G Model
ARTICLE IN PRESS
MAT-6138; No. of Pages 6
Maturitas xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
Maturitas journal homepage: www.elsevier.com/locate/maturitas
Current Opinion
Prevention of depression in older age Osvaldo P. Almeida a,b,c,∗ a
School of Psychiatry & Clinical Neurosciences, University of Western Australia, Australia WA Centre for Health & Ageing of the Centre for Medical Research, University of Western Australia, Australia c Department of Psychiatry, Royal Perth Hospital, Australia b
a r t i c l e
i n f o
Article history: Received 3 March 2014 Received in revised form 11 March 2014 Accepted 13 March 2014 Available online xxx Keywords: Depression Ageing Prevention Elderly Epidemiology Risk factors
a b s t r a c t Depression is a common disorder in later life that is associated with increased disability and costs, and negative health outcomes over time. Antidepressant treatments in the form of medications or psychotherapy are available, but a large proportion of those treated fail to respond fully, and relapse or recurrence of symptoms is frequent among those who recover. Hence, successful prevention would avoid these negative outcomes. This paper selectively reviews currently available observational and trial data on the prevention of depression. It initially reviews risk factors associated with depression, and then discusses strategies for primary (including universal, selective and indicated), secondary and tertiary prevention. Currently available evidence suggests that selective and indicated preventive interventions are feasible and initial results look promising. Existing trial data indicate that ongoing antidepressant treatments reduce the risk of relapse and recurrence of symptoms, but benefits may not extend beyond two or three years. At this point in time, no interventions have been shown to reduce the long term complications associated with depression. Mental health professionals will need to work collaboratively to develop primary, secondary and tertiary preventive interventions that are effective at targeting relevant risk factors systematically and that can be easily adopted into clinical practice. © 2014 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Understanding the pathways that lead to the onset, persistence and recurrence of depressive symptoms is a critical first step on the road to developing effective preventive measures. Over the past 50 years health professionals have described numerous factors that seem to modulate the risk of depression across the lifespan, although translation of this knowledge into practice has been slow and haphazard. Nonetheless, progress has been made. This paper will selectively review our growing understanding of the risk factors associated with depression and the strategies that have been used to date to prevent depression in later life. 2. Risk factors for depression in later life Over one decade ago, Cole and Dendukuri completed a systematic review of risk factors prospectively associated with depression in later life [1]. Their pooled analyses showed that depression
∗ Corresponding author at: School of Psychiatry & Clinical Neurosciences (M573), University of Western Australia, 35 Stirling Highway, Crawley, Perth, WA 6009, Australia. Tel.: +61 8 92242855; fax: +61 8 92248009. E-mail address: [email protected]
was more frequent among women and those with a disability, recent bereavement, poor sleep and past history of depression. The association between depression and age, education, marital status, socioeconomic status, poor health, cognitive impairment, living alone and new medical illnesses did not reach statistical significance. However, the number of studies providing usable data for each the risk factors analysed was small (2–7) and the review of risk factors was limited both in scope and time. There is consistent evidence that remote factors, such as childhood abuse, increase the risk of mood disorders in young [2,3] and older adults [4]. Limited access to education, adoption of hazardous lifestyle practices (e.g., risk drinking, smoking, physical inactivity, obesity), poor social support, financial strain, lack of a confidant, chronic medical problems, and significant life events (e.g., death, divorce, moving houses) may all contribute to increase the risk of depression in later life [5,6]. Existing data suggest that this multitude of factors do not mediate the risk of depression in isolation. Instead, each seems to facilitate exposure to a novel risk factor in a chain of events that ultimately leads to the onset of depressive symptoms. For example, people who experience childhood adversity are more likely than their counterparts to adopt hazardous lifestyle practices, such as the abuse of substances [7], which in turn are associated with social disadvantage and future chronic health problems [8] that increase the risk of depression in later life [9]. In addition, empirical
http://dx.doi.org/10.1016/j.maturitas.2014.03.005 0378-5122/© 2014 Elsevier Ireland Ltd. All rights reserved.
