ORIGINAL INVESTIGATION. Factors Associated With Recovery of Independence. among newly disabled older persons.

Transcription

1 ORIGINAL INVESTIGATION Factors Associated With Recovery of Independence Among Newly Disabled Older Persons Susan E. Hardy, MD; Thomas M. Gill, MD Background: Recent evidence indicates that most older persons who develop disability in their activities of daily living (ADLs) regain independent function, but many of these persons subsequently experience recurrent disability. The aims of this study were to identify independent predictors of time to and duration of recovery of independent ADL function among newly disabled communitydwelling older persons. Methods: From a cohort of 754 persons 70 years or older, we studied the 420 participants who experienced at least 1 episode of disability involving 1 or more key ADLs (bathing, dressing, walking, or transferring) during a median follow-up of 53 months. Comprehensive evaluations at baseline and every 18 months included demographic, medical, cognitive, psychological, social, behavioral, and physical factors. Activities of daily living function and hospital admissions were assessed during monthly telephone interviews, with a completion rate of 99.4%. Results: Of the 420 newly disabled participants, 342 (81.4%) recovered independent ADL function after a mean±sd of 4.9±0.5 months. In multivariable proportional hazards analysis, habitual physical activity, mild disability (1-2 ADLs) at onset, and hospitalization in the month of disability onset were independently associated with shorter time to recovery. Among participants who recovered, 251 (73.4%) experienced recurrent disability or death after a mean±sd of 7.3±8.5 months. Younger age, greater habitual physical activity, higher functional self-efficacy, and shorter duration of the prior disability episode were independently associated with longer duration of recovery. Conclusions: Habitual physical activity is an independent predictor of time to and duration of recovery of independent ADL function among newly disabled community-dwelling older persons. Because the other independent predictors for time to recovery differ from those for maintenance of recovery, different mechanisms may underlie these 2 recovery outcomes, suggesting that different interventions may be required to promote recovery than to maintain independent ADL function after recovery. Arch Intern Med. 2005;165: Author Affiliations: Department of Internal Medicine, Yale University School of Medicine, New Haven, Conn. Financial Disclosure: None. DISABILITY IN BASIC ACTIVIties of daily living (ADLs), such as bathing and walking, is common among communitydwelling older persons 1 and is often considered progressive or permanent. Previous research, however, has shown the dynamic nature of disability. 2 In a recent study that included monthly ADL assessments, we demonstrated recovery rates substantially higher than those previously reported, 3 with more than 80% of newly disabled older persons regaining independence. However, the time course of recovery was highly variable and nearly half of those who recovered developed recurrent disability within 6 months. 3 Given this variability, more accurate prognostic information is needed about recovery among newly disabled older persons. Prior studies have either focused on recovery after specific events such as a hip fracture 4-6 or used assessment intervals of 6 months or longer, 1,7,8 thereby underestimating the incidence of disability. 9,10 The objectives of this study were to identify independent predictors of time to and duration of recovery of ADL independence among newly disabled communitydwelling older persons. By improving prognostication, we hope to empower older persons, their families, and their clinicians to set realistic goals and plan for appropriate care. Also, some predictors may be modifiable and, hence, amenable to intervention. 106

2 METHODS STUDY POPULATION Participants were drawn from an ongoing longitudinal study, described in detail elsewhere, 3,11 of 754 community-dwelling persons, 70 years and older, who were nondisabled in 4 key ADLs (bathing, dressing, walking, and transferring). Potential participants were members of a large health plan and were excluded for life expectancy of less than 12 months, plans to move out of the area, or inability to speak English. Only 4.6% of persons contacted refused screening, and 75.2% of those eligible agreed to participate. To ensure a sufficient incidence of disability, persons with slow gait speed were oversampled. 3,11 Participants underwent comprehensive in-home assessments at baseline and at 18 and 36 months, and had monthly telephone interviews for a median of 53 months. DATA COLLECTION The comprehensive assessments were completed by trained research nurses using standard instruments. Data were collected on candidate predictors from several domains: demographic, medical, 11 cognitive, 12 psychological, 13,14 social, 15,16 behavioral, 17,18 and physical 11,19-22 (Table 1). The amount of missing data was less than 1% for all candidate predictors in the baseline assessments and less than 5% for subsequent assessments. During monthly telephone interviews, disability in each of the 4 key ADLs was assessed with the question, At the present time, do you need help from another person to perform the task. Participants who required personal assistance with at least 1 ADL were considered disabled. The reliability of our disability assessment was substantial for reassessments within 48 hours ( =0.75) and almost perfect for reassessments completed the same day ( =1.0). 