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Genomics, Nutrition, Obesity, and Diabetes

Posted on: Sunday, 26 March 2006, 03:03 CST

By Johnson, Rolanda L; Williams, Scott M; Spruill, Ida J

Purpose: To present evidence of genetic and environmental interactions as they relate to nutrition, diabetes, and obesity.

Methods: A review of seminal literature related to genetics, obesity, and diabetes.

Findings: Multifactorial interactions are important in the development of nutrition-related disorders, but the challenge remains to explain how these interactions are expressed. Treating subpopulations of people might be important and useful to some extent at present, but in the future treating people of given genetic predispositions and other personal and environmental factors will have greater effects on quality-of-life indicators and life expectancies.

Conclusions: Individualization coupled with multifactorial interactions will lead to new and more effective preventive and treatment modalities of nutrition-related disorders. With obesity and diabetes, genomics will bridge the traditional use of diet, exercise, and weight reduction with other environmental factors, ultimately leading to healthier lives.

JOURNAL OF NURSING SCHOLARSHIP, 2006; 38:1, 11-18. 2006 SIGMA THETA TAU INTERNATIONAL.

[Key words: genetics, obesity, diabetes, nutrition]

For the past decade, the incidence of obesity and diabetes has been increasing for all age groups in the United States (US) and many other countries. Obesity is often defined by body mass index (BMI), which is a measure of body fat based on height and weight. An ideal BMI ranges from 18.5 kg/m^sup 2^ to 24.9 kg/m^sup 2^. Overweight status is defined as 25 kg/m^sup 2^ to 29.9 kg/m^sup 2^ and obesity as a BMI of 30 kg/m^sup 2^ or greater. Although some differences have been reported in rates of obesity and diabetes across ethnic groups, the incidence of these disorders remains high and continues to rise in all racial groups. According to the Centers for Disease Control and Prevention (CDC; 2002), diabetes prevalence rose from 2.77 per 100 people to 7.9 per 100 from 1980 to 2001. The majority of these cases were type 2 Diabetes (T2D). The negative consequences of long-term disease include major complications such as heart disease, blindness, amputation, kidney failure, and even death.

For some time, emphasis has been on lifestyle changes as a way to decrease the incidence of disease. Although lifestyle has been documented as a cause of obesity and diabetes, it is not the only causative factor related to these diseases; genetic predisposition likely is important, and the sequencing of the human genome will allow the assessment of genetic influence on a person's health.

Since the sequencing of the human genome, researchers and geneticists have begun to document the interactions among genetic and environmental risks as precursors to chronic illnesses, including the influence of gene-diet interactions in disorders such as obesity and diabetes. For many years, researchers have been investigating what accounts for individual, ethnic, and racial variation in the prevalence of obesity and diabetes. The focus will now shift to studying how genotype can be used to understand the disease process and improve health. The aim of this article is to present the evidence of genetic and environmental interactions, especially as it relates to nutrition, diabetes, and obesity. In addition, ethical, legal, and social issues will be explored.

Obesity

Genomics and Pathophysiology

For many years, obesity has been attributed to an energy imbalance in which energy intake exceeds energy expenditure. Positive energy balance, or a state in which energy intake surpasses energy expenditure, results in increased fat stores in the body. Decreased fat stores results from energy expenditure that is greater than energy intake (Bandini & Flynn, 2003). Accumulation of fat stores has been explained by several factors pertaining to excess fat deposits, adipose tissue secretion of hormones, macrophages of the adipose tissue, and free fatty acids (Roth, Qiang, Marban, Redelt, & Lowell, 2004). In the human body, adipose tissue is the sole secretor of leptin, adiponectih, and resistin. Adiponectin secretion is believed to directly affect the development of "good fat." Leptin hormone is believed to act on the brain and to regulate food intake (Wauters et al., 2001).

