As new markers of poor nutritional status have been identified, the definition of undernutrition has been considerably refined. Most notably, better methods of measuring body composition and biochemical measures of inflammation and nutritional health have led to refined classification systems of undernutrition. Concurrently, there has been increasing recognition of clinical syndromes that appear to have a major nutritional component (e.g., failure to thrive). This report considers several aspects of undernutrition including the following:
Markers of Undernutrition
Weight loss and morphometric measures of undernutrition
Poor nutritional intake
Biochemical markers of malnutrition (albumin, transferrin, retinol binding protein)
Syndromes of Undernutrition
Body composition changes with aging or sarcopenia
Failure to thrive
None of these markers or syndromes (except poor nutritional intake) are specific for malnutrition, and it must be recognized that the interfaces
between nutrition, energy requirements, and disease are complex. Moreover, approaches to diagnosis and management usually have not followed these definitions. Finally, despite global research efforts, there are still many gaps in the understanding of undernutrition in older persons.
For each of these markers and syndromes, the following topics are addressed where information is available:
commonly used definitions,
clinical importance in different settings (e.g., frequency, increased risk for adverse events),
potentially treatable contributing factors and assessment methods (including current practice and a more optimal approach), and
approaches to treatment and treatment outcomes.
There is considerable overlap across conditions with respect to assessment, contributing factors, and treatments. Although this chapter focuses on markers and syndromes of undernutrition, it must be recognized that undernutrition may affect the course of specific acute (e.g., pneumonia [Riquelme et al., 1996]) and chronic diseases (e.g., congestive heart failure, chronic obstructive pulmonary disease, pressure sores). In some instances, the treatment of these diseases (e.g., congestive heart failure) may lead to dietary restrictions that compromise nutritional status (Reuben et al., 1997). In others, the burden of the disorder may lead to increased energy requirements. Finally, some disorders (e.g., stroke with dysphagia, malabsorption) may precipitate undernutrition because of the inability to ingest or absorb nutrients. Although the recognition of these potential influences is important and may guide management, undernutrition accompanying specific diseases will eventually be expressed through the markers and syndromes described below.
MARKERS OF UNDERNUTRITION
Several definitions of clinically important weight loss have been described. These vary according to the amount of weight lost and the duration of the weight loss. In outpatient settings, commonly employed definitions include more than 10 pounds in 6 months, 4 to 5 percent of body weight in 1 year, or 7.5 percent in 6 months.
In the nursing home, the definition of weight loss has usually followed that included in the Omnibus Budget Reconciliation Act (OBRA) regulations of 1987. This legislation mandated implementation of the
Minimum Data Set (MDS) and Resident Assessment Protocols (RAPs) in Medicare-certified nursing homes to ensure prompt identification and response to problems in nursing home residents. (The MDS is a functionally based assessment tool; RAPs utilize MDS assessment information to flag potential problem and risk areas in nursing home residents.) The OBRA MDS considers weight loss as greater than or equal to 5 percent of body weight in the past month or greater than or equal to 10 percent in the last 6 months.
A 4-year cohort study determined that the annual incidence of involuntary weight loss (defined as loss of more than 4 percent of body weight) among veterans followed in an outpatient setting was 13.1 percent. Over a 2-year follow-up period, those with involuntary weight loss had an increased risk of mortality (relative risk [RR] = 2.4, 95 percent confidence interval [CI] = 1.3–4.4), which was 28 percent among those who lost weight and 11 percent among those who did not. Individuals with voluntary weight loss had a 36 percent mortality rate during this time (Wallace et al., 1995). In a study of Alzheimer’s patients followed for up to 6 years, greater than or equal to 5 percent weight loss in any year before death predicted mortality (RR 1.5, 95 percent CI = 1.09–2.07); 22 percent of Alzheimer’s patients experienced such weight loss (White et al., 1998).
Two longitudinal studies also suggest that weight loss in later life predicts mortality. In the Established Populations for Epidemiologic Studies of the Elderly (EPESE) cohort, older persons who lost 10 percent of their body weight or more between ages 50 and 70 years had higher adjusted risks of mortality (men: RR = 1.69, 95 percent CI = 1.19–1.65; women: RR = 1.62, 95 percent CI = 1.45–1.97) (Losonczy et al., 1995). The Iowa Women’s Health Study demonstrated that women greater than or equal to 55 years of age who had an episode of unintentional weight loss (19 percent of the study participants) had an adjusted OR of 1.45 (95 percent CI = 1.24–1.70) for all-cause 5-year mortality (French et al., 1999). Although the time spans utilized in these latter definitions are impractical for clinical purposes, they do provide evidence of an association between weight loss and subsequent mortality.
For the nursing home population, there are fewer prevalence data. One study found that 5 percent of residents at one nursing home met these criteria (Blaum et al., 1997). Weight loss may be an insensitive measure of malnutrition because nursing home residents may stop eating for several weeks between weight measurements.
Potentially Treatable Contributing Factors and Assessment Methods
Many of the causes of weight loss (e.g., depression, type 2 diabetes, hyperthyroidism, gastrointestinal diseases, cancer) are treatable with effective therapies supported by randomized clinical trials (Blaum et al., 1995; Morley and Kraenzle, 1994; Wilson et al., 1998).
Among nursing home residents, reversible factors such as poor oral intake, feeding dependency, chewing problems, depressive symptoms or behavior, medications, and swallowing disorders were related to observed weight loss in two cross-sectional studies (Blaum et al., 1995; Morley and Kraenzle, 1994).