9,23 Disability in 3 or 4 ADLs was defined as severe 24 ; and in 1 or 2 ADLs, as mild. Recovery occurred when a participant reported no disability in any of the 4 ADLs. Restricted activity, defined as staying in bed for half a day or cutting down on one s usual activities, 11 and overnight hospitalizations during the past month were also ascertained. Follow-up interviews were included through May 19, 2003, when 151 (20.0%) of the participants had died and 31 (4.1%) had dropped out. Data are otherwise available for 99.4% of the remaining monthly interviews. STATISTICAL ANALYSIS Potential prognostic factors, chosen from factors previously associated with either disability 19,21,25-30 or recovery, 1,4-8 were evaluated during the most recent comprehensive assessment or the telephone interview in the month of disability onset. Variables were modeled as continuous unless there was evidence of a nonlinear relationship with either outcome. To observe the statistical assumption of independence, we included only the first episode of disability for each participant. We assessed the associations of potential prognostic factors with time to and duration of recovery using proportional hazards regression, because these models allow full use of our monthly data. Furthermore, when recovery is evaluated at a single time point, as in logistic regression analysis, any intervening transitions between disability and independence are ignored. Factors associated with time to outcome in the bivariate analyses (P.10) were considered in the multivariable analyses, which were adjusted for the time from the most recent comprehensive assessment to disability onset. Many of the potential predictors were highly correlated, particularly the physical measures, physical activity, and self-efficacy (Spearman r for all comparisons, ). Because of this high collinearity, backward elimination with a criterion of P.05 was used to identify the independent predictors. 31 All multivariable models had at least 20 events per variable. 32 All P values are 2-tailed, and all analyses were performed using SAS statistical software, version Time to Recovery Participants were entered into the analytic sample (n=420) at their first episode of disability and were observed until they recovered independence, died, or reached the end of follow-up. Participants who died were censored at the time of death in the primary analysis 34 and at the end of the study (May 19, 2003) in a secondary analysis. We defined zero time 35 as the first month of disability. Results were confirmed with logistic regression models of recovery at 3 months. To address the concern that recovery episodes lasting only 1 month might be due to measurement error, we repeated our primary analysis for recovery lasting 2 consecutive months or longer (ie, persistent ). Duration of Recovery Participants were entered into the analytic sample (n=342) at the time of recovery of independence. Duration was defined as the time from recovery to the first month of recurrent disability or death. Participants who experienced neither recurrent disability nor death were censored at the end of followup. In addition to the potential predictors considered for time to recovery, the duration of the preceding disability episode was considered as a potential predictor of duration of recovery. RESULTS The descriptive statistics for the potential prognostic factors among the 420 participants who experienced disability are presented in Table 1. Participants had a range of 0 to 6 chronic conditions. The most common conditions were hypertension (n=239), arthritis (n=156), diabetes mellitus (n=94), and myocardial infarction (n=89). Of the 420 participants, 342 (81.4%) regained independent ADL function after a mean±sd follow-up of 4.9±0.5 months; 215 participants (51.2%) recovered after a single month of disability. Among the remaining 127 participants, the most common patterns of recovery were stable disability until recovery (n=59) and a gradual decrease in the number of ADL disabilities (n=38). The characteristics of disability and recovery by specific ADL disabilities in the month of onset are presented in Table 2. Bathing disability was most common, and walking disability was least common, with most participants having other concurrent ADL disabilities. The patterns of recovery among the 4 ADLs were comparable. The bivariate associations of potential prognostic factors with time to recovery are presented in Table 1. In multivariable analyses, habitual physical activity, mild disability, and hospitalization remained independent predictors of time to recovery (Table 3). These same variables were independent predictors of recovery at 3 months. When the analysis was repeated for persistent recovery, the effect of hospitalization was considerably reduced (hazard ratio=1.05, P=.70). Censoring participants who died at the end of the study period had no effect on the results. 107

