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. Author manuscript; available in PMC: 2026 Feb 3.
Published before final editing as: J Appl Gerontol. 2025 Nov 20:7334648251398117. doi: 10.1177/07334648251398117

Subjective Financial Strain and Objective Financial Impacts Among Informal Caregivers in the United States

Yujun Zhu 1, Francesca Falzarano 1, Susanna Mage 1, Donna Benton 1, Kathleen Wilber 1, Susan Enguidanos 1
PMCID: PMC12863012  NIHMSID: NIHMS2135121  PMID: 41264890

Abstract

Informal caregivers provide critical unpaid care while facing significant financial, emotional, and physical challenges. This study examined factors associated with subjective financial strain and objective financial impacts among informal caregivers of older adults in the United States. Using data from the “Caregiving in the U.S. 2020” with 1,333 informal caregivers who reported caring for an adult aged 50+. Findings indicate that providing assistance with a greater number of instrumental activities of daily living (IADLs) and seeking information about financial help are both significantly associated with increased odds of experiencing subjective financial strain and objective financial impacts. Findings underscore the need for targeted financial support for informal caregivers heavily involved in assisting with IADLs. Financial assistance programs should consider the additional costs associated with these tasks. Policies should ensure that informal caregivers receive adequate and timely support once they request assistance to mitigate both objective and subjective aspects of financial burden.

Keywords: informal caregiving, IADLs, subjective financial strain, objective financial impacts

Introduction

Informal caregivers, defined as “an adult family member or other individual who has a significant relationship with, and who provides a broad range of assistance to an individual with a chronic or other health condition, disability or functional limitation,” provide more than $600 billion dollars of unpaid care annually (Act, 2022, p. 5; Reinhard et al., 2023). In 2023, caregivers of people with Alzheimer’s or other dementias provided an estimated 18.4 billion hours of informal, unpaid assistance, valued at $346.6 billion (Alzheimer’s Disease Facts and Figures, 2024). These informal caregivers provide critically important care ranging from help with activities of daily living (ADLs, e.g., toileting, bathing, and feeding), instrumental activities of daily living (IADLs, e.g., bill paying, transportation, and household chores), medical care and co-ordination, and emotional and psychological support. While ADL needs mainly depend on physical and health-related tasks, IADL needs involve more complex tasks and are closely related to psychosocial (social participation and support), cognitive (explicit and working memory), and economic resources (Beltz et al., 2022; Perrig-Chiello et al., 2006).

Recent studies have shown that informal caregivers’ personal finances are impacted by caregiving responsibilities. For example, about 11.4% of informal caregivers in California are below the federal poverty level and are more likely to report “extreme” financial stress than those in higher income brackets (Tan et al., 2021). Another study found that informal caregivers spent an average of $7,242 annually in caregiving-related costs and include household expenses, medical bills, personal expenses for informal caregivers (e.g., respite and travel) and their care recipient and patients (Skufca & Chuck, 2021). Those supporting individuals with dementia, mental health issues, or individuals with high-intensity care needs face even higher out-of-pocket costs (Skufca & Chuck, 2021). In addition, informal care provision can cause significant work-related disruptions, including reduced productivity (also referred to as presenteeism) reduced hours, job loss, or leaving the workforce entirely—all of which can worsen financial strain. Using cross-sectional data from the National Health and Aging Trends Study, Fakeye et al. (2023) found that roughly one in four employed informal caregivers experienced caregiving-related work productivity loss due to absenteeism or presenteeism. Specifically, findings showed that caregiving demands were associated with a decline in job productivity by about one-third, amounting to an estimated annual loss of $5,600 per caregiver (Fakeye et al., 2023).

Financial costs of caregiving are significantly associated with higher levels of caregiver burden (Johnson et al., 2023; Lai, 2012). This is concerning given existing research demonstrating the potential adverse implications of caregiver burden on both caregivers and care recipients’ physical and psychological well-being (Inguva et al., 2022). In a study of advanced cancer patients and their spousal caregivers, financial distress was highly prevalent (63% among patients and 65% among caregivers) and associated with psychological issues and poor physical quality of life (Kroll et al., 2022). A previous study also found individuals reporting higher levels of financial strain tended to experience more pronounced feelings of being overwhelmed by their caregiving responsibilities (Liu et al., 2019). Moreover, elevated financial burden experienced by informal caregivers has been associated with higher care non-adherence in patients, increased lifestyle-altering behaviors, and declining quality of life for both patients and their caregivers (Sadigh et al., 2022).

