Abstract
The CAPABLE program reduces disability in low-income older adults. In this study, we used CAPABLE baseline and five-month data to examine whether its effects in reducing activities of daily living (ADLs) and instrumental ADLs (IADLs) difficulties differed by participants’ financial strain status. At baseline, participants with financial strain were more likely to report higher scores on depression (p<0.001), have low energy (p<0.001), and usually feel tired (p=0.004) compared to participants without financial strain, but did not differ in ADL/IADL scores. Participants with financial strain benefited from the program in reducing ADL (relative risk [RR]: 0.61, 95% CI: 0.43, 0.86) and IADL disabilities (RR: 0.69, 95% CI: 0.54, 0.87), compared to those with financial strain receiving attention control. Individuals with financial strain benefited more from a home-based intervention on measures of disability than those without financial strain. Interventions that improve disability may be beneficial for financially strained older adults.
Keywords: health disparity, aging, intervention, physical function
Introduction
Financial strain, or having insufficient income to meet basic needs, is experienced by one third of the US population and is growing among older adults (McKenna, Law, & Pearce, 2017; Szanton, Thorpe, & Whitfield, 2010; Wilmarth, 2017). As a constant stressor, financial strain predicts poor health outcomes, including poor self-rated health status (Kahn & Pearlin, 2006), walking disability (Samuel et al., 2019), chronic conditions (Kahn & Pearlin, 2006), early disability onset (Matthews, Smith, Hancock, Jagger, & Spiers, 2005), increased psychological distress (Matthews et al., 2005), and mortality (Szanton et al., 2008), even accounting for objective socioeconomic indicators, such as income and educational attainment. Supported by the fundamental cause theory, financial strain may influence these health outcomes through key flexible resources (e.g., knowledge, money, power) that individuals can deploy to avoid risks and adopt protective strategies (Phelan & Link, 2013).
It is unclear whether individuals with financial strain benefit from non-pharmacological interventions or programs more or less or the same as people living without financial strain. For example, financial strain has been associated with treatment failure among dementia caregivers (Rose & Gitlin, 2017). While researchers may examine whether clinical trials have differential effects by factors such as race, gender, or depression status, few clinical trials designed to enhance daily functioning have examined whether intervention effects differ by financial strain status (Szanton, Thorpe, & Gitlin, 2014). To our knowledge, there have been no studies examining the role of financial strain on the efficacy of disability interventions.
Community Aging in Place–Advancing Better Living for Elders (CAPABLE) is an innovative program that reduces disabilities among low-income older adults through an interdisciplinary collaboration of occupational therapists (OT), and registered nurses (RN) and implementation of home modification and home improvement by handyworkers among other strategies designed to improved daily function (Szanton et al., 2019). However, it remains unknown if all participants benefited similarly on disability measures depending on their financial strain status. Although the whole sample was low-income, participants varied in financial strain (Gleason, Gitlin, & Szanton, 2019). Therefore, this study aims to examine whether the effects of CAPABLE program in reducing disabilities differ by participants’ baseline financial strain status.
Methods
Data source and participants
Data for this study are from a single-blind two-arm randomized control trial conducted in Baltimore, Maryland between March 2012, and April 2016. CAPABLE is a home-based intervention which includes up to 10 visits (60–90 minutes each) from an OT, a RN, and a handyworker over four months (Szanton, Wolff, et al., 2014). Following informed consent, 300 participants were randomized to receive either CAPABLE (n=152) or attention control (n=148) in which participants also received 10 visits over four months and identified sedentary activities they wanted to do. All participants were interviewed at home at baseline and five months by a trained research assistant blinded to group assignment. Participants were cognitively intact, 65 years or older reporting difficulty in at least one activity of daily living (ADL) or two instrumental ADL (IADL). Participants had incomes less than 200% of the federal poverty level ($22 980 annually for a 1-person household in the 48 contiguous US in 2013). The study design and intervention have been described in detail elsewhere (Szanton, Wolff, et al., 2014) and was approved by the Johns Hopkins University Institutional Review Board.
Measures
Disabilities
Disabilities in ADLs were assessed by self-reported difficulty or needing help performing any of eight ADLs (e.g., bathing, using the toilet, walking across a small room) (Katz, Ford, Moskowitz, Jackson, & Jaffe, 1963). For each activity, participants reported whether she/he did not have difficulty and did not need help (0), did not need help but had difficulty (1), or needed help regardless of difficulty (2) in the past month. Function on each task was scored from 0 to 2. Total scores ranged from 0 to 16, with higher scores indicating more disability; a 1-point change was considered clinically meaningful (Gill et al., 2002). This assessment has high test-retest reliability and sensitivity and predicts future mobility (Wallace & Shelkey, 2008).
