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. Author manuscript; available in PMC: 2023 Nov 2.
Published in final edited form as: J Aging Soc Policy. 2021 May 18;34(6):860–875. doi: 10.1080/08959420.2021.1927613

Profiles of Caregiving Arrangements of Community-dwelling People Living with Probable Dementia

Eric Jutkowitz 1,2,*, Lauren L Mitchell 3, Barbara H Bardenheier 4, Joseph E Gaugler 5
PMCID: PMC8599523  NIHMSID: NIHMS1714331  PMID: 34003081

Abstract

People living with dementia receive care from multiple caregivers, but little is known about the structure of their caregiving arrangements. This study used the Health and Retirement Study and latent class analyses to identify subgroups of caregiving arrangements based on caregiving hours received from spouses, children, other family/friends, and paid individuals among married (n=361) and unmarried (n=473) community-dwelling people with probable dementia. Three classes in the married sample (class 1 “low hours with shared care,” class 2 “spouse-dominant care,” and class 3 “children-dominant care”) were identified. In class 1, spouses, children, and paid individuals provided 53%, 22%, and 26% of the caregiving hours, respectively. Three classes in the unmarried sample (class 1 “low hours with shared care,” class 2 “children-dominant care,” and class 3 “paid-dominant care”) were identified. In unmarried class 1, children, other family/friends, and paid individuals provided 35%, 41% and 24% of the caregiving hours, respectively.

Keywords: dementia, caregiving, long-term care

Introduction

More than five million Americans are living with Alzheimer’s disease and Alzheimer’s disease-related dementia (ADRD) and they receive most of their long-term care support from family and friend caregivers (Alzheimer’s Association, 2018; Jutkowitz, Gaugler, et al., 2020; Kaye et al., 2010). Family/friend caregivers perform multiple tasks including assisting with functional limitations (e.g., managing finances and dressing), transportation, and managing medications and comorbidities (Friedman et al., 2015; Kasper et al., 2015; Schulz et al., 2016a; Gaugler & Kane, 2015). Although caregiving for a person with ADRD can be physically and emotionally challenging, caregiving can also have positive benefits including creating a sense of purpose and accomplishment (Cheng, 2017; Roth et al., 2015).

Older adults and people living with ADRD often want to live in their community, but they may experience challenges navigating a fragmented long-term care system (Gaugler & Kane, 2015). The provision of long-term care is the role of individuals, families, and to a lesser extent states and health plans (Gaugler & Kane, 2015; Jutkowitz, Gozalo, et al., 2020; Kaye, 2012; Kaye et al., 2010). When states and health plans offer long-term care services and supports, benefits are mostly for the care recipient (i.e., beneficiary) and marginalize the caregiving network (Schulz et al., 2016a).

Although people living with ADRD receive care from multiple caregivers, there are limited empirical data on the structure of such networks (Carpentier & Ducharme, 2003; Spillman et al., 2019; Friedman et al., 2015; Kasper et al., 2015; Wolff et al., 2016). The few empirical studies on ADRD caregiving networks are generally informed by the hierarchical compensation theoretical model or the task-specific model (Messeri et al., 1993). The hierarchical compensation model posits there is preference for caregivers based on the primacy of the relationship between the caregiver and care recipient (Cantor, 1979). In this framework, spouses are generally assumed to be the preferred caregiver. When a spouse is unavailable (e.g., a spouse also has a disability or care recipient is unmarried), then preference is given to the next most close relative (e.g., children). The task-specific model posits caregiving is a function of the care recipient’s needs, the availability of caregivers, and a match between the caregiver’s abilities and recipient’s needs (Litwak, 1985). For example, in a task-specific framework, a spouse may provide assistance with dressing while a paid caregiver may help with medical tasks. Empirical studies on the ADRD caregiving network generally support these frameworks. One large study found that married people living with ADRD are more likely to receive intensive caregiving (>200 hours per month) than their unmarried counterparts (Friedman et al., 2015). Another study found that people living with ADRD had larger caregiving networks than older adults without ADRD. While ADRD caregiving networks were characterized by caregivers that provide support for multiple tasks, older adults without ADRD were more likely to have caregivers that specialized in the help they delivered (Spillman et al., 2019).

