Abstract

This study examined health behaviors, utilization, and access to care among older Latina and Black American mothers who co-reside with a child with developmental disabilities. Using data from the National Health Interview Survey National Center for Health Statistics (2005a), we compared Latina and Black American caregivers to similar women who did not have caregiving responsibilities. Findings showed that Latina caregivers were more likely to smoke and have insurance; Black American caregivers were less likely to be able to afford medication and mental health care; and both groups were less likely to have seen a doctor in the past year than their noncaregiving counterparts. Findings suggest that service providers should consider developing programs that focus on health for caregivers of color. Furthermore, results suggest that providers should take into account differing trends across ethnicities when designing programs.

In a previous study (Magaña & Smith, 2006) on older Latina and Black American mothers living with a child with a developmental disability, we found that the stress of caring for their child over the mother's life course may affect her physical and emotional health. We compared the mental and physical health of midlife and older Latina caregivers to same-aged noncaregivers and found that midlife Latina mothers living with a child with a developmental disability were more likely to experience depressive symptoms and older Latina caregivers were more likely to experience heart problems and limitations due to arthritis than their noncaregiving peers. We also found that older Black American maternal caregivers were more likely than their age peers to experience limitations due to arthritis and were somewhat more likely to experience limitations due to diabetes than their noncaregiving peers. In a similar study (Magaña, Greenberg, & Seltzer, 2004), we compared older Black American mothers caring for an adult child with schizophrenia to a representative sample of noncaregiving age peers and found that the caregiving mothers had more arthritis, diabetes, and eye problems than their noncaregiving counterparts.

In contrast, researchers who have investigated the well being of older non-Hispanic White mothers of adult children with developmental disabilities have not found differences in levels of mental and physical health compared with their noncaregiving age peers (Chen, Ryan-Henry, Heller, & Chen, 2001; Krauss & Seltzer, 1993; Seltzer et al., 2001). Consequently, the physical and emotional health of women of color may be particularly vulnerable to the stress of caring for a child with disabilities across the mother's lifespan. However, the mechanisms by which their health declines are not well understood.

In studies (Collins & Winkleby, 2002; National Center for Health Statistics, 2005b; Sundquist, Winkleby, & Pudaric, 2001) on social determinants of health, researchers have reported the following risk factors for poor health: low socioeconomic status (SES); older age; maladaptive, health-related behaviors (e.g., poor exercise and diet, being overweight, smoking, and drinking); and poor access to and utilization of health services. As a follow up to our previous study on health outcomes, we sought to understand more about the relationship of caregiving to health among Latina and Black American women by examining the role of health-related behaviors, health care utilization, and access to health care in the caregiving context. Below, we summarize research on each of these three determinants of health and their relationship to caregiving.

In research that compared health behaviors of caregivers of older adults to same-aged noncaregivers, the results have been mixed. Some studies reported similar levels of cigarette smoking and alcohol consumption among caregivers of older adults compared with noncaregivers (Burton, Newsom, Schulz, Hirsch, & German, 1997; Kiecolt-Glaser, Dura, Speicher, Trask, & Glaser, 1991; Scharlach, Midanik, Runkle, & Soghikian, 1997), whereas other studies found that caregivers who smoked increased their smoking after the onset of their caregiving duties (Connell, 1994), or smoked and consumed less alcohol when compared with their age peers (Baumgarten et al., 1992). Research on the relationship of caregivers of older adults and obesity, diet, and exercise has yielded more consistent findings that link caregiving to higher levels of fat and caloric intake and lower levels of exercise compared with noncaregivers (Burton et al., 1997; Fuller-Jonap & Haley, 1995; Schulz et al., 1998; Vitaliano, Russo, Scanlan, & Greeno, 1996).

