In 2000, just fewer than 35 million adults (12.4%) of the American population were ages 65 years and older (U.S. Census Bureau, 2000). This number is expected to double m the next 30 years, growing to 70 million (20%) by 2030, with the oldest old (those ages 80 or 85 years and older) growing six times the rate of the general population (Administration on Aging, 2001). With life expectancy at 79 years for women and 72 years for men, older women are increasingly outnumbering older men, especially among the oldest old. Older women are three times as likely as men to be widowed, and 8 of 10 of the community-dwelling older individuals who live alone are women - a group at increased risk for poor nutrition. Data from community studies indicate that 2% to 16% of elderly persons are undernourished and that 20% are obese (Whitehead & Finucane, 1997). Both overweight and underweight (body mass index [BMI] <15th or >85th percentile) increase the relative risk in the older population.
The significance of good nutrition for the health and well being of elderly individuals is of great public interest because elderly individuals are disproportionately large consumers of health care resources (Payette, GrayDonald, Cyr, & Boutier, 1995). In a study of older patients admitted to a hospital, those who were malnourished had actual Hospital charges double that of those who were not malnourished. The average length of stay was 5.6 days longer than patients without malnutrition (Incalzi et al., 1994). Home-delivered meals can be provided to an older person for an entire year for what it costs to spend one day in the hospital (American Dietetic Association, 1995).
Nurses in a variety of settings from acute care to home care, are the health care professionals who have close contact with older individuals and are, therefore, ideally positioned to assess nutritional status. The purpose of this pilot study was to examine the nutritional health of community-dwelling older adults admitted to acute care and identified as at nutritional risk through routine hospital screening. The research questions are:
* Among hospitalized geriatric patients, what percent are classified the same way by hospital screening and the Nutritional Screening Initiative instruments DETERMINE Your Nutritional Risk and Level I Screen?
* Among those who are at nutritional risk, how many perceive themselves to be at nutritional risk?
* How do older adults identified as at nutritional risk think they could be assisted in improving their nutritional status?
BACKGROUND AND SIGNIFICANCE
Studies have shown that up to 50% of surgical patients and 44% of medical patients are malnourished on admission to hospital (Charalambous, 1993; Cope, 1994). The prevalence of protein energy malnutrition is higher in women (41%) than men (30%) (Constans et al., 1992). Covinsky et al. (1999) found that nearly one in six patients 70 or older was severely malnourished. This directly correlated with increased mortality, delayed functional recovery, and higher nursing home use (Covinsky et al., 1999). In a population of elderly veterans, Sullivan, Patch, Walls, and Lipschitz (1990) found the correlation between nutritional status and outcomes remained significant, even when age and non-nutritional variables were controlled. Patients with a compromised nutritional status have three times the number of major complications, stay in the hospital two thirds longer, and are three times as likely to die (Saffel-Shrier & Athas, 1993).
In studying predictors of inhospital mortality after hip fracture in elderly patients Incalzi et al. (1994) found that malnutrition had a heavy impact on inhospital mortality. Furthermore, any pre-existing nutritional deficits are likely to get worse during hospitalization because the majority of patients are unable to eat enough to meet most of their basal protein or energy requirements (Hanger, Smart, Merrilees, & Frampton, 1999). Impaired appetite, inadequate intakes of nutrients, and weight loss continue for long periods of time following hospital discharge. It is precisely at this point of greatest need that nutritional surveillance and support may be removed.
Sullivan, Sun, and Walls (1999) reports that the variable most strongly associated with mortality after hospital discharge was "nutrition risk." In view of the early discharge of hospitalized patients, the nutritional problems of elderly individuals before nutritional status is re-established may have a downwardly spiraling effect on long-term clinical outcomes (McCormack, 1997). Elderly patients who are undernourished at hospital discharge are at increased risk of early non -elective hospital re-admission and death within the subsequent 1 to 4 years (Sullivan et al., 1999).
MEASURES OF NUTRITIONAL HEALTH STATUS
Nutritional screening has been called a vital sign of America's health (Dwyer, 1991), yet malnutrition lacks standardized diagnostic criteria and assessment tools and is consequently difficult to recognize and quantify (Whitehead & Finucane, 1997). Nutritional problems often stem from a highly individual constellation of interacting physiologic, economic, and psychosocial causes that result in diminished nutrient intake. Despite these challenges, there is a need for simple, noninvasive and sensitive nutritional indicators that can be used in community settings to detect nutritional problems prior to hospitalization.
