TY - JOUR
AU - Freedman, Vicki, A.
AB - Abstract Objectives. Although racial and ethnic disparities in disability are well established and technology is increasingly used to bridge gaps between functional deficits and environmental demands, little research has focused on racial and ethnic disparities in device use. This study investigated whether use of mobility devices differs by race and ethnicity and explored several reasons for this difference. Methods. The sample included community-dwelling adults aged 65 and older from the 2002 and 2004 waves of the Health and Retirement Study. We used predisposing, need, and enabling factors to predict mobility device use alone and combined with personal care. Results. Blacks had the highest rates of using mobility devices, followed by Hispanics and then Whites. Need and enabling factors explained differences between Blacks and Whites in wheelchair use but not cane use or use of devices without personal care. Other predisposing factors explained most differences between Hispanics and Whites. Discussion. Because minorities appear to be using mobility devices in proportion to underlying need, increasing device use by minorities may not reduce disparities in mobility disability. Efforts to address racial/ethnic disparities in mobility disability in late life, therefore, may need to focus on differences in underlying functional decline rather than the accommodation of it. Race and ethnicity, Mobility device use, Older adults, Disparities SIZEABLE racial and ethnic disparities in late-life disability exist, with much higher rates reported among Blacks and those of Hispanic origin (Carrasquillo, Lantigua, & Shea, 2000; Mendes de Leon, Barnes, Bienias, Skarupski, & Evans, 2005; Schoeni, Martin, Andreski, & Freedman, 2005). Disability occurs when there is a gap between functional capability and the demands of the environment in which activities are performed (Verbrugge & Jette, 1994). Such gaps often can be reduced through the adoption of assistive technology (Agree, 1999). Indeed, a growing number of studies have suggested that assistive devices have efficacy in maintaining and improving functioning and quality of life (e.g., Mann, Ottenbacher, Fraas, Tomita, & Granger, 1999; Pew & Van Hemel, 2004; Verbrugge & Sevak, 2002) and in some cases may offer a potentially cost-effective substitute for personal care (Agree & Freedman, 2000). Understanding racial and ethnic differences in assistive device use therefore may offer important insights for addressing racial and ethnic disparities in disability. Relatively little research has focused explicitly on racial and ethnic disparities in assistive technology use, although a few studies have included race and/or ethnicity as predictors. Results from these studies are inconsistent, with some studies finding no differences in use by race (Mathieson, Jacobs Kronenfeld, & Keith, 2002; Resnik & Allen, 2006), others suggesting a disadvantage for minorities (Hartke, Prohaska, & Furner, 1998; Tomita, Mann, Fraas, & Burns, 1997), and still others finding that minorities are more likely than others to use devices (Resnik & Allen, 2006; Rubin & White-Means, 2001). Given such limited investigation into this topic, important questions remain. Of particular interest is whether older minorities use devices in proportion to their underlying need, whether they are more likely than others to experience access-related barriers to use, and whether racial/ethnic differences in device use are linked to differences in the propensity to substitute personal care with devices. The purpose of this research was to disentangle the effects of race/ethnicity, socioeconomic status, health, and functioning on the use of assistive devices by older Americans. We focused specifically on mobility-related devices, which are among the devices most commonly used by older adults (Cornman, Freedman, & Agree, 2005). We investigated three questions: (a) Are there racial/ethnic differences in the rates of mobility device use among older adults? (b) Are these differences linked to differences in rates of adopting or discontinuing the use of mobility devices or to differences in the chances of substituting devices for personal care? and (c) Do racial and ethnic differences in need and enabling factors account for differences in mobility device use in late life? Framework The Andersen behavioral framework (Andersen & Newman, 1973), which has been used in the study of long-term care, including nursing home stays (Mui & Burnette, 1994), home health care (White-Means & Rubin, 2004), and assistive device use (Hartke et al., 1998; Mathieson et al., 2002), serves as a starting point for our conceptualization. The framework suggests that the use of any form of health care is a function of predisposing, need, and enabling factors. Predisposing characteristics (e.g., sociodemographic characteristics) are factors that are exogenous to the onset of illness and contribute to an individual's inclination to use services. Need refers to an individual's health conditions and functional deficits. Enabling factors (e.g., income, health insurance) provide individuals with the means to obtain or use services. In this analysis, we depart from the Andersen model in several important ways. First, we view race/ethnicity