3 Table 1. Bivariate Associations of Potential Prognostic Factors With Time to Recovery and Duration of Recovery of Independent ADL Function Among Newly Disabled Older Persons Factor Measurement Details Time to Recovery (n = 420) Duration of Recovery (n = 342) Value* Hazard Ratio P Value Value* Hazard Ratio Demographic Age, y NA 81.2 ± ± Male sex NA 148 (35.2) (33.3) White race NA 380 (90.5) (90.6) Education, y NA 11.7 ± ± Living alone NA 176 (41.9) (41.2) Medical Chronic conditions 9 Self-reported and 2.0 ± ± physician-diagnosed Medications Prescription 7.2 ± ± and over-the-counter Body mass index Self-reported height 26.7 ± ± and weight Cognitive MMSE score 0 (low) to 30 (high) 26.1 ± ± Psychological Functional self-efficacy 0 (low) to 40 (high) Depressive symptoms CES-D: 0 (none) to 60 (many) Social Social activity 0 (low) to 30 (high) Social support MOS: 0 (low) to 28 (high) 21.9 ± ± Behavioral Habitual physical activity PASE: 0 (low) to 360 (high) 64.1 ± ± Smoking status Nonsmoker NA 141 (33.7) 1.00 NA 120 (35.2) 1.00 NA Former smoker NA 247 (59.1) (56.6) Current smoker NA 30 (7.2) (8.2) Alcohol use, AUDIT score 0 0 to (56.0) 1.00 NA 185 (54.7) 1.00 NA 1 0 to (18.0) (18.3) to (26.0) (26.9) Physical Timed rapid gait, s Back and forth over 12.7 ± ± a 3-m course Timed chair stands, s Up and down 3 times 12.4 ± ± Balance score SPPB: 0 (poor) to 4 (good) 2.3 ± ± Grip strength, kg Handheld dynamometer 21.4 ± ± Other Mild disability (1-2 ADLs) at onset NA 319 (76.0) (82.7) Hospitalized in the month of disability onset NA 230 (54.8) (58.8) Duration of prior disability episode, mo NA NA NA NA 3.3 ± Abbreviations: ADL, activities of daily living; AUDIT, Alcohol Use Disorders Identification Test; CES-D, Center for Epidemiological Studies Depression Scale; MMSE, Mini-Mental State Examination; MOS, Medical Outcomes Survey Social Support Scale; NA, data not applicable; PASE, Physical Activity Scale for the Elderly; SPPB, Short Physical Performance Battery balance component. *Data are given as mean±sd or number (percentage). Percentages are based on totals for each factor and may not total 100 because of rounding. Hazard ratios for continuous variables are per 1-point increase, except those for habitual physical activity, which are per 10-point increase. Hazard ratios for time to recovery can be interpreted as the relative hazard (similar to a relative risk) of recovering independent ADL function, with values greater than 1 indicating a higher likelihood of recovery. Hazard ratios for duration of recovery can be interpreted as the relative hazard of recurrent ADL disability or death, with values less than 1 indicating a lower likelihood of recurrent disability and, thus, a longer duration of recovery. Hazard ratios are adjusted for time from most recent comprehensive examination to disability onset. Hypertension, myocardial infarction, congestive heart failure, stroke, diabetes mellitus, arthritis, hip fracture, chronic lung disease, and cancer (other than minor skin cancers). Calculated as weight in kilograms divided by the square of height in meters. Alcohol use was nonlinearly related to both outcomes, and was categorized into quartiles. 0 indicates low-risk use; 40, higher-risk use. Data included only for duration of recovery. Time to recovery was determined for each participant s first disability episode, so there was no prior episode. P Value The descriptive statistics for the potential prognostic factors among the 342 participants who recovered are also presented in Table 1. Of these 342 participants, 251 (73.4%) experienced recurrent disability or death after a mean±sd follow-up of 7.3±8.5 months; 72 (21.1%) experienced only 1 month of recovery. Of these 72 participants, 57 (79.2%) had subsequent periods of independence, 46 (63.9%) had subsequent periods lasting 2 months or longer, and 37 (51.4%) were hospitalized or had restricted activity during the month of their recurrent disability. 108

4 Table 2. Disability and Recovery Characteristics for 420 Subjects by Specific ADL Disability in the Month of Disability Onset Characteristic Bathing (n = 293) Dressing (n = 224) Transferring (n = 139) Walking (n = 130) Concurrent disability in 1 other ADLs* 171 (58.4) 164 (73.2) 99 (71.2) 114 (87.7) Recovered* 226 (77.1) 166 (74.1) 95 (68.3) 88 (67.7) Duration of recovery, mo 6 (2-18) 6 (2-18) 8 (3-20) 7 (2-18) Recurrent disability 164 (72.6) 120 (72.3) 65 (68.4) 63 (71.6) Recurrent disability in same ADL 126 (76.8) 75 (62.5) 25 (38.5) 21 (33.3) Abbreviation: See Table 1. *Data are given as number (percentage) of the total in each group. Defined as complete recovery of independence in all ADLs. Data are given as median (interquartile range). Data are given as number (percentage) of those who recovered. Only one participant, disabled in bathing alone, experienced death without recurrent disability. Data are given as number (percentage) of those with a recurrent disability. For example, of those participants with a bathing disability who subsequently recovered full independence and then developed recurrent disability, 