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. Author manuscript; available in PMC: 2021 Jun 1.
Published in final edited form as: J Aging Health. 2019 Feb 22;32(5-6):453–461. doi: 10.1177/0898264319830262

Comparison of Healthcare Utilization Between Informal Caregivers and Non-Caregivers: An Analysis of the Health Information National Trends Survey

Kelly M Shaffer 1,2, Chandylen L Nightingale 3
PMCID: PMC7034877  NIHMSID: NIHMS1556074  PMID: 30793639

Abstract

OBJECTIVES:

The significant daily demands of providing unpaid care for someone with a disabling health condition can limit caregivers’ attention to their own health needs. Using a nationally-representative survey, this study examines whether caregivers report different healthcare utilization relative to non-caregivers.

METHODS:

Participants in the Health Information National Trends Survey 5 Cycle 1 reported sociodemographic and health factors (covariates) and healthcare utilization outcomes. Chi-square tests and multinomial logistic regression with jackknife variance estimation were used.

RESULTS:

Caregivers (N=391) did not differ from non-caregivers (N=2894) in time since routine check-up or number of healthcare visits in the past year in univariate tests (ps>.60) or multivariate tests controlling for covariates (ps>.11). No caregiving factor related to healthcare utilization among caregivers (ps>.25).

DISCUSSION:

Findings suggest that informal caregivers access routine healthcare at a frequency similar to non-caregivers. Further research should help determine whether increased service utilization during caregiving might help attenuate caregivers’ longer-term morbidity.

Keywords: Caregivers, Health Services Accessibility, Caregiving Burden

INTRODUCTION

Over 43 million Americans provided uncompensated care to close individuals (e.g., family members or close friends) with serious physical health conditions in 2015 (National Association for Caregiving [NAC] & AARP, 2015). This often-unrecognized care provided by these informal caregivers provides patients with essential emotional, practical, and medical care and is critical to the sustainability of the U.S. health care system (Reinhard, Feinberg, Choula, & Houser, 2015). The caregiving role, however, often places significant strain on caregivers and increases their risk for developing physical and mental health conditions (Buyck et al., 2013; Ji, Zöller, Sundquist, & Sundquist, 2012; Shaffer, Kim, Carver, & Cannady, 2017b). Despite these increased health risks, caregivers often describe triaging their health needs behind those of the patient (Applebaum, Farran, Marziliano, Pasternak, & Breitbart, 2014; Shaw et al., 2013). This conflict between potentially increased healthcare needs yet poor utilization of healthcare among caregivers is reflected in the literature, with inconsistent findings including lower utilization (Pruchno & Potashnik, 1989), no difference in utilization (Baumgarten et al., 1997; Bigatti & Cronan, 2002; Burton, Newsom, Schulz, Hirsch, & German, 1997; George & Gwyther, 1986; Kiecolt-Glaser et al., 1987), and higher utilization (Chan, Malhotra, Malhotra, Rush, & Østbye, 2013; Cochrane, Goering, & Rogers, 1997; Haley, Levine, Brown, Berry, & Hughes, 1987) among caregivers relative to non-caregivers. To help clarify these conflicting findings and to study the phenomena in the current healthcare climate, this study uses data from a nationally-representative survey of the adult U.S. population to test whether healthcare utilization differs between informal caregivers and non-caregivers.

Routine and appropriate access to healthcare may help attenuate the distress and premature physical morbidity observed among informal caregivers (Bass, Noelker, & Rechlin, 1996). At a population-level, the prevalences of serious health conditions are higher among individuals with a caregiving history, including a higher rate of cerebrovascular and cardiovascular diseases (Buyck et al., 2013; Ji et al., 2012). Psychoneuroimmunological research has demonstrated pro- and anti-inflammatory dysregulation among informal caregivers that can last for years, even after their caregiving responsibilities conclude (Kiecolt-Glaser et al., 2003; Rohleder, Marin, Ma, & Miller, 2009). Distressed and spousal caregivers appear at highest risk for developing physical health problems (Kim, Carver, Shaffer, Gansler, & Cannady, 2015; Schulz & Beach, 1999; Shaffer, Kim, Carver, & Cannady, 2017a; Shaffer et al., 2017b). Despite these risks, caregivers report multiple practical and psychological barriers that interfere with their ability to access appropriate healthcare services, frequently including scheduling difficulty, limited time, and prioritizing patients’ needs above their own (Applebaum et al., 2014; Shaw et al., 2013).