as a predisposing factor whose relationship with device use is mediated by need and enabling factors. That is, we recognize that race and ethnicity are socially constructed categories that are useful for identifying patterns of differences in health-related behaviors. These differences emerge in part because racial and ethnic identity shapes and conditions individuals' choices, which influence need-related and enabling factors that in turn may affect mobility device use. Previous studies have shown, for example, that functional limitations are more prevalent among older Hispanics and Blacks than older Whites (Carrasquillo et al., 2000; Clark, Mungai, Stump, & Wolinsky, 1997; Mendes de Leon et al., 2005). Older minorities also report having fewer economic resources with which to purchase and replace devices (Crystal & Shea, 1990; Shea, Miles, & Hayward, 1996) and have distinctive patterns of insurance coverage, with more being dually eligible for Medicare and Medicaid (Bulatao & Anderson, 2004). In addition, minorities are less likely to use health care services, such as seeing a primary care physician (White-Means, 2000), but they are more likely to use home health care (White-Means & Rubin, 2004), both valuable means of introducing mobility devices to older adults. We further acknowledge that cultural differences in attitudes about assistive devices may be important factors in the decision to use devices (Iezzoni, 2003; Roelands, Van Oost, Depoorter, & Buysse 2002), although we were not able to examine these factors in this study. In addition, we recognize that decisions about device use are dynamic. That is, mobility device use is a function of adoption and discontinuation, and there may be racial/ethnic differences in either or both processes. Minorities, for example, are less likely to recover functioning once lost (Bryant, Shetterly, Baxter, & Hamman, 2002; Rankin, 2002) and have fewer economic means to replace devices; thus, we might expect that they discontinue device use but continue using personal care more often than others. Finally, we recognize that people make decisions about device use within a broader caregiving context (e.g., devices may be used with or without personal care; Agree, Freedman, & Sengupta, 2004). Consequently, racial and ethnic differences in mobility device use may emerge from differences in the propensity to supplement personal care with devices (i.e., to use both together) or in the propensity to substitute such devices for personal care (i.e., to use only devices). For example, at least one study has suggested that among adults aged 50 and older with mobility limitations, non-Whites but not Hispanics are more likely than others to substitute mobility devices for personal care (Agree et al., 2004). Hypotheses This framework allowed us to test a number of key hypotheses. First, because of differences in need and enabling factors described previously, on balance we expected that older minorities would be more likely than other older adults to use mobility devices. Second, we expected that minorities would be more likely to adopt but also more likely to discontinue the use of mobility devices and that we would observe higher rates of substitution (equipment use only) among non-Hispanic Blacks. Finally, we expected racial and ethnic differences in the use of these devices to be reduced once we took into account differences in need factors. However, given the complex distribution of enabling factors, we did not have an a priori hypothesis of whether controlling for enabling factors would further reduce or enhance racial differences in rates of device use. Methods Data We used data from the Health and Retirement Study (HRS), a panel study of older adults that collects information regarding decisions that affect retirement, health insurance, saving and economic well-being, and the interplay of resources and late-life health transitions. The HRS is sponsored by the National Institute on Aging (Grant NIA U01AG009740) and is conducted by the University of Michigan. We based our analyses on the sample of respondents who were aged 65 and older in 2004. Some respondents had been interviewed since 1992 or 1993, and others were first interviewed in 1998. Baseline interviews were conducted in person, and follow-up interviews (conducted every 2 years) were administered by telephone. Each respondent answered health questions, although proxy interviews were also allowed. We also used data from the RAND Corporation HRS data files, which are a cleaned, processed, and streamlined collection of variables derived from the HRS (St. Clair et al., 2007). We focused on the most recently available waves (Health and Retirement Study 2006a; Health and Retirement Study 2006b) to examine cross-sectional use in 2004 and the transitions in device use between 2002 and 2004. Analytic Samples For analyses of cross-sectional use of mobility devices, we first selected all 10,612 community-dwelling adults aged 65 and older in 2004 who were eligible to be interviewed in the 2004 wave and who completed an interview. We excluded 192 respondents who identified their race as “other” and 319 respondents who were interviewed only in 2004 (i.e., not interviewed in 2002). To check for potential bias in excluding respondents interviewed