While financial strain is a subjective (psychological re-action to and appraisal of financial strain) experience of economic hardship, objective financial hardship also is commonly experienced among caregivers when they encounter financial difficulties related to caregiving. In a nationally representative survey, about 45% of informal caregivers reported experiencing at least one objective financial impact related to caregiving and a third of informal caregivers experienced two or more objective financial impacts (AARP & NAC, 2020). While objective economic scales measure the impact of caregiving on concrete financial variables, such as savings, bills, and income, subjective financial strain, which reflects the individual, psychological appraisal of one’s financial situation, also can negatively affect physical health and psychosocial outcomes (Glei et al., 2018; Kahn & Pearlin, 2006; Marshall et al., 2021). For example, individuals experiencing financial strain have higher rates of depression and anxiety, sleep deprivation, lower rates of physical activity, and higher rates of serious chronic conditions (Advani et al., 2014; Glei et al., 2018; Hall et al., 2008; Marshall et al., 2021).

Differences in experiences of caregiving have been well documented among racial/ethnic caregivers. Previous studies have found that minority informal caregivers tend to spend more hours caregiving than their White counterparts (Cohen et al., 2019; Fabius et al., 2020), which in turn may impact both health status and financial strain (Whitney et al., 2023). Additionally, Hispanic and Black informal caregivers tend to have lower incomes than White and Asian caregivers (Heo & Koeske, 2013; Whitney et al., 2023) and experience more financial impacts than White informal caregivers (AARP & NAC, 2025).

Research also has demonstrated that some of the ill effects of episodic financial strain can be averted if the occurrence is short-term and not followed by further episodes of hardship (Kahn & Pearlin, 2006). Thus, understanding factors associated with financial strain is an important step in mitigating this strain and burden. Although previous studies have provided valuable insights into descriptive variables related to caregiving (AARP & NAC, 2020), there is a dearth of information examining factors associated with financial aspects of caregiving while controlling for potential confounding variables. Thus, the purpose of this study was to investigate factors associated with both subjective financial strain and objective financial impacts experienced among informal caregivers of older adults, aged 50 or older in the United States.

Theoretical Framework and Hypotheses

Conceptually guided by the stress process model (Pearlin et al., 1990), which posits that care-related stress arises from both within and beyond the direct care environment, we examined caregiver demographic characteristics, care recipient conditions and health service use, caregiving intensity, and additional factors related to financial assistance seeking behaviors. We hypothesized that care intensity such as length of time care provided, weekly hours of caregiving, and assistance provided with ADLs and IADLs would be associated with subjective financial strain and objective financial impacts. We also hypothesized that subjective financial strain and objective financial impacts would be mitigated by caregivers’ socioeconomic status, such as education and income. This theoretical framework guided our selection of relevant variables in the analysis.

Methods

Data and Sample

We used publicly available, nationally representative data from the “Caregiving in the U.S. 2020” study conducted by National Alliance for Caregiving (NAC) and American Association of Retired Persons (AARP). The study was designed to ensure robust data collection and validation of caregiver status. Surveys were conducted online via Ipsos’ KnowledgePanel®, using a probability-based sample representative of the U.S. population. Participants were asked if anyone in the household “provided unpaid care to a relative or friend 18 years or older to help them take care of themselves.” Those identifying as an informal caregiver were administered the full survey that included items inquiring about caregiving activities and experiences. We limited our sample to those who self-identified as caring for an older adult 50 years and older in the past 12 months. In addition, participants with missing data for any variable of interest were excluded, resulting in a final analytic sample size of 1,333 (see Figure 1 for CONSORT flow diagram).

Figure 1.

Figure 1.

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Data selection

Measures

Dependent Variables

Subjective Financial Strain.

Caregivers were administered a single item to assess subjective perceptions of financial strain (how much of a financial strain would you say that caring for your care recipient is/was for you?), with response options ranging from 1 (no strain at all) to 5 (very much a strain). Consistent with prior literature, responses were categorized as no strain (1), some strain (2–3), and substantial strain (4–5) (Wolff et al., 2016).

Objective Financial Impacts.

Participants were administered 13 yes/no items asking if they have experienced objective financial impacts of caregiving related to six categories including savings, debt, bills, work, and home arrangement. For each category, a dichotomous variable was constructed. Savings impacts (3 items) was defined as having experienced change in at least one of the following areas: “stopped saving, used up personal short-term savings, or used up long-term savings such as retirement or education to pay for other things.” Debt impacts (4 items) was defined as having experienced change in at least one of the following: “took on more debt, borrowed money from family or friends, missed or was late paying student loan, or filed for bankruptcy.” Bill impacts (2 items) was defined as having experienced change in at least one of the following: “been unable to afford basic expenses like food or left bills unpaid or paid late.” Work impacts (2 items) was defined as having experienced change in at least one of the following: “had to start working, work more or find a second job or put off retirement or decide to never retire.” Home impacts (2 items) was defined as having experienced change in at least one of the following: “moved to a less expensive home, apartment, or other living arrangement, or was evicted or had home foreclosed.”

