ABSTRACT PREDICTING FRAILTY AMONG COMMUNITY DWELLING OLDER ADULTS IN THE NHANES III. By Amy Ranalli Rudden

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1 ABSTRACT PREDICTING FRAILTY AMONG COMMUNITY DWELLING OLDER ADULTS IN THE NHANES III By Amy Ranalli Rudden Although frailty appears frequently in the gerontological literature, there is little consensus as to what it really means, and even less consensus as to how it should be measured. This study conceptualized frailty as a multifaceted syndrome that involves deficits not only in physical function, but cognitive and sensory function as well. A scale was designed using principal component analysis to measure the degree of frailty among 3, 358 subjects aged in the National Health and Nutrition Examination Study III (NHANES III). The scale was then used to identify demographic predictors of frailty in the sample. The scale supported the notion that adding other dimensions besides the traditional physical items resulted in a more comprehensive scale. When applied to the sample, the degree of frailty was surprisingly low. With regard to demographic predictors, it was found that gender was a very weak predictor, whereas age was the most powerful predictor. Implications for this study rest in both the theoretical and the practical realms. Future research is recommended in order to further explore the multifaceted concept of frailty.

2 PREDICTING FRAILTY AMONG COMMUNITY DWELLING OLDER ADULTS IN THE NHANES III A Thesis Submitted to the Faculty of Miami University in partial fulfillment of the requirements for the degree of Master of Gerontological Studies Department of Sociology and Gerontology by Amy Ranalli Rudden Miami University Oxford, Ohio 2005 Advisor Jennifer M. Kinney, Ph.D. Reader Jane Karnes Straker, Ph.D. Reader Khadijeh (Shahla) Mehdizadeh, Ph.D.

3 Table of Contents Chapter I-Introduction 1 Trends 1 Definition of Frailty 2 Frailty Versus Disability 3 Demographic Predictors of Frailty 4 Conceptual Model 4 Chapter II-Methodology 7 Operationalization 7 Data Source 7 NHANES III Variables Used to Create the New Frailty Scale 9 Sample Characteristics 10 Chapter III-Results 13 Sub-Scale Reliability 16 Construction and Scoring of the Frailty Scale 17 Total Variance Explained 18 Correlation Between Demographic Characteristics and Frailty 18 Differences Among Gender, Race, and Marital Status Groups 19 Multivariate Analysis of Demographic Characteristics on Frailty 20 Chapter IV-Discussion 22 Overview of Results 22 Limitations of the Results 23 Implications and Directions for Future Research 24 Conclusion 26 References 27 Appendix A-Rudden Frailty Scale 30 ii

4 List of Tables Table 1- Demographic Characteristics of Study Sample 11 Table 2- Health Characteristics of Study Sample 12 Table 3- Rotated Component Matrix 15 Table 4- Chronbach s Alpha Results 17 Table 5- Frailty of the Population by Subscale and Rudden Frailty Scale Total 18 Table 6- Bivariate Correlations Between and Among Demographic Characteristics of Frailty 19 Table 7- Analysis of Variance: Frailty by Gender, Race, Marital Status 20 Table 8- Summary of Regression Analysis for Predictors of Total Frailty 21 iii

5 List of Figures Figure 1- Brocklehurst s model of breakdown (Rockwood et al., 1994) 5 iv

6 Acknowledgements As all those who are close to me know, this thesis has been a very significant part of my life for the past two years. I am now pleased to give my heartfelt thanks to all those who unconditionally supported me through the entire thesis process. First, I would like to say thank you to my thesis committee-jennifer, Shahla, and Jane for lending me their support while I was at Miami. I would not have gotten as far as I did without all of your patience and expertise. Thanks also to my classmates- Kara, Holly, Kate, Sarah, Crissy, and Matt who listened to my never ending complaining both while we were in school and after graduation. You guys are the best, and will always have a special place in my heart. Finally, a big thank you goes to Kerstin for sticking by me through it all, and never giving up hope that this thesis would be completed. You are a friend in the truest sense and I truly would not have finished if it had not been for you. If all I gained from writing this thesis were a group of wonderful and amazing friends, it would have been well worth the time and effort. Thank You!! v

