Individuals with major psychotic and/or affective disorders are at increased risk for developing metabolic syndrome due to lifestyle- and treatment-related factors. Numerous pharmacological and non-pharmacological interventions have been tested in inpatient and outpatient mental health settings to decrease these risk factors. This review focuses on primary care-based non-pharmacological (educational or behavioral) interventions to decrease metabolic syndrome risk factors in adults with major psychotic and/or affective disorders.
The authors conducted database searches of PsychINFO, MEDLINE and the Cochrane Database of Systematic Reviews, as well as manual searches and gray literature searches to identify included studies.
The authors were unable to identify any studies meeting a priori inclusion criteria because there were no primary care-based studies.
This review was unable to demonstrate effectiveness of educational interventions in primary care. Interventions to decrease metabolic syndrome risk have been demonstrated to be effective in mental health and other outpatient settings. The prevalence of mental illness in primary care settings warrants similar interventions to improve health outcomes for this population.
Comorbidity of mental illness and chronic physical illness
Individuals with major psychotic and/or affective disorders (for example, schizophrenia, bipolar disorder or major depressive disorder) experience higher rates of comorbid physical health problems compared with the general population. Cardiovascular risk and metabolic risk are increased in individuals with schizophrenia
[1–3] and depression
[4, 5]. Bipolar disorder has also been shown to be associated with metabolic syndrome
[6, 7]. Risk factors for cardiovascular disease and metabolic syndrome include: high blood pressure, large waist circumference, high triglyceride levels, low HDL cholesterol level, and high fasting blood sugar levels.
Causes of comorbidity in this population are thought to include psychiatric medication and lifestyle factors, such as diet and tobacco consumption. Atypical antipsychotic medication (AAP), commonly prescribed for patients with bipolar disorder or schizophrenia, increases risk for metabolic syndrome
[8–10]. Individuals with major psychotic disorders, especially schizophrenic disorders, also consume tobacco at higher rates than the general population
[1, 11–13], which partially explains the increased risk of cardiovascular disease in this population. Bobes et al.
 found that tobacco users with major psychotic or affective/mood disorders were more likely to consume daily alcohol and caffeine and less likely to avoid salt and saturated fats. Sedentary lifestyle and unhealthy food consumption patterns, including higher daily intake of calories and cholesterol, are common among individuals with major psychotic and/or affective disorders
Previous interventions tested
Many interventions intended to decrease risk factors for metabolic syndrome, both pharmacological and non-pharmacological, have been tested and described in the literature. Systematic reviews and meta-analyses of interventions to control risk factors for metabolic syndrome
[15–23] indicate that both pharmacological and non-pharmacological (that is, behavioral or educational) interventions can be effective in decreasing metabolic risk. The studies described in these systematic reviews generally take place in mental health settings, which may exclude those individuals with mental illness who receive treatment primarily in the primary care setting. Only one study included in these reviews
 features a primary care-based intervention. Previous weight loss interventions conducted in the primary care setting have demonstrated efficacy in many populations
Mental illness in primary care
Individuals with major psychotic or affective/mood disorders who are not psychiatrically hospitalized are generally treated for physical and sometimes mental health disorders in primary care settings in the U.S. due to a lack of integrated medical and behavioral health programs. Several studies in the U.S. and elsewhere have noted the prevalence of major psychotic or affective/mood disorders in the primary care setting. Serrano-Blanco et al.
 conducted a study with over 3,800 primary care patients and found that 29.9% had a diagnosis of major depressive disorder. Das et al.
 screened 1,157 primary care patients and found that approximately 10% met diagnostic criteria for bipolar disorder. Blount
 reported that 80% of individuals with a mental health disorder will see their primary care physician in a given year, while only 50% will see a mental health provider. Roca et al.
 reported on a similar study of more than 7,900 primary care patients and found that 29% of patients had been diagnosed with major depressive disorder. Fernandez et al.
 conducted a cross-sectional study in primary care and found that mood disorders are the second leading cause of quality-adjusted life years in the primary care setting. The loss of quality of life and prevalence of psychiatric disorders in primary care demonstrates a need for primary-care based interventions to decrease chronic comorbid conditions.