Other research suggests that, given the demanding nature of caregiving, healthier individuals may be more likely to “select in” to caregiving responsibilities, detailed by the “healthy caregiver hypothesis” (Fredman, Doros, Ensrud, Hochberg, & Cauley, 2009). Indeed, physically healthier individuals are more likely on average to take up and persist with caregiving responsibilities (McCann, Hebert, Bienias, Morris, & Evans, 2004). Some epidemiological research suggests caregivers may even report extended longevity compared to non-caregivers (Fredman, Lyons, Cauley, Hochberg, & Applebaum, 2015; Roth, Fredman, & Haley, 2015; Roth et al., 2013). However, other population-based surveys across Europe have found that, while caregivers who do not reside with the care recipient are generally healthy with milder effects to their long-term health, caregivers who co-reside with the care recipient (and likely have less choice in assisting with care) are in poorer health and experience more health decline over the course of caregiving (Kaschowitz & Brandt, 2017).

Findings among extant literature about healthcare utilization among informal caregivers have been mixed. Large population-based surveys have alternatively reported higher outpatient healthcare (Chan et al., 2013) and mental healthcare (Cochrane et al., 1997) usage among caregivers relative to non-caregivers, while others have suggested no differences in healthcare utilization (George & Gwyther, 1986). Studies using matched samples similarly find conflicting results: higher utilization (Haley et al., 1987), no differences (Baumgarten et al., 1997; Bigatti & Cronan, 2002; Burton et al., 1997; Kiecolt-Glaser et al., 1987), or lower utilization (Pruchno & Potashnik, 1989) in caregivers relative to demographically comparable non-caregivers. Another study suggests that healthcare utilization is suboptimal particularly among women who are actively providing care, but that their utilization normalized several years after caregiving responsibilities concluded (Zwart, Bakx, & Doorslaer, 2017). Much of this work has been conducted among samples of exclusively caregivers for people with dementia (Bremer et al., 2015; George & Gwyther, 1986; Haley et al., 1987; Kiecolt-Glaser et al., 1987; Pruchno & Potashnik, 1989), who experience particularly high-burden and chronic caregiving. Moreover, much of this work has had methodological limitations, including inadequate sample sizes, lack of confounder control, and sociodemographically homogenous samples (Baumgarten, 1989; Roth et al., 2013).

As such, the current study sought to address these limitations of and discrepancies within the literature by using a large, nationally-representative dataset that includes a broad range of potential barriers and facilitators to healthcare utilization among informal caregivers and non-caregivers. Aim 1 tested whether caregivers differ from non-caregivers in time since their last routine check-up; Aim 2 tested whether caregivers differ from non-caregivers in total number of healthcare appointments attended in the past year. Finally, Aim 3 explored whether factors related to the potential burden of the caregiving experience affect either time since last check-up or total number of past-year appointments.

METHODS

Study Design and Participants

The Health Information National Trends Survey (Nelson et al., 2004; HINTS, 2017) Version 5, Cycle 1 is a nationally-representative survey of civilian, non-institutionalized adults aged 18 and older in the U.S. Conducted by the National Cancer Institute (NCI), this survey assesses Americans’ access to and use of health information. HINTS was reviewed and approved by the Institutional Review Boards of NCI’s Special Studies and the main contractor (Westat, Inc.). Additional methodology details may be found in the Methodology Report (https://hints.cancer.gov/docs/methodologyreports/HINTS5_Cycle_1_Methodology_Rpt.pdf).