7 Chapter I. Introduction Because we are living in an aging society, one of the most pressing issues facing the United States today is the anticipated future health of our older population. According to 2000 census data, there were 35 million people over the age of 65 in the United States, representing 12.4% of the population (U.S. Dept. of Health and Human Services, 2000). There is consensus among those who study population aging that the percentage of persons 65 and older will continue to steadily increase throughout the 21 st century due to the aging of the baby boom generation and a declining fertility rate. By the year 2030, there will be approximately 70 million people over the age of 65, representing 20% of the population (U.S. Dept. of Health and Human Services, 2000). The 20 th century was witness to a dramatic increase in life expectancy. In the United States the average life expectancy increased from 47.6 in 1900 to 76.6 in 1998, in large part due to major advancements in the treatment and prevention of infectious disease, the development of new medical technologies, and improved hygiene and nutrition (Sahyoun, Lentzner, Hoyert, & Robinson, 2001). However, it is unclear as to whether we will continue to see major advances in life expectancy throughout the next century. According to a summary report from the Centers for Disease Control and Prevention, there is a lack of consensus on this issue (Sahyoun, Lentzner, Hoyert, & Robinson, 2001). Sahyoun et al. (2001) summarize arguments from both sides of the issue. On the one side, some experts say it is unlikely that we will see a reduction in mortality at the oldest ages without making dramatic medical advances against some of the most life threatening chronic conditions such as cancer, cardiovascular disease, cerebrovascular disease, and diabetes. In contrast, other experts argue that increased life expectancy is not only possible, but likely due to the current population being more robust, better educated, and undertaking more preventive strategies to avoid demise from chronic illness. Trends Although the maximum attainable life expectancy is an important issue and one of great debate, an equally important issue is whether these years of added life will be spent in an active, productive fulfilling state, or one of frailty characterized by declining health, disability, and lingering chronic illness. Earlier research tended to support the expansion of morbidity 1

8 hypothesis, in which increased life expectancy is accompanied by increased morbidity, which in turn leads to an increased amount of time spent in a state of frailty (Fries, 1992; McCormick & Skrabanek, 1988). Fortunately, more recent studies have shown support for the compression of morbidity hypothesis. These studies indicate a clear decline in the prevalence of disability (and in turn frailty) among the 65 and older population (Manton, Corder, & Stallard, 1997; Rothenberg, Lentzner, & Parker, 1991). Despite evidence that the proportion of older persons who are frail or disabled appears to have declined (Manton, Corder, & Stallard, 1997; Freedman & Soldo, 1994; Freedman & Martin, 1998), this evidence remains subject to controversy and debate. Regardless of whether the expansion or compression of morbidity hypothesis proves to be confirmed, the fact that the older population is increasing and will continue to increase throughout the next century cannot be disputed. This results in an increase in the absolute numbers of frail older people even if the prevalence of frailty declines (Gillick, 2001). According to a report from the U.S. Senate Special Committee on Aging, frailty currently affects 6.5 million people over the age 65 (U.S. Dept. of Health and Human Services, 1988). It is projected that this number will increase to over 10 million by the year Therefore, preventing frailty in those who are not affected and reducing it in those who are is one of the greatest challenges of the 21 st century (Gillick, 2001). Definition of Frailty In 1991 the National Institute on Aging allocated $41.9 million for research related to physical frailty, including its prevention and treatment (Cox, 1993). Although the term frailty has and continues to appear frequently in the gerontological literature, there seems to be little consensus as to what the term actually means. Definitions of frailty can best be viewed in terms of a continuum, which progresses from the very narrow and specific to the broad and comprehensive. For example, some researchers suggest that frailty is synonymous with disability (American Medical Association, 1990; Guralnik & Simomsick, 1993; Lawton, 1991), whereas others define frailty as a syndrome or a conglomeration of deficits in various areas of function (Buchner & Wagner, 1992; Rockwood et al., 1994; & Stawbridge et al., 1998). Thus our estimates of the prevalence of frailty are likely to differ and are dependent upon how the term is defined (Strawbridge et al., 1998). For example, one group of researchers who sought to evaluate 2

9 a self-report screening instrument to predict frailty outcomes in aging populations equated frailty with the need for nursing home placement, the receipt of long-term home care services, or simply having been deemed eligible to receive such services (Brody, Johnson, & Ried, 1997). Other researchers have categorized persons as frail based on the prevalence of certain chronic conditions that are commonly associated with old age or the presence of any single condition that a person characterizes as serious or restricting (Cox, 1993; Winograd, Gerety, Chung, Goldstein, Dominguez & Vallone, 1991), and others argue that there are certain illnesses considered to be marker conditions for frailty such as confusion, falls, immobility, incontinence, and pressure ulcers (Winograd, Gerety, Brown & Kolodny, 1988). Yet other researchers, as cited in Rockwood et al. (1994), conceptualize frailty as being synonymous with physical disability. These researchers assert that frailty, like disability, can be measured by a person s level of difficulty in completing activities of daily living (ADLs). Although it is probably safe to say that dependence on others to complete ADLs is a sufficient condition for frailty, it is less clear whether such dependence is a necessary condition for frailty (Rockwood et al., 1994). According to Strawbridge and colleagues (1998), the notion of equating frailty with disability is problematic because an older adult may have difficulty walking yet function rather well in all other physical activities. In essence, just because someone has a physical disability does not necessarily mean that they are frail. Strawbridge et al., argue that frailty should be defined more comprehensively and thus be measured by a variety of criteria such as functional disability, cognitive deficits, and other mental disorders, such as depression (Strawbridge et al., 1998). Additional criteria sometimes used to define persons as frail include sensory impairments, the adequacy of their social support systems, and the difficulties posed by the environment in which they live (Strawbridge et al., 1998). Thus, frailty can be thought of as a syndrome and can be defined as a combination of conditions and losses of capability, which make the elderly person more vulnerable to environmental challenge (Strawbridge et al., 1998). Frailty vs. Disability Frailty differs from disability in that frailty is characterized by an unstable state with a risk of functional loss so great that even a minor event may upset the delicate balance, therefore thrusting the individual into a state of disability and dependence (Rockwood et al., 1994). Thus, 3

