Overview: Nutritional Health in the Older Person
As a population, older adults are more likely than younger ones to be afflicted with a variety of age-related diseases and functional impairments that may interfere with the maintenance of good nutritional status. Members of this population are also at increased risk of drug-induced nutritional deficiencies due to the number of prescription drugs they take. As a result of these potential risks of malnutrition, the Department of Health and Human Services has identified nutrition as a priority area in the health goals for the nation in Healthy People 2010 (USDHHS, 2000). Although this overview focuses on older persons, other Medicare beneficiaries, particularly those with end-stage renal disease, also have high rates of nutritional disorders.
When considering the importance of nutrition in the health of Medicare beneficiaries, both the primary prevention of malnutrition and the role of nutrition in the management of health conditions prevalent in this population (secondary prevention) must be considered. Brief overviews of these two issues are presented here, and details are discussed in subsequent sections.
There is no universally accepted clinical definition of malnutrition (Klein et al., 1997). In fact, the term “malnutrition” has been used to refer to a wide range of deficiencies (e.g., protein–energy, vitamins, fiber, water) and excesses (e.g., obesity, hypervitaminosis), which may or may not
be clearly associated with adverse health outcomes (Reuben et al., 1995). The concept of malnutrition among older persons is more complicated because of the many settings along the continuum of care in which the elderly receive care.
community dwelling (including those receiving home care and Programs of All Inclusive Care (PACE),
institutionalized (nursing home) long-term care, and
The burden of acute and chronic disease differs across these settings, and nutritional requirements vary as a result. Moreover, an individual older person may move through many of these settings over the course of a single illness. Some measures of nutritional status vary in their degree of specificity for malnutrition across care settings. For example, changes in serum proteins among hospitalized older persons may be more reflective of inflammation and the acute-phase reaction than of malnutrition per se, whereas such changes may be more likely to indicate protein– energy undernutrition in community-dwelling persons. In addition, nursing home residents may have chronic inflammation, which complicates both the diagnosis and the management of malnutrition. Nevertheless, changes in these traditional indicators frequently have prognostic and clinical meaning and are therefore addressed in this chapter.
The most common nutritional disorder in older persons is obesity. Obesity has been defined variably by different organizations. Based on data from the Second National Health and Nutrition Examination Survey (NHANES II) (1976–1980), the threshold for obesity was defined as having a body mass index (BMI)1 exceeding 27.8 for men and 27.3 for women (NIH, 1985). Today, a BMI of 25 to 29.9 is considered to be overweight and a BMI of greater than or equal to 30 is considered obese (Meisler and St. Jeor, 1996; Mokdad et al., 1999; NHLBI, 1998).
The prevalence of overweight increases with age between the ages of 22 and 55 years but then stabilizes in women and declines in men (Van Itallie, 1985). The percentage of overweight and obese persons in the 65 to
74 year age range remains substantial however. Data from the Third National Health and Nutrition Examination Survey (NHANES III) (1988–1994) indicate that in the 65 to 74 year age range, approximately 34 percent of women and 44 percent of men are considered overweight (BMI 25 to 29.9) and an additional 27 percent of women and 24 percent of men are considered obese (BMI greater than or equal to 30) (NCHS, 1999). Older African-American and poor women have higher rates of obesity.
An important characteristic of adiposity accompanying aging is the distribution of fat, which is more likely to be centrally distributed in older persons. This central obesity is commonly associated with insulin resistance, hypertension, and lipid abnormalities (Schwartz, 1997).
Data on the risks associated with obesity in older persons are less consistent than for those with undernutrition. A substantial body of evidence links overweight to hypertension, dyslipidemia, heart disease, insulin resistance and diabetes, cholelithiasis, respiratory impairment, gout, and osteoarthritis (Pi-Sunyer, 1993). However, the relation between obesity and occurrence rates of specific diseases or overall mortality in persons over 65 years has received limited study. There is some evidence that the obesity-associated relative risk of disease occurrence is less in older than in younger persons. Although some data support the association of obesity and premature mortality in older persons (Calle et al., 1999), this evidence is inconsistent. Several cohort studies have demonstrated that a high BMI does not predict mortality, and, indeed, may even be protective against early death in older persons (Diehr et al., 1998; Fried et al., 1998; Stevens et al., 1998). In addition, overweight has been identified as a protective factor for hip fracture (independent of its relation to bone density) (Greenspan et al., 1994). However, other studies indicate that obesity is related to the development of functional impairment (Galanos et al., 1994; Vita et al., 1998). Thus, perhaps unique to the geriatric population, benefits versus risks of weight reduction should be analyzed on an individual basis. A recent Institute of Medicine report, Weighing the Options: Criteria for Evaluating Weight-Management Programs, reviewed the health benefits of weight loss in obesity (IOM, 1995). For this reason and those addressed above, obesity is not addressed separately, but only as it relates to specific conditions (e.g., hypertension, dyslipidemia, diabetes).