Please cite this article in press as: Almeida http://dx.doi.org/10.1016/j.maturitas.2014.03.005
OP.
Prevention
of
depression
in
older
age.
Maturitas
(2014),
G Model MAT-6138; No. of Pages 6
ARTICLE IN PRESS O.P. Almeida / Maturitas xxx (2014) xxx–xxx
2
Fig. 1. The figure illustrates possible pathways along the lifespan that facilitate the expression of depressive disorders. Vulnerability to mood disorders might include genetic variations that decrease the ability of the individual to manage stress effectively (e.g., serotonin receptor and CRP genetic polymorphisms). Early life adversities might be represented by physical or sexual abuse, limited education and loss of parents during childhood. Social stress might be characterised by financial strain, social isolation and poor social support. Common harmful lifestyle practices might consist of smoking, hazardous or harmful alcohol use, use of substances, physical inactivity and poor dietary habits. Examples of intermediate health hazards could be hypertension, obesity and diabetes, and examples of common comorbid diseases associated with depression could include coronary heart disease, stroke, Parkinson’s disease, dementia, cancers, sensory impairment, chronic pain and chronic respiratory diseases. In the proposed model, each factor facilitates exposure to other harmful downstream factors as well as to depression.
data from association studies suggest that certain genetic polymorphisms may decrease a person’s ability to manage psychosocial or physiological stress successfully, rendering them more susceptible to the onset of depressive symptoms. For example, Caspi and colleagues [10] showed that a common polymorphism of the serotonin receptor gene increases the probability of depressive episodes as the number of stressful life events accumulates (i.e., there is a gene x environment interaction mediating the risk of depression). Likewise, variations of the C-reactive protein gene that dampen response to physiological stress seem to increase the risk of depression, possibly because they hamper recovery from insult [11,12]. Taken together, the results of these observational studies indicate that exposure to risk factors that increase the risk of depression in later life starts at the time of gamete production and continues throughout the life course. If that is true, then the benefits of early interventions, such as education, may be long lasting [13]. Fig. 1 illustrates a hypothetical model whereby individual risk factors increase the chance of downstream exposure to additional risk factors as well as to depression [5]. 3. Interventions to prevent depression in later life 3.1. Primary prevention of depression Primary preventive interventions can be classified as universal, selective or indicated – they aim to avert the onset of clinically significant depressive symptoms. Universal interventions target the entire population at risk – they are expensive and require that a large number of people receive treatment for one person to benefit. Selective preventive interventions target people at high risk of depression (such as poststroke patients), whereas indicated preventive strategies are used to treat people with symptoms of depression who remain under the threshold for the diagnosis of a depressive episode (subsyndromal depression). Because the risk of depression is greater among those who are vulnerable or have subsyndromal depression, interventions targeting these populations are more economical than universal prevention because less people need to be treated to avoid one case of depression. But what should we do once we identify our target population? The management of risk factors to reduce the risk of undesirable health events has been used successfully in several areas of medicine, such as cardiology. The introduction of the Framingham Please cite this article in press as: Almeida http://dx.doi.org/10.1016/j.maturitas.2014.03.005
OP.
