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This chapter aims to explore the possibilities of preventing comorbid mental and physical disorders. It presents a framework of optional preventive strategies based on four explanatory models of comorbidity and six strategic dimensions. Addressing common early risk factors is discussed as one of these preventive strategies. Some examples of evidence-based prevention programs are presented that might contribute to prevention of comorbidity, needs for further research are discussed, and recommendations are presented for policy makers and practitioners to improve the perspectives for preventing mental and physical comorbidity. So far, preventing mental disorders and preventing physical disorders have been highly separated fields. It is recommended that both fields should broaden the range of baseline and outcome indicators and include longitudinal designs to understand the long-term broad-spectrum outcomes of preventive interventions better. Future policy plans and practices in physical and mental health should be more focused at preventing comorbidity, and enhance related expertise among policy-makers and practitioners. Finally, it is argued that the preventive approach of comorbidity should be broadened to ‘smart clusters' of highly related mental, physical and social problems, with the last possibly referring to important common risk factors.

As is extensively discussed and evidenced in this book, comorbidity of mental and physical disorders is a common phenomenon among patients in physical and mental healthcare, as well as in populations. Comorbidity with physical illnesses, particularly chronic physical illnesses, is reported especially for depression and anxiety disorders. This is in line with conclusions from the WHO World Mental Health Surveys in 18 countries, the results of which are presented in Global Perspectives on Mental-Physical Comorbidityin the WHO World Mental Health Surveys (2009) [1]. This international cross-sectional study measured the prevalence of mental and physical comorbidity during the year preceding data collection. Pooled across 18 surveys in developed and developing countries, odds ratios (ORs) between 1.8 and 3.3 were found for depression and dysthymia, and for different anxiety disorders in people with chronic pain conditions (arthritis, spinal pain, headache); among those with a heart disease, the ORs fell in the range of 1.9-2.7 [2]. Averaged across countries, the WHO study found that 36.9% of those with a depressive or anxiety disorder also suffered from a physical disorder. Prospective studies have shown that mental disorders could precede the onset of chronic physical disorders, but also that chronic physical disorders could precede the onset of mental disorders [3]. Mental and physical comorbidity represents a high burden to societies, as is illustrated by a recent Australian report on comorbidity. In 2007, almost 12% of Australians aged 16-85 had a mental disorder and a physical condition at the same time [4].

Comorbidity of mental disorders with physical disorders and comorbidity in general portends a poorer outcome for the patients and higher economic costs [2]. This includes poorer clinical course, higher risk of chronicity, disability, additive work-loss, poorer quality of life and mortality, as well as more healthcare utilization, poorer treatment adherence and reduced treatment success [5,6,7]. All of these outcomes stress the need to invest in prevention of comorbid disorders. If effective prevention strategies were implemented, such an investment could result in a tremendous reduction in human suffering, utilization of treatment services and huge cost savings in healthcare and social security.

Although the bulk of studies on comorbidity date from after 2000, there were studies on mental and physical comorbidity in the 1980s and 1990s [8,9,10,11]. By the 19th and 20th centuries, most mental hospitals had wards devoted to the treatment of physical illness of patients admitted because of mental illness. From the 1970s, a DSM-based assessment on the link between mental and physical diseases became an essential part of clinical diagnosis. Given this history, it is striking that there are very few publications on the prevention of comorbidity. Most of the current literature is almost exclusively focused on improving treatment for patients who already suffer from comorbid mental and physical illness.

This chapter aims to explore the possibility of preventing comorbid mental and physical disorders. It presents a theory-based framework of optional preventive strategies, describes examples of evidence-based prevention programs that might contribute to prevention of comorbidity, identifies further research needs and presents recommendations for policy makers and practitioners to improve the perspectives for preventing comorbidity.

Although the idea of preventing mental illness was introduced more than 100 years ago, science-based prevention has a history of around 30-40 years. Over the last decades, much progress has been made in understanding the risk and protective factors for mental disorders, which has been translated into a wide range of prevention programs. Prevention and health promotion, also in the mental health domain, have emerged internationally as a significant multidisciplinary field of science and practice, with a range of peer-reviewed scientific journals and specialized university departments and research centers in most continents. Currently, a wide range of science- and practice-based prevention programs are available. Thousands of controlled studies and a large range of systematic reviews and meta-analytic studies have been published showing that prevention programs targeting mental health can generate a wide range of positive outcomes [12,13,14,15]. These include strengthening protective factors (e.g. social-emotional skills, parenting competence, early parent-child interaction, coping with parental death and loss) and reducing the number of risk factors (e.g. child maltreatment, insecure attachment, early externalizing problems, bullying, substance use). There is also cumulative evidence of reductions in the onset of depression [16], anxiety symptoms and disorders [17,18], eating disorders [19], externalizing problems and conduct disorders [20,21,22], and substance use problems [23]. Some randomized longitudinal studies have found significant effects even up to 15 and 40 years later. A growing number of economic evaluations of such programs have also provided evidence of their potential cost-effectiveness, especially early childhood programs [24].

To date, evidence-based prevention programs are internationally exchanged, disseminated and implemented, and supported by online international and national databases that are freely accessible to policymakers and practitioners. Given the steadily growing availability of effective prevention programs and the awareness of the enormous human and economic burden of mental disorders, it is likely that investments in preventing and treating mental disorders will become more balanced during this century.

