Pedometer-based walking intervention for obesity in mental health patients

Management of Obesity In Psychiatric Mental Health Clinic

Introduction
Today, obesity has become a national public health problem in the United States, and more than one-in-three Americans are obese. Further, obesity has been recognized as a chronic disease by the American Association of Clinical Endocrinologists, the American Medical Association, the American College of Endocrinology, the American Society of Bariatric Physicians, the Endocrine Society, the Obesity Society, and the U.S. National Institutes of Health (Ampoy, 2019). Moreover, obesity represents more than a weight management problem because the condition can have a severe impact on health care consumers’ physical, metabolic and psychological health (Campoy, 2019).
Indeed, the U.S. National Heart, Lung and Blood Institute emphasizes that, “Obesity is a serious medical condition that can cause complications such as metabolic syndrome, high blood pressure, atherosclerosis, heart disease, diabetes, high blood cholesterol, cancers and sleep disorders” (Overweight and obesity, 2020, para. 2). Clearly, even the most well-adjusted health care consumers that suffer from obesity are faced with some serious constraints to their quality of life that can trigger various mental health disorders, including depression, anxiety and even suicide (Greenlee & Hyde, 2015).
Although every patient’s experience with obesity is unique in some fashion, interventions typically include some common approaches such as lifestyle modifications, various drugs with varying levels of efficacy, improved diet choices and increased physical activity (Overweight and obesity, 2020). Such interventions have assumed new importance and relevance in recent years as obesity has reached epidemic levels across the country.
In an effort to reverse these dangerous health care trends, the purpose of this project is to evaluate the effectiveness of a pedometer-based walking intervention in decreasing body-mass index (BMI) among adult patients in a mental health clinic with a BMI greater than 25kg per meter square. In furtherance of this overarching purpose, the project seeks to answer the following research question: “Does walking with a pedometer reduce BMI among 20 to 55-year-old overweight/obese adult patients in a mental health clinic within a period of 8 weeks?” The background and significance of this study is discussed below. Background and Significance The background of this problem is complex and its significance has become increasingly serious in recent years. Although there is an inextricable, documented relationship between mental health and obesity, it remains unclear whether people who are suffering from mental health disorders experience weight gain as a result of their mental condition or as a result of the side effects of the medications that are used to treat them. For example, according to a study by Simon, Von Korff, Saunders et al. (2006), “Obesity was associated with significant increases in lifetime diagnosis of major depression [and] is associated with an approximately 25% increase in odds of mood and anxiety disorders and an approximately 25% decrease in odds of substance use disorders” (p. 824).
Conversely, health care consumers may experience unwanted and unexpected weight gain that results in obesity as a result of the side effects of the medications that are typically used to treat mental disorders. In this regard, Bacon and Farnworth (2012) emphasize that:
Adverse side effects of the medications used to treat the symptoms of psychoses often include sedation and decreased metabolism, leading to rapid weight gain. This weight gain can lead to problems with an individual's health, wellbeing and quality of life and ability to perform necessary daily occupations. This is especially problematic for individuals with mental illness. (p. 62)
In other words, there is a “which came first, the chicken or the egg” quality to the debate concerning the relationship between obesity and mental disorders, but the research to date confirms this relationship irrespective of its primary causes (Bacon & Farnworth, 2012) and this issue directly relates to the problem of interest in this study which is discussed and described below. Problem Statement The problem of interest in this study concerns the fact that a growing body of scholarship has determined that an inordinate percentage of individuals suffering from mental disorders are also obese when compared to the general American population (Davies, 2016). For example, a study by Dickerson, Brown, Kreyenbuhl et al. (2006) using randomly selected mental health outpatients in Maryland determined that the BMI of these individuals was nearly double that of the overall population. Moreover, this finding has been replicated in numerous other studies which indicate that obesity in general and among mental health patients in particular has reached epidemic proportions nationwide and these issues are discussed further below.