10 frailty can be regarded as a precursor state to disability and dependence on others for ADLs, and is represented by a state of reduced physiologic capacity that is either not severe enough to interfere with the major activities required for daily living, or is compensated for by alternative strategies (Buchner & Wagner, 1992). In other words, people have a given amount of stamina that diminishes over time until they reach a threshold beneath which they are considered frail (Rockwood et al., 1994). Demographic Predictors of Frailty Research has shown that certain demographic variables can act as predictors of frailty, though most focus specifically on disability. For example, not much information is available in regard to race/ethnicity and frailty, due to the fact that research has focused on race and physical disability. This narrow research finds that non-whites are significantly more likely to report physical disabilities than whites (Jette, Crawford & Tennstedt, 1996; Johnson & Wolinsky, 1994; Zsembik, Peek & Peek, 2000). However, in a study by Strawbridge et al. (1998), which focused on frailty, it was found that there was little difference in frailty by ethnicity. Overall, frailty was found to be around one and one-half times higher in women than in men (Brody, Johnson & Ried, 1997; Smith & Baltes, 1998). However, Strawbridge et al. (1998) found that men had a higher incidence of frailty than women, though the difference was not statistically significant. In addition, an increase in age was found to have a substantial predictive ability on frailty (Brody, Johnson & Ried, 1997; Brown, Renwick & Raphael, 1995; Strawbridge et al., 1998). Education is an additional factor that predicts disability (Peek & Coward, 2000), though not much has been found on frailty specifically. However, Strawbridge et al. reported that increased education was related to a decrease in the prevalence of frailty. Conceptual Model Rockwood and associates (1994) took the notion of precariousness a step further and developed a dynamic model of frailty based on Brocklehurst s (1985) model of breakdown. This dynamic model of frailty (see Fig. 1) incorporates both biomedical and psychosocial factors and acknowledges that these factors are complexly intertwined in their function to maintain or threaten a person s independence (Rockwood, et al., 1994). The model is conceptualized as a scale with assets on one side and deficits on the other. Assets are those factors that help a 4

11 person to maintain his/her independence in the community. Additional assets not depicted in figure 1 include: social supports, spirituality, functional capacity, and the presence of a caregiver. In contrast, deficits are those factors that threaten independence: chronic illness, functional or cognitive incapacity, dependence on others for ADLs, and caregiver stress or burden (Rockwood et al., 1994). For those who are well, the assets profoundly outweigh the deficits so the scales are out of balance in a favorable direction. As people accumulate deficits they become increasingly more frail until the scales are in a precarious balance at which point even a small additional deficit, medical or social, may tip the scales in favor of the deficits at which point the person will be considered disabled. This model is dynamic because positive and negative changes in status occur as a result of the complex interaction of assets and deficits. Figure 1- Brocklehurst s model of breakdown Dynamic model of frailty in elderly people, in which the balance between assets (left) and deficits (right) determines whether a person can maintain independence in the community. Despite the emergence of this, and other comprehensive, dynamic conceptualizations of frailty (Brocklehurst, 1985; Witten, 1985), the current instruments and methods for assessing frailty rarely encompass more than the individual s capacity for physical functioning (Cox, 1993). This has resulted in only a small portion, presumably the most frail, being deemed eligible to receive services under most program criteria. If we are to ultimately succeed at identifying those at risk for frailty and developing interventions aimed at prevention of this syndrome, it is essential that our screening tools be more comprehensive. Therefore, the overarching research questions addressed in this study are: 1) what combination of sensory, cognitive and physical capabilities provides a comprehensive measure 5

12 of frailty and 2) given a comprehensive frailty measure, what demographic characteristics of older persons are the most related to frailty? Specifically, this study seeks to use the work of Buchner and Wagner (1992), Rockwood et al., (1994), and Strawbridge et al., (1998) as guides to develop an instrument that is more comprehensive than scales based solely on physical functioning (such as the ADL scale). In addition, the study seeks to identify demographic predictors of frailty using the developed scale applied to the NHANES III. 6