Independent Variables.

Variable selection was guided by Pearlin’s stress process model and prior empirical literature (Pearlin et al., 1990; Wolff et al., 2016).

Sample Characteristics.

Informal caregivers’ demographic characteristics included age, gender, race/ethnicity, education, household income per capita (derived by dividing the total reported household income by the number of individuals living in the household), living in a rural area, and employment status within the past year while providing care.

Care recipients’ demographic characteristics included age, gender, number of health conditions (e.g., short-term physical condition, long-term physical condition, emotional or mental health issues, memory problems, behavioral issues, and developmental or intellectual disorder), and number of overnight hospitalizations (ranging from none to three or more times) in the last 12 months.

Care Intensity.

Level of care intensity was measured by several variables including: (1) the respondent identified as a primary caregiver (primary or provides majority of care), (2) care recipient lives in caregiver’s household, (3) length of time care provided (ranging from less than 6 months to over 10 years), (4) weekly hours of caregiving, (5) number of ADLs requiring assistance (6-items; transferring, dressing, toileting, bathing/showering, feeding, and dealing with in-continence), and (6) number of IADLs requiring assistance (7-items; e.g., transportation, grocery or other shopping, housework, meal preparation, financial management, medication administration, and arranging outside services).

Other Caregiving- and Financial-Related Variables.

We also included items assessing whether the informal caregiver had a choice in taking on the caregiving role, experienced difficulty with getting affordable care, and whether they had ever requested information about financial help for the care recipient.

Analysis.

We conducted one-way analysis of variance (ANOVA) for continuous variables and chi-square tests for categorical variables to compare all demographic and caregiving-related characteristics by subjective financial strain and objective financial impacts, respectively. Next, we conducted logistic regression models to identify potential factors associated with subjective financial strain and objective financial impacts. We built the models by including the four main categories following our conceptual model: (1) caregivers’ demographic characteristics, (2) care recipients’ conditions, (3) care intensity, and (4) financial-related factors. Lastly, we conducted sensitivity analyses on a subsample (n = 259) of working caregivers who responded to both items assessing difficulty with assisting with ADLs and the time demands of managing finances, bills, or insurance claims. These analyses examined whether these challenges were associated with the financial aspects of caregiving after controlling for all covariates in the main analyses. Population weights were applied in regression models to ensure proper statistical inference. All analyses were conducted with STATA 17 (StataCorp); a p-value of < .05 was used to denote statistical significance.

Results

Descriptive Analyses

Descriptive statistics for sociodemographic characteristics and key study variables are presented in Table 1. The sample included 1,333 caregivers between the ages of 18 and 93 (Mage = 56, SD = 17). Participants were largely female (n = 794, 60%), non-Hispanic White (n = 796, 60%), and a majority of the sample (64%) self-reported as a primary caregiver. Twelve percent of participants resided in a rural geographic area. Care recipients were on average 77 years old (SD = 12), female (64%), with 67% of care recipients requiring caregiving assistance for a long-term physical condition. About 51% had at least one overnight hospitalization in the last 12 months. Caregivers provided an average of 23 hours (SD = 27.6) of care per week, assisting with roughly 1.7 (SD = 1.8) and 4.5 (SD = 1.8) ADL and IADLs, respectively. In addition, about 54% of informal caregivers reported having no choice in providing care and 24% had requested information about financial help. Approximately 40% of informal caregivers reported mild subjective financial strain and 15% reported moderate to severe strain. For objective indicators, the most commonly reported financial impacts were on savings (31%), followed by debt (25%) and paying bills (18%).

Table 1.

Sample Characteristics and Bivariate Relationships With Financial Strain and Impacts (N = 1,333)

