Research reportRisk factors for depression in later life; results of a prospective community based study (AMSTEL)
Introduction
Current knowledge about risk factors of late-life depression is largely derived from either clinical populations, or from cross-sectional studies in the community. Studies of clinical patients have the disadvantage of not being representative of the vast majority of depressive subjects in the community. Cross-sectional studies in the community suffer from methodological limitations such as recall and report bias in depressed subjects (Raphael and Cloitre, 1994), and contamination of the results as risk factors are not measured independently from depression. Temporal relations remain unclear since a characteristic found to be associated with depression may have antedated (or caused) the disorder, but it may also be its consequence. Likewise, cross-sectional designs cannot distinguish whether a characteristic has prognostic value for the course of depression once depression is present, or is actually associated with its aetiology. Finally, in cross-sectional designs chronic depression is over-represented, which may bias findings with regard to aetiology.
Prospective studies of the incidence of depression among the elderly are relatively scarce and have used different sets of risk factors and research methods. Green et al. (1992) found lack of satisfaction with life, feelings of loneliness and smoking to be significantly associated with the development of depression as measured by GMS–AGECAT three years later in a cohort of community living elderly. Multivariate analysis yielded two more factors; female gender, and bereavement of a close person within six months of the third-year diagnosis. Phifer and Murrell (1986) found the incidence of significant depression in a six months period to be closely associated with changes in physical health. Kennedy et al. (1990) also found aspects of physical health to be closely related to incidence of depression in a large sample of community-dwelling elderly in a two year follow-up. In a one year follow-up study with 3-monthly assessment of depressive symptomatology by Beekman et al. (1995a), depression incidence was also found to be associated with health related variables. A recent publication by Prince et al. (1998) revealed disablement, and more specifically handicap, to be the chief cause of onsets of depression in late-life in a one-year follow-up of community living elderly.
According to the Brown and Harris (1978) etiologic model, depression in adults may be the result of ‘social stress’ factors such as life events (loss) or long term difficulties, combined with vulnerability/protective factors such as social disadvantage, lack of intimate relationships, early traumatic life events, lower intelligence/education, personal history of depressive illness and family history. Earlier cross-sectional work from the Amsterdam Study of the Elderly (AMSTEL) (Van Ojen et al., 1995a, Van Ojen et al., 1995b, Van Ojen et al., 1995c) was inspired by the work of Brown and Harris. The AMSTEL data suggested three different subtypes of geriatric depression based on etiologic determinants. Early-onset depression was found to be associated with long-standing inborn susceptibility (Kendler et al., 1993a) and vulnerability due to previous episodes: ‘sensitization’ or ‘kindling’ (Post, 1992). Late-onset depression with cognitive impairment was mainly associated with the presence of organic vulnerability factors. Late-onset depression without cognitive impairment was found to be associated with factors related to current life-stresses.
The primary aim of the present study was to further investigate the aetiology of late life depression, studying incident cases in the community in a prospective longitudinal design using a comprehensive set of risk factors generally believed to be associated with depression. In this way we hoped to avoid the above-mentioned methodological pitfalls and develop more insight into the temporal and causal relations between risk factors and late-life depression. Secondly we wanted to investigate whether the differential etiologic pathways of late-life depression suggested by earlier cross-sectional data are confirmed using a longitudinal design.
Section snippets
Sampling and non-response
The population base for the study included all non-institutional individuals in the 65–84 age bracket who lived in the city of Amsterdam and were registered with a general practitioner at baseline (Van Ojen et al., 1995a). The sample was drawn from a list of 30 general practices spread throughout the city. The mean proportion of elderly individuals (15%), and the profile of the over-65 general practice-population in terms of age and gender, correspond to the non-institutionalised Amsterdam
Sample characteristics and response pattern
The demographic and functional profiles of the study sample at baseline and follow-up are presented in Table 1. Bivariate analyses showed significant differences between responders and subjects lost to follow-up on a number of baseline variables. Higher age, lower education, lower social-economic status and the existence of functional impairments, chronic disease, a lower MMSE score, an organic syndrome and depression all showed associations with non-response (p<0.001). When excluding the
Discussion
The aim of the present study was to model the aetiology of late life depression, studying incident cases in the community in a three-year prospective design. Of the subjects without depression at baseline, 15.9% had developed a GMS–AGECAT depressive syndrome at follow-up. Compared to previous studies of depression incidence in the elderly this is relatively high. Phifer and Murrell (1986) noted an incidence of 10.7% after only six months, using a Center for Epidemiologic Studies Depression
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