Several studies have suggested that being a caregiver is related to insufficient health care utilization (Burton et al., 1997; Gallant & Connell, 1997; Schulz et al., 1998; Vitaliano et al., 1996). Furthermore, there are racial and ethnic disparities in health care utilization that need to be taken into account for the populations of interest. For example, Freiman and Cunningham (1997) found the use of mental health care to be significantly lower among Black Americans and Latinos compared with non-Hispanic Whites. There are also potential cultural barriers to health care utilization for Latino caregivers, including language, acculturation, and social isolation (Chesney, Chavira, Hall, & Gary, 1982).

With respect to health care access, adults with a chronic condition are more likely to need prescribed medications to manage their symptoms and maintain the quality of their life. Reed (2005) found that access to prescription medication for adults with a chronic condition was more limited than for adults without a chronic condition. Although we found that some caregivers are more likely to experience chronic health conditions such as arthritis, heart problems, and diabetes than their age peers (Magaña & Smith, 2006), the relationship of caregiving to prescription drug access has not yet been examined. The relationship between out-of-pocket expenses and caregiving has been well documented among parents of children with disabilities (Caldwell, in press; Fujiura, Roccoforte, & Braddock, 1994; Leonard, Brust, & Sapienza, 1992). The family's SES is likely to be strained by greater medical expenses that result from caring for a child with a disability. To compensate for these expenses, caregivers often have to make choices about whether they can afford to access health care for themselves (Altman, Cooper, & Cunningham, 1999; Kasper, Giovannini, & Hoffman, 2000).

Because families of color often experience a lower SES, they are more likely to have inadequate access to physical and mental health care to begin with (Weinick, Zuvekas, & Cohen, 2000; Weisfeld & Perlman, 2005). Furthermore, the connection between limited health insurance and diminished access to health care is well documented in research on Latinos and Black Americans (Agency for Healthcare Research and Quality, 2000; Quinn, 2000).

In summary, our previous research (Magaña & Smith, 2006) found that health outcomes are different between older mothers of color who have children with developmental disabilities compared with women of the same age and racial and ethnic background who do not have children with disabilities. To understand potential mechanisms by which health may be compromised for these mothers, in the current study, we focused on understanding differences between caregivers and noncaregivers on health behaviors, health care utilization, and access to health care. Some research has shown a link between (a) poor health behaviors, underutilization of health care services, and lower access to health care and (b) caregiving. However, the available research on caregivers and determinants of health has focused primarily on non-Hispanic, White caregivers who are meeting the needs of a family member who is aging or has dementia. In this study, we explored this gap in the literature by examining the relationship of these health determinants and caregiving among older Latina and Black American mothers co-residing with a child with a developmental disability.

In our previous article (Magaña & Smith, 2006), we argued for the importance of within-group analysis because the social and cultural environments are different among racial–ethnic groups. Furthermore, we found some health outcomes differed between Black American caregivers and Latina caregivers. Thus, in the present study, we also analyzed our questions for each racial–ethnic group separately.

Our research questions were as follows:

  1. Do midlife and older Latina and Black American mothers living with a child with a developmental disability differ in their health behaviors, health care utilization, or access to health care from their age peers who do not live with a child with a developmental disability?

  2. How do these comparisons vary by age group (i.e., midlife women vs. older adults)?

Method

Sample and Procedures

The participants for this study were selected from the National Health Interview Survey (NHIS; National Center for Health Statistics, 2005a). We examined 162 Latina and Black American mothers who co-resided with their child who had a developmental disability and 2,754 of their age peers who did not co-reside with a child who had a developmental disability (we use the term Black American in our study rather than African American because there is ethnic variation in the Black population that could include those that identify as African Americans, Caribbean Blacks, or African Blacks; furthermore, the NHIS does not identify ethnic identities within the racial category Black). The NHIS is a series of cross-sectional data that uses a complex sample design involving stratification, clustering, and multistage sampling. We selected our sample from 3 years of data (1999–2001) because the number of midlife and older adult mothers caring for a child with a developmental disability within these ethnic groups was expected to be small. Additional details on the NHIS are available at the website (National Center for Health Statistics, 2005c).