In a review of current multi-item nutritional screening tools used in a variety of settings, two are identified for use in ambulatory settings (Reuben, Greendale, & Harrison, 1995). The Nutritional Risk Index (NRI) is a 16-item scale derived in pan from items included in the National Health and Nutrition Examination Survey I (NHANES I). The NRI was tested in community-dwelling samples in St. Louis and Houston (Wolinsky et al., 1990). Alpha reliability of the five dimensions range from .51 to .60, and is unacceptably low (Reuben et al., 1995).
A set of three tools was created as a direct response to the call from the 1988 Surgeon General's Workshop on Health Promotion and Aging and Healthy People 2000 to increase nutritional screening. Under the leadership of the American Academy of Family Physicians, the American Dietetic Association, and the National Council on the Aging, Inc., a multidisciplinary Blue Ribbon Advisory Committee formed the Nutrition Screening Initiative (NSI). Uniting professionals, including nurses, in their goal of health promotion and disease prevention through improved nutrition, a checklist was created. The "DETERMINE Your Nutritional Health" Checklist" is a self -administered screening tool intended to assist individuals in recognizing aspects of their eating habits and lifestyle that may place them at nutritional risk. The tool can be downloaded from the following website: www.aafp.org/PreBuilt/ NSI_DETERMINE.pdf. It was designed to be completed by either the elderly individual or their caregivers.
Risk factors are defined as "characteristics that are easily identified and that are associated with an increased likelihood of poor nutritional status" (Dwyer, 1991, p.4). DETERMINE is a mnemonic for the risk factors assessed by the Checklist:
* Eating poorly.
* Tooth loss and mouth pain.
* Economic hardship.
* Reduced social contact.
* Multiple medicines.
* Involuntary weight loss or gain.
* Needs assistance in self-care.
* Older than 80.
For the DETERMINE Your Nutritional Health Checklist, participants answer true or false to each of 10 questions. Answers of "true" are assigned from 1 to 4 points according to how much they increase nutritional risk. Points are totaled to give a score ranging from O (lowest risk) to 21 (highest risk). Based on scores of 6 or higher, it is suggested that individuals approach their health care provider. The points assigned were determined originally by a panel of gerontologists and nutritionists from beta weights shown in multiple regression analysis as predictors for consumption of essential nutrients reported in 24-hour recalls (Hendy, Nelson, & Greco, 1998).
A weakness of the Checklist is that it overpr edicts nutritional risk because of its poor sensitivity and specificity (Rush, 1993). The Checklist's sensitivity, specificity and positive predictive values are 46%, 85%, and 56%, respectively, for detecting fair or poor self-rated health and 36%, 85%, and 38%, respectively, for detecting intake of less than 75% of Recommended Dietary Allowance (RDA) for three or more nutrients (Posner, Jette, Smith, & Miller, 1993). Low sensitivity refers to the ability of the questionnaire to detect true cases. The DETERMINE Checklist identifies fewer than half of those with poor self-rated health or nutritional intake. Specificity, the ability to rule out those who do not have the problem, needs to be high to rule out "false positives" or those who do not have the condition of interest. A high incidence of false positives would mean that individuals not at risk would seek further assessment, overburdening the health care system and causing unnecessary worry to the individual (Rush, 1993).
As a result of these poor psychometric properties, the DETERMINE Checklist is more effective as an educational tool for public awareness of nutritional risk than as a screening or assessment tool. To increase awareness of the nutritional problems in elderly individuals, more than 1,000,000 copies of the DETERMINE Your Nutritional Health Checklist have been distributed by the NSI. It is also used in more than 40 states as a screening tool for programs serving older adults (Boult, Krinke, Urdangarin, & Skarin, 1999).
The NSI created a second tool, the Level I Screen, for use by professionals in health or social services as a nutritional assessment tool (Barrocas, Belcher, Champagne, & Jastram, 1995). The Level I Screen can be used in a variety of community and health care settings. It consists of four sections:
* Body mass index (BMI) and changes in weight.
* Eating habits.
* Living environment.
* Functional status.