76.8% were again disabled in bathing. These results are consistent with the initial pattern of disability. Table 3. Independent Predictors of Time to Recovery of Independent ADL Function Among Newly Disabled Older Persons Characteristic Habitual physical activity, per 10 points Mild disability at onset (1-2 ADLs) Hospitalized in the month of disability onset Hazard Ratio (95% Confidence Interval)* P Value The associations of potential prognostic factors with duration of recovery are presented in Table 1. Age, habitual physical activity, self-efficacy, and duration of the prior disability episode remained independent predictors of duration of recovery in multivariable analyses (Table 4). These results did not change appreciably in subsequent analyses that omitted the 3 ADL items from the self-efficacy scale and that considered participants with only a single month of subsequent independence as nonrecovered for the remainder of the follow-up. In a model that did not include duration of the prior disability episode, the other 3 independent predictors remained the same, and no new candidate predictors were significant. COMMENT 1.04 ( ) ( ) ( ).05 Abbreviation: See Table 1. *Hazard ratios are adjusted for the time from the most recent comprehensive assessment to disability onset. Cognitive function, functional self-efficacy, and alcohol use were initially considered for the model, but were eliminated in the selection of the best model. Hazard ratios can be interpreted as the relative hazard of recovering independent ADL function, with values greater than 1 indicating a higher likelihood of recovery. In this prospective cohort study, which included monthly assessments of ADL function, we found that habitual physical activity, the initial severity of disability, and hospitalization in the month of disability onset were independently associated with time to recovery of independent ADL function among newly disabled communitydwelling older persons. Furthermore, among persons who had recovered, we found that habitual physical activity, Table 4. Independent Predictors of Duration of Recovery of Independent ADL Function Among Newly Disabled Older Persons Characteristic Hazard Ratio (95% Confidence Interval)* P Value Age (in years) 1.03 ( ).01 Habitual physical activity, 0.96 ( ).01 per 10 points Functional self-efficacy, 0.97 ( ).001 per point Duration of prior disability episode, per month 1.09 ( ).001 Abbreviation: See Table 1. *Hazard ratios are adjusted for the time from the most recent comprehensive assessment to disability onset and the duration of the preceding disability episode. Male sex, depressive symptoms, social activity, alcohol use, timed gait, timed chair stands, balance, grip strength, and hospitalization in the month of disability onset were initially included in the model, but were eliminated in the selection of the best model. Hazard ratios can be interpreted as the relative hazard of recurrent ADL disability or death, with values less than 1 indicating a lower likelihood of recurrent disability and, thus, a longer duration of recovery. age, self-efficacy, and the duration of the prior disability episode were independently associated with duration of recovery. Habitual physical activity was a strong independent predictor of time to and duration of recovery. Multiple previous studies have demonstrated a strong association between habitual physical activity and maintenance of functional independence, and several randomized trials have shown that exercise-based interventions can slow or prevent functional decline among older persons As a potentially modifiable factor, physical activity represents an attractive target for interventions designed to promote recovery and maintenance of ADL independence. We found that time to recovery is also dependent on the initial severity of disability and on hospitalization in the month of disability onset. Counterintuitively, hospitalization during the month of disability onset was associated with shorter time to recovery, indicating that older persons who develop disability in response to an event leading to hospitalization are more likely to re- 109

5 cover than those whose disability develops insidiously, perhaps because of gradual progression of underlying conditions. This association, which was not attributable to the censoring of participants who died, may reflect different pathways to disability, such as the catastrophic vs progressive pathways described by Ferrucci and colleagues. 