Caregiving and Obesity among Black American Adults

Abstract

Black American adults often report higher rates of obesity and caregiving compared with other racial or ethnic groups. Consequently, many Black American caregivers and care recipients are obese or have obesity-related chronic conditions (e.g., diabetes, hypertension). This study investigated associations between caregiving and obesity among Black Americans, including the role of health behaviors and chronic conditions. The sample included data from 2015 and 2017 Behavioral Risk Factor Surveillance System for non-Hispanic Black (NHB) or African American adult caregivers (n = 2,562) and noncaregivers (n = 7,027). The association between obesity (dependent variable) and caregiving status, fruit consumption, vegetable consumption, physical activity, and number of chronic conditions (independent variables) were evaluated using hierarchical binomial logistic regressions. Caregiving, being female, and chronic conditions were associated with higher odds of obesity, while physical activity was associated with lower odds of obesity. Physical activity, diet, and chronic conditions did not account for differences in obesity among caregiving and noncaregiving Black Americans. Increasing understanding of health behaviors and chronic disease burden of NHB caregivers has implications for programs aiming to improve obesity-related outcomes for caregivers and recipients. Future research should investigate multilevel factors that contribute to observed differences.

Family caregivers are essential components of the health, social, and aging services infrastructure in the United States (Neugaard et al., 2008; Reeves et al., 2012; Schulz & Czaja, 2018). There are over 40 million family caregivers in the United States, representing family members, relatives, or friends who provide support and assistance, often unpaid, to children and adults with health problems or disabilities (Edwards et al., 2017; Neugaard et al., 2008; Singer et al., 2010). The aging of the U.S. population (Eifert et al., 2016), rise in chronic disease and multimorbidity, and standardization of chronic and complex disease management in home settings have heightened the need for family caregiver support. This support includes healthcare management, assistance with personal tasks (e.g., food preparation, transportation, finances), administering prescriptions, symptoms management, and emotional support (Schulz & Czaja, 2018). Consequently, individuals who are aging, managing health conditions, or living with a disability may decrease healthcare utilization (Friedman et al., 2019) and remain living at home for a longer period of time with the support of caregivers.

Seminal work by Pearlin et al. (1990) and Schulz and Beach (1999) underscore that caregivers are at increased vulnerability for poor health outcomes (Pearlin et al., 1990; Schulz & Beach, 1999). Caregiving tasks and responsibilities may be a barrier to caregivers’ own self-care and health-promoting behaviors (Gross et al., 2003; Y. Liu et al., 2020; McGuire et al., 2010), but research findings in this area are mixed. Some studies have reported that caregivers are more likely than noncaregivers to engage in behaviors that can negatively influence health, including smoking, diets with regular consumption of soda and fast food (Hoffman et al., 2012), and poorer-quality sleep (Moon & Dilworth-Anderson, 2015). Other studies, however, have reported better health habits such as increased physical activity (McGuire et al., 2010) and cancer screenings (Son et al., 2011) correlating with caregiving status, or similar levels of physical activity between caregivers and noncaregivers (Castro et al., 2007).

Obesity—or excess adiposity (i.e., body fat)—is measured with various methods, including body mass index (BMI), waist circumference, waist-to-hip ratio, skinfold thickness, magnetic resonance imaging (or MRI), and computerized tomography (or CT; Williams et al., 2015). Several of the aforementioned studies have discussed implications of obesity given associated health behaviors but did not report any observed independent effects of obesity on behaviors (Gross et al., 2003; Hoffman et al., 2012; Moon & Dilworth-Anderson, 2015; Son et al., 2011). Of note, Y. Liu and colleagues (2020) reported a higher prevalence of obesity among caregivers, while other studies reported no association between weight and caregiving status (Castro et al., 2007; McGuire et al., 2010).