Our sample was selected according to the following criteria: The caregiver group included Latina (non-Black Latina) and Black American (U.S.-born, non-Latina Black) mothers who were 40 years and older, lived with a minor or adult child with a developmental disability, and did not co-reside with anyone else who needed care due to a physical or mental health condition. We adapted criteria for identifying children with an intellectual or developmental disability from the work of Larson et al. (2001). In the person-level data file, we selected those household members who were identified as a minor or adult child to the respondent and had limitations in physical activity due to intellectual disability, other developmental delay, or epilepsy. We then identified children from the sample child core who, according to respondent report, were diagnosed by a health professional with intellectual disability, Down syndrome, cerebral palsy, autism, or other developmental delay. We excluded cases in which there was a child in the household with a functional limitation due to a physical or mental illness, or someone else in the household who needed care due to a physical or mental health condition or that needed assistance with daily living tasks.

The mean age of the children and adults with developmental disabilities was 17.9 years (SD = 11.3) and 59.4% were male. The majority of children and adults with disabilities were identified as having intellectual disability or other developmental disability (unspecified). About 93% of the mothers had one child with a developmental disability, whereas 7% had two or more children that met the criteria for having a developmental disability. Overall, we identified 83 Latina and 79 Black American mothers who were 40 years and older and co-resided with a child with a developmental disability. We were limited to mothers who co-resided with their child because the NHIS does not include data on children who live outside of the household.

The sample for the comparison group was determined by selecting all women who were at least 40 years old, did not have a child who met the criteria for a developmental disability, did not have a child with a functional limitation due to a physical or mental illness, did not live with anyone else who needed care due to a physical or mental health condition, and did not have an additional household member who needed assistance with daily living tasks. The sample sizes for the Latina and Black American comparison groups were 1,667 and 1,087, respectively.

Of the Latina mothers (caregivers and noncaregivers), 59.7% were of Mexican descent, 15.4% Central or South American, 10.2% Puerto Rican, 6.4% Cuban descent, 4.2% did not have a specified ethnicity, and 4.1% Dominican. The sample sizes of caregivers within the various Latina groups were not large enough to conduct within-group analyses of health outcomes between caregivers and noncaregivers. We tried to limit the potential differences among the Latino ethnicities by controlling for whether they were born in the United States, level of education, income, employment, and family size.

Table 1 presents the demographic characteristics of the Latina and Black American mothers and their comparison groups. For the Latina women, the only variable that was significantly different between caregivers and noncaregivers was percentage born in the United States. Almost 50% of the caregivers were born in the United States, whereas only 31% of the noncaregivers were born in the United States. For the Black American women, caregivers were significantly more likely to have incomes under $20,000 than noncaregivers. In addition, the caregiver group had more family members residing in the household than the noncaregiver group in the Black American sample; however, this difference was only marginally significant.

Table 1

Maternal Characteristics

Maternal Characteristics
Maternal Characteristics

Measures

Demographic variables

Age was used as a continuous variable in the analyses for the first research question. However, to determine the effect of being a midlife mother versus an older mother, the respondent's age was recoded from a continuous variable into a dichotomous variable: 0 (40 to 54 years) and 1 (55 and older). We recoded marital status of the respondent as 0 (not married) and 1 (married). The NHIS person-level variable on income reflected whether families were living in poverty and was coded 1 (less than $20,000) and 2 (more than $20,000). The respondent's education level was coded as 0 (never attended school or kindergarten only), 1 through 12 (grades), 13 (high school graduate/ GED), 14 (some college, no degree), 15 (associates degree), 16 (bachelor's degree), 17 (masters degree), and 18 (professionals or doctoral degree). The size of the respondent's family living in the household is reported as a continuous variable. Whether the Latina respondents were born in the United States was coded as a 0 (born outside the U.S.) or 1 (born in the U.S.).

Caregiver status

A dichotomous variable was constructed to determine the impact of being a caregiver on health behaviors, service utilization, and access to care: 0 (comparison group) and 1 (caregiver group).