Objectives of review
The prevalence of psychiatric disorders in primary care settings and the association between chronic mental and physical illness necessitates an exploration of primary care-based interventions to address these comorbid conditions. This review focuses on non-pharmacological, education-based interventions to address metabolic syndrome risk factors in patients with major psychotic or affective/mood disorders who are treated in the primary care setting. The emphasis is on metabolic syndrome risk factors because this combination of risk factors can lead to chronic illnesses and early mortality in this population
. Education-based interventions are important because they empower the patient to manage his/her illness independently and expand the role of social workers in the primary care setting. According to Michie, Fixsen, Grimshaw and Eccles
, systematic reviews of behavior change interventions typically produce modest effects. The primary author was involved in a primary care-based complex intervention to improve metabolic risk factors among patients with major psychotic and/or affective/mood disorders and patient reports indicated that they found the educational components most beneficial for self-management of illnesses
Electronic searches were conducted using MEDLINE, PsychINFO and the trials registry of the Cochrane Database of Systematic Reviews. The abstracts, titles and index terms of studies were searched in MEDLINE and PsychINFO using the following keywords: “schizophreni*” OR “schizoaffective” OR “bipolar” OR “major depressive disorder” OR “posttraumatic stress disorder” OR “serious mental illness” AND “metabolic syndrome” OR “high blood pressure” OR “triglycerides” OR “cholesterol” OR “HDL” OR “waist circumference” OR “blood sugar” OR “blood glucose” AND “intervention” OR “randomized controlled trial” OR “quasi-randomized” AND “primary care.” All titles in the Cochrane Schizophrenia Register were scanned for possible inclusion. Additionally, manual searches were conducted using references from literature found in the database search.
Inclusion and exclusion criteria
Studies were included if the population studied met the following criteria: adults ages 18 or older; diagnosed with one of the five mental illnesses which typically constitute major psychotic and/or affective disorders (schizophrenia (DSM-V code 295.9), schizoaffective disorder (DSM-V code 295.7), major depressive disorder (DSM-V code 296.3), or bipolar disorder (DSM-V codes 296.4 and 296.5)); and had risk factors for metabolic syndrome, including large waistline, a high triglyceride level, a low HDL cholesterol level, high blood pressure, and high fasting blood sugar level. The study setting must have been in a primary care location. The study design must have been either a randomized controlled trial (RCT) or a quasi-experimental study. Study outcomes must include one of the risk factors for metabolic syndrome (for example, blood pressure, waist circumference, triglyceride levels, blood glucose or (an increase in) HDL).
Studies were excluded if:
the population studied was younger than 18 years old or did not have a diagnosis of a major psychotic and/or affective disorders or risk factors for metabolic syndrome;
they were conducted in an inpatient or mental health-based setting;
they were not an RCT or quasi-experimental study, and
the outcome of the study did not include one of the risk factors for metabolic syndrome.
Our initial systematic search of databases MEDLINE and PsychINFO (which was not limited by setting) yielded 316 results. When "primary care" was added to the search, we found 19 additional results. A title search of the Cochrane Database of Systematic Reviews resulted in the identification of two systematic reviews; one review had no included studies and the other had six studies included in the quantitative synthesis. These studies were also identified in database searches and are part of the 363 total studies identified below. Manual searches from reference lists of articles found in the database search were conducted and 90 studies were found. A search of gray literature was conducted to decrease risk of publication bias using Open Grey (
http://www.opengrey.eu) with the same MESH terms, but no additional studies were found. A total of 363 unique studies were found from the collection of searches after duplicates were removed. The titles of all 363 of these results were reviewed separately by each reviewer and 303 were excluded based on setting or nature of intervention. There were no disagreements during this process. The remaining 60 articles were reviewed in abstract and 30 were excluded based on study design or setting. Full-text reviews were conducted by both reviewers CN and SJ for the remaining 30 of the studies and reviewers agreed that no studies met inclusion criteria; all studies were excluded. Additional file
1 provides a diagram of how studies were excluded. Table
1 lists all of the studies reviewed in full-text from database searches and manual searches with reasons for exclusion.