Historical and Societal Perspective Body image assumed growing importance to both American men and women during the latter half of the 20th century, even as managing weight became increasingly problematic for many health care consumers due to a number of environmental factors. Compounding the problem was the increased levels of mental health disorders in the United States during the second half of the 20th century, which were attributed to the exigencies of fighting a major world war. For instance, according to Brill and Cooper (1993), “Mental health problems are pandemic in modern society. After World War II, disorders of anxiety and panic were prevalent throughout the United States, affecting soldiers as well as other Americans” (p. 46). Since that time, mental health disorders and obesity have garnered a negative perception by many Americans which has resulted in severe disparities in health care, employment and other areas of social justice (Cardinal & Whitney, 2014).Moreover, unhealthy diet choices and sedentary lifestyles have further exacerbated the problem over the past several decades.
It is important to note, though, that in any setting, maintaining appropriate weight in any setting is a complex phenomenon that is affected by a wide array of community- and individual-level factors. For instance, while obesity levels vary across the globe, more middle-aged and older adults are obese compared to the general population in the United States today (Flegal, Carroll, Ogden & Johnson, 2002). In addition, minority groups such as African Americans and Hispanics are suffer from higher rate of obesity compared to the general American population, as well as other ethnic minority groups (Simon et al., 2006). In addition, these racial and ethnic differences in obesity rates are also higher for American women compared to American men (Simon et al., 2006).
On the one hand, there have been some modest changes in obesity levels that are related to socioeconomic status. In this regard, Simon et al. (2006) point out that, “In developed economies, obesity is inversely associated with income and other indicators of socioeconomic status, but this relationship may be weakening over time” (p. 825). On the other hand, though, there has been a proliferation of so-called “food deserts” in many American inner city settings where the lack of access to healthy foods has exacerbated obesity levels among young and old alike of every ethnicity and gender. For example, based on the findings that emerged from their study, Simon and his associates conclude that, “At the community level, obesity is associated with greater access to inexpensive, calorie-dense foods and with reduced opportunities for physical activity” (p. 826).
In sum, although body image remains an important consideration for most Americans, maintaining appropriate body weight represents a seriously challenging enterprise. In fact, many researchers are characterizing the obesity problem as a national epidemic that demands a broad-based, multidisciplinary response. For example, Barden and Conley (2015) note that, “Within the mental health professions, wellness has been defined as a way of life oriented toward optimal health and well-being, in which body, mind, and spirit are integrated” (p. 153).
Nevertheless, current trends indicate that increasing numbers of Americans of all age and demographic groups are suffering from weight management problems that may lead to obesity due to the combination of sedentary lifestyles and unhealthy dietary choices or a lack of accessibility to healthy foods. It is therefore little wonder that the incidence and prevalence of obesity has increased significantly in the United States in recent years and these issues are discussed below. Incidence and Prevalence As noted above, the prevalence of mental health disorders increased significantly in the United States during the second half of the 20th century. Past year prevalence levels for all types of mental health disorders are depicted in Figure 1 below.