score, and subsequent risk tables, led to the systematic assessment and management of factors prospectively associated with myocardial infarction and strokes, such as smoking, diabetes, blood pressure, lipid profile, gender and age [14]. Ensuing interventions targeting these factors have been successful at reducing the incidence of cardiovascular events [15]. A similar approach to the assessment and management of risk factors is yet to adopted in psychiatry, but preliminary data are starting to emerge. Schoevers and colleagues reported longitudinal data arising from the Amsterdam Study of the Elderly, which recruited 4051 adults aged 65 years or over living in the community [16]. Three years later, 2244 participants were available for a new assessment that included an interview with the Geriatric Mental State AGECAT. Three hundred and nine people (13.8%) developed clinically significant depressive symptoms during the follow up period, which were more frequent among those who reported loss of spouse, sleep complaints, past history of anxiety or depression, disability or chronic medical problems, and who showed evidence of generalised anxiety or subsyndromal depression at study entry. The investigators then developed two prevention models based on these data: one for people who had subsyndromal symptoms of depression at study entry (indicated prevention) and another for those who had lost their spouse (selective prevention). Risk factors associated with conversion to depression amongst those with subsyndromal symptoms included widowhood, disability, chronic illness, living alone and female gender. Factors associated with conversion to depression among those who had recently lost a spouse included disability, chronic illness and female gender. The absolute risk of depression when all risk factors were added approached 50%. The models derived from the Amsterdam Study of the Elderly were helpful in identifying those at greater risk of depression in later life, but provided limited guidance as to how to use these data to guide management, particularly because most of the variables investigated were not easily amenable to change. More recently, the investigators of the Depression and Early Prevention of Suicide in General Practice (DEPS-GP) trial reported the association between 19 risk factors and depression in a sample of over 20,000 older adults [5]. They produced a risk matrix that included the number of adverse childhood experiences (sexual or physical abuse, limited access to education, loss of a parent) and lifestyle practices (smoking, hazardous or harmful alcohol consumption, physical inactivity), intermediate health hazards (hypertension, diabetes, obesity), chronic diseases (cardiovascular, respiratory or cancer) and social or financial strain (financial hardship, poor social support). They used these cross-sectional data to calculate the risk of depression for each combination of risk factors, yielding probabilities that ranged from less than 5% to more than 80%. The authors suggested that their matrix could contribute to guide the assessment and management of people with or at risk of depression if the observed associations were causal [5]. For example, changes in lifestyle or the appropriate management of health hazards could potentially modify the risk of depression in the community. Six-year longitudinal data derived from the Health In Men Study (HIMS) focused on four potentially modifiable factors associated with increased risk of depression: abnormal body mass, physical inactivity, smoking and hazardous/harmful alcohol consumption [17]. The investigators created a risk matrix that adjusted the probability estimates for age, education, marital status and the presence of chronic medical diseases. The probability of incident depression was highest amongst those who were overweight or obese, physically inactive, smokers and harmful or hazardous alcohol users (>10%), and lowest ( A polymorphism increases risk of frailty. Maturitas 2012;71:261–6. [13] Bjelland I, Krokstad S, Mykletun A, Dahl AA, Tell GS, Tambs K. Does a higher educational level protect against anxiety and depression. The HUNT study. Soc Sci Med 2008;66:1334–45. [14] D’Agostino Sr RB, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation 2008;117:743–53. [15] Lindholm LH, Ibsen H, Dahlof B, et al. Cardiovascular morbidity and mortality in patients with diabetes in the Losartan Intervention For Endpoint
Please cite this article in press as: Almeida http://dx.doi.org/10.1016/j.maturitas.2014.03.005
OP.