Although energy undernutrition and protein–energy undernutrition are much less common, these disorders have major prognostic importance. Conditions of energy undernutrition include adult marasmus (energy undernutrition), in which normal serum proteins are maintained, and adult kwashiorkor (protein–energy undernutrition).
Protein–energy undernutrition (PEU) is defined as the presence of clinical (physical signs such as wasting, low BMI) and biochemical (albumin or other serum protein) evidence of insufficient intake. The most commonly used threshold to define PEU, albumin less than 3.5 g/dL, was derived in hospitalized patients (Bistrian et al., 1974). More recently, it has also been recognized that this threshold may be too high, even among hospitalized patients (Del Savio et al., 1996). Among outpatients, using the 3.5 g/dL threshold may miss older persons at substantial risk. For example, in the Established Populations for the Epidemiologic Studies of the Elderly (EPESE) cohort, the adjusted relative risk of mortality over 5 years for men who met the traditional criterion (<3.5 g/dL) was 1.9 and for women 3.7. However, that study also noted significantly increased relative risks (1.9 for men and 2.5 for women) among persons with more modest hypoalbuminemia (3.5–3.8 g/dL) (Corti et al., 1994). In the MacArthur Studies of Successful Aging, which enrolled older persons who had little or no functional impairment at the study’s onset, those with albumin levels less than or equal to 3.8 g/dL had an adjusted relative risk of 3-year mortality of 1.8 (Reuben et al., 1999). Moreover, in the general population, few older persons (approximately 1 percent) meet the traditional criterion, whereas approximately 8 percent meet the more liberal criterion of 3.8 g/dL (Reuben et al., 1997). Thus, there is evidence that this threshold is associated with substantial risk and also is prevalent.
Weight loss has commonly been used to define undernutrition. In fact, a history of weight loss from middle to old age may be more important than actual low body weight per se. An analysis of data from the EPESE cohort noted that after exclusion of participants who lost more than 10 percent of their weight after age 50 and adjustment for health status, the higher risk of death associated with low weight was eliminated (Losonczy et al., 1995). Objectively determined weight change has prognostic significance. In one sample of elderly persons admitted to a geriatric rehabilitation unit, weight loss (derived from medical records) predicted whether complications would develop on the unit as well as 1-year mortality (Sullivan et al., 1990, 1991). A Department of Veterans Affairs (VA) study of outpatients defined 4 percent or greater weight loss over 1 year as having the best test characteristics (sensitivity and specificity) in predicting subsequent mortality during a 2-year follow-up period; 28 percent of those with involuntary weight loss died compared to 11 percent of those without weight loss (Wallace et al., 1995). In that study, the annual incidence of involuntary weight loss of 4 percent or more was 13.1 percent. Of note, those with voluntary weight loss had no better prognosis (36 percent had a 2-year mortality) than those who had involuntary weight loss.
The prevalence of undernutrition is considerably higher among hos-
pitalized patients. A VA’s case series defined malnutrition as meeting two of the following four criteria:
weight–height ratio <90 percent of normal,
mid-arm muscle circumference (MAMC) <90 percent of normal,
albumin <3.5 g/dL, and
transferrin <200 mg/dL.
Of the 59 male patients age 65 or older in the study, 61 percent met at least two of these criteria, compared to 28 percent of the 93 younger patients admitted during the same time period (Bienia et al., 1982). Of those who met the criteria for malnutrition, 64 percent experienced infections during their illness (compared to 26 percent of those who were not malnourished), and 28 percent died (compared to 4 percent of those who were not malnourished). More recently, a VA study found that 21 percent of hospitalized older persons consumed less than half of their energy requirements; these patients with poor intake had higher in-hospital and 90-day mortality rates (Sullivan et al., 1999). Numerous studies have associated low serum albumin in hospitalized older persons (measured at various times during the hospitalization) with in-hospital complications, longer hospital stays, more frequent readmissions, in-hospital mortality, and increased mortality at 90 days and at 1 year (Agarwal et al., 1988; Anderson et al., 1984; Burness et al., 1996; Cederholm et al., 1995; D’Erasmo et al., 1997; Ferguson et al., 1993; Friedmann et al., 1997; Harvey et al., 1981; Herrmann et al., 1992; Incalzi et al., 1998; Marinella and Markert, 1998; McClave et al., 1992; Patterson et al., 1992; Sullivan and Walls, 1995; Volkert et al., 1992). When considering mortality, the lower the albumin level, the higher is the risk of death. Using Subjective Global Assessment (see below) as a measure of undernutrition, 40 percent of hospitalized older persons are moderately (24 percent) or severely (16 percent) malnourished; severely malnourished patients are more likely to die within 1 year of hospital discharge (adjusted odds ratio [OR] = 2.83) and to spend time in a nursing home during the year after discharge (adjusted OR = 3.22) (Covinsky et al., 1999). However, as discussed in chapter 4, the relationship between hypoalbuminemia and adverse outcomes may not necessarily be related to nutrition.