Figure 1. Mental health services received in past year among U.S. adults with any mental illness
Source: U.S. National Institute of Mental Health (2020) at https://www.nimh.nih.gov/health/ statistics/mental-illness.shtml
The incidence of obesity and extreme obesity for American adults that are aged 70 years and greater was more than three-quarters (75%) lower compared to the incidence of these conditions for health care consumers aged 18 to 29 years (1.5% versus 6.4%, and 0.2% versus 1.2%, respectively) (Pan, Freedman, Gillespie et al., 2011). Likewise, the prevalence rates for obesity of American adults during the period from 2015 through 2016 was 39.8%, meaning that about 93.3 million of American adults suffered from obesity during this period (Adult obesity facts, 2020).
As noted throughout, the increasing prevalence of obesity represents a major public health problem that has defied easy solutions to date. Defined as a BMI of 30 or greater, the prevalence of obesity among all American adults increased from less than one-quarter (23%) in 1990 to 31% by 2001, and these increases were experienced across all racial, ethnic and age groups for American men and women (Simon et al., 2006). The data from 2013 to 2014 also indicate significant prevalence levels for obesity among American adults, including the following findings by the National Institute of Diabetes and Digestive and Kidney Diseases: More than 2 in 3 adults (70.2 percent) were considered to be overweight or have obesity; About 1 in 3 adults (32.5 percent) were considered to be overweight; More than 1 in 3 adults (37.7 percent) were considered to have obesity; About 1 in 13 adults (7.7 percent) were considered to have extreme obesity; More than 1 in 3 (38.7 percent) of men, and about 1 in 4 (26.5 percent) of women were considered to be overweight; Obesity was higher in women (about 40 percent) than men (35 percent); Extreme obesity was higher in women (9.9 percent) than men (5.5 percent); and, Almost 3 in 4 men (73.7 percent) were considered to be overweight or have obesity; and about 2 in 3 women (66.9) were considered to be overweight or have obesity (Overweight & obesity statistics, 2020, para. 6). Despite major advances in health care and medical technologies in recent years that hold the promise of increased longevity for Americans in the future, the prevalence of obesity may offset these gains unless and until efficacious interventions are developed and implemented across the country (Simon et al., 2006). For example, Bacon & Farnworth (2012) emphasize that, “Given the expected increases in diabetes, cardiovascular disease, and other adverse consequences of obesity, increasing obesity rates are expected to produce an unprecedented decline in life expectancy in the United States” (p. 62).
Some indication of the historic trends that have been experienced with obesity in the United States can be discerned from the relevant statistical data that are depicted graphically in Figure 2 below. Although the National Institute of Mental Health and the U.S. Centers for Disease Control and Prevention do not report statistics specifically on the proposed study’s targeted population of 20 to 55-year-old overweight/obese adult patients, the overall increase in adults aged 20 years and over can be extrapolated from these trends.

Figure 2. Trends in adult overweight, obesity and extreme obesity among American adults: 1960-1962 and 2013-2014
Source: Overweight & Obesity Statistics at https://www.niddk.nih.gov/health-information/health-statistics/overweight-obesity
As can be seen from the trends depicted in Figure 1 above, while the number of overweight American men and women held essentially steady during the period from 1960 through 2014, the numbers of obese men and women aged 20 to 55 years overall experienced sustained and steady growth during this period. Likewise, the statistics concerning mental disorders are equally alarming. For example, according to the U.S. National Association of Mental Illness: 1 in 5 American adults experience a mental illness at some point during their lives; Nearly 1 in 25 (10 million) American adults live with a serious mental illness; One-half of all chronic mental illness begins by age 14 years and three-quarters by the age of 24 years (Mental health facts in America, 2020, p. 1). Not surprisingly, these trends have also resulted in some significant health care costs as well and these issues are discussed below.

Health Care Cost Overall, the costs that are associated with the additional health care burden that are directly attributable to obesity in the United States currently exceed a staggering $147 billion each year, and the health care costs for obese consumers are $1,429 higher compared to those for people with normal weight (Adult obesity facts, 2020). Furthermore, these costs represent a significant increase from just a few years ago. In this regard, according to a white paper published by the American Nurse Practitioner Foundation (2013), “The medical costs associated with obesity in the United States in 1995 were estimated at $79 billion; by 2008, obesity-associated medical costs had risen to an estimated $147 billion” (Nurse practitioners and the prevention and treatment of adult obesity, p. 1). Further, in 2008, the health care costs for treating obesity were estimated to be $1,429 higher for obese individuals compared to normally weighted individuals (Nurse practitioners and the prevention and treatment of adult obesity, 2013).
More recently, these costs have also experienced an across-the-board increase. For example, the average expenditures for individual health care consumers for the treatment of obesity in 2013 are set forth in Table 1 below.
Table 1
Increases in annual individual medical expenditures due to obesity and a one unit increase in BMI for different groups of adults
Sample
Total expenditures
Third party expenditures