The size and composition of caregiving networks have implications for long-term care policy. Currently, there are seven caregivers for every adult 80+, but by 2050 there are expected to be three caregivers for every adult 80+ (Redfoot et al., 2013). Family caregiving substitutes for nursing home and formal community-based care, but with fewer family/friend caregivers there will be great pressure on families, states, and the nation to meet the growing demand for caregiving and a greater reliance on formal care services (Bremer et al., 2017; Charles & Sevak, 2005; Gaugler & Kane, 2015). To help address current and impending care gaps, it is important to understand the diverse composition of family/friend caregiving arrangements.

The salience of understanding caregiving networks is also highlighted by ongoing state and federal policies to support caregivers and a cultural shift towards person- and family centered long-term care (National Quality Forum, 2020; Schulz et al., 2016). States have started to implement paid family leave policies to support employees that are also caregivers (Arora & Wolf, 2018). At the national level, the federal government provides grants to states for caregiver support programs, and the recently established RAISE Family Caregivers Council seeks to coordinate caregiver support efforts across federal agencies. Finally, a core feature of person- and family centered long-term care is collaboration between care recipients, the caregiving network, and health care providers (Feinberg, 2014). To successfully advance evidence-based caregiving policy and person- and family- centered care necessitates an improved understanding of diverse caregiving networks (Fabius et al., 2020; Gaugler, 2021).

We sought to identify subgroups of caregiving networks of community-dwelling people living with probable ADRD. In addition, we examined the relationship between the personal characteristics of people living with ADRD and the composition of their caregiving network. Informed by theory and empirical studies, we stratify our analyses based on the marital status of the person with ADRD (Friedman et al., 2015; Messeri et al., 1993). Although our study is exploratory, we expect that the number of functional activity limitations of the person with ADRD and access to more potential caregivers (being married and having more children) is positively associated with receiving more hours of caregiving.

Methods

Data and Sample

We used 2012 (most recent year available for our analysis) cross-sectional data from the Health and Retirement Study (RAND HRS and RAND HRS Family Files), which is a national survey of Americans 50+ (Juster & Suzman, 1994). HRS samples community-dwelling Americans and seeks to follow all respondents until death. During HRS interviews, which are conducted every two years, respondents or a proxy provide detailed demographic, family, and medical information. In addition, respondents report the amount of caregiving received from family, friends, and paid individuals.

We used the Langa-Weir algorithm to identify respondents predicted to have ADRD (Langa et al., 2018). The Langa-Weir algorithm predicts whether an HRS respondent has ADRD in each survey wave based on respondent answers to immediate and delayed recall test, serial 7 subtraction test, and backward count from 20 test (Langa et al., 2017, 2018; Wallace et al., 2005). For respondents with a proxy, the Langa-Weir algorithm predicts ADRD status based on the proxy’s assessment of the respondent’s memory, cognition, and physical functioning. In validation studies, the Langa-Weir algorithm correctly classified 76% of self-respondents and 84% of respondents with a proxy (Crimmins et al., 2011).

Our analytic sample consisted of all HRS respondents ≥65 years of age and predicted to have ADRD (i.e., probable ADRD) in 2012. We excluded people living with probable ADRD <65 years of age since the role of their caregivers may be different from people living with probable ADRD ≥65 (Wawrziczny et al., 2017). We also excluded HRS respondents with probable ADRD who were not living in the community at the time of their interview, had issues linking across HRS files that were merged for the analysis, or who had data missing on the outcome or covariates of interests (described below).

Caregiving Received

During HRS interviews, respondents reported whether they received assistance performing functional activities (preparing hot meals, shopping for groceries, making telephone calls, taking medication, getting across a room, dressing, bathing, toileting, eating, and getting in/out of bed). If a respondent received assistance for a functional activity, then they were asked about the individual(s) (i.e., caregiver) that helped them with the task and their relationship to the caregiver(s). We classified each caregiver as a spouse, child, other family/friend, or a paid individual employed by an organization or a nonrelative that was paid for caregiving. The respondent also reported the amount of time each caregiver provided assistance for the task and number of days the caregiver provided help. We calculated the total hours of caregiving received per month from each caregiver category.

Characteristics of People Living with Probable ADRD

We obtained the sociodemographic characteristics of respondents (age, gender, race, years of education, marital status, Medicaid enrollment, long-term care insurance, if they had a proxy respondent, net worth, number of children, and number of people living in the household) and number (0–8) of chronic conditions (high blood pressure or hypertension, diabetes or high blood sugar, cancer except skin cancer, lung disease except asthma or emphysema, heart attack/coronary heart disease/angina/congestive heart failure/or other heart problems, stroke, psychiatric problems, or arthritis). We also calculated the number (0–10) of functional activity limitations a respondent reported performing (1=respondent has some difficulty; 0=respondent has no difficulty), which is a combination of instrumental activities of daily living (preparing hot meals, shopping for groceries, making phone calls, and taking medication) and basic activities of daily living (getting across a room, dressing, bathing, toileting, eating, and getting in/out of bed).

Data Analysis

Following preliminary analyses and based on the literature, we stratified the sample into people living with probable ADRD that were married at the time of the HRS interview and unmarried at the time of the HRS interview (i.e., widowed, divorced, or never married at the time of the HRS interview) (Friedman et al., 2015). We compared the population characteristics of married and unmarried people living with probable ADRD with t tests or x2 tests.

We then conducted latent class analyses to identify data-driven subgroups of the hours of caregiving received by community-dwelling people living with probable ADRD (Collins & Lanza, 2009). Latent class indicators included the hours of care received by each caregiving source (spouse, children, other family, and paid caregivers) and the characteristics of the person with probable ADRD as predictors of class membership. We estimated a series of models with one, two, three, and four classes. We examined model fit statistics (i.e., Akaike Information Criterion, Bayesian Information Criterion) and model interpretability to determine the optimal number of classes. Our final latent class models were fit within each stratum. We assigned individuals to a class based on their maximum posterior probability, and then compared the demographic characteristics of individuals between each class using relative risk ratios. All analyses were approved by the Institutional Review Board of Brown University (3#1810002244) and conducted using Stata version 16 software.

Results

Of the 20,554 HRS (2012) respondents, 895 (4.4%) met our definition of ADRD, and 834 had no missing data and were included in our analytic sample. In the married stratum (n=361), respondents were on average 79.2 (SD=6.8) years of age, mostly men (62.9%), and generally not a Medicaid beneficiary (16.3% on Medicaid) (Table 1). In comparison, in the unmarried stratum (n=473) respondents were on average 82.9 (SD=8.2) years of age, mostly female (75.1%), and 31.9% were a Medicaid beneficiary (Table 1).

Table 1.

Sample Characteristics of People Living with Probable ADRD

Married at Time of HRS Interview Unmarried at Time of HRS Interview
Total Married Straum Class 1: low hours with shared care Class 2: Spouse- Dominant Care Class 3: Children- Dominant Care Total Unmarried Strauma Class 1: low hours with shared care Class 2: Children- Dominant Care Class 3: Paid- Dominant Care
n=361 n=282 (78%) n=65 (18%) n=14 (4%) n=473 n=392 (83%) n=57 (12%) n=24 (5%)
Age, mean (SD), y 79.2 (6.8) 78.9 (7.0) 79.5 (6.4) 83.2 (6.1) 82.9 (8.2)*** 82.2 (8.2) 85.2 (8.1) 88.6 (6.1)
Female, n (%) 134 (37.1) 107 (37.9) 19 (29.2) 8 (57.1) 356 (75.3)*** 290 (74.9) 49 (86.0) 17.8 (71.0)
Race, n (%)
 White 261 (72.3) 203 (72.0) 49 (75.4) 9 (64.2) 292 (61.7)** 245 (62.5) 28 (49.1) 19 (79.2)
 African American 79 (21.8) 63 (22.3) 12 (18.5) 4 (28.6) 152 (32.1) 122 (31.1) 27 (47.4) 3 (12.5)
 Otherb 21 (5.8) 16 (5.7) 4 (6.2) 1 (7.1) 29 (6.1) 25 (6.4) 2 (3.5) 2 (8.3)
Education, mean (SD), y 10.3 (4.0) 10.2 (4) 10.9 (4.2) 10.6 (4.1) 9.4 (4.0)** 9.5 (3.9) 8.5 (4.1) 11.4 (4.5)
Marital status, n (%)
 Married/partnered 361 (100) 282 (100) 65 (100) 14 (100) - - - -
 Separated /divorced - - - - 75 (15.9) 65 (16.6) 8 (14.0) 2 (8.3)
 Widowed - - - - 365 (77.2) 297 (75.8) 47 (82.5) 21 (87.5)
 Never married - - - - 33 (7.0) 30 (7.7) 2 (3.5) 1 (4.2)
Number (0–10) of functional limitations, mean (SD) 3.3 (3.5) 2.3 (3.0) 6.8 (2.7) 7.6 (2.5) 3.4 (3.3) 2.7 (2.9) 6.8 (2.7) 7.7 (2.3)
 Number (0–4) of instrumental activity of daily living limitations, mean (SD) 1.6 (1.6) 1.1 (1.4) 3.2 (1.0) 3.4 (1.0) 1.7 (1.7) 1.4 (1.6) 3.3 (1.1) 3.3 (1.0)
 Number (0–6) of basic activity of daily living limitations, mean (SD) 1.8 (2.2) 1.2 (1.9) 3.7 (2.2) 4.3 (1.8) 1.7 (2.1) 1.3 (1.8) 3.5 (2.0) 4.4 (1.9)
Number of chronic conditions, mean (SD) 3.2 (1.6) 3.1 (1.6) 3.6 (1.7) 4.3 (1.3) 3.2 (1.5) 3.1 (1.5) 3.7 (1.5) 3.8 (1.8)
Medicaid beneficiary, n (%) 59 (16.3) 45 (15.9) 11 (16.9) 3 (21.4) 150 (31.7)*** 125 (31.9) 20 (35.1) 5 (20.8)
Long-term care insurance, n (%) 39 (10.8) 27 (9.6) 10 (15.4) 2 (14.3) 34 (7.2) 29 (7.4) 4 (7.0) 1 (4.2)
Proxy respondent, n (%) 120 (33.2) 66 (23.4) 41 (63.1) 13 (92.9) 147 (31.1) 90 (22.9) 39 (68.4) 18 (75.0)
Net worth, mean (SD), $ $291,640 (516,202) $280,818 (472,393) $367,400 (706,826) $157,877 (212,891) $191,716
(1,394,134)		 $123,129 (257,412) $64,644 (121,528) $1,613,754c (6,040,989)
Number of children, mean (SD) 4.2 (2.7) 4.1 (2.6) 4 (2.9) 6.4 (3.9) 3.9 (3.0) 3.8 (2.9) 5.1 (3.1) 2.8 (2.9)
Number living household, mean (SD) 2.6 (1.1) 2.6 (1.1) 2.4 (0.8) 4 (1.9) 2.1 (1.6) 2 (1.5) 3.3 (2) 1.5 (0.7)
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a

Comparison between married and unmarried sample.

b

Other race includes American Indian, Alaskan Native, Asian, and Pacific Islander.

c

The mean net worth excluding one outliner was $390,526 (SD = 780,479).

*

p<0.05,

**

p<0.01,

***

p<0.001

Characteristics of Married People Living with Probable ADRD by Class

We identified three classes in the married stratum (Table 1) in which 78% (n=282) of respondents were classified as receiving “low hours with shared care,” 18% (n=65) “spouse-dominant care,” and 4% (n=14) “children-dominant care.” On average, people living with probable ADRD in the low hours with shared care class received 54.2 total hours of caregiving in a month, of which 28.6 hours (95%CI: 18.6, 38.7) were provided by a spouse, 9.1 hours (95%CI: 3.6, 14.5) were provided by children, 2.6 hours (95%CI: −1.7, 6.9) were provided by other family/friends, and 13.9 hours (95%CI: 5.5, 24.2) were provided by paid individuals (Figure 1). On average, people living with ADRD in the low hours with shared care class were 78.9 (SD=7.0) years old, predominately male, had 2.3 (SD=3.0) functional activity limitations, 4.1 (SD=2.6) children, and 2.6 (SD=1.1) people living in their household (Table 1).

Figure 1.

Figure 1.

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Hours of Caregiving Received by People Living with Probable ADRD

Married people living with probable ADRD in the spouse-dominant care class (n=65; 18%) received 455.8 hours of caregiving per month, of which 388.4 hours (95%CI: 364.3, 412.5) were provided by a spouse, with the remaining hours contributed by children (mean 18.7 hours 95%CI: 6.8, 30.7), other family/friends (mean 9.9 hours 95%CI: 0.8, 18.9), and paid individuals (mean 38.8 hours 95%CI: 16.8, 60.8) (Figure 1). On average, members of this class were 79.5 (SD=6.4) years of age, predominantly male, had 6.8 (SD=2.7) functional activity limitations, 4 (SD=2.9) children, and 2.4 (SD=0.8) people living in their household.

Married people living with probable ADRD in the children-dominant care class (n=14; 4%) received 739.2 hours of caregiving in a month. Most of this caregiving was provided by children (mean 486.3 hours 95%CI: 462.1, 510.6) with less from a spouse (mean 101.6 hours 95%CI: 61.1, 142.0), other family/friends (mean 77.8 95%CI: 58.6, 97.2), and paid individuals (mean 73.4 hours 95%CI: 26.9, 119.9) (Figure 1). On average, members of this class were 83.2 (SD=6.1) years old, predominately female, had 7.6 (SD=2.5) functional activity limitations, had 6.4 (SD=3.9) children, and had 4 (SD=1.9) people living in their household.

In a multinomial logistic regression used to predict class membership, functional activity limitations (relative risk ratio 1.48 95%CI: 1.31, 1.67) were associated with a greater risk of being in the spouse-dominant class relative to the low hours with shared care caregiving class (Table 2). In contrast, having more individuals living in the household (relative risk ratio 0.64 95%CI: 0.41, 0.99) was associated with a lower risk of being in the spouse-dominant class relative to the low hours with shared care.

Table 2.

Relative Risk of Class Membership by Characteristics

Married at Time of HRS Interview (n=361) Unmarried at Time of HRS Interview (n=473)
Spouse-Dominant Care relative to Low Hours with Shared Care Children-Dominant Care relative to Low Hours with Shared Care Children-Dominant Care relative to Low Hours with Shared Care Paid-Dominant Care relative to Low Hours with Shared Care
Relative Risk Ratio (95%CI) Relative Risk Ratio (95%CI) Relative Risk Ratio (95%CI) Relative Risk Ratio (95%CI)
Intercept 2.11 (0.03, 170.76) 0 (0, 0)*** 0 (0, 0.04)** 0 (0, 0.01)
Age 0.96 (0.91, 1.01)* 1.07 (0.96, 1.2) 1.01 (0.97, 1.06) 1.04 (0.96, 1.13)
Female 0.41 (0.19, 0.9) 3.24 (0.62, 16.77) 2.55 (0.9, 7.19) 0.46 (0.12, 1.81)
Race (ref = White)  
 African American 1.31 (0.51, 3.33) 1.06 (0.18, 6.36) 3.8 (1.67, 8.62) 0.55 (0.1, 3)
 Othera 2.15 (0.47, 9.88) 1.35 (0.07, 25.83) 1.04 (0.16, 6.67)** 2.14 (0.22, 20.36)
Education 1 (0.9, 1.11) 1.11 (0.91, 1.35) 1.01 (0.9, 1.13) 1.18 (0.99, 1.4)
Marital status (ref =Separated /divorced) - -
 Widowed - - 0.81 (0.3, 2.19) 5.76 (0.4, 83.35)
 Never married - - 0.72 (0.1, 5.35) 1.97 (0.03, 113.73)
Number of functional activity limitations 1.48 (1.31, 1.67)*** 1.42 (1.05, 1.93)* 1.38 (1.2, 1.58)*** 2.23 (1.61, 3.09)***
Number of chronic conditions 1.1 (0.87, 1.38) 1.06 (0.61, 1.85) 1.1 (0.86, 1.4) 1.25 (0.85, 1.85)
Medicaid (ref = no) 1.01 (0.37, 2.7) 0.83 (0.11, 6.37) 0.42 (0.16, 1.08) 0.74 (0.19, 2.88)
Long-term care insurance (ref = no) 2.6 (0.92, 7.36) 1.03 (0.08, 13) 0.77 (0.2, 3) 0.54 (0.05, 5.97)
Proxy respondent (ref = no) 1.6 (0.71, 3.59) 10.71 (0.98, 116.66) 3.61 (1.58, 8.25)*** 2.8 (0.71, 11.07)
Net worth (units of $10,000) 1 (0.99, 1.01) 0.98 (0.95, 1.01) 0.99 (0.97, 1.01) 1.01 (1, 1.02)
Number of children 0.98 (0.85, 1.12) 1.29 (1.03, 1.63)* 1.13 (1, 1.28)* 0.96 (0.74, 1.25)
Number of people living in the household 0.64 (0.41, 0.99)* 2 (1.08, 3.69)* 1.4 (1.14, 1.71)** 0.28 (0.12, 0.65)**
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a

Other race includes American Indian, Alaskan Native, Asian, and Pacific Islander.

*

p<0.05,

**

p<0.01,

***

p<0.001

An additional functional activity limitation (relative risk ratio 1.42 95%CI: 1.05, 1.93), having more children (relative risk ratio 1.29 95%CI: 1.03, 1.63), and more people living in the household (relative risk ratio 2.00 95%CI: 1.08, 3.69) were associated with a greater risk of being in the children-dominant class relative to the low hours with shared care class (Table 2).

Characteristics of Unmarried People Living with Probable ADRD by Class

We identified three classes in the unmarried stratum (Table 1) in which 83% (n=392) of respondents were classified as receiving “low hours with shared care,” 12% (n=57) “children-dominant care”, and 5% (n=24) “paid-dominant care.” Unmarried people living with probable ADRD in the low hours with shared care class received an average of 75.9 hours of caregiving in a month. In this class, children provided 26.9 hours (95%CI: 19.6, 34.3), other family/friends provided 30.9 hours (95%CI: 19.3, 42.6), and paid individuals provided 18.0 hours (95%CI: 11.7, 24.3) (Figure 1). People living with probable ADRD in this class were on average 82.2 (SD=8.2) years of age, predominately female, widowed (75.8%), had 2.7 (SD=2.9) functional limitations, 3.8 (SD=2.9) children, and 2.1 (SD=1.5) individuals living in their household.

Unmarried people living with probable ADRD in the children-dominant care class (n=57; 12%) received 515.5 hours of caregiving in a month. Most of this caregiving was provided by children (mean 401.9 hours 95%CI: 379.5, 424.3) followed by other family/friends (mean 91.2 hours 95%CI: 59.6, 122.9), and paid individuals (mean 21.7 hours 95%CI: 11.4, 45.6). Members of this class were, on average, 85.2 (SD=8.1) years of age, mostly female, had 6.8 (SD=2.7) functional activity limitations, 5.1 (SD=3.1) children, and 3.3 (SD=2.0) individuals living in their household.

Unmarried people living with probable ADRD in the paid-dominant care class (n=24; 5%) received 639.2 hours of caregiving, of which 71.8 hours (95%CI: 43.5, 100.1) were provided by children, 51.6 hours (95%CI: 4.9, 98.2) were provided by other family/friends, and 515.8 (95%CI: 487.4, 544.1) were provided by paid individuals. Individuals in this class were, on average, 88.6 (SD=5.7) years old, predominately female, had 7.7 (SD=2.3) functional activity limitations, 2.8 (SD=2.7) children, and 1.5 (SD=0.7) individuals living in their household.

Functional activity limitations (relative risk ratio 1.38 95%CI: 1.20, 1.58), children (relative risk ratio 1.13 95%CI: 1.0, 1.28) and people living in the household (relative risk ratio 1.40 95%CI: 1.14, 1.71) were positively associated with a greater risk of being in children-dominant class relative to the low hours with shared care.