Health behaviors

Health behaviors included dichotomous measurements of smoking tobacco, drinking alcohol, obesity, and physical exercise. The measure of smoking tobacco was created from a question in which respondents were asked, “Do you NOW smoke cigarettes every day, some days, or not at all?” Responses were coded as 1 (every day or some days) and 0 (not at all).

To distinguish between moderate versus problematic or heavy drinking, we used a series of items in the NHIS to create a dichotomous variable. The U.S. Department of Agriculture and the U.S. Department of Health and Human Services define moderate (versus heavy) drinking for women as 1 or less drinks per day (U.S. Department of Health and Human Services, 1995). The first item asked the respondent, “In ANY ONE YEAR, have you had at least 12 drinks of any type of alcoholic beverage?” Drinking was coded as 1 (yes) and 0 (no). Participants who responded “no” to this question were coded as drinking moderately or less (i.e., 0). Mothers who responded “yes” to the first question were asked to report the average number of drinks on days they drank alcohol. Respondents were then asked to report the average number of days per week that they drank. These two responses were multiplied to calculate the average number of drinks consumed in a week. This number was then divided by seven to determine the average number of drinks per day. Respondents who drank 1 drink per day on average or less were coded as drinking moderately or less (i.e., 0), and those who drank more than 1 drink per day were coded as heavy drinkers (i.e., 1).

Obesity was determined using body mass index (BMI). The BMI was calculated from the height (meters) and weight (kilograms) of the respondents [BMI = (weight/height)2]. A BMI of 30 or greater was coded 1 (obese) or 0 (not obese) if scores were lower than 30 (National Institutes of Health, 1998).

Participation in physical exercise was determined by a coding scheme used in a report compiled by the Federal Interagency Forum on Aging Related Statistics (2004), Older Americans 2004: Key Indicators of Well-Being. The authors of this report also used NHIS data. Regular exercise was defined as 10 min of vigorous activity 3 times per week and/or light or moderate activity a minimum of 30 min a day, 5 days a week. Two sets of items were used to indicate regular exercise. The first item set asked respondents, “How often do you do VIGOROUS activities for AT LEAST 10 MINUTES that cause HEAVY sweating or LARGE increases in breathing or heart rate?” For affirmative responses, secondary questions determined the actual number of minutes and days per week that this exercise took place. Physical exercise was coded 1 (yes) if the respondent vigorously exercised 3 days per week for at least 20 min each session and 0 (no). The second item set asked respondents, “How often do you do LIGHT OR MODERATE activities for AT LEAST 10 MINUTES that cause ONLY LIGHT sweating or a SLIGHT to MODERATE increase in breathing or heart rate?” For affirmative responses, secondary questions determined the actual number of minutes and days per week that this exercise took place. Physical exercise was coded 1 (yes) if the respondent moderately exercised 5 days per week for at least 30 min each session, and 0 (no).

Health care utilization

Health care utilization was determined by the participant's response to the following question: “During the past 12 months have you seen or talked to any of the following health care providers about your own health?” There were three categories for response: a general doctor who treats a variety of illnesses (e.g., general practice, family practice, internal medicine), a mental health professional (e.g., a psychiatrist, psychologist, psychiatric nurse, or clinical social worker), or a specialized provider (e.g., physical therapist, speech therapist, respiratory therapist, audiologist, or occupational therapist). Dichotomous variables were created for each of the health care providers, and were coded 0 (did not see/talk with provider) and 1 (saw/talked with provider).

Health care access

Health care access was measured by three variables. The first two variables were represented by responses to the following question: “During the past 12 months was there any time when you needed any of the following but didn't get it because you could not afford it?” The responses included prescription medicines and mental health care or counseling. Dichotomous variables were created for each type of access to health care, and were coded 0 (could not afford) and 1 (able to afford). Health care access was also measured by health insurance coverage. Respondents were asked, “Are you covered by health insurance or some other kind of health care plan?” Respondents were provided with a list of 13 different health care plans. If the respondent indicated that she was a member of any 1 or more of these 13 plans, she received a code of 1 (covered) and if not, a code of 0 was given (not covered).