In hospital settings (defined here as short-stay, acute care hospitals), the current approach to assessment of causes of weight loss and undernutrition is generally haphazard. Although many nursing intake forms include questions on weight loss, functional status related to nutrition, and special dietary needs, staff complete these forms in an inconsistent manner. At many institutions, dietary technicians spend significant amounts of time collecting data, which may have little clinical value, in order to meet the Joint Commission for Accreditation of Healthcare Organizations (JCAHO) mandate of nutritional assessment data collection of all hospitalized persons.
Usually nursing home residents are weighed once a month. When the RAP for malnutrition is triggered by any of the MDS nutrition criteria, there must be documentation of responses by the health care team, including an assessment of feeding as well as investigation, when appropriate, for medical disorders that can cause weight loss.
The assessment of weight loss is guided by other associated symptoms (e.g., gastrointestinal, cancer-related, depression, diabetes) if they are present. In addition, other potential contributors to weight loss or any of the other undernutrition disorders are evaluated for potentially remediable conditions. This assessment may include some or all of the following:
assessment of food security, if the older person is community dwelling (e.g., specific questions about financial status, referral to social worker);
assessment of food-related functional status (e.g., specific questions about shopping, meal preparation, and feeding);
assessment of appetite and documentation of dietary intake (e.g., dietitian referral, 72-hour calorie count);
assessment of depressive symptoms (e.g., dietitian referral, 72-hour calorie count);
assessment of dental and chewing status (e.g., documented oral examination or referral to a dentist);
assessment of swallowing ability (e.g., bedside swallowing study, referral for swallowing study, or videofluoroscopy);
assessment of medications that might be associated with decreased appetite (e.g., digoxin, fluoxetine, anticholinergics);
assessment of cognitive impairment (e.g., screening for dementia with the Mini-Mental State Examination); and
assessment of disease-related dietary restrictions (e.g., low salt, low protein).
Approaches to Treatment and Treatment Outcomes
Treatment of specific identified causes of weight loss such as cancer or thyroid disease is supported by clinical trials. However, to date, no randomized clinical trial data have evaluated the ability of consultation by a dietitian or the use of nutritional supplements to provide clinical or health utilization benefits for older persons other than in situations following recovery from pneumonia or hip fracture (Schürch et al., 1998; Woo et al., 1994).
Among homebound elderly with involuntary weight loss or baseline low body mass index (BMI), a case series of 12 weeks of dietary supplements (500 kcal per day) demonstrated increases in weight, total lymphocyte count, and general well-being score (Gray-Donald et al., 1994). A subsequent randomized clinical trial using the same intervention demonstrated increases in weight (2.1 kg in the supplemented group compared to 0.6 kg in the control group, p < 0.01) but no changes in functional status (Gray-Donald et al., 1995). A case-series of persons who had lost at least 20 percent of their body weight or at least 10 percent in 3 months demonstrated improvement in nutritional parameters, including serum albumin, after being hospitalized in a nutritional support unit and receiving enteral nutrition via a nasogastric tube which provided approximately three times the measured energy expenditure for 4 weeks (Hébuterne et al., 1995).
In nursing home settings, many residents who sustain weight loss do so because they are not adequately fed, in part due to limitations of nursing resources (see discussion of “poor nutritional intake” below) (Kayser-Jones and Schell, 1997). Although no studies are available to suggest that nursing home staffing or behavioral changes can improve dietary intake, these problems are potentially correctable. A case-control study of nursing home residents who were receiving oral supplements at least twice daily for weight loss or poor appetite demonstrated that most of these
residents regained weight back to their admission weight over a period of 9 to 10 months (Johnson et al., 1993). In a nonrandomized study that provided increased nutritional support to nursing home residents, undernourished residents (defined by BMI, weight loss, and anthropometric measurements) who gained weight over 10 months had fewer recurring infections and were less likely to die. They had a 17 percent mortality rate, compared to a 45 percent mortality rate among those who were undernourished but lost weight during the follow-up period, and a 35 percent mortality rate among those who were undernourished and maintained their weight (Keller, 1995).
Anthropometric measures are used in research and in some clinical settings to identify older persons with malnutrition. Some of the more common measurements include: triceps skinfold thickness (TSF), which is measured on the upper arm, halfway between the inferior border of the acromion process and the tip of the olecranon process, and mid-arm muscle circumference (MAMC) (Bienia et al., 1982; Shenkin et al., 1996). The MAMC is calculated using the mid upper-arm circumference (AC) and the standard formula: MAMC = AC – 3.14 (TSF) (Bienia et al., 1982).
Because TSF thickness spans a wide range among normal individuals, sequential changes in the same individual may be more valuable than one-time measurements (Shenkin et al., 1996). However, measurement error increases with size of skinfold, and inter- and intraobserver variation may be large (Fuller et al., 1991). Moreover, these anthropometric measurements suffer from poorer reliability in elderly compared to younger subjects, in part because of difficulties in accurately locating anatomic landmarks (Sullivan et al., 1989) and because of age-related changes in skin elasticity. For example, a TSF measurement taken at the level of the midarm may vary by as much as 150 percent from a measurement taken only 1 to 2 centimeters above or below this point (Sullivan et al., 1989). With aging, a smaller proportion of total body fat is subcutaneous; therefore, skinfold thickness is less likely to indicate total body fat in older compared to younger persons.