Through the manual search, 13 systematic reviews were identified for further review of citations. Table
2 provides a list of the 13 systematic reviews. These reviews examined a total of 221 studies. Raters CN and SJ independently screened titles or abstracts from these studies and all 221 studies were rejected for not meeting the inclusion criteria.
# of studies reviewed in article
Alvarez-Jiminez, Hetrick, Gonzalez-Blanch, Gleeson and McGorry,
Non-pharmacological management of antipsychotic-induced weight gain: systematic review and meta-analysis of randomized controlled trials
Individual and group interventions, cognitive behavioral therapy and nutritional counseling were more effective than treatment as usual.
Efficacy of behavioural interventions in managing atypical antipsychotic weight gain
When behavioral interventions were initiated at the start of atypical antipsychotic (AAP) treatment, amount of weight gain was decreased. When initiated after the start of AAP treatment, weight loss was achieved. Insulin regulation and A1c (metabolic syndrome risk factors) were also improved.
Behavioral management of antipsychotic-induced weight gain: a review
No RCTs identified, but interventions appear to be effective.
Although we identified no studies that met the a priori inclusion criteria, there were 16 studies identified during database and manual searches that examined similar interventions in non-primary care settings. These studies (listed in Table
3) demonstrate that controlled trials with education interventions to improve physical health can be conducted with individuals with major psychotic and/or affective disorders; the systematic reviews shown in Table
2 indicate that these interventions can be effective. Also, it should be recognized that no evidence of effective primary care-based studies does not mean that such intervention is ineffective; further studies are needed in this area to determine whether such interventions can be effective in primary care settings.
Similar interventions not in primary care settings
A cognitive behavioral group intervention for weight loss in patients treated with atypical antipsychotics
Based on Diabetes Prevention Project (DPP) program to prevent diabetes
Of the 16 similar studies of educational interventions, reviewers identified 6 studies that may be able to be implemented in the primary care setting
[42, 51, 53, 56, 63, 65]. Those studies of interventions that might not be appropriate for primary care include interventions that were too long
[45, 47, 61], provided products or services that might not be available in primary care settings
[43, 48, 55, 62, 71] or required patients to have not yet developed physical risk factors prior to the intervention
An examination and discussion of the details of the interventional components of the studies possible in primary care identified in Table
3 is warranted here, because future studies in the primary care setting must adequately describe their interventions in order to be replicated or subject to systematic review. The methodological quality of these studies is summarized in Table
4. All of these studies provided explicit descriptions of the intervention components; McKibbin et al.
, Weber and Wyne
 and Kwon et al.
 also described session-by-session content of the intervention in table and narrative format; Brar et al.
 described sessions in narrative format only. Khazaal et al.
 used an intervention previously developed by one of the authors, so readers can review that intervention in detail elsewhere, but it was not described in detail in the article. Srkinar et al.
 provided a description of the length of the educational intervention and a list of topics, but no sequence or table of sessions was provided. All studies identified as possible in primary care included an intervention element that was not education (or example, food tasting, exercise sessions, provision of pedometers), so the effectiveness of the educational component alone may not be able to be determined from these studies; however, complex interventions are very common in behavioral health research
Methodological quality of studies appropriate for primary care
Control group received treatment as usual and were weighed every four weeks.
Yes; previous Diabetes Prevention Project
Yes (t-testt-test, statistical significance set at 0.05)
Missing from the descriptions of many articles reviewed in this study were details about who implemented an intervention and where it took place. A number of studies stated that participants were recruited from a certain hospital or facility (for example, Khazaal et al.
 and Skrinar et al.