In spite of these promising developments, major challenges exist in preventing mental disorders and promoting mental health. First, reviews and meta-analyses have shown that on average the effect sizes of prevention programs are small to moderate albeit significant, mostly ranging between 0.15 and 0.40. Meta-analyses have also shown large differences in effect sizes between programs, ranging from highly effective to showing no effect and in some cases even negative effects. This emphasizes the urgent need for program improvement and knowledge on the moderators and principles of effectiveness. Secondly, owing to the use of labor-intensive methods in many programs, low levels of implementation and poor resources and infrastructure for prevention, the population reach of these preventive interventions is still marginal. This contrasts with the much wider implementation and public reach of programs aimed at reducing the risk of chronic physical diseases such as those on reducing risk behaviors (e.g. smoking, substance use, consuming unhealthy food, risky driving) and environmental risk factors (e.g. air pollution, safe cars and roads, quality of food).

Finally, although Kessler and Price [25] already in 1993 advocated for investment in the prevention of comorbidity in psychiatric disorders, prevention research has only marginally addressed this issue. The fields of physical diseases and mental disorders prevention are highly separated. Even in cases where risk factors are addressed with a potential broad-spectrum outcome, testing their impact on the onset of both mental and physical illnesses is exceptional. Most disorder prevention programs in mental health are targeted at preventing a single disorder (e.g. depression).

To understand how to prevent physical and mental comorbidity and to measure if interventions are effective in preventing comorbidity, we first need to understand what comorbidity means, how we can differentiate between types of comorbidity and what the causal processes are underlying comorbidity.

Comorbidity can be defined at an individual leveland at a population level,paralleling a clinical and a public health approach. This is a relevant distinction as prevention encompasses both preventive treatment and public health actions. Clinicians in physical and mental healthcare are challenged to identify the risk of comorbidity in individual patients and to act accordingly to prevent comorbidity. This requires widening clinical assessment and treatment to address the risk of multiple disorders in the physical and mental health domains, and, if needed, to involve other clinical disciplines.

Preventing comorbidity at the population level requires a public health way of thinking [26]. This includes population-based assessment, finding groups at high risk of comorbidity, identifying risk and protective factors, taking policy measures, initiating intervention programs to reduce the risk of disorders and comorbidity, and rigorously testing their efficacy and effectiveness. As discussed in the next section, interventions could range across a wide spectrum of optional preventive strategies that could start before the onset of a primary disorder and even before birth.

A distinction is commonly made between concurrent comorbidityand sequential comorbidity. Concurrent comorbidityrefers to a situation in which a person has two or more disorders at the same time or at least during the same period. In such cases, taking timely action to prevent the onset of both disorders would be the most desirable approach. This is only possible when both disorders have evidence-based common risk or protective factors that are measurable and malleable during the antecedent period. For instance, growing empirical support exists for serious childhood adversities as a risk factor for both mental disorders and chronic physical diseases [1,27]. Serious motor vehicle accidents with life-threatening experiences represent another example, as they could result in both serious physical injuries and a posttraumatic stress disorder among survivors. The many successful measures that have been adopted in recent decades to reduce serious traffic accidents have likely prevented many physical diseases or disability as well as comorbid posttraumatic stress disorders.

Sequential comorbidity refers to the onset of a secondary disease that is significantly associated with or influenced by an already existing primary disease. A well-known example of sequential comorbidity within the mental health domain is the relation between child anxiety disorders and adolescent major depression. In their longitudinal community study, Wittchen et al. [28] found that in the case of comorbidity, anxiety disorders mainly precede the onset of major depression. The ORs for later onset of depression ranged from 2.5 for specific phobia to 3.7 and 3.8 for panic disorder and agoraphobia. The time delay between the onset of the two related disorders could be short (e.g. a month or a year) or might even extend over one or more decades. The development of sequential comorbidity could encompass longitudinal pathways from the start of life into late adulthood [28]. It should be stressed, however, that anxiety symptoms might be an expression of child depression, which means that the example might not reflect the sequential onset of two comorbid disorders, but age-related manifestations of a similar underlying long-term depressive disorder.

The distinction between concurrent and sequential comorbidity is less transparent than it looks at first sight. Concurrent refers to the co-occurrence of two disorders during a specific period of measurement, which could be the preceding week, month or year. In the case of a chronic physical disease, the onset of a reactive depression might follow months after the onset of a chronic heart disease. When their illness periods (prevalence) overlap, they could be considered as concurrent diseases, but as sequential comorbidity when we use onset as the criterion. As primary prevention aims to reduce onset of diseases, the onset criterion is of more strategic value as it offers more information on possible causal sequences and timing of preventive interventions and their outcomes. The onset of a primary disease could then be used as a trigger for interventions to prevent the onset of a related secondary disease. Further, when the secondary disorder is likely to start during the episode of the primary disorder, it is most practical that clinicians integrate efforts to prevent a secondary disorder in their treatment of the primary disorder. Finally, even when sequential comorbidity is established, how disorders are related remains an important question. Theory-based prospective studies are needed to establish if the onset of the second disorder is mediated by the features and outcomes of the primary disorder, or a delayed result from a common risk factor.