A nomogram is included to assist in the calculation of BMI. The screener asks a series of Yes or No statements to assess for nutritional risk factors. Based on any Yes answer, it is suggested that a referral be made to a health care or social services professional, dietician, or to available community services such as congregate meal services, counseling services or day care programs. A physician should be notified for anyone with an unintended weight change of 10 pounds in 6 months, a BMI greater than 27 or a BMI less than 22.
The third tool created by the NSI is the Level II Screen. This diagnostic tool adds clinical data such as skinfold thickness, laboratory data, and assessment of cognitive impairment and depression. It facilitates the collection of information needed to make a diagnosis of malnutrition and provides additional data needed for planning care. This tool is most appropriately used by physicians or nurses in a clinical setting such as a hospital or physician's office (Quinn, 1997).
Neither the Level I nor the Level II Screen has a scoring system for weighting risk factors. The intent of these diagnostic tools was that interventions would be instituted for any area of nutritional risk. Lack of a quantifiable scoring system means that a clinician has no way of knowing how many risk factors constitute a serious nutritional risk. Nonetheless, these instruments include important risk factors such as BMI not measured by the DETERMINE Checklist. This pilot used both the DETERMINE Your Nutritional Health Checklist and the Level I Screen.
On admission to the University of Wisconsin Hospital, all patients are screened into two categories - not at nutritional risk or at nutritional risk based on a dietician's decision. This setting, therefore, offers an ideal opportunity to compare the tools using a population of communitydwelling older adults. Use of both tools with the same sample permits comparisons between the tools previously unreported in the literature.
A cross-sectional descriptive pilot study was conducted at a Wisconsin tertiary care academic health center during a 2-month period. A convenience sample goal of 10 was based on hospital admission data for the previous year, which indicated that the patients in this hospital are largely younger. Therefore, it would be difficult to recruit enough participants from the old-old population, the population intended for future study by the author. Consequently, inclusion criteria were:
* Age 65 or older.
* Identified as at nutritional risk by a hospital staff dietician.
* Cognitive status: able to communicate and remember recent dietary intake, a subjective decision made by the screening dietician.
Human subjects approval was obtained from the Health Sciences Human Subjects Committee at the University of Wisconsin, Madison.
A staff dietician routinely screens patients admitted to this tertiary care center for nutritional risk based on diagnosis, modified diet, age, and lab values (University of Wisconsin Health, 2000). All patients are classified as not at risk, or at nutritional risk. The criteria used to identify individuals who are at nutritional risk are:
* Admitting diagnosis associated with moderate or high nutrition risk. Examples of high-risk diagnoses are diabetes, dysphagia, cancer, bowel obstruction or major abdominal surgery. Examples of moderate risk diagnoses include congestive heart failure, decubiti, myocardial infarction or osteoporosis.
* Patients on modified diets such as diabetic diets or cardiac diets.
* Laboratory values as available (e.g., serum albumin, serum cholesterol, blood urea nitrogen, creatinine).
* Age of patient greater than 80.
The dietician covering the geriatric unit screened potential participants for inclusion criteria and asked permission to be contacted by a researcher. The dietician also screened for cognitive status, assessing whether the participant could answer questions and had sufficient recall to give information about past dietary habits.
The dietician notified the researcher by e-mail when a participant agreed to be contacted. Within the next working day, the researcher contacted the participant to obtain informed consent, including permission to collect demographic data from the patient chart and to set up a convenient time for an interview. All interviews were conducted in the hospital rooms of the participants within 48 hours of admission.
The interview consisted of nutritional assessment using two NSI tools, the DETERMINE Your Nutritional Health Checklist and the Level I Screen. The researcher read the questions from these tools. Height and weight were by self-report. While weight on admission was usually recorded in the chart for verification, height was not.
The second part of the interview consisted of several questions intended to probe personal perceptions, attitudes, and knowledge of nutritional health. These questions were:
* "How would you rate your nutritional status?"
* "Tell me what eating means to you."
* "Are there things that you can think of that would help you eat a more balanced diet?"
* "Do you have any suggestions for ways that people can improve their nutrition as they grow older?"
The interview was tape recorded for later transcription. Interviews varied in length from 10 minutes to half an hour depending on the individual. The purpose of the interviews was to elicit the viewpoint of the participants, therefore, while probing questions were used to elucidate meanings, no education was attempted. Triangulation of methods was used to tap into the experiences of these older adults, thereby getting better and more data than structured interviews alone provide.