Nevertheless, in community-dwelling older persons, low corrected arm muscle area and low TSF predict subsequent 40- to 46-month ageadjusted mortality. For example, in a prospective cohort study, having a corrected arm muscle area below the 5th percentile was associated with a RR of 3.5 (95 percent CI = 1.6–8.2), and having a corrected arm muscle
area between the 5th and 10th percentiles was associated with a RR of 2.2 (95 percent CI = 1.0–4.9). In the same study, having a TSF below the 5th percentile was associated with a RR of 4.9 (95 percent CI = 2.1–11.1). BMI did not remain in the logistic model and the authors noted that BMI determinations can be inaccurate in the elderly due to difficulties in obtaining accurate heights and the effects of edema or dehydration on weight (Campbell et al., 1990).
Potentially Treatable Contributing Factors and Assessment Methods
The contributors to anthropometric abnormalities have not been formally studied but are not likely to differ substantially from those contributing to weight loss or low BMI. Assessment methods for abnormal anthropometric measures are similar to those used for weight loss.
Approaches to Treatment and Treatment Outcomes
Anthropometric measures have been used as entry criteria in some clinical trials of nutritional supplementation in hospitalized older persons (Bastow et al., 1983; Gariballa et al., 1998). A randomized clinical trial studied the administration of a 600 kcal and 20 g protein supplementation twice daily to patients who had sustained a stroke and who had anthropometric evidence of undernutrition by TSF and MAMC. Subjects in the supplemented group demonstrated a smaller decrease in serum albumin than those in the control group (mean decrease 1.5 g/L compared to 4.4 g/L, p = 0.025) and a nonsignificant reduction in 3-month mortality (10 percent in the supplemented group versus 35 percent in the control group, p = 0.12) (Gariballa et al., 1998). Another clinical trial of women hospitalized for hip fracture who were classified as thin or very thin based on arm circumference and TSF studied the effect of overnight supplementary nasogastric tube feedings of 1,000 calories, which were continued until discharge or death. Rehabilitation time to independent mobility (median 16 days in the treated group compared to 23 days in the control group, p = 0.02) and hospital stay were shortened (median 29 days in the treated group compared to 38 days in the control group, p = 0.04), particularly among the very thin (Bastow et al., 1983).
Low Body Mass Index
Low BMI (weight [kg] versus height [m2]) is considered definitive for chronic protein–energy undernutrition (PEU) if less than 17 and for being consistent with but not diagnostic of PEU if between 17 to 20 (Shenkin et al., 1996).
Among community-dwelling older persons, BMI has been shown to demonstrate a U-shaped relationship to functional impairment, with increased risk among those at the lowest and highest BMIs (Galanos et al., 1994). However, change in BMI may be more important than actual value. In the EPESE study, persons who were in the lowest quintile of BMI at age 50 were not at increased risk of mortality during old age (Losonczy et al., 1995).
Potentially Treatable Contributing Factors and Assessment Methods
There are two population groups of older persons who have low BMI: those who have always been thin and those whose BMI has declined. Among the latter group, the causes of low BMI are not likely to differ substantially from the causes of weight loss. Assessment methods for low BMI are similar to those used for weight loss.
Approaches to Treatment and Treatment Outcomes
A randomized clinical trial of nutritional supplements for demented patients with low BMI (15.1–19.9) who were admitted to a psychiatric hospital and who received a 600 kcal oral supplement demonstrated significant increases in weight (3.7 versus 0.6 kg), MAMC (0.5 cm versus no change), and TSF (1.5 versus 0.5 mm) at 12 weeks compared to the placebo group (Carver and Dobson, 1995).
Other studies have included low BMI, in addition to weight loss or abnormal anthropometric measurements, as an entry criterion (see discussion of weight loss above).
Poor Nutritional Intake
Generally, poor nutritional intake has been defined as average or usual intake of servings of food groups, nutrients, or energy below recommended amounts. Estimates for energy needs may be obtained from published references (WHO/FAO/UNU, 1985) or calculated using regression equations (e.g., Harris-Benedict). Many of the regression equations in use take into account age, height, and/or body weight. The energy needs are then adjusted for the estimates of activity level and the effects of disease and treatment.
A threshold percentage used to define poor nutritional intake has been 66 or 75 percent of the Recommended Dietary Allowance (RDA) (IOM, 1994). This is not an appropriate use of the RDA as the numbers are derived in multiple ways from available data (IOM, 1997; NRC, 1986).
While some of these recommended intakes are based on the minimum average amount most individuals are thought to need to prevent deficiency, plus additional amounts to account for decreased absorption or bioavailability of the nutrient and for individual variation in requirements, others are based on what appear to be average intakes of healthy groups of people (IOM, 1994).
Newer methodology indicates that a more appropriate reference intake for use in assessing adequacy for a specific nutrient in a group of people is the Estimated Average Requirement (IOM, 1994, 1997). However, these reference intakes are not yet available for all nutrients of interest (IOM, 1997, 1998). Some recent studies conducted in hospital settings have used less than or equal to 30 and 50 percent of estimated energy requirements as a threshold (Incalzi et al., 1998; Sullivan et al., 1999). The MDS uses less than 75 percent of food provided as the threshold to trigger the malnutrition resident assessment protocol. These are subjective assessments frequently conducted by nursing staff.