Undernutrition in the nursing home is a particularly complex issue because of the burden of chronic disease and medications affecting nutritional status in this population and logistical difficulties in providing adequate food intake, in large part due to staffing issues (Kayser-Jones and Schell, 1997). A review of 14 surveys of nutritional status conducted among chronically institutionalized older persons concluded that only 5 to 18 percent of nursing home residents had energy intakes below their
estimated requirement on the basis of body weight, but up to 30 percent ate less than 0.8 g protein/kg body weight per day; 15 to 60 percent had substandard MAMC, serum albumin, or both (Rudman and Feller, 1989). A Canadian study of one nursing home, which used a rating system that included seven anthropometric measurements, identified severe undernutrition in 18 percent of residents, moderate undernutrition in 27 percent, and mild-to-moderate overnutrition in 18 percent (Keller, 1993). Data from 26 VA nursing homes indicated that 12 percent of residents had body weights less than 80 percent of standard, and 28 percent had albumin levels less than 3.5 g/dL (Abbasi and Rudman, 1993). Several emerging concepts of nutritional disorders of older persons have been identified that fall outside the traditional classifications of malnutrition. Among these have been “failure to thrive” (which carries its own International Classification of Diseases, 9th Revision [ICD-9] code), cachexia, wasting, and sarcopenia. Attempts have been made to apply standardized nomenclature for these syndromes (Roubenoff et al., 1997; Sarkisian and Lachs, 1996), but there has been little validation research supporting these proposed definitions. Nevertheless, these syndromes incorporate constructs such as cytokine production, immune defense, and functional status. Thus, they expand the traditional concepts of nutrition to include pathophysiologic pathways and physiologic and functional outcomes. These are described in greater detail in chapter 4.
PREVALENCE OF NUTRITION RELATED CONDITIONS
Nutrition therapy may be a key element in managing many of the most common and important disorders of older persons including hypertension, congestive heart failure, diabetes, dyslipidemia, coronary artery disease, osteoporosis, malignancies, and renal failure. These diseases are particularly common in the elderly population. The estimated prevalence of certain disorders among persons 65 years of age or older who may benefit from nutrition therapy can be found in Table 2.1. Moreover, 87 percent of the population 65 years or older has at least one of these conditions (NCHS, 1997). The effectiveness of nutrition therapy for each of these disorders is described in subsequent chapters.
SCREENING FOR NUTRITION RISK
Over the past several decades, numerous attempts have been made to develop screening instruments that identify older persons who need more comprehensive nutritional assessment (Reuben et al., 1995). These can be categorized as follows:
TABLE 2.1 Estimated Prevalences of Conditions Among U.S. Individuals Age 65 Years and Older
Chronic renal insufficiencyb
Hyperlipidemia (LDL >130 or on medication)d
a Hypertension is defined as having a systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg or taking blood pressure medication.
b Chronic renal insufficiency includes a creatinine level of >2.5 in women and >3.0 in men.
c Elevated low-density lipoprotein (LDL) cholesterol is defined as having a serum LDL cholesterol ≥130 mg/dl and/or taking cholesterol lowering medication.
d The prevalence of diabetes was based on self-report.
SOURCE: NCHS (1997).
brief self-reported screening instruments (e.g., the Nutrition Screening Initiative’s DETERMINE Checklist, the Mini-Nutritional Assessment);
clinician-determined brief screening instruments (e.g., Subjective Global Assessment); and
multimethod techniques (e.g., Prognostic Nutritional Index, Hospital Prognostic Index).
Because few of these are in common usage, the topic is not reviewed in depth. However, the Nutrition Screening Initiative’s Determine Your Nutritional Health Checklist has received wide attention and has been incorporated into screening instruments in many health care settings. The Mini-Nutritional Assessment and Subjective Global Assessment have also received increased attention. Accordingly, brief descriptions and discussions of the properties of these instruments are provided.
