0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Original Investigation |

Disability During the Last Two Years of Life FREE

Alexander K. Smith, MD, MS, MPH1,2; Louise C. Walter, MD1,2; Yinghui Miao, MPH1,2; W. John Boscardin, PhD1,2,3; Kenneth E. Covinsky, MD, MPH1,2
[+] Author Affiliations
1Division of Geriatrics, Department of Medicine, University of California, San Francisco
2Veterans Affairs Medical Center, San Francisco, California
3Department of Epidemiology and Biostatistics, University of California, San Francisco
JAMA Intern Med. 2013;173(16):1506-1513. doi:10.1001/jamainternmed.2013.8738.
Text Size: A A A
Published online

Importance  Whereas many persons at advanced ages live independently and are free of disability, we know little about how likely older people are to be disabled in the basic activities of daily living that are necessary for independent living as they enter the last years of life.

Objective  To determine national estimates of disability during the last 2 years of life.

Design  Prospective cohort study.

Setting  A nationally representative study of older adults in the United States.

Participants  Participants 50 years and older who died while enrolled in the Health and Retirement Study between 1995 and 2010. Each participant was interviewed once at a varying time point in the last 24 months of life. We used these interviews to calculate national estimates of the prevalence of disability across the 2 years prior to death. We modeled the prevalence of disability in the 2 years prior to death for groups defined by age at death and sex.

Main Outcomes and Measures  Disability was defined as need for help with at least 1 of the following activities of daily living: dressing, bathing, eating, transferring, walking across the room, and using the toilet.

Results  There were 8232 decedents (mean [SD] age at death, 79 [11] years; 52% women). The prevalence of disability increased from 28% (95% CI, 24%-31%) 2 years before death to 56% (95% CI, 52%-60%) in the last month of life. Those who died at the oldest ages were much more likely to have disability 2 years before death (ages 50-69 years, 14%; 70-79 years, 21%; 80-89 years, 32%; 90 years or more, 50%; P for trend, <.001). Disability was more common in women 2 years before death (32% [95% CI, 28%-36%]) than men (21% [95% CI, 18%-25%]; P < .001), even after adjustment for older age at death.

Conclusions and Relevance  Those who live to an older age are likely to be disabled, and thus in need of caregiving assistance, many months or years prior to death. Women have a substantially longer period of end-of-life disability than men.

Figures in this Article

The population of US adults older than 85 years is expected to triple, from 5.4 million to 19 million between 2008 and 2050.1 This explosion of our nation’s older adult population will occur in the context of a health care system that is primarily focused on disease management and is unprepared to manage the patient and caregiver needs imposed by disability.2 It also occurs in the context of a culture in which many live in both fear and denial of the disablement that occurs with aging.3 The public is bombarded with messages that frailty and disability are not inevitable, and the most popular medical personalities assail the public with health messages that healthy living will lead to a long life free of disability to the end of life.4

Many people do live into their eighth and ninth decades free of disability and able to live independently. However, it is also the case that with increasing age, the end-of-life course is increasingly likely to be marked by disability.58 Thus, it is likely that most well-functioning older adults and their families will need to be prepared for a period of disability as they continue to age and approach the last years of life. Preparation for this period of disability may be particularly important for older women, who are much more likely to be widowed and lack a spousal caregiver.9 However, there is surprisingly little national data on a person’s likelihood of being disabled during the last months of life. Furthermore, we lack national estimates of how end-of-life disability varies according to age at death, sex, and socioeconomic status. These knowledge gaps limit our ability to plan for supportive services for disabled older adults in their last years of life and target services to the most vulnerable groups.

We therefore conducted a study of the nationally representative Health and Retirement Study (HRS) to describe the prevalence of disability and functional problems during the last 2 years of life. To help target services to the most vulnerable to disability, we present findings for key groups, including the oldest adults and women.

Participants

The HRS is an ongoing nationally representative longitudinal study of changes in health and wealth in persons older than 50 years, funded by the National Institute on Aging. The HRS uses a national area probability sample of US households. Participants are interviewed every 2 years. Enrollment began in 1992, and additional participants are added every 6 years so that the study remains representative of the US population older than 50 years. Follow-up rates are high (85%-93%), and date of death is determined for nearly all participants (99%).10 Each participant is interviewed once every 2 years. Thus, generally, each HRS participant is interviewed once during the last 2 years of life, and the timing of this end-of-life interview is random, based on the time between the last interview of life and date of death. The 1-hour HRS interviews are conducted primarily by telephone, but face-to-face interviews are conducted for most participants who are 80 years or older, too ill to participate in the telephone interview, or unable to access a telephone. For participants who are too ill or cognitively impaired to conduct an interview, proxy interviews are conducted with participants’ next of kin.