Data Analysis

Weighting

We used frequency weights provided in the NHIS (National Center for Health Statistics, 2005a) data to accurately reflect the number of persons represented by any given case after adjusting for the probability of being included in the sample. Even with the use of weighted data, the methods of clustering and stratification generally result in biased variance estimates. Therefore, we conducted all analyses with SUDAAN 9.0.1 (Research Triangle Institute, 2005), a statistical package that calculates robust variances and corrects for standard errors for clustering and stratification.

Method of analysis

Logistic regression methods were used to determine the association between caregiving versus noncaregiving and measures of health behaviors, health care utilization, or health care access when controlling for demographic characteristics (age, education, marital status, income, employment status, family size, and birthplace [i.e., in the United States vs. foreign born for the Latina sample]). Separate models were run for each ethnic group.

To examine the association between caregiving and health behaviors, health care utilization, and health care access for midlife caregivers and older caregivers, separate regressions were run within each ethnicity and within each age group. Because the caregiver groups were considerably small, especially among the sample of older caregivers, an alpha level of .10 was used for statistical tests. Those differences reported as p < .10 are described as being only marginally significant.

Missing data

The group-level mean was imputed for those cases with missing data on the education variable (Allison, 2001). The group-level mean was calculated by controlling for race, age group, and caregiver status. The SUDAAN 9.0.1 software was used to generate predicted probabilities for the dichotomous variables with missing data (marital status, employment status, income) by regressing each dichotomous variable on race, age group, caregiving status, education level, family size, and birthplace (foreign vs. American). The missing data were coded 1 if the predicted probability was estimated at .50 or greater and 0 if the predicted probability was estimated at less than .50 (Allison, 2001).

Results

In Table 2, percentages of the use of maladaptive health behaviors and health services and percentages of health care access variables are presented by ethnicity and age group. It is notable that, in the health behaviors category, all groups had high rates of obesity and low levels of exercise. The percentages of women who reported talking to a doctor in the past year were fairly low, but ranged between 43.3% for older Latina caregivers to 81.6% for older Black American noncaregivers.

Table 2

Percentages for Health Behaviors, Health Care Utilization, and Access to Health Care Among Caregiving and Noncaregiving Women

Percentages for Health Behaviors, Health Care Utilization, and Access to Health Care Among Caregiving and Noncaregiving Women
Percentages for Health Behaviors, Health Care Utilization, and Access to Health Care Among Caregiving and Noncaregiving Women

In the first research question, we asked, “Do midlife and older adult Latina and Black American mothers living with a child with a developmental disability differ in their health behaviors, health care utilization, or access to health care from their age peers who do not live with a child with a developmental disability?” For Latina mothers, we did not find a statistically significant relationship between being a caregiver and health behaviors, or health care utilization (see Table 3). However, with regards to access to health care, we found that Latina caregivers were 2.6 times more likely than noncaregivers to have health insurance.

Table 3

Odds Ratios for Caregiving as a Predictor of Health Behaviors, Health Care Utilization, and Access to Health Care (Adjusting for Age, Income, Education, Marital Status, Employment, Family Size, and U.S. Residency)

Odds Ratios for Caregiving as a Predictor of Health Behaviors, Health Care Utilization, and Access to Health Care (Adjusting for Age, Income, Education, Marital Status, Employment, Family Size, and U.S. Residency)
Odds Ratios for Caregiving as a Predictor of Health Behaviors, Health Care Utilization, and Access to Health Care (Adjusting for Age, Income, Education, Marital Status, Employment, Family Size, and U.S. Residency)

Among the Black American mothers, we found relationships between caregiving and each of the three outcomes: health behaviors, health care utilization, and access to health care (see Table 3). Black American caregivers were less likely to exercise (this finding was marginally significant), more likely to have talked to a mental health professional, and less likely to have talked to a general doctor than their comparison group. Black American caregivers were also less likely to have talked to a physical or occupational therapist than their comparison group (also marginally significant). Most significant, Black American caregivers were 4.3 times more likely to be unable to afford prescription medication and 8.9 times more likely to be unable to afford services from a mental health professional than the Black American noncaregivers.