24 The receipt of rehabilitative services after hospitalization is another possible explanation for this finding. Interventions that quickly identify and ameliorate the effects of events leading to hospitalization may facilitate recovery by decreasing the severity of disability. For example, efforts to increase mobility during hospital stays are associated with less functional decline in older persons, 45,46 and might also lead to more rapid recovery. Further research is warranted to evaluate the effects of rehabilitative services on the recovery process and to better characterize the events that precipitate disability. While several previous studies have found that younger age is associated with a higher rate of recovery among older persons, 1,7,8 our findings of no age effect are consistent with those of Hansen and colleagues, 47 who studied recovery from disability 1 month after hospitalization. One possible explanation for this discrepancy is the difference in the length of the assessment intervals between our study and others. We found that younger age was associated with longer duration of recovery, indicating that older persons who recover are more likely to experience recurrent disability or death over 6 to 12 months and, thus, would have been classified as not recovered in prior studies with assessment intervals of 6 months or longer. The monthly assessments of function provided a unique opportunity to examine predictors of the duration of recovery among older persons who recovered independent function. In addition to habitual physical activity, we found that younger age, greater self-efficacy, and duration of the prior disability episode were independent predictors of longer duration of recovery. To help interpret the magnitude of the hazard ratios, we offer 2 examples. First, walking for 30 minutes 5 days a week would add 50 points to the physical activity score, 17 which would reduce the likelihood of recurrent disability by about 20%. Second, a change from being fairly to completely confident on 5 of the 10 self-efficacy activities would reduce the likelihood of recurrent disability by 26%. It is unlikely that selfefficacy is simply a surrogate for recurrent disability because participants were explicitly asked about their confidence rather than their actual performance of the activities, self-efficacy was assessed before the disabling event, and our results did not change after the 3 ADL questions were omitted from the efficacy scale. The duration of the prior disability episode was strongly associated with the duration of recovery. It is unlikely that this association is attributable to participants with longer disability durations having less subsequent follow-up during which to experience recurrent disability or death. Because the duration of total follow-up in our study was much longer than the durations of disability and recovery, we were able to observe nearly three quarters of participants until recurrent disability or death. In addition, disability durations were shorter and recovery durations were substantially longer among those who remained independent compared with those who experienced recurrent disability or death (data not shown), suggesting that the association between the durations of disability and recovery was not an artifact of limited follow-up. Recent research has demonstrated that a history of disability, even only of 1 or 2 months, is strongly associated with future disability and death. 48 This finding and those of the present study suggest that history of disability, including attributes such as duration and number of episodes, may be an important determinant of subsequent disability and recovery. While some previous studies have incorporated multiple transitions between disabled and independent states in models of the disabling process, the effects of prior disability episodes on subsequent recovery have not been explicitly considered. Future studies will need to incorporate multiple episodes of disability and recovery and account for the effects of disability history. Physical measures, particularly gait speed, have consistently been shown in previous studies to be strong independent predictors of disability. 19,20,53 Although all of our physical measures were significant predictors of recurrent disability in bivariate analyses, none were identified as independent predictors. There are several possible explanations for this apparent discrepancy. First, in contrast to other studies, our outcome was recurrent disability, contingent on recovery from a previous episode of disability. Second, our physical measures were assessed before the initial disability episode and may have been altered more by the intervening disabling event than other potential predictors, such as self-efficacy. Third, the physical measures were highly correlated with physical activity and self-efficacy. Because many of the prognostic factors identified in bivariate analyses were highly intercorrelated, the independent predictors we identified may not be the best prognostic factors in other populations. 54 Other significant factors from the bivariate analyses may still have effects on recovery, either directly or through their effect on the independent factors. For example, improving balance and gait through physical therapy or exercise may increase the duration of recovery either directly or indirectly through enhancement of self-efficacy or increased physical activity. With the exception of habitual physical activity, the factors associated with time to recovery differed from those associated with duration of recovery. Time to recovery was most strongly associated with factors related to the onset of disability (ie, the type of precipitating event), while duration of recovery was more strongly associated with factors previously associated with risk for disability. 38 Some of these are indicators of frailty, defined as a state of reduced physiologic reserve associated with increased susceptibility to disability. 55 Our bivariate results provide additional support for a mechanistic difference, because few of the factors that predicted time to recovery also predicted duration of recovery. Because older persons who have recently recovered independent function are at high risk for recurrent disability, 48 they represent an important target population for interventions to promote maintenance of independence. We recognize that the associations found in our epidemiologic study support, but do not prove, causation. Randomized trials will be needed to determine if interven- 110