Surveys were distributed by mail between January 2017 and May 2017. A Spanish version of the questionnaire was provided to households registered with a Hispanic surname. To maximize the response rate, a pre-paid incentive was provided with the first mailing, multiple non-response follow-ups were made, and one of the non-response follow-ups utilized express delivery. Of 13,360 surveys mailed, 3,285 participants returned surveys (response rate=32.4%). Survey non-response is correlated with being male, younger age, being of a racial minority background, having less education, being Hispanic, having fewer health problems, and having less access to healthcare. To compensate for non-response, selection weights were calibrated by the NCI to adjust for each of these variables using data from the American Community Survey and the National Health Interview Survey, permitting generalizations of results to the national population.

HINTS 5 Cycle 1 is the first HINTS survey to systematically assess caregiving status and related information. Informal caregivers (n=391) self-identified as a caregiver for an adult by answering affirmatively to the item “Are you currently caring for or making health care decisions for someone with a medical, behavioral, disability, or some other condition?” Informal caregiving surveys typically focus on informal care provided to individuals 18 years of age and older given the anomalous, age-discordant nature of this caregiving experience (e.g., AARP & Project Catalyst, 2016; NAC & AARP, 2015). As such, for the current analysis, participants exclusively reporting caregiving for a child (n=189) were not included in the caregiver subsample.

Measures

The specific wording of all measures reported in this study may be found at: https://hints.cancer.gov/docs/Instruments/HINTS5_Cycle1_Annotated_Instrument_English.pdf

Healthcare utilization.

Participants indicated the time since their last routine check-up. A “routine checkup” was defined in the survey as “a general physical exam, not an exam for a specific injury, illness, or condition.” Responses were “Within the past year,” “1–2 years ago,” “3–5 years ago,” “More than 5 years ago,” “Never,” and “Don’t know.” Responses for 3–5 years ago and 5 or more years ago were collapsed for the present analyses. For both caregiver and non-caregiver samples, fewer than 2% of participants responded “Never” or “Don’t know,” as such, these responses were excluded from the current analyses.

Participants also indicated their number of health care visits in the past year. A “health care visit” was defined in the survey as “not counting times you went to an emergency room, how many times [you went] to a doctor, nurse, or other health professional to get care for yourself.” Responses were “None,” “1 time,” “2 times,” “3 times,” “4 times,” “5–9 times,” and “10 or more times.” Responses for 5–9 times and 10 or more times were collapsed for the present analyses.

Caregiving factors.

As approximate indicators of objective caregiving burden, caregivers reported their relationship to the care recipient, number of hours spent caregiving per week (response options were “less than 5 hours per week,” “5–14 hours per week,” “15–20 hours per week,” “21–34 hours per week,” and “35 or more hours per week”), and number of conditions affecting the care recipient.

Covariates.

Participants reported their age, gender, occupational status, marital status, and education. Rurality of the participants’ address was determined according to the National Center for Health Statistics Urban-Rural Classification Scheme for Counties. Participants also reported whether they had health insurance; their perceived general health; whether a doctor had ever diagnosed them with diabetes, hypertension, a heart condition, lung disease, arthritis, depression or anxiety; level of distress (using the Patient Health Questionnaire [PHQ]-4 [Löwe et al., 2010] sum score); whether they had at least one person available to provide them emotional support or practical support if needed; number of days engaging in any moderate or vigorous physical activity; and whether they had a smoking history.

Analytic Strategy

Research aims were addressed using weighted chi square tests of independence that tested whether caregiver characteristics were associated with healthcare utilization variables. Univariate analyses comparing healthcare utilization outcomes with caregiver status (Aims 1 & 2) and caregiving factors (Aim 3) used chi square tests of independence with SAS 9.4 SURVEYFREQ. Multivariate analyses comparing healthcare utilization outcomes with caregiver status (Aims 1 & 2) controlling for covariates used multinomial logistic regressions with SAS 9.4 SURVEYREG. These procedures were used to account for the complex sampling design of the HINTS survey. Analyses were weighted using the full-sample weights provided in the public use datasets, yielding nationally-representative estimates. Jackknife variance estimation with repeated replications was used to estimate standard errors, reducing estimate bias and therefore risk of Type I error. These procedures are in accordance with published HINTS analysis recommendations (NCI, 2017). Alpha of .05 was used to determine significance for all tests.