Finally, functional activity limitations (relative risk ratio 2.23 95%CI: 1.61, 3.09) and having fewer people living in the household (relative risk ratio 0.28 95%CI: 0.12, 0.65) were associated with being assigned to the paid-dominant care class relative to low hours with shared care (Table 2).

Discussion

We identified six distinct caregiving arrangements of community-dwelling people living with probable ADRD: three groups of married adults and three groups of unmarried adults. We found large variation in the total hours of caregiving received across the classes. Despite the range in caregiving hours, people living with probable ADRD across all groups received considerably more hours of caregiving compared to estimates in the literature for people living without ADRD (Friedman et al., 2015).

We observed key differences in the characteristics of people living with probable ADRD who were married and unmarried. Foremost, married people living with probable ADRD were on average younger, more likely to be men, have more children and live in a household with more people than their unmarried counterparts. In both the married and unmarried stratum, having more children was associated with membership in the children-dominant care class. As hypothesized, we found that greater access to potential caregivers (having a spouse, more children, and living with more people) is associated with receiving more caregiving. Although access to potential caregivers was positively associated with the hours of caregiving received, individuals that received more caregiving also had more functional activity limitations. Our analysis was not designed to determine the directionality between the availability of caregivers and need for caregiving.

Most people living with probable ADRD in our analysis received “low hours with shared care” and on average people in this class had 2 functional activity limitations. In contrast, people living with probable ADRD in the other classes had on average 7 functional activity limitations. We do not have data to classify ADRD severity (e.g., measures of disease stage, or behaviors). Although caregivers can reduce functional activity decline, people living with probable ADRD in the low hours with shared care classes are likely in an earlier disease stage than their counterparts (Gitlin et al., 2010; Jutkowitz, MacLehose, et al., 2017).

A proportion of people with probable ADRD in the low hours with shared care class will continue to live in the community as they develop more functional activity limitations. The composition of their caregiving network is also likely to change (Spillman et al., 2019). Providing caregivers with support in the early stages of the disease (e.g., when people with probable ADRD are in a shared class) may help them effectively manage future disease progression. Although non-pharmacologic interventions that provide caregivers with skills have been shown to reduce behaviors and nursing home admissions among people with ADRD in the community, these interventions are not widely disseminated (Gitlin et al., 2010; Samus et al., 2014).

Spouses and children were the largest providers of caregiving for people living with probable ADRD. Most spouse caregivers will outlive their care recipients with ADRD, but close to 18% may not (Gaugler et al., 2018). When spouses are the predominate caregiver, interventions are needed to support spouses in maintaining their own health and developing plans for if the spouse is no longer able to provide care.

In all the classes, children were predicted to provide some caregiving. In two classes children were the predominant caregiver. Many children of people living with ADRD are of working age, so policymakers must develop strategies to support working caregivers (Nobel, 2017). Early studies examining state paid family leave laws indicate these policies may reduce the need for nursing homes (Arora & Wolf, 2018). However, most paid family leave policies are structured to support caregivers for acute care needs (e.g., helping a care recipient after a hospitalization). It is unclear whether existing policies effectively support working ADRD caregivers. For paid family leave laws to fully support caregivers of people living with ADRD, these policies must account for the clinical course of ADRD and long duration of the disease (Gaugler, 2021).

Reliance on spouse and children caregivers is unsustainable, as the number of people living with ADRD is expected to increase and the number of available family caregivers is expected to decrease (Redfoot et al., 2013). Already, an estimated 22% of the older adult population is aging alone with no spouse or nearby children (Carney et al., 2016). The unmarried with paid-dominant care class (n=24; 5%) provides insight into a future where there are fewer caregivers. Aside from differences in the number children, individuals in the unmarried with paid-dominant care class were similar to unmarried people receiving children-dominant care. The differences in number of children and distribution of caregiving hours between paid and unpaid caregiving classes supports literature that family caregivers substitute for paid community care and nursing homes (Bremer et al., 2017; Charles & Sevak, 2005; Gaugler & Kane, 2015).