Obesity has been directly and indirectly associated with increased risk of comorbidity, reduced quality of life, and premature mortality (Jastreboff et al., 2019; Williams et al., 2015). Indeed, while it is widely known that caregivers often support individuals diagnosed with obesity-related conditions such as diabetes, heart disease, and stroke (National Alliance for Caregiving & AARP, 2020), limited research has examined contributors to obesity among caregivers themselves. Analysis of data from women in the 2009 Behavioral Risk Factor Surveillance System (BRFSS) linked caregiving with greater odds of obesity among White women but not among non-White women (Reeves et al., 2012). In a longitudinal study of caregiving and adiposity in the United Kingdom (Lacey et al., 2018), gender and employment-related differences were observed: Women who were caregivers had higher adiposity compared with women who were not caregivers, but this difference was not observed in men (adiposity was assessed via BMI, waist circumference, and percentage body fat calculated using bioelectrical impedance). However, higher adiposity was observed among male caregivers also working part-time and female caregivers working full-time compared with noncaregiving counterparts with similar levels of employment (Lacey et al., 2018). In contrast, in a longitudinal study of middle age and older adults in Germany, Hajek and König (2017) found that the onset of informal caregiving was associated with increasing BMI in men, but not women. Findings from these studies highlight a number of sociodemographic factors that may be associated with obesity among caregivers (e.g., gender, age) that warrant further investigation.

Several national studies have reported that Black Americans have higher rates of family caregiving (National Academies of Sciences, Engineering, and Medicine [NASEM], 2016; National Alliance for Caregiving & AARP, 2020; Rote et al., 2019; Rote & Moon, 2018) and obesity (Ogden et al., 2020) compared with other racial or ethnic groups. However, research at the intersection of these two issues is sparse. Strong cultural justifications for caregiving (Dilworth-Anderson et al., 2005) and increased need for support among Black Americans due to high rates of serious and chronic illnesses compared with other racial and ethnic groups (Centers for Medicare and Medicaid Services, 2012; National Center for Health Statistics, 2016) may help explain the higher prevalence of caregiving among Black Americans. Pathways leading to increased obesity among African American adults are complex (Huang et al., 2009); factors operating at different ecological levels (i.e., individual, familial, and community levels) often make weight management and engagement in health-promoting, weight-related behaviors a challenge among this population (Jackson et al., 2010). Thus, while both family caregiving and obesity are common among Black Americans, the relationship between the two remains unclear.

The purpose of this study was to examine whether caregiving status is associated with obesity among Black Americans. There were two research questions guiding this study. First, is there a difference in obesity prevalence between Black American caregivers and noncaregivers? We hypothesized that caregivers would be more likely to be obese compared with noncaregivers. Second, do health behaviors or chronic health conditions help to explain observed relationships (if any) between caregiver status and weight status? We hypothesized that lower levels of physical activity, less consumption of fruits and vegetables, and a higher number of chronic health conditions would account for variation in obesity among caregiving and noncaregiving Black Americans.

Method

Study Design and Data Source

Data for this study were drawn from the BRFSS, an ongoing system of landline and cellular telephone surveys that collect state-level data from noninstitutionalized U.S. residents, age 18 and older, regarding health-related behaviors, conditions, and preventive service utilization (Centers for Disease Control and Prevention [CDC], 2023). Data are collected from adults in all 50 states, the District of Columbia, and three U.S. territories. Components of the BRFSS include a standardized core questionnaire, optional modules chosen for use by states, and state-added questions. In 2005, the BRFSS began pilot-testing an optional caregiver module to collect public health data on informal or unpaid caregiving (CDC, 2022). A 10-item optional caregiver module was included in the BRFSS from 2009 to 2012. After further revisions and testing, a nine-item caregiver module was launched in 2015. Institutional review board approval was not required because BRFSS data are deidentified and publicly available.

Sample

Data from 2015 and 2017 were combined to obtain a sufficient sample of non-Hispanic Black or African American adults. After excluding respondents who were pregnant at the time of survey (n = 1,858), the final analytic sample included 9,589 respondents. Of those respondents, there were 2,562 caregivers and 7,027 noncaregivers.

Measures

Caregiver Status

Caregiver status, the main independent variable, was determined by responses 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?” Caregivers were defined as participants who responded “yes” to this question; non-caregivers were defined as those who responded “no.”