13 Chapter II. Methodology Operationalization For this study, operationalization of the term frailty is modeled after, but not identical to, the work of Strawbridge et al. (1998). Because frailty is not a specific disease or problem, but rather a syndrome involving numerous problems and losses of capability, we must assure a measurement of frailty that encompasses the multiple domains upon which symptoms can be manifested. Based on previous research (e.g. Buchner & Wagner, 1992; Fried, 1992; Guralnik & Simonsick, 1993), the domains used in this study include: physical, cognitive, and sensory capabilities. Data Source This research used data from the National Health and Nutrition Examination Survey (NHANES III), which was conducted from The NHANES III is a combination of the National Health Examination Survey, which was used to assess the amount, distribution, and the effects of illness and disability in the United States, and the National Nutrition Surveillance System, which measured the nutritional status of the US population over time. Four NHANES surveys have been conducted since 1970: 1. NHANES I ; 2. NHANES II ; 3. Hispanic Health and Nutrition Examination Survey ; and 4. NHANES III In addition, the NHANES Epidemiological Follow-Up Survey is an ongoing project that has been conducting interviews with the NHANES I population in order to provide a longitudinal picture (CDC, 2000). The overarching goals of the NHANES are to estimate the prevalence of various diseases and risk factors within the United States; analyze the risk factors for selected diseases; explore emerging public health issues; examine the relationship between diet, nutrition, and health; monitor trends in risk behaviors and environmental exposures; and monitor trends in the prevalence, awareness, treatment and control of various diseases (CDC, 2000). This study used data exclusively from the NHANES III. The NHANES III was designed to obtain nationally representative information on the health and nutritional status of the population in the United States through interviews and direct physical examinations. The NHANES III includes the responses of 33,994 people aged two months and older from selected 7

14 households across the United States. Sampling was conducted using a complex, stratified, multistage, probability design (U.S. Dept. of Health and Human Services, 1998). The NHANES III had a response rate of 86%. Minority populations accounted for 30% of the sample. In addition, infants and children between one and five years of age and older adults aged 60 and above were sampled at a higher rate. The NHANES III was the first NHANES to include infants as young as two months and to remove an upper age limit for adult participants. Also, the NHANES III was the first NHANES survey to allow for the physical examination portion of the survey to be conducted in the homes of those persons who were unable or unwilling to go to the exam center, primarily very young children and the elderly (U.S. Dept. of Health and Human Services, 1998). Data used in this research derived from the Adult Household Data and Examination Data sections. The Adult Household Data file contains 20,050 cases and provides information on adults 17 years of age and older. The Household Adult questionnaire was administered in-person by trained field staff and questions were asked either directly to the respondent or to a proxy respondent. This section of the survey included questions on topics such as health service usage, selected health conditions and diseases, cognitive orientation, health insurance, nutrition, sensory impairment, exercise, functional impairment, use of alcohol and tobacco, vitamin and medication usage, a three-point blood pressure measurement, and demographic data (U.S. Dept. of Health and Human Services, 1998). The examination data file contains 31,311 cases and provides information on persons aged two months and older. This file contains demographic data, information on selected health conditions, diet and nutrition information, information on the use of alcohol, drugs and tobacco, a physician s examination, a physical function evaluation, questions about medication usage, a blood pressure measurement, height, weight, and body measurements, as well as a battery of other tests used by health professionals to assess an individual s health status. The examination portion of the survey was administered to respondents at either the medical examination center (MEC) or in the respondents homes. The home version of the survey was conducted for those aged two through 11 months and those 20 years and older who were unable to visit the MEC. The home examination consisted of an abbreviated version of the MEC examination (U.S. Dept. of Health and Human Services, 1998). Because conditions leading to frailty are more likely at older ages, only data on persons age 70 and older were used in this study. As such, data on 3,358 individuals were included in this research. 8

15 NHANES III Variables Used to Create the New Frailty Scale In order to create a more comprehensive scale to measure frailty, three separate domains were examined for this study, using variables from the NHANES III survey. The three domains encompassed variables reflecting physical, cognitive and sensory impairments of respondents. Physical functioning. To create the pool of variables to measure the physical functioning section of the scale, 11 items that assessed the degree of difficulty with physical functioning tasks and whether participants use any assistive devices to complete various tasks (e.g. eating utensil, walker, cane, wheel chair) were used. The specific tasks that were used include: Doing chores around the house (e.g. vacuuming, sweeping), preparing own meals, managing money (e.g. keeping track of expenses, paying bills), walking from one room to another on the same level, getting in or out of bed, eating (e.g. holding a fork), dressing (e.g. tying shoes), assistance of another person for personal care needs (i.e. bathing), use of assistive devices to get around (e.g. cane, wheelchair), use of special eating utensils, and the use of any aids to help with dressing (e.g. button hooks, zipper pulls). One item, needing the help of another person in handling routine needs (e.g. everyday household chores, shopping, getting out), was not used because of a skip pattern that resulted in too few subjects answering the question. For seven of the items (doing chores around the house, preparing meals, managing money, walking from one room to another, getting out of bed, eating and dressing) the interviewer recorded the degree of difficulty that the subject reported with each task (1= no difficulty, 2= some difficulty, 3= much difficulty, 4=unable to do). The item that assessed whether the participant needed the assistance of another person for personal care needs was answered with a yes (2) or no (1). For the three items that asked about the use of assistive devices, the interviewer recorded whether or not the subjects used an assistive device (yes=2, no=1). Cognitive. Ten items are contained in the NHANES III orientation section. The first three items inquired as to how participants were informed about the survey (e.g. via letter). These items were not included because they were not integral to cognitive functioning. The fourth item screened participants under the age of 60 and was not included because only respondents over the age of 70 were included in this study. The remaining six items assessed orientation (i.e. date, day of week, street address, city etc.). For each item, the interviewer recorded whether the response was correct or incorrect (i.e. 1=correct, 2=error). For the day of 9

