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

O.P. Almeida, H. Alfonso, J Pirkis, N. Kerse, M. Sim, L. Flicker, J. Snowdon, B. Draper, G. Byrne, R. Goldney, N.T. Lautenschlager, N. Stocks, M. Scazufca, M. Huisman, R. Araya, J. Pfaff

Research output: Contribution to journalArticleAcademicpeer-review

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 amatrix 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.
Original languageEnglish
Pages (from-to)280-291
JournalInternational Psychogeriatrics
Volume23
Issue number2
DOIs
Publication statusPublished - 2011

Cite this

Almeida, O. P., Alfonso, H., Pirkis, J., Kerse, N., Sim, M., Flicker, L., ... Pfaff, J. (2011). A practical approach to assess depression risk and to guide risk reduction strategies in later life. International Psychogeriatrics, 23(2), 280-291. https://doi.org/10.1017/S1041610210001870
Almeida, O.P. ; Alfonso, H. ; Pirkis, J ; Kerse, N. ; Sim, M. ; Flicker, L. ; Snowdon, J. ; Draper, B. ; Byrne, G. ; Goldney, R. ; Lautenschlager, N.T. ; Stocks, N. ; Scazufca, M. ; Huisman, M. ; Araya, R. ; Pfaff, J. / A practical approach to assess depression risk and to guide risk reduction strategies in later life. In: International Psychogeriatrics. 2011 ; Vol. 23, No. 2. pp. 280-291.
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title = "A practical approach to assess depression risk and to guide risk reduction strategies in later life",
abstract = "Background: Many factors have been associated with the onset and maintenance of depressive symptoms inlater life, although this knowledge is yet to be translated into significant health gains for the population. Thisstudy gathered information about common modifiable and non-modifiable risk factors for depression withthe aim of developing a practical probabilistic model of depression that can be used to guide risk reductionstrategies.Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years orover in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor ormajor) 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 age15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smokingand 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 in1665 (8.0{\%}) of our subjects.Multivariate logistic regression showed depression was independently associatedwith age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcoholuse, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medicalconditions (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 amatrix that showedthat the probability of depression increased progressively with the accumulation of risk factors, from less than3{\%} for those with no adverse factors to more than 80{\%} for people reporting the maximum number of riskfactors.Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction ofrisk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigatethe impact of risk factors can change the prevalence and incidence of depression in later life.",
author = "O.P. Almeida and H. Alfonso and J Pirkis and N. Kerse and M. Sim and L. Flicker and J. Snowdon and B. Draper and G. Byrne and R. Goldney and N.T. Lautenschlager and N. Stocks and M. Scazufca and M. Huisman and R. Araya and J. Pfaff",
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Almeida, OP, Alfonso, H, Pirkis, J, Kerse, N, Sim, M, Flicker, L, Snowdon, J, Draper, B, Byrne, G, Goldney, R, Lautenschlager, NT, Stocks, N, Scazufca, M, Huisman, M, Araya, R & Pfaff, J 2011, 'A practical approach to assess depression risk and to guide risk reduction strategies in later life' International Psychogeriatrics, vol. 23, no. 2, pp. 280-291. https://doi.org/10.1017/S1041610210001870

A practical approach to assess depression risk and to guide risk reduction strategies in later life. / Almeida, O.P.; Alfonso, H.; Pirkis, J; Kerse, N.; Sim, M.; Flicker, L.; Snowdon, J.; Draper, B.; Byrne, G.; Goldney, R.; Lautenschlager, N.T.; Stocks, N.; Scazufca, M.; Huisman, M.; Araya, R.; Pfaff, J.

In: International Psychogeriatrics, Vol. 23, No. 2, 2011, p. 280-291.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - A practical approach to assess depression risk and to guide risk reduction strategies in later life

AU - Almeida, O.P.

AU - Alfonso, H.

AU - Pirkis, J

AU - Kerse, N.

AU - Sim, M.

AU - Flicker, L.

AU - Snowdon, J.

AU - Draper, B.

AU - Byrne, G.

AU - Goldney, R.

AU - Lautenschlager, N.T.

AU - Stocks, N.

AU - Scazufca, M.

AU - Huisman, M.

AU - Araya, R.

AU - Pfaff, J.

PY - 2011

Y1 - 2011

N2 - Background: Many factors have been associated with the onset and maintenance of depressive symptoms inlater life, although this knowledge is yet to be translated into significant health gains for the population. Thisstudy gathered information about common modifiable and non-modifiable risk factors for depression withthe aim of developing a practical probabilistic model of depression that can be used to guide risk reductionstrategies.Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years orover in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor ormajor) 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 age15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smokingand 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 in1665 (8.0%) of our subjects.Multivariate logistic regression showed depression was independently associatedwith age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcoholuse, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medicalconditions (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 amatrix that showedthat the probability of depression increased progressively with the accumulation of risk factors, from less than3% for those with no adverse factors to more than 80% for people reporting the maximum number of riskfactors.Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction ofrisk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigatethe impact of risk factors can change the prevalence and incidence of depression in later life.

AB - Background: Many factors have been associated with the onset and maintenance of depressive symptoms inlater life, although this knowledge is yet to be translated into significant health gains for the population. Thisstudy gathered information about common modifiable and non-modifiable risk factors for depression withthe aim of developing a practical probabilistic model of depression that can be used to guide risk reductionstrategies.Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years orover in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor ormajor) 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 age15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smokingand 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 in1665 (8.0%) of our subjects.Multivariate logistic regression showed depression was independently associatedwith age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcoholuse, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medicalconditions (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 amatrix that showedthat the probability of depression increased progressively with the accumulation of risk factors, from less than3% for those with no adverse factors to more than 80% for people reporting the maximum number of riskfactors.Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction ofrisk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigatethe impact of risk factors can change the prevalence and incidence of depression in later life.

U2 - 10.1017/S1041610210001870

DO - 10.1017/S1041610210001870

M3 - Article

VL - 23

SP - 280

EP - 291

JO - Psychogeriatrics

JF - Psychogeriatrics

SN - 1041-6102

IS - 2

ER -