Obesity

Obesity, the dependent variable, was based on a BRFSS-calculated variable of BMI. Self-reported height and weight were used to calculate BMI, by dividing a person’s weight in kilograms by the square of their height in meters (kg/m²). Obesity was categorized as a BMI of 30.0 or higher, and nonobesity was categorized as a BMI below 30.0.

Physical Activity

Physical activity was based on a BRFSS-calculated summary variable capturing minutes of total physical activity per week. This continuous variable was calculated based on respondent reports of (1) the two most common nonwork-related physical activities they engaged in, (2) how often they took part in these activities (reported as times per week or times per month), and (3) how long they took part in the activity (reported in hours and minutes). Higher scores indicated more minutes of physical activity.

Diet

Fruit and vegetable consumption were based on BRFSS-calculated summary variables reporting times per day these foods were consumed. Fruit consumption data were based on respondent reports of how often they consumed 100% pure fruit juice or fruit. Data on vegetable consumption were from respondent reports of how often they ate vegetables or beans. Consumption per day was included as a continuous variable. Higher scores indicated greater daily consumption of fruits and vegetables.

Chronic Conditions

The number of chronic conditions was calculated based on respondent affirmative reports of ever being told (yes/no) whether they had any of the following conditions: high blood cholesterol, a depressive disorder, asthma, high blood pressure, chronic obstructive pulmonary disease, kidney disease, cancer, angina or coronary heart disease, heart attack/myocardial infarction, stroke, diabetes, or arthritis. Higher scores indicated a greater number of chronic conditions.

Covariates

Continuous covariates included age and number of persons in respondent’s household. Income was measured (in dollars) categorically with four groups: missing/not available, 0–34,999, 35,000–74,999, and ≥75,000. Covariates measured dichotomously include sex (male versus female), educational attainment (high school diploma or less versus some college or more education), marital status (married or in a relationship versus other), employment status (employed, homemaker, or student versus out of/unable to find work), and health insurance (no insurance versus insured).

Data Analysis

Mean and proportional differences between caregiving and noncaregiving groups for demographics and health-related variables were assessed using a one-way analysis of variance and chi-square tests with weighted data. The associations between obesity (dependent variable) and caregiving status, fruit consumption, vegetable consumption, physical activity, and chronic conditions (independent variables) were evaluated using hierarchical binary logistic regressions. Model 1 included caregiver status (only). Next, Model 2 included caregiver status along with demographic variables and count of respondent chronic conditions. Model 3 included variables from the previous models along with fruit and vegetable consumption. Last, Model 4 included variables from the previous models and physical activity.

In line with BRFSS guidelines, regression analyses included complex sampling weights provided with the BRFSS datasets, which were applied after constructing the aggregate sample and creating a new, consistently named weight variable (CDC, 2016, 2018). Weighted data are used to reduce potential bias resulting from nonresponse or noncoverage of certain segments of the population (CDC, 2016, 2018); p values less than .05 were considered statistically significant. All statistical procedures were performed using IBM SPSS Statistics software (Version 25).

Results

Sample characteristics for the overall study population, and caregiving and non-caregiving sub-samples, are presented in Table 1. The total sample size of non-Hispanic Black American adults completing the 2015 or 2017 BRFSS survey included in the weighted data analysis is 9,782,372 participants. The average age of the study population was 44.7 years old (SE = 0.3). About 51% were women, 37% married or in a relationship, 58% had some college degree or more, and 86% had health insurance. With regard to health-related factors, 38% were classified as obese. On average, respondents reported consuming less than two servings per day of fruit and vegetables and engaging in approximately 37 minutes of exercise per week.