16 the week, the degree of the error was also recorded. These six items were selected for the pool because they were the most relevant questions to assess one s cognitive ability. Sensory function. The vision and hearing module contained 18 items. Because of extensive skip patterns in the interview schedule, which dramatically reduced the number of participants, only four items could be used. The four items measured the ability to: recognize a friend across the street, read regular newspaper print, hear most things that people say, and hear over the telephone. For each item, the participant indicated whether they were able to perform the activity (Yes=1) or are unable or have difficulty performing (No=2). Sample Characteristics Demographics. For the purposes of this study, subjects included in the analysis were those aged 70 and older who completed both the adult household survey and the examination portion of the NHANES III. A total of 3,358 subjects met the criteria for inclusion in the study and are described in Table 1. Although the majority of subjects were under the age of 80, subjects 80 and over made up almost 45% of the sample. Despite the greater numbers of women among the older population, numbers of men and women in the sample were roughly equal. Although the majority of subjects were non-hispanic Whites, minority populations accounted for 30% of the sample. Slightly less than half of the subjects reported either being married or living as married, and 46% were widowed, divorced, or separated. Two-thirds reported living with at least one other person. Almost one-third of the sample received a yearly income of less than $20,000 per year, and 60% of subjects reported having less than a high school education. Although the sample is weighted, the study did not use the weights, therefore the results do not reflect the population statistics due to oversampling or undersampling. 10

17 Table 1 Demographic Characteristics of Study Sample Characteristic Sample N Valid Mean (SD) Range Percent Age 78.2 (5.6) , , Gender Male 1, Female 1, Race/Ethnicity Non-Hispanic White 2, Non-Hispanic Black Mexican American Other Number of Persons in 2.1 (1.3) 1-10 Household 1 1, , Marital Status Married/living as married 1, Widowed/Divorced/Separated 1, Never married Education (in years of school) 9.4 (4.4) (<HS) 1, (HS) (College +) Income (in dollars) $25,897 $0-99,000 <$20,000 2, >$20,000 1, (27,968) Health. With respect to health status (see Table 2), approximately 62% of subjects reported their health as being excellent, very good, or good, whereas over one-third rated their health as fair or poor. Less than one-third of the sample reported having any functional limitations, as evidenced by the need for assistance with ADLs (such as walking, dressing, transferring, eating) and Independent Activities of Daily Living (IADLs) (such as preparing 11

18 meals, doing household chores, and managing money). However, according to a measure of body mass index (BMI), which is based on a measure of weight and height, over one-half of the subjects can be classified as being either overweight or obese based on CDC classifications (CDC, 1998). Furthermore, the overwhelming majority reported having at least one chronic condition and slightly over one-half reported having two or more chronic conditions. Chronic conditions included hypertension, diabetes, arthritis, respiratory conditions (such as emphysema, chronic bronchitis and asthma) and history of a heart attack or stroke. Table 2 Health Characteristics of Study Sample Characteristic Sample N Valid Percent Mean (SD) Range Self rated health Excellent/Very good Good 1, Fair/Poor 1, BMI (5.0) 2-52 Underweight Normal 1, Overweight 1, Obese No. of Chronic Conditions 1 chronic condition 1, or more chronic conditions 1,

19 Chapter III. Results This chapter is organized into three main sections. The first section describes the process used to construct a three dimensional measure of frailty. The second section displays bivariate associations between demographic characteristics and the total and subscale frailty scales. The third section presents the results of multiple regression analyses conducted to identify demographic predictors of frailty. Principal component analysis was used to develop a measure of frailty, which was comprised of three domains: physical, cognitive, and sensory impairments. The first step in the development of the scale was to identify items in the NHANES III that were conceptually consistent with the constructs of physical, cognitive, and sensory impairment frailty. An SPSS principal component analysis was conducted to examine the factor structure that emerged. The three-factor solution supported the three distinct domains as suggested in the frailty concept. To measure the first domain, physical frailty, NHANES III items that assessed independence in ADLs (five items), IADLs (three items), and the use of assistive devices (three items) were selected. An additional IADL item (assistance with routine needs) could not be included because of skip patterns in the data. To measure the second domain, cognitive frailty, all possible items of time and place orientation were selected (six items). Finally, to assess the third domain, sensory impairment frailty, four items assessing vision and hearing function were selected. A number of items could not be included due to skip patterns in the data. The components of the frailty scale were developed using factor analysis aimed at identifying the variables that are the strongest predictors of the physical, sensory, and cognitive domains of frailty. Before conducting the analyses, the suitability of the data for factor analysis was assessed by examining the correlation matrix for the presence of coefficients equal to or greater than 0.4. Bartlett s Test of Sphericity was statistically significant with a p-value of.000 and the Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.87 thus exceeding the recommended value of 0.6. Once the scale was created, it was applied to the NHANES III and tested using demographic predictors of frailty. According to a broad overview of the literature, determining a threshold (whether or not to include an item in the scale), for factor loading is both arbitrary and subjective. The literature 13