Entire Sample
 Subjective Financial Strain
No Strain
 Some Strain
 Substantial Strain
N = 1,333 N = 597 N = 532 N = 204 p-Value
Caregiver age, mean (SD) 55.9 (16.5) 58.7 (16.6) 54.2 (15.9) 51.8 (16.8) <.001
Female caregiver, n (%) 794 (59.6) 366 (61.3) 304 (57.1) 124 (60.8)
Caregiver race/ethnicity, n (%) .032
 Non-Hispanic White 796 (59.7) 387 (64.8) 300 (56.4) 109 (53.4)
 Non-Hispanic Black 156 (11.7) 71 (11.9) 58 (10.9) 27 (13.2)
 Asian, Pacific Island 150 (11.3) 53 (8.9) 68 (12.8) 29 (14.2)
 Hispanic 168 (12.6) 62 (10.4) 77 (14.5) 29 (14.2)
 Other 63 (4.7) 24 (4.0) 29 (5.5) 10 (4.9)
Caregiver education, n (%) .807
 Less than high school 58 (4.4) 23 (3.9) 25 (4.7) 10 (4.9)
 High school graduate 288 (21.6) 130 (21.8) 111 (20.9) 47 (23.0)
 Some college 298 (22.4) 131 (21.9) 114 (23.4) 53 (26.0)
 Technical school, associate degree 147 (11.0) 66 (11.1) 56 (10.5) 25 (12.3)
 Bachelor’s degree 309 (23.2) 140 (23.5) 127 (23.9) 42 (20.6)
 Graduate or professional degree 233 (17.5) 107 (17.9) 99 (18.6) 27 (13.2)
Caregiver household income per capita, n (%) <.001
 Under $15k 326 (24.5) 125 (20.9) 130 (24.4) 71 (34.8)
 $15–$ 29k 339 (25.4) 139 (23.3) 142 (26.7) 58 (28.4)
 $30–$49k 302 (22.7) 145 (24.3) 119 (22.4) 38 (18.6)
 $50–$74k 165 (12.4) 81 (13.6) 65 (12.2) 19 (9.3)
 $75–$99k 93 (7.0) 42 (7.0) 44 (8.3) 7 (3.4)
 $100k or more 108 (8.1) 65 (10.9) 32 (6.0) 11 (5.4)
Employed while caregiving 739 (55.4) 303 (50.8) 318 (59.8) 118 (57.8) .007
Care recipient age, mean (SD) 77 (12) 79 (12) 75 (12) 73 (13) <.001
Female care recipient, n (%) 858 (64.4) 395 (66.2) 351 (66.0) 112 (54.9) .009
Number of care recipient conditions, mean (SD) 1.7 (1.1) 1.4 (0.9) 1.8 (1.1) 2.2 (1.3) <.001
Hospitalizations, n (%)
 None 649 (48.7) 328 (54.9) 258 (48.5) 63 (30.9)
 One time 304 (22.8) 127 (21.3) 136 (25.6) 41 (20.1)
 Two times 187 (14.0) 74 (12.4) 70 (13.2) 43 (21.1)
 Three or more times 193 (14.5) 68 (11.4) 68 (12.8) 57 (27.9)
 Primary caregiver, n (%) 856 (64.2) 358 (60.0) 348 (65.4) 150 (73.5) .002
 Care recipient lives with caregiver, n (%) 190 (31.8) 221 (41.5) 104 (51.0) 515 (38.6) <.001
 Caregiver lives in a rural area, n (%) 158 (11.9) 68 (11.4) 63 (11.8) 27 (13.2) .781
Length of caregiving, n (%)
 Less than 6 months 303 (22.7) 161 (27.0) 116 (21.8) 26 (12.8) .003
 6 months–1 year 243 (18.2) 109 (18.3) 90 (16.9) 44 (21.6)
 1–4 years 412 (30.9) 183 (30.7) 165 (31.0) 64 (31.4)
 5–9 years 215 (16.1) 84 (14.1) 94 (17.7) 37 (18.1)
 10 years or more 160 (12.0) 60 (10.1) 67 (12.6) 33 (16.2)
Weekly hours of caregiving, mean (SD) 23.3 (27.6) 17.5 (24.3) 24.9 (27.9) 36.3 (30.8) <.001
Number of ADLs helped with, mean (SD) 1.7 (1.8) 1.3 (1.7) 1.9 (1.9) 2.3 (2.0) <.001
Number of IADLs helped with, mean (SD) 4.5 (1.8) 3.9 (1.8) 4.8 (1.7) 5.2 (1.7) <.001
Had no choice in caregiving role, n (%) 722 (54.2) 252 (42.2) 322 (60.5) 148 (72.6) <.001
Requested information about financial help, n (%) 322 (24.2) 79 (13.2) 161 (30.3) 82 (40.2) <.001
Had difficulty getting affordable services, mean (SD) 3 (1) 2 (1) 3 (1) 4 (1) <.001
Saving impacts 414 (31.1) 70 (11.7) 196 (36.8) 148 (72.6) <.001
Debt impacts 328 (24.6) 57 (9.6) 152 (28.6) 119 (58.3) <.001
Bill impacts 242 (18.2) 48 (8.0) 100 (18.8) 94 (46.1) <.001
Home impacts 92 (6.9) 11 (1.8) 42 (7.9) 39 (19.1) <.001
Work impacts 182 (13.7) 24 (4.0) 87 (16.4) 71 (34.8) <.001
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Bivariate Analyses