Table 1:

Select Characteristics of Non-Hispanic Black American Adult Caregivers and Noncaregivers

	Total (N = 9,782,372)		Caregivers (n = 2,606,956)		Noncaregivers (n = 7,175,416)
Characteristic	M (SE)	% (SE)	M (SE)	% (SE)	M (SE)	% (SE)	p
Age (years)	44.7 (0.3)		44.2 (0.7)		44.8 (0.4)		.457
Female		50.7 (1.0)		57.4 (2.1)		48.3 (1.2)	<.001
Married or in a relationship		37.1 (1.0)		37.2 (1.9)		37.1 (1.1)	.961
Education							.314
High school graduate or less		42.3 (1.0)		40.5 (2.0)		42.9 (1.2)
Some college or more		57.7 (1.0)		59.5 (2.0)		57.1 (1.2)
Employed/self-employed		68.4 (0.9)		68.5 (1.7)		68.4 (1.0)	.932
Insured		86.0 (0.9)		85.1 (1.8)		86.3 (1.0)	.535
Income level ($)							.047
0–34,999		39.8 (1.0)		40.9 (1.9)		39.4 (1.2)
35,000–74,999		25.7 (0.9)		25.1 (1.8)		25.9 (1.1)
$\hspace{1em}\ge$ 75,000		22.9 (0.9)		19.8 (1.6)		24.0 (1.0)
Missing data		11.6 (0.7)		14.2 (1.7)		10.6 (0.7)
Number in household	3.0 (0.0)		3.1 (0.1)		3.0 (0.1)		.094
Count of chronic conditions	1.7 (0.0)		1.7 (0.0)		1.6 (0.0)		.093
Obesity		37.7 (1.0)		41.7 (2.0)		36.2 (1.1)	.008
Fruit consumption	1.6 (0.0)		1.7 (0.1)		1.5 (0.0)		.053
Vegetable consumption	1.8 (0.0)		1.9 (0.1)		1.8 (0.0)		.159
Physical activity	37.3 (0.9)		40.2 (1.9)		36.3 (1.1)		.072

Note: Behavioral Risk Factor Surveillance System (BRFSS) 2015 and 2017 weighted data were used. In line with Centers for Disease Control and Prevention guidelines for BRFSS data analysis, weighted data are analyzed, such that the number of cases analyzed with weighted data mirror population estimates. Thus, the total weighted sample size (N = 9,782,372) noted here is greater than the survey sample size (N = 9,589).

Similarities and differences were observed when comparing the characteristics of caregiving and noncaregiving adults. Caregivers were more likely to be obese than noncaregivers (42% versus 36%; p < .008). A larger proportion of caregivers were female (p < .001) and a smaller proportion of caregivers had income of $75,000 and above compared with noncaregivers (p = .047). No other significant differences were observed between caregivers and noncaregivers.

The models examining the association between caregiving status, health behaviors, and obesity are presented in Table 2. In Model 1, the odds of being obese were higher among caregivers compared with noncaregivers (odds ratio [OR] = 1.26; 95% confidence interval [CI] [1.04, 1.52]). After adjusting for covariates and adding number of chronic conditions in Model 2, caregivers continued to have higher odds of being obese than non-caregivers (OR = 1.22; 95% CI [1.01, 1.48]). In Model 3, fruit consumption and vegetable consumption were added to the models. Neither of these factors were associated with obesity. Caregiver status remained associated with higher odds of obesity (OR = 1.23; 95% CI [1.01, 1.48]).

Table 2:

Associations between Caregiver Status, Demographics, Health Factors, and Obesity among Non-Hispanic Black American Adults