20 also revealed that most studies select a threshold of 0.3 or greater. A factor loading threshold of 0.4 was used in this study. Therefore, any item that resulted in a 0.4 factor loading or higher was considered substantial. Table 3 presents the pool of items originally included in the factor analysis, organized by conceptual domain along with their loading scores. 14

21 Table 3 Rotated Component Matrix Factor Physical Cognitive Component Component What is the day of the week? 2.7 E Sensory Component What is your complete address: Street 6.9 E E-02 What is your complete address: 5.2 E E-02 City/Town What is your complete address: State 2.9 E What is your complete address: Zip Code What is today s date? Difficulty doing chores around the E house Difficulty preparing own meals Difficulty managing your money Difficulty walking room to room, E E-02 level Difficulty getting in and out of bed E E-02 Difficulty eating E E-02 Difficulty dressing yourself E E-02 Use of assistive devices to get E E-02 around? Do you use any special eating E utensils? Use aids or devices to help you dress E Assistance of another person for E personal care needs With glasses, can you recognize a friend across the street? With glasses, can you read regular newspaper print? With aid, can you hear most things 7.4 E E that people say? Can you hear over the telephone? 9.5 E E

22 When factor analysis was run, only items that loaded at a 0.4 or higher were substantial and included in the scale. These items, for the physical domain were: doing chores around the house (e.g. vacuuming, sweeping), preparing own meals, managing money (e.g. keeping track of expenses, paying bills), walking from one room to another on the same level, getting in or out of bed, eating (e.g. holding a fork), dressing (e.g. tying shoes), assistance of another person for personal care needs (i.e. bathing), and use of assistive devices to get around (e.g. cane, wheelchair). When factor analysis was run on the cognitive function items, all items were loaded and therefore included in the scale, except for what is today s date. This created the cognitive domain with the five following items: what is the day of the week?, what is your complete address: street?, what is your complete address: city/town?, what is your complete address: state?, and what is your complete address: zip code?. With respect to the items that were conceptually classified as measuring sensory function, when factor analysis was run, all four items loaded on the sensory domain. Those items included: with glasses, can you recognize a friend across the street?, with glasses, can you read regular newspaper print?, with aid, can you hear most things people say?, and can you hear over the telephone?. Sub-Scale Reliability Chronbach s alpha reliability analysis was conducted on the items in the three domains to see if all the items were indeed a good fit. The test explored whether the scale would be more reliable if any one item were deleted. Table 4 presents the results of these analyses. As can be seen in the table, for the physical and sensory domains, all items were retained (standardized item alpha and , respectively). However, on the cognitive domain, one question was deleted. With all five items, the alpha was , and when the question what is the day of the week? was deleted, the alpha increased to , thus the question was deleted from the scale. The alpha for all items combined in the total scale was not obtained. 16

23 Table 4 Chronbach s Alpha Results Question Alpha if Item Deleted Cognitive Domain: Alpha.7328 What is your complete address: Street?.5473 What is your complete address: City/Town?.6452 What is your complete address: State?.6400 What is your complete address: Zip Code?.6260 Physical Domain: Alpha.9022 Degree of difficulty doing chores around the house?.8921 Degree of difficulty preparing own meals?.8790 Degree of difficulty managing your money?.8958 Degree of difficulty walking room to room, 1 level?.8813 Degree of difficulty getting in and out of bed?.8863 Degree of difficulty eating?.8982 Degree of difficulty dressing yourself?.8865 Use of assistive devices to get around?.8981 Assistance of another person for personal care.9001 needs? Sensory Domain: Alpha.5764 With glasses, can you recognize a friend across the.4975 street? With glasses, can you read regular newspaper print?.4979 With aid, can you hear most things that people say?.4905 Can you hear over the telephone?.5381 Construction and Scoring of the Frailty Scale Based on the preliminary analysis, the Rudden Frailty Scale was created using simple index construction, which involved summing the 17 items. The Rudden Frailty Scale is presented in Appendix A. Using this technique, each item was weighted equally, based on the small variation in loading and the reasoning that multiple correlation between the scale and the total set of factors does not change a large amount for small variations in the weighting (Kim & Mueller, 1978). With respect to scoring, possible responses for the physical, cognitive, and sensory items ranged from one to four, depending on the question that was asked. To score the scale, the responses for all 17 items were summed, resulting in an overall frailty score. 17