ANOVA and chi-square tests were conducted to examine the bivariate relationships among subjective financial strain and our independent variables. Results indicated that younger age of the caregiver and care recipient were both associated with greater levels of subjective financial strain. Asian Pacific Islander (65%) participants had the highest reports of subjective financial strain (p = .032), followed by Hispanic (63%) informal caregivers. Informal caregivers with the highest level of household income per capita ($100k or more) had the lowest proportion (40%) of reported subjective financial strain. Those with greater subjective financial strain provided care to individuals with more health conditions, hospitalizations, and ADL and IADL needs. Further, being a primary caregiver, co-residing with the care recipient, and greater number of hours of care provided weekly were all associated with higher subjective financial strain. Lastly, 65% of informal caregivers who reported having no choice in taking on caregiving responsibilities reported experiencing subjective financial strain. Among informal caregivers who had requested information about financial help, 75% reported subjective financial strain. Further, subjective financial strain was also associated with difficulty accessing affordable services for care recipients.

Multivariate Analyses

Results from the logistic regression models for subjective financial strain and each objective financial impact as outcomes are shown in Table 2.

Table 2.

Multivariate Regression Results for Factors Associated With Subjective Financial Strain and Objective Financial Impacts

Subjective
 Saving
 Debt
 Bills
 Home
 Work
OR (95% CI)
Caregiver age 0.996 (0.986–1.005) 1.002 (0.991–1.012) 0.993 (0.982–1.003) 0.985* (0.973–0.997) 0.984 (0.968–1.000) 0.998 (0.983–1.014)
Female caregiver 0.830 (0.644–1.070) 0.986 (0.738–1.318) 1.055 (0.778–.431) 1.022 (0.715–1.462) 1.140 (0.675–1.927) 1.209 (0.815–1.793)
Caregiver race/ethnicity
 Non-Hispanic Black 0.812 (0.544–1.212) 1.149 (0.710–1.859) 1.500 (0.963–2.338) 2.146* (1.266–3.635) 1.455 (0.725–2.920) 1.731* (1.027–2.917)
 Asian, Pacific Island 1.214 (0.785–1.878) 0.713 (0.423–1.201) 0.510 (0.251–1.039) 0.885 (0.439–1.784) 0.946 (0.362–2.468) 1.532 (0.758–3.097)
 Hispanic 1.077 (0.731–1.588) 1.191 (0.774–1.832) 0.979 (0.619–1.547) 1.650 (0.997–2.732) 1.536 (0.755–3.125) 0.863 (0.468–1.593)
 Other 1.233 (0.709–2.146) 1.514 (0.791–2.900) 0.803 (0.371–1.740) 1.555 (0.746–3.244) 0.777 (0.266–2.273) 0.926 (0.349–2.454)
Caregiver education 1.004 (0.922–1.095) 1.050 (0.948–1.162) 1.022 (0.916–1.141) 0.932 (0.821–1.058) 1.084 (0.890–1.320) 1.025 (0.884–1.188)
Caregiver household income per capita 0.904* (0.824–0.993) 0.757* (0.675–0.849) 0.760* (0.666–0.867) 0.732* (0.621–0.864) 0.789* (0.623–0.998) 0.912 (0.776–1.071)
Employed while caregiving 1.210 (0.922–1.588) 1.381* (1.003–1.902) 1.213 (0.864–1.702) 1.254 (0.841–1.868) 0.950 (0.573–1.576) 3.625* (2.177–6.036)
Care recipient age 0.973* (0.961–0.985) 0.981 (0.968–0.994) 0.976 (0.963–0.990) 0.986 (0.970–1.001) 0.975* (0.953–0.997) 0.987 (0.970–1.005)
Female care recipient 0.934 (0.717–1.216) 0.925 (0.683–1.252) 0.970 (0.714–1.316) 1.190 (0.820–1.725) 1.266 (0.738–2.171) 1.401 (0.924–2.123)
Number of care recipients’ condition 1.286* (1.147–1.441) 1.177* (1.021–1.356) 1.240* (1.069–1.439) 1.229* (1.039–1.454) 1.591* (1.281–1.976) 1.416* (1.199–1.672)
Hospitalizations 1.195* (1.063–1.344) 1.100 (0.963–1.256) 1.107 (0.965–1.271) 1.237* (1.056–1.448) 1.129 (0.915–1.393) 1.044 (0.868–1.255)
Primary caregiver 1.014 (0.775–1.327) 1.039 (0.750–1.440) 0.708* (0.504–0.994) 1.044 (0.707–1.541) 0.953 (0.535–1.699) 1.135 (0.732–1.760)
Care recipient lives with caregiver 1.128 (0.829–1.535) 1.947* (1.372–2.764) 1.806* (1.248–2.613) 1.360 (0.902–2.051) 3.671* (1.939–6.950) 2.609* (1.625–4.189)
Caregiver lives in a rural area 1.293 (0.829–1.869) 1.124 (0.725–1.742) 1.639* (1.041–2.581) 1.537 (0.949–2.490) 0.712 (0.275–1.844) 0.986 (0.528–1.843)
Length of caregiving 1.138* (1.032–1.254) 1.077 (0.956–1.213) 1.172* (1.035–1.326) 1.139 (0.990–1.310) 1.561* (1.281–1.902) 1.210* (1.039–1.410)
Weekly hours of caregiving 1.008* (1.002–1.014) 1.004 (0.999–1.010) 1.004 (0.997–1.010) 1.008* (1.002–1.015) 0.997 (0.988–1.007) 0.995 (0.987–1.003)
Number of ADLs helped with 1.040 (0.961–1.125) 0.981 (0.895–1.075) 0.952 (0.866–1.047) 0.884* (0.793–0.956) 1.021 (0.881–1.184) 0.994 (0.885–1.116)
Number of IADLs helped with 1.139* (1.043–1.243) 1.152* (1.048–1.268) 1.118* (1.012–1.235) 1.189* (1.054–1.340) 1.105 (0.936–1.351) 1.226* (1.067–1.409)
Had no choice in caregiving role 1.699* (1.320–2.186) 1.397* (1.042–1.874) 1.045 (0.769–1.420) 0.866 (0.611–1.229) 0.886 (0.539–1.455) 1.088 (0.734–1.635)
Requested information about financial help 1.787* (1.343–2.378) 2.006* (1.451–2.773) 1.771* (1.271–2.469) 1.548* (1.052–2.278) 1.574 (0.902–2.747) 2.100* (1.403–3.144)
Had difficulty getting affordable services 1.726* (1.549–1.924) 1.322* (1.182–1.478) 1.290* (1.145–1.454) 1.351* (1.178–1.550) 1.114 (0.909–1.366) 1.399* (1.196–1.637)
Pseudo R2 0.193 0.172 0.160 0.207 0.226 0.213
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*