RESULTS

Sample descriptives are presented in Table 1. On average, relative to non-caregivers, the caregiver sample was older and had a higher proportion of individuals who were female, partnered, and diagnosed with arthritis (ps<.05). The caregiver sample also trended towards reporting greater distress and having a higher proportion of individuals who were not employed and who were diagnosed with depression or anxiety (.06<ps<.09).

Table 1:

Sample Description

Non-caregivers (N=2894) n(w%) or M(SD) Caregivers (N=391) n(w%) or M(SD) Difference test χ2 or t ([df], p)
Age 46.56 (0.41) 51.80 (1.24) 3.05 ([3284] .002)
Gender 6.37 ([1, 49] .01)
 Male 1175 (50.1) 128 (39.2)
 Female 1662 (49.9) 252 (60.8)
Occupational Status 3.62 ([1, 49] .06)
 Employed 1423 (59.2) 166 (51.4)
 Not Employed1 1328 (40.8) 202 (48.6)
Marital Status2 8.79 ([1, 49] .004)
 Partnered 1495 (53.9) 256 (65.8)
 Not partnered 1290 (46.1) 125 (34.2)
Education 0.52 ([1, 49] .47)
 High school or less 747 (31.9) 86 (29.2)
 Vocational/Some college or more 2055 (68.1) 293 (70.8)
Rurality 0.23 ([1, 49] .63)
 Metropolitan 2518 (86.0) 330 (84.5)
 Non-metropolitan 376 (14.0) 61 (15.5)
Born in the United States 0.15 ([1, 49] .70)
 Yes 2433 (85.7) 327 (84.7)
 No 383 (14.3) 58 (15.3)
Health Insurance 0.17 ([1, 49] .68)
 Yes 2719 (91.6) 370 (92.8)
 No 138 (8.4) 19 (7.2)
General Health 0.08 ([1, 49] .77)
 Excellent/Very good/Good 2343 (83.1) 319 (82.1)
 Fair/ Poor 517 (16.9) 68 (17.9)
Diabetes 0.96 ([1, 49] .33)
 Yes 582 (17.1) 79 (20.6)
 No 2243 (82.9) 303 (79.4)
Hypertension 0.15 ([1, 49] .70)
 Yes 1286 (37.5) 174 (39.0)
 No 1540 (62.5) 209 (61.0)
Heart Condition 0.16 ([1, 49] .69)
 Yes 295 (7.8) 30 (8.7)
 No 2541 (92.2) 357 (91.3)
Lung Disease 0.81 ([1, 49] .37)
 Yes 376 (11.2) 52 (13.4)
 No 2456 (88.8) 333 (86.6)
Arthritis 5.85 ([1, 49] .02)
 Yes 873 (22.3) 135 (29.8)
 No 1962 (77.7) 251 (70.2)
Depression / Anxiety 2.98 ([1, 49] .09)
 Yes 620 (22.4) 110 (29.2)
 No 2211 (77.6) 273 (70.8)
Distress3 2.02 (0.10) 2.46 (0.30) 1.80 ([3284] .07)
Someone for Emotional Support 1.31 ([1, 49] .26)
 Yes 2503 (87.5) 322 (84.6)
 No 348 (12.5) 64 (15.4)
Someone for Practical Support 1.99 ([1, 49] .17)
 Yes 2269 (82.6) 290 (78.3)
 No 579 (17.4) 95 (21.7)
Physical Activity Days Per Week 0.43 ([1, 49] .52)
 0 801 (25.4) 104 (27.9)
 ≥1 2038 (74.6) 280 (72.1)
Smoking History 2.56 ([1, 49] .12)
 <100 cigarettes 1755 (62.7) 230 (55.6)
 ≥100 cigarettes 1120 (37.3) 159 (44.4)
Healthcare Utilization Outcomes
Time Since Routine Check-up4 0.35 ([2, 49] .71)
 Within past year 2124 (70.0) 296 (69.7)
 1–2 years ago 381 (15.9) 49 (14.0)
 ≥3 years ago 284 (14.1) 34 (16.3)
Number of Health Care Visits in Past Year (Excluding ER) 0.62 ([6, 49] .60)
 None 412 (17.0) 50 (19.2)
 1–2 times 1024 (40.2) 135 (35.1)
 3–4 times 794 (23.6) 114 (23.3)
 ≥5 times 622 (19.3) 88 (22.4)
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Note. Columns present weighted percentages (w%) or means and standard deviations. Difference test compares Non-caregivers and Caregivers.