[32]
[33] [34] [35]
[36] [37]
[38]
[39] [40]
[41]
[42] [43]
[44] [45]
[46]
5
reduction in hypertension study (LIFE): a randomised trial against atenolol. Lancet 2002;359:1004–10. Schoevers RA, Smit F, Deeg DJ, et al. Prevention of late-life depression in primary care: do we know where to begin. Am J Psychiatry 2006;163:1611–21. Almeida OP, Hankey GJ, Yeap BB, Golledge J, McCaul K, Flicker L. A risk table to assist health practitioners assess and prevent the onset of depression in later life. Prev Med 2013;57:878–82. Underwood M, Lamb SE, Eldridge S, et al. Exercise for depression in elderly residents of care homes: a cluster-randomised controlled trial. Lancet 2013;382:41–9. Rovner BW, Casten RJ, Hegel MT, Leiby BE, Tasman WS. Preventing depression in age-related macular degeneration. Arch Gen Psychiatry 2007;64: 886–92. Taylor G, McNeill A, Girling A, Farley A, Lindson-Hawley N, Aveyard P. Change in mental health after smoking cessation: systematic review and meta-analysis. BMJ 2014;348:g1151. Hackett ML, Yapa C, Parag V, Anderson CS. Frequency of depression after stroke: a systematic review of observational studies. Stroke 2005;36:1330–40. Almeida OP, Waterreus A, Hankey GJ. Preventing depression after stroke: results from a randomized placebo-controlled trial. J Clin Psychiatry 2006;67:1104–9. Hackett ML, Anderson CS, House A, Halteh C. Interventions for preventing depression after stroke. Cochrane Database Syst Rev 2008:CD003689. Robinson RG, Jorge RE, Moser DJ, et al. Escitalopram and problem-solving therapy for prevention of poststroke depression: a randomized controlled trial. JAMA 2008;299:2391–400. Almeida OP, McCaul K, Hankey GJ, Norman P, Jamrozik K, Flicker L. Homocysteine and depression in later life. Arch Gen Psychiatry 2008;65:1286–94. Hankey GJ. Is homocysteine a causal and treatable risk factor for stroke. Lancet Neurol 2007;6:751–2. Almeida OP, Marsh K, Alfonso H, Flicker L, Davis TM, Hankey GJ. B-vitamins reduce the long-term risk of depression after stroke: the VITATOPS-DEP trial. Ann Neurol 2010;68:503–10. Van’t Veer-Tazelaar P, Smit F, van Hout H, et al. Cost-effectiveness of a stepped care intervention to prevent depression and anxiety in late life: randomised trial. Br J Psychiatry 2010;196:319–25. van’t Veer-Tazelaar PJ, van Marwijk HW, van Oppen P, et al. Prevention of latelife anxiety and depression has sustained effects over 24 months: a pragmatic randomized trial. Am J Geriatr Psychiatry 2011;19:230–9. Tedeschini E, Levkovitz Y, Iovieno N, Ameral VE, Nelson JC, Papakostas GI. Efficacy of antidepressants for late-life depression: a meta-analysis and meta-regression of placebo-controlled randomized trials. J Clin Psychiatry 2011;72:1660–8. Mitchell AJ, Subramaniam H. Prognosis of depression in old age compared to middle age: a systematic review of comparative studies. Am J Psychiatry 2005;162:1588–601. Kok RM, Heeren TJ, Nolen WA. Continuing treatment of depression in the elderly: a systematic review and meta-analysis of double-blinded randomized controlled trials with antidepressants. Am J Geriatr Psychiatry 2011;19:249–55. Reynolds 3rd CF, Dew MA, Pollock BG, et al. Maintenance treatment of major depression in old age. N Engl J Med 2006;354:1130–8. Kerse N, Flicker L, Pfaff JJ, et al. Falls, depression and antidepressants in later life: a large primary care appraisal. PLoS ONE 2008;3:e2423. Almeida OP, Alfonso H, Hankey GJ, Flicker L. Depression, antidepressant use and mortality in later life: the Health In Men Study. PLoS ONE 2010;5: e11266. Jorm AF. History of depression as a risk factor for dementia: an updated review. Aust N Z J Psychiatry 2001;35:776–81. Pan A, Sun Q, Okereke OI, Rexrode KM, Hu FB. Depression and risk of stroke morbidity and mortality: a meta-analysis and systematic review. JAMA 2011;306:1241–9. Prina AM, Huisman M, Yeap BB, et al. Hospital costs associated with depression in a cohort of older men living in Western Australia. Gen Hosp Psychiatry 2014;36:33–7. Prina AM, Huisman M, Yeap BB, et al. Association between depression and hospital outcomes among older men. CMAJ 2013;185:117–23. van Walraven C, Mamdani MM, Wells PS, Williams JI. Inhibition of serotonin reuptake by antidepressants and upper gastrointestinal bleeding in elderly patients: retrospective cohort study. BMJ 2001;323:655–8. Coupland C, Dhiman P, Morriss R, Arthur A, Barton G, Hippisley-Cox J. Antidepressant use and risk of adverse outcomes in older people: population based cohort study. BMJ 2011;343:d4551. Funk KA, Bostwick JR. A comparison of the risk of QT prolongation among SSRIs. Ann Pharmacother 2013;47:1330–41. Pfaff JJ, Almeida OP. A cross-sectional analysis of factors that influence the detection of depression in older primary care patients. Aust N Z J Psychiatry 2005;39:262–5. Gilbody S, Sheldon T, House A. Screening and case-finding instruments for depression: a meta-analysis. CMAJ 2008;178:997–1003. Gilbody S, Whitty P, Grimshaw J, Thomas R. Educational and organizational interventions to improve the management of depression in primary care: a systematic review. JAMA 2003;289:3145–51. Almeida OP, Pirkis J, Kerse N, et al. A randomized trial to reduce the prevalence of depression and self-harm behavior in older primary care patients. Ann Fam Med 2012;10:347–56.