Prior to implementation of the MDS, the RDA was used as a goal for monitoring nutritional intake and is still used as a standard by many dietitians working in nursing home settings. Subsequent to OBRA implementation in 1987, the specific MDS items for poor nutritional intake are the following:
The resident complains about the taste of many foods.
The resident regularly or repeatedly complains of hunger.
The resident leaves 25 percent or more of his or her food uneaten at most meals.
The unreliability and subjective nature of accurately assessing these measures have been raised. Two studies have documented that nursing home staff significantly overestimate nutritional intake of nursing home residents (Kayser-Jones et al., 1997; Pokrywka et al., 1997).
In summary, efforts to develop assessment tools for use with elderly have not yet been able to identify aspects of health and status that can be monitored and evaluated objectively in older individuals with varying stages of functional capability that will accurately discriminate between those at risk and those not.
Although older persons under-report energy intake (Goran and Poehlman, 1992; Sawaya et al., 1996; Tomoyasu et al., 1999), community surveys estimate that between 37 to 40 percent of elderly men and women (those age 65 and over) report energy intakes less than two-thirds of the
RDA (Ryan et al., 1992). A recent study identified poor nutrient intake (less than 50 percent of calculated maintenance energy requirements) in 21 percent of hospitalized older persons (Sullivan et al., 1999). These persons had higher rates of in-hospital (RR = 8.0, 95 percent CI = 2.8–22.6) and 90-day mortality (RR = 2.9, 95 percent CI = 1.4–6.1). Another prospective observational study demonstrated that low caloric intake (less than 30 percent of estimated need) during the first 3 days of hospitalization could predict in-hospital mortality independently of serum albumin, lymphocytopenia, and activities of daily living impairment on admission (Incalzi et al., 1998).
A review of 14 surveys of nutritional status conducted among chronically institutionalized older persons concluded that 5 to 18 percent of nursing home residents had energy intakes below their recommended average energy expenditure (Rudman and Feller, 1989). In one study, 26 percent of nursing home residents met the MDS criterion for poor oral intake and 9 percent met the criterion for hunger (Blaum et al., 1997).
Potentially Treatable Contributing Factors and Assessment Methods
In hospitalized older persons, diagnostic testing and other reasons for a “nothing by mouth” restriction may contribute to poor nutritional intake beyond the burden of their acute illness. However, in hospital settings, nurses and aides can routinely observe dietary intake and thus offer the potential for inexpensive detection of potential nutritional disorders among hospitalized older persons. In addition, dietetic staff also frequently monitor nutritional intake of older hospitalized patients to meet JCAHO requirements. In general though, the methods for communicating poor dietary intake observed by nursing staff and dietary technicians to physicians have been informal and haphazard. Whether formal calorie counts obtained by food records provide additional value beyond nurse and aide observations has not been established. One report documented that among hospitalized patients, a 1-day calorie count corresponded very closely to the values obtained by a 3-day calorie count for energy and protein intake (Breslow and Sorkin, 1993).
In a qualitative study at two community nursing homes, the following problems with nursing home feeding were identified, largely due to an inadequate number of qualified staff (Kayser-Jones and Schell, 1997):
lack of personal care,
residents being served their meals in bed,
residents being poorly positioned at mealtimes,
trays being poorly positioned at mealtimes,
poor quality of care at mealtimes,
residents being fed quickly and forcibly,
solid food being mixed with liquids,
dysphagia being undiagnosed and unrecognized, and
some residents receiving little or no food.
In addition, many of the medical contributing factors mentioned above (see weight loss) are also applicable to poor intake in the nursing home.
Approaches to Treatment and Treatment Outcomes
There is a large body of literature supporting the value of providing inpatient parenteral and enteral nutrition to older persons who have inadequate intake in the hospital. In addition, there is anecdotal evidence of appetite stimulation and resulting increased energy intake among older persons following administration of large doses of megesterol acetate, an appetite stimulant (Castle et al., 1995). Although evidence supports the use of this appetite stimulant in acquired immune deficiency syndrome (AIDS) and cancer patients (Loprinzi et al., 1994; Oster et al., 1994; Von Roenn et al., 1994), randomized clinical trials indicating benefit in older persons have not been published and toxicity in older persons remains a concern.
Biochemical Markers of Malnutrition
Although the relationship between serum albumin and nutritional intake is not well established, hypoalbuminemia is commonly considered a sign of malnutrition. However, low serum albumin levels may be a better measure of inflammation and associated decrease in albumin synthesis, increase in albumin degradation, and transcapillary leakage than of malnutrition (Rothschild et al., 1988). Thus, the relationship between hypoalbuminemia and adverse outcomes may not necessarily be directly related to nutrition. Hypoalbuminemia is considered in greater detail below in the discussion of PEU. Other proteins, particularly prealbumin and transferrin, are also considered nutritional markers. These proteins have shorter half-lives (prealbumin’s half-life is 48 hours; transferrin’s is 7 to 10 days). Accordingly, they may reflect more recent intake and may be valuable in monitoring response to treatment and like serum albumin, are also affected by inflammation. They are also considered in greater detail below in the discussion of PEU.
