Abstract
Objectives. To examine associations between caregiving mental or behavioral health outcomes among emerging US adults, defined as persons aged 18 to 25 years.
Methods. The study sample included emerging adult respondents to the 2015–2017 Behavioral Risk Factor Surveillance System’s caregiving module. Exposures were caregiver (n = 3087), expectant caregiver (n = 2303), and noncaregiver (n = 12 216) status. Expectant caregivers were defined as persons not currently providing care but anticipating doing so within the next 2 years. Outcomes included frequent mental distress (FMD), drinking (binge or heavy), and current smoking (cigarette or e-cigarette use). We used robust Poisson regression to calculate adjusted prevalence ratios (APRs) and corresponding 95% confidence intervals (CIs). We adjusted all models for income.
Results. Caregivers had a similar prevalence of FMD when compared with both expectant caregivers (APR = 1.67; 95% CI = 1.28, 2.17) and noncaregivers (APR = 1.50; 95% CI = 1.23, 1.82). Caregivers had a higher prevalence of current cigarette smoking compared with noncaregivers (APR = 1.44; 95% CI = 1.21, 1.71).
Conclusions. Among emerging adults, providing care is associated with poorer mental health. Point estimates looking at FMD were higher when we compared caregivers with expectant caregivers, suggesting a difference in exchangeability between comparison groups.
Public Health Implications. This study highlights the importance of including emerging adults in caregiving research.
In 2015, approximately 43.5 million US adults provided informal care in the form of routine care or assistance with activities of daily living (ADLs; e.g., bathing, dressing, or feeding) or instrumental activities of daily living (IADLs; e.g., managing finances, housekeeping, or cooking) to family or friends who were ill, injured, or disabled. Providing informal care has been associated with poor mental health.1–3 Limited evidence suggests that this association may be stronger among younger caregivers compared with older caregivers,4–6 though interpreting existing findings comparing age groups is difficult because of inconsistently defined age categories for “younger” caregivers, the upper bound of which has been defined as high as 64 years.4
Emerging adults, those aged 18 to 25 years, have largely been excluded from caregiving research but account for an estimated 12% to 18% of informal caregivers in the United States.7 Emerging adults may be uniquely susceptible to the stresses of caregiving, as this life stage is a critical period of neurodevelopment when connections between key structures involved in mental health, such as the amygdala and prefrontal cortex, are still forming.8 Emerging adulthood is also characterized by increased independence, development of long-term relationships, and decision-making around education and career goals.9 Disruption to these developmental milestones could have long-term adverse mental health impacts. Projected shortages of middle-aged adult informal caregivers (ages 45–65 years)10 suggests that emerging adults may be increasingly relied upon for caregiving activities, indicating that their unique needs should be considered in public health planning. The behavioral health impact of caregiving at this age is not well understood and is of particular interest because of the unique vulnerabilities of individuals at this life stage.5,6,9
The few studies examining health outcomes among emerging adult caregivers have found an association between caregiving and poor mental health, specifically anxiety and depression.5,6 Previous research has found that emerging adults may use avoidance or distraction strategies, such as drinking and smoking, to cope with feelings of anxiety and depression.11 However, these studies were limited by small, nonrepresentative samples5,11 or were conducted outside the United States and may not generalize to emerging adults within the United States.6,11 Nationally representative studies of emerging adult caregivers in the United States are needed to understand the health impacts of caregiving for this segment of the population.
Further complicating caregiving research, existing studies frequently compare caregivers with all noncaregivers,1,4–6 likely including as noncaregivers individuals who are unable or unwilling to provide informal care. Those who would never serve as informal caregivers may differ in meaningful ways from those who would, possibly confounding any identified associations. Defining a more exchangeable comparison group, expectant caregivers, composed only of persons who anticipate providing informal care in the future, would reduce unmeasured confounding and improve the public health benefit of caregiving research.
In this study, we hypothesized that among emerging adults, caregivers are at greater risk for poor mental health and unhealthy coping mechanisms. To evaluate this, we examined associations between caregiving and frequent mental distress (FMD) as well as risky health behaviors (binge drinking, heavy drinking, tobacco cigarette use, and e-cigarette use). As a secondary aim, we examined the associations between caregiving and FMD by type of care (personal or household) and weekly hours of care provided. Characterizing the behavioral health of emerging adult caregivers is timely and necessary.