p < .05.

Population weights were applied.

Subjective Financial Strain.

Examining subjective financial strain as an outcome showed that older care-recipient age (OR = 0.97, 95% CI: 0.96–0.99) and informal caregivers’ higher household income per capita (OR = 0.90, 95% CI: 0.82–0.99) were associated with lower odds of reporting higher subjective financial strain. Further, poorer care-recipient health (OR = 1.29, 95% CI: 1.15–1.44), hospitalizations (OR = 1.20, 95% CI: 1.06–1.34), greater duration of caregiving (OR = 1.1, 95% CI: 1.03–1.25), more hours of care provided weekly (OR = 1.01, 95% CI: 1.00–1.01), and assisting with a greater number of IADLs (OR = 1.14, 95% CI: 1.04–1.24) were significantly associated with increased subjective financial strain. Informal caregivers who reported no choice in providing care (OR = 1.70, 95% CI: 1.32–2.19), requested information about financial help (OR = 1.79, 95% CI: 1.34–2.38), and had trouble getting affordable services for care recipients (OR = 1.73, 95% CI: 1.55–1.92) also showed greater odds of reporting subjective financial strain.

Objective Financial Impacts.

Each category of objective financial impacts were subsequently examined as outcomes (see Table 2 for odds ratios and confidence intervals). For impacts on savings, informal caregivers’ household income per capita, employment, care recipient health conditions, co-residing with care recipients, number of IADLs requiring assistance, having no choice in caregiving, requesting information for financial help, and difficulty getting affordable services for care recipients were significant predictors. Similarly, household income per capita, care-recipient health conditions, IADL assistance, duration of caregiving, requesting information for financial assistance, and difficulty accessing affordable care-recipient services also were significantly associated with debt impacts. Informal caregivers living in rural areas had greater odds of reporting debt impacts.

Bill impacts were significantly associated with informal caregiver’s age, household income per capita, care recipient health conditions, hospitalizations, hours of weekly care provision, number of IADLs requiring assistance, requesting information for financial assistance, and having difficulty obtaining affordable scare-recipient services. Alternatively, age of the care recipient, care-recipient health conditions, co-residing with the care recipient, and duration of caregiving were all associated with home impacts.