Our findings have implications for caregiving intervention research. A majority of ADRD caregiving interventions address a dyadic relationship between the person living with ADRD and their “primary caregiver.” Our findings support growing recognition that people living with ADRD receive care from multiple individuals and that caregiver intervention research should expand to be family-centered (recognizing a broad definition of family) that includes multiple members of the caregiving network (Carpentier & Ducharme, 2003; Gallagher-Thompson et al., 2020; Jacobs et al., 2018). Members of the caregiving network can assume different tasks and decision-making responsibilities. For example, a child caregiver may help manage finances from a distance, while a spouse provides daily support with dressing and meal preparation. The task-specific framework of caregiving may be a useful tool to inform approaches to engage caregivers (Messeri et al., 1993). For example, in an advanced care planning intervention it may be important to engage all caregivers responsible for decision-making. In contrast, for an intervention that involves managing the home environment it may only be necessary to engage the primary caregiver. In practice there are many challenges when incorporating members of the caregiving network in interventional research. Challenges that need to be addressed include healthcare benefits that focus on the care recipient and marginalize caregivers as well as caregivers not being included in the healthcare team (Schulz et al., 2016).

Limitations

Our study has several limitations. First, the validated algorithm used to identify people living with ADRD is subject to measurement error. Second, respondents only reported the hours of caregiving received for functional activity limitations. Importantly, caregivers of people living with ADRD provide care beyond support for functional activity limitations including managing comorbidities and communicating with the care recipient’s medical teams. In this respect, the caregiving hours reported may be underestimated. Third, we used cross-sectional data and had limited information on ADRD clinical symptoms (e.g., behaviors) which may affect the amount of caregiving received (Jutkowitz, Kuntz, et al., 2017). Therefore, we are unable to evaluate how caregiving arrangements evolve over the course of ADRD trajectories. However, consistent with prior studies and our hypothesis we found that more functional activity limitations and in some cases having a proxy respondent were associated with being assigned to a class receiving higher amounts of caregiving (Jutkowitz, Gaugler, et al., 2020; Jutkowitz, Gozalo, et al., 2020). Fourth, we did not have data on individual, family, and health system level culture. The values and beliefs of individuals, communities, and health systems greatly contribute to the identification of caregivers, role of caregivers, and organization/delivery of caregiving (Gallagher-Thompson et al., 2020).

Conclusion

In conclusion, people living with ADRD receive a considerable amount of caregiving; however, we identified subgroups in the organization of family/friend caregiving networks. Importantly, marital status and functional activity limitations are key factors in determining caregiving arrangements. Policies designed to support people living with ADRD and their caregivers need to consider the heterogeneous composition of caregiving arrangements.

Key Points:

  • Little is known about variation in the organization of dementia caregiver networks.

  • We find there is heterogeneity in the dementia caregiving network.

  • Most people living with dementia receive caregiving from a group of individuals.

  • Long-term care policy should account for diverse caregiving arrangements.

Acknowledgements:

The Health and Retirement Study is produced and distributed by the University of Michigan with funding from the National Institute on Aging (grant number NIA U01AG009740) Ann Arbor, MI.

Funding/Support: This work was supported by grants from National Institute on Aging (1R21AG059623-01 and 1R01AG060871-01 both to EJ), from the Brown School of Public Health (EJ), and by the Office of Academic Affiliations, Department of Veterans Affairs (LLM).

Footnotes

Disclosure Statement: All authors report no conflicts of interest.

Ethics approval and consent to participate: This is a secondary analysis using the publicly available Health and Retirement Study. This analysis was approved by the Institutional Review Board of Brown University under protocol 3#1810002244.

Contributor Information

Eric Jutkowitz, Department of Health Services, Policy & Practice, Brown University School of Public Health, Box G-S121-6, 121 S. Main Street, 6th Floor, Providence, RI 02912; Providence Veterans Affairs (VA) Medical Center, Center of Innovation in Long Term Services and Supports, Providence, RI, 02908, Phone: 401-863-2060, Fax: 401-863-3489,.

Lauren L. Mitchell, Center for Care Delivery & Outcomes Research, Minneapolis VA Healthcare System, One Veterans Drive, Minneapolis, MN 55417..

Barbara H. Bardenheier, Department of Health Services, Policy & Practice, Brown University School of Public Health, Providence, RI 02912..

Joseph E. Gaugler, Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN 55455..

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