BMI $ (SE)
Obesity $ (SE)
BMI $ (SE)
Obesity $ (SE)

Total (N?=?31,591)
197 (43)
3429 (799)
180 (41)
3210 (793)

Males (N?=?12,349)
244 (94)
3565 (1437)
225 (87)
3395 (1381)

Females (N?=?19,242)
179 (59)
3359 (804)
164 (38)
3116 (783)

White (N?=?12,895)
144 (59)
2557 (1173)
134 (54)
2454 (1084)

Non-White (N?=?18,696)
261 (71)
4086 (1050)
240 (70)
3799 (1034)

Private insurance (N?=?19,384)
216 (53)
3846 (1077)
199 (51)
3581 (1041)

Medicaid (N?=?4464)
182 (102)
2954 (1711)
170 (96)
2809 (1633)

Uninsured (N?=?7152)
91 (51)
1689 (922)
N/A
N/A



Source: Biener, Cawley & Meyerhoefer, 2017, p. 7
The data set forth in ?Table 1 above indicates that obesity increases the health care costs of adults by an average of $3,429 (in 2013 dollars) (Biener et al., 2017).
Likewise, the health care costs of treating mental health disorders are also significant and on the rise, amounting to $71 billion to treat depressive disorders alone (the most expensive category of mental health disorders), trailing only the costs to treat diabetes mellitus ($101.4 billion), ischemic heart disease ($88.1 billion), low back and neck pain ($87.6 billion), hypertension ($83.9 billion) and injuries due to falls ($76.3 billion) in terms of health care costs nationwide (Winerman, 2017).
These enormous costs are expected to continue to increase well into the foreseeable future unless efficacious interventions are developed and implemented for all demographic groups, including those health care consumers suffering from a combination of mental health disorders and obesity. These costs also mean that advanced practice registered nurses have an important role to play in weight management initiatives and these issues are discussed below.
Supporting Evidence for Advanced Practice Registered Nursing
Although there has been some modest progress made in recent years with respect to the awareness of obesity among health care consumers suffering from mental health disorders, the problem is still “relatively invisible in mental health contexts” (Ashley, 2015, p. 3). According to a white paper by the American Nurse Practitioner Foundation (ANPF) (2013), advanced practice registered nurses in particular can help motivate obese individuals to lose weight and keep it off. In this regard, the ANPF reports that, “Initially, patients might not be ready to lose weight and may require that ongoing assessment and support. The [advanced practice nurse] might need to have discussions about the importance of weight loss at more than one visit, while being sensitive to the patient’s readiness and/or ability to change” (Nurse practitioners and the prevention and treatment of adult obesity, p. 8).
Here again, although every patient’s experience is unique, there are some common strategies that are available that can help motivate obese people to initiate and adhere to a daily physical fitness regimen. For instance, the ANPF adds that, “A number of strategies can facilitate patient motivation. One recommended strategy is to facilitate the patient in identifying at least one compelling and personal reason to lose weight” (p. 8). Some typical examples of these types of individual reasons that may have varying levels of relevance for obese individuals with mental health disorders include the following: Decreasing the risk of a complicated pregnancy; Being able to keep up with or play with children or grandchildren; Walking without losing one’s breath; or, Preventing further chronic diseases (Nurse practitioners and the prevention and treatment of adult obesity, 2013, p. 8). In many instances, obese patients desperately want and need information concerning how they can prevent the adverse consequences of obesity, and advanced practice nurses are in a good position to provide this information in a culturally sensitive fashion (Nurse practitioners and the prevention and treatment of adult obesity, 2013). Therefore, regardless of the treatment setting, it is vitally important for advanced practice registered nurses to take the initiative and introduce evidence-based interventions that can help this population better manage its weight and any corresponding mental health disorders that might be caused or exacerbated by obesity. To this end, the weight-management initiative developed for this study will use the following instruments to achieve its research goals:
Instruments: Weight scale Stadiometer Fitbit app BMI calculator app Self- efficacy for exercise questionnaire