Other Biochemical Markers of Undernutrition
Several biological markers of nutritional disorders are being actively investigated in research protocols. They are mentioned only briefly here because many of these are nonspecific markers of inflammation (e.g., C-reactive protein [CRP] and cytokines) and because research on these markers, especially with respect to assessment and treatment, is limited. Cytokines are discussed briefly below under “cachexia.” Low or falling serum cholesterol has been explored as another nutritional marker. In a case-control study of older persons with normal cholesterol levels on admission to the hospital (≥160 mg/dL), those whose cholesterol levels fell to less than or equal to 120 mg/dL during hospitalization (9 percent of admissions among persons ≥65 years) had more infectious and noninfectious complications, and their length of stay was nearly three times as long as those who maintained normal cholesterol levels. Inpatient mortality rates were higher in the acquired hypocholesterolemia group, although not significantly so (Noel et al., 1991). Another study indicated that at their hospital discharge nutritional assessment, 26 percent of hospitalized older persons had serum cholesterol less than 150 mg/dL (Sullivan et al., 1995). However, acquired hypocholesterolemia may not be nutritionally mediated. Ongoing inflammation and proinflammatory cytokines, particularly interleukin-6 (IL-6), may be responsible for acquired hypocholesterolemia (Ettinger et al., 1995).
A variety of demographic and nutrition-related variables were considered as potential predictors of 1-year mortality in a prospective cohort study at a Department of Veterans Affairs nursing home (Rudman and Feller, 1989). In multivariate analysis, only serum cholesterol and hematocrit remained statistically significant. The authors reported a “mortality risk index” (MRI) using the equation: 0.1 (serum cholesterol in mg/dl) + (hematocrit in %) = MRI. When MRI was less than 60, patients were classified as at high risk of dying (when MRI = 60, specificity was 85 percent and sensitivity was 90 percent). Another study found that total cholesterol was predictive of pressure ulcers among tube-fed residents of a long-term care facility (Henderson et al., 1992).
SYNDROMES OF UNDERNUTRITION
Body Composition Changes with Aging
The aging process affects multiple organ system functions that may impact on nutritional assessment and intervention. For example, changes in the skin may alter anthropometric measures. Changes in cardiac and/ or renal functions may necessitate fluid restrictions that alter feeding pre-
scriptions. The degree of change observed in organ function varies considerably among older individuals. Individualized assessment and intervention are therefore necessary.
The aging process is associated with notable changes in body composition. Therefore, well-standardized nutrient requirements for younger or middle-aged adults may not be applicable to older persons. With aging, a gradual decline in lean body mass (LBM) and an increase in body fat occur (Baumgartner et al., 1995) (see Box 4.1). A reduction in LBM results in a lower basal metabolic rate, thus reducing the energy needs of older persons. Novak (1972) studied 500 men and women, aged 18 to 85 years, and observed that body fat was increased, respectively, from 18 to 36 percent in younger versus older men and from 33 to 44 percent in younger versus older women. As total body fat increases with aging, intraabdominal fat stores often increase. Abdominal adiposity has been linked to the development of insulin resistance, coronary artery disease, dyslipidemia, hypertension, and type 2 diabetes mellitus (Poehlman et al., 1995).
Age-related loss of skeletal muscle mass is referred to as sarcopenia (Rosenberg, 1989). Biopsy studies reveal a reduction in the number and size of type II muscle fibers with aging, while type I fibers are spared (Lexell, 1995).
There has been considerable interest in studying sarcopenia because of its possible relationship to loss of strength and functional decline (Evans and Campbell, 1993). Two recent major symposia have summarized current knowledge regarding sarcopenia and have highlighted limitations in understanding it (Kehayias and Heymsfield, 1997; Lexell and Dutta, 1997).
The prevalence of clinically relevant sarcopenia is unknown (Baumgartner et al., 1998); moreover, the relationship between sarcopenia and undernutrition has not been established. It is not clear whether sarcopenia is an inexorable part of aging, or is more a reflection of sedentary lifestyle or as yet unrecognized factors. The role, if any, of nutritional intervention awaits further clarification. It is clear, however, that assessment of energy needs for many older persons must take into consideration a decline in lean body mass and reduced physical activity.
Potentially Treatable Contributing Factors and Assessment Methods
Possible causal factors for sarcopenia include age-related accelerated muscle loss or changes in muscle accretion or responsiveness to trophic hormonal or neurologic factors. Decline in endogenous growth hormone production, altered cytokine regulation, decreased androgen and estrogen production, and loss of alpha motor neurons in the spinal column have been suggested as factors (Roubenoff et al., 1997). Changes in dietary intake, protein metabolism, or disuse atrophy resulting from a sedentary lifestyle may also be contributors (Bortz, 1982; Dutta and Hadley, 1995; Evans and Campbell, 1993).
Major difficulties in the study of sarcopenia include the lack of valid methods for routine assessment of skeletal muscle mass and function in humans. Current high-technology standards for the measurement of muscle mass include total body counting of the naturally occurring potassium isotope (40K), dual-energy x-ray absorptiometry, computed tomography, and magnetic resonance imaging (Chumlea et al., 1995; Heymsfield et al., 1990; Selberg et al., 1993; Sjostrom, 1991).
