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A practical approach to assess depression risk and to guide risk reduction strategies in later life

Published online by Cambridge University Press:  30 September 2010

Osvaldo P. Almeida ,
Helman Alfonso ,
Jane Pirkis ,
Ngaire Kerse ,
Moira Sim ,
Leon Flicker ,
John Snowdon ,
Brian Draper ,
Gerard Byrne  and
Robert Goldney
...Show all authors
Osvaldo P. Almeida*
Affiliation:
Western Australian Centre for Health & Ageing, Centre for Medical Research of the University of Western Australia, Perth, Australia School of Psychiatry & Clinical Neurosciences, University of Western Australia, Perth, Australia Department of Psychiatry, Royal Perth Hospital, Perth, Australia
Helman Alfonso
Affiliation:
Western Australian Centre for Health & Ageing, Centre for Medical Research of the University of Western Australia, Perth, Australia School of Psychiatry & Clinical Neurosciences, University of Western Australia, Perth, Australia
Jane Pirkis
Affiliation:
School of Population Health, University of Melbourne, Melbourne, Australia
Ngaire Kerse
Affiliation:
School of Population Health, University of Auckland, Auckland, New Zealand
Moira Sim
Affiliation:
School of Nursing, Midwifery and Postgraduate Medicine, Edith Cowan University, Perth, Australia
Leon Flicker
Affiliation:
Western Australian Centre for Health & Ageing, Centre for Medical Research of the University of Western Australia, Perth, Australia School of Medicine and Pharmacology, University of Western Australia, Perth, Australia Department of Geriatric Medicine, Royal Perth Hospital, Perth, Australia
John Snowdon
Affiliation:
Department of Psychological Medicine, University of Sydney, Sydney, Australia
Brian Draper
Affiliation:
School of Psychiatry, University of New South Wales, Sydney, Australia
Gerard Byrne
Affiliation:
School of Medicine, University of Queensland, Brisbane, Australia
Robert Goldney
Affiliation:
Department of Psychiatry, University of Adelaide, Adelaide, Australia
Nicola T. Lautenschlager
Affiliation:
Western Australian Centre for Health & Ageing, Centre for Medical Research of the University of Western Australia, Perth, Australia School of Psychiatry & Clinical Neurosciences, University of Western Australia, Perth, Australia Academic Unit for Psychiatry of Old Age, St Vincent's Health, Department of Psychiatry, University of Melbourne, Melbourne, Australia
Nigel Stocks
Affiliation:
Unit of General Practice, University of Adelaide, Adelaide, Australia
Marcia Scazufca
Affiliation:
Institute and Department of Psychiatry, Medical School, University of São Paulo, São Paulo, Brazil
Martijn Huisman
Affiliation:
EMGO Institute for Health and Care Research, Department of Psychiatry, VU University Medical Center; Department of Sociology, VU University Amsterdam, Amsterdam, The Netherlands
Ricardo Araya
Affiliation:
Department of Psychiatry, University of Bristol, Bristol, U.K.
Jon Pfaff
Affiliation:
Western Australian Centre for Health & Ageing, Centre for Medical Research of the University of Western Australia, Perth, Australia School of Psychiatry & Clinical Neurosciences, University of Western Australia, Perth, Australia
*
Correspondence should be addressed to: Professor Osvaldo P. Almeida, WA Centre for Health & Ageing (M573), University of Western Australia, 35 Stirling Highway, Crawley, Perth, WA 6009, Australia. Phone: +61 8 9224 2720; Fax: +61 8 9224 8009. Email: osvaldo.almeida@uwa.edu.au.
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Abstract

Background: Many factors have been associated with the onset and maintenance of depressive symptoms in later life, although this knowledge is yet to be translated into significant health gains for the population. This study gathered information about common modifiable and non-modifiable risk factors for depression with the aim of developing a practical probabilistic model of depression that can be used to guide risk reduction strategies.

Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years or over in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor or major) according to the Patient Health Questionnaire (PHQ-9) assessment was the main outcome of interest. Other measured exposures included self-reported age, gender, education, loss of mother or father before age 15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smoking and alcohol use, physical activity, obesity, diabetes, hypertension, and prevalent cardiovascular diseases, chronic respiratory diseases and cancer.

Results: The mean age of participants was 71.7 ± 7.6 years and 57.9% were women. Depression was present in 1665 (8.0%) of our subjects. Multivariate logistic regression showed depression was independently associated with age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcohol use, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medical conditions (clinical history of coronary heart disease, stroke, asthma, chronic obstructive pulmonary disease, emphysema or cancers), and social or financial strain. We stratified the exposures to build a matrix that showed that the probability of depression increased progressively with the accumulation of risk factors, from less than 3% for those with no adverse factors to more than 80% for people reporting the maximum number of risk factors.

Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction of risk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigate the impact of risk factors can change the prevalence and incidence of depression in later life.

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Type
Research Article
Information
International Psychogeriatrics , Volume 23 , Issue 2 , March 2011 , pp. 280 - 291
Copyright
Copyright © International Psychogeriatric Association 2010

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