Direct relationships exist between leptin levels, body mass index, and fat mass (Wauters, Considine, & Van Gaal, 2000). The regulation of appetite is attributed to leptin. Leptin enters into the central nervous system and, along with insulin, is produced in the body as a function of body fat percentage. Both molecules signal the brain to reduce food intake (Porte, Baskin, & Schwartz, 2002). Adiponectin increases sensitivity to insulin and the disposal of glucose while resistin increases resistance to insulin (Roth et al., 2004). Plasma free fatty acids are catalysts for the regulation of basal insulin secretion as well as insulin sensitivity. Elevated levels of free fatty acids decrease the effect of insulin by interfering with metabolism in the muscle and liver, thus contributing to obesity.

Patterns of gene expression in obesity have been linked to the sites where excess fat is stored in the human body. Most of the body's fat is concentrated subcutaneously, but a small yet significant amount is distributed in abdominal adipose tissue. The location of these fats determines the variations of body shapes. Upper-body fat is a precursor to several chronic illnesses such as diabetes and cardiovascular disease. Recent research findings support the hypothesis that abdominal fat deposits are closely related to metabolic complications of obesity. This hypothesis is complicated, however, by the debate over the defining characteristics of the visceral adipose tissue. Of primary concern is identifying the best method to measure the visceral adipose tissue and, second, determining which areas of abdominal visceral adipose tissue to measure. Clarifying these concerns will lead to better determination of obesity-related complications (Fried & Ross, 2004).

The control of body weight involves a complex set of factors that ultimately regulates the balance between energy intake and energy expenditure. Genes with putative roles in several processes that ultimately affect this balance have been identified, usually from animal-model studies. For example, leptin (LEP), leptin receptor (LEPR), melanocortin 4 receptor (MC4R), pro-opiomlenocortin (POMC), and other genes have been hypothesized to affect energy intake, while energy expenditure can be affected by uncoupling protein genes (UCPl, UCP2, UCP3) as well as many others (Marti, Moreno-Aliaga, Hebebrand, & Martinez, 2004). Nevertheless, numerous "obesity gene" candidates warrant consideration of the genetic predisposition to this phenotype or the outward expression of the gene based on strong, if not compelling, preliminary evidence.

Although the overall genetic contribution to BMI and related phenotypic variation has been shown to be quite high (the heritable proportion of variation of several obesity related phenotypes has been estimated to range from 40-70%; Comuzzie & Allison, 1998), evaluating the contribution of any single gene to human obesity has been difficult, with the exception of specific mutations with very low frequency in the population and do not account for the majority of cases (Snyder et al., 2004). In contrast, in animal studies, single loci can be shown to have significant effects on obesity. For example, as of 2003, at least 10 naturally occurring polymorphisms in mouse genes with defined homologues to human genes were shown to have an effect on rodent obesity. Studies of these candidates and over 80 other genes have shown an association with obesity in at least one study, but as with most other complex phenotypes, associations often are not replicated across studies (Hirschhorn, Lohmueller, Byrne, & Hirschhorn, 2002; Williams et al., 2004). As of 2003, over 400 genes had been directly or indirectly associated with human obesity (Snyder et al., 2004). The large number might indicate the importance of maintaining correct energy balance for survival or the inability to pinpoint important genetic factors. Clearly, much work remains to be done to gain knowledge of how genes affect human energy balance and the distribution of adiposity.

This inability to provide simple genetic answers to people with an obese phenotype is not unusual among common diseases, but it shows the influence that multiple factors can have on clinical endpoints. These factors include the interactions among many genes (Williams, Haines, & Moore, 2004). Extensive evidence indicates that environmental factors are important, not the least of which is the dramatic rise in prevalence of obesity in the last few decades (Hill, Wyatt, Reed, Peters, 2003; Reilly, 2003). Yet, evidence indicates that, although factors in the overall environment promote the increased prevalence of obesity, dietary and other lifestyle changes do not affect all people equally (Marti et al., 2004; Perusse & Bouchard, 1999, 2000). Rather, people of different genotypes might respond to environmental changes quite differently. In the Figure, three hypothetical genotypes are combined with three environments to yield nine different phenotypes. In this case, the phenotype is shown as BMI but it could be any phenotype. An importan\t point is that genetic variation interacts in a complex way with environments. For example, genotype 1 could produce either the smallest or the largest BMI, depending on the environment. Similarly, environment 3 can produce a high BMI (with genotype 3) or a low BMI (with genotype 1).