METHODS
The Behavioral Risk Factor Surveillance System (BRFSS) conducts more than 400 000 landline and cellular telephone surveys of noninstitutionalized adults each year across the United States, including the territories of Puerto Rico and Guam.12 Annual cross-sectional BRFSS surveys consist of core questions and optional modules regarding health behaviors and conditions, and health care service use. BRFSS data are representative of the general US population by age, gender, and race.13 In the current study, we used BRFSS data from US states and territories that implemented the caregiving module between 2015 and 2017. The caregiving module was implemented by 23 states and territories in 2015, 21 in 2016, and 12 in 2017, with some states implementing the module during multiple years.
Study Population
The study sample consisted of emerging adults (aged 18–25 years) who participated in the BRFSS caregiving module between 2015 and 2017. Because of irregularities in California responses, whereby expectant caregivers were also classified as caregivers, we removed all Californian respondents from analyses (n = 355). Figure 1 illustrates the identification process for the analytic sample used in the current study. The study sample included 3087 caregivers, 2303 expectant caregivers, and 12 216 noncaregivers. E-cigarette data were only available for years 2016 and 2017; thus, analyses of e-cigarette data were restricted to these 2 years. The study sample for e-cigarette use included 1598 caregivers, 1256 expectant caregivers, and 7241 noncaregivers.
FIGURE 1—
Identification of Emerging Adult Caregivers, Expectant Caregivers, and Noncaregivers From the Behavioral Risk Factor Surveillance System: United States, 2015–2017
Note. Shaded boxes indicate responses excluded from this study.
aFinal comparison groups.
Exposure
Caregivers were defined as persons who answered “yes” to the question “During the past 30 days, did you provide regular care or assistance to a friend or family member who has a health problem or disability?”12 Persons whose care recipient died within the past 30 days were excluded from analyses (n = 12). Expectant caregivers were persons who answered “no” to the initial caregiving question but “yes” to the following question: “In the next 2 years, do you expect to provide care or assistance to a friend or family member who has a health problem or disability?” Noncaregivers were persons who answered “no” to both questions.
Caregivers were asked about the type of care provided and weekly hours of care provided. Personal care was assessed by asking “In the past 30 days, did you provide care for this person by managing personal care such as giving medications, feeding, dressing, or bathing?” Household care was assessed by asking whether respondents “managed household tasks such as cleaning, managing money, or preparing meals” within the same timeframe. BRFSS does not capture type of care with the granularity necessary to specifically categorize IADLs and ADLs, as generally defined in the caregiving literature. In this study, we used personal and household care as proxies for ADLs and IADLs, respectively. We categorized type of care provided as
neither—for respondents answering “no” to both questions,
household only—for respondents answering “no” to the first question and “yes” to the second,
personal only—for respondents answering “yes” to the first question and “no” to the second, or
both—for respondents answering “yes” to both questions.
Weekly hours of care provided was assessed with the question “In an average week, how many hours of do you provide care or assistance?” Response options to this question were
any care up to 8 hours,
between 9 and 19 hours,
between 20 and 39 hours,
40 or more hours,
don’t know/not sure.
We treated respondents answering “don’t know/not sure” as missing.
Outcomes
Our primary outcome of interest was FMD. Respondents were asked, “thinking about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?” Respondents who reported 14 or more days of poor mental health were classified as experiencing FMD. This definition of FMD has been used in previous studies and is considered a valid and reliable measure of a person’s mental health.4,14,15
Our secondary outcomes of interest were binge drinking, heavy drinking, cigarette smoking, and e-cigarette smoking—health behaviors that may be proxies for avoidant or distraction coping mechanisms.16 To assess drinking behaviors, the BRFSS survey asks questions regarding frequency and volume of alcohol consumption. From these questions, we defined binge drinkers as those who consumed 5 or more drinks on 1 occasion for men, and 4 or more drinks on 1 occasion for women. We defined heavy drinking as consuming more than 14 drinks per week for men, and more than 7 drinks per week for women. These definitions are consistent with Centers for Disease Control and Prevention (CDC) classifications of binge drinking and heavy drinking.17 Similarly, the BRFSS includes questions regarding history and frequency of cigarette and e-cigarette use. We defined current cigarette smokers as those who ever smoked at least 100 cigarettes and currently smoked cigarettes at least some days per week. We defined e-cigarette smokers as persons currently smoking e-cigarettes at least some days per week.