1

“Not Employed” comprises positive responses to: unemployed, homemaker, student, retired, disabled, and other.

2

“Partnered” comprises responses to: married, living as married; “Not partnered” comprises responses to: divorced, widowed, separated, single.

3

Patient Health Questionnaire-4 sum score.

4

Responses for “Never” and “Do Not Know” were removed due to low frequency (responses ≤ 2%) for both caregivers and non-caregivers.

Aim 1: Caregiver Status and Time Since Routine Check-Up

There were no differences between caregivers’ and non-caregivers’ reported time since their last routine check-up in univariate analyses (p=.71, Table 1) or in multivariate analyses controlling for sociodemographic and health/wellness covariates (F[2,49]=1.75, p=.19, Table 2 for Odds Ratios). For categorical predictors, an odds ratio greater than 1 indicates individuals endorsing the reference category are more likely to report having a checkup within the past year relative to the alternative timeframe (i.e., 1–2 or >3 years). For continuous predictors, an odds ratio greater than 1 indicates that as predictor score increases, likelihood that the caregiver reported being seen for their last check-up within the alternative timeframe (i.e., 1–2 or >3 years) relative to the past year also increases. Among covariates, higher likelihood of reporting longer time since last check-up was associated with male gender, being born in the U.S., not having health insurance, not having hypertension, and not having emotional support.

Table 2.

