ment Health 20:329-35|
|Leger, Kate A; Charles, Susan T; Turiano, Nicholas A et al. (2016) Personality and Stressor-Related Affect. J Pers Soc Psychol :|
|Briley, Daniel A; Tropf, Felix C; Mills, Melinda C (2016) What Explains the Heritability of Completed Fertility? Evidence from Two Large Twin Studies. Behav Genet :|
|Taber, Jennifer M; Klein, William M P; Suls, Jerry M et al. (2016) Lay Awareness of the Relationship between Age and Cancer Risk. Ann Behav Med :|
|Koffer, Rachel E; Ram, Nilam; Conroy, David E et al. (2016) Stressor diversity: Introduction and empirical integration into the daily stress model. Psychol Aging 31:301-20|
|Holahan PhD, Carole K; Holahan PhD, Charles J; Li Ms, Xiaoyin et al. (2016) Association of health-related behaviors, attitudes, and appraisals to leisure-time physical activity in middle-aged and older women. Women Health :1-16|
|Zilioli, Samuele; Slatcher, Richard B; Chi, Peilian et al. (2016) Childhood Adversity, Self-Esteem, and Diurnal Cortisol Profiles Across the Life Span. Psychol Sci 27:1249-65|
|Song, Jieun; Mailick, Marsha R; Greenberg, Jan S et al. (2016) Cognitive Aging in Parents of Children with Disabilities. J Gerontol B Psychol Sci Soc Sci 71:821-30|
Showing the most recent 10 out of 412 publications