Most research on comorbidity is targeted at increasing the knowledge on prevalence and consequences of comorbidity, and on early detection and appropriate treatment. The causes of comorbidity are studied much less [7]. For prevention policies and programs, the latter type of studies are crucial, as preventive interventions typically aim to influence causes of diseases to lower the risk of onset. Designing an effective prevention approach to mental and physical comorbidity is only possible when we have insight into the underlying causal mechanisms. For this reason, this section is focused on understanding how multiple diseases could be related and how risk and protective factors might contribute to comorbidity. Next, we present a comprehensive framework of optional preventive strategies to reduce comorbidity.

To describe how and why disorders could be related, we differentiate between four models: (1) common antecedent model, (2) sequential comorbidity model, (3) bidirectional comorbidity model and (4) accidental comorbidity model.

The common antecedent modelassumes that common, broad-spectrum factors influence the onset of multiple disorders, irrespective of whether the onset and prevalence of these disorders is co-occurring or separated over time. For childhood adversities (e.g. child abuse and neglect, parental mental illness, parental death and divorce), especially in the case of an accumulation of childhood adversities, extensive evidence exists for a wide range of long-term negative outcomes such as increased risk of depression, conduct disorders, drug and alcohol abuse, low self-esteem, poor emotional competence, risky sexual behavior, suicidal behavior, and adult-onset asthma, obesity and hypertension [1,3].

The sequential comorbidity model presumes that features and outcomes of a primary disorder or its treatment increase the onset of a secondary disorder. Examples of factors that mediate the causal relationship between both disorders are serious stress experiences resulting from the primary disorder (e.g. pain, psychotrauma, physical disability, dependency, unemployment, social isolation), harmful coping behaviors (e.g. smoking, alcohol use, inactivity), negative social reactions (e.g. social stigma) or negative side effects of medication. Preventive interventions could aim to reduce or compensate for these mediating outcomes. In the bidirectional model,two disorders and their outcomes are assumed to reinforce each other's development and chronic course. In this case, preventive interventions could address mediating outcomes of both disorders. Finally, in the accidental comorbidity model comorbid disorders are considered to be a random phenomenon, with no evidence of mutual influence or common causes. Each disorder is assumed to have an independent causal trajectory. The prevention of both disorders would require the implementation of separate primary preventive interventions, each addressing a different disorder.

To prevent comorbid mental and physical illness, one could choose from different intervention scenarios. Each strategy is defined by the combination of choices on a range of target- and strategy-related dimensions that roughly represent the ‘what-who-why-when framework'. This framework of choices is composed of six dimensions:

(1) Target. This dimension concerns choices such as ‘Which combination of comorbid disorders is targeted?', ‘Which of them should be prevented?' and ‘The mental disorder, physical disorder, or both?'.

(2) Target population. Should the target population be chosen through universal, selective or indicated prevention? This refers to a choice about the width and level of risk of the targeted population. Universal prevention targets whole populations, selective prevention targets groups at risk and indicated prevention targets persons or groups at high risk when they show subclinical symptoms that might grow into a diagnosable disorder. Targeted persons or groups could be at risk of the primary disorder, the secondary disorder or both. Identifying persons at high risk requires the use of risk assessment tools that are still poorly developed in psychiatry.

(3) Factors. Which evidence-based risk or protective factors are targeted? This concerns especially the choice between addressing common causal factors or disorder-specific factors. Common factors are shared by multiple disorders, also called broad-spectrum factors. Disorder-specific factors could be related to either a physical disorder or a comorbid mental disorder. Risk factors for depression include, for instance, a parental mental illness, negative cognitive style, serious loss experiences, physical illnesses (e.g. diabetes, stroke, cardiac disease, loss of hearing), poverty and exposure to childhood traumas, while parental care, secure attachment, coping skills, social-emotional competence and social support are considered to protect against depression. Several of these factors (e.g. poverty, childhood maltreatment, secure attachment, social support) can also be considered as broad-spectrum factors. There is growing evidence that high risk is not just defined by single risk factors, but by the number of accumulating risk factors [28,29,30]; reducing this number by targeting the most malleable factors might be a cost-effective strategy to prevent disorders.

(4) Timing. This refers to choices concerning when to intervene. In the case of sequential comorbidity, the options are to provide a preventive intervention prior to, during or after a primary disorder, or prior to the secondary disorder. For instance, some studies suggest that depression in children, adolescents and young adults increases the risk of adult obesity [31,32]. To lower the risk of secondary obesity, one could aim to prevent depression in adolescents, treat first episodes of depression effectively, prevent relapses, educate people with depression about healthy lifestyles, or detect and treat early eating problems among those with chronic depression. When common factors are targeted, a choice needs to be made about when to intervene along the life span. This will depend on when a common risk or protective factor emerges and the most sensitive period during which such a factor could be influenced. For instance, research outcomes suggest that maternal depression, anxiety and chronic stress during pregnancy and early child maltreatment may result in a disturbed emotional brain and stress-response system (HPA axis) in childhood that is associated with long-term vulnerability to mental disorders and weakened immunity against chronic diseases. This points to the need to start preventive interventions as early as during pregnancy and infancy.

(5) Provider. Who will provide the preventive intervention and from which setting? This could be general practitioners, public nurses, mental health professionals, medical specialists in hospitals, public health professionals, health educators, or peers and experts-by-experience. It is highly desirable to integrate prevention in the work of all of these disciplines. Related to this is the choice between providing preventive support integrated in the treatment process (e.g. following a stepped care model) or by a referral to separately provided prevention programs.