6 tions directed at the identified predictors can alter disability outcomes. Patterns of recovery among the 4 key ADLs were comparable. Although dressing and bathing may be more affected by some risk factors (eg, deficits in cognitive or upper extremity function) than walking and transferring, disability for each of these activities is likely multifactorial. Further research is needed to determine whether similar mechanisms account for recovery and maintenance of independence for these different ADLs. It is unlikely that brief recovery durations (ie, only 1 month) were attributable to measurement error. First, most participants with brief recoveries experienced subsequent periods of independence. Second, most recurrent episodes were preceded by hospitalization or restricted activity. Third, our disability assessment was highly reliable. These brief recoveries may reflect unstable disability, defined as substantial fluctuations in function with minor external events. 56 Because brief periods of disability have considerable prognostic importance, 48 brief periods of recovery may also be clinically important. We were unable to determine the precise cause of our participants disability, which may not be readily apparent in the absence of a catastrophic event. 57 Disability is multifactorial, 30,55,58,59 and many episodes of disability are not preceded by a problem leading to hospitalization or restricted activity. 30,60,61 Many older persons, for example, report common symptoms, such as pain and fatigue, as the cause of prevalent disability, 57 and recent evidence indicates that events leading to restricted activity, another multifactorial process, 11 are independently associated with decline in ADL function. 62 Although the time to and duration of recovery likely differ depending on the specific events precipitating disability, determination of the causes of individual episodes is complex and beyond the scope of this study. Because persons with slow gait speed were oversampled, our population may have had lower rates of recovery and levels of physical activity and self-efficacy than a population-based sample of older adults. Because our participants were members of a single health plan in a small urban area, our results may not be generalizable to older persons in other settings. However, our population reflects the demographic characteristics of persons 65 years or older in New Haven County, Connecticut, which are comparable to the United States as a whole with the exception of race. 63 Furthermore, the high participation and follow-up rates and the paucity of missing data enhance the generalizability of our findings. 64 In summary, habitual physical activity is an important predictor of time to and duration of recovery. Because the other independent predictors for time to recovery differ from those for maintenance of recovery, different mechanisms may underlie these 2 outcomes, suggesting that different interventions may be required to promote recovery than to maintain independent ADL function. Accepted for Publication: August 20, Correspondence: Susan E. Hardy, MD, Department of Internal Medicine, Yale University School of Medicine, 20 York St, Tompkins Basement 15, New Haven, CT (susan.hardy@yale.edu). Funding/Support: This study was supported in part by grant R01AG17560 from the National Institute on Aging, Bethesda, Md; a grant from the Robert Wood Johnson Foundation, Princeton, NJ; the Paul Beeson Physician Faculty Scholar in Aging Research; and a grant from the Patrick and Catherine Weldon Donaghue Medical Research Foundation, West Hartford, Conn. The study was conducted at the Claude D. Pepper Older Americans Independence Center, Yale University School of Medicine (grant P30AG21342). Dr Hardy is a student in the Investigative Medicine Program at Yale University School of Medicine (grant K30HL004145), and is supported by training grant T32AG1934 from the National Institute on Aging and a Pfizer/AGS Foundation for Health in Aging Junior Faculty Scholar award. Dr Gill is the recipient of Midcareer Investigator Award K24AG in Patient-Oriented Research from the National Institute on Aging. Previous Presentation: This study was presented at the Annual Scientific Meeting of the Gerontological Society of America; November 23, 2003; San Diego, Calif. Acknowledgment: We thank Joseph Agostini, MD, for his careful review of an earlier version of the manuscript; Denise Shepard, BSN, Martha Oravetz, RN, Shirley Hannan, RN, Andrea Benjamin, BSN, Alice Kossack, Barbara Foster, Shari Lani, Alice Van Wie, and the late Bernice Hebert, RN, for assistance with data collection; Evelyne Gahbauer, MD, MPH, for data management and programming; Wanda Carr and Geraldine Hawthorne for assistance with data entry and management; Peter Charpentier, MPH, for development of the participant tracking system; and Joanne McGloin, MDiv, MBA, for leadership and advice as the project director. REFERENCES 1. Manton KG. A longitudinal study of functional change and mortality in the United States. J Gerontol. 