, but it was not clear from the articles whether the actual educational intervention took place in the hospital or in an outpatient setting. Of the studies identified as possible in primary care, only Khazaal et al.
, Kwon et al.
 and Weber and Wyne
 provided a clear description of who was implementing the intervention, so it is not clear if academic researchers, dietitians, medical professionals or social workers were implementing the other interventions. It is also not clear in several studies, including Srkinar et al.
 and Khazaal et al.
, who was collecting any of the data, which could affect participant outcomes (for example, if the patients had an existing relationship with the data collectors) and may be subject to detection bias if assessors were not blind to allocation.
Health outcomes from complex behavioral interventions can be nebulous because multiple factors affect outcomes; however, the RCT format of the studies discussed here improves study rigor
. Two studies
[63, 65] resulted in no statistically significant reduction in metabolic risk factors, with both studies citing small sample sizes and other factors (for example, lack of transportation, motivation) as being possible explanations for these results. Khazaal et al.
 found limited reduction in weight and body mass index (BMI) in the experimental group. Some subjects’ medications were also changed during the study, although the authors used statistical methods to account for the possible impact of these changes
. McKibbin et al.
 and Kwon et al.
 reported significant reductions in metabolic syndrome risk factors (weight, BMI) as a result of their interventions. Kwon et al.
 also observed significant weight loss in the control group, which suggests possible threats to internal validity in the design. These authors do note that several members of the experimental group lost a greater percentage of body weight than anyone in the control group.
The authors were unable to identify rigorous, primary care-based interventions to address physical illness among individuals with mental illness. As the literature expands to include primary care-based interventions, additional systematic reviews and meta-analyses are warranted to assess effectiveness in this setting. Systematic reviews of high-quality RCTs are the most rigorous form of effectiveness research, as single RCTs can have weak designs or biased results
. Quality assurance protocols, such as the CLEAR NPT checklist for non-pharmacological trials
, which provides a checklist for components of quality in a study, should be incorporated into future studies in this area to provide standardized guidelines for making effectiveness claims.
Adequate reporting of interventional content and components is also essential to the expansion of literature in this subject area and groups, such as the Workgroup for Intervention Development and Evaluation Research (WIDER), have developed suggestions for intervention reporting (
http://interventiondesign.co.uk). WIDER advocates for the successful adoption of behavior change interventions and the expansion of CONSORT (
http://www.consort-statement.org) and APA guidelines to allow for improved reporting of these interventions. In behavioral intervention research, theories regarding the specific mechanism of change within an intervention should be utilized during the development of the intervention and should be described in the final report
Social work researchers and direct service social workers in health care settings have an opportunity to design and implement high-quality behavioral and educational programs for individuals with major psychotic and/or affective disorders using the criteria described above. Social workers are among the few professionals in health care settings who have the skills and opportunity to work closely with the patients most in need of health-related behavior change interventions, as they are generally able to spend more time with patients in health care settings and have access to medical information in collocated health and mental health settings. Interventions to decrease metabolic syndrome risk factors have been demonstrated to be successful in mental health settings, but the primary service in mental health settings is mental health. Primary care-based interventions are important for conveying the message that the focus is on physical health, even if the population is comprised of individuals with major psychotic and/or affective disorders. Social workers or social work researchers participating in health-focused interventions that do not follow published guidelines for research and reporting of RCTs are missing an important opportunity to enhance systematic reviews of literature about this population.
Atypical antipsychotic medication
Body mass index
Diabetes Awareness and Rehabilitation Training
Randomized control trial
The authors would like to acknowledge the contributions of Timothy Sharma, who assisted with study design and acquisition of data. This contribution was not funded by any outside source.
College of Social & Behavioral Sciences and Social Work, Eastern Washington University
Department of Epidemiology/Biostatistics, George Washington University, School of Public Health
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