Potential Confounders
On the basis of previous literature, we identified 7 covariates as potential confounders: age, gender (male or female), current insurance status (insured or uninsured), race/ethnicity (Black, Hispanic, multiracial, White, or other, which included Asian, Native American, and Pacific Islander), highest level of educational attainment (< high school, high-school diploma or general educational development credential, some college, or college degree), yearly household income ($0–$14 999, $15 000–$24 999, $25 000–$34 999, $35 000–$49 999, or ≥ $50 000), current employment status (unable to work, employed, homemaker, retired, student, or unemployed), and respondent’s state of residence. For highest level of educational attainment, the category of “< high school” collapses respondents who answered, “never attended school or only kindergarten,” “grades 1 through 8,” and “grades 9 through 11.” All other categories for highest level of educational attainment reflect BRFSS response options. To examine confounding, each covariate was included separately in the primary analytic model. We only included potential confounders that resulted in at least a 10% change in the adjusted point estimate compared with the crude estimate in the final model. Only household income met this criterion.
Statistical Analyses
We adjusted data by using CDC-provided weights to account for the sampling methodology that included oversampling of underrepresented groups, as well as nonresponse. We used Poisson regression with robust standard errors to calculate adjusted prevalence ratios (APRs) and 95% confidence intervals (CIs). We fit separate complete-case models by using expectant caregivers and noncaregivers as the comparison group. Primary analyses assessed associations between caregiving status and FMD, as well as drinking and smoking outcomes. Secondary analyses examined the association between type of care and hours of care provided and FMD. In addition, because BRFSS questions regarding FMD and drinking each asked about respondents’ experiences within the past 30 days, we performed sensitivity analyses on all models by removing caregivers who indicated providing care for fewer than 30 days. We assessed goodness of fit for all models by using a deviance test. We conducted all analyses in R Programming Language18 using base R version 3.6.1 within RStudio 1.1.456.19
RESULTS
After weighting, nearly 1 in 5 (18.1%) emerging US adults were functioning as caregivers, and 13.9% were expecting to become caregivers within the next 2 years (Table 1). Male and Hispanic respondents comprised a greater proportion of expectant caregivers compared with caregivers and noncaregivers. Caregivers were less likely to be students than were expectant caregivers or noncaregivers, while noncaregivers were least likely to be unemployed. Among the 3 exposure groups, noncaregivers were the most likely to report a yearly household income of $50 000 or more.
TABLE 1—
Characteristics of Study Population by Caregiver Status: Behavioral Risk Factor Surveillance System, United States, 2015–2017
| Current Caregivers (n = 3087), No. (Weighted %) | Expectant Caregivers (n = 2303), No. (Weighted %) | Noncaregivers (n = 12 216), No. (Weighted %) | |
| Age, y | |||
| 18–20 | 1967 (59) | 1393 (59) | 8101 (61) |
| 21–25 | 1120 (41) | 910 (41) | 4115 (39) |
| Gender | |||
| Male | 1501 (50) | 1227 (58) | 6507 (51) |
| Female | 1582 (50) | 1075 (42) | 5705 (49) |
| Race/ethnicitya | |||
| Black | 374 (16) | 265 (16) | 999 (13) |
| Hispanic | 437 (17) | 425 (25) | 1854 (20) |
| Other | 152 (3) | 134 (3) | 506 (2) |
| Multiracial | 247 (6) | 227 (9) | 931 (8) |
| White | 1828 (58) | 1224 (48) | 7791 (57) |
| Highest level of education completedb | |||
| < high school | 249 (12) | 234 (16) | 726 (11) |
| High school or GED | 1160 (11) | 976 (10) | 4338 (15) |