(6) Method. This concerns the choice of intervention methods and theories and principles of change. Evidence-based prevention programs use a wide variety of intervention methods, such as home-visiting, parenting education, school-based programs, group-based courses, internet-based interventions, self-help books, support groups, individual counseling and preventive medication. These methods make use of different mechanisms of change to influence causal factors, such as providing information, feedback, modeling, competence training, emotional support and biological agents, as well as through environmental changes.

Figure 1 offers an overview of six alternative prevention strategies (PS) that could contribute to the prevention of comorbidity-based on combinations of choices at the target, target population, factor and timing dimensions. Preventive interventions could start during pregnancy and infancy to influence the development of common risk and protective factors early in life or during childhood and adolescence (PS1). Other interventions are targeted at disorder-specific risk factors (PS2) and prodromal or subclinical symptoms preceding the primary disorder (PS3), at effective treatment of the primary disorder (PS4), reducing negative outcomes of the primary disorder or its treatment (PS5), and addressing specific risk factors and subclinical symptoms of secondary disorders (PS6).

Fig. 1

Model of strategies to prevent comorbidity across the developmental trajectory and targeted at common or disorder-specific factors.

Fig. 1

Model of strategies to prevent comorbidity across the developmental trajectory and targeted at common or disorder-specific factors.

Close modal

Following the strategic framework, many available evidence-based prevention programs might be useful as components of an integral approach to reduce comorbidity, although they were not developed originally for this purpose. We do not have the opportunity here to review all prevention programs that might be useful to reduce comorbidity, but some examples will show that effective preventive actions might be possible.

The first example concerns the prevention of early child abuse and neglect, earlier identified as a broad-spectrum risk factor for both mental disorders and chronic physical diseases. In their Lancet review on interventions to prevent child maltreatment in 2009, Macmillan et al. [33] concluded that some home-visit programs have shown significant results in controlled trials. Effective programs include among others the Nurse-Family Partnership program that was evaluated in three randomized controlled trials across different US regions [34]. The program uses trained nurses that visit low-income first-time mothers during pregnancy and infancy, many of whom are single mothers or who have to cope with other life stressors. The nurses offer parent education, promote a healthy lifestyle, help the mothers to develop supportive relationships, and link them to appropriate health and social services. The studies showed a wide variety of positive outcomes, including healthier maternal diets and less smoking, 75% fewer preterm deliveries, less irritable and fussy babies, a large drop in cases of child maltreatment, fewer emergency visits and less injury requiring medical examination, higher IQ among children of smoking mothers, and shorter periods of maternal dependency on social welfare. Fifteen years later, children from the intervention group showed dramatically less exposure to child abuse over this period, and lower levels of adolescent substance abuse, arrests and convictions than children from the control condition. Several other home-visit programs were not successful in reducing child maltreatment. Likely conditions for successful programs are a theory base, use of trained professionals (nurses) and safeguarding program fidelity during implementation. Also starting home-visiting during pregnancy might have significantly contributed to the success of the Nurse-Family Partnership program.

Two other types of programs have shown significant benefits in randomized trials, as reported by Macmillan et al. [33]. In the Safe Environment for Every Kid (SEEK) program, pediatric residents were trained to identify family problems and to link families to a social worker if needed. Families served by these trained residents showed fewer child-protection service reports, fewer instances of medical neglect, and less harsh punishment reported by parents, although the results were only marginally significant. Triple P is an Australian multicomponent program on positive parenting that addresses both universal and targeted populations of parents, using a wide variety of educational methods (e.g. group work, mass media, books, lectures). The results across 48 controlled studies showed significant reductions in ineffective parenting and depression among parents and less behavioral problems among their children, and in one large randomized trial across 18 US counties around 1 in 5 less cases of registered child abuse and less child maltreatment injuries [35,36]. The program is currently implemented in a wide range of countries around the world.

Most intervention programs that aim to prevent the onset of depression make use of cognitive-behavioral treatment principles to educate at-risk individuals to challenge negative beliefs, enhance positive thinking, and strengthen their problem solving and social skills. A wide variety of such programs have been standardized for adolescents, adults and elderly. The best known are the Coping with Depression Course and the Penn Resilience Program. These types of programs are provided in different formats such as group-based courses, self-help books in combination with telephone support and as internet-based programs. Each of these formats can easily be provided by physical and mental health services or by national institutes or nongovernmental organizations in the case of internet-based programs. Several reviews and meta-analyses across a large range of controlled trials have shown that these programs are effective in reducing depression-prone risk factors and depressive symptoms in different age groups, including older adults [37,38]. Face-to-face, internet-based and self-help formats were all found to be effective. A meta-analysis of 19 randomized controlled trials that tested the impact of selected and indicated depression prevention programs found an average 22% reduction in the onset of depressive episodes as a result of participation in comparison to the incidence in the control groups [17]. One randomized controlled trial tested the integration of preventive interventions in a stepped care mental health service model for elderly with an elevated level of depressive symptoms [39]. Implementation of this prevention-oriented stepped care model resulted in a 50% reduction in incident depression or anxiety among elderly people aged 75 years or older, which was sustained over 24 months.