Figure. Interactions between genetics and environment in complex disease such as obesitv.

As an example, the effect of variable fatty acid dietary intake varies by a leptin genotype (Nieters, Becker, & Linseisen, 2002). Another example is a genotype in the β3 adrenoreceptor gene that increases risk of obesity relative to other genotypes, given a sedentary lifestyle (Marti, Corbalan, Martinez-Gonzales, & Martinez, 2002). These findings exemplify the general rule that in obesity (as well as other similar phenotypes) genes act as a function of their environments and that environmental variation is different in different genotypes (Perusse & Bouchard, 1999, 2000).

Nutritional Influences and Nutrigenomics

The primary nutritional issue related to obesity is the imbalance between energy expenditure and energy intake. Simply stated, obesity results from more caloric intake than expenditure. The primary goal of many people is to lose weight. The literature indicates some basic steps in weight reduction: (a) reduce consumption of saturated fat, trans-fatty acids, and cholesterol; (b) consume low-fat diets consisting of less than 30% total fat calories; (c) consume low- calorie, high fiber, and high-nutrient foods, including proteins that are low in total and saturated fatty acids; (d) balance caloric consumption and physical activity to prevent obesity; (e) develop eating patterns consistent with lifestyle, including foods from the essential food groups to include balanced levels of protein, vitamins, minerals, and fiber; (f) consume a diet in which 55% or more of the caloric intake is from vegetables, fruits, and whole grains; and (g) limit alcohol consumption to a moderate amount (two drinks or 1 to 2 ounces per day; Arden et al., 2004; Krauss et al., 2000; Miller, 2005). Although culture and lifestyle accounts for approximately 30% of the variation in BMI, genetics accounts for 40% to 70% (Marti et al., 2004). These percentages indicate the need to focus on multifactorial interactions. Moreover, the above strategies for weight control must be considered and implemented within the context of a person's culture. All of these factors influence dietary choices and regimens.

Despite the need for general dietary recommendations, current research findings show the effects of nutrigenomics, which is the study of the interaction between nutritional intake and genetic variation, or gene-diet interactions. Individual genetic responses to nutrient intake influence how the body reacts to specified nutrients or toxins within the body. Advances in nutrigenomics allow for the identification of individual variations or responses to common obesity interventions such as low-fat and low-cholesterol diets that can be attributed to individual genotypes, while confirming that implementing single dietary changes might not sufficiently treat or prevent obesity. For example, genetic and familial propensities to obesity coupled with diets higher in fat will most likely result in higher BMI, which further confirms the multifactorial interaction component of obesity. Similarly, research findings have begun to show that dietary supplements can compensate for genetic polymorphisms to enhance overall health status. Although data show the importance of gene-diet interactions, new discoveries in practice and research are needed (Eckel, 2005; One Person Health, 2005; Perusse & Bouchard, 2000). In essence, "The right diet needs to be matched with the right person" (Eckel, 2005, p. 97) in order to yield the greatest effect. Moreover, the "right diet" must be defined in the context of individual genotype.

Nursing Implications

The nursing implications, though appearing simple, are immense. For many years the focus on weight reduction via diet and exercise has been the primary mode of obesity treatment. A recent trend in obesity treatment now includes surgical procedures. With advances in genetics and nutrition research, nursing interventions and treatment modalities should become more individualized. Meticulous assessments are needed to monitor the effectiveness of treatments. Furthermore, exploration of obesity-associated risk factors, nutrition, and other treatments is needed. The examination of genetic susceptibility is necessary for prescribing appropriate treatment modalities. Nurses will need to assess genetic susceptibility as they delineate these complex relationships, ultimately leading to more effective obesity treatment.

Diabetes

Genomics and Pathophysiology

Diabetes is a medical disorder characterized by high levels of blood glucose resulting from defects in insulin secretion, insulin action, or insulin production by the beta cells in the pancreas. When insulin production is insufficient, cells become insulin resistant or respond poorly to the effects of insulin, and glucose is not metabolized properly, nor stored appropriately in the liver and muscles. The net effect is persistent high levels of blood glucose, poor protein synthesis, and other metablic abnormalities (Votey, 2004).