In total, 28 390 participants were interviewed between January 1995 and December 2010; of these, 10 250 died. We excluded 1989 participants who had their last interview prior to the last 2 years of life (720 days of life; 1 month was defined as a 30-day increment) and 29 participants who had implausible interview dates relative to their date of death. Our final sample consisted of 8232 decedents. We compared the 1989 participants with interviews prior to the last 2 years of life to participants in our final sample as described in the Results. This study was approved by the Committee on Human Subjects Research at the University of California, San Francisco.

Measures

Our primary analysis described the prevalence of older adults who have disability in activities of daily living (ADLs) during the last 2 years of life. The need for help with these activities generally means that the person will need daily assistance from a family member, friend, or formal long-term care services.11,12 Measures included 6 ADLs: dressing, bathing, eating, transferring in or out of bed, walking across the room, and using the toilet. Participants were first asked whether they have difficulty with each ADL. Participants reporting difficulty were then asked whether they required assistance for that ADL; those who responded “yes” were considered to have disability. Participants who reported the need for assistance with 3 or more ADLs were considered severely disabled.6 We additionally report the prevalence of selected higher order mobility and functional problems,11 defined as difficulty or inability to walk several blocks, walk 1 block, walk up several flights of stairs, walk up 1 flight of stairs, take medications, and manage finances.

We evaluated predictors of disability that had been shown to correlate with disability in previous studies, including sociodemographic factors (age, sex, race and/or ethnicity, educational attainment, and household net worth), chronic conditions (high blood pressure, heart disease, diabetes mellitus, cancer, cognitive impairment, stroke, lung disease, and arthritis), and health events (hospitalizations or falls during the last 2 years).57 We used household net worth at enrollment because we were concerned that household net worth at the last interview prior to death might be confounded—as individuals become disabled and consider nursing home placement, they often “spend down” their assets to qualify for Medicaid’s long-term care benefit.13

Analysis

HRS participants reported disability at a range of time points during the last 2 years of life. We first used these reports to present the unadjusted monthly prevalence of disability during the last 2 years of life. We then used these reports to model the probability that a participant would be disabled across the last 2 years of life. We used HRS survey weights to calculate national estimates of the prevalence of disability during the last 2 years of life. To construct these estimates, we modeled the prevalence of disability using a restricted cubic spline with 4 knots placed at standard cut points (Harrell’s recommended cutpoints14), in this case 23, 17, 10, and 2 months prior to death. To assess the robustness of our results to the number and location of the knots, a variety of alternative locations and numbers of knots were also examined. Results were extremely similar for a wide variety of knot choices. We found that the restricted cubic spline models were superior to the linear model in all cases using Wald tests. Goodness of fit for the logistic regression models was verified by means of a modified Hosmer-Lemeshow approach.15,16 Nonsignificant values suggested a good fit for all models. The C statistic ranged from 0.71 to 0.77 across models, suggesting very good model discrimination.

We used the spline model in a multivariable regression analysis to estimate the probability of disability during the last 2 years of life for relevant subgroups. Model covariates included age at death, sex, race and/or ethnicity, educational attainment, and household net worth. Probabilities were determined for subgroups holding other covariates fixed at their population means. Because differences by age and sex were of central interest, we additionally present model results stratified by age at death and sex.

We conducted several additional analyses to place our findings in context and test the robustness of our findings. First, we examined time trends in disability for 2000 through 2010. Second, to contrast disability rates among patients who are dying with disability rates in the general living population of older adults, we report rates of disability by age among the entire 2010 HRS cohort (14 436 participants). Third, we were concerned that the 1989 participants with no interview during the last 2 years of life may have differed systematically from interviewed participants in our sample. Therefore, we compare these groups by age, sex, race and/or ethnicity, and disability during the last 3 months of life as described by next of kin in after-death interviews.

All analyses used survey weights provided by the HRS to account for the complex survey design and unequal probability of participant selection.17 Reported percentages may not sum to 100.0% due to the use of survey weights. All analyses were conducted in Stata, Version 12 (StataCorp).

Characteristics of the participants are described in Table 1. The mean (SD) age at the time of death was 81 (11) years for women and 77 (11) years for men. Overall, 52% were female. Twenty-two percent of decedent women were 90 years and older, and 11% of decedent men were 90 years and older. Differences between participants interviewed in the last year of life and participants interviewed 1 to 2 years prior to death were not significant for sex, race and/or ethnicity, educational attainment, or net worth; participants interviewed 1 to 2 years prior to death were a mean of 1 year younger at death than those interviewed in the last year of life (P < .001).

Table Graphic Jump LocationTable 1.  Characteristics of Participantsa

Unadjusted and modeled adjusted findings were similar (Figure 1). Because of slight differences between participants interviewed across the 2 years before death, and to leverage the power of modeling, we focus on the adjusted findings for the remainder of the results.

Place holder to copy figure label and caption
Figure 1.
Prevalence of Unadjusted and Adjusted Disability in Activities of Daily Living During the Last 2 Years of Life

Diamonds represent the mean monthly prevalence of disability in an activity of daily living (ADL) (bathing, getting out of bed, dressing, eating, walking across a room, and using the toilet). Bars represent 95% confidence intervals. The line represents ADL disability modeled as a spline with knots at 23, 17, 10, and 2 months prior to death, adjusted for age at death, sex, race and/or ethnicity, educational attainment, and household net worth. Gray shading above and below the line represents modeled 95% confidence intervals.

Graphic Jump Location

The prevalence of disability (requiring assistance with ADLs) increased during the last 2 years of life (Figures 1, 2, and 3 and Table 2). Twenty-four months prior to death, 46% (95% CI, 42%-50%) of participants had an ADL difficulty, 28% (95% CI, 24%-31%) had ADL disability, and 12% had severe ADL disability (95% CI, 9%-14%), increasing to 68% (95% CI, 64%-72%), 56% (95% CI, 52%-60%), and 40% (95% CI, 36%-44%), respectively, in the last month of life (Figure 2). The increase in prevalence was steeper for severe ADL disability than for ADL difficulty, with the steepest increase in prevalence of severe disability occurring in the last 6 months of life. Examining the prevalence of disability by individual ADL revealed a similar pattern of increasing prevalence during the months before death, with highest rates for bathing disability and dressing disability (eFigure 1 in Supplement).

Place holder to copy figure label and caption
Figure 2.
Prevalence of Difficulty, Disability, and Severe Disability in Activities of Daily Living During the Last 2 Years of Life

Prevalence of difficulty or disability, defined as the need for assistance, with any of 6 activities of daily living (ADLs). Outcomes are modeled as a spline with knots at 23, 17, 10, and 2 months prior to death, adjusted for age at death, sex, race and/or ethnicity, educational attainment, and household net worth. Severe disability is defined as a report of 3 or more ADL disabilities.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.
Prevalence of Disability in Activities of Daily Living by Age and Sex During the Last 2 Years of Life

Prevalence of disability modeled as a spline with knots at 23, 17, 10, and 2 months prior to death, stratified by age at death and sex, adjusted for race and/or ethnicity, educational attainment, and household net worth. Panels show age at death of 50 to 69 (A), 70 to 79 (B), 80 to 89 (C), and at least 90 (D) years. Gray shading above and below the line represents modeled 95% confidence intervals.

Graphic Jump Location
Table Graphic Jump LocationTable 2.  Prevalence of Disability in Activities of Daily Living During the Last 2 Years of Life Across Subgroupsa

Most older adults had difficulty with walking and stair climbing during the last 2 years of life (eFigure 2 in Supplement). Two years prior to death, 69% of older adults had difficulty with walking several blocks, 45% walking 1 block, 82% climbing several flights of stairs, 53% climbing 1 flight of stairs, 22% managing finances, and 14% taking medications. In the last month of life, these rates increased to 85% for walking several blocks, 68% for walking 1 block, 91% for several flights of stairs, 72% for 1 flight of stairs, 45% for managing finances, and 32% for taking medications.

Those who died at advanced old age were much more likely to be disabled during the 2 years prior to death than those who died at younger ages (Figure 3 and Table 2). Fifty percent (95% CI, 45%-55%) of participants who died at 90 years or older were disabled 24 months prior to death, 59% (95% CI, 56%-62%) 12 months prior to death, and 77% (95% CI, 73%-80%) in the last month of life. In contrast, the prevalence of disability for individuals who died younger than 70 years was at least 35% lower at any time point during the last 2 years of life.

Even after adjustment for age of death and other sociodemographic factors, women were more likely to experience disability during the 2 years before death than men (Table 2). At any given age at death, women were more likely to be disabled than men during the 2 years prior to death (Figure 3). Among social factors, household net worth was a major predictor of disability in the 2 years prior to death (Table 2). The highest burden of ADL disability was experienced by those in the lowest quartile of net worth (32% in the 2 years prior to death [95% CI, 28%-35%]) and the lowest burden among those with the greatest wealth (23% in the 2 years prior to death [95% CI, 19%-27%]). Participants with lower educational attainment were more likely to experience disability. In unadjusted analysis, married or partnered participants were less likely to become disabled during the 2 years before death (31% vs 42%; P < .001), but this relationship reversed after adjustment for sociodemographic factors (Table 2). Differences by race and/or ethnicity were not found after adjustment for socioeconomic factors. All examined chronic conditions and health events were associated with end-of-life disability (Table 2).

To place our findings in context and to test the robustness of our findings, we conducted several additional analyses. First, no time trend for disability was present for the years 2000 through 2010 (P for trend, .42). Second, we examined rates of disability among all living participants in the 2010 HRS for comparison, and these were lower for all subgroups when compared with disability at the end of life (see eTable 1 in Supplement). Third, we compared the 1989 decedent participants who were not interviewed during the last 2 years of life with the 8232 decedent participants in our sample and found them to be similar in terms of age, sex, and race and/or ethnicity (all P > .40). However, when we compared after-death reports by next of kin about disability during the last 3 months of life, disability was 4% more common among the 1989 excluded decedents than among the 8232 participants in our sample (78% vs 74%; P = .02).

Those who live to an older age are much more likely than those who die at younger ages to be disabled in basic ADLs and thus dependent on caregiver assistance months or years prior to death. More than one-third of all older adults can expect to need assistance with ADL disability 1 year prior to death, and more than one-quarter 2 years prior to death. Nearly all older adults will have difficulty walking or climbing stairs 2 years before death. Half of all older adults who live to their tenth decade will be disabled in ADLs 2 years prior to death, and more than two-thirds 6 months prior to death, and thus be dependent on the help of family or paid caregivers for a protracted period. Among women and men who live to the same age, women will be disabled substantially longer before death. The poor bear a greater burden of functional impairment and disability in the 2 years prior to death than the wealthy.

Many persons are now living independently into their ninth and 10th decades. Although we often cannot exactly predict when these individuals are entering their last 2 years of life, we know with certainty that all will have an end-of-life experience and, in most cases, will need assistance with basic activities for a protracted period before death. From a societal perspective, the number of persons living with disability prior to death will balloon as the population ages.

Our data do not directly address the compression of morbidity hypothesis, which suggests that as life expectancy increases on a societal level, the amount of time spent in disabled states will decrease, although we found no time trend in rates of disability over the most recent 10 years.18 Our data do raise the question of whether it makes sense to sell the public a view of aging that purports that it is reasonable to expect to both live a long life and remain free of disability throughout life.4 Our findings add to the evidence that those who live to advanced ages will spend greater periods of time in states of disability prior to death than those who die at younger ages.6,7

One response to the information that we present is to increase resources directed at the prevention of disability prior to death. Many people fear living in a state of disability prior to death, and some fear living in a prolonged state of disability prior to death more than death itself.19 Yet previous research suggests that once older adults become disabled, they often report that they maintain a good quality of life.20 Younger, nondisabled persons underestimate their ability to adapt to disability in advanced age. Efforts directed at prevention of disability are important. For many older adults, however, disability is part of life. Our findings suggest that many older adults have a prolonged period of time to learn to adapt and cope with disability prior to death.

Another response to this information is an acknowledgment of the inevitability of disability at the end of life, and support for formal and informal care systems that promote a high quality of life for disabled persons nearing the end of life.20 Our current system is too focused on disease-specific outcomes, such as glycosylated hemoglobin levels for patients with diabetes mellitus or survival in patients with heart failure.21 But these outcomes do a poor job of capturing the goals of older adults, who often live with disability, multiple chronic conditions, and cognitive impairment for months or years prior to death. Our health care system needs to be redirected toward meeting the goals of the many older adults whose priority is maintaining physical function and a high quality of life in their last years.21

The needed ADL assistance in the last years of life that we describe is often provided by unpaid family caregivers, resulting in a considerable savings to our society.22 Our current health care system does an inadequate job of supporting family caregivers, many of whom, untrained and unprepared, struggle for months and years providing in-home care for disabled older adults with little support from our health care or social systems.2,23,24 Caregiving is a duty for some and a gift for others. But caregiving also places a substantial physical, psychological, and financial strain on families.25,26 Successful health care innovations that incorporate family caregivers have been developed,2730 but in comparison with drug and device innovations designed for older adults, these health care innovations have not been widely implemented and disseminated.

Whereas previous research demonstrated that women are more likely to become disabled then men,5,31 to our knowledge, this is the first national study to demonstrate that women are at risk for increased disability at all time points during the last 2 years of life, independent of age of death. The combination of higher life expectancy and higher rates of disability at any given age at death makes end-of-life disability a crucial yet generally unrecognized women’s health issue. As with many issues in geriatrics, the etiology of this gender gap is likely multifactorial, attributable to some mix of gender differences in rates of disabling conditions (eg, depression and osteoarthritis), geriatric syndromes (eg, falls), and predisposing physiologic factors (eg, body fat composition and sarcopenia).31 Furthermore, women disproportionately bear the burden of providing care for disabled older adults. Whereas disabled older men are likely to be cared for by a spouse, disabled older women are more likely to be living alone, with few financial resources, cared for by a daughter.31 Policy makers need to account for these gender disparities when designing interventions to support women in their last years of life.

Our estimates of disability during the last 2 years of life are likely conservative, for 2 reasons. First, according to next of kin after the participant’s death, the 1989 excluded participants without an interview in the last 2 years had 4% higher rates of disability than participants included in our sample. Second, next of kin of participants included in our sample report higher rates of any disability during the last 3 months of life (74%) than participants reported themselves in the last month of life (56%). This is likely because disability continues to increase during the final month, and next of kin report their last recollections of their loved ones from the final days of life, when rates of disability are highest.

Older age disability is known to be a dynamic process, and older persons have episodes of recurrence and remission of disability before becoming permanently disabled.11,12 Our study design is not able to capture individual trajectories of function. Although our analyses do not provide data about the disability trajectories that individuals may experience during the last months of life,6 they do provide detailed estimates of the proportion of persons who will have ADL disability and thus need caregiving assistance at some point during the last 2 years of life. They also provide national estimates of the disability burden in men and women and how the risk of disability varies by wealth. These detailed estimates, which to our knowledge did not previously exist, provide essential data that provide insights into population health and caregiving needs in the last 2 years of life.

Regardless of whether compression of morbidity is occurring, it is important for our health care system and society to plan better for the increase in end-of-life disability that is inevitable in an aging population. Preventive efforts are important, yet so too are funding, research, and policy initiatives that address quality of life concerns of adults living with disability in their last years. Our health care systems are designed to pay for disease management and are sorely unprepared to meet the needs that stem from disability. Policy changes might first target the most vulnerable groups, particularly women who live to advanced age and the families that care for them.

Corresponding Author: Alexander K. Smith, MD, MS, MPH, Division of Geriatrics, University of California, San Francisco, 4150 Clement St (181G), San Francisco, CA 94121 (aksmith@ucsf.edu).

Accepted for Publication: April 16, 2013.

Published Online: July 8, 2013. doi:10.1001/jamainternmed.2013.8738.

Author Contributions: Dr Smith had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Smith, Covinsky.

Analysis and interpretation of data: All authors.

Drafting of the manuscript: Smith.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Smith, Miao, Boscardin.

Obtained funding: Smith, Covinsky.

Administrative, technical, and material support: Smith.

Study supervision: Smith.

Conflict of Interest Disclosures: None reported.

Funding/Support: Dr Smith was supported by the National Center for Research Resources University of California, San Francisco–Clinical and Translational Science Institute (UL1 RR024131) and a Paul Beeson Career Development Award in Aging (1K23AG040772-01A1). Drs Walter and Covinsky were supported by K-24 grants from the National Institute on Aging (K24AG029812 and 1K24AG041180-01, respectively).

Role of the Sponsor: The National Institutes of Health had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.

US Census Bureau. 2008 National Population Projections. http://www.census.gov/population/projections/data/national/2008.html. 2008. Accessed October 29, 2012.
Levine  C.  The loneliness of the long-term care giver. N Engl J Med. 1999;340(20):1587-1590.
PubMed   |  Link to Article
Gillick  MR. The Denial of Aging: Perpetual Youth, Eternal Life, and Other Dangerous Fantasies. Boston, MA: Harvard University Press; 2007.
Roizen  MF, Oz  MC. You Staying Young: The Owner's Manual for Extending Your Warranty. New York, NY: Free Press; 2007.
Katz  S, Branch  LG, Branson  MH, Papsidero  JA, Beck  JC, Greer  DS.  Active life expectancy. N Engl J Med. 1983;309(20):1218-1224.
PubMed   |  Link to Article
Gill  TM, Gahbauer  EA, Han  L, Allore  HG.  Trajectories of disability in the last year of life. N Engl J Med. 2010;362(13):1173-1180.
PubMed   |  Link to Article
Zhao  J, Barclay  S, Farquhar  M, Kinmonth  AL, Brayne  C, Fleming  J; Cambridge City Over-75s Cohort Study Collaboration.  The oldest old in the last year of life: population-based findings from Cambridge City Over-75s Cohort Study participants aged 85 and older at death. J Am Geriatr Soc. 2010;58(1):1-11.
PubMed   |  Link to Article
Kulminski  A, Ukraintseva  SV, Akushevich  I, Arbeev  KG, Land  K, Yashin  AI.  Accelerated accumulation of health deficits as a characteristic of aging. Exp Gerontol. 2007;42(10):963-970.
PubMed   |  Link to Article
Stone  R, Cafferata  GL, Sangl  J.  Caregivers of the frail elderly: a national profile. Gerontologist. 1987;27(5):616-626.
PubMed   |  Link to Article
University of Michigan Health and Retirement Study. Sample Sizes and Response Rates. http://hrsonline.isr.umich.edu/sitedocs/sampleresponse.pdf. 2011. Accessed October 29, 2012.
Verbrugge  LM, Jette  AM.  The disablement process. Soc Sci Med. 1994;38(1):1-14.
PubMed   |  Link to Article
Covinsky  KE, Pierluissi  E, Johnston  CB.  Hospitalization-associated disability: “she was probably able to ambulate, but I’m not sure”. JAMA. 2011;306(16):1782-1793.
PubMed   |  Link to Article
Feder  J, Komisar  HL, Niefeld  M.  Long-term care in the United States: an overview. Health Aff (Millwood). 2000;19(3):40-56.
PubMed   |  Link to Article
Harrell  FEJ. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. New York, NY: Springer; 2001.
Archer  KJ, Lemeshow  S.  Goodness-of-fit test for a logistic regression model fitted using survey sample data. Stata J. 2006;6(1):97-105.
Paul  P, Pennell  ML, Lemeshow  S.  Standardizing the power of the Hosmer-Lemeshow goodness of fit test in large data sets. Stat Med. 2013;32(1):67-80.
PubMed   |  Link to Article
University of Michigan Health and Retirement Study. Sampling Weights. 1999. http://hrsonline.isr.umich.edu/sitedocs/wghtdoc.pdf. Accessed October 29, 2012.
Fries  JF.  Aging, natural death, and the compression of morbidity. N Engl J Med. 1980;303(3):130-135.
PubMed   |  Link to Article
Sutherland  HJ, Llewellyn-Thomas  H, Boyd  NF, Till  JE.  Attitudes toward quality of survival: the concept of “maximal endurable time”. Med Decis Making. 1982;2(3):299-309.
PubMed   |  Link to Article
King  J, Yourman  L, Ahalt  C,  et al.  Quality of life in late life disability: “I don't feel bitter because I am in a wheelchair”. J Am Geriatr Soc. 2012;60(3):569-576.
PubMed   |  Link to Article
Reuben  DB, Tinetti  ME.  Goal-oriented patient care—an alternative health outcomes paradigm. N Engl J Med. 2012;366(9):777-779.
PubMed   |  Link to Article
Arno  PS, Levine  C, Memmott  MM.  The economic value of informal caregiving. Health Aff (Millwood). 1999;18(2):182-188.
PubMed   |  Link to Article
Levine  C, Halper  D, Peist  A, Gould  DA.  Bridging troubled waters: family caregivers, transitions, and long-term care. Health Aff (Millwood). 2010;29(1):116-124.
PubMed   |  Link to Article
Katz  SJ, Kabeto  M, Langa  KM.  Gender disparities in the receipt of home care for elderly people with disability in the United States. JAMA. 2000;284(23):3022-3027.
PubMed   |  Link to Article
Rabow  MW, Hauser  JM, Adams  J.  Supporting family caregivers at the end of life: “they don’t know what they don’t know”. JAMA. 2004;291(4):483-491.
PubMed   |  Link to Article
Covinsky  KE, Goldman  L, Cook  EF,  et al; SUPPORT Investigators.  The impact of serious illness on patients’ families. JAMA. 1994;272(23):1839-1844.
PubMed   |  Link to Article
Boyd  CM, Reider  L, Frey  K,  et al.  The effects of guided care on the perceived quality of health care for multi-morbid older persons: 18-month outcomes from a cluster-randomized controlled trial. J Gen Intern Med. 2010;25(3):235-242.
PubMed   |  Link to Article
Wolff  JL, Giovannetti  ER, Boyd  CM,  et al.  Effects of guided care on family caregivers. Gerontologist. 2010;50(4):459-470.
PubMed   |  Link to Article
Naylor  MD, Brooten  DA, Campbell  RL, Maislin  G, McCauley  KM, Schwartz  JS.  Transitional care of older adults hospitalized with heart failure: a randomized, controlled trial. J Am Geriatr Soc. 2004;52(5):675-684.
PubMed   |  Link to Article
Coleman  EA, Parry  C, Chalmers  S, Min  SJ.  The care transitions intervention: results of a randomized controlled trial. Arch Intern Med. 2006;166(17):1822-1828.
PubMed   |  Link to Article
Newman  AB, Brach  JS.  Gender gap in longevity and disability in older persons. Epidemiol Rev. 2001;23(2):343-350.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.
Prevalence of Unadjusted and Adjusted Disability in Activities of Daily Living During the Last 2 Years of Life

Diamonds represent the mean monthly prevalence of disability in an activity of daily living (ADL) (bathing, getting out of bed, dressing, eating, walking across a room, and using the toilet). Bars represent 95% confidence intervals. The line represents ADL disability modeled as a spline with knots at 23, 17, 10, and 2 months prior to death, adjusted for age at death, sex, race and/or ethnicity, educational attainment, and household net worth. Gray shading above and below the line represents modeled 95% confidence intervals.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Prevalence of Difficulty, Disability, and Severe Disability in Activities of Daily Living During the Last 2 Years of Life

Prevalence of difficulty or disability, defined as the need for assistance, with any of 6 activities of daily living (ADLs). Outcomes are modeled as a spline with knots at 23, 17, 10, and 2 months prior to death, adjusted for age at death, sex, race and/or ethnicity, educational attainment, and household net worth. Severe disability is defined as a report of 3 or more ADL disabilities.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.
Prevalence of Disability in Activities of Daily Living by Age and Sex During the Last 2 Years of Life

Prevalence of disability modeled as a spline with knots at 23, 17, 10, and 2 months prior to death, stratified by age at death and sex, adjusted for race and/or ethnicity, educational attainment, and household net worth. Panels show age at death of 50 to 69 (A), 70 to 79 (B), 80 to 89 (C), and at least 90 (D) years. Gray shading above and below the line represents modeled 95% confidence intervals.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1.  Characteristics of Participantsa
Table Graphic Jump LocationTable 2.  Prevalence of Disability in Activities of Daily Living During the Last 2 Years of Life Across Subgroupsa

