Developmental processes are inherently time-related, with various time metrics and transition points being used to proxy how change is organized with respect to the theoretically underlying mechanisms. Using data from 4 Swedish studies of individuals aged 70-100+ (N = 453) who were measured every 2 years for up to 5 waves, we tested whether depressive symptoms (according to the Center for Epidemiologic Studies Depression Scale; Radloff, 1977) are primarily driven by aging-, disablement-, or mortality-related processes, as operationally defined by time-from-birth, time-to/from-disability-onset (1st reported impairment in Personal Activities of Daily Living; Katz, Ford, Moskowitz, Jackson, & Jaffe, 1963), and time-to-death metrics. Using an approach based on Akaike weights, we tested whether developmental trajectories (for each time metric) of depressive symptoms in late life are more efficiently described as a single continuous process or as a 2-phase process. Comparing fits of linear and multiphase growth models, we found that 2-phase models demonstrated better fit than did single-phase models across all time metrics. Time-to-death and time-to/from-disability-onset models provided more efficient descriptions of changes in depressive symptoms than did time-from-birth models, with time-to-death models representing the best overall fit. Our findings support prior research that late-life changes in depressive symptoms are driven by disablement and, particularly, mortality processes, rather than advancing chronological age. From a practical standpoint, time-to/from-disability-onset and, particularly, time-to-death metrics may provide better "base" models from which to examine changes in late-life depressive symptoms and determine modifiable risk and protective factors. Developmental researchers across content areas can compare age with other relevant time metrics to determine if chronological age or other processes drive the underlying developmental change in their construct of interest.