Nutrition Screening Initiative
The Nutrition Screening Initiative (NSI), a partnership of the American Academy of Family Physicians, the American Dietetic Association, and the National Council on Aging, Inc., has developed a tiered approach to nutrition screening. The first tier consists of the Determine Your Nutritional Health Checklist. The Determine Checklist was originally devel-
oped as a tool to increase consumer’s nutrition awareness. It is a brief 10-item questionnaire that can be administered and scored by older Americans and/or their caregivers. The Determine Checklist scores range from 0 (lowest risk) to 21 (highest risk). Those found to be at risk of poor nutritional status based on the checklist are thought to need further screening.
The second tier consists of the Level I and Level II screening tools. The Level I screening tool is designed for use in any setting in which older Americans come into contact with professionals in the health care and social service system. It includes height and weight measurement (and calculated BMI), as well as questions about 10-pound weight gain or loss within the prior 6 months, eating habits, living environment, and functional status. The Level II screening tool is designed to obtain more diagnostic information in clinical settings. It includes anthropometric measurements (BMI, midarm circumference, MAMC, triceps skinfold), laboratory data (serum albumin and cholesterol), information on therapeutic drug use, and information on clinical problems that might affect eating, eating habits, living environment, functional status, and cognitive and affective status (Lipschitz et al., 1992).
A study using a stratified random sample of Medicare beneficiaries age 70 and older living in six New England states was conducted to calibrate the Determine Checklist. After reviewing the data from the study, NSI’s technical review committee selected a score of 6 as the threshold for identifying older persons at high nutritional risk. The study estimated that 24 percent of all Medicare beneficiaries would fall into this high-risk group, and it found that those at high risk were more likely to have been hospitalized overnight during the prior year (Posner et al., 1993).
Using a score of 6 as a cut point to predict inadequate nutrition, the study found that the sensitivity, specificity, and positive predictive value of the Determine Checklist were 36, 85, and 38 percent, respectively. Using the same cut point, the sensitivity, specificity, and positive predictive value for identifying perceived fair or poor health status were 46, 85, and 56 percent, respectively. When examining individual items, the strongest predictors of inadequate nutrition were “not enough money,” “eating fewer than two meals per day,” and “eating few fruits and vegetables.” The only items significantly associated with fair or poor perceived health were “taking three or more drugs per day” and “having changed one’s diet because of illness.”
A longitudinal study found that several individual items of the Determine Checklist predicted 8- to 12-year mortality, but the summary score for the entire instrument had a considerably lower predictive value than the individual items (Sahyoun et al., 1997).
The Determine Checklist has been criticized for having poor test characteristics, retaining items that are not significantly associated with outcomes of interest, and using outcomes that are not well-defined pathologic states and do not have proven treatments (Rush, 1993). In addition, the methodology of the validation study by Posner et al. (1993) is questioned for relying on a single 24-hour recall as the criterion of validity (Rush, 1993), which assumes that stability in dietary intake is greater than is likely (Thompson and Byers, 1994).
The Mini-Nutritional Assessment (MNA) is an 18-item instrument, requiring 20 minutes to complete, which incorporates several anthropometric measures, dietary intake questions, and health and functional status questions (Vellas et al., 1999). The developers used discriminant analysis techniques applied to several cross-sectional samples to establish cut points for being “at risk” of malnutrition and being undernourished. The instrument has been validated against clinical judgment of nutritional status, dietary intake, and biochemical measures (Guigoz et al., 1994). Predictive validity for weight loss, the occurrence of acute disease, and the need for assistance have been demonstrated in a Danish study (Beck and Ovesen, 1997). The most recent validation study conducted by Azad et al. (1999) however, indicated poor sensitivity and specificity compared to a nutritionist’s assessment. These studies indicate that the MNA has potential, but more extensive validation is needed before this instrument can be recommended for widespread use.
Subjective Global Assessment
The Subjective Global Assessment (SGA) combines weight change, dietary intake, gastrointestinal symptoms, functional capacity, and physical examination findings to classify individuals as well nourished, moderately malnourished or severely malnourished (Detsky et al., 1987b, 1994). The SGA has demonstrated predictive validity in the identification of patients at risk for postoperative complications (Detsky et al., 1987a; VA TPN Cooperative Study Group, 1991). Personnel who administer the SGA must be trained to achieve acceptable interobserver reliability. A recent study of 369 patients who were at least 70 years of age and admitted to a general medical service in a tertiary care hospital found that those patients classified as severely malnourished by SGA were more likely than well-nourished patients to die within 12 months of discharge (OR = 2.83, 95 percent confidence interval [CI] = 1.47–5.45), to be dependent in activities of daily living 3 months after discharge (OR = 2.81, CI = 1.06–7.46),
and to spend time in a nursing home during the 12 months after discharge (OR = 3.22, CI = 1.05–9.87) (Convinsky et al., 1999).
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