Design The intervention consists of engaging in a 30-minute brisk walk, 3 times a week for 8 weeks with weekly telephone coaching and reminders and three in-person sessions (weeks 1, 4, and 8). These coaching sessions were conducted using a Motivational Interviewing (MI) approach in order to enhance self-efficacy. All participants will receive written information published by U.S. government and local healthcare services concerning the importance of physical activity and healthy diet choices as well as additional online and community-based resources as part of any obesity-targeted intervention. Participants were educated on how to use these resources to set and attain their goals.
The first week consisted of signing the informed consent, baseline anthropometric measurements and completion of a Self-Efficacy for Exercise (SEE) Scale. Each participant was instructed to carry their phones with the downloaded pedometer app (fitbit) while engaging in a 30-minute brisk walk, 3 times a week for 8 weeks. Participants were advised not to change their dietary or walking habits the first week before the intervention. Participants were asked to keep daily logs of their dietary intake which will be obtained at the end of the intervention. Anthropometrics measurements were taken at baseline and also after 8 weeks of intervention in the morning prior to eating breakfast. This research strategy is congruent with the pragmatic guidance provided by Tudor-Locke and McClain (2009) who note that although pedometers do not provide the same accuracy as some other motion-sensor devices such as accelerometers, pedometers do provide a number of important statistics that can help evaluate physical activity levels and any corresponding weight loss. Furthermore, pedometers are also more practical because they are relatively inexpensive and easy to use while still providing many of the same advantages of more expensive and difficult-to-use motion sensor devices. In this regard, Tudor-Locke and McClain (2009) report that:
Although pedometers are not designed to detect physical activity intensity directly, they do provide a simple and affordable means of tracking daily physical activity volume (especially walking) expressed as a summary output of steps per day. Additionally, their output correlates highly with that of different accelerometers. (p. 164)
Body mass (weight) was measured on a scale in kilograms (nearest 0.1kg), while height was measured with a stadiometer in meters to the (nearest 0.1cm) with no shoes on and minimal amount of clothing (no heavy jacket or sweaters). Week four consisted of an in-person session where anthropometric measurement was taken to evaluate progress and provide encouragement. Week eight was the final in-person session in which BMI was measured and a final SEE scale questionnaire was given to evaluate the difference from pre-to-post intervention.
The iPhone/Android GPS pedometer app automatically collects the number of steps taken in a given time period. This data was communicated to the principal investigator on a weekly basis using a pre-assigned subject code to protect anonymity. In addition, the subject’s baseline BMI and ending BMI as calculated by the BMI calculator app was transmitted to the principal investigator as the project commenced and ended, respectively. A data collection form was used for recording this weekly data and subsequent data analysis.
The weekly step data collected by the GPS pedometer app was averaged over an 8 week data collection period and comparisons with subject age and baseline BMI and post-intervention BMI was performed to determine if adult obese patients in primary care who have a BMI greater than 25kg/meter square and that use a pedometer, experience greater weight loss results. A pre and post design was used to evaluate the efficacy of the intervention using an activity monitor for an 8-week period in combination with other treatment protocols in reducing body mass index levels.
With the help of the IBM SPSS statistics 26, a paired samples t test will be done after the pedometer-based walking intervention to evaluate if the decrease in BMI was associated with the activity monitor as a weight loss measure. Positive feedback and encouragement on a weekly basis was used throughout the 8 week intervention period to enhance self-efficacy. This weight management intervention is based on the best current guidance from health care experts in the field of obesity and the relevant literature in this area is reviewed below. Literature Review There has been a growing body of scholarship directed at better understanding the connection between mental health and obesity. One of the more challenging aspects of treating obesity in mental health contexts that has emerged from the research to date concerns the precise etiology of the condition. As noted above, although there is an inextricable relationship between mental health disorders and obesity, it remains unclear what role each factor plays in exacerbating weight gain in this population. For example, according to Ashley (2015), “Adverse side effects of the medications used to treat the symptoms of psychoses often include sedation and decreased metabolism, leading to rapid weight gain” (p. 4).