Multinomial Logistic Regression Predicting Healthcare Utilization

Time Since Routine Checkup Number of Healthcare Visits in Past Year
1–2 years ago vs. Past year ≥3 years ago vs. Past year 3–4 times vs. 1–2 times ≥5 times vs. 1–2 times None vs. 1–2 times
OR [95% CI] OR [95% CI] OR [95% CI] OR [95% CI] OR [95% CI]
Age 0.99 [0.98, 1.00] 0.98 [0.96, 1.00] 1.01 [1.00, 1.03] 1.00 [0.98, 1.01] 1.00 [0.99, 1.02]
Gender (Male) 0.92 [0.60, 1.43] 0.49 [0.28, 0.85] 1.40 [1.02, 1.92] 1.30 [0.87, 1.94] 0.62 [0.39, 1.00]
Occupational Status (Not Employed) 1.41 [0.91, 2.20] 1.10 [0.62, 1.95] 0.86 [0.59, 1.26] 0.68 [0.42, 1.11] 0.93 [0.57, 1.51]
Marital Status (Partnered) 0.96 [0.63, 1.48] 1.78 [1.16, 2.74] 1.05 [0.76, 1.46] 1.00 [0.68, 1.47] 1.58 [1.06, 2.36]
Education (Vocational or more) 1.32 [0.83, 2.10] 1.01 [0.57, 1.80] 0.99 [0.63, 1.56] 0.77 [0.48, 1.26] 1.22 [0.74, 2.03]
Rurality (Non-metropolitan) 0.82 [0.47, 1.44] 0.84 [0.38, 1.85] 1.33 [0.87, 2.02] 1.91 [0.72, 1.97] 0.90 [0.52, 1.55]
Born in the U.S. (Yes) 0.58 [0.35, 0.97] 0.38 [0.18, 0.80] 0.94 [0.53, 1.66] 0.55 [0.27, 1.09] 1.10 [0.60, 1.99]
Health Insurance (Yes) 1.58 [0.92, 2.74] 6.50 [2.90, 14.55] 0.79 [0.30, 2.11] 0.26 [0.05, 1.46] 3.58 [1.75, 7.34]
General Health (Fair/poor) 1.34 [0.69, 2.68] 0.82 [0.41, 1.66] 0.83 [0.48, 1.44] 0.34 [0.18, 0.64] 0.98 [0.52, 1.87]
Diabetes (Yes) 1.01 [0.62, 1.65] 1.21 [0.44, 3.29] 0.73 [0.45, 1.21] 0.64 [0.37, 1.11] 1.38 [0.78, 2.44]
Hypertension (Yes) 1.80 [1.10, 2.94] 3.85 [2.24, 6.62] 0.92 [0.63, 1.35] 1.01 [0.74, 1.37] 2.35 [1.47, 3.75]
Heart Condition (Yes) 1.28 [0.54, 3.06] 0.88 [0.20, 3.85] 1.00 [0.57, 1.77] 0.84 [0.43, 1.62] 1.68 [0.75, 3.76]
Lung Disease (Yes) 0.75 [0.43, 1.33] 1.13 [0.49, 2.61] 0.94 [0.53, 1.70] 0.67 [0.37, 1.20] 1.06 [0.41, 2.72]
Arthritis (Yes) 1.41 [0.88, 2.25] 1.65 [0.67, 4.07] 0.83 [0.56, 1.23] 0.48 [0.32, 0.72] 1.41 [0.77, 2.57]
Depression /Anxiety (Yes) 1.07 [0.56, 2.04] 1.23 [0.60, 2.50] 0.57 [0.39, 0.81] 0.44 [0.31, 0.64] 1.10 [0.51, 2.36]
Distress 1.05 [0.97, 1.13] 0.96 [0.87, 1.06] 1.00 [0.91, 1.10] 0.99 [0.90, 1.09] 1.00 [0.91, 1.09]
Emotional Support (Yes) 1.10 [0.54, 2.26] 2.48 [1.29, 4.77] 0.83 [0.47, 1.50] 0.49 [0.19, 1.29] 1.73 [0.98, 3.05]
Practical Support (Yes) 0.85 [0.55, 1.32] 1.03 [0.56, 1.89] 0.83 [0.53, 1.31] 0.73 [0.48, 1.13] 1.16 [0.70, 1.90]
Physical Activity (No days) 0.75 [0.49, 1.14] 1.17 [0.68, 2.00] 1.06 [0.71, 1.58] 0.84 [0.53, 1.33] 0.67 [0.44, 1.01]
Smoking History (<100 cigarettes) 0.78 [0.54, 1.14] 1.08 [0.75, 1.56] 1.21 [0.90, 1.63] 1.54 [1.12, 2.10] 0.97 [0.64, 1.47]
Caregiver Status (No) 0.87 [0.51, 1.47] 1.72 [0.85, 3.49] 0.99 [0.65, 1.52] 1.18 [0.75, 1.83] 1.25 [0.71, 2.19]
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Note. OR: Odds Ratio; CI: Confidence Interval; bolding indicates significant (p<.05) ORs.

Aim 2: Caregiver Status and Number of Health Care Visits

There were no differences between caregivers’ and non-caregivers’ number of reported healthcare visits in the past year in univariate analyses (p=.60, Table 1) or in multivariate analyses controlling for sociodemographic and health/wellness covariates (F[3,49]=0.40, p=.75, Table 2 for Odds Ratios). For categorical predictors, an odds ratio greater than 1 indicates individuals endorsing the reference category are more likely to report 1–2 healthcare visits in the past year relative to the alternative number of healthcare visits (i.e., 3–4, ≥5, none). For continuous predictors, an odds ratio greater than 1 indicates that as predictor score increases, likelihood that the caregiver reported the alternative number of healthcare visits (i.e., 3–4, ≥5, none) relative to 1–2 times also increases. Among covariates, higher likelihood of reporting more healthcare visits during the past year was associated with older age, female gender, poorer general health, having arthritis, having anxiety and/or depression, and having a smoking history. Higher likelihood of reporting no healthcare visits during the past year was associated with not being partnered, not having health insurance, and not having hypertension.

Aim 3: Caregiving Characteristics and Healthcare Utilization

Caregivers’ healthcare utilization was not related to caregiving burden factors including relationship to care recipient (ps>.14), hours spent caregiving per week (ps>.63), or number of care recipient conditions (ps>.64, Table 3).