Type 1 diabetes (TlD). TlD generally occurs in young, lean patients and is characterized by the marked inability of the pancreas to secrete insulin because of autoimmune destruction of the beta cells. Approximately 5% to 10% of all American cases of diabetes are TlD. The distinguishing characteristic of a patient with TlD is that these patients are dependent on exogenous insulin. TlD is more commonly diagnosed in children and adolescents, but it can occur in adults as well. The autoimmune attack might be triggered by a reaction to an infection, such as one of the viruses of the Coxsackie virus family. Experimental transplantation of beta cells is being investigated in several research programs and it might be clinically available in the future (Scobie, 2002).

Type 2 diabetes (T2D). T2D typically occurs in people older than 40 years with a family history of diabetes. Although it is increasingly being diagnosed in children and adolescents, approximately 90% of patients in whom diabetes has been diagnosed have this type. In general T2D is associated with older age, obesity, family history of diabetes, prior history of gestational diabetes, impaired glucose tolerance (IGT), physical inactivity, impaired glucose fasting (IGF), and race or ethnicity (World Health Organization, 2004). The disease might also be caused by other conditions such as hemochromatosis, polycystic ovary syndrome, and certain types of steroids. African American, Hispanic/Latino American, Native American, and some Asian American people are at particularly high risk for T2D.

Type 2 diabetes is initially treated by changes in diet and through weight loss, which can restore insulin sensitivity even when the weight lost is modest (e.g., 10 to 15 lbs). When undetected for years, severe complications can result, including renal disease and ultimately failure. Although researchers know that a risk for type 2 diabetes can be inherited, researchers have had difficulties identifying specific causative gene mutations. Some of the problems might include the number of genes controlling fuel intake and fuel regulation, and their relationship to environmental influences such as personal lifestyle. For example, if two people have the same mutation but different outcomes, researchers have a difficult time distinguishing which gene is important in the development of T2D when combined with a lifestyle with certain eating or exercise behaviors. An example of this phenomenon is the Beta3-adrenergic receptor gene. The Beta3-adrenergic receptor gene makes a protein in fat cells that is involved in determining how much fuel the body burns when a person is resting. A mutation in this gene slows down fat metabolism, enhancing the tendency for obesity. One specific mutation in the Beta3 gene is called TRP64ARG. The TRP64ARG mutation causes the Beta3-adrenegic receptor gene to make an altered protein. People with two copies of this mutation tend to develop T2D at an earlier age. This genotype is most common in Pima Indian, African American, and Mexican American people (Adams, 2000).

Other types of diabetes. Gestational diabetes (GD) is defined as any degree of glucose intolerance with onset or first recognition during pregnancy. Gestational diabetes occurs more frequently among African American, Hispanic/Latino American, and Native American people, obese women, and women with a family history of diabetes. Approximately, 20% to 50% of these women go on to develop T2D (Votey, 2004).

Other types of diabetes, previously called "secondary diabetes," are caused by other illnesses or medications. Depending on the primary process (e.g., destruction of pancreatic beta cells or development of peripheral insulin resistance), these types of diabetes are more similar to type 1 or type 2 diabetes. The most common are diseases of the pancreas that destroy the pancreatic beta cells (e.g., hemochromatosis hormonal syndromes); that cause peripheral insulin resistance (e.g., acromegaly, Gushing syndrome); and drug-induced diabetes. All other specific forms of diabetes, accounting for up to 5% of all diagnosed cases of diabetes, are termed type 3 and are known as genetic defects in beta cells, genetic defects in insulin action, genetically related insulin resistance, disease of the exocrine pancreas, chemicals-induced diabetes, or endocrinopathies (American Diabetes Association, 2005). Maturity-onset diabetes of the young (MODY) is a form of T2D that affects many generations in the same family with onset in people under 25 years of age.