Prevention
of
depression
in
older
age.
Maturitas
(2014),
G Model MAT-6138; No. of Pages 6 6
ARTICLE IN PRESS O.P. Almeida / Maturitas xxx (2014) xxx–xxx
[47] Joling KJ, van Hout HP, van’t Veer-Tazelaar PJ, et al. How effective is bibliotherapy for very old adults with subthreshold depression? A randomized controlled trial. Am J Geriatr Psychiatry 2011;19:256–65. [48] Walker JG, Mackinnon AJ, Batterham P, et al. Mental health literacy, folic acid and vitamin B12, and physical activity for the prevention of depression in older adults: randomised controlled trial. Br J Psychiatry 2010;197:45–54.
Please cite this article in press as: Almeida http://dx.doi.org/10.1016/j.maturitas.2014.03.005
OP.
[49] Almeida OP, Garrido GJ, Alfonso H, et al. 24-month effect of smoking cessation on cognitive function and brain structure in later life. Neuroimage 2011;55:1480–9. [50] Dahlof B, Lindholm LH, Hansson L, Schersten B, Ekbom T, Wester PO. Morbidity and mortality in the Swedish Trial in Old Patients with Hypertension (STOPHypertension). Lancet 1991;338:1281–5.
Prevention
of
depression
in
older
age.
Maturitas
(2014),
ARTICLE IN PRESS
MAT-6138; No. of Pages 6
Maturitas xxx (2014) xxx–xxx
Contents lists available at ScienceDirect
Maturitas journal homepage: www.elsevier.com/locate/maturitas
Current Opinion
Prevention of depression in older age Osvaldo P. Almeida a,b,c,∗ a
School of Psychiatry & Clinical Neurosciences, University of Western Australia, Australia WA Centre for Health & Ageing of the Centre for Medical Research, University of Western Australia, Australia c Department of Psychiatry, Royal Perth Hospital, Australia b
a r t i c l e
i n f o
Article history: Received 3 March 2014 Received in revised form 11 March 2014 Accepted 13 March 2014 Available online xxx Keywords: Depression Ageing Prevention Elderly Epidemiology Risk factors
a b s t r a c t Depression is a common disorder in later life that is associated with increased disability and costs, and negative health outcomes over time. Antidepressant treatments in the form of medications or psychotherapy are available, but a large proportion of those treated fail to respond fully, and relapse or recurrence of symptoms is frequent among those who recover. Hence, successful prevention would avoid these negative outcomes. This paper selectively reviews currently available observational and trial data on the prevention of depression. It initially reviews risk factors associated with depression, and then discusses strategies for primary (including universal, selective and indicated), secondary and tertiary prevention. Currently available evidence suggests that selective and indicated preventive interventions are feasible and initial results look promising. Existing trial data indicate that ongoing antidepressant treatments reduce the risk of relapse and recurrence of symptoms, but benefits may not extend beyond two or three years. At this point in time, no interventions have been shown to reduce the long term complications associated with depression. Mental health professionals will need to work collaboratively to develop primary, secondary and tertiary preventive interventions that are effective at targeting relevant risk factors systematically and that can be easily adopted into clinical practice. © 2014 Elsevier Ireland Ltd. All rights reserved.