In our second research question, we asked “How do these comparisons vary by age group (i.e., midlife women versus older adults)?” For Latina women, we found a relationship between caregivers and each of the three categories (see Table 4). In the category of health behaviors, we found that midlife Latina caregivers were two times more likely to smoke than their comparison group, whereas there were no older Latina caregivers who smoked. With respect to health care utilization, older Latina caregivers were less likely to have talked to a general doctor, yet more likely to have talked to a physical or occupational therapist than Latina noncaregivers. There were no differences between Latina, midlife caregivers and noncaregivers in this category. When we examined health care utilization, we found that midlife Latina caregivers were more likely to have health insurance than midlife noncaregivers, but there were no differences in health insurance between older caregivers and noncaregivers.

Table 4

Odds Ratios for Caregiving as a Predictor of Health Behaviors, Health Care Utilization, and Access to Health Care by Ethnic and Age Group (Adjusting for Age, Income, Education, Marital Status, Employment, Family Size, and U.S. Residency)

Odds Ratios for Caregiving as a Predictor of Health Behaviors, Health Care Utilization, and Access to Health Care by Ethnic and Age Group (Adjusting for Age, Income, Education, Marital Status, Employment, Family Size, and U.S. Residency)
Odds Ratios for Caregiving as a Predictor of Health Behaviors, Health Care Utilization, and Access to Health Care by Ethnic and Age Group (Adjusting for Age, Income, Education, Marital Status, Employment, Family Size, and U.S. Residency)

Table 4 shows that there were no differences between midlife or older Black American caregivers and their age peers in the category of health behaviors. The finding in the overall Black American sample that caregivers were less likely to exercise is not significant when broken down by age groups. This may be due to an already weak finding being subjected to smaller sample sizes, thus weakening it further.

With respect to health care utilization, both midlife and older Black American caregivers were more likely than noncaregivers to have talked to a mental health professional. Midlife Black American caregivers were less likely to have talked to a general doctor than their midlife counterparts, whereas midlife Black American caregivers were less likely to have talked to a physical or occupational therapist than their comparison group. In regards to health care access, we found that midlife and older Black American caregivers were more likely than noncaregivers to report being unable to afford prescription medication. Midlife Black American caregivers were 11.1 times more likely than noncaregivers to be unable to afford mental health services, whereas there were no differences in ability to afford mental health services between older Black American caregivers and noncaregivers.

Because we did not expect to find that Latina caregivers would have greater access to health insurance than Latina noncaregivers, we conducted additional analysis. Research on immigrant Latinos has found that foreign-born Latinos have lower rates of insurance access than U.S.-born Latinos because they may not be entitled to programs available to citizens and legal residents only and they tend to work in jobs in which insurance is not offered or is more expensive (Blewitt, Davern, & Rodin, 2005; Delgado, 2007; Hayes-Bautista, 2004). Using chi-square comparisons, we examined whether the rates of those insured differed between U.S.-born and foreign-born Latinas in our sample. Contrary to expectations, we found that foreign-born caregivers had significantly more insurance coverage (83.9%) than foreign-born noncaregivers (60.2%), χ2(4, N = 1,750) = 10.8, p = .001. However, there were no differences between caregivers and noncaregivers who were U.S. born.

Discussion

In this study, we examined the relationship of caregiving to health behaviors, health care utilization, and access to health care among Latina and Black American women who were 40 years and older. We compared women who were living with a child with developmental disabilities with their same-racial/ethnic-group counterparts who were not living with a child with a disability on health-related measures.

Regarding health behaviors for Black American women, both caregivers and noncaregivers were relatively similar with the exception of exercise. Caregivers were slightly less likely to exercise than noncaregivers. We did not find significant differences with respect to smoking, drinking, and levels of obesity.