only in 2004, we reran all analyses of cross-sectional use in 2004 using a sample that included these respondents. The results (not shown) were nearly identical. Our final sample size for analyses of cross-sectional use was 10,101. We limited the analysis of adoption to the subset of the 2004 respondents who were not using devices in 2002 (n = 8,877); we limited the analysis of abandonment to the remaining respondents who were using devices in 2002 (n = 1,224). By drawing the sample in this way, we excluded respondents who died or were lost to follow-up between 2002 and 2004. With respect to loss to follow-up, there were no significant racial/ethnic differences among those who were not using devices in 2002 (the adoption sample; 3.9% of non-Hispanic Whites, 4.6% of non-Hispanic Blacks, and 3.6% of Hispanics) or among those using devices in 2002 (the sample for discontinued use; 3.7% of non-Hispanic Whites, 2.6% of non-Hispanic Blacks, and 3.1% of Hispanics). With respect to mortality, there were no significant differences in the adoption sample (4.9% of non-Hispanic Whites, 5.7% of non-Hispanic Blacks, and 3.5% of Hispanics), but among those using devices in 2002 non-Hispanic Whites were more likely than minorities to have died by 2004 (24.0% of non-Hispanic Whites, 18.1% of non-Hispanic Blacks, and 16.7% of Hispanics). It is not clear whether these differential rates of mortality by race and ethnicity biased results, because patterns of abandonment up to the point of death are unknown. Outcomes We examined racial/ethnic differences in the use, adoption, and discontinuation of use of mobility devices in the context of personal care arrangements. Respondents reported whether they used mobility devices for two indoor mobility activities (crossing a room or getting into or out of a chair), which may have excluded mobility devices used solely outdoors. Respondents also reported which devices they used. We classified respondents who reported using canes, walkers, or wheelchairs for crossing a room or getting into or out of a chair as using mobility devices. Although a few respondents (n = 30) reported using “other equipment” such as railings, orthopedic shoes, braces, prosthesis, and furniture/walls, small sample sizes precluded us from including these devices as a separate category. Finally, respondents also reported whether anyone ever helped with walking and transferring, and we classified respondents as using personal care for mobility if they reported receiving help with these activities. Note that if a respondent reported “don't know” or refused to answer questions about device use or personal care (<0.7% of cases), we assumed that he or she did not use devices or personal care. We created three outcome measures. We first analyzed a dichotomous measure that indicated whether a respondent used any mobility devices in 2004. Most of the prior literature has analyzed device use in this way. However, because both the characteristics of devices (e.g., simple devices with few moving parts like canes vs more complex devices with some degree of automation such as a wheelchair) and the means for acquiring devices (e.g., canes can be easily purchased in a drug store, whereas walkers and wheelchairs are more often paid for by insurance) differ by type of device (Agree & Freedman 2000), racial differences in device use may depend on the type of device used. We therefore also considered a three-category measure that classified the type of mobility device used in 2004: used no mobility devices; used a cane only (4 respondents also used crutches); and used walkers or wheelchairs, with or without also using a cane. Although it would have been ideal to maintain a separate category for walkers, which fall between canes and wheelchairs in terms of complexity and ease of procurement, the small numbers of respondents using walkers and wheelchairs precluded us from so doing. Finally, in order to explore racial/ethnic differences in the propensity to use mobility devices in place of personal care, we examined an expanded outcome that indicated whether a respondent, in 2004, used no assistance, mobility devices only, or any personal care (with or without devices). We attempted to further separate those using devices into groups by type of device, but small sample sizes prohibited us from maintaining this distinction in analyses involving personal care. We examined all three outcomes among the full sample (to examine cross-sectional use of devices) and among the sample of those not using devices in 2002 (to analyze adoption of devices). Analyses of discontinued device use among respondents using devices in 2002 were similar, but they differed in three ways. First, the dichotomous outcome indicated that a respondent was not using mobility devices in 2004. Second, because of small sample sizes, we did not look at the discontinued use of specific devices. Third, we examined a slightly different combination of personal care and mobility device use to allow identification of those discontinuing use but continuing personal care. Specifically, we classified individuals into those who at follow-up continued to use a mobility device, used neither devices nor personal care, or discontinued use of devices but used personal care only. Predictors We used