Disabilities performing IADLs were measured by self-reported difficulty or need for help on eight items (e.g., doing laundry, preparing meals, using the telephone) (Lawton & Brody, 1969). Response options and scoring scheme were similar for ADLs.
Financial Strain
Financial strain was ascertained by asking participants “In general, how do your finances usually work out at the end of the month? Do you find that you usually end up with some money left over, just enough to make ends meet, or not enough money to make ends meet?” We used this both as a three-category variable (“some money left over,” “just enough,” and “not enough”) and a binary variable (“some money left over” vs. “just enough and not enough” indicating having financial strain) based on previous literature (Palta et al., 2015; Szanton et al., 2010).
Demographics and Health-related Covariates
Age, sex, race/ethnicity, education level, and living arrangement were obtained at baseline. Depressive symptoms were evaluated by the Patient Health Questionnaire-9 (PHQ-9) (Lamers et al., 2008). Pain was measured by the Brief Pain Inventory (Radbruch et al., 1999), with a cutoff of five or more indicating intense pain and distress pain. Total number of medical conditions was calculated based on a list of conditions: high blood pressure, arthritis, cholesterol, diabetes, cancer, heart disease, depression, and other conditions. Participants were also asked whether they had low energy, were usually tired or usually weak in the last month. They were asked whether they had unintentional weight loss in the past year.
Data Analysis
Three hundred participants were enrolled and assessed at baseline and 37 (12%) dropped out by five months. We used intention-to-treat analysis. Control and intervention participants’ characteristics were balanced at baseline except that intervention participants had higher pain distress in the previous week, and more of them reported tiredness, and unintentional weight loss (Szanton et al., 2019). Baseline characteristics between those with and without financial strain were compared using t-tests for continuous variables, and Chi-square or Fisher’s exact tests for categorical variables.
Many participants scored a zero reflecting no disability on their five-month follow up ADL and IADL assessment. Because this resulted in overdispersion, we used the negative binomial regression model to examine intervention effects. We reported both crude and adjusted intervention effects controlling for sex, race/ethnicity, baseline ADL/IADL status, and prognostic factors such as pain distress, tiredness, and unintentional weight loss the year prior to baseline (Szanton et al., 2019). The intervention effects were estimated as relative risk (RR) defined as the ratio of means of ADL/IADL disability score between the intervention group and the control group.
We first tested an interaction term between financial strain as a binary variable (having strain or not) and treatment group variable (CABABLE vs. attention control) using models described above. We then examined intervention effects stratified by financial strain status as a binary and as a three-category variable, respectively. This allowed us to observe the magnitude and direction of intervention effects by financial strain status as an “exposure” because the study was not powered to detect significance of an interaction term between financial strain and treatment group variables. Data analyses were performed using Stata Version 15.0 (StataCorp, 2017). A p-value of less than 0.05 was considered statistically significant.
Results
Most participants were female (87%) and African-American (86%), with a mean age of 76 years (SD=7.6). About 16% had more than 12 years’ education and half lived alone. Participants had a mild depression (mean=6.9, SD=5.1); more than half were bothered by pain, had unusually low energy in the past month, and experienced unintentional weight loss in the past year. By study design, participants had difficulty in daily activities, with a mean ADL total score of 4.0 and a mean IADL total score of 5.9. About 82% (N=245) of participants reported financial strain at baseline. They were more likely to be depressed (p<0.001), have low energy (p<0.001) and feel tired (p=0.004) at baseline (Table1). About 76% (N=238) of participants had financial strain at 5 months; overall, participants improved on their ADL (mean=2.5) and IADL total score (mean=4.1) at 5 months (not shown in Table 1).
Table 1.