| Some college | 1180 (37) | 759 (43) | 4615 (34) |
| College grad | 492 (39) | 331 (32) | 2513 (40) |
| Employment statusc | |||
| Unable to work | 72 (2) | 48 (3) | 184 (2) |
| Employed | 1745 (54) | 1263 (52) | 7062 (53) |
| Homemaker | 86 (2) | 55 (2) | 322 (3) |
| Student | 793 (29) | 689 (32) | 3613 (35) |
| Unemployed | 358 (12) | 215 (11) | 917 (8) |
| Annual household income,d $ | |||
| 0–14 999 | 322 (13) | 269 (15) | 1245 (13) |
| 15 000–24 999 | 610 (25) | 460 (25) | 1916 (20) |
| 25 000–34 999 | 323 (13) | 230 (14) | 1168 (11) |
| 35 000–49 999 | 330 (14) | 256 (15) | 1452 (14) |
| ≥ 50 000 | 731 (34) | 476 (31) | 3465 (42) |
| Insurance status | |||
| Insured | 2580 (80) | 1931 (79) | 10 383 (84) |
| Uninsured | 453 (19) | 406 (20) | 1632 (15) |
Note. GED = general educational development certification. Missing data for gender: n = 9; education: n = 33; employment: n = 165; income: n = 4353; and insurance: n = 301.
Race/ethnicity categories are mutually exclusive. Race = “other” includes respondents identifying as American Indian/Alaska Native, Asian, and Native Hawaiian/Pacific Islander.
Category of “< high school” includes “never attended school or kindergarten,” “grades K–8,” and “grades 9–11.” All other categories reflect Behavioral Risk Factor Surveillance System response options.
Employment categories reflect the response options available in the Behavioral Risk Factor Surveillance System survey.
Annual household income categories reflect response options available in the Behavioral Risk Factor Surveillance System survey.
Among caregivers, 20.8% experienced FMD, compared with 13.5% and 12.8% among expectant caregivers and noncaregivers, respectively (Table 2). After we adjusted for household income, the weighted prevalence of FMD among caregivers was 67% higher compared with expectant caregivers (APR = 1.67; 95% CI = 1.28, 2.17) and 50% higher compared with noncaregivers (APR = 1.50; 95% CI = 1.23, 1.82). Cigarette smoking was more prevalent among caregivers compared with noncaregivers (APR = 1.44; 95% CI = 1.21, 1.71), but did not differ compared with expectant caregivers. There were no significant associations between caregiving and drinking behaviors or e-cigarette use (Table 2).
TABLE 2—
Adjusted Prevalence Ratios for Behavioral Health Outcomes Comparing Caregivers to Expectant Caregivers and Noncaregivers: Behavioral Risk Factor Surveillance System Survey, United States, 2015–2017
| Outcome Prevalence by Caregiving Exposure Groups,a % |
|||||
| Behavioral Health Outcomes | Caregiver (n = 3087) | Expectant Caregiver (n = 2303) | Noncaregiver (n = 12 216) | Caregivers Compared With Expectant Caregivers, APR (95% CI) | Caregivers Compared With Noncaregivers, APR (95% CI) |
| Frequent mental distress | 20.8 | 13.5 | 12.8 | 1.67 (1.28, 2.17) | 1.50 (1.23, 1.82) |
| Binge drinking | 26.2 | 22.7 | 25.3 | 1.15 (0.93, 1.44) | 1.11 (0.96, 1.28) |
| Heavy drinking | 6.9 | 6.8 | 6.2 | 1.04 (0.66, 1.63) | 1.26 (0.95, 1.67) |
| Cigarette smoking | 20.2 | 17.6 | 12.8 | 1.02 (0.78, 1.32) | 1.44 (1.21, 1.71) |
| E-cigarette smokingb | 10.7 | 8.8 | 9.0 | 0.97 (0.60, 1.55) | 0.97 (0.69, 1.35) |
Note. APR = adjusted prevalence ratio; CI = confidence interval. All adjusted models controlled for income. Among caregivers, missing data for frequent mental distress: n = 53; for binge drinking: n = 71; for heavy drinking: n = 96; for cigarette smoking: n = 10; and for e-cigarette smoking: n = 0. Among expectant caregivers, missing data for frequent mental distress: n = 41; for binge drinking: n = 43; for heavy drinking: n = 62; for cigarette smoking: n = 10; and for e-cigarette smoking: n = 2. Among noncaregivers, missing data for frequent mental distress: n = 128; for binge drinking: n = 222; for heavy drinking: n = 283; for cigarette smoking: n = 27; and for e-cigarette smoking: n = 8.