a combined race/ethnicity variable reflecting three groups: non-Hispanic Black (Black), non-Hispanic White (White), and Hispanic. We created this variable based on two questions: Respondents were first asked whether they considered themselves Hispanic or Latino and then were asked whether they considered themselves primarily White or Caucasian, Black or African American, American Indian, Asian, or something else. (Note that the public release data files of the HRS included only a masked version of the race variable, which was coded White or Caucasian, Black or African American, and other.) Need was reflected in two sets of indicators: functional limitations and chronic conditions. Functioning was assessed using two scale indicators of the number of upper body and lower body activities with which a respondent had difficulty (Freedman, Aykan, & Kleban, 2003). Upper body limitations included having difficulty (yes or can't do) with pulling or pushing large objects, lifting or carrying weights more than 10 pounds, getting up from a chair after sitting for long periods, sitting for about 2 hours, and reaching or extending arms above shoulder level. Lower body limitations included having difficulty with stooping, kneeling, or crouching; walking several blocks; walking one block; climbing several flights of stairs without resting; and climbing one flight of stairs without resting. We also tested measures of severity of difficulty and changes in functioning between 2002 and 2004. However, results (not shown) were nearly identical, and we retained the count measures of upper and lower body limitations. Chronic conditions were measured using indicators of whether a respondent had ever been told by a doctor that he or she had ever had the following conditions: hypertension, diabetes, heart disease (including heart attack, angina, congestive heart failure, or other heart problems), stroke, and arthritis. We also included a measure of obesity based on a transformation of self-reported height and weight into body mass index, with a cutoff of body mass index ≥30. Enabling factors included three measures of economic access (income, assets, health insurance) and health care utilization, all taken from the RAND HRS files. Income was a measure of total couple income from earnings, capital, pensions/annuities, Social Security, unemployment/workman's compensation, and other government transfers. Total assets included the values of real estate (primary home and other), vehicles, businesses, individual retirement accounts, Keogh accounts, stocks, bonds, mutual funds, savings/money market accounts, and other savings. If data were missing on any component of income or assets, RAND performed a complex imputation procedure for filling in the missing data (see St. Clair et al., 2007). One or more components of income were imputed for 60% of the sample, and one or more components of total assets were imputed for 49% of the sample. For both income and assets, we used a quartile specification. We classified health insurance into four groups: Medicare alone, Medicare and Medicaid, Medicare and supplemental insurance (private, Veterans Affairs, and/or long-term care), and other insurance. Finally, we included three indicators of the use of health services in the past 2 years or since the previous interview: any overnight hospitalizations, number of visits with medical professionals, and any stays at a nursing home or long-term care facility. We also controlled for other predisposing factors that research has shown to affect choice of care arrangements, including age, gender, education, and kin availability. Measures of kin availability included marital status (married vs not married) and number of living children (0 children, 1 child, 2–3 children, 4 or more children, or missing on number of children [1.7%]). We examined three levels of education: less than high school, high school, and more than high school. Analysis We first used chi-square tests to assess whether there were statistically significant racial/ethnic differences in rates of mobility device use in 2004 and in rates of adopting and discontinuing use of mobility devices between 2002 and 2004. We then tested for racial/ethnic differences in the use, adoption, and discontinued use of devices combined with personal care. To examine whether need and enabling factors accounted for racial differences in mobility device use, we fit a series of four logistic regression models to predict any mobility device use; a series of multinomial logistic regressions to predict type of device used (no devices, cane only, wheelchair or walker); and a second set of multinomial logistic regressions to predict device use and personal care (no devices, mobility devices only, any personal care). The modeling strategy was the same for each of the three outcomes. The first model included race and ethnicity only. The second included other predisposing variables. Next we added need-related factors to determine whether the relationship between race and ethnicity and mobility device use changed when need was controlled. Finally, we ran a model that included race, predisposing, need, and enabling characteristics to examine, over and above the effects of differences in need, whether economic factors exacerbated or attenuated