Selected baseline characteristics of CAPABLE program participants, stratified by financial strain status
| Variables | All (N = 300) | With financial strain (n = 245) | Without financial strain (n = 55) | P values |
|---|---|---|---|---|
| Age, mean (SD), y (65–95) | 75.7 (7.6) | 75.6 (7.7) | 76.3 (7.1) | 0.517 |
| Female sex, No. (%) | 262 (87.3) | 215 (87.8) | 47 (85.5) | 0.643 |
| Race/ethnicity, No. (%) | ||||
| White | 40 (13.3) | 32 (13.1) | 8 (14.6) | 0.858 |
| Black | 259 (86.3) | 212 (86.5) | 47 (85.5) | |
| Asian | 1 (0.4) | 1 (0.4) | 0 | |
| Education, No. (%) | ||||
| < 12 y | 98 (32.8) | 80 (32.8) | 18 (32.7) | 0.652 |
| = 12 y | 153 (51.2) | 127 (52.1) | 26 (47.3) | |
| ≥ 12 y | 48 (16.0) | 37 (15.1) | 11 (20.0) | |
| Living alone, No. (%) | 150 (51.0) | 120 (50.0) | 30 (54.5) | 0.562 |
| PHQ-9 score, mean (SD) (0–25) | 6.9 (5.1) | 7.3 (5.2) | 4.5 (3.8) | <0.001 |
| Pain in the last week | ||||
| Intensity ≥ 5 | 217 (72.6) | 179 (73.4) | 38 (69.1) | 0.521 |
| Distress ≥ 5 | 207 (69.2) | 172 (70.5) | 35 (63.6) | 0.320 |
| No. of medical conditions, mean (SD) (0–8) | 3.3 (1.4) | 3.3 (0.1) | 3.0 (0.2) | 0.140 |
| Energy in past month, No. (%) | ||||
| Unusually low energy | 154 (56.4) | 136 (61.8) | 18 (34.0) | <0.001 |
| Usually tired | 170 (62.3) | 146 (66.4) | 24 (45.3) | 0.004 |
| Usually weak | 131 (48.0) | 110 (50.0) | 21 (39.6) | 0.175 |
| Unintentional weight loss in the past year, No. (%) | 175 (64.1) | 142 (64.6) | 33 (62.3) | 0.756 |
| Baseline disabilities, mean (SD) (0–16) | ||||
| ADL total score | 4.0 (3.0) | 4.0 (3.1) | 4.0 (2.8) | 0.975 |
| IADL total score | 5.9 (4.0) | 6.0 (3.8) | 5.3 (4.1) | 0.251 |
| Treatment groups, No. (%) | ||||
| Intervention | 152 (50.7) | 118 (48.2) | 34 (61.8) | 0.067 |
| Control | 148 (49.3) | 127 (51.8) | 21 (38.2) | |
Notes: SD-standard deviation; ADL-activities of daily living; IADL-instrumental activity of daily living.
The interaction term between financial strain and treatement groups was insignificant (now shown in Table 2), indicating no significant differences for ADL and IADL outcomes by financial strain. However, when stratified on a binary financial strain variable, the intervention significantly reduced ADL total score (Table 2) for participants reporting financial strain at baseline. They had a 30% reduction in ADL total scores (RR: 0.69, 95% CI: 0.49, 0.98) before covariate adjustment and a 39% reduction after adjustment (RR: 0.61, 95% CI: 0.43, 0.86). Intervention effects on reducing IADL scores were significant after adjustment within the financial strain subgroup. When stratified on a three-category financial strain variable, the intervention groups showed similar findings and overall there was a pattern that people reporting more financial strainhad lower relative risk estimates of ADLs and IADLS after the intervention (Table 3) compared to those without baseline financial strain. All the adjusted intervention effects were in the same direction, although some were not significant.
Table 2.
Comparison of CAPABLE program intervention effects from baseline to 5 months stratified by financial strain status as a binary variable
| With financial strain (n = 215) | Without financial strain (n = 48) | |||||
|---|---|---|---|---|---|---|
| Outcomes | Mean change (SE) | Crude RR (95% CI) | Adjusted RR (95% CI)§ | Mean change (SE) | Crude RR (95% CI) | Adjusted RR (95% CI)§ |
| ADL total score | ||||||
| Control group (reference) | −0.6 (0.3) | 1.00 | 1.00 | −2.0 (0.5) | 1.00 | 1.00 |
| Intervention group | −1.1 (0.2) | 0.69 (0.49, 0.98) * | 0.61 (0.43, 0.86) ** | −1.0 (0.4) | 0.82 (0.38, 1.74) | 0.93 (0.41, 2.09) |
| IADL total score | ||||||
| Control group | −1.0 (0.3) | 1.00 | 1.00 | −1.7 (0.6) | 1.00 | 1.00 |
| Intervention group | −2.0 (0.3) | 0.75 (0.56, 1.00) | 0.69 (0.54, 0.87) ** | −1.4 (0.4) | 1.01 (0.53, 1.92) | 0.89 (0.57, 1.40) |
Notes:
p < 0.05;
p <0.01;
p <0.001;
model adjusted for sex, race, unintentional weight loss, tiredness, and pain distress;
RR – relative risk; CI - confidence interval; SE - standard error; ADL - activities of daily living; IADL - instrumental activity of daily living.