While chronic physical illnesses increase the risk of secondary mental disorders, such as depression and anxiety disorders, one might expect that public health efforts to prevent physical illnesses might also result in a lower incidence of secondary mental disorders. For instance, meta-analyses and systematic reviews have shown that the risk of type 2 diabetes and cardiovascular disease can be reduced through behavioral counseling to promote physical activity and a healthy diet [40,41,42]. No insight exists, however, on the impact of such programs at the onset of secondary depression among those at risk.

This exploratory paper has revealed a range of weaknesses in current knowledge and challenges for future prevention research. These challenges concern both the development of basic knowledge on the causal mechanisms of comorbidity, and the need to understand what works and how to prevent comorbidity.

The first challenge is to better understand what common risk and protective factors and shared developmental trajectories are in the etiology of mental disorders and chronic physical diseases. The science of developmental psychopathology could serve as a great source for such knowledge as this field is typically multidisciplinary in nature and studies complex and long-term etiological trajectories. The aim is to understand the spectrum of long-term mental and physical outcomes of common early risk factors (multifinality) as well as the different etiological paths toward a similar disorder (equifinality). Its multidisciplinary nature facilitates the integration of knowledge from genetic and epigenetic, biological, neurological, psychological and social research. This cross-fertilization of research approaches offers great opportunities to understand the interplay of biological, behavioral and social forces along the life span, and how the development of mental and somatic disorders is intertwined.

The growing knowledge on the narrow relationships between mental and physical disorders challenges the current practice in prevention research of treating the mental and physical disease domains as completely separated fields. As a consequence, in current prevention studies in the physical and mental health domains, major opportunities are missed to understand possible broad-spectrum effects of prevention programs that surpass the originally targeted domain. It is likely that both programs could contribute to outcomes in the other domain - outcomes that have remained undetected so far. Breaking through the borders between both domains could also open research on innovative approaches where prevention programs from both domains could be combined to create a higher level of ‘collective impact'. For instance, under what conditions could lifestyle programs contribute to the prevention of depression and anxiety? How can depression prevention and mental health promotion programs be combined with lifestyle education in order to reduce smoking and obesity more effectively?

To understand the relationship between mental and physical processes and disorders better, it is necessary to broaden the range of baseline and outcome indicators in prevention studies. In prevention studies primarily targeting common mental disorders, more physical health indicators should be added, and likewise, mental health indicators should be added to studies primarily targeting physical disorders. Currently, it is common practice in trials targeted at the prevention of a specific disorder to measure at baseline only the presence of that disorder to exclude those with the disorder from participation in the trial. It is, however, likely that many included subjects had other disorders in the preceding year or at baseline that remained unnoticed. Including a wider set of health and mental health indicators could offer more insight into the impact of prevention trials on comorbidity, as well as in the impact of comorbid disorders on the outcomes of prevention trials.

Lastly, it would be desirable to combine the use of a wider spectrum of outcome indicators with longitudinal research designs in prevention studies. Many prevention and mental health promotion programs address early risk and protective factors (e.g. child maltreatment, parenting, social and emotional resilience) that might be related to a broad spectrum of mediating or long-term health outcomes. Studies that measure only short-term outcomes will likely undervalue the potential spectrum of effects of a prevention program.

In conclusion, a major issue for the future research agenda is to study what the potential of current evidence-based programs in the mental health domain is to prevent comorbidity, to improve both physical and mental health, and to learn how physical and mental health are related along the lifespan.

The analysis and findings presented in this chapter show that a wide range of policy- and practice-based strategies are possible to prevent comorbidity, as illustrated in table 1. This should have implications for the work of individual physical and mental health practitioners, as well as for national and local public health and prevention policies.

Table 1

Policy- and practice-based strategies to prevent comorbidity of mental and physical disorders

Policy- and practice-based strategies to prevent comorbidity of mental and physical disorders
Policy- and practice-based strategies to prevent comorbidity of mental and physical disorders

Recognizing the interrelatedness of mental disorders with chronic physical diseases, and the role of common risk and protective factors, future policy plans should be more focused at integrated approaches, addressing mental and physical outcomes simultaneously. Currently, prevention of mental disorders still occupies a marginal and undervalued position in public health policies and health budgets worldwide. Finding opportunities for shared preventative and health promotion approaches might open new perspectives for preventing mental disorders. It will offer better opportunities to expand the reach in the population. It will also offer opportunities to increase the resources and professional capacity to implement prevention for mental health. This will be more likely when evidence shows that preventive interventions in the mental health domain are successfully targeting risk and protective factors that also have an impact on the development of chronic physical diseases. Given the growing knowledge of the impact of stress and depression on the functioning of the immune system, such a perspective is not imaginary.

To make practitioners and local health and mental health services more willing and capable to address the prevention of comorbidity, their expertise in preventative strategies and interventions needs to be expanded. This initially requires making prevention and comorbidity a standard element in the training of general practitioners, nurses, psychiatrists, psychologists and social workers. Secondly, the knowledge and accessibility of available evidence-based preventative interventions need to be increased. This could be facilitated by easily accessible databases of effective prevention programs as these are already available in some countries, such as the USA, the Netherlands, Norway and Germany. By establishing an international network of such databases, international exchange of new evidence-based programs and best practices could be improved.