1. Introduction Understanding the pathways that lead to the onset, persistence and recurrence of depressive symptoms is a critical first step on the road to developing effective preventive measures. Over the past 50 years health professionals have described numerous factors that seem to modulate the risk of depression across the lifespan, although translation of this knowledge into practice has been slow and haphazard. Nonetheless, progress has been made. This paper will selectively review our growing understanding of the risk factors associated with depression and the strategies that have been used to date to prevent depression in later life. 2. Risk factors for depression in later life Over one decade ago, Cole and Dendukuri completed a systematic review of risk factors prospectively associated with depression in later life [1]. Their pooled analyses showed that depression
∗ Corresponding author at: School of Psychiatry & Clinical Neurosciences (M573), University of Western Australia, 35 Stirling Highway, Crawley, Perth, WA 6009, Australia. Tel.: +61 8 92242855; fax: +61 8 92248009. E-mail address: [email protected]
was more frequent among women and those with a disability, recent bereavement, poor sleep and past history of depression. The association between depression and age, education, marital status, socioeconomic status, poor health, cognitive impairment, living alone and new medical illnesses did not reach statistical significance. However, the number of studies providing usable data for each the risk factors analysed was small (2–7) and the review of risk factors was limited both in scope and time. There is consistent evidence that remote factors, such as childhood abuse, increase the risk of mood disorders in young [2,3] and older adults [4]. Limited access to education, adoption of hazardous lifestyle practices (e.g., risk drinking, smoking, physical inactivity, obesity), poor social support, financial strain, lack of a confidant, chronic medical problems, and significant life events (e.g., death, divorce, moving houses) may all contribute to increase the risk of depression in later life [5,6]. Existing data suggest that this multitude of factors do not mediate the risk of depression in isolation. Instead, each seems to facilitate exposure to a novel risk factor in a chain of events that ultimately leads to the onset of depressive symptoms. For example, people who experience childhood adversity are more likely than their counterparts to adopt hazardous lifestyle practices, such as the abuse of substances [7], which in turn are associated with social disadvantage and future chronic health problems [8] that increase the risk of depression in later life [9]. In addition, empirical
http://dx.doi.org/10.1016/j.maturitas.2014.03.005 0378-5122/© 2014 Elsevier Ireland Ltd. All rights reserved.
Please cite this article in press as: Almeida http://dx.doi.org/10.1016/j.maturitas.2014.03.005
OP.
Prevention
of
depression
in
older
age.
Maturitas
(2014),
G Model MAT-6138; No. of Pages 6
ARTICLE IN PRESS O.P. Almeida / Maturitas xxx (2014) xxx–xxx
2
Fig. 1. The figure illustrates possible pathways along the lifespan that facilitate the expression of depressive disorders. Vulnerability to mood disorders might include genetic variations that decrease the ability of the individual to manage stress effectively (e.g., serotonin receptor and CRP genetic polymorphisms). Early life adversities might be represented by physical or sexual abuse, limited education and loss of parents during childhood. Social stress might be characterised by financial strain, social isolation and poor social support. Common harmful lifestyle practices might consist of smoking, hazardous or harmful alcohol use, use of substances, physical inactivity and poor dietary habits. Examples of intermediate health hazards could be hypertension, obesity and diabetes, and examples of common comorbid diseases associated with depression could include coronary heart disease, stroke, Parkinson’s disease, dementia, cancers, sensory impairment, chronic pain and chronic respiratory diseases. In the proposed model, each factor facilitates exposure to other harmful downstream factors as well as to depression.