Table 3.

Caregiving Factors Related to Caregivers’ Healthcare Utilization

Time Since Routine Checkup Number of Healthcare Visits in Past Year
Past Year n(w%) 1–2 Years n(w%) ≥3 Years n(w%) F ([dfn,dfd] p) 1–2 Times n(w%) 3–4 Times n(w%) ≥5 Times n(w%) None F ([dfn,dfd] p)
Relationship to Care Recipient 1.13 ([6, 49] .36) 1.59 ([9, 49] .14)
Other person only 56 (68.2) 14 (18.9) 9 (13.0) 19 (17.1) 29 (26.6) 22 (40.2) 12 (16.1)
Multiple recipients 25 (75.0) 3 (17.4) 2 (7.6) 9 (37.2) 9 (19.9) 7 (17.9) 7 (25.0)
Parent only 118 (61.5) 19 (14.4) 15 (24.1) 63 (36.1) 40 (21.1) 32 (17.9) 20 (24.9)
Spouse only 97 (80.7) 13 (9.9) 8 (9.4) 44 (43.2) 36 (25.9) 27 (20.5) 11 (10.4)
Hours Spent Caregiving Per Week 0.57 ([4, 49] .68) 0.72 ([6, 49] .63)
Less than 5 103 (74.9) 17 (11.8) 11 (13.3) 44 (34.4) 42 (25.9) 29 (18.5) 20 (21.3)
5 to less than 35 112 (63.6) 21 (17.0) 11 (19.4) 56 (36.7) 45 (24.2) 31 (20.0) 13 (19.1)
≥35 or more 275 (70.4) 47 (13.8) 31 (15.8) 24 (32.1) 20 (19.6) 24 (34.1) 13 (14.1)
Care Recipient Conditions 0.22 ([2, 49] .80) 0.56 ([3, 49] .64)
Single condition 100 (72.9) 18 (13.5) 11 (13.5) 42 (36.1) 43 (25.4) 24 (18.3) 24 (20.3)
Multiple conditions 184 (68.7) 28 (13.2) 21 (18.1) 87 (35.0) 64 (21.8) 62 (25.6) 23 (17.6)
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Note. Columns present weighted percentages.

DISCUSSION

This analysis of a large, nationally-representative survey found no differences in the time since last routine check-up or in the total number of healthcare appointments during the last year between informal caregivers and non-caregivers. Healthcare utilization also did not differ within caregivers by factors potentially associated with caregiving burden. These nationally-representative estimates suggest that over two-thirds of both caregivers and non-caregivers had their last routine check-up in the past year, and over one-third had one or two appointments in the past year. These figures contrast with the roughly one-sixth of the population having their last check-up three or more years ago and no healthcare visits in the past year.

Findings that recency and frequency of non-emergency healthcare did not differ between caregivers and non-caregivers fit with most prior studies examining this research question (Baumgarten et al., 1997; Bigatti & Cronan, 2002; Burton et al., 1997; George & Gwyther, 1986; Kiecolt-Glaser et al., 1987). Caregivers in the current study did, however, report a higher prevalence of arthritis relative to non-caregivers, consistent with findings from other surveys (Ji et al., 2012; Kim et al., 2015), suggesting these caregivers may benefit from additional medical care. Moreover, in one study, about one in five caregivers reported that their caregiving responsibilities caused them to delay and/or forego medical care (Mazanec, Daly, Douglas, & Lipson, 2011). As such, it remains unclear whether caregivers may benefit from increased access to healthcare relative to standard care, both to help manage current comorbidities as well as mitigate the development of additional comorbidities.