	Model 1		Model 2		Model 3		Model 4
Characteristic	OR	[95% CI]	OR	[95% CI]	OR	[95% CI]	OR	[95% CI]
Caregiver	1.26	[1.04, 1.52]	1.22	[1.01, 1.48]	1.23	[1.01, 1.48]	1.23	[1.02, 1.49]
Age			1.00	[1.00, 1.01]	1.00	[1.00, 1.01]	1.00	[1.00, 1.01]
Female			1.34	[1.13, 1.60]	1.35	[1.13, 1.60]	1.34	[1.12, 1.59]
Married/in a relationship			1.06	[0.88, 1.29]	1.07	[0.88, 1.29]	1.07	[0.88, 1.30]
High school diploma or less education			1.03	[0.85, 1.23]	1.02	[0.85, 1.23]	1.03	[0.86, 1.24]
Employed			0.97	[0.78, 1.20]	0.97	[0.78, 1.20]	0.96	[0.78, 1.19]
Insured			0.93	[0.70, 1.25]	0.93	[0.69, 1.25]	0.93	[0.69, 1.25]
Income ($)a
35,000–74,999			1.27	[0.91, 1.78]	1.08	[0.86, 1.36]	1.07	[0.86, 1.25]
≥75,000			1.48	[1.08, 2.04]	0.93	[0.72, 1.20]	0.92	[0.71, 1.19]
Missing			1.37	[1.03, 1.83]	0.73	[0.54, 0.97]	0.72	[0.54, 0.97]
Number of people in household			1.04	[0.97, 1.10]	1.04	[0.97, 1.10]	1.04	[0.97, 1.10]
Number of chronic conditions			1.17	[1.10, 1.25]	1.17	[1.10, 1.25]	1.17	[1.10, 1.25]
Fruit consumption					0.98	[0.92, 1.05]	0.99	[0.92, 1.06]
Vegetable consumption					0.99	[0.94, 1.05]	1.00	[0.94, 1.06]
Physical activity							0.98	[0.97, 1.00]

Notes: Behavioral Risk Factor Surveillance System 2015 and 2017 weighted data were used. OR = odds ratio; CI = confidence interval.

^aThe reference category is $0–34,999.

In the fourth and final model, physical activity was added to existing variables. Caregiver status remained associated with obesity in the fully adjusted model (OR = 1.23; 95% CI [1.02, 1.49]). Every one-minute increase in physical activity was associated with a corresponding 1.7% decrease in the odds of being obese (OR = 0.98; 95% CI [0.97, 1.00]). Moreover, each additional chronic health condition was associated with a corresponding 17.4% increase in the odds of being obese (OR = 1.17; 95% CI [1.10, 1.25]). Interactions between caregiver status and health behaviors as well as caregiver status and chronic conditions were tested, but were not significant (p > .05; data not in tables).

Discussion

This study aimed to determine whether family caregiving was associated with obesity among Black American adults. Results indicate that caregivers were more likely to be obese than noncaregivers. In addition, higher odds of obesity among caregivers remained after accounting for diet, physical activity, number of chronic health conditions, and sociodemographic factors.

The association between caregiving and obesity among Black Americans is consistent with findings from studies with other subpopulations in the United States and in international research, though important differences should be noted. An earlier analysis of BRFSS data examined the associations between caregiving and cancer risk behaviors among women, with racial stratification modeled as White respondents versus non-White respondents (Reeves et al., 2012). This study found the association between caregiving and obesity to be significant for White women only; the association between caregiving and obesity among non-White women in the sample was not significant. In contrast, the present study found that after controlling for gender, caregiving was associated with obesity among Black Americans. It is possible that analyzing data from Black Americans exclusively helped to uncover associations that were previously masked with the use of a heterogeneous non-White racial subgroup.

Findings from the present study suggest that physical activity, dietary habits, and the number of chronic health conditions do not completely attenuate the difference in odds of obesity between caregiving and noncaregiving Black Americans. As such, alternative explanations should be explored in future research. For example, it is possible that caregivers and care recipients have increased exposure to risk factors that contribute to obesity and the need for caregiving (e.g., care recipients’ health problems) and decreased exposure to protective factors that would reduce their likelihood of negative health outcomes. Future studies accounting for variations in exposure to obesity-related risk and protective factors among Black Americans would add an important context to these findings. In addition, data were not available to account for obesity prior to the onset of caregiving in the analysis. If obesity that predates the onset of caregiving helps to explain the noted association, identifying factors associated with both the likelihood of future caregiving and obesity risk could be important avenues for intervention.

The connections between mental health and physical health also cannot be ignored. Broader research points to a bidirectional relationship between obesity and mental health, with several physiological pathways identified as potential mediators of the noted associations (Avila et al., 2015). Studies often report poorer mental health among caregivers compared with noncaregivers (Anderson et al., 2013), including more days with poorer mental health within the past month (Trivedi et al., 2013). While several studies have reported better mental health among Black American caregivers compared with caregivers of other racial groups (C. Liu et al., 2021), this is not an indicator that the mental health of Black American caregivers should not be a priority (Cothran et al., 2022). Thus, social work research and interventions that prioritize integrated approaches to addressing physical and mental health among caregivers could help to meet important needs and disrupt suspected pathways between mental health and obesity (Robinson et al., 2022; Stanhope et al., 2015).