Within-group weighted percentages of behavioral health outcomes by exposure group presented.
Data only available for years 2016 and 2017 (caregiver: n = 1598; expectant caregiver: n = 1256; and noncaregiver: n = 7241).
The association between caregiving and FMD differed by type of care provided. Compared with expectant caregivers, caregivers who reported managing solely personal tasks (APR = 1.97; 95% CI = 1.20, 3.24) or both personal and household tasks (APR = 1.95; 95% CI = 1.43, 2.65) had a significantly higher prevalence of FMD; the association was not significant for caregivers providing household tasks only. A similar pattern held when we compared caregivers with noncaregivers as was seen when comparing to expectant caregivers (Table 3). In addition, we observed a nonlinear pattern between FMD and hours of care provided. FMD was more prevalent among caregivers providing 8 or fewer hours, 9 to 19 hours, and 40 or more hours when compared with either reference group, but not among those providing 20 to 39 hours of care per week. Deviance goodness-of-fit tests performed on all primary and secondary models did not indicate any evidence of poor fit.
TABLE 3—
Adjusted Prevalence Ratios of Frequent Mental Distress, Disaggregating Caregivers by Type of Care and Weekly Hours of Care Provided, Comparing Caregivers to Expectant Caregivers and Noncaregivers: Behavioral Risk Factor Surveillance System Survey, United States, 2015–2017
| Frequent Mental Distress Prevalence by Caregiving Exposure Groupsa |
|||||
| Subcategories of Care | Caregiver (n = 3087) | Expectant Caregiver (n = 2303) | Noncaregiver (n = 12 216) | Caregivers Compared With Expectant Caregivers, APR (95% CI) | Caregivers Compared With Noncaregivers, APR (95% CI) |
| Totalb | 20.8 | 13.5 | 12.8 | 1.67 (1.28, 2.17) | 1.50 (1.23, 1.82) |
| Type of care provided | |||||
| Neither household nor personal | 11.0 | . . . | . . . | 1.15 (0.64, 2.06) | 1.02 (0.59, 1.77) |
| Household only | 18.5 | . . . | . . . | 1.35 (0.96, 1.88) | 1.20 (0.90, 1.60) |
| Personal only | 20.6 | . . . | . . . | 1.97 (1.20, 3.24) | 1.81 (1.13, 2.91) |
| Both household and personal | 24.6 | . . . | . . . | 1.95 (1.43, 2.65) | 1.76 (1.36, 2.28) |
| Weekly hours of care provided | |||||
| ≤ 8 | 18.6 | . . . | . . . | 1.53 (1.12, 2.08) | 1.37 (1.06, 1.77) |
| 9–19 | 24.7 | . . . | . . . | 2.23 (1.54, 3.22) | 1.97 (1.42, 2.75) |
| 20–39 | 16.2 | . . . | . . . | 1.31 (0.67, 2.54) | 1.18 (0.64, 2.20) |
| ≥ 40 | 30.9 | . . . | . . . | 2.25 (1.53, 3.32) | 2.06 (1.46, 2.91) |
Note. APR = adjusted prevalence ratio; CI = confidence interval; FMD = frequent mental distress. All models adjusted for income. Missing data for FMD among caregivers: n = 53; among expectant caregivers: n = 41, and among noncaregivers: n = 128. Missing data for type of care provided: n = 51. Missing data for weekly hours of care provided: n = 109.
Within-group weighted percentage of FMD by exposure group presented. For caregivers, weighted percentage of FMD by subcategories of care also presented.
Total within-group percentage of FMD by exposure group.