Examining work impacts as an outcome found being employed, care recipient health conditions, co-residing with the care recipient, duration of caregiving, number of IADLs requiring assistance, requesting information for financial assistance, and having difficulty getting affordable services for care recipients were significant predictors.

Figure 2 shows the marginal effects of increasing IADL dependency on the predicted probability of reporting subjective financial strain. Specifically, the probability of experiencing some and substantial financial strain increased from 35% and 10% when providing no help with IADLs to 43% and 18% when help was provided for 7 IADLs, respectively.

Figure 2.

Figure 2.

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Predicted impact of IADL dependency on each level of subjective financial strain

Our sensitivity analyses indicated that greater number of IADLs requiring assistance (OR = 1.29, 95% CI: 1.03–1.61) and more time spent managing finances, bills, or insurance claims (OR = 2.25, 95% CI: 1.52–3.32) was associated with increased subjective financial strain.

Discussion

Building on prior work, our study provides novel insights into factors associated with subjective financial strain and objective financial impacts among a large sample of diverse informal caregivers. Results showed that informal caregivers’ household income and greater care intensity, specifically the number of IADLs requiring assistance differentially influenced both subjective financial strain and objective impacts, highlighting several important directions for future research.

Care recipients’ health conditions were associated with both subjective and objective assessments of strain. In contrast to some previous studies (Bullock et al., 2003; Kirby & Lau, 2010; Mier, 2007; Siefert et al., 2008), race/ethnicity was not significantly associated with financial strain and most of the impacts after controlling for other factors. This finding aligns with a previous study using an earlier wave of the Caregiving in the U.S. data (2015), with authors suggesting that the expectation of taking on a caregiving role may have better prepared minority informal caregivers for potential financial strains/impacts (Willert & Minnotte, 2021). Further, greater use of social services found among minority informal caregivers may also contribute to offsetting potential financial strain and impacts (Fabius et al., 2020).

Findings related to our hypothesis on income and education were mixed. Expectedly, higher income was associated with lower levels of subjective financial strain and those with higher income were less likely to report experiencing many of the objective impacts; however, education was not a significant factor. While prior work examining older adults have shown income and education to be associated with financial strain (Samuel et al., 2019; Tucker-Seeley et al., 2009), research in family caregiving contexts has been mixed with some concluding no education-based protective effects among informal caregivers (Lai, 2012; Oedekoven et al., 2019).

As discussed by Åkerman et al. (2023) financial strain may more adequately represent the perceived situation of the household that exists independently of educational qualifications and/or other objective indicators of financial strain. For example, Sun et al. (2009) found that perceived feelings of income inadequacy were associated with caregiver depression and anxiety, but household income was not significantly related. Subjective experiences are impacted by external factors (e.g., care responsibilities, worry, anxiety about future costs, and perceived loss of financial control) which may uniquely contribute to subjective financial strain among informal family caregivers (Tough et al., 2019). Consistent with Tucker-Seeley and Thorpe (2019)’s theoretical model, financial well-being is a multidimensional construct that includes a psychosocial component, wherein the subjective experiences of financial strain may operate independently of objective financial resources. In line with this, findings are consistent with Pearlin et al. (1990)’s stress process model, which highlights that multidimensional factors differentially impact informal caregivers’ experiences and outcomes, largely due to their appraisal and ability to cope with the caregiving role. This points to the possibility that, despite resource advantages, educated family caregivers also are subject to perceived financial strain, highlighting the importance of assessing subjective appraisals in addition to objective indicators.

Supporting our hypothesis, we found that care intensity, specifically the number of IADLs provided, was significantly associated with both subjective financial strain and objective financial impacts. This suggests that the more complex, intensive, and time-consuming aspects of caregiving contribute to subjective financial strain and objective financial impacts. More hours of care provision may preclude or reduce the ability to work, therefore increasing subjective financial strain and objective financial impacts among caregivers. Additionally, IADL tasks, which include activities such as managing finances, shopping for groceries, and handling housecleaning or cooking, often entail additional financial costs. For instance, if the care recipient is unable to perform these tasks, caregivers may need to hire help, increasing care expenses (Reinhard et al., 2023). One notable IADL to consider is financial management, which is especially time-consuming and typically falls on the primary unpaid caregiver. This responsibility carries a significant financial burden, as supported by our sensitivity analyses, and can be a source of considerable stress and financial strain.