Frequencies from the two screening tools were tabulated for general trends and comparisons between the three measures of nutritional risk:
* Hospital dietician screening.
* The DETERMINE Your Nutritional Health Checklist.
* Level I Screen.
Naturalistic qualitative evaluation of transcripts was analyzed by the researcher to tap into the experiences of these older adults for meaning beyond that revealed by questionnaires. Using the evaluation methods of Cuba and Lincoln (1981), content was categorized using single words as the unit of analysis. These units of analysis were then enumerated and sorted into mutually exclusive, independent, and exhaustive categories reflecting the purpose of this research, which was to understand the nutritional health of community-dwelling older adults. Single interviews precluded verification with participants.
BODY MASS INDEX (BMI)
The sample (N = 10) consisted of four men and six women with an age range of 68 to 86 (Mean 74, S.D. 6.6). All were White. In this sample, 50% lived with a spouse, 30% lived alone, 10% lived with a child, and 10% lived with a non-relative roommate.
Scores from the DETERMINE Your Nutritional Health Checklist ranged from 5 to 10 of a possible 21. All of these individuals were at nutritional risk as measured by the DETERMINE Your Nutritional Health Checklist. Of these, 40% were at moderate risk, with scores from 3 to 5, and 60% were at high nutritional risk with scores of 6. It was of interest that 90% had a BMI of 27 (Table), yet all of these individuals considered themselves healthy nutritionally. As one man stated, "I'm 280 pounds. How can I be malnourished?" A common misperception in this sample was that being overweight precludes the possibility of being undernourished.
When asked to rate their nutritional health, only one person self-rated nutritional health as "fair." The others (90%) rated themselves as "good." The participants all felt they did a good job of eating a nutritious diet and knew what constituted a good diet (e.g., saying "I know what a good diet is"). In response to the question, "Are there things that you can think of that would help you eat a more balanced diet?," the entire sample replied "no," explaining that they currently were eating well. The last question in the interviews was: "Do you have any suggestions for ways that people can improve their nutrition as they grow older?" Being open to change was a common theme. An example of a response is, "That's very important, to try new things. Things that maybe you didn't grow up with or you just aren't used to."
Several spoke of the ways they try to eat a healthy diet by, for example, maintaining a garden to eat fresh vegetables. Four of the 10 specifically mentioned cutting down on fat by reducing the quantity of red meat and trimming fat from meat eaten. Yet none of these older individuals actually consumed the amounts recommended for all four food group categories included in the Level I Screen (vegetables = 3 or more servings; fruit = 2 or more servings; dairy = 2 servings; and breads, cereals, grains or pasta = 6 servings) per day. Only 40% ate enough milk or dairy; 50% enough vegetables; 60% enough fruit; and 90% ate enough bread, cereal, pasta, and grains.
From the DETERMINE Checklist, two risk factors were present in the entire sample. The first was having an illness that affected the kind or amount of food eaten. While this was to be expected in a population recently admitted to acute care, several spoke of not feeling well for a long time before admission and the impact of not feeling well on eating. The second risk factor present in the entire sample was taking three or more prescribed or over-the-counter medications a day.
Three individuals (30%) answered yes to, "I am not always physically able to shop, cook and/or feed myself." The Level I Screen provided a more complete picture of activities of daily living (ADL) ability. One person usually or always needed assistance with bathing. All were able to dress, groom, toilet, and feed themselves. Mobility was a more problematic area. Mobility was assessed with questions related to:
* Walking or moving about.
* Traveling outside the home.
* Preparing food.
* Shopping for food or other necessities.
Use of an assistive device such as a walker or cane was counted as needing assistance with mobility. In this sample, 80% needed assistance with walking or moving about. Half needed help when traveling outside the home and 30% needed help to prepare food. Grocery shopping was a difficult or impossible chore for 60% of these older adults, requiring assistance from spouses, other family members, or neighbors. Reasons cited were poor vision, dizziness, and poor mobility. Loss of appetite was cited by 30% of this sample. Half of the older adults interviewed in this pilot study experienced a weight change of 10 pounds in the previous 6 months. In this sample, 30% ate alone most of the time. None of those interviewed for this pilot ate fewer than two meals a day.
One person in this sample answered Yes to not always having enough money to buy food - the risk factor assigned the most points (4) in the DETERMINE Checklist. One gender difference noted in this sample was that none of the men lived alone or cooked for themselves. One man helped his wife with cooking responsibilities. The others depended on their spouses or another family member for meal preparation.