Risk Factors

The American Diabetes Association (ADA) lists the following as risk facto\rs for T2D: (a) age over 45 years; (b) BMI over 25 kg/ m2; (c) family history of diabetes; (d) habitual physical inactivity; (e) race or ethnicity, including African American, Hispanics American, Native American, Asian American, Pacific Islander; (f) previously identified impaired fasting glucose (IFG), impaired glucose tolerance (IGT); (g) history of gestational diabetes, or delivery of a baby weighing more than 9 pounds; (h) blood pressure above 140/90 in adults; (i) HDL cholesterol above 35 mg/dl or triglyceride level above 250 mg/dl; (j) polycystic ovary syndrome; and (k) history of vascular disease (American Diabetes Association, 2005).

Diabetes screening is recommended for adults beginning at age 40 and every 3 years thereafter. Earlier screening is recommended for those with risk factors such as obesity, family history of diabetes, and high-risk ethnicity populations. Screening can vary according to circumstances and might be a routine glucose screening or an oral glucose tolerance test. Of primary genetic importance is a family predisposition to diabetes and the person's genotype.

Genetic Mutations

As with obesity, the etiology of diabetes is based on multiple risk factors, both environmental and genetic. Because of its increasing importance to public health, T2D is the focus of this discussion. Several environmental risk factors might be responsible for T2D, including an increasingly sedentary lifestyle, high-fat, high-carbohydrate, or high-calorie diets. Given the fact that obesity is highly heritable (genetic), even this environmental risk factor for diabetes has a genetic component. Although the prevalence of T2D is increasing worldwide, the greatest increases are in non- European populations (Zimmet, Alberti, & Shaw, 2001). For example, studies of Native Americans have indicated the potential for environmental change to significantly affect the prevalence of disease.

The increase of disease prevalence is associated with changing lifestyle, but the increases are not uniform across populations, possibly indicating underlying genetic differences and health inequalities across populations. Overall, the evidence for genetic involvement is compelling, with the risk to affected siblings being 4 to 6 times the risk in the general population (Florez, Hirschhorn, & Altshuler, 2003). Although shared environments can possibly account for increased risk to siblings, environment alone does not increase risk, as studies of twins have shown. As with most other complex phenotypes, specifying genetic variants that increase diabetes risk has been much more difficult than determining a substantial genetic component.

Studies of genetic factors T2D abound, but very few findings are replicated consistently. Family-based linkage analyses have shown many possible disease loci, but only a few loci have been repeated. One such consistent linkage peak is on the long arm of chromosome 20 that has been found in West African, Finnish, American Caucasian, French, Chinese, and Japanese populations (Ghosh et al., 1999; Ji et al., 1997; Luo et al., 2001; Mori et al., 2002; Rotimi et al., 2004; Zouali et al., 1997).

In one case, an interaction between linkage peaks was found. The interaction appeared to be between loci on chromosomes 2 and 15. These linkages led to the identification of calpain 10 as a diabetes- candidate gene on chromosome 2 (Cox et al., 1999). The gene on chromosome 15 has not yet been identified, and the calpain 10 finding has not been universally replicated (Florez et al., 2003), although the lack of replication might be the result of interactions with other genes or environmental factors that differ across the study populations.

In addition to studies based on linkage, many studies with a candidate-gene approach have been published. Florez et al. (2003) listed the few findings that meet the most stringent criteria: three or more studies each with p values below .05, two studies with p values both below .01, or one study replicating a previous finding with p<.001. Only six genes meet these criteria. Two of the most reproduced are peroxisome proliferator-activated γ (PARγ) and potassium inward rectifier channel (K^sub ir^6.2 KCNJ11), and both are targets for antidiabetic medications, although the mechanism leading to disease is not clear. The underlying genetic basis of T2D is not completely resolved; however, genetic susceptibility combined with certain environmental factors increases a person's propensity to T2D (National Human Genome Research Institute [NHGRI]), 2004; O'Rahilly, Barroso, Sc Wareham, 2005).

Nutritional Management

Nutrition is an integral component of diabetes self-management. The ADA (2005) recommends that nutritional therapy be individualized with consideration given to a person's usual food and eating habits, metabolic profile, treatment goal, and desired outcomes. Yet many misconceptions continue to exist concerning nutrition and diabetes, such as a diabetic diet, food pyramid, and sugar-free diets. The best available evidence must still take into account individual circumstances and cultural and ethnic preferences. The goals of nutrition therapy that apply to all people with diabetes should include (a) maintenance of optimal metabolic outcomes; (b) prevention and treatment of the chronic complications of diabetes; (c) modification of nutritional intake and lifestyle as appropriate for preventing and treating obesity, dyslipidemia, cardiovascular disease, hypertension, and nephropathy; (d) improvement of health through healthy food choices and physical activity; and (e) attention to individual nutritional needs, including personal and cultural preferences and lifestyle.