racial/ethnic differences in use. Because we were primarily interested in explaining the racial/ethnic differences in these outcomes, we present only the odds ratios (ORs) for the race/ethnicity effect from each model. (Full models are available upon request.) There are no formal statistical tests for assessing whether mediating factors account for the relationship between race/ethnicity and device use. However, if they do, results should show a substantial change in the size of the race or ethnicity OR, a change in direction of the race or ethnicity OR, or a change in significance of the race or ethnicity OR. We also performed F tests to test for the significance of each set of factors added to the models. We weighted all analyses and adjusted them for the complex sample design of the HRS; we performed analyses using Stata Version 9 statistical software. Note that we also tested whether need and enabling factors explained racial/ethnic differences in the adoption of devices and found that results were nearly identical to results for the cross-sectional use of devices. Hence, we do not present the results for adoption. Small sample sizes precluded us from modeling the discontinued use of mobility devices. Results Racial Differences in Device Use Black elders had the highest rates of using any mobility device (24.9%), followed by Hispanics (19.4%) and Whites (15.3%; see Table 1). Black elders were nearly twice as likely as White elders to be using a cane only. Although the difference was not as large, Blacks were also more likely than Whites to be using any wheelchair or walker (11.5% vs 8.2%, respectively). Although Hispanic elders were also more likely than White elders to be using canes and wheelchairs or walkers, the gap between these two groups was much smaller. When we considered a combination of mobility devices and personal care, a similar picture emerged. For example, 19.6% of Blacks, 15.0% of Hispanics, and 12.7% of Whites used only devices. Blacks were also the most likely to be using personal care, either alone or combined with devices. Rates of adopting devices, but not discontinuing use, differed by race and ethnicity (see Table 2). Among those not using a mobility device in 2002, minorities, particularly Blacks, were significantly more likely than Whites to start using a mobility device by 2004, generally using the device alone rather than combined with personal care. Overall, 11.8% of Blacks and 7.9% of Hispanics compared to 7.5% of Whites who were not using mobility devices in 2002 started to use such devices in 2004. Racial/ethnic differences in adoption of devices were primarily accounted for by the higher rates of Blacks starting to use canes. There were, however, no significant differences in rates of discontinued use, with approximately 18% to 23% of Whites, Blacks, and Hispanics no longer using devices in 2004 that were used in 2002. Although there were no significant racial differences in discontinuing device use, 3.4% of Blacks but only 1.2% of Whites who used a device in 2002 used only personal care in 2004 (second to the last row, Table 2). Role of Predisposing, Need, and Enabling Factors Minority elders had more functional need than Whites, had fewer economic resources, were more likely to be dually eligible for Medicare and Medicaid, and were less likely to have supplemental insurance (results not shown). We turn next to whether these differences in need and enabling factors accounted for racial differences in the use of mobility devices. As shown in Table 3, Blacks and Hispanics were significantly more likely than Whites to use any mobility device (ORs = 1.83 and 1.33, respectively; Model 1). Including the other predisposing factors reduced the size of the OR for Blacks to 1.70 (Model 2), although the difference between Blacks and Whites remained significant. For Hispanics, the OR was reduced to 1.19 and was no longer statistically significant. When we controlled for both predisposing and need factors, the OR for Blacks was further reduced to 1.53 (Model 3). The gap in device use between Blacks and Whites became even smaller when we added enabling factors (OR = 1.42; Model 4). However, in all models, the difference between Blacks and Whites remained statistically significant. Although predisposing, need, and enabling factors accounted for some of the differences between Blacks and Whites in the use of canes only, the differences remained statistically significant when all factors were controlled. Need and enabling factors, however, accounted for the differences between Blacks and Whites in the use of walkers and wheelchairs. The OR for Blacks versus Whites in the simple model that included race only was 1.58 (Model 1) and was reduced to 1.45 (Model 2) when other predisposing factors were added, although the racial difference remained significant. Adding need factors further reduced the OR to 1.23 (Model 3); adding enabling factors reduced it to 1.12 (Model 4). The difference between Blacks and Whites was not statistically significant in these last two models. When we extended the outcome to include both mobility devices and personal care (the last two columns of Table 3), two patterns emerged as noteworthy. First, predisposing, need, and enabling factors did not fully account for