1988;43:S153-S Verbrugge LM, Reoma JM, Gruber-Baldini AL. Short-term dynamics of disability and well-being. J Health Soc Behav. 1994;35: Hardy SE, Gill TM. Recovery from disability among community-dwelling older persons. JAMA. 2004;291: Cree M, Carriere KC, Soskolne CL, Suarez-Almazor M. Functional dependence after hip fracture. Am J Phys Med Rehabil. 2001;80: Michel JP, Hoffmeyer P, Klopfenstein C, Bruchez M, Grab B, d Epinay CL. Prognosis of functional recovery 1 year after hip fracture: typical patient profiles through cluster analysis. J Gerontol A Biol Sci Med Sci. 2000;55:M508-M Ostir GV, Goodwin JS, Markides KS, Ottenbacher KJ, Balfour J, Guralnik JM. Differential effects of premorbid physical and emotional health on recovery from acute events. J Am Geriatr Soc. 2002;50: Gill TM, Robison JT, Tinetti ME. Predictors of recovery in activities of daily living among disabled older persons living in the community. J Gen Intern Med. 1997; 12: Branch LG, Katz S, Kniepmann K, Papsidero JA. A prospective study of functional status among community elders. Am J Public Health. 1984;74: Gill TM, Hardy SE, Williams CS. Underestimation of disability among communityliving older persons. J Am Geriatr Soc. 2002;50: Guralnik JM, Ferrucci L. Underestimation of disability occurrence in epidemiological studies of older people: is research on disability still alive? J Am Geriatr Soc. 2002;50: Gill TM, Desai MM, Gahbauer EA, Holford TR, Williams CS. Restricted activity among community-living older persons: incidence, precipitants, and health care utilization. Ann Intern Med. 2001;135: Folstein MF, Folstein SE, McHugh PR. Mini-Mental State : a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975; 12: Kohout FJ, Berkman LF, Evans DA, Cornoni-Huntley J. Two shorter forms of the CES-D (Center for Epidemiological Studies Depression) depression symptoms index. J Aging Health. 1993;5:

7 14. Tinetti ME, Mendes de Leon CF, Doucette JT, Baker DI. Fear of falling and fallrelated efficacy in relationship to functioning among community-living elders. J Gerontol. 1994;49:M140-M Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med. 1991; 32: Cornoni-Huntley J, Brock DB, Ostfeld AM, Taylor JO, Wallace RB, Lafferty ME, eds. Established Populations for Epidemiologic Studies of the Elderly: Resource Data Book. Bethesda, Md: National Institute on Aging; Washburn RA, Smith KW, Jette AM, Janney CA. The Physical Activity Scale for the Elderly (PASE): development and evaluation. J Clin Epidemiol. 1993;46: Piccinelli M, Tessari E, Bortolomasi M, et al. Efficacy of the alcohol use disorders identification test as a screening tool for hazardous alcohol intake and related disorders in primary care: a validity study. BMJ. 1997;314: Gill TM, Williams CS, Tinetti ME. Assessing risk for the onset of functional dependence among older adults: the role of physical performance. J Am Geriatr Soc. 1995;43: Guralnik JM, Ferrucci L, Pieper CF, et al. Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery. J Gerontol A Biol Sci Med Sci. 2000;55:M221-M Giampaoli S, Ferrucci L, Cecchi F, et al. Hand-grip strength predicts incident disability in non-disabled older men. Age Ageing. 1999;28: Rantanen T, Guralnik JM, Foley D, et al. Midlife hand grip strength as a predictor of old age disability. JAMA. 1999;281: Landis JR, Koch GC. The measurement of observer agreement for categorical data. Biometrics. 1977;33: Ferrucci L, Guralnik JM, Simonsick EM, Salive M, Corti MC, Langlois J. Progressive versus catastrophic disability: a longitudinal view of the disablement process. J Gerontol A Biol Sci Med Sci. 1996;51:M123-M LaCroix AZ, Guralnik JM, Berkman LF, Wallace RB, Satterfield S. Maintaining mobility in late life, II: smoking, alcohol consumption, physical activity, and body mass index. Am J Epidemiol. 1993;137: Mendes de Leon CF, Glass TA, Berkman LF. Social engagement and disability in a community population of older adults: the New Haven EPESE. Am J Epidemiol. 2003;157: Mendes de Leon CF, Seeman TE, Baker DI, Richardson ED, Tinetti ME. Selfefficacy, physical decline, and change in functioning in community-living elders: a prospective study. J Gerontol B Psychol Sci Soc Sci. 1996;51:S183- S Miller ME, Rejeski WJ, Reboussin BA, Ten Have TR, Ettinger WH. Physical activity, functional limitations, and disability in older adults. J Am Geriatr Soc. 2000; 48: Guralnik JM, Land KC, Blazer D, Fillenbaum GG, Branch LG. Educational status and active life expectancy among older blacks and whites. N Engl J Med. 1993; 329: Gill TM, Williams CS, Tinetti ME. The combined effects of baseline vulnerability and acute hospital events on the development of functional dependence among community-living older persons. J Gerontol A Biol Sci Med Sci. 1999;54:M377-M Ambler G, Brady AR, Royston P. Simplifying a prognostic model: a simulation study based on clinical data. Stat Med. 2002;21: Concato J, Peduzzi P, Holford TR, Feinstein AR. Importance of events per independent variable in proportional hazards analysis, I: background, goals, and general strategy. J Clin Epidemiol. 