24 Total Variance Explained: Based on principal component analysis, 26% of the variance within the frailty scale was explained by the physical items. Thirteen percent was explained by the cognitive items, and nine percent was explained by the sensory items. When the Rudden Frailty Scale was computed for participants in the NHANES III sample (N= 3,358), frailty scores ranged from 17 (no impairment on any of the items) to 44 (high impairment on each item). The mean score was 19.6, with a standard deviation of 4.4 for the overall frailty score. A large portion of respondents (44%) reported having no frailty at all in any of the domains. The median score was 18, still very low in the frailty scale. Table 5 presents the results for the three subscales that comprise the Rudden Frailty Scale. With respect to the cognitive domain, the impairment mean was very low with an average score of 4.4 and a SD of.91 (Range= 4-8). Eighty-three percent of respondents had no cognitive impairment at all. The sensory impairment mean was also low, with an average score of 4.4 and a SD of.82 (Range= 4-8). Almost three-fourths of respondents (73%) had no problems with any of the four sensory factors. Physical frailty scores ranged from 0 to 36, with a mean of 11.3 (sd=4.3). Over half (55%) of respondents reported no impairment at all in the physical frailty domain. Table 5 Frailty of Population by Subscale and Rudden Frailty Scale Total Domain Mean (SD) Range Percent with No Frailty Physical 11.3 (4.3) % Cognitive 4.4 (0.91) % Sensory 4.4 (0.82) % Total (all three of above domains) 19.6 (4.4) % Correlation Between Demographic Characteristics and Frailty Table 6 presents a correlation matrix of key demographic characteristics and the composite frailty score. As can be seen in the table, all of the correlations reached statistical significance, but in general, the magnitude of the correlations was low. Age and household size show a positive relationship to frailty. As would be expected, income and education are negatively related. 18

25 Table 6 Bivariate Correlations Between and Among Demographic Characteristics and Frailty Variable Age Household Total Family Education Total Frailty Size Income Age ** -.096** -.067**.262** Household Size Total family income ** -.203**.119** ** -.141** Education ** Total Frailty ** Correlation is significant at the.01 level (two tailed) Differences Among Gender, Race, and Marital Status Groups A series of analyses of variance were conducted to determine whether there were differences in frailty as a function of gender, race/ethnicity, and marital status. The results of these analyses are presented in Table 7. Household size and education were not included in these analyses because they were not clearly defined categorical variables. As can be seen in the table, significant differences were found for gender, race, and marital status. With respect to gender, women had significantly higher mean frailty scores than did men. The mean score for married respondents was significantly lower than for those who were widowed/divorced or separated, as well as never married. Another statistically significant difference found in the demographic variables examined showed that race was a factor that influenced degree of frailty. Whites had a lower mean score on the frailty scale than Blacks, Mexican Americans, or others. 19

26 Table 7 Analysis of Variance: Frailty by Gender, Race, and Marital Status Characteristic Total N Mean Frailty Score (SD) F statistic (Sig.) Gender 4.3 (0.038) Male (4.2) Female (4.5) Race/Ethnicity 3.2 (0.023) Non-Hispanic White (4.4) Non-Hispanic Black (4.1) Mexican American (4.0) Other (5.4) Marital Status 9.5 (0.000) Married/Living as married (3.9) Widowed/Divorced/Separated (4.7) Never married (4.9) Demographic Predictors of Frailty In order to identify demographic predictors of frailty a series of multiple regression analyses were conducted. The independent variables used in the equations were selected based on previous reports in the literature and bivariate associations found in the present research. Specifically, these categories were age, gender, race/ethnicity, household size, and education. However, when regressions were run using race as a variable, it became clear that there was a possibility of an interaction term. Although it appears that race affects total frailty, it cannot be determined from this study. Future research in this area is suggested. Regression equations with total frailty and frailty subscales scores as dependent variables were constructed. In each equation age was entered first, followed by education, household size, and gender (which was dummy coded). Results of the multiple linear regression showed that age has the greatest impact on frailty (see Table 8). Specifically, as age increases, frailty increases. When age was held constant, education also showed a significant effect on frailty; those with lower education, had higher frailty scores. With regard to household size, when both age and education were held constant, it was found that as household size increased, the level of frailty also increased. Finally, with relation to gender, holding age, education, and household size constant, it was found that females have a higher frailty score than males. Results in Table 8 show that the demographic model described above had a limited influence on explaining variance in frailty scores. Only 11% of the variation in frailty was 20

27 explained by age, education level, household size and gender combined. Age accounted for the largest percentage of variation (6.5%), followed by education (3.3%), household size (0.9%) and finally gender (0.6%). This chapter described the results of analyses used to construct the Rudden Frailty Score. In addition, demographic predictors of frailty were regressed on the new frailty score in order to determine what respondent characteristics were most related to frailty. The next chapter discusses the implications of these findings for future research in further defining and operationalizing the concept of frailty. Table 8 Summary of Regression Analysis for Predictors of Total Frailty Factor B β t Sig. R 2 R 2 Change Constant Age Education Household Size Gender