Sensitivity analyses removing caregivers who had been providing care for fewer than 30 days (n = 854) resulted in APR estimates that were similar to the primary model estimates (Appendix Tables A and B, available as supplements to the online version of this article at http://www.ajph.org). The exception was the APR for FMD among caregivers providing household care in comparison with expectant caregivers, which resulted in a 10.1% change in APR from 1.35 (95% CI = 0.96, 1.88) to 1.49 (95% CI = 1.05, 2.13).
DISCUSSION
To our knowledge, this is the first population-based study examining behavioral health outcomes among emerging adult caregivers in the United States. Our results show that caregiving among emerging adults is associated with higher FMD, consistent with the limited previous literature5–7 and the general literature on caregiving.1–4 When we examined FMD by type of care and weekly hours of care provided, we found the impact of caregiving on mental health was not the same for all caregivers. Consistent with previous literature, our results suggest that caregiving that includes managing any personal care (a proxy for ADLs) has a stronger association with FMD.3,14,20 Consistent with findings by Levine et al.,7 approximately 57% of caregivers in our sample managed any personal tasks. The higher prevalence of FMD among caregivers managing any personal tasks could be attributable to the difficult nature of assisting with such intimate tasks. Alternatively, it could be attributable to the emotional strain of having a friend or family member with a disease or disability severe enough to require such care.
Results from analyses categorizing caregivers by weekly hours of care provided were unexpected. The prevalence of FMD among caregivers providing 9 to 19 hours of care and 40 or more hours of care was 123% and 125% greater, respectively, when compared with expectant caregivers, and 97% and 106% greater when compared with noncaregivers, respectively. This suggests that providing 9 to 19 and 40 or more hours of weekly care have similar impacts on mental health. There were no significant associations between providing 20 to 39 hours of care and FMD when we compared caregivers with either expectant caregivers or noncaregivers. Results indicating higher prevalence of FMD among caregivers providing any care up to 8 hours per week when compared with either expectant caregivers (53% greater) or noncaregivers (37% greater) suggests that even caregiving for minimal time poses a risk of FMD among emerging adults. Given that approximately 63% of emerging adult caregivers provided 8 or fewer hours of care per week, this finding is particularly notable.
The significantly higher prevalence of smoking among emerging adult caregivers compared with noncaregivers lends limited evidence that they are more likely to use avoidant or distraction coping strategies.11,16 However, we did not find evidence that caregiving was associated with problem or risky drinking or e-cigarette use. As binge drinking is prevalent among emerging adults in the general population,21 differences associated with caregiving may be difficult to detect. Caregivers in our study were significantly more likely to be smokers than were noncaregivers, but not compared with expectant caregivers. An explanation is that emerging adult caregivers use smoking as a distraction coping mechanism in response to the stress of caregiving, and that expectant caregivers do the same in response to a lower level of similar stress. Alternatively, emerging adults whose family members smoke may be more likely to smoke themselves, and those family members may be more likely to need care because of the negative health consequences of smoking.
Our study population characteristics appear consistent with those reported by Levine et al.7 However, demographic characteristics of this population differ notably from more recent estimates of both the general US caregiving population and caregivers aged 18 to 34 years, the most similar age group reported in national estimates.22 Half of the caregivers in our study were male, compared with only 40% of all caregivers in previous studies.22 Our study sample of caregivers aged 18 to 25 years included a much larger fraction who were White (58%) and smaller proportions who were African American (16%) or Hispanic (17%) than previous national estimates.22 These demographic differences suggest that emerging adult caregivers are a unique subset of the broader young adult caregiver category.