data from association studies suggest that certain genetic polymorphisms may decrease a person’s ability to manage psychosocial or physiological stress successfully, rendering them more susceptible to the onset of depressive symptoms. For example, Caspi and colleagues [10] showed that a common polymorphism of the serotonin receptor gene increases the probability of depressive episodes as the number of stressful life events accumulates (i.e., there is a gene x environment interaction mediating the risk of depression). Likewise, variations of the C-reactive protein gene that dampen response to physiological stress seem to increase the risk of depression, possibly because they hamper recovery from insult [11,12]. Taken together, the results of these observational studies indicate that exposure to risk factors that increase the risk of depression in later life starts at the time of gamete production and continues throughout the life course. If that is true, then the benefits of early interventions, such as education, may be long lasting [13]. Fig. 1 illustrates a hypothetical model whereby individual risk factors increase the chance of downstream exposure to additional risk factors as well as to depression [5]. 3. Interventions to prevent depression in later life 3.1. Primary prevention of depression Primary preventive interventions can be classified as universal, selective or indicated – they aim to avert the onset of clinically significant depressive symptoms. Universal interventions target the entire population at risk – they are expensive and require that a large number of people receive treatment for one person to benefit. Selective preventive interventions target people at high risk of depression (such as poststroke patients), whereas indicated preventive strategies are used to treat people with symptoms of depression who remain under the threshold for the diagnosis of a depressive episode (subsyndromal depression). Because the risk of depression is greater among those who are vulnerable or have subsyndromal depression, interventions targeting these populations are more economical than universal prevention because less people need to be treated to avoid one case of depression. But what should we do once we identify our target population? The management of risk factors to reduce the risk of undesirable health events has been used successfully in several areas of medicine, such as cardiology. The introduction of the Framingham Please cite this article in press as: Almeida http://dx.doi.org/10.1016/j.maturitas.2014.03.005
OP.
score, and subsequent risk tables, led to the systematic assessment and management of factors prospectively associated with myocardial infarction and strokes, such as smoking, diabetes, blood pressure, lipid profile, gender and age [14]. Ensuing interventions targeting these factors have been successful at reducing the incidence of cardiovascular events [15]. A similar approach to the assessment and management of risk factors is yet to adopted in psychiatry, but preliminary data are starting to emerge. Schoevers and colleagues reported longitudinal data arising from the Amsterdam Study of the Elderly, which recruited 4051 adults aged 65 years or over living in the community [16]. Three years later, 2244 participants were available for a new assessment that included an interview with the Geriatric Mental State AGECAT. Three hundred and nine people (13.8%) developed clinically significant depressive symptoms during the follow up period, which were more frequent among those who reported loss of spouse, sleep complaints, past history of anxiety or depression, disability or chronic medical problems, and who showed evidence of generalised anxiety or subsyndromal depression at study entry. The investigators then developed two prevention models based on these data: one for people who had subsyndromal symptoms of depression at study entry (indicated prevention) and another for those who had lost their spouse (selective prevention). Risk factors associated with conversion to depression amongst those with subsyndromal symptoms included widowhood, disability, chronic illness, living alone and female gender. Factors associated with conversion to depression among those who had recently lost a spouse included disability, chronic illness and female gender. The absolute risk of depression when all risk factors were added approached 50%. The models derived from the Amsterdam Study of the Elderly were helpful in identifying those at greater risk of depression in later life, but provided limited guidance as to how to use these data to guide