Approaches to Treatment and Treatment Outcomes
Potential approaches to treatment of sarcopenia include administration or modulation of trophic factors (Rudman et al., 1990) or resistance strength training (Evans and Cyr-Campbell, 1997). Growth hormone (GH) levels may be 29 to 70 percent lower in elderly compared with younger men (Corpas et al., 1993). Papadakis and coworkers (1996) randomized 52 men to 6 months of GH replacement versus placebo, and found that LBM increased by an average of 4.3 percent in men who received GH, in comparison to a decrease of 0.1 percent in those receiving placebo. Fat mass also declined in the treatment group (down 13.1 percent with therapy versus 0.1 percent with placebo). Despite favorable improvements in body composition, there were no statistically significant improvements in muscle strength, systemic endurance, or functional status. Insulin-like growth factor I (IGF-I), which is released by the liver in response to GH,
also declines with age. Rudman et al. (1990) randomized 21 healthy men aged 61 to 81 with low plasma IGF-I levels into GH treatment for 6 months or a no-treatment group. At follow-up, the treatment group exhibited an 8.8 percent increase in LBM, a 14.4 percent decrease in total body fat, a 7.1 percent increase in skin thickness, and a recovery of IGF-I to levels usually observed in younger people. The no-treatment group exhibited little change in outcome variables.
Testosterone also declines in aging men. When six elderly men with reduced testosterone concentrations were administered testosterone by injection for 4 weeks to achieve serum concentrations comparable to younger men, increased fractional synthetic rate of muscle protein and increased muscle strength (hamstring and quadriceps) were observed (Urban et al., 1995). Since increased mRNA concentrations of IGF-I were detected, it was suggested that IGF-I might mediate the observed response to testosterone. A prospective, randomized trial of testosterone versus placebo injection in 32 older men over a 12-month period found significant improvement in hand-grip strength and increased hemoglobin and lowered leptin levels in the treatment group in comparison to placebo (Sih et al., 1997). A more recent prospective, randomized trial of testosterone versus placebo by cutaneous patch in 108 older men over a 36-month period found a significant increase in LBM and a decrease in total body fat, but no increase in strength of knee flexion and extension in the treatment group in comparison to placebo (Snyder et al., 1999). Serum IGF-I concentrations fell significantly in both groups during study, but significantly less in the treatment group.
Skeletal muscle mass is responsive to changes in physical activity. Fiatarone and colleagues (1994) conducted a randomized, placebo-controlled trial of resistance exercise and/or multinutrient supplementation for over 10 weeks in 100 frail nursing home residents. Participants who received resistance exercise training had significant improvements in muscle strength, gait velocity, and stair-climbing power. Cross-sectional thigh muscle area increased in exercisers but declined in nonexercisers. Nutrient supplementation alone or as a supplement to exercise had no beneficial effect on primary outcome measures.
Cachexia and wasting, in which body cell mass is diminished, occur in illness, injury, or disease and are not part of the normal aging process. Because these are newly defined conditions, research on their clinical importance, assessment, and treatment is limited. Although the terms “cachexia” and “wasting” have often been used interchangeably in the clinical setting to describe patients with severe weight loss and compro-
mised nutrition intake, Roubenoff and coworkers (1997) have recently suggested distinct syndrome definitions based on the presence or absence of cytokine-mediated response to injury or disease. Although patients may exhibit components of both inflammatory or injury response and semistarvation, this framework serves as a useful conceptual approach. Patients with components of both cachexia (cytokine-mediated inflammatory/injury response) and wasting (semi-starvation) are particularly challenging to treat successfully.
Cachexia is characterized by increased cytokine production as a result of underlying inflammatory disease or critical illness or injury. The inflammatory cytokines (tumor necrosis factor [TNF], IL-1, and IL-6) may mediate changes in metabolism indirectly by altering the secretion of hormones and directly by affecting target organs (Roubenoff, 1997). The resulting hormonal milieu favors a catabolic state. It is noteworthy that TNF was originally called “cachectin” because of its suspected role in cachexia (Beutler et al., 1985). These three cytokines are believed to play key roles in triggering the acute-phase metabolic response to inflammation or injury. Manifestations of this response may include elevation in resting energy expenditure, a net export of amino acids from muscle to liver, an increase in gluconeogenesis, a shift toward the production of acute-phase proteins, and a decline in the synthesis of albumin (Kushner, 1993). Despite the loss of body cell mass, observable weight loss may be modest or nonexistent because of an increase in the extracellular fluid compartment.
Although the acute-phase metabolic response may be an appropriate adaptive response for acute injury or inflammation, it can be associated with increased complications and mortality if severe or protracted. Life is not sustainable when body cell mass falls below 60 percent of usual levels (Kotler et al., 1989; Winick, 1979).
Potentially Treatable Contributing Factors
Diseases or injury states in which cachexia is present at varying degrees include rheumatoid arthritis, congestive heart failure, chronic obstructive pulmonary disease, human immunodeficiency virus (HIV) infection without serious opportunistic infection, and critical injury with adequate nutrition support (Roubenoff et al., 1997). Patients with rheumatoid arthritis who had adequate nutritional intakes evidenced reduced body cell mass in comparison to weight-matched controls (Roubenoff et al., 1992, 1994). Rheumatoid patients with the highest levels of catabolic
cytokines had the lowest lean body mass (Roubenoff et al., 1992). Congestive heart failure patients may suffer appreciable loss of body cell mass with concomitant increase in extracellular water, resulting in net weight gain. Elevated levels of TNF and its soluble receptors have been detected in patients with heart failure (Anker et al., 1997). Decline of body cell mass in HIV patients without severe weight loss was found to identify individuals with subsequent risk of mortality (Kotler et al., 1989). Severe burn injury can elicit a profound cytokine-mediated catabolic response that may result in negative nitrogen balance even in the face of aggressive nutrition support (Cannon et al., 1992; Wolfe, 1996).