This pilot study compared two tools designed for use with community-dwelling older adults, to a hospital admission nutritional screening. AU of those screened by a dietician as at nutritional risk on admission to acute care, were also screened as at nutritional risk by the NSI tool, DETERMINE Your Nutritional Health Checklist. A second tool, the Level I Screen, does not have a scoring system, nonetheless, it also identified these seniors as at nutritional risk. Additionally, the Level I Screen provided expanded information on specific areas of nutritional deficiency and calculated BMI.
Only one person answered Yes to eating few fruits or vegetables in the DETERMINE Checklist, yet 70% ate less than the recommended amounts of fruits and vegetables according to the Level I Screen, and the entire sample ate inadequate amount of all four categories assessed (i.e., fruits, vegetables, dairy, grains). The added specificity provided by the Level I Screen gave a more complete picture of dietary intake than the "I eat few fruits or vegetables or milk products" question in the Checklist. This additional information may be useful for nutritional education targeting dietary deficiencies.
Poor nutrition is believed to occur with increasing frequency with aging (Wallace, Schwartz, LaCroix, Uhlmann, & Pearlman, 1995). Two nutritional risk factors identified by both tools were present in all those interviewed. A response of "I have an illness or condition that made me change the kind/amount of food I eat" is not surprising in a sample of older adults admitted to acute care. However, for most of those interviewed, the nutritional decline had occurred over a long period of time, suggesting that early nutritional intervention might have had an impact on the need for hospitalization. It is estimated that 85% of noninstitutionalized older individuals have one or more chronic conditions that could improve with proper nutrition and that up to 50% have clinically identifiable problems that require nutritional intervention (CornoniHuntley et al., 1985).
Polypharmacy was the second risk factor present in the entire sample. All those older adults took three or more prescribed or over-the-counter drugs daily, a finding consistent with the literature. Independent elderly individuals take, on average, three or more drugs (Morrisson, 1997). Multiple drugs increase the possibility of interaction effects, side effects, and reduced appetite (Lipschitz, Ham, & White, 1992). Loss of appetite, another major cause of undernutrition in older adults (Chapman & Nelson, 1 994), was reported by 30% of the sample. Loss of appetite may lead to weight loss. Half of those interviewed for this pilot study reported an unintended change m weight of 10 or more pounds in the previous 6 months.
Several studies have shown that weight loss in the year prior to hospital admission is highly predictive of complications during hospitalization among older adults (Sullivan & Walls, 1995). Weight loss in older adults has been associated with depression (Thompson & Morris, 1991). Depression occurs in one of eight older adults (Lipschitz et al., 1992), often following loss of a spouse. A measurement of depression was not included in either the DETERMINE Checklist or the Level I Screen.
Reduced mobility in later life can impact nutrition by making shopping and cooking more difficult - a problem for 70% of this sample. Among non-institutionalized older adults, 50% of those 85 and older need assistance in performing everyday ADLs such as bathing, dressing, or preparing meals (U.S. Census Bureau, 1996). Older adults with health problems and marginal functional status may require extensive support from family, friends, and social support agencies.
The highest score in the DETERMINE Checklist was an 81 -year-old woman who lived alone and answered Yes to the DETERMINE Checklist statement, "I don't always have enough money to buy the food I need." Studies have found a significant difference in nutritional intake between individuals with low and high socioeconomic status (Ryan & Bower, 1989; Tayback, Kumanyika, & Chee, 1990). As many as 40% of older Americans have incomes of less than $6,000 annually (Lipschitz et al., 1992). Among those ages 75 or older, 16% live in poverty (U.S. Census Bureau, 1996). The Level I Screen measures this risk with the statement, "Is unable or prefers not to spend money for food ($25 to $30 per person spent on food each week)" based on the U.S. Department of Agriculture minimum food expenditure of $30 per week per individual as necessary for meeting the RDAs (Barrocas et al., 1995). For this woman, living alone may have also meant loneliness, which has been shown to relate to dietary inadequacies (Walker & Beauchene, 1991) and skipping meals (Davis, Murphy, & Neuhaus, 1988), a practice present in none of those interviewed.