We also found that caregivers who reported subjective financial strain were more likely to request information about financial help compared to those who did not report subjective financial strain (33% vs 14%). Similarly, caregivers who reported objective financial impacts were more likely to seek financial assistance compared to those who did not experience objective financial impacts. In the multivariate analyses, requesting information about financial help was significantly associated with higher likelihood of experiencing both subjective strain and most objective financial impacts. This finding suggests that individuals who seek out financial support may be actively searching for assistance due to financial distress but may not receive adequate support. Consequently, their financial challenges remain unresolved, exacerbating their sense of strain. Future research is needed to determine if seeking information on financial assistance is related to actual receipt of such help.

Given the high prevalence of informal caregivers facing financial hardship due to care costs (AARP & NAC, 2025), disruptions to work productivity via increased rates of absenteeism and presenteeism (Fakeye et al., 2023), and the documented links between financial strain on adverse physical and mental health outcomes across the lifespan (Kahn & Pearlin, 2006), results of our study highlight critical policy implications for supporting caregivers related to the availability and accessibility of financial assistance programs. Caregivers actively seeking information about financial help are likely in urgent need of support. Policies should ensure that once caregivers seek assistance, they receive adequate and timely support to mitigate their financial burdens. Moreover, our findings suggest that targeted support should be provided to caregivers heavily involved in IADLs. Financial assistance programs should consider the additional costs associated with these tasks and offer appropriate compensation or subsidies.

The study’s findings should be considered within the context of its limitations. First, due to the nature of this cross-sectional study, it does not capture how caregiving impacts financial outcomes over time. To mitigate this limitation, we included the duration of caregiving to explore whether long-term caregiving was associated with subjective financial strain and objective financial impacts. Additionally, the current analyses rely on secondary data which limited our ability to measure subjective financial strain beyond a single-item indicator. Future research should include more comprehensive assessments of subjective financial strain to further explore how this construct uniquely impacts caregiving outcomes compared to objective measures. Next, due to the wording of the questions, we lack information on causality or timing. Participants were asked how much of a subjective financial strain or any of the objective financial impacts they experienced, and if they had ever requested information about financial help, but it is unclear from whom the help was requested or the outcomes of these requests. Consequently, we cannot determine whether assistance was sought from official agencies or informal support groups, nor can we ascertain if any assistance was received or if the financial issues were resolved. Further, while a large body of work in cancer populations has identified predictors of financial toxicity, future studies should focus on how predictors of financial strain may differentially impact various conditions. Although we included weekly hours of caregiving and the number of ADL and IADL supports provided, we were unable to differentiate the allocation of time spent on each caregiving task. Future research using longitudinal assessments of family caregivers are needed to elucidate how subjective financial strain may change over the course of the caregiving trajectory. Additional studies also should explore how perceptions of strain may differ across types of diagnoses as well as how informal (e.g., family and friends) and formal (e.g., agencies and organizations) social supports may influence the experience and perception of financial strain. Finally, research is needed to focus on the development of family-centered interventions to alleviate financial burden with the goal of increasing quality of life and quality of care in both caregivers and their care recipients.

Conclusion

The growing necessity of informal caregivers to assist the increasing number of individuals living with chronic illness or disability underscores a critical public health crisis with far-reaching physical, psychosocial, and economic implications. Despite a growing knowledge base documenting financial strain as a common experience among family caregivers (Reinhard et al., 2023), prior research in this area has been largely limited to cancer populations and little research has focused on correlates and predictors that may differentially impact financial strain. This study provided novel and important insights regarding the demographic and care-related indicators associated with financial strain and impact among a large, nationally representative sample of informal caregivers.

What this paper adds

  • Our study provides novel insights into factors associated with subjective financial strain and objective financial impacts among a large sample of informal caregivers.

  • Care intensity, specifically the number of IADLs provided, was significantly associated with both subjective financial strain and objective financial impacts.

  • Findings suggest that individuals who seek financial support may be actively doing so in response to financial distress, yet they may not receive adequate support.

Applications of study findings

  • Targeted assistance is needed for informal caregivers heavily involved in IADLs, which often involve greater time and cost.

  • Informal caregivers seeking financial help are likely in urgent need and should receive timely, adequate support to reduce financial burdens.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was partially funded by a grant from the Administration for Community Living through award number 90CGPS0005-01-00. Research reported in this publication was also supported by the National Institute on Aging of the National Institutes of Health under Award Number R00AG073509 (PI: Falzarano). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Ethical Considerations

This study did not involve the collection of new data from human participants. It utilizes publicly available secondary data sources. Therefore, Institutional Review Board (IRB) was not required.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The “Caregiving in the U.S. 2020” public use data files are publicly accessible on the National Alliance for Caregiving website. This study is not preregistered.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The “Caregiving in the U.S. 2020” public use data files are publicly accessible on the National Alliance for Caregiving website. This study is not preregistered.

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