The research to date also indicates that obesity is closely associated with various types of mood disorders. For instance, community-based surveys conducted throughout North America have identified associations between depressive symptoms and obesity, as well as other types of psychological distress which fall under the umbrella of mental disorders (Simon, Von Korff & Saunders, 2009). The mental health disorders that are associated with obesity are far more pronounced among American women than men, though, as well as a stronger relationship between depression and obesity among individuals aged 65 years and younger (Simon et al., 2009). Likewise, community survey data beginning in the 1950s indicates that there is also a stronger relationship between depression and obesity among individuals in higher socioeconomic brackets (Simon et al., 2009).
The foregoing findings were identified primarily in North American Caucasian samples, and may not be completely generalizable to other ethnic or cultural groups, but other types of studies have also identified a relationship between obesity and mental health disorders that are universally applicable. For instance, cross-cultural longitudinal studies have determined that mental disorders such as depression serve to predict the eventual onset of obesity and that obesity also predicts the eventual onset of depression in the aforementioned iterative cycle. Longitudinal studies have also determined that the extent to which obesity is successfully managed and weight is lost is the extent to which the severity and frequency of corresponding mental disorders are diminished (Simon et al., 2009). In addition, the results of a study by Camden (2009) found that, “Although differences in obesity rates exist among certain groups, research indicates that some degree of increase has occurred among all groups regardless of age, gender, ethnicity, socioeconomic status, or race” (p. 38). In sum, virtually any type of evidence-based nursing intervention that is designed to help patients lose weight and keep it off can be regarded as efficacious for patients in any treatment setting provided that the unique challenges that are involved are taken into account in its implementation and administration.
It is important to note, though, that the increased sedentary lifestyle and a decreased metabolic rate that are associated with psychotropic drugs can both result in unwanted weight gain to the point of obesity and even extreme obesity, meaning that even under the best of circumstances people who suffer from mental disorders may also develop obesity as a result of the medications that are used to treat the condition in the first place. In other words, the side effects from these medications are a vicious spiraling cycle where people gain weight which worsens their mental health condition which will require additional medications with corresponding adverse side effects (Ashley, 2015).
Not surprisingly, obesity has been consistently demonstrated to be particularly problematic for individuals who are already suffering from various mental illnesses (Bacon & Farnworth, 2012). In fact, the weight gain that is caused by psychotropic medications is typically inordinately rapid, and this type of weight gained over a short time can result in a host of health care issues besides mental health disorders, including stroke, heart disease, diabetes and even death (Bacon & Farnworth, 2012). Any or all of these conditions can accentuate mental health disorders.
In many cases, the weight gained in this fashion also causes diminished self esteem and dissatisfaction with body image which can also exacerbate eating disorders that are associated with psychotropic medications. In addition, Bacon and Farnworth (2012) stress that obesity in mental health care settings introduces a number of constraints to physical activity that further intensify the problems that are associated with rehabilitation, including daily activities such as toileting, dressing, ambulating and socializing. Nonadherence with medication regimens has also been cited as a problem when treating obesity in mental health care settings (Bacon & Farnworth, 2012).
The foregoing constraints to physical fitness in mental health care settings reinforce the need for additional physical activity by this population. As Brill and Cooper (1993) noted early on, “Researchers have shown that regular physical activity and exercise are important factors in the promotion of good health in adults and are effective means of preventing hypertension, obesity, and diabetes” (p. 45). The intervention that was developed for this analysis was based on current physical activity guidelines that recommend that adults take part in at least 30 minutes of moderate intensity physical activity each day as well as 20 or more minutes of vigorous intensity physical activity three to four times each week to achieve optimal mental health and physical fitness outcomes (Bacon & Farnworth, 2012).
While additional research in this area is still needed, the studies to date concerning mental health interventions for institutionalized individuals have consistently identified unbalanced allocations of time allocated each day, with the majority of daily activities being devoted to passive leisure pastimes or personal care. Indeed, one study that employed daily time-use diaries of patients in an inpatient mental health care setting found that an inordinate amount of time was used for leisure activities, personal care and other occupations with just 2% being devoted to physical activities (Bacon & Farnworth, 2012).