Finally, this book is devoted to the relationship between mental and physical disorders. There are good reasons, however, to assume that the relationship between both types of problems is caused or at least reinforced by existing social problems, such as poverty, unemployment, discrimination, domestic violence, war-related traumas, housing problems, poor social networks, social isolation and social stigma. Such social circumstances could be considered as common risk factors or even as the ‘root of the roots'. For this reason, the message of this book is that the single disorder approach to address mental-physical comorbidity should be expanded to focus on social-mental-physical comorbidity. The public health and prevention approaches in the future should not be targeted at single disorders one by one, but at so-called ‘smart clusters' of highly related social, mental and physical problems, especially those clusters that concentrate in low-income countries, problem areas, disadvantaged communities or populations at high risk for an accumulation of problems. This challenges health and public health managers, health promoters, nongovernmental organizations, community leaders, citizen groups, private companies, policy makers and politicians to sit together and communicate about an effective integral preventive approach to such clusters of problems. In such a comprehensive approach, multiple social measures and preventive interventions could be combined in a complementary way, where the collective impact is larger and has a broader spectrum than could be achieved by stand-alone interventions and programs. Such a smart cluster and integral approach could be concentrated at crucial stages of the life span, such as a ‘healthy start in life' to facilitate children growing up in healthy, safe and caring environments that enhance their physical, mental and social resilience, and immune systems, and will contribute to less mental, physical and social problems during their adolescence and adulthood. Integrating a focus on the social determinants in a mental health approach is in line with the core messages of the recent WHO Comprehensive Mental Health Action Plan 2013-2020 [43].

In conclusion, the field of mental health and physical health should become more integrated, which would make working on the prevention of comorbidity a normal phenomenon instead of an exception. In the end it will be the well-being of the person that will gain most from it.

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Bierman KL, Coie JD, Dodge KA, et al: The effects of the Fast Track Program on serious problem outcomes at the end of elementary school. J Clin Child Adolesc Psychol 2004;33:650-661.
21.
Grove AG, Evans SW, Pastor DA, Mack SD: A meta-analytic examination of follow-up studies of programs designed to prevent the primary symptoms of oppositional defiant and conduct disorders. Aggress Violent Behav 2008;13:169-184.
22.
Wilson WJ, Lipsey MW: School-based interventions for aggressive and disruptive behavior: update of a meta-analysis. Am J Prev Med 2007;33(2 suppl):S130-S143.
23.
Jackson C, Geddes R, Haw S, Frank J: Interventions to prevent substance use and risky sexual behavior in young people: a systematic review. Addiction 2011;107:733-747.
24.
Aos S, Lieb R, Mayfield J, Miller M, Pennucci A: Benefits and Costs of Prevention and Early Intervention Programs for Youth. Olympia, Washington State Institute for Public Policy, 2004.
25.
Kessler R, Price R: Primary prevention of secondary disorders: a proposal and agenda. Am J Community Psychol 1993;21:607-633.
26.
Oldenburg B, O'Neil A, Cocker F: Public health perspectives on the co-occurence of non-communicable diseases and common mental disorders; in Sartorius N, Holt RIG, Maj M (eds): Comorbidity of Mental and Physical Disorders. Key Issues Ment Health. Basel, Karger, 2015, vol 179, pp 15-22.
27.
Scott KM: The development of mental-physical comorbidity; in Von Korff MR, Scott KM, Gureje O (eds): Global Perspectives on Mental-Physical Comorbidity in the WHO World Mental Health Surveys. New York, Cambridge University Press, 2009, pp 97-107.
28.
Wittchen HH, Kessler RC, Pfister H, Lieb M: Why do people with anxiety disorders become depressed? A prospective longitudinal community study. Acta Psychiatr Scand Suppl 2000;406:14-23.
29.
Appleyard K, Byron E, Van Dulmen MH, Sroufe LA: When more is not better: the role of cumulative risk in child behavior outcomes. J Child Psychol Psychiatry 2005;46:235-245.
30.
Rutter M, Quinton D: Parental psychiatric disorder: effects on children. Psychol Med 1984;14:853-880.
31.
Hassler G, Pine DS, Gamma A, Milos G, Ajdacic V, Eich D, Rössler W, Angst J: The associations between psychopathology and overweight: a 20-year prospective study. Psychol Med 2004;34:1047-1057.
32.
Kawada T, Inagaki H, Wakayama Y, Katsumata M, Li Q, Li Q, Otsuka T: Depressive state and subsequent weight gain in workers: a 4-year follow up study. Work 2011;38:123-127.
33.
Macmillan HL, Wathen CN, Barlow J, Fergusson DM, Leventhal JM, Taussig HN: Interventions to prevent child maltreatment and associated impairment. Lancet 2009;373:250-266.
34.
Olds DL: The nurse-family partnership: an evidence-based preventive intervention. Infant Ment Health J 2006;27:5-25.
35.
De Graaf I, Speetjens P, Smit F, de Wolff M, Tavecchio L: Effectiveness of the Triple P Positive Parenting Program on parenting: a meta-analysis. Fam Relat 2008;57:553-566.
36.
Prinz RJ, Sanders MR, Shapiro CJ, Whitaker DJ, Lutzker JR: Population-based prevention of child maltreatment: the US Triple P system population trial. Prev Sci 2009;10:1-12.
37.
Forsman AK, Schierenbeck I, Wahlbeck K: Psychosocial interventions for the prevention of depression in older adults: systematic review and meta-analysis. J Aging Health 2011;23:387-416.
38.
Calear AL, Christensen H: Systematic review of school-based prevention and early intervention programs for depression. J Adolesc 2010;33:429-438.
39.
van't Veer-Tazelaar PJ, van Marwijk HW, van Oppen P, van der Horst HE, Smit F, Cuijpers P, Beekman AT: Prevention of late-life anxiety and depression has sustained effects over 24 months: a pragmatic randomized trial. Am J Geriatr Psychiatry 2011;19:230-239.
40.
Esposito K, Kastorini CM, Panagiotakos DB, Giugliano D: Prevention of type 2 diabetes by dietary patterns: a systematic review of prospective studies and meta-analysis. Metab Syndr Relat Disord 2010;8:471-476.
41.
Lin JS, O'Connor E, Whitlock EP, Beil TL: Behavioral counseling to promote physical activity and a healthful diet to prevent cardiovascular disease in adults: a systematic review for the U.S. Preventive Services Task Force. Ann Intern Med 2010;153:736-750.
42.
Rawal LB, Tapp RJ, Williams ED, Chan C, Yasin S, Oldenburg B: Prevention of type 2 diabetes and its complications in developing countries: a review. Int J Behav Med 2012;19:121-133.
43.
World Health Organization: Comprehensive Mental Health Action Plan 2013-2020. Geneva, WHO, 2013.