Nursing Implications

Healthcare providers should adopt the patient-empowerment model and learn to accept patients as partners in setting goals to improve their health outcomes. As society continues to age, the incidence of diabetes will continue to soar. Providers must step out of personal comfort zones and traditional models of care, which often includes making the decisions and telling patients what to do. Nurses must assess and treat patients as individuals, and make patients stakeholders in their own health care. Enough evidence now exists to indicate that T2D can be prevented or delayed (Diabetes Control and Complications Trial, 1993). New models of care and interventions to identify people at risk for developing diabetes should be designed. These models must incorporate individual and familial genetic suceptibility factors. Moreover, nurses should identify creative ways to implement these programs at nontraditional sites such as the workplace, schools, social clubs, and grocery stores. Individualized meal plans should replace traditional diabetic diets. Diabetes treatment, management, and prevention necessitate a multidisciplinary, multifaceted approach (Patlak, 2002).

Nutrition Supplements and Genetics

In addition to a diet with the appropriate amounts of proteins, fats, and carbohydrates, the ingestion of vitamins and minerals or micronutrients is also important. However, the general public is inundated with messages to ingest vitamins and minerals, and overconsumption of these supplements might occasionally occur. Contributing to the possible overconsumption of micronutrients is the differential response of individuals to these micronutrients. Some of these sensitivities can be attributed to genetic predisposition. For example, an autosomal recessive disease of copper storage, Wilson disease, promotes the storage of copper in the liver, brain, and cornea, and people with 6-phosphate dehydrogenase deficiency have an increased sensitivity to vitamin C. Although tolerable upper-intake levels (UL) have been established to minimize the risk of ingesting excessively high levels of vitamins and minerals, healthcare providers must consider all of the possible ramifications related to people with nutritional disorders.

Natural homeostatic processes are designed to balance the standing level of vitamins and minerals within the body. But what happens in people who have complications because of obesity and diabetes? How they will respond to UL is uncertain. Caution must be used to evaluate them and their bodies' responses to established daily recommended doses of vitamins and minerals. Moreover, how genotypes should be weighted when determining the influences of consumption of vitamins and minerals is unclear. More research is needed to determine the effects and coexisting relationships between genetics and nutritional supplements.

Genomic Applications in Practice

Genetic testing and counseling. The etiology of diseases such as obesity and T2D and the underlying genetic risk factors that predispose people to these phenotypes are inherently complex and diverse. Such complexity makes the possibility of a simple genetic test remote. Rather, scientists and clinicians are in a stage of understanding the genetic basis of complex genetic diseases, based on observations about shared phenotypes in families, and becoming aware of the overall level of genetic risk, not the genetic risk imposed by any single factor. For example, virtually all children of two obese parents are obese (Reilly, 2003). However, one cannot be confident of any particular genetic (allelic or genotypic) risks with the exception of those extremely rare cases of single genes that cause obesity. Therefore, the important factor now is counseling people on the basis of empirical data by relating risk as a function of the pattern of disease in families. Such empiric risk- recurrence data are based on data from many families in which the number of affected family members and degree of relatedness are known. Based on these data, one can estimate the possibility of another family member developing the disease.

These estimates come with many caveats (Nussbaum, Mclnnes, & Willard, 2004). One is that the numbers are an average acr\oss families with presumably heterogeneous causes of disease, making the application to any single person tenuous. Also, as environmental risks change, the underlying genetic risk factors might also change (Figure); hence, historical data might not indicate current risk status. Therefore, although counseling can be given, it must be done with great caution.

Ethical considerations. Some fundamental ethical issues should be considered in the management of genetics, obesity, and diabetes. One issue aside from genetics is that of discrimination. Protocols must be established and maintained to prevent discrimination during genetic testing. One fear is the use of genetic information while potentially violating the ethical rights of individuals. Throughout all phases of testing and treatment, adherence to ethical principles is important (Saraivaetal., 2001).