Blacks' increased propensity to use mobility devices without personal care (OR for Blacks was 1.44 in Model 4 vs 1.77 in Model 1). Second, enabling factors, but not need factors, accounted for differences between Hispanics and Whites in the use of devices combined with personal care. When we added enabling factors to the models, the OR for Hispanics was reduced from 1.87 (Model 3) to 1.55 (Model 4) and was no longer significant. Discussion In this study, we investigated whether there are differences by race and ethnicity in rates of mobility device use; whether these differences are linked to racial differences in rates of adopting and discontinuing use of mobility devices or to differences in substitution of devices for personal care; and, finally, whether racial and ethnic differences in need and enabling factors account for differences in mobility device use. We found that minority elders had higher rates of mobility device use, especially cane use, than White elders and that this difference was largely due to the fact that minorities, Blacks in particular, had higher rates of adopting mobility devices during the period of study. There were no racial or ethnic differences, however, in rates of discontinuing use. Furthermore, Blacks but not Hispanics were more likely than Whites to adopt devices alone (i.e., without personal care). We also found that predisposing, need, and enabling factors accounted for some of the racial and ethnic differences in mobility device use. In particular, need and enabling factors seemed to fully account for differences between Black and White elders in the use of walkers and wheelchairs, but not canes or the propensity to substitute devices for personal care. Although other predisposing factors explained most differences between Hispanics and Whites, enabling factors accounted for differences between these groups in the use of mobility devices with personal care, which favored minorities. In analyses not shown, this latter finding was linked to the high rates of dual eligibility for Medicare and Medicaid among minority elders. That is, higher rates of using personal care with mobility devices among minorities were linked to higher rates of Medicaid coverage, which funds both formal care and mobility devices. That need and enabling factors accounted for racial differences in the use and adoption of wheelchairs and/or walkers suggests that Black elders appear to be able to secure such devices when first needed. However, although the racial and ethnic differences in discontinued use of mobility devices were not statistically significant, minority elders, specifically Black elders, who were using devices at the beginning of the study period were more likely than White elders to be using personal care without devices at the end of the period. Black elders, therefore, may discontinue the use of mobility devices at rates that are higher than their rates of recovery. In other words, they may be more likely to stop using mobility devices while there is still a need for help. This result could reflect the possibility that Black elders are less likely to recover from lower body limitations or that minority elders have fewer resources to replace devices as needed. Although we were unable to identify in this analysis reasons for discontinued use, this finding warrants further investigation into the relationship between race and ethnicity, recovery, and mobility device use. Enabling factors emerged as an explanation for higher rates of use among Black older adults, particularly for complex devices. Whereas canes are relatively inexpensive and readily available at local drug stores, more complex devices such as wheelchairs and walkers are generally prescribed and more likely to be fully covered for those dually eligible for Medicare and Medicaid, insurance coverage much more common among minority elders. Had we examined other types of devices such as home modifications, the effects of the enabling factors may have been different. Rubin and White-Means (2001), for example, reported that, to accommodate their disabilities, Black older adults were more likely to use portable assistive devices and White older adults were more likely to use home modifications, which are less likely to be covered by insurance. Our study has several limitations. First, the 2-year data collection interval necessarily may miss respondents who adopted or discontinued use of devices multiple times within the interval and, therefore, may lead to underestimated rates of starting and stopping mobility device use. Second, our sample of Hispanic elders and the sample used for analyses of discontinued use were relatively small. As such, we may not have had the power to detect significant ethnic differences in patterns of device use or differences in discontinued use. Finally, our data did not allow us to control for racial differences in health beliefs, attitudes toward devices, preferences, and other psychosocial factors that research has shown to be important predictors of device use (Iezzoni, 2003; Roelands et al., 2002). Several smaller scale qualitative studies have reported that although older adults recognize the benefits of the use of canes and other mobility devices (including improvements in and ease of performing mobility tasks and an