While the DETERMINE Checklist provides a cruder measure of fruit, vegetable, and dairy intake than the Level I Screen, it should be kept in mind that this tool was intended for self-administration by older adults as a tool to increase nutritional awareness among older adults, not as a measurement of malnutrition.
The proportion of overweight and obesity in this sample was higher than expected. Overweight is defined as a BMI between 25 (the NSI upper limit of healthy weight [American Academy of Family Physicians, 2003]) and 30 (the Centers for Disease Control and Prevention  cutoff for obesity). This means that 40% of this sample were overweight and 50% were obese. Obesity continues to increase rapidly in the United States. Mokdad et al. (1999) report the prevalence of obesity among non-institutionalized adults in the United States has increased from 12% in 1991 to 17.9% in 1998 (Mokdad et al., 1999) and continued to climb to 18.9% in 1999 (Mokdad et al., 2000). This growth is in men and women in all ages, sociodemographic groups and regions of the country (Flegal, Carroll, Kuczmarski, & Johnson, 1998).
Wisconsin, the site of this pilot ranks 24th in percentage of obese adults with a rate of 19.4% in 2000, up from 12.7% in 1991 (Mokdad et al., 2001). Looking specifically at elderly individuals, Dwyer, Gallo, and Reichel (1993) report obesity is present in 25% of older men, more than 33% of older women, and almost 66% of elderly Black women. Despite this high prevalence, none of these older individuals perceived themselves to be at nutritional risk, and all but one rated their nutritional health as good. Consequently, these at-risk older adults had no suggestions for ways they could improve their own nutritional health.
Several limitations of this study include the use of a convenience sample and the small sample size of 10 individuals. Another important limitation is the use of self-report for height used to calculate BMI. In more than half the medical records, height was not recorded on admission. Admission procedures at this hospital do not include a measured height, therefore all the data on height in this study are by self-report. Because height in older adults is commonly underreported, BMI calculated from self-report will underestimate true BMI. This means that the incidence of obesity is probably higher than these data would indicate.
A final limitation of this study is the poor psychometric properties of the DETERMINE Checklist. It has been found to have fairly low sensitivity, specificity, and positive predictive value in Medicare beneficiaries (Posner et al., 1993) and in apparently healthy European older adults (de Groot, Beck, Schroll, & van Staveren, 1998). Nonetheless these interviews provide important insight into the perceptions of a nutritionally at-risk sample of community-dwelling older adults.
Future direction for research should be an exploration of the nutritional status of old-oid individuals, a population that is growing faster than any other segment of the population and is disproportionately made up of women living alone and in poverty. Earlier detection of nutritional problems provides the opportunity for interventions before malnutrition affects current diseases, overall health, and quality of life in old age.
IMPLICATIONS FOR PRACTICE
While the DETERMINE Checklist has been used as a screening tool for nutritional risk, it has a number of limitations for clinical nurses seeking a useful tool to screen for nutritional risk in community-dwelling older adults. When used by health care professionals, the Checklist should be augmented with additional information, such as questions about weight and height, enabling calculation of BMI. A strength of the Checklist is that it is brief and easy-to-use, taking only a few minutes to complete. This is a great advantage when dealing with an elderly population who may have limited energy or patience for lengthy questionnaires. A brief tool is more likeiy to be used by busy health professionals who may be burdened with paperwork.
The difference in patient perception of nutritional health and the screening tool scores has important implications for nurse educators. Interventions based on standardized screening tools may not be successful if patients do not consider themselves at nutritional risk. None of those interviewed expressed a lack of knowledge or desire for more information about nutrition. Yet, these older adults were unaware of the specific recommendations of the food pyramid and were eating insufficient quantities of numerous food groups.
The rate of increasing obesity in all segments of the population including elderly individuals has important implications for practice because obesity is associated with diabetes, coronary heart disease, gallbladder disease, high blood cholesterol level, high blood pressure, or osteoarthritis (Kotz, Billington, & Levine, 1999). Jensen suggests that a sedentary lifestyle may be the dominant contributing factor to the growth of obesity in elderly individuals (Jensen & Rogers, 1998). Older adults need to be encouraged to incorporate more activity into their daily lives. Enjoyable ways to do this might include playing with grandchildren, Tai Chi lessons, walking in the mall, or gardening. Even small increases in physical activity scattered throughout the day may have a benefit in improving health, function, and quality of life.
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BODY MASS INDEX (BMI)