With the discovery of new genetic information and translation into practice, an overriding question is who will benefit from the knowledge. Subpopulations of people with high incidences of obesity and diabetes might not have full access to the benefit that can be derived from this new knowledge. The ethical quandary is how the populations that will benefit the most from the new discoveries will receive the information. With the never-ending discussion of cost, who will be responsible for genetics testing, evaluation, and treatment? If, as in so many other cases, the "needy" subpopulations do not benefit from these discoveries, then knowledge might appear to be gained for the sake of knowledge or for a few instead of the masses who are plagued with obesity and diabetes. Perhaps an overriding benefit still not adequately known in the general population is that this information can be used to prevent disease. Prevention is a cost-effective approach to chronic disease, and one that can reduce the nation's healthcare cost. Such overall control costs might allow more people to benefit from new knowledge (clayton, 2003).

National Health Policy Resources

Several national organizations and policies have been established in response to the mandate to action in the areas of obesity and diabetes. In August 2004, a Strategic Plan for NIH Obesity Research was presented. Four goals were outlined to prevent and treat obesity via (a) lifestyle modification; (b) pharmacologie, surgical, or medical procedures; (c) establishing relationships to other health disorders; and (d) emphasizing multidisciplinary training and research along with meeting the needs of specific populations (U.S. Department of Health of Human Service [U.S. DHHS], 2004). Healthier US, an initiative of the U.S. DHHS, set the stage for the country's health agenda to live healthier lives regardless of age, socioeconomic status, and fitness abilities. In other words people should live their "healthiest best" (Johnson, 2005). To this end, over $35 million dollars have been designated for health promotion and disease prevention programs. National associations like the National Obesity Association and the American Heart Association have established platforms with one central message: that an epidemic of obesity and diabetes exists, not only in the United States, but also internationally, and that only serious interventions can prevent catastrophic results.

Researchers must continue to explore genetic predisposition and the interactions between genes and environmental factors. Genomics should allow the creation of a new concept of the individual for diagnosis and treatment. Although treating subpopulations of people is important and useful, treating people of given genetic predispositions and other personal and environmental factors (i.e., individualized care and treatment) will be better. Nurses must ultimately recognize the heterogeneity among individuals. With obesity and diabetes, prevention is preferred and traditional use of diet, exercise, and weight reduction are important, but the use of genomic data will be routine in the not too distant future. Such data will permit healthcare providers to design better treatment and prevention plans for healthier lives.

Conclusions

Worldwide incidence of obesity and diabetes continue to increase and abating this epidemic requires deliberate action. Currently the genetics of obesity or diabetes cannot be linked to any single gene. Probably several genes contribute to these disorders, and future research will help to delineate them. However, the study of the roles of the identified genes in multifactorial interactions will be necessary. Explaining the interactions of the environment, genes, and other factors will yield the most important data on the nutrition related disorders. Given the current state of the science of nutritional disorders, nurses must initiate multifactorial plans of care. Balancing consumption and energy expenditure are necessary for reducing the prevalence of these diseases, but genetic predispositions cannot be overlooked because they affect how this balance can be achieved for each person, and how each person can achieve the best possible quality of life.

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Rolanda L. Johnson, RN, MSN, PhD, lota, Assistant Professor, School of Nursing; Scott M. Williams, PhD, Associate Professor, Division of Cardiovascular Medicine, Department of Medicine and Center for Human Genetics Research; both at Vanderbilt University, Nashville, TN; Ida J. Spruill, RN, MSN, LSW, Doctoral Student, School of Nursing, Hampton University, Hampton, VA. Correspondences to Dr. Johnson, Vanderbilt University School of Nursing, Godchaux Hall, Nashville, TN 37240. E-mail: rolanda.johnson@vanderbilt.edu or rolanda.johnson@vanderbilt.edu.fx4243vz

Accepted for publication June 20, 2005.

Copyright Sigma Theta Tau International, Inc., Honor Society of Nursing First Quarter 2006

Source: Journal of Nursing Scholarship

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