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Data & Figures

Fig. 1

Model of strategies to prevent comorbidity across the developmental trajectory and targeted at common or disorder-specific factors.

Fig. 1

Model of strategies to prevent comorbidity across the developmental trajectory and targeted at common or disorder-specific factors.

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Table 1

Policy- and practice-based strategies to prevent comorbidity of mental and physical disorders

Policy- and practice-based strategies to prevent comorbidity of mental and physical disorders
Policy- and practice-based strategies to prevent comorbidity of mental and physical disorders

Contents

References

1.
Von Korff MR, Scott KM, Gureje O: Global Perspectives on Mental-Physical Comorbidity in the WHO World Mental Health Surveys. New York, Cambridge University Press, 2009.
2.
Gureje O: The pattern and nature of mental-physical comorbidity: specific or general?; in Von Korff MR, Scott KM, Gureje O (eds): Global Perspectives on Mental-Physical Comorbidity in the WHO World Mental Health Surveys. New York, Cambridge University Press, 2009, pp 51-83.
3.
Gilbert R, Spatz Widom C, Browne K, Fergusson D, Webb E, Janson S: Burden and consequences of child maltreatment in high-income countries. Lancet 2009;373:68-81.
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Fried LP, Ferrucci L, Darer J, Williamson JD, Anderson G: Untangling the concepts of disability, frailty, and comorbidity: implications for improved targeting and care. J Gerontol A Biol Sci Med Sci 2004;59:255-263.
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Gijsen R, Hoeymans N, Schellevis FG, Ruwaard D, Satariano WA, van den Bos GA: Causes and consequences of comorbidity: a review. J Clin Epidem 2001;54:661-674.
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Romano J, Turner J: Chronic pain and depression: does the evidence support a relationship? Psychol Bull 1985;97:18-34.
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Turner R, Noh S: Physical disability and depression: a longitudinal analysis. J Health Soc Behav 1988;29:23-37.
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Eaton WW, Armenian H, Gallo J, Pratt L, Ford DE: Depression and risk for onset of type II diabetes. A prospective population-based study. Diabetes Care 1996;19:1097-1102.
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Penninx BW, Beekman AT, Ormel J, Kriegsman DM, Boeke AJ, Eijk JT, Deeg DJ: Psychological status among elderly people with chronic diseases: does type of disease play a part? J Psychosom Res 1996;40:521-534.
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Hosman CM, Jane-Llopis E, Saxena S (eds): Prevention of Mental Disorders: Effective Interventions and Policy Options. WHO Summary Report 2004. Geneva, World Health Organization, 2004.
13.
Saxena S, Jane-Llopis E, Hosman C: Prevention of mental and behavioral disorders: implications for policy and practice. World Psychiatry 2006;5:5-14.
14.
Institute of Medicine and National Research Council: Preventing Mental, Emotional, and Behavioral Disorders among Young People: Progress and Possibilities. Committee on Prevention of Mental Disorders and Substance Abuse among Children, Youth and Young People. Washington, National Academic Press, 2009.
15.
Anderson P, Jane-Llopis E, Hosman C: Reducing the silent burden of impaired mental health. Health Prom Int 2011;26(suppl 1):i4-i9.
16.
Cuijpers P, Van Straten A, Smit F, Mihalopoulos C, Beekman A: Preventing the onset of depressive disorders: a meta-analytic review of psychological interventions. Am J Psychiatry 2008;165:1272-1280.
17.
Fisak BJ Jr, Richard D, Mann A: The prevention of child and adolescent anxiety: a meta-analytic review. Prev Sci 2011;12:255-268.
18.
Teubert D, Pinquart M: A meta-analytic review on the prevention of symptoms of anxiety in children and adolescents. J Anxiety Disord 2011;25:1046-1059.
19.
Taylor CB, Bryson S, Luce KH, Cunning D, Doyle AC: Prevention of eating disorders in at-risk college-age women. Arch Gen Psychiatry 2006;63:881-888.
20.
Bierman KL, Coie JD, Dodge KA, et al: The effects of the Fast Track Program on serious problem outcomes at the end of elementary school. J Clin Child Adolesc Psychol 2004;33:650-661.
21.
