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      Loneliness as a specific risk factor for depressive symptoms: cross-sectional and longitudinal analyses.

      Psychology and Aging
      Aged, Cross-Sectional Studies, Depression, diagnosis, etiology, psychology, Female, Follow-Up Studies, Health Status, Hostility, Humans, Loneliness, Male, Middle Aged, Questionnaires, Risk Factors, Severity of Illness Index, Social Support, Stress, Psychological

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          Abstract

          The extent to which loneliness is a unique risk factor for depressive symptoms was determined in 2 population-based studies of middle-aged to older adults, and the possible causal influences between loneliness and depressive symptoms were examined longitudinally in the 2nd study. In Study 1, a nationally representative sample of persons aged 54 and older completed a telephone interview as part of a study of health and aging. Higher levels of loneliness were associated with more depressive symptoms, net of the effects of age, gender, ethnicity, education, income, marital status, social support, and perceived stress. In Study 2, detailed measures of loneliness, social support, perceived stress, hostility, and demographic characteristics were collected over a 3-year period from a population-based sample of adults ages 50-67 years from Cook County, Illinois. Loneliness was again associated with more depressive symptoms, net of demographic covariates, marital status, social support, hostility, and perceived stress. Latent variable growth models revealed reciprocal influences over time between loneliness and depressive symptomatology. These data suggest that loneliness and depressive symptomatology can act in a synergistic effect to diminish well-being in middle-aged and older adults. ((c) 2006 APA, all rights reserved).

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            Applied Longitudinal Data Analysis : Modeling Change and Event Occurrence

            Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways, and the elderly become frail and forgetful. Beyond these natural processes and events, external forces and interventions instigate and disrupt change: test scores may rise after a coaching course, drug abusers may remain abstinent after residential treatment. By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives. This book is concerned with behavioral, social, and biomedical sciences. It offers a presentation of two of today's most popular statistical methods: multilevel models for individual change and hazard/survival models for event occurrence (in both discrete- and continuous-time). Using data sets from published studies, the book takes you step by step through complete analyses, from simple exploratory displays that reveal underlying patterns through sophisticated specifications of complex statistical models.
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              Loneliness and Health: Potential Mechanisms

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