However, we found that there were many differences between Black American caregivers and noncaregivers with respect to health care utilization and access. Caregivers were less likely to have talked to a general practitioner or a physical or occupational therapist and more likely to have talked to a mental health professional than their noncaregiving counterparts. Most strikingly, caregivers were less likely to afford prescription medication and services from a mental health professional than the comparison group. These findings suggest that Black American caregivers have more difficulty utilizing and accessing services, which may be related to lower incomes and poor access to resources to begin with, and out-of-pocket costs for their child with the disability. For example, Caldwell (in press) found that many caregivers of children with developmental disabilities reported that they did not seek needed care from a doctor due to financial cost. Furthermore, Caldwell found that low incomes and out-of-pocket expenses for the child with developmental disabilities were related to lower access to health care for the caregiver. Out-of-pocket costs included paying for transportation, respite care, recreational services, and medical and dental care for their child with developmental disabilities (Caldwell, in press). Given our previous findings that Black American caregivers had more limitations due to arthritis and were more likely to have diabetes than noncaregivers, their inability to afford prescription medications is particularly troubling.

A surprising finding was that the Black American caregivers were more likely to see a mental health professional than noncaregivers. In our analysis of the same sample on health outcomes, we found no differences between caregivers and noncaregivers on depressive symptoms (Magaña & Smith, 2006). It may be that mental health measures such as those assessing depressive symptoms do not capture psychological distress adequately among this population. Use of mental health services may be an important indication that there is more psychological distress among Black American caregivers than has been previously reported.

When we examined midlife versus older caregivers, we found that both midlife and older Black American caregivers were more likely to talk to mental health professionals than noncaregivers in those age groups. Only midlife Black American caregivers were less likely to see a doctor than noncaregivers; Black American women who were 55 years and older were similar in their rates of talking to a doctor. This may be because more of the older caregivers have access to government insurance programs such as Medicare, and they are more likely to suffer from chronic health conditions requiring medical visits. Both midlife and older caregivers were more likely unable to afford prescription medication than noncaregivers, but only midlife caregivers were more likely to not be able to afford seeing a mental health professional.

For Latina women, the only significant difference between caregivers and noncaregivers for the whole sample was in health insurance coverage. Surprisingly, noncaregivers were less likely to have health insurance than caregivers. When we looked more closely at this, the difference between caregivers and noncaregivers was primarily among foreign-born Latinas, whereas the U.S.-born Latinas had similar rates of insurance across caregiver status. Research shows that Latinos in general have less access to health insurance than the general population, particularly those who are not U.S. born (Delgado, 2007; Hayes-Bautista, 2004). Barriers to receiving insurance among foreign-born Latinos include not having access to government programs as well as working in jobs that are predominantly low paying and that have little or no insurance available. If insurance is available, Latino employees often choose not to access it because the premiums are too high (Blewitt et al., 2005). It may be that Latino families who have a child with a developmental disability are more likely to access whatever health care insurance options are available because of the needs of the child, regardless of cost, which may in turn make insurance available to the caregivers and other family members.

We found additional differences between Latina caregivers and noncaregivers when we investigated the relationship between caregiving and health-related variables by midlife and older groups. Midlife caregivers were more likely to smoke and have access to health insurance than noncaregivers. In our previous analysis (Magaña & Smith, 2006), we found that the midlife Latina caregivers had higher rates of depression than older Latina caregivers; perhaps smoking is one of the ways that caregivers try to reduce stress.

Latina caregivers who were 55 years and older were less likely to talk to a general doctor than noncaregivers in this age group. Because the level of health insurance coverage is relatively similar, there may be other issues for older Latina caregivers such as not being able to invest time in taking care of themselves due to their caregiving responsibilities. However, older Latina caregivers were more likely to have seen a physical or occupational therapist than their noncaregiving counterparts. Previous research has shown a link between caregiving and arthritis for older Latinas (Magaña & Smith, 2006), which may be driving the use of the physical or occupational therapists.