1995;48: SAS Institute Inc. SAS/STAT User s Guide, Version 8. Cary, NC: SAS Institute Inc; Arriagada R, Rutqvist LE, Kramar A, Johansson H. Competing risks determining event-free survival in early breast cancer. Br J Cancer. 1992;66: Feinstein AR. Clinical Epidemiology: the Architecture of Clinical Research. Philadelphia, Pa: WB Saunders Co; Wu SC, Leu SY, Li CY. Incidence of and predictors for chronic disability in activities of daily living among older people in Taiwan. J Am Geriatr Soc. 1999; 47: Ferrucci L, Izmirlian G, Leveille S, et al. Smoking, physical activity, and active life expectancy. Am J Epidemiol. 1999;149: Stuck AE, Walthert JM, Nikolaus T, Bula CJ, Hohmann C, Beck JC. Risk factors for functional status decline in community-living elderly people: a systematic literature review. Soc Sci Med. 1999;48: Gill TM, Baker DI, Gottschalk M, Peduzzi PN, Allore H, Byers A. A program to prevent functional decline in physically frail, elderly persons who live at home. N Engl J Med. 2002;347: Binder EF, Schechtman KB, Ehsani AA, et al. Effects of exercise training on frailty in community-dwelling older adults: results of a randomized, controlled trial. J Am Geriatr Soc. 2002;50: Li F, Harmer P, McAuley E, et al. An evaluation of the effects of Tai Chi exercise on physical function among older persons: a randomized controlled trial. Ann Behav Med. 2001;23: Penninx BW, Messier SP, Rejeski WJ, et al. Physical exercise and the prevention of disability in activities of daily living in older persons with osteoarthritis. Arch Intern Med. 2001;161: Jette AM, Lachman M, Giorgetti MM, et al. Exercise it s never too late: the strongfor-life program. Am J Public Health. 1999;89: Ettinger WH Jr, Burns R, Messier SP, et al. A randomized trial comparing aerobic exercise and resistance exercise with a health education program in older adults with knee osteoarthritis: the Fitness Arthritis and Seniors Trial (FAST). JAMA. 1997;277: Siebens H, Aronow H, Edwards D, Ghasemi Z. A randomized controlled trial of exercise to improve outcomes of acute hospitalization in older adults. J Am Geriatr Soc. 2000;48: Brown CJ, Friedkin SK, Inouye SK. Prevalence and outcomes of low mobility in hospitalized older patients. J Am Geriatr Soc. 2004;52: Hansen K, Mahoney J, Palta M. Risk factors for lack of recovery of ADL independence after hospital discharge. J Am Geriatr Soc. 1999;47: Gill TM, Kurland B. The prognostic effect of prior disability episodes among nondisabled community-living older persons. Am J Epidemiol. 2003;158: Lagergren M. Disability transitions in an area-based system of long-term care for the elderly and disabled. Health Policy. 1994;28: Mendes de Leon CF, Beckett LA, Fillenbaum GG, et al. Black-white differences in risk of becoming disabled and recovering from disability in old age: a longitudinal analysis of two EPESE populations. Am J Epidemiol. 1997;145: Mendes de Leon CF, Glass TA, Beckett LA, Seeman TE, Evans DA, Berkman LF. Social networks and disability transitions across eight intervals of yearly data in the New Haven EPESE. J Gerontol B Psychol Sci Soc Sci. 1999;54:S162-S Beckett LA, Brock DB, Lemke JH, et al. Analysis of change in self-reported physical function among older persons in four population studies. Am J Epidemiol. 1996;143: Studenski S, Perera S, Wallace D, et al. Physical performance measures in the clinical setting. J Am Geriatr Soc. 2003;51: Van Steen K, Curran D, Kramer J, et al. Multicollinearity in prognostic factor analyses using the EORTC QLQ-C30: identification and impact on model selection. Stat Med. 2002;21: Buchner DM, Wagner EH. Preventing frail health. Clin Geriatr Med. 1992;8: Campbell AJ, Buchner DM. Unstable disability and the fluctuations of frailty. Age Ageing. 1997;26: Ettinger WH Jr, Fried LP, Harris T, Shemanski L, Schulz R, Robbins J. Selfreported causes of physical disability in older people: the Cardiovascular Health Study. J Am Geriatr Soc. 1994;42: Kempen GI, Verbrugge LM, Merrill SS, Ormel J. The impact of multiple impairments on disability in community-dwelling older people. Age Ageing. 1998; 27: Verbrugge LM, Lepkowski JM, Imanaka Y. Comorbidity and its impact on disability. Milbank Q. 1989;67: Ferrucci L, Guralnik JM, Pahor M, Corti MC, Havlik RJ. Hospital diagnoses, Medicare charges, and nursing home admissions in the year when older persons become severely disabled. JAMA. 1997;277: Gill TM, Allore H, Holford TR, Guo Z. The development of insidious disability in activities of daily living among community-living older persons. Am J Med. 2004; 117: Gill TM, Allore H, Holford TR, Guo Z. Physical frailty, intervening events, and the development of disability in activities of daily living among community-living older persons. JAMA. 2004;292: US Census Bureau. American FactFinder. Available at: Accessed May 29, Szklo M. Population-based cohort studies. Epidemiol Rev. 1998;20: