Depression and Unmet Needs for Assistance With Daily Activities Among Community-Dwelling Older Adults

Depression and Unmet Needs for Assistance With Daily Activities Among Community-Dwelling Older... Abstract Background and Objectives This study aims to investigate the impact of depressive symptoms on adverse consequences of unmet needs for assistance with daily activities among community-dwelling older adults. Research Design and Methods Data came from round 1 to 5 of the National Health and Aging Trends Study. Study sample consisted of 3,400 Medicare beneficiaries needing assistance with activities of daily living (ADL), instrumental activities of daily living (IADL), or mobility for any two consecutive years between 2011 and 2015. Study outcome was the number of self-reported adverse consequences of unmet needs for assistance with daily activities (e.g., went without eating, wet or soiled clothes). Mixed-effects negative binomial regression was used to estimate the association of lagged depressive symptoms and covariates in period t−1 and the number of adverse consequences of unmet needs in period t. Results The prevalence rates of adverse consequences of unmet needs were twice as high among older adults with elevated depressive symptoms as those without depression. After adjusting for covariates, prior wave depressive symptoms were associated with 1.24 times the rate of adverse consequences of unmet needs for assistance with ADL (Incidence Rate Ratio [IRR] = 1.24, 95% confidence interval [CI] = 1.09–1.41, p < .01) and IADL (IRR = 1.24, 95% CI = 1.06–1.44, p < .01), and 1.14 times the rate of adverse consequences of unmet needs for assistance with mobility (IRR = 1.14, 95% CI = 1.03–1.27, p < .05). Discussion and Implications Caring for older adults with mental health and long-term care needs calls for an integrated social and health services system. Depression, Long-term care, Unmet need, Adverse consequences An estimated 20–40% of U.S. older adults needing assistance with daily activities, such as dressing, eating, and shopping for groceries, report unmet needs or receive insufficient assistance (Allen, Piette, & Mor, 2014; Desai, Lentzner, & Weeks, 2001; Kennedy, 2001; LaPlante, Kaye, Kang, & Harrington, 2004; Shea et al., 2003). Up to half of these older adults experience adverse consequences due to unmet needs, such as going without eating, wetting or soiling clothes, making a mistake in taking medications, and having to stay inside (Allen & Mor, 1997; Allen et al., 2014; Desai et al., 2001). These adverse consequences of unmet needs have a profound impact on older adults’ quality of life and health outcomes. A number of studies have suggested that unmet needs precede functional decline and increase the risk of emergency room visit, hospital admission, nursing home placement, and premature mortality (Gaugler, Kane, Kane, & Newcomer, 2005; Hass, DePalma, Craig, Xu, & Sands, 2015; Xu, Covinsky, Stallard, Thomas, & Sands, 2012). Preventing adverse consequences of unmet needs has important public health implications for improving the quality of life of older adults and reducing health care costs. Previous studies have consistently linked physical function limitations to adverse consequences of unmet needs for assistance with daily activities (Allen et al., 2014; Desai et al., 2001; LaPlante et al., 2004). However, little is known regarding the psychosocial risk factors. This study begins to fill this knowledge gap by assessing the impact of depressive symptoms on the adverse consequences of unmet needs. Depression is a leading cause of global disease burden (Ferrari et al., 2013). Clinically significant depressive symptoms affect 15% of community-living older adults (Blazer, 2003), and the rate is substantially higher among people with physical function limitations (Chen et al., 2012). As an important indicator of psychosocial health, depressive symptoms can be treated successfully with psychotherapy, pharmacological treatment, or a combination (DeRubeis, Siegle, & Hollon, 2008). Examining the impact of depressive symptoms may inform practice and policy to reduce the incidence of adverse consequences of unmet needs for assistance with daily activities. Conceptual Framework Allen et al (2014) constructed a conceptual framework on the pathway to unmet need and its adverse consequences, which was the basis of the framework of this study. Severity of illness and impairment determines the level of needs for assistance. Whether needs for assistance will cause adverse consequences depends on the adequacy of informal and formal long-term services and supports (LTSS). In the case of individuals with depression, level of needs for assistance is higher than those without depression due to the increased severity of illness and impairment associated with depression. Depressive symptoms can cause neural, hormonal, and immunological alterations and worsen physical health and functioning (Penninx et al., 1998). Studies have consistently showed that depression increases the risk of physical disability (Ormel, Rijsdijk, Sullivan, van Sonderen, & Kempen, 2002; Schillerstrom, Royall, & Palmer, 2008). Depression may also increase the risk of adverse consequences by limiting informal and formal LTSS access. The interpersonal theory of depression posits that the behaviors of individuals with depression such as negative self-statements, passivity, and social withdrawal can erode social support (Hames, Hagan, & Joiner, 2013), limiting the availability and intensity of informal LTSS from family, friends, and neighbors. The socioeconomic disadvantages associated with depression and other mental illness (Muntaner, Eaton, Miech, & O’Campo, 2004) reduce access to formal LTSS by diminishing the ability to purchase long-term care insurance and services. The purpose of this study is to investigate the impact of depressive symptoms on adverse consequences of unmet needs for assistance with activities of daily living (ADL), instrumental activities of daily living (IADL), and mobility. The primary study hypothesis is that elevated depressive symptoms at prior wave (i.e., period t−1) are associated with more adverse consequences of unmet needs at current wave (i.e., period t). Figure 1 shows the 1-year lagged effect of depressive symptoms on adverse consequences of unmet needs. This analytical model was set up to establish a time order between depressive symptoms and adverse consequences of unmet needs. Figure 1. View largeDownload slide Analytical model of lagged effect of depressive symptoms on adverse consequences of unmet needs Figure 1. View largeDownload slide Analytical model of lagged effect of depressive symptoms on adverse consequences of unmet needs Design and Methods Data We analyzed data from round 1 (2011) through round 5 (2015) of the National Health and Aging Trends Study (NHATS). The NHATS is a nationally representative panel study of Medicare beneficiaries aged 65 years and older. Persons in older age groups and African Americans were oversampled. A total of 7,777 older adults who lived in the community (including traditional community settings, retirement communities, and alternative residential care) completed sample person interviews at baseline. Annual follow-up interviews were conducted regardless of their residential status. This study included 3,400 Medicare beneficiaries who reported needs for assistance with any daily activities (ADL, IADL, and mobility) for two consecutive years from 2011 to 2015. Study sample was restricted to participants needing assistance with daily activities because having a need is a prerequisite of experiencing adverse consequences of unmet needs. The restriction of reporting need for two consecutive years was necessary for estimating models with lagged independent variables. After excluding participants with missing data on the depression screener (n = 39), the final sample size was 3,361. Measures Needs for Assistance With Daily Activities The NHATS asks a series of questions regarding limitations in performing ADLs (including eating, bathing, toileting, and dressing), IADLs (including laundry, shopping for groceries or personal items, meal preparation, banking or paying bills, and keeping track of medication), and mobility tasks (going outside the home, getting around inside the home, and getting out of bed). Respondents were asked if, in the last month, they performed each activity with assistance or alone. Respondents who performed an activity with assistance were asked if the reason for assistance was related to health or functioning. Respondents who performed an activity alone were asked how difficult it was to do the activity. Respondents were classified as having needs for personal assistance if they (a) received assistance with an activity due to health or functioning reasons or (b) had difficulty performing an activity alone. Summary indicators of needs for assistance with daily activities were created for ADL, IADL, and mobility domains. Adverse Consequences of Unmet Needs Respondents who reported a need for assistance with a daily activity were asked if they experienced the adverse consequence associated with that activity due to lack of assistance or difficulty in performing the activity. For example, if respondents reported a need for assistance with eating, they would then be asked if they ever went without eating during the last month because no one was there to help or they had difficulty eating alone. Questions concerning adverse consequences were asked only for respondents who reported a need for assistance with that specific daily activity. The adverse consequences corresponding to the daily activities were: went without eating, went without taking a bath, wet or soiled clothes, went without getting dressed, went without clean laundry, went without groceries or personal items, went without a hot meal, went without handling bills and banking matters, made a mistake in taking prescribed medicines, had to stay inside, did not go to places inside one’s home, and had to stay in bed. Summary indicators of the number of adverse consequences were created by the domain of activities with which they were associated (i.e., adverse consequences associated with unmet needs for assistance with ADL, IADL, and mobility, respectively). Depression The Patient Health Questionnaire-2 (PHQ-2; Löwe, Kroenke, & Gräfe, 2005) is intended for use in clinical practice. It asks participants to rate how often they have been bothered by “little interest or pleasure in doing things” and “feeling down, depressed or hopeless” over the last 2 weeks on a 0–3 point scale. PHQ-2 scores range from 0 to 6. We used a cutoff score of 3 to indicate elevated depressive symptoms. A cutoff score of 3 has a sensitivity of 0.87 and a specificity of 0.78 for major depressive disorder, and a sensitivity of 0.79 and specificity of 0.86 for any depressive disorder (Löwe et al., 2005). Covariates Adjusting for potential confounding variables is important to determine the independent impact of depressive symptoms. Allen et al.’s framework (2014) and relevant literature guided the selection of possible common causes of depression and adverse consequence of unmet needs. Covariates included sociodemographic characteristics, indicators of illness and impairment severity, and proxies for access to informal and formal LTSS. Sociodemographic characteristics included age groups (65–69, 70–74, 75–79, 80–84, 85–89, or 90+), sex (female or male), race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, or other race/multi-race), and education (less than high school, high school graduate, some college but no degree, or college graduate). Indicators of illness and impairment included dementia status, the number of self-reported chronic physical illnesses (including heart disease, arthritis, osteoporosis, diabetes, lung disease, stroke, and cancer), an indicator of past-year hospitalization, and the count of needs for assistance with daily activities. NHATS classifies participants into 3 groups—no dementia, possible dementia, and probable dementia—based on self-reported diagnosis of dementia or Alzheimer’s disease, AD8 Dementia Screening Interview, and cognitive tests (Kasper, Freedman, & Spillman, 2013). A continuous variable of community social support was included as an indicator of informal LTSS. Community social support was a three-item measure of participants’ agreement with the following statements on a three-point Likert scale: people in this community “know each other well”, “are willing to help each other”, and “can be trusted”. Original responses were reverse coded and averaged to generate a composite score, with higher scores indicating better social support. This scale has good internal consistency in this study sample (Cronbach’s alpha = 0.73). Proxies of access to formal LTSS included a dichotomous indicator of long-term care insurance coverage and an indicator of Medicaid coverage (representing Medicare-Medicaid dual eligibility in this study). Data Analysis Chi-square tests were used to compare sample characteristics and prevalence rates of adverse consequences by depression status at baseline, accounting for NHATS complex survey design. Mixed-effects negative binomial regression models were estimated using prior-wave (period t−1) depressive symptoms and covariates to predict the number of adverse consequences of unmet needs for assistance with ADL, IALD, and mobility at current wave (period t), respectively. To ease the interpretation of model estimates, the postestimation command margins was used to calculate the predicted counts of adverse consequences of unmet needs for individuals with elevated depressive symptoms and those without. Statistical analyses were conducted using Stata 12.0 SE version (StataCorp, TX). We did not account for the complex survey design in mixed-effects models. Consensus has not been reached on how to incorporate weights in generalized linear mixed models with longitudinal data, particularly when the weights are not constant within the individual (Bertolet, 2008). NHATS provides different sampling weights at different study waves for the same individual. Methodological guidance is lacking regarding which weight to use. Second, simulation studies have found little differences between findings from unweighted analyses and scaled-weighted analyses, particularly in the case of noninformative sampling weights (where the sampling design does not correlate with the outcome; Carle, 2009). Third, there are limited software programs that can properly incorporate different types of scaled weights in generalized multilevel modeling (Carle, 2009). Results One in five (20.4%) older adults needing assistance for daily activities had elevated depressive symptoms at baseline, representing over 2.8 million people in the population. Table 1 presents weighted sample characteristics stratified by depression status at baseline. The following groups were overrepresented in older adults with elevated depressive symptoms: Hispanics, people with lower education, people with possible or probable dementia, people with more chronic physical illnesses and needs for personal assistance, people who were hospitalized in past 12 months, and Medicare-Medicaid dual eligibles. One in 10 older adults with elevated depressive symptoms reported long-term care insurance coverage as compared to 17% of those without elevated depressive symptoms. On average, older adults with elevated depressive symptoms reported 0.12 point lower on the community social support scale. Table 1. Weighted Sample Characteristics by Depression Status at Baseline With elevated depressive symptoms (n = 703) Without elevated depressive symptoms (2,658) p value Sociodemographic characteristics  Age groups (%) .277   65–69 years 21.6 (17.4, 26.6) 19.5 (17.9, 21.3)   70–74 years 21.7 (18.5, 25.2) 19.5 (17.7, 21.5)   75–79 years 20.2 (17.0, 23.7) 20.8 (19.2, 22.5)   80–84 years 18.1 (15.3, 21.3) 19.0 (17.6, 20.5)   85–89 years 13.5 (11.3, 16.0) 13.8 (12.3, 15.3)   90 years or over 5.0 (4.0, 6.2) 7.4 (6.3, 8.7)  Sex (%)   Female 61.2 (57.6, 64.6) 63.6 (61.5, 65.8) .271   Male 38.8 (35.4, 42.4) 36.4 (34.3, 38.5)  Race/ethnicity (%) <.001   White, Non-Hispanic 71.3 (66.0, 76.0) 80.2 (77.7, 82.4)   Black, Non-Hispanic 11.4 (9.4, 13.8) 8.8 (7.7, 9.9)   Hispanic 13.3 (10.1, 17.3) 7.0 (5.3, 9.2)   Other 4.0 (2.4, 6.6) 4.1 (2.9, 5.8)  Education (%) <.001   Less than high school 35.6 (31.2, 40.3) 22.9 (20.9, 25.0)   High school 28.8 (25.3, 32.5) 27.7 (25.7, 29.9)   Some college, no degree 17.7 (14.7, 21.1) 21.7 (19.7, 23.9)   College graduate 17.9 (14.3, 22.2) 27.7 (25.0, 30.5) Severity of illness and impairment  Dementia status (%) <.001   No dementia 57.2 (51.9, 62.4) 74.8 (72.7, 76.9)   Possible dementia 17.5 (14.3, 21.1) 12.4 (11.0, 14.0)   Probable dementia 25.3 (21.8, 29.2) 12.8 (11.3, 14.4)  Number of chronic physical illnesses (mean) 3.25 (3.12, 3.37) 2.67 (2.62, 2.73) <.001  Number of needs for assistance with daily activities (mean) 5.42 (5.11, 5.73) 2.85 (2.72, 2.98) <.001  Hospitalized in past 12 months 35.6 (31.9, 39.4) 24.6 (22.7, 26.6) <.001  Access to long-term services and supports   Community social support scale (mean) 2.28 (2.22, 2.33) 2.40 (2.37, 2.43) <.001   Long-term care insurance (%) 10.6 (8.3, 13.4) 17.4 (15.8,19.20) <.001   Medicare-Medicaid dual enrollees (%) 25.7 (22.2, 29.5) 14.8 (12.8, 17.1) <.001 With elevated depressive symptoms (n = 703) Without elevated depressive symptoms (2,658) p value Sociodemographic characteristics  Age groups (%) .277   65–69 years 21.6 (17.4, 26.6) 19.5 (17.9, 21.3)   70–74 years 21.7 (18.5, 25.2) 19.5 (17.7, 21.5)   75–79 years 20.2 (17.0, 23.7) 20.8 (19.2, 22.5)   80–84 years 18.1 (15.3, 21.3) 19.0 (17.6, 20.5)   85–89 years 13.5 (11.3, 16.0) 13.8 (12.3, 15.3)   90 years or over 5.0 (4.0, 6.2) 7.4 (6.3, 8.7)  Sex (%)   Female 61.2 (57.6, 64.6) 63.6 (61.5, 65.8) .271   Male 38.8 (35.4, 42.4) 36.4 (34.3, 38.5)  Race/ethnicity (%) <.001   White, Non-Hispanic 71.3 (66.0, 76.0) 80.2 (77.7, 82.4)   Black, Non-Hispanic 11.4 (9.4, 13.8) 8.8 (7.7, 9.9)   Hispanic 13.3 (10.1, 17.3) 7.0 (5.3, 9.2)   Other 4.0 (2.4, 6.6) 4.1 (2.9, 5.8)  Education (%) <.001   Less than high school 35.6 (31.2, 40.3) 22.9 (20.9, 25.0)   High school 28.8 (25.3, 32.5) 27.7 (25.7, 29.9)   Some college, no degree 17.7 (14.7, 21.1) 21.7 (19.7, 23.9)   College graduate 17.9 (14.3, 22.2) 27.7 (25.0, 30.5) Severity of illness and impairment  Dementia status (%) <.001   No dementia 57.2 (51.9, 62.4) 74.8 (72.7, 76.9)   Possible dementia 17.5 (14.3, 21.1) 12.4 (11.0, 14.0)   Probable dementia 25.3 (21.8, 29.2) 12.8 (11.3, 14.4)  Number of chronic physical illnesses (mean) 3.25 (3.12, 3.37) 2.67 (2.62, 2.73) <.001  Number of needs for assistance with daily activities (mean) 5.42 (5.11, 5.73) 2.85 (2.72, 2.98) <.001  Hospitalized in past 12 months 35.6 (31.9, 39.4) 24.6 (22.7, 26.6) <.001  Access to long-term services and supports   Community social support scale (mean) 2.28 (2.22, 2.33) 2.40 (2.37, 2.43) <.001   Long-term care insurance (%) 10.6 (8.3, 13.4) 17.4 (15.8,19.20) <.001   Medicare-Medicaid dual enrollees (%) 25.7 (22.2, 29.5) 14.8 (12.8, 17.1) <.001 Note: 95% confidence intervals in parentheses. Sampling weights and design factors were accounted for when estimating prevalences/means. View Large Table 1. Weighted Sample Characteristics by Depression Status at Baseline With elevated depressive symptoms (n = 703) Without elevated depressive symptoms (2,658) p value Sociodemographic characteristics  Age groups (%) .277   65–69 years 21.6 (17.4, 26.6) 19.5 (17.9, 21.3)   70–74 years 21.7 (18.5, 25.2) 19.5 (17.7, 21.5)   75–79 years 20.2 (17.0, 23.7) 20.8 (19.2, 22.5)   80–84 years 18.1 (15.3, 21.3) 19.0 (17.6, 20.5)   85–89 years 13.5 (11.3, 16.0) 13.8 (12.3, 15.3)   90 years or over 5.0 (4.0, 6.2) 7.4 (6.3, 8.7)  Sex (%)   Female 61.2 (57.6, 64.6) 63.6 (61.5, 65.8) .271   Male 38.8 (35.4, 42.4) 36.4 (34.3, 38.5)  Race/ethnicity (%) <.001   White, Non-Hispanic 71.3 (66.0, 76.0) 80.2 (77.7, 82.4)   Black, Non-Hispanic 11.4 (9.4, 13.8) 8.8 (7.7, 9.9)   Hispanic 13.3 (10.1, 17.3) 7.0 (5.3, 9.2)   Other 4.0 (2.4, 6.6) 4.1 (2.9, 5.8)  Education (%) <.001   Less than high school 35.6 (31.2, 40.3) 22.9 (20.9, 25.0)   High school 28.8 (25.3, 32.5) 27.7 (25.7, 29.9)   Some college, no degree 17.7 (14.7, 21.1) 21.7 (19.7, 23.9)   College graduate 17.9 (14.3, 22.2) 27.7 (25.0, 30.5) Severity of illness and impairment  Dementia status (%) <.001   No dementia 57.2 (51.9, 62.4) 74.8 (72.7, 76.9)   Possible dementia 17.5 (14.3, 21.1) 12.4 (11.0, 14.0)   Probable dementia 25.3 (21.8, 29.2) 12.8 (11.3, 14.4)  Number of chronic physical illnesses (mean) 3.25 (3.12, 3.37) 2.67 (2.62, 2.73) <.001  Number of needs for assistance with daily activities (mean) 5.42 (5.11, 5.73) 2.85 (2.72, 2.98) <.001  Hospitalized in past 12 months 35.6 (31.9, 39.4) 24.6 (22.7, 26.6) <.001  Access to long-term services and supports   Community social support scale (mean) 2.28 (2.22, 2.33) 2.40 (2.37, 2.43) <.001   Long-term care insurance (%) 10.6 (8.3, 13.4) 17.4 (15.8,19.20) <.001   Medicare-Medicaid dual enrollees (%) 25.7 (22.2, 29.5) 14.8 (12.8, 17.1) <.001 With elevated depressive symptoms (n = 703) Without elevated depressive symptoms (2,658) p value Sociodemographic characteristics  Age groups (%) .277   65–69 years 21.6 (17.4, 26.6) 19.5 (17.9, 21.3)   70–74 years 21.7 (18.5, 25.2) 19.5 (17.7, 21.5)   75–79 years 20.2 (17.0, 23.7) 20.8 (19.2, 22.5)   80–84 years 18.1 (15.3, 21.3) 19.0 (17.6, 20.5)   85–89 years 13.5 (11.3, 16.0) 13.8 (12.3, 15.3)   90 years or over 5.0 (4.0, 6.2) 7.4 (6.3, 8.7)  Sex (%)   Female 61.2 (57.6, 64.6) 63.6 (61.5, 65.8) .271   Male 38.8 (35.4, 42.4) 36.4 (34.3, 38.5)  Race/ethnicity (%) <.001   White, Non-Hispanic 71.3 (66.0, 76.0) 80.2 (77.7, 82.4)   Black, Non-Hispanic 11.4 (9.4, 13.8) 8.8 (7.7, 9.9)   Hispanic 13.3 (10.1, 17.3) 7.0 (5.3, 9.2)   Other 4.0 (2.4, 6.6) 4.1 (2.9, 5.8)  Education (%) <.001   Less than high school 35.6 (31.2, 40.3) 22.9 (20.9, 25.0)   High school 28.8 (25.3, 32.5) 27.7 (25.7, 29.9)   Some college, no degree 17.7 (14.7, 21.1) 21.7 (19.7, 23.9)   College graduate 17.9 (14.3, 22.2) 27.7 (25.0, 30.5) Severity of illness and impairment  Dementia status (%) <.001   No dementia 57.2 (51.9, 62.4) 74.8 (72.7, 76.9)   Possible dementia 17.5 (14.3, 21.1) 12.4 (11.0, 14.0)   Probable dementia 25.3 (21.8, 29.2) 12.8 (11.3, 14.4)  Number of chronic physical illnesses (mean) 3.25 (3.12, 3.37) 2.67 (2.62, 2.73) <.001  Number of needs for assistance with daily activities (mean) 5.42 (5.11, 5.73) 2.85 (2.72, 2.98) <.001  Hospitalized in past 12 months 35.6 (31.9, 39.4) 24.6 (22.7, 26.6) <.001  Access to long-term services and supports   Community social support scale (mean) 2.28 (2.22, 2.33) 2.40 (2.37, 2.43) <.001   Long-term care insurance (%) 10.6 (8.3, 13.4) 17.4 (15.8,19.20) <.001   Medicare-Medicaid dual enrollees (%) 25.7 (22.2, 29.5) 14.8 (12.8, 17.1) <.001 Note: 95% confidence intervals in parentheses. Sampling weights and design factors were accounted for when estimating prevalences/means. View Large Table 2 presents the population totals of people needing assistance and prevalence rates of adverse consequences of unmet needs for assistance with each daily activity at baseline. Older adults with elevated depressive symptoms reported higher rates of adverse consequences of unmet needs for 9 of the 12 daily activities compared to those without depression. People needing assistance toileting reported the highest rate of adverse consequence, with 55.8% of those with elevated depressive symptoms and 38% of those without depression reporting having wetted or soiled clothes. Rates of adverse consequences of unmet needs for all three mobility tasks were high among people with elevated depressive symptoms (21%, 33%, and 39%, respectively). Summary indicators showed that rates of adverse consequences of unmet needs were twice as high in older adults with elevated depressive symptoms as those without depression (37.4% vs 18.4% for ADL-related adverse consequences, 26.7% vs 15.4% for IADL-related adverse consequences, and 42.0% vs 24.5% for mobility-related adverse consequences, p < .001 for all comparisons). People with elevated depressive symptoms also reported higher number of adverse consequences associated with ADL (0.61 vs 0.33), IADL (0.52 vs 0.26), and mobility tasks (0.84 vs 0.51). Table 2. Baseline Prevalence Rates of Adverse Consequences of Unmet Needs for Assistance With Daily Activities Among Those Needing Assistance, by Depression Status With elevated depressive symptoms Without elevated depressive symptoms p value Activities of daily living  Need assistance eating N = 628,390 N = 867,632   Went without eating (%) 6.1 (2.6, 13.9) 3.5 (1.4, 8.8) .381  Need assistance bathing N = 1,209,958 N = 2,505,975   Went without taking a bath (%) 15.3 (11.1, 20.7) 11.6 (8.6, 15.3) .230  Need assistance toileting N = 831,646 N = 1,210,856   Wet or soiled clothes (%) 55.8 (48.8, 62.5) 38.0 (32.4, 43.9) <.001  Need assistance dressing N = 1,336,243 N = 2,836,948   Went without getting dressed (%) 15.1 (11.8, 19.1) 4.5 (2.9, 7.0) <.001  Need assistance with one or more ADL tasks N = 1,784,255 N = 4,068,451   Had at least one adverse consequence (%) 37.4 (32.3, 42.7) 18.4 (15.7, 21.4) <.001  Number of adverse consequences (mean) 0.61 (0.52, 0.69) 0.33 (0.27, 0.38) <.001 Instrumental activities of daily living  Need assistance doing laundry N = 1,389,761 N = 2,772,108   Went without clean laundry (%) 10.5 (6.2, 17.3) 1.9 (1.0, 3.7) <.001  Need assistance shopping for groceries/personal items N = 1,665,397 N = 3,794,956   Went without groceries or personal items (%) 10.1 (6.9, 14.7) 5.3 (3.7, 7.6) .014  Need assistance with meal preparation N = 1,513,272 N = 3,328,722   Went without a hot meal (%) 13.4 (9.9, 17.9) 8.4 (6.7, 10.4) .009  Need assistance banking or paying bills N = 1,316,544 N = 2,493,475   Went without handling bills/ banking matters (%) 10.4 (6.7, 15.9) 4.0 (2.3, 7.0) .004  Need assistance keeping track of medication N = 1,214,658 N = 2,679,613   Made a mistake in taking prescribed medicines (%) 21.8 (16.5, 28.1) 19.5 (16.4, 23.0) .451  Need assistance with one or more IADL tasks N = 2,235,069 N = 6,221,082   Had at least one adverse consequence (%) 26.7 (22.5, 31.5) 15.4 (13.7, 17.4) <.001  Number of adverse consequences (mean) 0.52 (0.36,0.68) 0.26 (0.21, 0.31) <.001 Mobility  Need assistance going outside the home N = 1,426,294 N = 3,257,959   Had to stay inside (%) 38.7 (32.7, 45.1) 24.6 (20.6, 29.1) <.001  Need assistance getting around inside the home N = 1,425,890 N = 2,918,625   Did not go to places inside one’s home (%) 32.6 (28.0, 37.6) 23.7 (20.0, 27.8) .008  Needing assistance getting out of bed N = 1,480,312 N = 3,016,622   Had to stay in bed (%) 20.6 (16.2, 25.9) 7.3 (5.4, 9.6) <.001  Need assistance with one or more mobility tasks N = 2,030,479 N = 5,237,974   Had at least one adverse consequence (%) 42.0 (37.0, 47.2) 24.5 (21.6, 27.6) <.001  Number of adverse consequences (mean) 0.84 (0.74, 0.95) 0.51 (0.43, 0.58) <.001 With elevated depressive symptoms Without elevated depressive symptoms p value Activities of daily living  Need assistance eating N = 628,390 N = 867,632   Went without eating (%) 6.1 (2.6, 13.9) 3.5 (1.4, 8.8) .381  Need assistance bathing N = 1,209,958 N = 2,505,975   Went without taking a bath (%) 15.3 (11.1, 20.7) 11.6 (8.6, 15.3) .230  Need assistance toileting N = 831,646 N = 1,210,856   Wet or soiled clothes (%) 55.8 (48.8, 62.5) 38.0 (32.4, 43.9) <.001  Need assistance dressing N = 1,336,243 N = 2,836,948   Went without getting dressed (%) 15.1 (11.8, 19.1) 4.5 (2.9, 7.0) <.001  Need assistance with one or more ADL tasks N = 1,784,255 N = 4,068,451   Had at least one adverse consequence (%) 37.4 (32.3, 42.7) 18.4 (15.7, 21.4) <.001  Number of adverse consequences (mean) 0.61 (0.52, 0.69) 0.33 (0.27, 0.38) <.001 Instrumental activities of daily living  Need assistance doing laundry N = 1,389,761 N = 2,772,108   Went without clean laundry (%) 10.5 (6.2, 17.3) 1.9 (1.0, 3.7) <.001  Need assistance shopping for groceries/personal items N = 1,665,397 N = 3,794,956   Went without groceries or personal items (%) 10.1 (6.9, 14.7) 5.3 (3.7, 7.6) .014  Need assistance with meal preparation N = 1,513,272 N = 3,328,722   Went without a hot meal (%) 13.4 (9.9, 17.9) 8.4 (6.7, 10.4) .009  Need assistance banking or paying bills N = 1,316,544 N = 2,493,475   Went without handling bills/ banking matters (%) 10.4 (6.7, 15.9) 4.0 (2.3, 7.0) .004  Need assistance keeping track of medication N = 1,214,658 N = 2,679,613   Made a mistake in taking prescribed medicines (%) 21.8 (16.5, 28.1) 19.5 (16.4, 23.0) .451  Need assistance with one or more IADL tasks N = 2,235,069 N = 6,221,082   Had at least one adverse consequence (%) 26.7 (22.5, 31.5) 15.4 (13.7, 17.4) <.001  Number of adverse consequences (mean) 0.52 (0.36,0.68) 0.26 (0.21, 0.31) <.001 Mobility  Need assistance going outside the home N = 1,426,294 N = 3,257,959   Had to stay inside (%) 38.7 (32.7, 45.1) 24.6 (20.6, 29.1) <.001  Need assistance getting around inside the home N = 1,425,890 N = 2,918,625   Did not go to places inside one’s home (%) 32.6 (28.0, 37.6) 23.7 (20.0, 27.8) .008  Needing assistance getting out of bed N = 1,480,312 N = 3,016,622   Had to stay in bed (%) 20.6 (16.2, 25.9) 7.3 (5.4, 9.6) <.001  Need assistance with one or more mobility tasks N = 2,030,479 N = 5,237,974   Had at least one adverse consequence (%) 42.0 (37.0, 47.2) 24.5 (21.6, 27.6) <.001  Number of adverse consequences (mean) 0.84 (0.74, 0.95) 0.51 (0.43, 0.58) <.001 Notes: ADL = activities of daily living; IADL = instrumental activities of daily living. N represents estimated population totals. 95% confidence intervals in parentheses. Sampling weights and design factors were adjusted when estimating population totals, prevalence, and means. View Large Table 2. Baseline Prevalence Rates of Adverse Consequences of Unmet Needs for Assistance With Daily Activities Among Those Needing Assistance, by Depression Status With elevated depressive symptoms Without elevated depressive symptoms p value Activities of daily living  Need assistance eating N = 628,390 N = 867,632   Went without eating (%) 6.1 (2.6, 13.9) 3.5 (1.4, 8.8) .381  Need assistance bathing N = 1,209,958 N = 2,505,975   Went without taking a bath (%) 15.3 (11.1, 20.7) 11.6 (8.6, 15.3) .230  Need assistance toileting N = 831,646 N = 1,210,856   Wet or soiled clothes (%) 55.8 (48.8, 62.5) 38.0 (32.4, 43.9) <.001  Need assistance dressing N = 1,336,243 N = 2,836,948   Went without getting dressed (%) 15.1 (11.8, 19.1) 4.5 (2.9, 7.0) <.001  Need assistance with one or more ADL tasks N = 1,784,255 N = 4,068,451   Had at least one adverse consequence (%) 37.4 (32.3, 42.7) 18.4 (15.7, 21.4) <.001  Number of adverse consequences (mean) 0.61 (0.52, 0.69) 0.33 (0.27, 0.38) <.001 Instrumental activities of daily living  Need assistance doing laundry N = 1,389,761 N = 2,772,108   Went without clean laundry (%) 10.5 (6.2, 17.3) 1.9 (1.0, 3.7) <.001  Need assistance shopping for groceries/personal items N = 1,665,397 N = 3,794,956   Went without groceries or personal items (%) 10.1 (6.9, 14.7) 5.3 (3.7, 7.6) .014  Need assistance with meal preparation N = 1,513,272 N = 3,328,722   Went without a hot meal (%) 13.4 (9.9, 17.9) 8.4 (6.7, 10.4) .009  Need assistance banking or paying bills N = 1,316,544 N = 2,493,475   Went without handling bills/ banking matters (%) 10.4 (6.7, 15.9) 4.0 (2.3, 7.0) .004  Need assistance keeping track of medication N = 1,214,658 N = 2,679,613   Made a mistake in taking prescribed medicines (%) 21.8 (16.5, 28.1) 19.5 (16.4, 23.0) .451  Need assistance with one or more IADL tasks N = 2,235,069 N = 6,221,082   Had at least one adverse consequence (%) 26.7 (22.5, 31.5) 15.4 (13.7, 17.4) <.001  Number of adverse consequences (mean) 0.52 (0.36,0.68) 0.26 (0.21, 0.31) <.001 Mobility  Need assistance going outside the home N = 1,426,294 N = 3,257,959   Had to stay inside (%) 38.7 (32.7, 45.1) 24.6 (20.6, 29.1) <.001  Need assistance getting around inside the home N = 1,425,890 N = 2,918,625   Did not go to places inside one’s home (%) 32.6 (28.0, 37.6) 23.7 (20.0, 27.8) .008  Needing assistance getting out of bed N = 1,480,312 N = 3,016,622   Had to stay in bed (%) 20.6 (16.2, 25.9) 7.3 (5.4, 9.6) <.001  Need assistance with one or more mobility tasks N = 2,030,479 N = 5,237,974   Had at least one adverse consequence (%) 42.0 (37.0, 47.2) 24.5 (21.6, 27.6) <.001  Number of adverse consequences (mean) 0.84 (0.74, 0.95) 0.51 (0.43, 0.58) <.001 With elevated depressive symptoms Without elevated depressive symptoms p value Activities of daily living  Need assistance eating N = 628,390 N = 867,632   Went without eating (%) 6.1 (2.6, 13.9) 3.5 (1.4, 8.8) .381  Need assistance bathing N = 1,209,958 N = 2,505,975   Went without taking a bath (%) 15.3 (11.1, 20.7) 11.6 (8.6, 15.3) .230  Need assistance toileting N = 831,646 N = 1,210,856   Wet or soiled clothes (%) 55.8 (48.8, 62.5) 38.0 (32.4, 43.9) <.001  Need assistance dressing N = 1,336,243 N = 2,836,948   Went without getting dressed (%) 15.1 (11.8, 19.1) 4.5 (2.9, 7.0) <.001  Need assistance with one or more ADL tasks N = 1,784,255 N = 4,068,451   Had at least one adverse consequence (%) 37.4 (32.3, 42.7) 18.4 (15.7, 21.4) <.001  Number of adverse consequences (mean) 0.61 (0.52, 0.69) 0.33 (0.27, 0.38) <.001 Instrumental activities of daily living  Need assistance doing laundry N = 1,389,761 N = 2,772,108   Went without clean laundry (%) 10.5 (6.2, 17.3) 1.9 (1.0, 3.7) <.001  Need assistance shopping for groceries/personal items N = 1,665,397 N = 3,794,956   Went without groceries or personal items (%) 10.1 (6.9, 14.7) 5.3 (3.7, 7.6) .014  Need assistance with meal preparation N = 1,513,272 N = 3,328,722   Went without a hot meal (%) 13.4 (9.9, 17.9) 8.4 (6.7, 10.4) .009  Need assistance banking or paying bills N = 1,316,544 N = 2,493,475   Went without handling bills/ banking matters (%) 10.4 (6.7, 15.9) 4.0 (2.3, 7.0) .004  Need assistance keeping track of medication N = 1,214,658 N = 2,679,613   Made a mistake in taking prescribed medicines (%) 21.8 (16.5, 28.1) 19.5 (16.4, 23.0) .451  Need assistance with one or more IADL tasks N = 2,235,069 N = 6,221,082   Had at least one adverse consequence (%) 26.7 (22.5, 31.5) 15.4 (13.7, 17.4) <.001  Number of adverse consequences (mean) 0.52 (0.36,0.68) 0.26 (0.21, 0.31) <.001 Mobility  Need assistance going outside the home N = 1,426,294 N = 3,257,959   Had to stay inside (%) 38.7 (32.7, 45.1) 24.6 (20.6, 29.1) <.001  Need assistance getting around inside the home N = 1,425,890 N = 2,918,625   Did not go to places inside one’s home (%) 32.6 (28.0, 37.6) 23.7 (20.0, 27.8) .008  Needing assistance getting out of bed N = 1,480,312 N = 3,016,622   Had to stay in bed (%) 20.6 (16.2, 25.9) 7.3 (5.4, 9.6) <.001  Need assistance with one or more mobility tasks N = 2,030,479 N = 5,237,974   Had at least one adverse consequence (%) 42.0 (37.0, 47.2) 24.5 (21.6, 27.6) <.001  Number of adverse consequences (mean) 0.84 (0.74, 0.95) 0.51 (0.43, 0.58) <.001 Notes: ADL = activities of daily living; IADL = instrumental activities of daily living. N represents estimated population totals. 95% confidence intervals in parentheses. Sampling weights and design factors were adjusted when estimating population totals, prevalence, and means. View Large Table 3 shows incidence rate ratios from mixed-effects negative binomial regression. Likelihood-ratio tests of alpha for these models were statistically significant, suggesting that the negative binomial model is more appropriate than the Poisson model. Likelihood-ratio tests of the fitted models vs null models (i.e., constant-only model) were also significant, indicating better model fit of the fitted models. Holding covariates constant, people with prior-wave elevated depressive symptoms compared to those without depression had 1.24 times the rate of adverse consequences of unmet needs for assistance with ADL (incidence rate ratio [IRR] = 1.24, 95% confidence interval [CI] = 1.09–1.41, p < .01) and IADL (IRR = 1.24, 95% CI = 1.06–1.44, p < .01), and 1.14 times the rate for assistance with mobility (IRR = 1.14, 95% CI = 1.03–1.27, p < .05). Table 3. Incidence Rate Ratios for Lagged Independent Variables Associated With the Count of Adverse Consequences of Unmet Needs From Mixed-Effects Negative Binomial Regression Domains of adverse consequences of unmet needs Lagged independent variables ADL IADL Mobility Elevated depressive symptoms 1.24 (1.09, 1.41)** 1.24 (1.06, 1.44)** 1.14 (1.03, 1.27)* Age in 5-year interval 0.97 (0.93, 1.01) 0.89 (0.84, 0.94)*** 0.98 (0.94, 1.01) Male sex 0.98 (0.85, 1.13) 1.14 (0.96, 1.36) 0.91 (0.81, 1.03) Race/ethnicity  White, Non-Hispanic Reference Reference Reference  Black, Non-Hispanic 0.90 (0.77, 1.05) 0.97 (0.80, 1.18) 1.01 (0.88, 1.15)  Hispanic 0.85 (0.66, 1.08) 1.24 (0.92, 1.69) 1.37 (1.13, 1.66)**  Other 1.31 (0.92, 1.85) 1.08 (0.69, 1.69) 1.58 (1.18, 2.12)** Education  Less than high school Reference Reference Reference  High school 1.03 (0.87, 1.23) 0.93 (0.74, 1.16) 1.04 (0.90, 1.20)  Some college, no degree 1.08 (0.89, 1.31) 1.21 (0.95, 1.53) 1.01 (0.86, 1.19)  College graduate 1.14 (0.95, 1.38) 1.31 (1.04, 1.66)* 1.05 (0.89, 1.23) Dementia status  No dementia Reference Reference Reference  Possible dementia 1.12 (0.93, 1.33) 0.92 (0.77, 1.12) 1.10 (0.96, 1.26)  Probable dementia 1.13 (0.97, 1.32) 0.71 (0.58, 0.86)*** 0.94 (0.82, 1.07) Number of chronic physical illnesses 1.06 (1.01, 1.10)** 1.06 (1.01, 1.12)* 1.07 (1.03, 1.11)*** Number of needs for assistance with daily activities 1.13 (1.11, 1.16)*** 1.01 (0.99, 1.04) 1.10 (1.08, 1.12)*** Hospitalized in past 12 months 1.05 (0.93, 1.19) 1.02 (0.89, 1.17) 1.02 (0.93, 1.13) Community social support 0.85 (0.77, 0.94)** 0.81 (0.72, 0.91)*** 0.90 (0.83, 0.97)** Long-term care insurance 1.07 (0.90, 1.27) 1.02 (0.85, 1.24) 0.92 (0.80, 1.07) Medicare-Medicaid dual enrollees 1.16 (1.00, 1.35)* 1.21 (1.01, 1.47)* 1.05 (0.93, 1.19) Model specifics  Number of persons 1,731 2,634 4,348  Number of person-years 3,493 5,804 2,122  Likelihood-ratio test of alpha = 0: χ2(01) 34.0*** 291.73*** 89.88***  Likelihood-ratio test of fitted model vs null model: χ2(18) 242.43*** 106.99*** 253.12*** Domains of adverse consequences of unmet needs Lagged independent variables ADL IADL Mobility Elevated depressive symptoms 1.24 (1.09, 1.41)** 1.24 (1.06, 1.44)** 1.14 (1.03, 1.27)* Age in 5-year interval 0.97 (0.93, 1.01) 0.89 (0.84, 0.94)*** 0.98 (0.94, 1.01) Male sex 0.98 (0.85, 1.13) 1.14 (0.96, 1.36) 0.91 (0.81, 1.03) Race/ethnicity  White, Non-Hispanic Reference Reference Reference  Black, Non-Hispanic 0.90 (0.77, 1.05) 0.97 (0.80, 1.18) 1.01 (0.88, 1.15)  Hispanic 0.85 (0.66, 1.08) 1.24 (0.92, 1.69) 1.37 (1.13, 1.66)**  Other 1.31 (0.92, 1.85) 1.08 (0.69, 1.69) 1.58 (1.18, 2.12)** Education  Less than high school Reference Reference Reference  High school 1.03 (0.87, 1.23) 0.93 (0.74, 1.16) 1.04 (0.90, 1.20)  Some college, no degree 1.08 (0.89, 1.31) 1.21 (0.95, 1.53) 1.01 (0.86, 1.19)  College graduate 1.14 (0.95, 1.38) 1.31 (1.04, 1.66)* 1.05 (0.89, 1.23) Dementia status  No dementia Reference Reference Reference  Possible dementia 1.12 (0.93, 1.33) 0.92 (0.77, 1.12) 1.10 (0.96, 1.26)  Probable dementia 1.13 (0.97, 1.32) 0.71 (0.58, 0.86)*** 0.94 (0.82, 1.07) Number of chronic physical illnesses 1.06 (1.01, 1.10)** 1.06 (1.01, 1.12)* 1.07 (1.03, 1.11)*** Number of needs for assistance with daily activities 1.13 (1.11, 1.16)*** 1.01 (0.99, 1.04) 1.10 (1.08, 1.12)*** Hospitalized in past 12 months 1.05 (0.93, 1.19) 1.02 (0.89, 1.17) 1.02 (0.93, 1.13) Community social support 0.85 (0.77, 0.94)** 0.81 (0.72, 0.91)*** 0.90 (0.83, 0.97)** Long-term care insurance 1.07 (0.90, 1.27) 1.02 (0.85, 1.24) 0.92 (0.80, 1.07) Medicare-Medicaid dual enrollees 1.16 (1.00, 1.35)* 1.21 (1.01, 1.47)* 1.05 (0.93, 1.19) Model specifics  Number of persons 1,731 2,634 4,348  Number of person-years 3,493 5,804 2,122  Likelihood-ratio test of alpha = 0: χ2(01) 34.0*** 291.73*** 89.88***  Likelihood-ratio test of fitted model vs null model: χ2(18) 242.43*** 106.99*** 253.12*** Notes: ADL = activities of daily living; IADL = instrumental activities of daily living. Independent variables in period t−1 were used to predict dependent variables in period t. Analytical sample consisted of persons who reported needing assistance in a specific domain (i.e., ADL, IADL, and mobility) for any 2 consecutive years between 2011 and 2015. Survey wave was included as a covariate (results not shown). 95% confidence intervals in parentheses. *p < .05, **p < .01, ***p < .001. View Large Table 3. Incidence Rate Ratios for Lagged Independent Variables Associated With the Count of Adverse Consequences of Unmet Needs From Mixed-Effects Negative Binomial Regression Domains of adverse consequences of unmet needs Lagged independent variables ADL IADL Mobility Elevated depressive symptoms 1.24 (1.09, 1.41)** 1.24 (1.06, 1.44)** 1.14 (1.03, 1.27)* Age in 5-year interval 0.97 (0.93, 1.01) 0.89 (0.84, 0.94)*** 0.98 (0.94, 1.01) Male sex 0.98 (0.85, 1.13) 1.14 (0.96, 1.36) 0.91 (0.81, 1.03) Race/ethnicity  White, Non-Hispanic Reference Reference Reference  Black, Non-Hispanic 0.90 (0.77, 1.05) 0.97 (0.80, 1.18) 1.01 (0.88, 1.15)  Hispanic 0.85 (0.66, 1.08) 1.24 (0.92, 1.69) 1.37 (1.13, 1.66)**  Other 1.31 (0.92, 1.85) 1.08 (0.69, 1.69) 1.58 (1.18, 2.12)** Education  Less than high school Reference Reference Reference  High school 1.03 (0.87, 1.23) 0.93 (0.74, 1.16) 1.04 (0.90, 1.20)  Some college, no degree 1.08 (0.89, 1.31) 1.21 (0.95, 1.53) 1.01 (0.86, 1.19)  College graduate 1.14 (0.95, 1.38) 1.31 (1.04, 1.66)* 1.05 (0.89, 1.23) Dementia status  No dementia Reference Reference Reference  Possible dementia 1.12 (0.93, 1.33) 0.92 (0.77, 1.12) 1.10 (0.96, 1.26)  Probable dementia 1.13 (0.97, 1.32) 0.71 (0.58, 0.86)*** 0.94 (0.82, 1.07) Number of chronic physical illnesses 1.06 (1.01, 1.10)** 1.06 (1.01, 1.12)* 1.07 (1.03, 1.11)*** Number of needs for assistance with daily activities 1.13 (1.11, 1.16)*** 1.01 (0.99, 1.04) 1.10 (1.08, 1.12)*** Hospitalized in past 12 months 1.05 (0.93, 1.19) 1.02 (0.89, 1.17) 1.02 (0.93, 1.13) Community social support 0.85 (0.77, 0.94)** 0.81 (0.72, 0.91)*** 0.90 (0.83, 0.97)** Long-term care insurance 1.07 (0.90, 1.27) 1.02 (0.85, 1.24) 0.92 (0.80, 1.07) Medicare-Medicaid dual enrollees 1.16 (1.00, 1.35)* 1.21 (1.01, 1.47)* 1.05 (0.93, 1.19) Model specifics  Number of persons 1,731 2,634 4,348  Number of person-years 3,493 5,804 2,122  Likelihood-ratio test of alpha = 0: χ2(01) 34.0*** 291.73*** 89.88***  Likelihood-ratio test of fitted model vs null model: χ2(18) 242.43*** 106.99*** 253.12*** Domains of adverse consequences of unmet needs Lagged independent variables ADL IADL Mobility Elevated depressive symptoms 1.24 (1.09, 1.41)** 1.24 (1.06, 1.44)** 1.14 (1.03, 1.27)* Age in 5-year interval 0.97 (0.93, 1.01) 0.89 (0.84, 0.94)*** 0.98 (0.94, 1.01) Male sex 0.98 (0.85, 1.13) 1.14 (0.96, 1.36) 0.91 (0.81, 1.03) Race/ethnicity  White, Non-Hispanic Reference Reference Reference  Black, Non-Hispanic 0.90 (0.77, 1.05) 0.97 (0.80, 1.18) 1.01 (0.88, 1.15)  Hispanic 0.85 (0.66, 1.08) 1.24 (0.92, 1.69) 1.37 (1.13, 1.66)**  Other 1.31 (0.92, 1.85) 1.08 (0.69, 1.69) 1.58 (1.18, 2.12)** Education  Less than high school Reference Reference Reference  High school 1.03 (0.87, 1.23) 0.93 (0.74, 1.16) 1.04 (0.90, 1.20)  Some college, no degree 1.08 (0.89, 1.31) 1.21 (0.95, 1.53) 1.01 (0.86, 1.19)  College graduate 1.14 (0.95, 1.38) 1.31 (1.04, 1.66)* 1.05 (0.89, 1.23) Dementia status  No dementia Reference Reference Reference  Possible dementia 1.12 (0.93, 1.33) 0.92 (0.77, 1.12) 1.10 (0.96, 1.26)  Probable dementia 1.13 (0.97, 1.32) 0.71 (0.58, 0.86)*** 0.94 (0.82, 1.07) Number of chronic physical illnesses 1.06 (1.01, 1.10)** 1.06 (1.01, 1.12)* 1.07 (1.03, 1.11)*** Number of needs for assistance with daily activities 1.13 (1.11, 1.16)*** 1.01 (0.99, 1.04) 1.10 (1.08, 1.12)*** Hospitalized in past 12 months 1.05 (0.93, 1.19) 1.02 (0.89, 1.17) 1.02 (0.93, 1.13) Community social support 0.85 (0.77, 0.94)** 0.81 (0.72, 0.91)*** 0.90 (0.83, 0.97)** Long-term care insurance 1.07 (0.90, 1.27) 1.02 (0.85, 1.24) 0.92 (0.80, 1.07) Medicare-Medicaid dual enrollees 1.16 (1.00, 1.35)* 1.21 (1.01, 1.47)* 1.05 (0.93, 1.19) Model specifics  Number of persons 1,731 2,634 4,348  Number of person-years 3,493 5,804 2,122  Likelihood-ratio test of alpha = 0: χ2(01) 34.0*** 291.73*** 89.88***  Likelihood-ratio test of fitted model vs null model: χ2(18) 242.43*** 106.99*** 253.12*** Notes: ADL = activities of daily living; IADL = instrumental activities of daily living. Independent variables in period t−1 were used to predict dependent variables in period t. Analytical sample consisted of persons who reported needing assistance in a specific domain (i.e., ADL, IADL, and mobility) for any 2 consecutive years between 2011 and 2015. Survey wave was included as a covariate (results not shown). 95% confidence intervals in parentheses. *p < .05, **p < .01, ***p < .001. View Large Number of adverse consequences of unmet needs differed by demographic characteristics. The incidence rate of adverse consequences of unmet needs for assistance with IADL slightly declined with age. Non-black racial minorities (e.g., Asian and Pacific Islanders, American Indians, mixed race) and Hispanics had a higher incidence rate of adverse consequences associated with mobility as compared to non-Hispanic whites. People with college degrees as compared to those without a high school diploma had a higher incidence rate of adverse consequences for assistance with IADL. Several time-varying covariates were significantly associated with adverse consequences of unmet needs. Compared to those without dementia, participants with probable dementia at the prior wave had lower incidence rate of adverse consequences of unmet needs for assistance with IADL. Number of chronic physical illnesses and needs for assistance at the prior wave were associated with greater incidence rates of adverse consequences of unmet needs. Prior-wave community social support was consistently associated with lower incidence rate of adverse consequences of unmet needs. Prior-wave Medicare–Medicaid dual enrollees had greater incidence rate of adverse consequences associated with ADL and IADL needs. Table 4 shows the predicted counts of adverse consequences of unmet needs by depression status. Older adults with elevated depressive symptoms at a prior wave were expected to have an average of a 0.41 count of adverse consequences of unmet needs for assistance with ADL, a 0.33 count for that with IADL, and 0.51 for that with mobility. Given the same value of covariates, the predicted count of adverse consequences of unmet needs was 0.33 for ADL needs, 0.20 for IADL needs, and 0.45 for mobility needs among older adults without elevated depressive symptoms at a prior wave. Table 4. Predicted Counts of Adverse Consequences of Unmet Needs by Depression Status Predicted counts of adverse consequences of unmet needs With elevated depressive symptoms Without elevated depressive symptoms Activities of daily living 0.41 (0.37, 0.45) 0.33 (0.30, 0.36) Instrumental activities of daily living 0.24 (0.21, 0.28) 0.20 (0.18, 0.21) Mobility 0.51 (0.47, 0.56) 0.45 (0.42, .0.48) Predicted counts of adverse consequences of unmet needs With elevated depressive symptoms Without elevated depressive symptoms Activities of daily living 0.41 (0.37, 0.45) 0.33 (0.30, 0.36) Instrumental activities of daily living 0.24 (0.21, 0.28) 0.20 (0.18, 0.21) Mobility 0.51 (0.47, 0.56) 0.45 (0.42, .0.48) Note: Predicted counts of adverse consequences were obtained using margins command in Stata, after the estimation of mixed-effects negative binomial regression using prior-wave depressive symptoms and covariates to predict current-wave adverse consequences in each domain. 95% confidence intervals in parentheses. p < .05 for comparisons by depression status. View Large Table 4. Predicted Counts of Adverse Consequences of Unmet Needs by Depression Status Predicted counts of adverse consequences of unmet needs With elevated depressive symptoms Without elevated depressive symptoms Activities of daily living 0.41 (0.37, 0.45) 0.33 (0.30, 0.36) Instrumental activities of daily living 0.24 (0.21, 0.28) 0.20 (0.18, 0.21) Mobility 0.51 (0.47, 0.56) 0.45 (0.42, .0.48) Predicted counts of adverse consequences of unmet needs With elevated depressive symptoms Without elevated depressive symptoms Activities of daily living 0.41 (0.37, 0.45) 0.33 (0.30, 0.36) Instrumental activities of daily living 0.24 (0.21, 0.28) 0.20 (0.18, 0.21) Mobility 0.51 (0.47, 0.56) 0.45 (0.42, .0.48) Note: Predicted counts of adverse consequences were obtained using margins command in Stata, after the estimation of mixed-effects negative binomial regression using prior-wave depressive symptoms and covariates to predict current-wave adverse consequences in each domain. 95% confidence intervals in parentheses. p < .05 for comparisons by depression status. View Large Discussion One in five older adults with needs for assistance with daily activities had elevated depressive symptoms. The prevalence rate of adverse consequences of unmet needs in older adults with elevated depressive symptoms was twice as high as that in older adults without depression. After adjusting for potential confounders, older adults with elevated depressive symptoms at the prior wave had 1.24 times the rate of ADL- and IADL-related adverse consequences of unmet needs, and 1.14 times the rate of morbidly related adverse consequences of unmet needs. This study is the first to examine the longitudinal association of depressive symptoms and the number of adverse consequences of unmet needs for assistance with daily activities among Medicare beneficiaries. We included multiple domains of needs and conducted a population-based study. Previous studies have suggested a temporary association of poor mental health functioning (e.g., depressive symptoms, psychological distress) and unmet needs (Allen & Mor, 1997; Choi & McDougall, 2009; Quail, Wolfson, & Lippman, 2011). This study extends previous work by showing the vulnerability of older adults with depression in terms of a longer-term risk of adverse events due to inadequate assistance for performing daily activities. The link between depression and adverse consequences of unmet needs provides an alternative explanation for the high rates of hospitalization and nursing home admissions among older adults with depression (Xiang & An, 2015). This link could also explain why older adults with depressive symptoms report lower quality of life given that the adverse consequences examined are closely related to quality of life (Chachamovich, Fleck, Laidlaw, & Power, 2008). The mechanisms underlying the pathway from depression to adverse consequences of unmet needs are beyond the scope of this study. As previously mentioned, depression could increase the risk of adverse consequences due to its association with severity of illness and impairment and LTSS access. Depressive symptoms such as social withdrawal, avoidance, and passivity may discourage help seeking behaviors and inhibit the expression of needs (Barney, Griffiths, Christensen, & Jorm, 2009). Depressive symptoms could also reduce the motivation to care for one’s needs and cause self-neglect (Egede & Osborn, 2010). Future studies should focus on identifying amenable mechanisms such as LTSS access. Non-black minorities as compared to non-Hispanic whites reported a higher incidence rate of mobility-related adverse consequences. Minority older adults are more likely to live in substandard, inaccessible housing, and live alone in socially and economically disadvantaged areas with limited resources to improve their home environment (Clarke & Gallagher, 2013). Unexpectedly, college degree was associated with a higher incidence rate of IADL-related adverse consequences. An examination of the unadjusted prevalence rate of each IADL-related adverse consequence showed no significant differences by education level, with the exception of medication-related adverse consequence. More than one in five older adults with a college degree reported making a mistake in taking medications in past month compared to one in 10 older adults without a high school diploma. This result could reflect a reporting bias associated with education level such that people with higher education are more likely to become aware and report a mistake in taking prescribed medications. Consistent with Allen et al.’s framework (2014), number of chronic physical illnesses and needs were associated with higher rates of adverse consequences of unmet needs whereas community social support was associated with lower rates of adverse consequences. Unexpectedly, probable dementia was associated with a lower rate of IADL-related adverse consequences. An examination of the unadjusted prevalence rate of each IADL-related adverse consequence showed that the biggest difference was medication-related adverse consequence. Among older adults needing assistance taking medications, more than one in five of those with no or possible dementia reported making a mistake in taking medications in the past month. The rate was halved among older adults with probable dementia. Caregivers of people with dementia tend to provide more extensive assistance than caregivers of people with other conditions, possibly due to the heightened dependency of people with dementia (Alzheimer’s Association, 2014). As a result, people with dementia experience a lower rate of adverse consequences. This is consistent with the Allen et al.’s framework (2014), which proposes the adequacy of family support moderates the relationship between severity of illness and adverse consequences of unmet needs. Medicare–Medicaid dual eligibles have higher rates of ADL- and IADL-related adverse consequences. This finding contradicts our conceptualization that Medicaid coverage would reduce this risk by providing better LTSS coverage. Although dual eligibles have better insurance coverage for formal LTSS than their counterparts with Medicare only, this coverage may not translate into better quality of care. Dual eligibles experience elevated social and economic disadvantages, burden of disease and disability, and risk of poor quality LTSS (Rahman, Grabowski, Gozalo, Thomas, & Mor, 2014). A recent descriptive study showed higher rates of adverse consequences of unmet needs for several daily activities among Medicare–Medicaid dual eligibles as compared to those with Medicare only (Allen et al., 2014). Dual eligibility status may be better conceptualized as a constellation of social, psychological, and physical vulnerabilities than an indicator of access to LTSS. The higher risk of adverse consequences of unmet needs among dual eligibles also implies that better insurance coverage for LTSS is not enough. A focus on improving the quality of LTSS is needed. Implications for Policy and Practice The temporary and longitudinal association of depressive symptoms and adverse consequences of unmet needs call for coordination and integration of mental health services and LTSS, particularly home- and community-based services. Medicaid is the single largest payer for both mental health services (CMS, 2015) and LTSS (Reaves & Musumeci, 2015). More states are expanding home- and community-based services and delivering mental health services and LTSS through capitated Medicaid managed care programs (Saucier, Kasten, Burwell, & Gold, 2012), which has the potential to improve access and quality of services. Several states have also formed state mental health and aging coalitions to improve access to mental health services for older adults. The establishment of the Aging and Disability Resource Center Program in 2003—a single point of entry into LTSS for older adults and persons with disability—creates additional opportunities to integrate mental health services and LTSS. Despite these opportunities, challenges remain meeting the mental health and LTSS needs of the aging population. Ageism and stigma associated with mental illness, a shortage of health and mental health providers who specialize in geriatrics, concerns over the quality of home- and community-based services, and barriers to implementing evidence-based programs in the real world settings are among the frequently voiced challenges (Allen et al., 2014; Bartels, 2003; Leichsenring, 2004; Sirey et al., 2001). Future research, practice, advocacy, and policy efforts should address these challenges to enhance community living. Preventing and treating depression in late life may have added benefit of reducing the needs for LTSS and the incidence of adverse consequences for unmet needs, which, in turn, can improve quality of life among older adults. Future studies should explore whether alleviation of depressive symptoms are associated with a reduction in the needs for LTSS and associated adverse consequences. Depression prevention and treatment intervention studies should also consider including the needs for LTSS and associated adverse consequences as secondary intervention outcomes. Limitations This study has several limitations. Bradshaw (1972) classifies the operationalization of needs into four categories: normative need (distinguished by experts), felt need (as perceived by an individual), expressed need (the amount of help received or demanded), and comparative need (assessed in reference to the needs of individuals with similar characteristics). The measures used in this study assessed expressed need (whether assistance was received) and felt need (perceived difficulty in performing daily activity alone). Discrepancies between different definitions of needs have been documented (Verbrugge & Sevak, 2002). In addition, we used a dichotomous indicator of needs and did not assess needs as a continuum (LaPlante et al., 2004). Assessment of depressive symptoms was limited to PHQ-2, which is designed as a screener to be followed by the PHQ-9 to probe depression severity. Study findings were based on an observational study and causality cannot be inferred. The lagged association between depressive symptoms at time t−1 and adverse consequences of unmet needs at time t is likely to be influenced by the temporary association between depression and adverse consequences at time t−1 continuing to time t. We conducted sensitivity analysis using Cox proportional hazards model to examine the relationship between depression and new occurrence of adverse consequences among participants who were initially free of adverse consequences. These results conformed to the findings reported here. Study sample was restricted to people needing assistance for two consecutive years, representing a population with high needs. Generalizations to older adults with a low level of needs may be problematic. Due to low counts of adverse consequences on some items, we grouped adverse consequences into three needs domains in multivariable analysis and could not examine within-domain variation. Conclusions Depressive symptoms are positively associated with the number of adverse consequences of unmet needs for assistance with daily activities among older adults. Coordinated and integrated mental health services and LTSS programs are needed to improve access and quality of care for older adults with both mental health and long-term care needs. Funding This work was supported by a training grant from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR), located in the Administration for Community Living (ACL) in the U.S. Department of Health and Human Services, Grant Number 90AR5019 (PI: Allen Heinemann, PhD). Conflict of Interest The authors declare that there is no conflict of interest. References Allen S. M. , & Mor V . ( 1997 ). The prevalence and consequences of unmet need. Contrasts between older and younger adults with disability . Medical Care , 35 ( 11 ), 1132 – 1148 . doi:10.1097/00005650-199711000-00005 Google Scholar CrossRef Search ADS PubMed Allen S. M. Piette E. R. , & Mor V . ( 2014 ). 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Depression and Unmet Needs for Assistance With Daily Activities Among Community-Dwelling Older Adults

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Abstract

Abstract Background and Objectives This study aims to investigate the impact of depressive symptoms on adverse consequences of unmet needs for assistance with daily activities among community-dwelling older adults. Research Design and Methods Data came from round 1 to 5 of the National Health and Aging Trends Study. Study sample consisted of 3,400 Medicare beneficiaries needing assistance with activities of daily living (ADL), instrumental activities of daily living (IADL), or mobility for any two consecutive years between 2011 and 2015. Study outcome was the number of self-reported adverse consequences of unmet needs for assistance with daily activities (e.g., went without eating, wet or soiled clothes). Mixed-effects negative binomial regression was used to estimate the association of lagged depressive symptoms and covariates in period t−1 and the number of adverse consequences of unmet needs in period t. Results The prevalence rates of adverse consequences of unmet needs were twice as high among older adults with elevated depressive symptoms as those without depression. After adjusting for covariates, prior wave depressive symptoms were associated with 1.24 times the rate of adverse consequences of unmet needs for assistance with ADL (Incidence Rate Ratio [IRR] = 1.24, 95% confidence interval [CI] = 1.09–1.41, p < .01) and IADL (IRR = 1.24, 95% CI = 1.06–1.44, p < .01), and 1.14 times the rate of adverse consequences of unmet needs for assistance with mobility (IRR = 1.14, 95% CI = 1.03–1.27, p < .05). Discussion and Implications Caring for older adults with mental health and long-term care needs calls for an integrated social and health services system. Depression, Long-term care, Unmet need, Adverse consequences An estimated 20–40% of U.S. older adults needing assistance with daily activities, such as dressing, eating, and shopping for groceries, report unmet needs or receive insufficient assistance (Allen, Piette, & Mor, 2014; Desai, Lentzner, & Weeks, 2001; Kennedy, 2001; LaPlante, Kaye, Kang, & Harrington, 2004; Shea et al., 2003). Up to half of these older adults experience adverse consequences due to unmet needs, such as going without eating, wetting or soiling clothes, making a mistake in taking medications, and having to stay inside (Allen & Mor, 1997; Allen et al., 2014; Desai et al., 2001). These adverse consequences of unmet needs have a profound impact on older adults’ quality of life and health outcomes. A number of studies have suggested that unmet needs precede functional decline and increase the risk of emergency room visit, hospital admission, nursing home placement, and premature mortality (Gaugler, Kane, Kane, & Newcomer, 2005; Hass, DePalma, Craig, Xu, & Sands, 2015; Xu, Covinsky, Stallard, Thomas, & Sands, 2012). Preventing adverse consequences of unmet needs has important public health implications for improving the quality of life of older adults and reducing health care costs. Previous studies have consistently linked physical function limitations to adverse consequences of unmet needs for assistance with daily activities (Allen et al., 2014; Desai et al., 2001; LaPlante et al., 2004). However, little is known regarding the psychosocial risk factors. This study begins to fill this knowledge gap by assessing the impact of depressive symptoms on the adverse consequences of unmet needs. Depression is a leading cause of global disease burden (Ferrari et al., 2013). Clinically significant depressive symptoms affect 15% of community-living older adults (Blazer, 2003), and the rate is substantially higher among people with physical function limitations (Chen et al., 2012). As an important indicator of psychosocial health, depressive symptoms can be treated successfully with psychotherapy, pharmacological treatment, or a combination (DeRubeis, Siegle, & Hollon, 2008). Examining the impact of depressive symptoms may inform practice and policy to reduce the incidence of adverse consequences of unmet needs for assistance with daily activities. Conceptual Framework Allen et al (2014) constructed a conceptual framework on the pathway to unmet need and its adverse consequences, which was the basis of the framework of this study. Severity of illness and impairment determines the level of needs for assistance. Whether needs for assistance will cause adverse consequences depends on the adequacy of informal and formal long-term services and supports (LTSS). In the case of individuals with depression, level of needs for assistance is higher than those without depression due to the increased severity of illness and impairment associated with depression. Depressive symptoms can cause neural, hormonal, and immunological alterations and worsen physical health and functioning (Penninx et al., 1998). Studies have consistently showed that depression increases the risk of physical disability (Ormel, Rijsdijk, Sullivan, van Sonderen, & Kempen, 2002; Schillerstrom, Royall, & Palmer, 2008). Depression may also increase the risk of adverse consequences by limiting informal and formal LTSS access. The interpersonal theory of depression posits that the behaviors of individuals with depression such as negative self-statements, passivity, and social withdrawal can erode social support (Hames, Hagan, & Joiner, 2013), limiting the availability and intensity of informal LTSS from family, friends, and neighbors. The socioeconomic disadvantages associated with depression and other mental illness (Muntaner, Eaton, Miech, & O’Campo, 2004) reduce access to formal LTSS by diminishing the ability to purchase long-term care insurance and services. The purpose of this study is to investigate the impact of depressive symptoms on adverse consequences of unmet needs for assistance with activities of daily living (ADL), instrumental activities of daily living (IADL), and mobility. The primary study hypothesis is that elevated depressive symptoms at prior wave (i.e., period t−1) are associated with more adverse consequences of unmet needs at current wave (i.e., period t). Figure 1 shows the 1-year lagged effect of depressive symptoms on adverse consequences of unmet needs. This analytical model was set up to establish a time order between depressive symptoms and adverse consequences of unmet needs. Figure 1. View largeDownload slide Analytical model of lagged effect of depressive symptoms on adverse consequences of unmet needs Figure 1. View largeDownload slide Analytical model of lagged effect of depressive symptoms on adverse consequences of unmet needs Design and Methods Data We analyzed data from round 1 (2011) through round 5 (2015) of the National Health and Aging Trends Study (NHATS). The NHATS is a nationally representative panel study of Medicare beneficiaries aged 65 years and older. Persons in older age groups and African Americans were oversampled. A total of 7,777 older adults who lived in the community (including traditional community settings, retirement communities, and alternative residential care) completed sample person interviews at baseline. Annual follow-up interviews were conducted regardless of their residential status. This study included 3,400 Medicare beneficiaries who reported needs for assistance with any daily activities (ADL, IADL, and mobility) for two consecutive years from 2011 to 2015. Study sample was restricted to participants needing assistance with daily activities because having a need is a prerequisite of experiencing adverse consequences of unmet needs. The restriction of reporting need for two consecutive years was necessary for estimating models with lagged independent variables. After excluding participants with missing data on the depression screener (n = 39), the final sample size was 3,361. Measures Needs for Assistance With Daily Activities The NHATS asks a series of questions regarding limitations in performing ADLs (including eating, bathing, toileting, and dressing), IADLs (including laundry, shopping for groceries or personal items, meal preparation, banking or paying bills, and keeping track of medication), and mobility tasks (going outside the home, getting around inside the home, and getting out of bed). Respondents were asked if, in the last month, they performed each activity with assistance or alone. Respondents who performed an activity with assistance were asked if the reason for assistance was related to health or functioning. Respondents who performed an activity alone were asked how difficult it was to do the activity. Respondents were classified as having needs for personal assistance if they (a) received assistance with an activity due to health or functioning reasons or (b) had difficulty performing an activity alone. Summary indicators of needs for assistance with daily activities were created for ADL, IADL, and mobility domains. Adverse Consequences of Unmet Needs Respondents who reported a need for assistance with a daily activity were asked if they experienced the adverse consequence associated with that activity due to lack of assistance or difficulty in performing the activity. For example, if respondents reported a need for assistance with eating, they would then be asked if they ever went without eating during the last month because no one was there to help or they had difficulty eating alone. Questions concerning adverse consequences were asked only for respondents who reported a need for assistance with that specific daily activity. The adverse consequences corresponding to the daily activities were: went without eating, went without taking a bath, wet or soiled clothes, went without getting dressed, went without clean laundry, went without groceries or personal items, went without a hot meal, went without handling bills and banking matters, made a mistake in taking prescribed medicines, had to stay inside, did not go to places inside one’s home, and had to stay in bed. Summary indicators of the number of adverse consequences were created by the domain of activities with which they were associated (i.e., adverse consequences associated with unmet needs for assistance with ADL, IADL, and mobility, respectively). Depression The Patient Health Questionnaire-2 (PHQ-2; Löwe, Kroenke, & Gräfe, 2005) is intended for use in clinical practice. It asks participants to rate how often they have been bothered by “little interest or pleasure in doing things” and “feeling down, depressed or hopeless” over the last 2 weeks on a 0–3 point scale. PHQ-2 scores range from 0 to 6. We used a cutoff score of 3 to indicate elevated depressive symptoms. A cutoff score of 3 has a sensitivity of 0.87 and a specificity of 0.78 for major depressive disorder, and a sensitivity of 0.79 and specificity of 0.86 for any depressive disorder (Löwe et al., 2005). Covariates Adjusting for potential confounding variables is important to determine the independent impact of depressive symptoms. Allen et al.’s framework (2014) and relevant literature guided the selection of possible common causes of depression and adverse consequence of unmet needs. Covariates included sociodemographic characteristics, indicators of illness and impairment severity, and proxies for access to informal and formal LTSS. Sociodemographic characteristics included age groups (65–69, 70–74, 75–79, 80–84, 85–89, or 90+), sex (female or male), race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, or other race/multi-race), and education (less than high school, high school graduate, some college but no degree, or college graduate). Indicators of illness and impairment included dementia status, the number of self-reported chronic physical illnesses (including heart disease, arthritis, osteoporosis, diabetes, lung disease, stroke, and cancer), an indicator of past-year hospitalization, and the count of needs for assistance with daily activities. NHATS classifies participants into 3 groups—no dementia, possible dementia, and probable dementia—based on self-reported diagnosis of dementia or Alzheimer’s disease, AD8 Dementia Screening Interview, and cognitive tests (Kasper, Freedman, & Spillman, 2013). A continuous variable of community social support was included as an indicator of informal LTSS. Community social support was a three-item measure of participants’ agreement with the following statements on a three-point Likert scale: people in this community “know each other well”, “are willing to help each other”, and “can be trusted”. Original responses were reverse coded and averaged to generate a composite score, with higher scores indicating better social support. This scale has good internal consistency in this study sample (Cronbach’s alpha = 0.73). Proxies of access to formal LTSS included a dichotomous indicator of long-term care insurance coverage and an indicator of Medicaid coverage (representing Medicare-Medicaid dual eligibility in this study). Data Analysis Chi-square tests were used to compare sample characteristics and prevalence rates of adverse consequences by depression status at baseline, accounting for NHATS complex survey design. Mixed-effects negative binomial regression models were estimated using prior-wave (period t−1) depressive symptoms and covariates to predict the number of adverse consequences of unmet needs for assistance with ADL, IALD, and mobility at current wave (period t), respectively. To ease the interpretation of model estimates, the postestimation command margins was used to calculate the predicted counts of adverse consequences of unmet needs for individuals with elevated depressive symptoms and those without. Statistical analyses were conducted using Stata 12.0 SE version (StataCorp, TX). We did not account for the complex survey design in mixed-effects models. Consensus has not been reached on how to incorporate weights in generalized linear mixed models with longitudinal data, particularly when the weights are not constant within the individual (Bertolet, 2008). NHATS provides different sampling weights at different study waves for the same individual. Methodological guidance is lacking regarding which weight to use. Second, simulation studies have found little differences between findings from unweighted analyses and scaled-weighted analyses, particularly in the case of noninformative sampling weights (where the sampling design does not correlate with the outcome; Carle, 2009). Third, there are limited software programs that can properly incorporate different types of scaled weights in generalized multilevel modeling (Carle, 2009). Results One in five (20.4%) older adults needing assistance for daily activities had elevated depressive symptoms at baseline, representing over 2.8 million people in the population. Table 1 presents weighted sample characteristics stratified by depression status at baseline. The following groups were overrepresented in older adults with elevated depressive symptoms: Hispanics, people with lower education, people with possible or probable dementia, people with more chronic physical illnesses and needs for personal assistance, people who were hospitalized in past 12 months, and Medicare-Medicaid dual eligibles. One in 10 older adults with elevated depressive symptoms reported long-term care insurance coverage as compared to 17% of those without elevated depressive symptoms. On average, older adults with elevated depressive symptoms reported 0.12 point lower on the community social support scale. Table 1. Weighted Sample Characteristics by Depression Status at Baseline With elevated depressive symptoms (n = 703) Without elevated depressive symptoms (2,658) p value Sociodemographic characteristics  Age groups (%) .277   65–69 years 21.6 (17.4, 26.6) 19.5 (17.9, 21.3)   70–74 years 21.7 (18.5, 25.2) 19.5 (17.7, 21.5)   75–79 years 20.2 (17.0, 23.7) 20.8 (19.2, 22.5)   80–84 years 18.1 (15.3, 21.3) 19.0 (17.6, 20.5)   85–89 years 13.5 (11.3, 16.0) 13.8 (12.3, 15.3)   90 years or over 5.0 (4.0, 6.2) 7.4 (6.3, 8.7)  Sex (%)   Female 61.2 (57.6, 64.6) 63.6 (61.5, 65.8) .271   Male 38.8 (35.4, 42.4) 36.4 (34.3, 38.5)  Race/ethnicity (%) <.001   White, Non-Hispanic 71.3 (66.0, 76.0) 80.2 (77.7, 82.4)   Black, Non-Hispanic 11.4 (9.4, 13.8) 8.8 (7.7, 9.9)   Hispanic 13.3 (10.1, 17.3) 7.0 (5.3, 9.2)   Other 4.0 (2.4, 6.6) 4.1 (2.9, 5.8)  Education (%) <.001   Less than high school 35.6 (31.2, 40.3) 22.9 (20.9, 25.0)   High school 28.8 (25.3, 32.5) 27.7 (25.7, 29.9)   Some college, no degree 17.7 (14.7, 21.1) 21.7 (19.7, 23.9)   College graduate 17.9 (14.3, 22.2) 27.7 (25.0, 30.5) Severity of illness and impairment  Dementia status (%) <.001   No dementia 57.2 (51.9, 62.4) 74.8 (72.7, 76.9)   Possible dementia 17.5 (14.3, 21.1) 12.4 (11.0, 14.0)   Probable dementia 25.3 (21.8, 29.2) 12.8 (11.3, 14.4)  Number of chronic physical illnesses (mean) 3.25 (3.12, 3.37) 2.67 (2.62, 2.73) <.001  Number of needs for assistance with daily activities (mean) 5.42 (5.11, 5.73) 2.85 (2.72, 2.98) <.001  Hospitalized in past 12 months 35.6 (31.9, 39.4) 24.6 (22.7, 26.6) <.001  Access to long-term services and supports   Community social support scale (mean) 2.28 (2.22, 2.33) 2.40 (2.37, 2.43) <.001   Long-term care insurance (%) 10.6 (8.3, 13.4) 17.4 (15.8,19.20) <.001   Medicare-Medicaid dual enrollees (%) 25.7 (22.2, 29.5) 14.8 (12.8, 17.1) <.001 With elevated depressive symptoms (n = 703) Without elevated depressive symptoms (2,658) p value Sociodemographic characteristics  Age groups (%) .277   65–69 years 21.6 (17.4, 26.6) 19.5 (17.9, 21.3)   70–74 years 21.7 (18.5, 25.2) 19.5 (17.7, 21.5)   75–79 years 20.2 (17.0, 23.7) 20.8 (19.2, 22.5)   80–84 years 18.1 (15.3, 21.3) 19.0 (17.6, 20.5)   85–89 years 13.5 (11.3, 16.0) 13.8 (12.3, 15.3)   90 years or over 5.0 (4.0, 6.2) 7.4 (6.3, 8.7)  Sex (%)   Female 61.2 (57.6, 64.6) 63.6 (61.5, 65.8) .271   Male 38.8 (35.4, 42.4) 36.4 (34.3, 38.5)  Race/ethnicity (%) <.001   White, Non-Hispanic 71.3 (66.0, 76.0) 80.2 (77.7, 82.4)   Black, Non-Hispanic 11.4 (9.4, 13.8) 8.8 (7.7, 9.9)   Hispanic 13.3 (10.1, 17.3) 7.0 (5.3, 9.2)   Other 4.0 (2.4, 6.6) 4.1 (2.9, 5.8)  Education (%) <.001   Less than high school 35.6 (31.2, 40.3) 22.9 (20.9, 25.0)   High school 28.8 (25.3, 32.5) 27.7 (25.7, 29.9)   Some college, no degree 17.7 (14.7, 21.1) 21.7 (19.7, 23.9)   College graduate 17.9 (14.3, 22.2) 27.7 (25.0, 30.5) Severity of illness and impairment  Dementia status (%) <.001   No dementia 57.2 (51.9, 62.4) 74.8 (72.7, 76.9)   Possible dementia 17.5 (14.3, 21.1) 12.4 (11.0, 14.0)   Probable dementia 25.3 (21.8, 29.2) 12.8 (11.3, 14.4)  Number of chronic physical illnesses (mean) 3.25 (3.12, 3.37) 2.67 (2.62, 2.73) <.001  Number of needs for assistance with daily activities (mean) 5.42 (5.11, 5.73) 2.85 (2.72, 2.98) <.001  Hospitalized in past 12 months 35.6 (31.9, 39.4) 24.6 (22.7, 26.6) <.001  Access to long-term services and supports   Community social support scale (mean) 2.28 (2.22, 2.33) 2.40 (2.37, 2.43) <.001   Long-term care insurance (%) 10.6 (8.3, 13.4) 17.4 (15.8,19.20) <.001   Medicare-Medicaid dual enrollees (%) 25.7 (22.2, 29.5) 14.8 (12.8, 17.1) <.001 Note: 95% confidence intervals in parentheses. Sampling weights and design factors were accounted for when estimating prevalences/means. View Large Table 1. Weighted Sample Characteristics by Depression Status at Baseline With elevated depressive symptoms (n = 703) Without elevated depressive symptoms (2,658) p value Sociodemographic characteristics  Age groups (%) .277   65–69 years 21.6 (17.4, 26.6) 19.5 (17.9, 21.3)   70–74 years 21.7 (18.5, 25.2) 19.5 (17.7, 21.5)   75–79 years 20.2 (17.0, 23.7) 20.8 (19.2, 22.5)   80–84 years 18.1 (15.3, 21.3) 19.0 (17.6, 20.5)   85–89 years 13.5 (11.3, 16.0) 13.8 (12.3, 15.3)   90 years or over 5.0 (4.0, 6.2) 7.4 (6.3, 8.7)  Sex (%)   Female 61.2 (57.6, 64.6) 63.6 (61.5, 65.8) .271   Male 38.8 (35.4, 42.4) 36.4 (34.3, 38.5)  Race/ethnicity (%) <.001   White, Non-Hispanic 71.3 (66.0, 76.0) 80.2 (77.7, 82.4)   Black, Non-Hispanic 11.4 (9.4, 13.8) 8.8 (7.7, 9.9)   Hispanic 13.3 (10.1, 17.3) 7.0 (5.3, 9.2)   Other 4.0 (2.4, 6.6) 4.1 (2.9, 5.8)  Education (%) <.001   Less than high school 35.6 (31.2, 40.3) 22.9 (20.9, 25.0)   High school 28.8 (25.3, 32.5) 27.7 (25.7, 29.9)   Some college, no degree 17.7 (14.7, 21.1) 21.7 (19.7, 23.9)   College graduate 17.9 (14.3, 22.2) 27.7 (25.0, 30.5) Severity of illness and impairment  Dementia status (%) <.001   No dementia 57.2 (51.9, 62.4) 74.8 (72.7, 76.9)   Possible dementia 17.5 (14.3, 21.1) 12.4 (11.0, 14.0)   Probable dementia 25.3 (21.8, 29.2) 12.8 (11.3, 14.4)  Number of chronic physical illnesses (mean) 3.25 (3.12, 3.37) 2.67 (2.62, 2.73) <.001  Number of needs for assistance with daily activities (mean) 5.42 (5.11, 5.73) 2.85 (2.72, 2.98) <.001  Hospitalized in past 12 months 35.6 (31.9, 39.4) 24.6 (22.7, 26.6) <.001  Access to long-term services and supports   Community social support scale (mean) 2.28 (2.22, 2.33) 2.40 (2.37, 2.43) <.001   Long-term care insurance (%) 10.6 (8.3, 13.4) 17.4 (15.8,19.20) <.001   Medicare-Medicaid dual enrollees (%) 25.7 (22.2, 29.5) 14.8 (12.8, 17.1) <.001 With elevated depressive symptoms (n = 703) Without elevated depressive symptoms (2,658) p value Sociodemographic characteristics  Age groups (%) .277   65–69 years 21.6 (17.4, 26.6) 19.5 (17.9, 21.3)   70–74 years 21.7 (18.5, 25.2) 19.5 (17.7, 21.5)   75–79 years 20.2 (17.0, 23.7) 20.8 (19.2, 22.5)   80–84 years 18.1 (15.3, 21.3) 19.0 (17.6, 20.5)   85–89 years 13.5 (11.3, 16.0) 13.8 (12.3, 15.3)   90 years or over 5.0 (4.0, 6.2) 7.4 (6.3, 8.7)  Sex (%)   Female 61.2 (57.6, 64.6) 63.6 (61.5, 65.8) .271   Male 38.8 (35.4, 42.4) 36.4 (34.3, 38.5)  Race/ethnicity (%) <.001   White, Non-Hispanic 71.3 (66.0, 76.0) 80.2 (77.7, 82.4)   Black, Non-Hispanic 11.4 (9.4, 13.8) 8.8 (7.7, 9.9)   Hispanic 13.3 (10.1, 17.3) 7.0 (5.3, 9.2)   Other 4.0 (2.4, 6.6) 4.1 (2.9, 5.8)  Education (%) <.001   Less than high school 35.6 (31.2, 40.3) 22.9 (20.9, 25.0)   High school 28.8 (25.3, 32.5) 27.7 (25.7, 29.9)   Some college, no degree 17.7 (14.7, 21.1) 21.7 (19.7, 23.9)   College graduate 17.9 (14.3, 22.2) 27.7 (25.0, 30.5) Severity of illness and impairment  Dementia status (%) <.001   No dementia 57.2 (51.9, 62.4) 74.8 (72.7, 76.9)   Possible dementia 17.5 (14.3, 21.1) 12.4 (11.0, 14.0)   Probable dementia 25.3 (21.8, 29.2) 12.8 (11.3, 14.4)  Number of chronic physical illnesses (mean) 3.25 (3.12, 3.37) 2.67 (2.62, 2.73) <.001  Number of needs for assistance with daily activities (mean) 5.42 (5.11, 5.73) 2.85 (2.72, 2.98) <.001  Hospitalized in past 12 months 35.6 (31.9, 39.4) 24.6 (22.7, 26.6) <.001  Access to long-term services and supports   Community social support scale (mean) 2.28 (2.22, 2.33) 2.40 (2.37, 2.43) <.001   Long-term care insurance (%) 10.6 (8.3, 13.4) 17.4 (15.8,19.20) <.001   Medicare-Medicaid dual enrollees (%) 25.7 (22.2, 29.5) 14.8 (12.8, 17.1) <.001 Note: 95% confidence intervals in parentheses. Sampling weights and design factors were accounted for when estimating prevalences/means. View Large Table 2 presents the population totals of people needing assistance and prevalence rates of adverse consequences of unmet needs for assistance with each daily activity at baseline. Older adults with elevated depressive symptoms reported higher rates of adverse consequences of unmet needs for 9 of the 12 daily activities compared to those without depression. People needing assistance toileting reported the highest rate of adverse consequence, with 55.8% of those with elevated depressive symptoms and 38% of those without depression reporting having wetted or soiled clothes. Rates of adverse consequences of unmet needs for all three mobility tasks were high among people with elevated depressive symptoms (21%, 33%, and 39%, respectively). Summary indicators showed that rates of adverse consequences of unmet needs were twice as high in older adults with elevated depressive symptoms as those without depression (37.4% vs 18.4% for ADL-related adverse consequences, 26.7% vs 15.4% for IADL-related adverse consequences, and 42.0% vs 24.5% for mobility-related adverse consequences, p < .001 for all comparisons). People with elevated depressive symptoms also reported higher number of adverse consequences associated with ADL (0.61 vs 0.33), IADL (0.52 vs 0.26), and mobility tasks (0.84 vs 0.51). Table 2. Baseline Prevalence Rates of Adverse Consequences of Unmet Needs for Assistance With Daily Activities Among Those Needing Assistance, by Depression Status With elevated depressive symptoms Without elevated depressive symptoms p value Activities of daily living  Need assistance eating N = 628,390 N = 867,632   Went without eating (%) 6.1 (2.6, 13.9) 3.5 (1.4, 8.8) .381  Need assistance bathing N = 1,209,958 N = 2,505,975   Went without taking a bath (%) 15.3 (11.1, 20.7) 11.6 (8.6, 15.3) .230  Need assistance toileting N = 831,646 N = 1,210,856   Wet or soiled clothes (%) 55.8 (48.8, 62.5) 38.0 (32.4, 43.9) <.001  Need assistance dressing N = 1,336,243 N = 2,836,948   Went without getting dressed (%) 15.1 (11.8, 19.1) 4.5 (2.9, 7.0) <.001  Need assistance with one or more ADL tasks N = 1,784,255 N = 4,068,451   Had at least one adverse consequence (%) 37.4 (32.3, 42.7) 18.4 (15.7, 21.4) <.001  Number of adverse consequences (mean) 0.61 (0.52, 0.69) 0.33 (0.27, 0.38) <.001 Instrumental activities of daily living  Need assistance doing laundry N = 1,389,761 N = 2,772,108   Went without clean laundry (%) 10.5 (6.2, 17.3) 1.9 (1.0, 3.7) <.001  Need assistance shopping for groceries/personal items N = 1,665,397 N = 3,794,956   Went without groceries or personal items (%) 10.1 (6.9, 14.7) 5.3 (3.7, 7.6) .014  Need assistance with meal preparation N = 1,513,272 N = 3,328,722   Went without a hot meal (%) 13.4 (9.9, 17.9) 8.4 (6.7, 10.4) .009  Need assistance banking or paying bills N = 1,316,544 N = 2,493,475   Went without handling bills/ banking matters (%) 10.4 (6.7, 15.9) 4.0 (2.3, 7.0) .004  Need assistance keeping track of medication N = 1,214,658 N = 2,679,613   Made a mistake in taking prescribed medicines (%) 21.8 (16.5, 28.1) 19.5 (16.4, 23.0) .451  Need assistance with one or more IADL tasks N = 2,235,069 N = 6,221,082   Had at least one adverse consequence (%) 26.7 (22.5, 31.5) 15.4 (13.7, 17.4) <.001  Number of adverse consequences (mean) 0.52 (0.36,0.68) 0.26 (0.21, 0.31) <.001 Mobility  Need assistance going outside the home N = 1,426,294 N = 3,257,959   Had to stay inside (%) 38.7 (32.7, 45.1) 24.6 (20.6, 29.1) <.001  Need assistance getting around inside the home N = 1,425,890 N = 2,918,625   Did not go to places inside one’s home (%) 32.6 (28.0, 37.6) 23.7 (20.0, 27.8) .008  Needing assistance getting out of bed N = 1,480,312 N = 3,016,622   Had to stay in bed (%) 20.6 (16.2, 25.9) 7.3 (5.4, 9.6) <.001  Need assistance with one or more mobility tasks N = 2,030,479 N = 5,237,974   Had at least one adverse consequence (%) 42.0 (37.0, 47.2) 24.5 (21.6, 27.6) <.001  Number of adverse consequences (mean) 0.84 (0.74, 0.95) 0.51 (0.43, 0.58) <.001 With elevated depressive symptoms Without elevated depressive symptoms p value Activities of daily living  Need assistance eating N = 628,390 N = 867,632   Went without eating (%) 6.1 (2.6, 13.9) 3.5 (1.4, 8.8) .381  Need assistance bathing N = 1,209,958 N = 2,505,975   Went without taking a bath (%) 15.3 (11.1, 20.7) 11.6 (8.6, 15.3) .230  Need assistance toileting N = 831,646 N = 1,210,856   Wet or soiled clothes (%) 55.8 (48.8, 62.5) 38.0 (32.4, 43.9) <.001  Need assistance dressing N = 1,336,243 N = 2,836,948   Went without getting dressed (%) 15.1 (11.8, 19.1) 4.5 (2.9, 7.0) <.001  Need assistance with one or more ADL tasks N = 1,784,255 N = 4,068,451   Had at least one adverse consequence (%) 37.4 (32.3, 42.7) 18.4 (15.7, 21.4) <.001  Number of adverse consequences (mean) 0.61 (0.52, 0.69) 0.33 (0.27, 0.38) <.001 Instrumental activities of daily living  Need assistance doing laundry N = 1,389,761 N = 2,772,108   Went without clean laundry (%) 10.5 (6.2, 17.3) 1.9 (1.0, 3.7) <.001  Need assistance shopping for groceries/personal items N = 1,665,397 N = 3,794,956   Went without groceries or personal items (%) 10.1 (6.9, 14.7) 5.3 (3.7, 7.6) .014  Need assistance with meal preparation N = 1,513,272 N = 3,328,722   Went without a hot meal (%) 13.4 (9.9, 17.9) 8.4 (6.7, 10.4) .009  Need assistance banking or paying bills N = 1,316,544 N = 2,493,475   Went without handling bills/ banking matters (%) 10.4 (6.7, 15.9) 4.0 (2.3, 7.0) .004  Need assistance keeping track of medication N = 1,214,658 N = 2,679,613   Made a mistake in taking prescribed medicines (%) 21.8 (16.5, 28.1) 19.5 (16.4, 23.0) .451  Need assistance with one or more IADL tasks N = 2,235,069 N = 6,221,082   Had at least one adverse consequence (%) 26.7 (22.5, 31.5) 15.4 (13.7, 17.4) <.001  Number of adverse consequences (mean) 0.52 (0.36,0.68) 0.26 (0.21, 0.31) <.001 Mobility  Need assistance going outside the home N = 1,426,294 N = 3,257,959   Had to stay inside (%) 38.7 (32.7, 45.1) 24.6 (20.6, 29.1) <.001  Need assistance getting around inside the home N = 1,425,890 N = 2,918,625   Did not go to places inside one’s home (%) 32.6 (28.0, 37.6) 23.7 (20.0, 27.8) .008  Needing assistance getting out of bed N = 1,480,312 N = 3,016,622   Had to stay in bed (%) 20.6 (16.2, 25.9) 7.3 (5.4, 9.6) <.001  Need assistance with one or more mobility tasks N = 2,030,479 N = 5,237,974   Had at least one adverse consequence (%) 42.0 (37.0, 47.2) 24.5 (21.6, 27.6) <.001  Number of adverse consequences (mean) 0.84 (0.74, 0.95) 0.51 (0.43, 0.58) <.001 Notes: ADL = activities of daily living; IADL = instrumental activities of daily living. N represents estimated population totals. 95% confidence intervals in parentheses. Sampling weights and design factors were adjusted when estimating population totals, prevalence, and means. View Large Table 2. Baseline Prevalence Rates of Adverse Consequences of Unmet Needs for Assistance With Daily Activities Among Those Needing Assistance, by Depression Status With elevated depressive symptoms Without elevated depressive symptoms p value Activities of daily living  Need assistance eating N = 628,390 N = 867,632   Went without eating (%) 6.1 (2.6, 13.9) 3.5 (1.4, 8.8) .381  Need assistance bathing N = 1,209,958 N = 2,505,975   Went without taking a bath (%) 15.3 (11.1, 20.7) 11.6 (8.6, 15.3) .230  Need assistance toileting N = 831,646 N = 1,210,856   Wet or soiled clothes (%) 55.8 (48.8, 62.5) 38.0 (32.4, 43.9) <.001  Need assistance dressing N = 1,336,243 N = 2,836,948   Went without getting dressed (%) 15.1 (11.8, 19.1) 4.5 (2.9, 7.0) <.001  Need assistance with one or more ADL tasks N = 1,784,255 N = 4,068,451   Had at least one adverse consequence (%) 37.4 (32.3, 42.7) 18.4 (15.7, 21.4) <.001  Number of adverse consequences (mean) 0.61 (0.52, 0.69) 0.33 (0.27, 0.38) <.001 Instrumental activities of daily living  Need assistance doing laundry N = 1,389,761 N = 2,772,108   Went without clean laundry (%) 10.5 (6.2, 17.3) 1.9 (1.0, 3.7) <.001  Need assistance shopping for groceries/personal items N = 1,665,397 N = 3,794,956   Went without groceries or personal items (%) 10.1 (6.9, 14.7) 5.3 (3.7, 7.6) .014  Need assistance with meal preparation N = 1,513,272 N = 3,328,722   Went without a hot meal (%) 13.4 (9.9, 17.9) 8.4 (6.7, 10.4) .009  Need assistance banking or paying bills N = 1,316,544 N = 2,493,475   Went without handling bills/ banking matters (%) 10.4 (6.7, 15.9) 4.0 (2.3, 7.0) .004  Need assistance keeping track of medication N = 1,214,658 N = 2,679,613   Made a mistake in taking prescribed medicines (%) 21.8 (16.5, 28.1) 19.5 (16.4, 23.0) .451  Need assistance with one or more IADL tasks N = 2,235,069 N = 6,221,082   Had at least one adverse consequence (%) 26.7 (22.5, 31.5) 15.4 (13.7, 17.4) <.001  Number of adverse consequences (mean) 0.52 (0.36,0.68) 0.26 (0.21, 0.31) <.001 Mobility  Need assistance going outside the home N = 1,426,294 N = 3,257,959   Had to stay inside (%) 38.7 (32.7, 45.1) 24.6 (20.6, 29.1) <.001  Need assistance getting around inside the home N = 1,425,890 N = 2,918,625   Did not go to places inside one’s home (%) 32.6 (28.0, 37.6) 23.7 (20.0, 27.8) .008  Needing assistance getting out of bed N = 1,480,312 N = 3,016,622   Had to stay in bed (%) 20.6 (16.2, 25.9) 7.3 (5.4, 9.6) <.001  Need assistance with one or more mobility tasks N = 2,030,479 N = 5,237,974   Had at least one adverse consequence (%) 42.0 (37.0, 47.2) 24.5 (21.6, 27.6) <.001  Number of adverse consequences (mean) 0.84 (0.74, 0.95) 0.51 (0.43, 0.58) <.001 With elevated depressive symptoms Without elevated depressive symptoms p value Activities of daily living  Need assistance eating N = 628,390 N = 867,632   Went without eating (%) 6.1 (2.6, 13.9) 3.5 (1.4, 8.8) .381  Need assistance bathing N = 1,209,958 N = 2,505,975   Went without taking a bath (%) 15.3 (11.1, 20.7) 11.6 (8.6, 15.3) .230  Need assistance toileting N = 831,646 N = 1,210,856   Wet or soiled clothes (%) 55.8 (48.8, 62.5) 38.0 (32.4, 43.9) <.001  Need assistance dressing N = 1,336,243 N = 2,836,948   Went without getting dressed (%) 15.1 (11.8, 19.1) 4.5 (2.9, 7.0) <.001  Need assistance with one or more ADL tasks N = 1,784,255 N = 4,068,451   Had at least one adverse consequence (%) 37.4 (32.3, 42.7) 18.4 (15.7, 21.4) <.001  Number of adverse consequences (mean) 0.61 (0.52, 0.69) 0.33 (0.27, 0.38) <.001 Instrumental activities of daily living  Need assistance doing laundry N = 1,389,761 N = 2,772,108   Went without clean laundry (%) 10.5 (6.2, 17.3) 1.9 (1.0, 3.7) <.001  Need assistance shopping for groceries/personal items N = 1,665,397 N = 3,794,956   Went without groceries or personal items (%) 10.1 (6.9, 14.7) 5.3 (3.7, 7.6) .014  Need assistance with meal preparation N = 1,513,272 N = 3,328,722   Went without a hot meal (%) 13.4 (9.9, 17.9) 8.4 (6.7, 10.4) .009  Need assistance banking or paying bills N = 1,316,544 N = 2,493,475   Went without handling bills/ banking matters (%) 10.4 (6.7, 15.9) 4.0 (2.3, 7.0) .004  Need assistance keeping track of medication N = 1,214,658 N = 2,679,613   Made a mistake in taking prescribed medicines (%) 21.8 (16.5, 28.1) 19.5 (16.4, 23.0) .451  Need assistance with one or more IADL tasks N = 2,235,069 N = 6,221,082   Had at least one adverse consequence (%) 26.7 (22.5, 31.5) 15.4 (13.7, 17.4) <.001  Number of adverse consequences (mean) 0.52 (0.36,0.68) 0.26 (0.21, 0.31) <.001 Mobility  Need assistance going outside the home N = 1,426,294 N = 3,257,959   Had to stay inside (%) 38.7 (32.7, 45.1) 24.6 (20.6, 29.1) <.001  Need assistance getting around inside the home N = 1,425,890 N = 2,918,625   Did not go to places inside one’s home (%) 32.6 (28.0, 37.6) 23.7 (20.0, 27.8) .008  Needing assistance getting out of bed N = 1,480,312 N = 3,016,622   Had to stay in bed (%) 20.6 (16.2, 25.9) 7.3 (5.4, 9.6) <.001  Need assistance with one or more mobility tasks N = 2,030,479 N = 5,237,974   Had at least one adverse consequence (%) 42.0 (37.0, 47.2) 24.5 (21.6, 27.6) <.001  Number of adverse consequences (mean) 0.84 (0.74, 0.95) 0.51 (0.43, 0.58) <.001 Notes: ADL = activities of daily living; IADL = instrumental activities of daily living. N represents estimated population totals. 95% confidence intervals in parentheses. Sampling weights and design factors were adjusted when estimating population totals, prevalence, and means. View Large Table 3 shows incidence rate ratios from mixed-effects negative binomial regression. Likelihood-ratio tests of alpha for these models were statistically significant, suggesting that the negative binomial model is more appropriate than the Poisson model. Likelihood-ratio tests of the fitted models vs null models (i.e., constant-only model) were also significant, indicating better model fit of the fitted models. Holding covariates constant, people with prior-wave elevated depressive symptoms compared to those without depression had 1.24 times the rate of adverse consequences of unmet needs for assistance with ADL (incidence rate ratio [IRR] = 1.24, 95% confidence interval [CI] = 1.09–1.41, p < .01) and IADL (IRR = 1.24, 95% CI = 1.06–1.44, p < .01), and 1.14 times the rate for assistance with mobility (IRR = 1.14, 95% CI = 1.03–1.27, p < .05). Table 3. Incidence Rate Ratios for Lagged Independent Variables Associated With the Count of Adverse Consequences of Unmet Needs From Mixed-Effects Negative Binomial Regression Domains of adverse consequences of unmet needs Lagged independent variables ADL IADL Mobility Elevated depressive symptoms 1.24 (1.09, 1.41)** 1.24 (1.06, 1.44)** 1.14 (1.03, 1.27)* Age in 5-year interval 0.97 (0.93, 1.01) 0.89 (0.84, 0.94)*** 0.98 (0.94, 1.01) Male sex 0.98 (0.85, 1.13) 1.14 (0.96, 1.36) 0.91 (0.81, 1.03) Race/ethnicity  White, Non-Hispanic Reference Reference Reference  Black, Non-Hispanic 0.90 (0.77, 1.05) 0.97 (0.80, 1.18) 1.01 (0.88, 1.15)  Hispanic 0.85 (0.66, 1.08) 1.24 (0.92, 1.69) 1.37 (1.13, 1.66)**  Other 1.31 (0.92, 1.85) 1.08 (0.69, 1.69) 1.58 (1.18, 2.12)** Education  Less than high school Reference Reference Reference  High school 1.03 (0.87, 1.23) 0.93 (0.74, 1.16) 1.04 (0.90, 1.20)  Some college, no degree 1.08 (0.89, 1.31) 1.21 (0.95, 1.53) 1.01 (0.86, 1.19)  College graduate 1.14 (0.95, 1.38) 1.31 (1.04, 1.66)* 1.05 (0.89, 1.23) Dementia status  No dementia Reference Reference Reference  Possible dementia 1.12 (0.93, 1.33) 0.92 (0.77, 1.12) 1.10 (0.96, 1.26)  Probable dementia 1.13 (0.97, 1.32) 0.71 (0.58, 0.86)*** 0.94 (0.82, 1.07) Number of chronic physical illnesses 1.06 (1.01, 1.10)** 1.06 (1.01, 1.12)* 1.07 (1.03, 1.11)*** Number of needs for assistance with daily activities 1.13 (1.11, 1.16)*** 1.01 (0.99, 1.04) 1.10 (1.08, 1.12)*** Hospitalized in past 12 months 1.05 (0.93, 1.19) 1.02 (0.89, 1.17) 1.02 (0.93, 1.13) Community social support 0.85 (0.77, 0.94)** 0.81 (0.72, 0.91)*** 0.90 (0.83, 0.97)** Long-term care insurance 1.07 (0.90, 1.27) 1.02 (0.85, 1.24) 0.92 (0.80, 1.07) Medicare-Medicaid dual enrollees 1.16 (1.00, 1.35)* 1.21 (1.01, 1.47)* 1.05 (0.93, 1.19) Model specifics  Number of persons 1,731 2,634 4,348  Number of person-years 3,493 5,804 2,122  Likelihood-ratio test of alpha = 0: χ2(01) 34.0*** 291.73*** 89.88***  Likelihood-ratio test of fitted model vs null model: χ2(18) 242.43*** 106.99*** 253.12*** Domains of adverse consequences of unmet needs Lagged independent variables ADL IADL Mobility Elevated depressive symptoms 1.24 (1.09, 1.41)** 1.24 (1.06, 1.44)** 1.14 (1.03, 1.27)* Age in 5-year interval 0.97 (0.93, 1.01) 0.89 (0.84, 0.94)*** 0.98 (0.94, 1.01) Male sex 0.98 (0.85, 1.13) 1.14 (0.96, 1.36) 0.91 (0.81, 1.03) Race/ethnicity  White, Non-Hispanic Reference Reference Reference  Black, Non-Hispanic 0.90 (0.77, 1.05) 0.97 (0.80, 1.18) 1.01 (0.88, 1.15)  Hispanic 0.85 (0.66, 1.08) 1.24 (0.92, 1.69) 1.37 (1.13, 1.66)**  Other 1.31 (0.92, 1.85) 1.08 (0.69, 1.69) 1.58 (1.18, 2.12)** Education  Less than high school Reference Reference Reference  High school 1.03 (0.87, 1.23) 0.93 (0.74, 1.16) 1.04 (0.90, 1.20)  Some college, no degree 1.08 (0.89, 1.31) 1.21 (0.95, 1.53) 1.01 (0.86, 1.19)  College graduate 1.14 (0.95, 1.38) 1.31 (1.04, 1.66)* 1.05 (0.89, 1.23) Dementia status  No dementia Reference Reference Reference  Possible dementia 1.12 (0.93, 1.33) 0.92 (0.77, 1.12) 1.10 (0.96, 1.26)  Probable dementia 1.13 (0.97, 1.32) 0.71 (0.58, 0.86)*** 0.94 (0.82, 1.07) Number of chronic physical illnesses 1.06 (1.01, 1.10)** 1.06 (1.01, 1.12)* 1.07 (1.03, 1.11)*** Number of needs for assistance with daily activities 1.13 (1.11, 1.16)*** 1.01 (0.99, 1.04) 1.10 (1.08, 1.12)*** Hospitalized in past 12 months 1.05 (0.93, 1.19) 1.02 (0.89, 1.17) 1.02 (0.93, 1.13) Community social support 0.85 (0.77, 0.94)** 0.81 (0.72, 0.91)*** 0.90 (0.83, 0.97)** Long-term care insurance 1.07 (0.90, 1.27) 1.02 (0.85, 1.24) 0.92 (0.80, 1.07) Medicare-Medicaid dual enrollees 1.16 (1.00, 1.35)* 1.21 (1.01, 1.47)* 1.05 (0.93, 1.19) Model specifics  Number of persons 1,731 2,634 4,348  Number of person-years 3,493 5,804 2,122  Likelihood-ratio test of alpha = 0: χ2(01) 34.0*** 291.73*** 89.88***  Likelihood-ratio test of fitted model vs null model: χ2(18) 242.43*** 106.99*** 253.12*** Notes: ADL = activities of daily living; IADL = instrumental activities of daily living. Independent variables in period t−1 were used to predict dependent variables in period t. Analytical sample consisted of persons who reported needing assistance in a specific domain (i.e., ADL, IADL, and mobility) for any 2 consecutive years between 2011 and 2015. Survey wave was included as a covariate (results not shown). 95% confidence intervals in parentheses. *p < .05, **p < .01, ***p < .001. View Large Table 3. Incidence Rate Ratios for Lagged Independent Variables Associated With the Count of Adverse Consequences of Unmet Needs From Mixed-Effects Negative Binomial Regression Domains of adverse consequences of unmet needs Lagged independent variables ADL IADL Mobility Elevated depressive symptoms 1.24 (1.09, 1.41)** 1.24 (1.06, 1.44)** 1.14 (1.03, 1.27)* Age in 5-year interval 0.97 (0.93, 1.01) 0.89 (0.84, 0.94)*** 0.98 (0.94, 1.01) Male sex 0.98 (0.85, 1.13) 1.14 (0.96, 1.36) 0.91 (0.81, 1.03) Race/ethnicity  White, Non-Hispanic Reference Reference Reference  Black, Non-Hispanic 0.90 (0.77, 1.05) 0.97 (0.80, 1.18) 1.01 (0.88, 1.15)  Hispanic 0.85 (0.66, 1.08) 1.24 (0.92, 1.69) 1.37 (1.13, 1.66)**  Other 1.31 (0.92, 1.85) 1.08 (0.69, 1.69) 1.58 (1.18, 2.12)** Education  Less than high school Reference Reference Reference  High school 1.03 (0.87, 1.23) 0.93 (0.74, 1.16) 1.04 (0.90, 1.20)  Some college, no degree 1.08 (0.89, 1.31) 1.21 (0.95, 1.53) 1.01 (0.86, 1.19)  College graduate 1.14 (0.95, 1.38) 1.31 (1.04, 1.66)* 1.05 (0.89, 1.23) Dementia status  No dementia Reference Reference Reference  Possible dementia 1.12 (0.93, 1.33) 0.92 (0.77, 1.12) 1.10 (0.96, 1.26)  Probable dementia 1.13 (0.97, 1.32) 0.71 (0.58, 0.86)*** 0.94 (0.82, 1.07) Number of chronic physical illnesses 1.06 (1.01, 1.10)** 1.06 (1.01, 1.12)* 1.07 (1.03, 1.11)*** Number of needs for assistance with daily activities 1.13 (1.11, 1.16)*** 1.01 (0.99, 1.04) 1.10 (1.08, 1.12)*** Hospitalized in past 12 months 1.05 (0.93, 1.19) 1.02 (0.89, 1.17) 1.02 (0.93, 1.13) Community social support 0.85 (0.77, 0.94)** 0.81 (0.72, 0.91)*** 0.90 (0.83, 0.97)** Long-term care insurance 1.07 (0.90, 1.27) 1.02 (0.85, 1.24) 0.92 (0.80, 1.07) Medicare-Medicaid dual enrollees 1.16 (1.00, 1.35)* 1.21 (1.01, 1.47)* 1.05 (0.93, 1.19) Model specifics  Number of persons 1,731 2,634 4,348  Number of person-years 3,493 5,804 2,122  Likelihood-ratio test of alpha = 0: χ2(01) 34.0*** 291.73*** 89.88***  Likelihood-ratio test of fitted model vs null model: χ2(18) 242.43*** 106.99*** 253.12*** Domains of adverse consequences of unmet needs Lagged independent variables ADL IADL Mobility Elevated depressive symptoms 1.24 (1.09, 1.41)** 1.24 (1.06, 1.44)** 1.14 (1.03, 1.27)* Age in 5-year interval 0.97 (0.93, 1.01) 0.89 (0.84, 0.94)*** 0.98 (0.94, 1.01) Male sex 0.98 (0.85, 1.13) 1.14 (0.96, 1.36) 0.91 (0.81, 1.03) Race/ethnicity  White, Non-Hispanic Reference Reference Reference  Black, Non-Hispanic 0.90 (0.77, 1.05) 0.97 (0.80, 1.18) 1.01 (0.88, 1.15)  Hispanic 0.85 (0.66, 1.08) 1.24 (0.92, 1.69) 1.37 (1.13, 1.66)**  Other 1.31 (0.92, 1.85) 1.08 (0.69, 1.69) 1.58 (1.18, 2.12)** Education  Less than high school Reference Reference Reference  High school 1.03 (0.87, 1.23) 0.93 (0.74, 1.16) 1.04 (0.90, 1.20)  Some college, no degree 1.08 (0.89, 1.31) 1.21 (0.95, 1.53) 1.01 (0.86, 1.19)  College graduate 1.14 (0.95, 1.38) 1.31 (1.04, 1.66)* 1.05 (0.89, 1.23) Dementia status  No dementia Reference Reference Reference  Possible dementia 1.12 (0.93, 1.33) 0.92 (0.77, 1.12) 1.10 (0.96, 1.26)  Probable dementia 1.13 (0.97, 1.32) 0.71 (0.58, 0.86)*** 0.94 (0.82, 1.07) Number of chronic physical illnesses 1.06 (1.01, 1.10)** 1.06 (1.01, 1.12)* 1.07 (1.03, 1.11)*** Number of needs for assistance with daily activities 1.13 (1.11, 1.16)*** 1.01 (0.99, 1.04) 1.10 (1.08, 1.12)*** Hospitalized in past 12 months 1.05 (0.93, 1.19) 1.02 (0.89, 1.17) 1.02 (0.93, 1.13) Community social support 0.85 (0.77, 0.94)** 0.81 (0.72, 0.91)*** 0.90 (0.83, 0.97)** Long-term care insurance 1.07 (0.90, 1.27) 1.02 (0.85, 1.24) 0.92 (0.80, 1.07) Medicare-Medicaid dual enrollees 1.16 (1.00, 1.35)* 1.21 (1.01, 1.47)* 1.05 (0.93, 1.19) Model specifics  Number of persons 1,731 2,634 4,348  Number of person-years 3,493 5,804 2,122  Likelihood-ratio test of alpha = 0: χ2(01) 34.0*** 291.73*** 89.88***  Likelihood-ratio test of fitted model vs null model: χ2(18) 242.43*** 106.99*** 253.12*** Notes: ADL = activities of daily living; IADL = instrumental activities of daily living. Independent variables in period t−1 were used to predict dependent variables in period t. Analytical sample consisted of persons who reported needing assistance in a specific domain (i.e., ADL, IADL, and mobility) for any 2 consecutive years between 2011 and 2015. Survey wave was included as a covariate (results not shown). 95% confidence intervals in parentheses. *p < .05, **p < .01, ***p < .001. View Large Number of adverse consequences of unmet needs differed by demographic characteristics. The incidence rate of adverse consequences of unmet needs for assistance with IADL slightly declined with age. Non-black racial minorities (e.g., Asian and Pacific Islanders, American Indians, mixed race) and Hispanics had a higher incidence rate of adverse consequences associated with mobility as compared to non-Hispanic whites. People with college degrees as compared to those without a high school diploma had a higher incidence rate of adverse consequences for assistance with IADL. Several time-varying covariates were significantly associated with adverse consequences of unmet needs. Compared to those without dementia, participants with probable dementia at the prior wave had lower incidence rate of adverse consequences of unmet needs for assistance with IADL. Number of chronic physical illnesses and needs for assistance at the prior wave were associated with greater incidence rates of adverse consequences of unmet needs. Prior-wave community social support was consistently associated with lower incidence rate of adverse consequences of unmet needs. Prior-wave Medicare–Medicaid dual enrollees had greater incidence rate of adverse consequences associated with ADL and IADL needs. Table 4 shows the predicted counts of adverse consequences of unmet needs by depression status. Older adults with elevated depressive symptoms at a prior wave were expected to have an average of a 0.41 count of adverse consequences of unmet needs for assistance with ADL, a 0.33 count for that with IADL, and 0.51 for that with mobility. Given the same value of covariates, the predicted count of adverse consequences of unmet needs was 0.33 for ADL needs, 0.20 for IADL needs, and 0.45 for mobility needs among older adults without elevated depressive symptoms at a prior wave. Table 4. Predicted Counts of Adverse Consequences of Unmet Needs by Depression Status Predicted counts of adverse consequences of unmet needs With elevated depressive symptoms Without elevated depressive symptoms Activities of daily living 0.41 (0.37, 0.45) 0.33 (0.30, 0.36) Instrumental activities of daily living 0.24 (0.21, 0.28) 0.20 (0.18, 0.21) Mobility 0.51 (0.47, 0.56) 0.45 (0.42, .0.48) Predicted counts of adverse consequences of unmet needs With elevated depressive symptoms Without elevated depressive symptoms Activities of daily living 0.41 (0.37, 0.45) 0.33 (0.30, 0.36) Instrumental activities of daily living 0.24 (0.21, 0.28) 0.20 (0.18, 0.21) Mobility 0.51 (0.47, 0.56) 0.45 (0.42, .0.48) Note: Predicted counts of adverse consequences were obtained using margins command in Stata, after the estimation of mixed-effects negative binomial regression using prior-wave depressive symptoms and covariates to predict current-wave adverse consequences in each domain. 95% confidence intervals in parentheses. p < .05 for comparisons by depression status. View Large Table 4. Predicted Counts of Adverse Consequences of Unmet Needs by Depression Status Predicted counts of adverse consequences of unmet needs With elevated depressive symptoms Without elevated depressive symptoms Activities of daily living 0.41 (0.37, 0.45) 0.33 (0.30, 0.36) Instrumental activities of daily living 0.24 (0.21, 0.28) 0.20 (0.18, 0.21) Mobility 0.51 (0.47, 0.56) 0.45 (0.42, .0.48) Predicted counts of adverse consequences of unmet needs With elevated depressive symptoms Without elevated depressive symptoms Activities of daily living 0.41 (0.37, 0.45) 0.33 (0.30, 0.36) Instrumental activities of daily living 0.24 (0.21, 0.28) 0.20 (0.18, 0.21) Mobility 0.51 (0.47, 0.56) 0.45 (0.42, .0.48) Note: Predicted counts of adverse consequences were obtained using margins command in Stata, after the estimation of mixed-effects negative binomial regression using prior-wave depressive symptoms and covariates to predict current-wave adverse consequences in each domain. 95% confidence intervals in parentheses. p < .05 for comparisons by depression status. View Large Discussion One in five older adults with needs for assistance with daily activities had elevated depressive symptoms. The prevalence rate of adverse consequences of unmet needs in older adults with elevated depressive symptoms was twice as high as that in older adults without depression. After adjusting for potential confounders, older adults with elevated depressive symptoms at the prior wave had 1.24 times the rate of ADL- and IADL-related adverse consequences of unmet needs, and 1.14 times the rate of morbidly related adverse consequences of unmet needs. This study is the first to examine the longitudinal association of depressive symptoms and the number of adverse consequences of unmet needs for assistance with daily activities among Medicare beneficiaries. We included multiple domains of needs and conducted a population-based study. Previous studies have suggested a temporary association of poor mental health functioning (e.g., depressive symptoms, psychological distress) and unmet needs (Allen & Mor, 1997; Choi & McDougall, 2009; Quail, Wolfson, & Lippman, 2011). This study extends previous work by showing the vulnerability of older adults with depression in terms of a longer-term risk of adverse events due to inadequate assistance for performing daily activities. The link between depression and adverse consequences of unmet needs provides an alternative explanation for the high rates of hospitalization and nursing home admissions among older adults with depression (Xiang & An, 2015). This link could also explain why older adults with depressive symptoms report lower quality of life given that the adverse consequences examined are closely related to quality of life (Chachamovich, Fleck, Laidlaw, & Power, 2008). The mechanisms underlying the pathway from depression to adverse consequences of unmet needs are beyond the scope of this study. As previously mentioned, depression could increase the risk of adverse consequences due to its association with severity of illness and impairment and LTSS access. Depressive symptoms such as social withdrawal, avoidance, and passivity may discourage help seeking behaviors and inhibit the expression of needs (Barney, Griffiths, Christensen, & Jorm, 2009). Depressive symptoms could also reduce the motivation to care for one’s needs and cause self-neglect (Egede & Osborn, 2010). Future studies should focus on identifying amenable mechanisms such as LTSS access. Non-black minorities as compared to non-Hispanic whites reported a higher incidence rate of mobility-related adverse consequences. Minority older adults are more likely to live in substandard, inaccessible housing, and live alone in socially and economically disadvantaged areas with limited resources to improve their home environment (Clarke & Gallagher, 2013). Unexpectedly, college degree was associated with a higher incidence rate of IADL-related adverse consequences. An examination of the unadjusted prevalence rate of each IADL-related adverse consequence showed no significant differences by education level, with the exception of medication-related adverse consequence. More than one in five older adults with a college degree reported making a mistake in taking medications in past month compared to one in 10 older adults without a high school diploma. This result could reflect a reporting bias associated with education level such that people with higher education are more likely to become aware and report a mistake in taking prescribed medications. Consistent with Allen et al.’s framework (2014), number of chronic physical illnesses and needs were associated with higher rates of adverse consequences of unmet needs whereas community social support was associated with lower rates of adverse consequences. Unexpectedly, probable dementia was associated with a lower rate of IADL-related adverse consequences. An examination of the unadjusted prevalence rate of each IADL-related adverse consequence showed that the biggest difference was medication-related adverse consequence. Among older adults needing assistance taking medications, more than one in five of those with no or possible dementia reported making a mistake in taking medications in the past month. The rate was halved among older adults with probable dementia. Caregivers of people with dementia tend to provide more extensive assistance than caregivers of people with other conditions, possibly due to the heightened dependency of people with dementia (Alzheimer’s Association, 2014). As a result, people with dementia experience a lower rate of adverse consequences. This is consistent with the Allen et al.’s framework (2014), which proposes the adequacy of family support moderates the relationship between severity of illness and adverse consequences of unmet needs. Medicare–Medicaid dual eligibles have higher rates of ADL- and IADL-related adverse consequences. This finding contradicts our conceptualization that Medicaid coverage would reduce this risk by providing better LTSS coverage. Although dual eligibles have better insurance coverage for formal LTSS than their counterparts with Medicare only, this coverage may not translate into better quality of care. Dual eligibles experience elevated social and economic disadvantages, burden of disease and disability, and risk of poor quality LTSS (Rahman, Grabowski, Gozalo, Thomas, & Mor, 2014). A recent descriptive study showed higher rates of adverse consequences of unmet needs for several daily activities among Medicare–Medicaid dual eligibles as compared to those with Medicare only (Allen et al., 2014). Dual eligibility status may be better conceptualized as a constellation of social, psychological, and physical vulnerabilities than an indicator of access to LTSS. The higher risk of adverse consequences of unmet needs among dual eligibles also implies that better insurance coverage for LTSS is not enough. A focus on improving the quality of LTSS is needed. Implications for Policy and Practice The temporary and longitudinal association of depressive symptoms and adverse consequences of unmet needs call for coordination and integration of mental health services and LTSS, particularly home- and community-based services. Medicaid is the single largest payer for both mental health services (CMS, 2015) and LTSS (Reaves & Musumeci, 2015). More states are expanding home- and community-based services and delivering mental health services and LTSS through capitated Medicaid managed care programs (Saucier, Kasten, Burwell, & Gold, 2012), which has the potential to improve access and quality of services. Several states have also formed state mental health and aging coalitions to improve access to mental health services for older adults. The establishment of the Aging and Disability Resource Center Program in 2003—a single point of entry into LTSS for older adults and persons with disability—creates additional opportunities to integrate mental health services and LTSS. Despite these opportunities, challenges remain meeting the mental health and LTSS needs of the aging population. Ageism and stigma associated with mental illness, a shortage of health and mental health providers who specialize in geriatrics, concerns over the quality of home- and community-based services, and barriers to implementing evidence-based programs in the real world settings are among the frequently voiced challenges (Allen et al., 2014; Bartels, 2003; Leichsenring, 2004; Sirey et al., 2001). Future research, practice, advocacy, and policy efforts should address these challenges to enhance community living. Preventing and treating depression in late life may have added benefit of reducing the needs for LTSS and the incidence of adverse consequences for unmet needs, which, in turn, can improve quality of life among older adults. Future studies should explore whether alleviation of depressive symptoms are associated with a reduction in the needs for LTSS and associated adverse consequences. Depression prevention and treatment intervention studies should also consider including the needs for LTSS and associated adverse consequences as secondary intervention outcomes. Limitations This study has several limitations. Bradshaw (1972) classifies the operationalization of needs into four categories: normative need (distinguished by experts), felt need (as perceived by an individual), expressed need (the amount of help received or demanded), and comparative need (assessed in reference to the needs of individuals with similar characteristics). The measures used in this study assessed expressed need (whether assistance was received) and felt need (perceived difficulty in performing daily activity alone). Discrepancies between different definitions of needs have been documented (Verbrugge & Sevak, 2002). In addition, we used a dichotomous indicator of needs and did not assess needs as a continuum (LaPlante et al., 2004). Assessment of depressive symptoms was limited to PHQ-2, which is designed as a screener to be followed by the PHQ-9 to probe depression severity. Study findings were based on an observational study and causality cannot be inferred. The lagged association between depressive symptoms at time t−1 and adverse consequences of unmet needs at time t is likely to be influenced by the temporary association between depression and adverse consequences at time t−1 continuing to time t. We conducted sensitivity analysis using Cox proportional hazards model to examine the relationship between depression and new occurrence of adverse consequences among participants who were initially free of adverse consequences. These results conformed to the findings reported here. Study sample was restricted to people needing assistance for two consecutive years, representing a population with high needs. Generalizations to older adults with a low level of needs may be problematic. Due to low counts of adverse consequences on some items, we grouped adverse consequences into three needs domains in multivariable analysis and could not examine within-domain variation. Conclusions Depressive symptoms are positively associated with the number of adverse consequences of unmet needs for assistance with daily activities among older adults. Coordinated and integrated mental health services and LTSS programs are needed to improve access and quality of care for older adults with both mental health and long-term care needs. Funding This work was supported by a training grant from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR), located in the Administration for Community Living (ACL) in the U.S. Department of Health and Human Services, Grant Number 90AR5019 (PI: Allen Heinemann, PhD). Conflict of Interest The authors declare that there is no conflict of interest. References Allen S. M. , & Mor V . ( 1997 ). The prevalence and consequences of unmet need. Contrasts between older and younger adults with disability . Medical Care , 35 ( 11 ), 1132 – 1148 . doi:10.1097/00005650-199711000-00005 Google Scholar CrossRef Search ADS PubMed Allen S. M. Piette E. R. , & Mor V . ( 2014 ). 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The GerontologistOxford University Press

Published: Feb 15, 2017

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