Table 3.
Comparison of CAPABLE program intervention effects from baseline to 5 months stratified by financial strain status as a three-category variable
| Some left over (n = 48) | Just enough (n = 123) | Not enough (n = 92) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Outcomes | Mean change (SE) | Crude RR (95% CI) | Adjusted RR (95% CI)§ | Mean change (SE) | Crude RR (95% CI) | Adjusted RR (95% CI)§ | Mean change (SE) | Crude IRR (95% CI) | Adjusted RR (95% CI)§ |
| ADL total score | |||||||||
| Control group (reference) | −2.0 (0.5) | 1.00 | 1.00 | −0.5 (0.4) | 1.00 | 1.00 | −0.7 (0.3) | 1.00 | 1.00 |
| Intervention group | −1.0 (0.4) | 0.82 (0.38,1.74) | 0.93 (0.41,2.09) | −1.2 (0.2) | 0.61 (0.39,0.95) * | 0.58 (0.36,0.91) * | −1.1 (0.3) | 0.79 (0.47,1.34) | 0.61 (0.37,0.99) * |
| IADL total score | |||||||||
| Control group (reference) | −1.7 (0.6) | 1.00 | 1.00 | −1.2 (0.4) | 1.00 | 1.00 | −0.7 (0.4) | 1.00 | 1.00 |
| Intervention group | −1.4 (0.4) | 1.01 (0.53,1.92) | 0.89 (0.57,1.40) | −1.7 (0.3) | 0.84 (0.55,1.28) | 0.78 (0.55,1.11) | −2.4 (0.4) | 0.65 (0.44,0.97) * | 0.53 (0.39,0.73) *** |
Notes:
p < 0.05;
p <0.01;
p <0.001;
model adjusted for sex, race, unintentional weight loss, tiredness, and pain distress;
RR – relative risk; CI - confidence interval; SE - standard error; ADL - activities of daily living; IADL - instrumental activity of daily living.
Discussion
Our study found that CAPABLE participants with financial strain at baseline tended to have lower relative risks of ADL and IADL difficulties if they received CAPABLE compared to the control group. This study contributes to the literature by showing that individuals having financial strain benefit more from a home-based intervention addressing disability among low-income older adults than those with financial strain receiving attention control.
The differential intervention effects could be explained in several ways. First, it could be due to different levels of readiness to engage in the program. Gleason et al. found that participants reporting high financial strain tended to have high readiness at the start of the CAPABLE program intervention (Gleason et al., 2019). Rose and Gitlin however found the opposite – financial strained individuals did not do well in a caregiver intervention (Rose & Gitlin, 2017). Another study reported that family caregivers who reported their caregiving financially strained them were more likely to reach out for assistance than those caregivers who did not (Henning-Smith, Lahr, & Casey, 2019). Second, interventions with home repairs used in CAPABLE may be of particular value for people with financial strain. Third, the increased self-efficacy that CAPABLE participants obtain through the program may be especially important for people with financial strain.
This study has limitations. First, we used a single question to measure financial stain. However, previous studies have measured financial strain with a single question and consistently predicted multiple poor health outcomes (Dijkstra-Kersten, Biesheuvel-Leliefeld, van der Wouden, Penninx, & van Marwijk, 2015; Palta et al., 2015; Szanton et al., 2008). Second, this study was not designed to detect significant intervention effects among subgroups suggesting that we were underpowered for the interaction analysis. Third, the sample was mainly African-American and female and without severe persistent disability so study results may not generalize to other populations.
In conclusion, our study found that low-income disabled older participants with financial strain receiving CAPABLE seemed to improve more in ADLs and IADLs compared to those without financial strain. Interventions that improve disability may be beneficial for financial strained older adults.
Funding Acknowledgments:
This study was supported by grant R01AG040100 from the National Institutes of Health.
Footnotes
Ethical Approval: This study was approved under the following Institutional Review Board (IRB) protocol/human subjects approval number: Johns Hopkins University Institutional Review Board (NA_00031539)
Declaration of Conflicting Interests: Drs Szanton and Gitlin reported being inventors of the CAPABLE training program, for which the Johns Hopkins University is entitled to fees. This arrangement has been reviewed and approved by the Johns Hopkins University in accordance with its conflict of interest policies.
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