Indeed, it may be useful for future studies to investigate physiological responses to the stress of caregiving to help explain the association between caregiving and obesity (Capistrant, 2016; Scott et al., 2012). Caregiving is an arduous task; the stress and strain that often accompany caregiving is a risk factor for poor health outcomes (Bauer & Sousa-Poza, 2015; Hoffman et al., 2012; Kotronoulas et al., 2012; Schulz & Beach, 1999). In the caregiver stress process model, caregiving-related stress may result from the challenges of fulfilling multiple roles when taking on caregiving and family responsibilities and other daily activities (Pearlin et al., 1990; Revenson et al., 2016). Examining the association between psychological distress and cytokine levels among caregivers, Sherwood et al. (2016) suggested that caregivers with high BMI were less likely to attain the state of physical adaptation to stress in response to a more demanding and conflicting schedule of caregiving. Moreover, examining whether the associations between obesity and caregiving remain when considering short-term vs. long-term care (e.g., 30 days versus 30 months) were beyond the scope of the current study. However, a longitudinal study of Alzheimer’s disease caregivers showed that the duration of caregiving was directly associated with increased C-reactive protein levels, thereby contributing to other risk factors including poor cardiovascular health and obesity (Von Känel et al., 2012). Further research should examine physiological responses to caregiving stress among Black Americans and also take into account broader sociocontextual factors that influence stress and coping among this population (Cogburn, 2019; Harrell et al., 2003).

In the Black American community, the family has been a cornerstone of support for the vulnerable and chronically ill (Bennett et al., 2014; Turner et al., 2004). Black Americans often rely more heavily on family caregivers and report lower usage of formal caregiving services than their White counterparts (Crawley et al., 2000; Rizzuto & Aldridge, 2018). This reliance on family caregiving among Black Americans has been attributed to several factors such as mistrust of the healthcare systems, greater availability of family support, and deeply rooted cultural and spiritual beliefs that the family should care for one another (Bennett et al., 2014; Turner et al., 2004). Future research should investigate whether associations between caregiving and obesity are stronger for certain subgroups. For example, mixed-methods studies that examine whether associations between caregiving and obesity differ by care recipient illness type with quantitative methods, and include qualitative methods to better understand similarities and differences in the lived experiences of caregivers and care recipients by illness type, could be very useful for identifying key commonalities to inform broader research and intervention efforts.

Additional Considerations for Social Work Research and Practice

There are several additional considerations that can inform this important area of work. First, an increased use of caregiving and social needs assessments by social workers can provide a more comprehensive understanding of Black American caregiver experiences and unmet needs, and help to facilitate timely interventions to improve health outcomes. There is increasing support for these types of efforts. The recent report Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation’s Health advocates for five activities (i.e., 5As) to better integrate social care (NASEM, 2019; Zebrack et al., in press). Adjustment and assistance include activities focused on individuals that respond to social risks and protective factors, alignment and advocacy include activities focused on social care in communities, and awareness recognizes individual- and community-targeted efforts informed by socioeconomic and contextual factors most relevant to the populations they aim to serve (NASEM, 2019). Social work practice with Black American caregivers and care recipients that aligns with and helps to build momentum of these broader initiatives can play a critical role in strengthening policy and system-level support for social care and healthcare integration (Zebrack et al., in press).