increased sense of security and safety) and even accept their use as functional impairment threatens safety, older adults also associate the use of canes and other mobility devices with negative psychological consequences such as feeling old, losing their abilities, looking handicapped, and losing their independence (Aminzadeh & Edwards, 2000; Copolillo, 2001; Copolillo, Collins, Randall, & Cash, 2002). Although racial differences in these attitudes and beliefs have not been previously examined, the persistent differences between Blacks and Whites in the use of canes observed in our study may be a reflection of racial differences in the balance between the benefits of cane use and the negative attitudes and beliefs about what using a cane symbolizes. Although it appears that older minorities are obtaining devices in relation to their need and are not facing access-related barriers, these individuals continue to experience higher rates of mobility difficulty. In the context of the disablement process advanced by the Institute of Medicine (1991), minorities are more likely to experience acute and chronic diseases that lead to differentials in impairments and functional difficulties (Kington & Smith, 1997). By reducing the gap between environmental demands and functional capacity, assistive technology may reduce racial gaps in disability (Agree, 1999). This study suggests that because minorities appear to be using mobility devices in proportion to underlying need, further increases in the rate of mobility device use by minorities may not reduce racial gaps in mobility disability. Efforts to address racial disparities in mobility disability in late life, therefore, may need to focus on racial disparities in earlier stages of the disablement process, such as chronic diseases or aspects of the environment that impede mobility. Decision Editor: Kenneth F. Ferraro, PhD Table 1. Mobility Device Use by Race and Ethnicity in 2004. Variable . Total . White Non-Hispanic . Black Non-Hispanic . Hispanic . pa . Mobility device use     Uses any mobility device 16.2 15.3 24.9 19.4 .0000 Mobility device use by type of device     Uses a cane only 7.7 7.1 13.4 8.9 .0000     Uses walkers/wheelchairsb 8.6 8.2 11.5 10.5 Mobility device use and personal care     Uses neither mobility devices nor personal care 83.2 84.3 73.7 79.4 .0000     Use only mobility devices 13.4 12.7 19.6 15.0     Uses personal care only 0.6 0.5 1.5 1.3     Uses mobility devices and personal care 2.9 2.6 5.2 4.4 N 10,101 7,985 1,314 802 Variable . Total . White Non-Hispanic . Black Non-Hispanic . Hispanic . pa . Mobility device use     Uses any mobility device 16.2 15.3 24.9 19.4 .0000 Mobility device use by type of device     Uses a cane only 7.7 7.1 13.4 8.9 .0000     Uses walkers/wheelchairsb 8.6 8.2 11.5 10.5 Mobility device use and personal care     Uses neither mobility devices nor personal care 83.2 84.3 73.7 79.4 .0000     Use only mobility devices 13.4 12.7 19.6 15.0     Uses personal care only 0.6 0.5 1.5 1.3     Uses mobility devices and personal care 2.9 2.6 5.2 4.4 N 10,101 7,985 1,314 802 Notes: Data are weighted percentages and unweighted Ns. ap-value is for a modified chi-square test that is adjusted for survey design. bRespondents may also use a cane. Open in new tab Table 1. Mobility Device Use by Race and Ethnicity in 2004. Variable . Total . White Non-Hispanic . Black Non-Hispanic . Hispanic . pa . Mobility device use     Uses any mobility device 16.2 15.3 24.9 19.4 .0000 Mobility device use by type of device     Uses a cane only 7.7 7.1 13.4 8.9 .0000     Uses walkers/wheelchairsb 8.6 8.2 11.5 10.5 Mobility device use and personal care     Uses neither mobility devices nor personal care 83.2 84.3 73.7 79.4 .0000     Use only mobility devices 13.4 12.7 19.6 15.0     Uses personal care only 0.6 0.5 1.5 1.3     Uses mobility devices and personal care 2.9 2.6 5.2 4.4 N 10,101 7,985 1,314 802 Variable . Total . White Non-Hispanic . Black Non-Hispanic . Hispanic . pa . Mobility device use     Uses any mobility device 16.2 15.3 24.9 19.4 .0000 Mobility device use by type of device     Uses a cane only 7.7 7.1 13.4 8.9 .0000     Uses walkers/wheelchairsb 8.6 8.2 11.5 10.5 Mobility device use and personal care     Uses neither mobility devices nor personal care 83.2 84.3 73.7 79.4 .0000     Use only mobility devices 13.4 12.7 19.6 15.0     Uses personal care only 0.6 0.5 1.5 1.3     Uses mobility devices and personal care 2.9 2.6 5.2 4.4 N 10,101 7,985 1,314 802 Notes: Data are weighted percentages and unweighted Ns. ap-value is for a modified chi-square test that is adjusted for survey design. bRespondents may also use a cane. Open in new tab Table 2. Rates of Adoption and Discontinuation of Mobility Device Use 2002–2004 by Race and Ethnicity. . Total . White Non-Hispanic . Black Non-Hispanic . Hispanic . pa . Adopt Any Mobility Device     Among those not using mobility devices in 2002, percent using any mobility device in 2004 7.8 7.5 11.8 7.9 .0003 Adopt Mobility Devices by Type of Device     Among those not using mobility devices in 2002, percent.....         using a cane only in 2004 4.4 4.2 7.9 4.2 .0004         using walkers/wheelchairs in 2004b 3.3 3.3 3.9 3.7 Adopt Mobility Devices and Personal Care     Among those not using any mobility devices in 2002, percent.....         