Our use of expectant caregivers as a comparison group was novel. We hypothesized that there may be important differences between those who expect to take on the caregiving role and those who do not. We found that APRs of frequent mental distress were similar when we compared caregivers to both expectant caregivers and noncaregivers, but point estimates were consistently higher when expectant caregivers were the reference group. It is possible that, among emerging adults, only those with good mental health would ever become caregivers, resulting in the observed trend in point estimate differences between expectant caregivers and noncaregivers. This trend suggests a difference in exchangeability between expectant caregivers and noncaregivers. Studies comparing caregivers with general noncaregivers among emerging adults may thus underestimate the impact of caregiving on mental health. Our findings contrast with those of Buyck et al.,1 who found “potential” caregivers had greater odds of depression than caregivers in all but the highest level of burden compared with noncaregivers.1 However, comparison of these results is limited by differing definitions between potential and expectant caregivers, as well as different population age ranges. The study by Buyck et al. also used categories of caregiver burden that cannot be reconstructed with BRFSS data
Strengths
The use of expectant caregivers and noncaregivers as distinct reference groups is a strength for our study. While point estimates of FMD were similar when using either reference group, the observed pattern of consistently higher estimates when using expectant caregivers as the referent implies a potential difference in the exchangeability between expectant caregivers and noncaregivers. Another strength of the present study is the utilization of nationally representative data to estimate the current emerging adult caregiver population in the United States, a necessary first step to understanding relevant risks to their health.
Limitations
The current study had several limitations. First, BRFSS does not collect information to reproduce a previously used index that combined the type of care and weekly hours of care provided.5,20 This limited our ability to compare our results to previous studies. However, results from our analyses deconstructing caregiving status by type of care and weekly hours of care suggest a nonlinear association between hours of caregiving and FMD, challenging the necessity for using traditional burden-of-care indices among this population.
Second, BRFSS does not capture whether a caregiver’s role is shared with either other informal caregivers or paid caregivers. Those who assume sole caregiving responsibility may be differentially affected compared with those who share caregiving responsibilities.
Third is the amount of missingness in the data. Because we performed complete-case analyses adjusting for income without addressing income missingness, the effective sample size was reduced. However, presuming the missingness was nondifferential, we believe the relative prevalence estimates were likely attenuated, underestimating the effect of caregiving on these outcomes.
Fourth, the prevalences of binge drinking and smoking in the study sample were lower than national estimates reported for the same age range of adults.21 These differences could be driven by underreporting attributable to social desirability bias, attenuating APRs.
Finally, because BRFSS is a cross-sectional survey, temporality between exposure and outcome cannot be established. We attempted to mitigate issues of temporality by conducting sensitivity analyses removing caregivers who had been providing care for fewer than 30 days (a period that overlaps with the BRFSS measure of FMD). However, the sensitivity analyses themselves cannot establish temporality, and it remains possible that caregiving respondents chronically experienced FMD before becoming a caregiver.
Public Health Implications
By the year 2050, an estimated 20% of the US population will be aged 65 years or older.23 Correspondingly, a shortage of informal caregivers aged 45 to 64 years is anticipated,10 poising emerging adults to fill the widening informal caregiving gap over the coming years. Results from the present study indicate that, among emerging adults, frequent mental distress was more prevalent among caregivers than among expectant caregivers or noncaregivers. Adverse mental health during emerging adulthood may disrupt the myriad biological, social, and economic transitions that characterize this stage of life, resulting in short-term and long-term impacts. The lifelong impact of providing regular, informal care during emerging adulthood is not well researched. However, given the unique vulnerabilities of emerging adults and their demonstrated increased risk of adverse mental health compared with their general noncaregiving peers, further research on the health impacts of caregiving during emerging adulthood is warranted. The necessity of informal caregiving and its public health importance is already a current area of focus24; this study highlights that emerging adults warrant particular attention.
ACKNOWLEDGMENTS
This study is partially supported by the University of Washington Center of Excellence for Maternal and Child Health through the Health Resources and Service Administration of the US Department of Health and Human Services under grant T76MC00011. Additional support comes from the University of Washington Center for the Study of Demography and Ecology through a Shanahan Endowment Fellowship, the Eunice Kennedy Shriver National Institute of Child Health and Human Development under training grant T32HD007543, and the Eunice Kennedy Shriver National Institute of Child Health and Human Development research infrastructure grant P2CHD042828.
Note. The views expressed in this publication do not necessarily reflect the official policies of the Department of Health and Human Services or the National Institutes of Health; nor does mention by trade names, commercial practices, or organizations imply endorsement by the US government.
CONFLICTS OF INTEREST
The authors have no conflicts of interest to disclose.
HUMAN PARTICIPANT PROTECTION
This study was determined not to be a human participant research and was exempted from review by the University of Washington Human Subjects Division.
Footnotes
See also Kent, p. 1720.
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