One of the important findings of this study was that the differences in health behaviors and health care utilization and access between caregivers and noncaregivers were distinct across ethnicities. For Black American caregivers, not being able to afford medication and mental health care were important issues. Lower utilization of health care was an issue for this group as well. However, health behaviors were not very different between caregivers and noncaregivers. For midlife Latina caregivers, smoking was a problematic health behavior compared with midlife noncaregivers. Older Latina caregivers reported visiting a doctor less frequently than their noncaregiving counterparts but were more likely to visit an occupational therapist. Health insurance was more available to Latina caregivers than noncaregivers, and there were no differences with respect to other aspects of access to health care. It appears that, for Latinas, caring for children with disabilities may increase access to health care; however, this dynamic was not found for Black American caregivers.

These findings suggest that, in developing programs to address the physical and mental health needs of caregivers, there needs to be distinct emphases for different groups. For Black American caregivers, helping them access mental health services if they feel they need them is an important brokering function that service providers can offer. Exploring with Black American caregivers ways in which they might be able to access prescription medications is needed as well. They may need advocates to help them access resources that may be available in the medical system through special programs. For both groups, caregivers were less likely to see a general doctor about their own health. This was particularly true for older Latina caregivers and midlife Black American caregivers. This finding suggests that for both groups, asking caregivers about whether they use health services to monitor their own health and exploring ways in which they can increase health care utilization are warranted by service providers.

Previous research indicates that depression screenings are important when working with Latina caregivers. Follow up on these screenings by service providers is important, including the exploration of stress-reduction activities. For those who are using smoking as a form of stress reduction, specific referrals can be offered to help replace this behavior with more healthy activities.

There are limitations to the interpretation of the findings from this study. First, because of the small sample size, especially with respect to older adult caregivers, our findings may underestimate the relationship between caregiving and health behaviors, service utilization, and access to care among Latina and Black American caregivers. Second, the cross-sectional nature of this study did not allow us to assign causality with respect to caregiving and these health-related outcomes. Longitudinal research is needed to determine the causal manner in which caregiving contributes to these outcomes. Third, the NHIS (National Center for Health Statistics, 2005c) does not include data on children living outside of the household; thus, it was possible for mothers included in the comparison group to have had children with a disability who were living outside of their household. This may have led to a self-selection bias in which those who were relatively healthy elected to continue co-residency with their son or daughter.

In summary, services for people with developmental disabilities usually focus on the consumer with the disability but provide little focus on family caregivers, who are most often mothers. A larger percentage of people with developmental disabilities who are Black and Latino live at home with their families than non-Latino White people with developmental disabilities (Heller & Factor, 1988; Heller, Markwardt, Rowitz, & Farber 1994), and research has shown that there may be a cumulative effect on health for caregivers in these families (Magaña & Smith, 2006). This research coupled with the current findings on health behaviors, utilization, and access call attention to the need for developmental disability service providers to address the mental and physical health care needs of the family caregivers in addition to those of the child with disability.

Table 2

Extended

Extended
Extended

References

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Support for this manuscript was provided by the John A. Hartford Foundation Geriatric Social Work Faculty Scholars Program, the National Institute on Disability and Rehabilitation Research–funded Rehabilitation Research and Training Center on Aging with Developmental Disabilities at the University of Illinois at Chicago, and the Waisman Center at the University of Wisconsin—Madison. Support was also provided by National Institute of Mental Health Training Grant T32 17104 (principal investigator: Linda B. Cottler).

Author notes

Authors: Sandy Magaña, PhD (magana@waisman.wisc.edu), Associate Professor, School of Social Work and Waisman Center, 1350 University Ave., University of Wisconsin—Madison, Madison, WI 53706. Matthew J. Smith, PhD, Postdoctoral Research Fellow, Department of Psychiatry and Behavioral Sciences, Northwestern University, Feinberg School of Medicine, Chicago, IL