28 Chapter IV. Discussion Overview of Results This chapter begins with an overview and discussion of the results. It is followed by sections on the limitations of the data and the analytic processes. The chapter concludes with a statement on complications of the research, and suggestions for future research in this area. Using the NHANES III, a scale was created to measure frailty, that included information on three domains: physical, cognitive and sensory. The completed scale consists of 17 items; nine items in the physical domain, and four questions in each of the other two domains. The completed scale was applied to the sample of adults over the age of 70 to describe their level of frailty and to examine demographic predictors of frailty. When the scale was used to assess frailty among adults aged 70 and over in the NHANES III, it was found that the population tested had extremely low degrees of frailty. When other characteristics were controlled for, women were more frail than men, people with lower levels of education were more frail than people with higher levels of education, those that live with a larger number of people in their household were more frail and those who were older were more frail. Results showed that those never married and those divorced/separated/widowed were more frail on average, than those married. These results are similar to those shown in previous research on predictors of disability (Palmore & Burchett, 1997; Peek & Coward, 2000). Race was an issue that, although important, could not be examined conclusively due to other interacting variables. Age, household size, gender and education explained about 11% of the variation of frailty in the sample, with age being the most important predictor. Gender accounted for less of the variance than did household size or education. The scale supported the idea that adding other dimensions besides the traditional physical items resulted in a more comprehensive scale. The scale followed the model of Strawbridge et al. (1998) and embraced the comprehensive and dynamic model described by Rockwood et al. (1994). The results from this research are congruent with the findings in Strawbridge et al. (1998) where prevalence of frailty was significantly related to education and age, but no statistically significant difference was found with regard to gender. Although these results showed a statistically significant relationship, it was a less powerful predictor when compared to 22

29 education, age and household size. These results support Strawbridge et al. (1998) who suggested that the additional factors that are examined in this scale minimize the confounding variables associated with gender. The broader measures used in this scale may simply be a more sensitive measure of underlying physical, cognitive and sensory problems than the activities of daily living or gross mobility measures used in many disability studies (Strawbridge et al., p. S13, 1998). For example, where women traditionally report more difficulty with activities of daily living, research shows that men typically have more sensory impairment (particularly hearing loss) in older age. Adding this second dimension levels the playing field and thus explains why gender was such a weak predictor of frailty. When applied to the NHANES III, the degree of frailty was surprisingly low. The mean was 19.6 in a scale that ranged from 17 to a maximum of 44. The percent with no frailty in the total scale was 44%, as opposed to 54.9% on the physical scale, 72.5% on the sensory scale and 82.5% on the cognitive scale. This shows that as the scale combined the three dimensions the prevalence of respondents with no frailty decreased, supporting the original hypothesis that frailty is a multi-dimensional concept. The results also suggest a possible hierarchy among frailty sub-dimensions and their likelihood of occurrence among the older population. Limitations of the Results This research is not without limitations. Some limitations derive from the NHANES III itself, while other limitations are due to the analytic strategy used in this research. One major limitation of the NHANES III is that it did not question adults that were in an institutional settings, presumably the most frail. This does not allow for the frailty scale to be generalized to older adults in general, but only to community-dwelling elders. Design issues are also another limitation of the survey. Because of numerous screening questions, several factors (such as assistance with routine needs) were asked of too few respondents to be included. In addition, the survey items were based primarily on examining one s physical state, with only a limited amount of information gathered on psychosocial factors, such as social support, mental health, and spirituality. A second limitation with the NHANES III involves the survey design and the use of skip patterns. For example, the sensory impairment domain contained 18 items. However, only four items were answered by the entire sample and were the ones that could be used in this study. 23

30 Another limitation with the NHANES III is that it is a cross-sectional study. Thus it can only be concluded that the variables measured are correlated with frailty at one point in time. As a result, there is no way to examine causes leading to frailty. Finally, because the scale was only tested on a population of community dwelling elders as opposed to the entire older population, the study focused only on a presumably less frail population. For example, applying the frailty scale to persons in institutional settings would likely produce very different results in frailty prevalence. The second set of limitations involves the analytical strategy used in this research. An examination of race by gender interactions in the regression model suggested some additional explorations that were beyond the scope of this study. Second, the frailty scale could not be validated against popularly used scales such as the ADL scale, because ADLs themselves were included in the instrument. Also, although the literature supports the summation of item scores versus the use of factor weights, one might argue for the use of factor scores because the physical subscale items significantly outnumbered the items in the other two subscales and thus contributed more to the calculations of overall frailty. On the other hand, it can also be argued that because the physical domain accounted for the greatest proportion of variance (11%) in the frailty scale, summing was a valid method of scale development. Implications and Directions for Future Research Implications of this study rest in both the theoretical and the practical realms. At the theoretical level, having a specific definition of frailty that distinguishes it from disability emphasizes the notion that frailty is a multifaceted syndrome that encompasses much more than the physical domains traditionally associated with disability. This broader view of frailty can also be used as a way to provide insight to policy makers into the multi-faceted needs of the elderly population. On a practical level, because this scale is short, it can easily be applied with minimal monetary and staff investment, allowing for quick identification of the degree of frailty in older adults. In addition, because it covers multiple domains, services can be targeted to specific areas of need. Furthermore, not only could more people receive services, it would also allow targeting specific interventions to frail older adults. 24