INTRODUCTION: The escalation of the older adult population enhances the importance of better understanding factors that contribute to the adaptation and well-being among this population. Few empirical studies exist which combine factors that affect older adults' experiences relative to life quality on a multidimensional level. Biological changes alone are unlikely to explain dramatic variation in sustaining dimensions of human functioning with age; consequently, there is a need to identify factors beyond the biological changes that influence the potentialities of aging. Such information may be useful to expand and understand the prerequisites necessary to create conditions that will foster health and overall quality of life for our rapidly growing aging society. METHODS: The purpose of the present study was to determine the extent to which quality of life is associated with selected biopsychosocial variables. A cross-sectional research design was employed to collect data from a sample of adults living in an active 55+ retirement community. The total number of participants were: N = 222, comprised of n = 95 women (43%) and n = 127 men (57%). The sample ranged in age from 55 to 89, with a mean age of 68. To determine whether biological, sociological, cultural, and psychological variables could account for a significant portion of the variance in quality of life, a multiple regression was performed. All statistical procedures were performed using SAS. Data were analyzed by gender; and the significance level was set at p <.05. RESULTS: Results of the multiple regression on quality of life were significant for both females [F (7, 53) = 11.39, p<.0001] and males [F (5, 105) = 18.60, p<.0001]. The regression produced an R2 = .6008 for women, indicating that 60% of the variability in quality of life was accounted for by the model; significant contributors to the model when added last were: locus of control (p<.0001), sexual self-confidence (p<.005), and number of chronic health conditions (p<.02). The multiple regression for men produced an R2 = .4679, indicating that 47% of the variability in quality of life was accounted for by the model; significant contributors to the model when added last were: locus of control (p<.0001), sexual satisfaction (p<.0002), health (p<.004), and age (p<.004). CONCLUSIONS: Based on the research literature and the current results of this investigation, it appears necessary to incorporate a biopsychosocial approach when investigating factors that influence quality of life among the aging population. Keyword(s): health promotion