management, particularly because most of the variables investigated were not easily amenable to change. More recently, the investigators of the Depression and Early Prevention of Suicide in General Practice (DEPS-GP) trial reported the association between 19 risk factors and depression in a sample of over 20,000 older adults [5]. They produced a risk matrix that included the number of adverse childhood experiences (sexual or physical abuse, limited access to education, loss of a parent) and lifestyle practices (smoking, hazardous or harmful alcohol consumption, physical inactivity), intermediate health hazards (hypertension, diabetes, obesity), chronic diseases (cardiovascular, respiratory or cancer) and social or financial strain (financial hardship, poor social support). They used these cross-sectional data to calculate the risk of depression for each combination of risk factors, yielding probabilities that ranged from less than 5% to more than 80%. The authors suggested that their matrix could contribute to guide the assessment and management of people with or at risk of depression if the observed associations were causal [5]. For example, changes in lifestyle or the appropriate management of health hazards could potentially modify the risk of depression in the community. Six-year longitudinal data derived from the Health In Men Study (HIMS) focused on four potentially modifiable factors associated with increased risk of depression: abnormal body mass, physical inactivity, smoking and hazardous/harmful alcohol consumption [17]. The investigators created a risk matrix that adjusted the probability estimates for age, education, marital status and the presence of chronic medical diseases. The probability of incident depression was highest amongst those who were overweight or obese, physically inactive, smokers and harmful or hazardous alcohol users (>10%), and lowest ( A polymorphism increases risk of frailty. Maturitas 2012;71:261–6. [13] Bjelland I, Krokstad S, Mykletun A, Dahl AA, Tell GS, Tambs K. Does a higher educational level protect against anxiety and depression. The HUNT study. Soc Sci Med 2008;66:1334–45. [14] D’Agostino Sr RB, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation 2008;117:743–53. [15] Lindholm LH, Ibsen H, Dahlof B, et al. Cardiovascular morbidity and mortality in patients with diabetes in the Losartan Intervention For Endpoint
Please cite this article in press as: Almeida http://dx.doi.org/10.1016/j.maturitas.2014.03.005
OP.
[32]
[33] [34] [35]
[36] [37]
[38]
[39] [40]
[41]
[42] [43]
[44] [45]
[46]
5
reduction in hypertension study (LIFE): a randomised trial against atenolol. Lancet 2002;359:1004–10. Schoevers RA, Smit F, Deeg DJ, et al. Prevention of late-life depression in primary care: do we know where to begin. Am J Psychiatry 2006;163:1611–21. Almeida OP, Hankey GJ, Yeap BB, Golledge J, McCaul K, Flicker L. A risk table to assist health practitioners assess and prevent the onset of depression in later life. Prev Med 2013;57:878–82. Underwood M, Lamb SE, Eldridge S, et al. Exercise for depression in elderly residents of care homes: a cluster-randomised controlled trial. Lancet 2013;382:41–9. Rovner BW, Casten RJ, Hegel MT, Leiby BE, Tasman WS. Preventing depression in age-related macular degeneration. Arch Gen Psychiatry 2007;64: 886–92. Taylor G, McNeill A, Girling A, Farley A, Lindson-Hawley N, Aveyard P. Change in mental health after smoking cessation: systematic review and meta-analysis. BMJ 2014;348:g1151. Hackett ML, Yapa C, Parag V, Anderson CS. Frequency of depression after stroke: a systematic review of observational studies. Stroke 2005;36:1330–40. Almeida OP, Waterreus A, Hankey GJ. Preventing depression after stroke: results from a randomized placebo-controlled trial. J Clin Psychiatry 2006;67:1104–9. Hackett ML, Anderson CS, House A, Halteh C. Interventions for preventing depression after stroke. Cochrane Database Syst Rev 2008:CD003689. Robinson RG, Jorge RE, Moser DJ, et al. Escitalopram and problem-solving therapy for prevention of poststroke depression: a randomized controlled trial. JAMA 2008;299:2391–400. Almeida OP, McCaul K, Hankey GJ, Norman P, Jamrozik K, Flicker L. Homocysteine and depression in later life. Arch Gen Psychiatry 2008;65:1286–94. Hankey GJ. Is homocysteine a causal and treatable risk factor for stroke. Lancet Neurol 2007;6:751–2. Almeida OP, Marsh K, Alfonso H, Flicker L, Davis TM, Hankey GJ. B-vitamins reduce the long-term risk of depression after stroke: the VITATOPS-DEP trial. 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OP.
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