Approaches to Treatment and Treatment Outcomes
Anticytokine agents and anabolic hormones offer potential to modulate response to inflammation or injury, but have been applied in limited settings (e.g., rheumatic diseases) to date. Adjunctive nutrition support may serve to blunt semistarvation and associated wasting.
Wasting has been differentiated from cachexia by its loss of body cell mass without increased cytokine production (Roubenoff et al., 1997). Semi-starvation results in obvious nonvolitional weight loss without manifestations of the acute-phase metabolic response. In pure wasting syndrome, resting energy expenditure may well be reduced and visceral proteins preserved. Increased extracellular fluid is not observed. The common feature of wasting conditions is poor dietary intake that results in weight loss.
Potentially Treatable Contributing Factors
Disorders in which wasting is a clinically observable component include marasmus, cancer, advanced AIDS with opportunistic infection, critical illness without nutrition support, and chronic organ failure syndromes (i.e., renal, hepatic, lung) (Roubenoff et al., 1997). Many patients with these disorders may have evidence of inflammation as measured by cytokine and CRP stimulation. Thus, the distinction between wasting and cachexia may not be as clear as previously thought. Marasmus is the classic syndrome of semistarvation with loss of subcutaneous fat and skeletal muscle that may be readily detected by change in body weight and upper-arm anthropometry. Among cancer, AIDS, and organ failure syndrome patients, observed weight loss determined to be due to wasting carries a poor prognosis.
Approaches to Treatment and Treatment Outcomes
Interventions for wasting syndromes have generally focused on increasing nutrient intake through nutritional supplementation and appetite stimulation via drug therapy. However, outcome and ability to accrue lean body mass appear largely to be determined by the underlying disease process.
PEU is defined by the presence of both clinical (physical signs such as wasting, low BMI) and biochemical (albumin or other 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, this threshold has been questioned as increased risk of adverse outcomes has been identified among hospitalized patients with higher levels of serum albumin (Del Savio et al., 1996).
The prevalence of PEU varies widely across settings. Using a threshold of less than or equal to 3.5 g/dL, 25 to 53 percent of elderly patients meet this criteria among hospitalized older persons (Bienia et al., 1982; Constans et al., 1992), as do 35 percent of geriatric rehabilitation unit patients (Sullivan et al., 1995). Among community-dwelling older persons sampled in the first National Health and Nutrition Examination Survey (NHANES), 1 percent of persons 55 to 74 years of age had albumin levels less than 3.5 g/dL, but 8 percent had values of less than or equal to 3.8 g/dL (Reuben et al., 1997). The prevalence of hypoalbuminemia rises with age as a result of the increased burden of diseases and probably a slight physiological decrease in albumin level with aging. Among those 90 years of age or older in the EPESE cohort, 10 percent had values less than 3.5 g/dL (Salive et al., 1992). Community-dwelling older persons who are homebound appear to be at particular risk for hypoalbuminemia; 19 percent had serum albumin levels less than 3.5 g/dL in one survey (Ritchie et al., 1997). In the nursing home setting, approximately 28 percent of residents have albumin levels less than 3.5 g/dL (Abbasi and Rudman, 1993).
Numerous studies have associated low serum albumin in hospitalized older persons (measured at various times during 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; Sullivan et al., 1995; Volkert et al., 1992). When considering mortality, the lower the albumin level, the higher the risk of death. Among nursing home residents who were hospitalized, one prospective cohort study found that severe hypoalbuminemia predicted mortality (Ferguson et al., 1993).
Low serum albumin has been predictive of 1-year mortality in male nursing home residents (Rudman et al., 1987). Similarly, a prospective cohort study found that hypoalbuminemia predicted 3-month mortality among long-term care residents receiving tube feedings (Henderson et al., 1992).
In community-dwelling populations, hypoalbuminemia predicts higher mortality rates at 3, 5, and 9 to 10 years (Agarwal et al., 1988; Corti et al., 1994; Klonoff-Cohen et al., 1992; Sahyoun et al., 1996) and in healthier older persons (Reuben et al., 1999). The magnitude of this risk is most pronounced in those who meet the classic hypoalbuminemic criterion of less than 3.5 g/dL. In the EPESE cohort, the adjusted RR of mortality over 5 years for those who met this criterion was 1.9 for men and 3.7 for women. That study also noted significantly increased RR (1.9 for men and 2.5 for women) among persons with more modest hypoalbuminemia (≤3.8 g/dL). 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 3.8 g/dL had an adjusted RR of 3-year mortality of 1.8 (Reuben et al., 1999).
Prealbumin has also been shown to provide long-term prognostic value of mortality for patients admitted to a geriatric assessment unit (Mühlethaler et al., 1995). Low prealbumin and transferrin levels predicted short-term (3 month) mortality among nursing home residents (Woo et al., 1989).
Potentially Treatable Contributing Factors and Assessment Methods
Using data from the first NHANES, 14 risk factors for hypoalbuminemia were identified (Reuben et al., 1997). These included age greater than or equal to 65 years; receipt of welfare; having a condition that interferes with eating; vomiting greater than or equal to 3 days per month; prior surgery for gastrointestinal tumor; having heart failure; having recurring cough attacks; feeling tired, worn out, or exhausted; loss of teeth or having poor dentition; getting little or no exercise; being prescribed a low salt diet; currently smoking cigarettes; trouble chewing firm meats; and having albuminuria, glycosuria, or hematuria. Those who had between three and five of these conditions had an odds ratio of 2.73 for
having an albumin level less than or equal to 3.8 g/dL, and those with six or more risk factors had an odds ratio of 6.44. Many of these risk factors are modifiable; however, the link between modifying risk factors and reduction of hypoalbuminemia and subsequent consequences has not yet been established.