References

US Census Bureau. 2008 National Population Projections. http://www.census.gov/population/projections/data/national/2008.html. 2008. Accessed October 29, 2012.
Levine  C.  The loneliness of the long-term care giver. N Engl J Med. 1999;340(20):1587-1590.
PubMed   |  Link to Article
Gillick  MR. The Denial of Aging: Perpetual Youth, Eternal Life, and Other Dangerous Fantasies. Boston, MA: Harvard University Press; 2007.
Roizen  MF, Oz  MC. You Staying Young: The Owner's Manual for Extending Your Warranty. New York, NY: Free Press; 2007.
Katz  S, Branch  LG, Branson  MH, Papsidero  JA, Beck  JC, Greer  DS.  Active life expectancy. N Engl J Med. 1983;309(20):1218-1224.
PubMed   |  Link to Article
Gill  TM, Gahbauer  EA, Han  L, Allore  HG.  Trajectories of disability in the last year of life. N Engl J Med. 2010;362(13):1173-1180.
PubMed   |  Link to Article
Zhao  J, Barclay  S, Farquhar  M, Kinmonth  AL, Brayne  C, Fleming  J; Cambridge City Over-75s Cohort Study Collaboration.  The oldest old in the last year of life: population-based findings from Cambridge City Over-75s Cohort Study participants aged 85 and older at death. J Am Geriatr Soc. 2010;58(1):1-11.
PubMed   |  Link to Article
Kulminski  A, Ukraintseva  SV, Akushevich  I, Arbeev  KG, Land  K, Yashin  AI.  Accelerated accumulation of health deficits as a characteristic of aging. Exp Gerontol. 2007;42(10):963-970.
PubMed   |  Link to Article
Stone  R, Cafferata  GL, Sangl  J.  Caregivers of the frail elderly: a national profile. Gerontologist. 1987;27(5):616-626.
PubMed   |  Link to Article
University of Michigan Health and Retirement Study. Sample Sizes and Response Rates. http://hrsonline.isr.umich.edu/sitedocs/sampleresponse.pdf. 2011. Accessed October 29, 2012.
Verbrugge  LM, Jette  AM.  The disablement process. Soc Sci Med. 1994;38(1):1-14.
PubMed   |  Link to Article
Covinsky  KE, Pierluissi  E, Johnston  CB.  Hospitalization-associated disability: “she was probably able to ambulate, but I’m not sure”. JAMA. 2011;306(16):1782-1793.
PubMed   |  Link to Article
Feder  J, Komisar  HL, Niefeld  M.  Long-term care in the United States: an overview. Health Aff (Millwood). 2000;19(3):40-56.
PubMed   |  Link to Article
Harrell  FEJ. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. New York, NY: Springer; 2001.
Archer  KJ, Lemeshow  S.  Goodness-of-fit test for a logistic regression model fitted using survey sample data. Stata J. 2006;6(1):97-105.
Paul  P, Pennell  ML, Lemeshow  S.  Standardizing the power of the Hosmer-Lemeshow goodness of fit test in large data sets. Stat Med. 2013;32(1):67-80.
PubMed   |  Link to Article
University of Michigan Health and Retirement Study. Sampling Weights. 1999. http://hrsonline.isr.umich.edu/sitedocs/wghtdoc.pdf. Accessed October 29, 2012.
Fries  JF.  Aging, natural death, and the compression of morbidity. N Engl J Med. 1980;303(3):130-135.
PubMed   |  Link to Article
Sutherland  HJ, Llewellyn-Thomas  H, Boyd  NF, Till  JE.  Attitudes toward quality of survival: the concept of “maximal endurable time”. Med Decis Making. 1982;2(3):299-309.
PubMed   |  Link to Article
King  J, Yourman  L, Ahalt  C,  et al.  Quality of life in late life disability: “I don't feel bitter because I am in a wheelchair”. J Am Geriatr Soc. 2012;60(3):569-576.
PubMed   |  Link to Article
Reuben  DB, Tinetti  ME.  Goal-oriented patient care—an alternative health outcomes paradigm. N Engl J Med. 2012;366(9):777-779.
PubMed   |  Link to Article
Arno  PS, Levine  C, Memmott  MM.  The economic value of informal caregiving. Health Aff (Millwood). 1999;18(2):182-188.
PubMed   |  Link to Article
Levine  C, Halper  D, Peist  A, Gould  DA.  Bridging troubled waters: family caregivers, transitions, and long-term care. Health Aff (Millwood). 2010;29(1):116-124.
PubMed   |  Link to Article
Katz  SJ, Kabeto  M, Langa  KM.  Gender disparities in the receipt of home care for elderly people with disability in the United States. JAMA. 2000;284(23):3022-3027.
PubMed   |  Link to Article
Rabow  MW, Hauser  JM, Adams  J.  Supporting family caregivers at the end of life: “they don’t know what they don’t know”. JAMA. 2004;291(4):483-491.
PubMed   |  Link to Article
Covinsky  KE, Goldman  L, Cook  EF,  et al; SUPPORT Investigators.  The impact of serious illness on patients’ families. JAMA. 1994;272(23):1839-1844.
PubMed   |  Link to Article
Boyd  CM, Reider  L, Frey  K,  et al.  The effects of guided care on the perceived quality of health care for multi-morbid older persons: 18-month outcomes from a cluster-randomized controlled trial. J Gen Intern Med. 2010;25(3):235-242.
PubMed   |  Link to Article
Wolff  JL, Giovannetti  ER, Boyd  CM,  et al.  Effects of guided care on family caregivers. Gerontologist. 2010;50(4):459-470.
PubMed   |  Link to Article
Naylor  MD, Brooten  DA, Campbell  RL, Maislin  G, McCauley  KM, Schwartz  JS.  Transitional care of older adults hospitalized with heart failure: a randomized, controlled trial. J Am Geriatr Soc. 2004;52(5):675-684.
PubMed   |  Link to Article
Coleman  EA, Parry  C, Chalmers  S, Min  SJ.  The care transitions intervention: results of a randomized controlled trial. Arch Intern Med. 2006;166(17):1822-1828.
PubMed   |  Link to Article
Newman  AB, Brach  JS.  Gender gap in longevity and disability in older persons. Epidemiol Rev. 2001;23(2):343-350.
PubMed   |  Link to Article

Correspondence

CME
Also Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
Your answers have been saved for later.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
Submit a Comment

Multimedia

Supplement.

eFigure 1. Prevalence of Individual ADL Disabilities During the Last Two Years of Life

eFigure 2: Prevalence of Functional Difficulty During the Last Two Years of Life

eTable 1. Prevalence of Disability in Living Health and Retirement Study Subjects, 2010 (N=14,436)

Supplemental Content

Some tools below are only available to our subscribers or users with an online account.

Web of Science® Times Cited: 1

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Collections
PubMed Articles