Second, interventions should be sensitive and responsive to how weight-related perceptions and stigma influence caregiver health, including their ability to access and receive appropriate healthcare (Tomiyama et al., 2018). Research indicates that women, who traditionally and historically are more likely to take on caregiving roles, are more susceptible to fat stigma than men, and this stigma may contribute to weight retention and gain (Brewis, 2014). Researchers have also argued that weight stigma is a key contributor to the growing prevalence of obesity (Tomiyama et al., 2018). Thus, it is important to address weight-related stigma, bias, and stereotypes social workers may hold about obese individuals—who could be in roles of caregiver and/or care recipient—that can negatively influence their social work practice (Green et al., 2020; Lawrence et al., 2019; McCardle, 2008; Shinan-Altman, 2017). Social work education and training that increase understanding of obesity as both a health risk and a social stigma, and highlight the opportunities for social workers to engage with and advocate for effective policies and practices to prevent obesity and reduce obesity-related stigma, can help to alleviate mistreatment of obese individuals (Lawrence et al., 2012). Given the noted bias in medical treatment against Black Americans (Hall et al., 2015; Smedley et al., 2003), intersectional approaches to addressing discrimination faced by Black Americans who are obese are certainly warranted.

Third, a culturally informed, strength-based perspective acknowledging the critical support provided by Black American caregivers and families is necessary. More specifically, interventions that seek to build on the substantial resources that already exist in families can help to promote collaboration with families and guard against deficit models that lead to victim blaming and harm. Collaboration is a familiar—but understudied—topic in caregiving-related research and practice. A recent study by Ellis and colleagues (2022) provides a framework for conceptualizing family caregiver collaboration and quantitative index to capture variation in collaboration across family contexts with multiple caregivers. Obesity-related interventions that include multiple individuals serving in caregiving roles within a family system may benefit from research such as this when making decisions about intervention design and evaluation that can improve practice and, conversely, help to inform ongoing theory and measurement development.

Limitations and Strengths

This analysis uses cross-sectional data and, as such, cannot account for obesity among caregivers prior to the onset of caregiving or variation in obesity over time. It also does not account for caregivers who may be obese but metabolically healthy (or conversely, not obese, but metabolically unhealthy). Second, caregivers are defined in the BRFSS as those who report providing care at the time of the study. This analysis is unable to consider previous caregiving experiences of respondents. Third, as BRFSS data are collected with adults, this study does not examine associations between caregiving and obesity among individuals under the age of 18 who are caregivers. Last, available data do not allow us to account for ethnic diversity among Black Americans.

Despite these limitations, there are several strengths. Population-based studies that compare outcomes for caregivers and noncaregivers recruited and enrolled with similar methods have been described as “surprisingly rare” in comparison with the large majority of studies of family caregiving utilizing clinical or convenience samples (Roth et al., 2015). The BRFSS provides nationally representative data through well-tested and refined methodology, which results in a large and robust sample for analysis of this racial subgroup. In addition, results obtained in this study can be compared with data from future annual surveys to examine patterns over time. Population-based studies examining risk factors and risk predictors are informative for intervention implementation, including policy and practice strategies that can make the greatest impact on population health (Neta et al., 2018). Last, this study can help inform future within-group research with Black Americans in this topic area, providing a useful compliment to (more common) racially comparative studies (Kauh et al., 2021; Whitfield et al., 2008). While comparative studies that draw attention to important racial disparities are critical for making progress, these types of studies are not sufficient for increasing understanding of variation within racial groups. More specificity can be particularly helpful for designing targeted and tailored intervention programs to support this population (Kreuter et al., 2003; McCarthy et al., 2021). Overall, this study investigates critical questions that—based on health, aging, and demographic trends—are expected to grow in relevance in the years to come.

Conclusion

Family caregiving contributes immensely to the health of the U.S. population and the healthcare system. As such, the health of caregivers is closely tied to those for whom they provide care. Given their role in supporting individuals and families, and their pursuit of social justice for vulnerable groups, social work researchers and practitioners are uniquely positioned to advocate for and support the health of Black American caregivers, particularly those affected by weight-related health challenges. Broader attention to the use of caregiver needs assessments and the disruption of weight-related stigma is needed, as are culturally informed, strength-based interventions. Social work interventions that attend to the health of caregivers, care recipients, and the broader family can help to address both the independent and interdependent aspects of health and build on existing forms of collaborative care.

 

This research was supported by grants from the National Heart, Lung, and Blood Institute [R25HL126145: Ellis, Thorpe, Bruce] and the National Institute of Minority Health and Health Disparities [U54MD000214: Thorpe].