The assessment of hypoalbuminemia includes tests of liver and renal function to exclude cirrhosis and nephrotic syndrome. Other assessment methods are similar to those used to evaluate weight loss and are described above.
Approaches to Treatment and Treatment Outcomes
Among hospitalized older persons, the most relevant research has been that aimed at poor nutritional intake (summarized above and in chapter 2). There have been no randomized clinical trials of specific treatments for PEU or hypoalbuminemia in community-dwelling older persons, but a small case-series indicated that a nurse-administered, in-home assessment may uncover remediable problems that contribute to hypoalbuminemia (Reuben et al., 1999).
Failure to Thrive
This term was originally coined to describe infants who failed to achieve height, weight, or behavioral milestones consistent with population-based normative data. It was later adapted to describe older persons who lose weight, decline in physical and/or cognitive function, and demonstrate signs of hopelessness and helplessness (Braun et al., 1988). In 1991, the National Institute on Aging described failure to thrive as “a syndrome of weight loss, decreased appetite and poor nutrition, and inactivity, often accompanied by dehydration, depressive symptoms, impaired immune function, and low cholesterol” (Lonergan, 1991). Some people have advocated abandoning this term as a disease construct in favor of four treatable contributing domains: (1) impaired physical functioning, (2) malnutrition, (3) depression, and (4) cognitive impairment (Sarkisian and Lachs, 1996). Because failure to thrive has not been approached systematically, prevalence data are not available. Specific treatments have not been developed or tested. Accordingly, the approach to failure to thrive is not considered separately.
LIMITATIONS OF CURRENT EVIDENCE
The detection of undernutrition in older persons in all settings is limited by the lack of valid and reliable detection methods. Other than in
specific situations (e.g., after hip fracture), the treatment of undernutrition is more empirical than evidence based.
Undernutrition is exceedingly common among hospitalized older persons. Some are undernourished at the time of admission; others become undernourished during the hospitalization as a result of poor nutritional intake and high energy requirements. The treatment for undernutrition depends on the underlying cause. Although there are limited data supporting nutritional intervention in this setting, efforts to assess dietary intake and intervene should be encouraged. The JCAHO has designated the geriatric population as being at high risk and has required screening within 24 hours. Although the details of this screening are not specified, in practice, substantial amounts of dietitian and dietary technician time are spent in attempting to meet JCAHO requirements with little evidence that this actually benefits the care of patients.
Undernutrition among nursing home residents is also common. Inadequate numbers of qualified staff and resulting feeding problems are major contributors. Treatable acute and chronic medical problems may also be important contributing factors.
Most markers (i.e., weight loss, body composition, and biochemical) that are used to indicate undernutrition are not specific for this disorder and may be affected by both acute and chronic illness. Nevertheless, all convey valuable prognostic information.
Newly defined syndromes, such as sarcopenia, cachexia, and wasting, may occur singly or in combination. The contributions of nutritional components as well as age-related changes and disease must be considered. The role(s) for nutritional therapy in the treatment of these syndromes awaits clarification.
There is a pressing need for research on undernutrition in older persons. In many instances, key issues have not been formally studied. In other instances, the research previously conducted does not provide definitive answers.
Although the optimal method for identifying undernutrition in hospitalized older persons has not been determined, the currently employed methods are time consuming and insufficient. The current standards for screening for risk of malnutrition in hospitalized Medicare beneficiaries must be revised and standardized. While additional research is being conducted, it is rational to focus on assessments that
have prognostic value (e.g., weight loss, serum proteins) or which indicate that patients are not receiving adequate intake in the hospital, particularly patients whose hospitalization exceeds 72 hours. If potential undernutrition is identified, it is imperative that this information be communicated formally to the physician responsible for the patient’s care.
Community-dwelling older persons and nursing home residents who have experienced weight loss should be evaluated by a dietitian for potentially reversible causes as part of their Medicare benefits. This evaluation should include some or all of the following:
food-related functional status
appetite and dietary intake
medications that might be associated with decreased appetite
disease-related dietary restrictions.
Adequacy of feeding assistance in nursing home and hospital settings should be a performance standard for licensing.
The federal government, through agencies such as the National Institute on Aging, the Agency for Healthcare Research and Quality, and the Health Care Financing Administration, should support clinical research on nutrition in older persons. Some of the most important research questions include the following:
Which body composition and biochemical measures are most specific for undernutrition?
What are the best methods for identifying older persons with undernutrition in hospital settings?
What are the benefits of provision of nutritional supplements among older persons who have experienced decreased appetite during hospitalization?
What are the benefits of provision of nutritional supplements among older persons who have lost weight for which an identifiable cause has not been found?
What are the most appropriate methods for providing nutritional intake for older persons who will not or cannot safely ingest sufficient nutritional intake?
What are the best methods to ensure that nursing home residents are adequately fed?
What are the most effective combinations of nutrition therapy, exercise, trophic factors, and appetite stimulants that lead to optimal outcomes among those with undernutrition?
What is the role of nutrition therapy among older persons who have evidence of sarcopenia, cachexia, or wasting syndromes?
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