Grove AG, Evans SW, Pastor DA, Mack SD: A meta-analytic examination of follow-up studies of programs designed to prevent the primary symptoms of oppositional defiant and conduct disorders. Aggress Violent Behav 2008;13:169-184.
22.
Wilson WJ, Lipsey MW: School-based interventions for aggressive and disruptive behavior: update of a meta-analysis. Am J Prev Med 2007;33(2 suppl):S130-S143.
23.
Jackson C, Geddes R, Haw S, Frank J: Interventions to prevent substance use and risky sexual behavior in young people: a systematic review. Addiction 2011;107:733-747.
24.
Aos S, Lieb R, Mayfield J, Miller M, Pennucci A: Benefits and Costs of Prevention and Early Intervention Programs for Youth. Olympia, Washington State Institute for Public Policy, 2004.
25.
Kessler R, Price R: Primary prevention of secondary disorders: a proposal and agenda. Am J Community Psychol 1993;21:607-633.
26.
Oldenburg B, O'Neil A, Cocker F: Public health perspectives on the co-occurence of non-communicable diseases and common mental disorders; in Sartorius N, Holt RIG, Maj M (eds): Comorbidity of Mental and Physical Disorders. Key Issues Ment Health. Basel, Karger, 2015, vol 179, pp 15-22.
27.
Scott KM: The development of mental-physical comorbidity; in Von Korff MR, Scott KM, Gureje O (eds): Global Perspectives on Mental-Physical Comorbidity in the WHO World Mental Health Surveys. New York, Cambridge University Press, 2009, pp 97-107.
28.
Wittchen HH, Kessler RC, Pfister H, Lieb M: Why do people with anxiety disorders become depressed? A prospective longitudinal community study. Acta Psychiatr Scand Suppl 2000;406:14-23.
29.
Appleyard K, Byron E, Van Dulmen MH, Sroufe LA: When more is not better: the role of cumulative risk in child behavior outcomes. J Child Psychol Psychiatry 2005;46:235-245.
30.
Rutter M, Quinton D: Parental psychiatric disorder: effects on children. Psychol Med 1984;14:853-880.
31.
Hassler G, Pine DS, Gamma A, Milos G, Ajdacic V, Eich D, Rössler W, Angst J: The associations between psychopathology and overweight: a 20-year prospective study. Psychol Med 2004;34:1047-1057.
32.
Kawada T, Inagaki H, Wakayama Y, Katsumata M, Li Q, Li Q, Otsuka T: Depressive state and subsequent weight gain in workers: a 4-year follow up study. Work 2011;38:123-127.
33.
Macmillan HL, Wathen CN, Barlow J, Fergusson DM, Leventhal JM, Taussig HN: Interventions to prevent child maltreatment and associated impairment. Lancet 2009;373:250-266.
34.
Olds DL: The nurse-family partnership: an evidence-based preventive intervention. Infant Ment Health J 2006;27:5-25.
35.
De Graaf I, Speetjens P, Smit F, de Wolff M, Tavecchio L: Effectiveness of the Triple P Positive Parenting Program on parenting: a meta-analysis. Fam Relat 2008;57:553-566.
36.
Prinz RJ, Sanders MR, Shapiro CJ, Whitaker DJ, Lutzker JR: Population-based prevention of child maltreatment: the US Triple P system population trial. Prev Sci 2009;10:1-12.
37.
Forsman AK, Schierenbeck I, Wahlbeck K: Psychosocial interventions for the prevention of depression in older adults: systematic review and meta-analysis. J Aging Health 2011;23:387-416.
38.
Calear AL, Christensen H: Systematic review of school-based prevention and early intervention programs for depression. J Adolesc 2010;33:429-438.
39.
van't Veer-Tazelaar PJ, van Marwijk HW, van Oppen P, van der Horst HE, Smit F, Cuijpers P, Beekman AT: Prevention of late-life anxiety and depression has sustained effects over 24 months: a pragmatic randomized trial. Am J Geriatr Psychiatry 2011;19:230-239.
40.
Esposito K, Kastorini CM, Panagiotakos DB, Giugliano D: Prevention of type 2 diabetes by dietary patterns: a systematic review of prospective studies and meta-analysis. Metab Syndr Relat Disord 2010;8:471-476.
41.
Lin JS, O'Connor E, Whitlock EP, Beil TL: Behavioral counseling to promote physical activity and a healthful diet to prevent cardiovascular disease in adults: a systematic review for the U.S. Preventive Services Task Force. Ann Intern Med 2010;153:736-750.
42.
Rawal LB, Tapp RJ, Williams ED, Chan C, Yasin S, Oldenburg B: Prevention of type 2 diabetes and its complications in developing countries: a review. Int J Behav Med 2012;19:121-133.
43.
World Health Organization: Comprehensive Mental Health Action Plan 2013-2020. Geneva, WHO, 2013.
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