We propose to conduct a survey with a probability sample of Japanese adults (N = 1,000, divided equally by gender) aged 30 to 70 from the Tokyo metropolitan area. Data will be collected on sociodemographic characteristics (age, gender, marital status, educational status, income), psychosocial characteristics (e.g., independence/interdependence, personality traits, sense of control, goal orientations, social support, family obligation, social responsibility), mental health (depression, anxiety, well-being, life satisfaction), and physical health (chronic conditions, health symptoms, functional limitations, health behaviors). These measures parallel those in a national longitudinal sample of midlife Americans known as MIDUS. The central objective is to compare the Japanese sample (MIDJA) with the U.S. sample (MIDUS) to test the hypothesis that the construct of interdependence predicts well-being and health in Japan, whereas the construct of independence predicts well-being and health in the U.S. We also predict age differences in health and well-being, some suggesting cultural similarities (e.g., declining purpose in life with age) and others indicating cultural differences (e.g., more age increments on other aspects of well-being in Japan compared to the U.S.). We also propose to collect biomarkers on approximately half of the Japanese survey sample (n = 500). We will include assessments of neuroendocrine regulation, immune function, and cardiovascular risk. These will parallel biological assessments in Project 4 of the ongoing MIDUS II P01. Thus, in both cultures we will examine linkages between psychosocial factors and biology to test the hypothesis that the construct of interdependence is more strongly linked with biological risk in Japan, whereas the construct of independence is more strongly linked with biological risk in the U.S. A final integrative goal is to combine sociodemographic, psychosocial, and reported health assessments to identify (via recursive partitioning) culture-specific pathways to high or low allostatic load (a multi-system indicator of biological risk). Since our prior submission, we have added extensive findings to Preliminary Studies that demonstrate (with pilot data) support for our guiding hypotheses and also document the feasibility of our proposed biological data collection.
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