Certainly, part of this problem relates to the need to ensure the safety of patients and staff in mental health settings and the overcrowded conditions that frequently characterize mental health care facilities in the United States, but it is apparent that even modest increases in physical fitness activities each day could contribute to mental and physical health in a number of ways. In addition, interventions for obesity and overweight patients can facilitate their care by nursing staff. For example, Camden (2009) emphasizes that there are a number of nursing challenges associated with caring for obese and overweight patients in any practice setting. Indeed, Camden (2009) concludes that, “The challenges of caring for larger, heavier patients arise in all healthcare settings. When an obese patient needs nursing care, physical size can complicate even the most basic interventions, regardless of the practice setting” (p. 37).
Based on the foregoing findings, this study will be guided by the conceptual framework that is described below. Theory or Conceptual Framework The conceptual framework for this analysis will be novel but it draws on the work by Dalen, Brody, Staples et al. (2015). While current evidence-based interventions for weight management typically include a physical activities component, these traditional interventions may be less effective in a mental health treatment setting due to the above-described constraints and daily time allocations for patients. Therefore, ensuring that individuals undergoing mental health treatments engage in the recommended daily physical activities requires a significant change in current clinical protocols which invariably involves some expenditure of scarce organizational resources.
Consequently, it is vitally important to ensure that an appropriate conceptual framework that takes into account the unique challenges that are associated with treating obesity among the population of interest is used to guide the process. In this regard, Dalen, Brody, Staples et al. (2015) report that:
One area of research that has received little attention in treatment development efforts is the influence of psychological factors [which] play a prominent role in obesity and eating behavior and in the development and maintenance of metabolic syndrome. Indeed, the widespread prevalence of psychological distress in obesity populations is thought to be a key factor in the inability to maintain behavior change over time. (p. 578)
Furthermore, the psychological distress that is linked to obesity results in higher levels of anxiety, poor body image, low self esteem and depression (Ashley, 2015). Therefore, the conceptual framework for this analysis takes into account the mutual effects of obesity on mental health disorders and vice versa.
Discussion Implications for Optimized Care Achieving optimal health care outcomes with obese patients who are suffering from mental health disorders demands the use of evidence-based interventions that can address the full range of factors that are involved. Both obesity and mental disorders are widely recognized as being complex conditions that can adversely affect quality of life, daily functioning, and individual safety. Consequently, the population of interest is at especially high levels of risk for social stigma, health care complications, and premature mortality which combine to exacerbate mental health disorders and individual well-being (Ashley, 2015).

Implications for Advanced Practice Registered Nursing Because advanced practice registered nurses are on the front lines of delivering patient care as well as serving in various leadership, research and educational capacities (McNeal, 2010), the potential implications of the findings that emerge from this study are far-reaching and significant for health care consumers suffering from various mental disorders and/or corresponding unintentional weight gain. In addition, this intervention also has the potential to facilitate and improve nursing care while simultaneously reducing the costs of the health burden for the targeted population of 20 to 55-year-old overweight/obese adult patients by helping them lose weight and keep it off. Since obesity and overweight are closely associated with the incidence and prevalence of mental disorders, these benefits outcomes can also help reduce and event prevent future inpatient stays.

Limitations The primary limitation involved in this analysis concerns the limited number of subjects that will be available to participate in this voluntary health care initiative. A secondary limitation relates to the potential for researcher bias to influence the selection of studies for inclusion in the literature review in support of this intervention as well as how this information is interpreted and interpolated into the final analysis. Despite these limitations, the novel intervention is based on the current recommendations from national health care organizations concerning minimum individual daily physical activity needs.