Prior literature has suggested a “healthy caregiver effect,” or that healthier individuals may be more prone to choose to take on caregiving compared to less healthier individuals (Fredman et al., 2009; Kaschowitz & Brandt, 2017; Mccann et al., 2004; Zwart et al., 2017). To that end, one possibility for the pattern of no differences in healthcare utilization between the caregiver and non-caregiver samples analyzed here may be that the caregiver sample was already more engaged in their own healthcare so impacts of the physical and time demands of caregiving on healthcare use were not detectable. Support for this interpretation is limited, however, given that caregivers were more likely to have received a diagnosis of arthritis and depression or anxiety and report greater overall distress relative to non-caregivers, suggesting the caregivers in this analysis were not substantively healthier individuals overall. The HINTS survey did not assess whether the caregiver lived with the care recipient, or the caregivers’ perceived agency in taking on the caregiving role; future research should assess these factors and their relation to caregivers’ health and healthcare utilization across the caregiving trajectory.

There were also no differences in healthcare utilization within caregivers according to approximate measures of caregiving burden, including relationship to care recipient, hours spent caregiving, or whether the care recipient had multiple health conditions. These results are at odds with findings from a large survey conducted by Bremer and colleagues across several European countries (Bremer et al., 2015), which demonstrated that more time spent caregiving was associated with increased healthcare utilization among informal caregivers for individuals with dementia. Importantly, however, Bremer and colleagues’ findings also differed substantially across countries, likely due to regional differences in cultural expectations and public policy (Calvó-Perxas et al., 2018). Future examination of the extent to which regional differences in healthcare systems, work-leave policies, politics, and culture affect caregivers’ healthcare utilization and access may highlight important discrepancies in caregivers’ experiences in the U.S. healthcare climate as well.

Regardless, the promising results that caregivers appear to sustain typical engagement with primary healthcare suggest that dissemination of caregiving-related resources via primary care may be an effective way to reach caregivers. Prior studies of primary-care based interventions support the potential effectiveness of this strategy to improve caregiver well-being, particularly among the most distressed caregivers (Mitchell, Girgis, Jiwa, Sibbritt, & Burridge, 2010; Mitchell et al., 2013). Identifying effective models of care delivery for caregivers is important, not only to improve caregivers’ own well-being, but also to that of patients and, ultimately, to key healthcare system goals (Kent et al., 2016; Longacre, Ridge, Burtness, Galloway, & Fang, 2012).

Strengths and Limitations

Strengths of this study include the use of a large, nationally-representative dataset with the ability to control for a broad range of potential confounders; however, the HINTS survey was not designed to specifically address research questions for the current study. Limitations arising from this include the limited assessment of the caregiving experience – for instance, the duration of caregiving was not assessed, which may be pertinent to understanding whether caregiving could have affected time since last check-up. It should be noted, however, that only two caregivers reported caring for a person with an acute condition (e.g., broken bone), while more chronic conditions of dementia, cancer, and aging-related issues were most frequently endorsed. Another limitation of the caregiving assessment is that individuals self-identified as “providing care for or making healthcare decisions for” another close individual. As such, the caregiving sample may comprise a wide range of levels of caregiving responsibilities – from remote healthcare proxies to individuals living with, and providing daily care for, the care recipient. However, our inclusion of caregiving burden questions helps to differentiate effects between these potentially discrepant caregiving groups. Moreover, there was no measurement of type of healthcare visits utilized – prior studies indicate that although overall healthcare use may not differ between caregivers and non-caregivers, types of appointments may differ, with caregivers using more mental healthcare services relative to non-caregivers (Baumgarten et al., 1997; Cochrane et al., 1997).

Conclusion

Overall, there was no evidence for differences in healthcare utilization between informal caregivers and non-caregivers who responded to a national health survey, controlling for a wide variety of potential confounding factors. Future research should examine whether caregivers are accessing adequate mental and physical healthcare to manage their overall health needs, and whether additional preventive care would help mitigate the known health disparities between caregivers and non-caregivers. Given that caregivers appear to sustain routine contact with primary care, disseminating caregiver resources via primary care may represent an effective way to reach caregivers.

Acknowledgements:

We gratefully acknowledge the support of Fabian Camacho, M.S., M.A., for his help conducting power analyses for this paper.

FUNDING

This work was supported by the National Institutes of Health, National Cancer Institute (T32 CA009461 [PI: Jamie Ostroff] and Cancer Center Support Grant P30 CA008748 [PI: Craig Thompson]).

Footnotes

Conflicts of interest: None reported

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