using mobility devices only in 2004 6.9 6.6 10.3 7.0 .0001         using personal care and/or mobility devices 2004 1.4 1.2 2.5 2.4     N 8,877 7,130 1,061 686 Discontinue Use of Mobility Devices     Among those using mobility devices in 2002, percent not using any mobility device in 2004 20.9 20.9 22.8 17.7 .6313 Discontinue Use of Mobility Devices and Personal Care Among those using any mobility devices in 2002, percent.....         not using any mobility devices or personal care in 2004 19.5 19.7 19.4 17.7 .1904         not using any mobility device but using personal care in 2004 1.4 1.2 3.4 0.0     N 1,224 855 253 116 . Total . White Non-Hispanic . Black Non-Hispanic . Hispanic . pa . Adopt Any Mobility Device     Among those not using mobility devices in 2002, percent using any mobility device in 2004 7.8 7.5 11.8 7.9 .0003 Adopt Mobility Devices by Type of Device     Among those not using mobility devices in 2002, percent.....         using a cane only in 2004 4.4 4.2 7.9 4.2 .0004         using walkers/wheelchairs in 2004b 3.3 3.3 3.9 3.7 Adopt Mobility Devices and Personal Care     Among those not using any mobility devices in 2002, percent.....         using mobility devices only in 2004 6.9 6.6 10.3 7.0 .0001         using personal care and/or mobility devices 2004 1.4 1.2 2.5 2.4     N 8,877 7,130 1,061 686 Discontinue Use of Mobility Devices     Among those using mobility devices in 2002, percent not using any mobility device in 2004 20.9 20.9 22.8 17.7 .6313 Discontinue Use of Mobility Devices and Personal Care Among those using any mobility devices in 2002, percent.....         not using any mobility devices or personal care in 2004 19.5 19.7 19.4 17.7 .1904         not using any mobility device but using personal care in 2004 1.4 1.2 3.4 0.0     N 1,224 855 253 116 Notes: Data are weighted percentages and unweighted Ns. ap-value is for a modified chi-square test that is adjusted for survey design. bRespondents may also use a cane. Open in new tab Table 2. Rates of Adoption and Discontinuation of Mobility Device Use 2002–2004 by Race and Ethnicity. . Total . White Non-Hispanic . Black Non-Hispanic . Hispanic . pa . Adopt Any Mobility Device     Among those not using mobility devices in 2002, percent using any mobility device in 2004 7.8 7.5 11.8 7.9 .0003 Adopt Mobility Devices by Type of Device     Among those not using mobility devices in 2002, percent.....         using a cane only in 2004 4.4 4.2 7.9 4.2 .0004         using walkers/wheelchairs in 2004b 3.3 3.3 3.9 3.7 Adopt Mobility Devices and Personal Care     Among those not using any mobility devices in 2002, percent.....         using mobility devices only in 2004 6.9 6.6 10.3 7.0 .0001         using personal care and/or mobility devices 2004 1.4 1.2 2.5 2.4     N 8,877 7,130 1,061 686 Discontinue Use of Mobility Devices     Among those using mobility devices in 2002, percent not using any mobility device in 2004 20.9 20.9 22.8 17.7 .6313 Discontinue Use of Mobility Devices and Personal Care Among those using any mobility devices in 2002, percent.....         not using any mobility devices or personal care in 2004 19.5 19.7 19.4 17.7 .1904         not using any mobility device but using personal care in 2004 1.4 1.2 3.4 0.0     N 1,224 855 253 116 . Total . White Non-Hispanic . Black Non-Hispanic . Hispanic . pa . Adopt Any Mobility Device     Among those not using mobility devices in 2002, percent using any mobility device in 2004 7.8 7.5 11.8 7.9 .0003 Adopt Mobility Devices by Type of Device     Among those not using mobility devices in 2002, percent.....         using a cane only in 2004 4.4 4.2 7.9 4.2 .0004         using walkers/wheelchairs in 2004b 3.3 3.3 3.9 3.7 Adopt Mobility Devices and Personal Care     Among those not using any mobility devices in 2002, percent.....         using mobility devices only in 2004 6.9 6.6 10.3 7.0 .0001         using personal care and/or mobility devices 2004 1.4 1.2 2.5 2.4     N 8,877 7,130 1,061 686 Discontinue Use of Mobility Devices     Among those using mobility devices in 2002, percent not using any mobility device in 2004 20.9 20.9 22.8 17.7 .6313 Discontinue Use of Mobility Devices and Personal Care Among those using any mobility devices in 2002, percent.....         not using any mobility devices or personal care in 2004 19.5 19.7 19.4 17.7 .1904         not using any mobility device but using personal care in 2004 1.4 1.2 3.4 0.0     N 1,224 855 253 116 Notes: Data are weighted percentages and unweighted Ns. ap-value is for a modified chi-square test that is adjusted for survey design. bRespondents may also use a cane. Open in new tab Table 3. Effects of Race and Ethnicity on the Use of Mobility Devices Controlling for Predisposing, Need, and Enabling Factors (N = 10,101). . . Mobility Device Use by Type of Devicea . . Mobility Device Use and Personal Carea . . Model . Uses any Device (vs No Device)b . Canes Only (vs No Device) . Walkers and/or Wheelchairsc (vs No Device) . Devices Only (vs No Devices or Personal Care) . Personal Care or Devices (vs No Devices or Personal Care) . Model 1: Race     Non-Hispanic Blackd 1.83** (1.52–2.21) 2.12** (1.74–2.59) 1.58** (1.18–2.12) 1.77** (1.48–2.12) 2.53** (1.64–3.90)     Hispanicd 1.33* (1.03–1.71) 1.31 (0.94–1.82) 1.35 (1.00–1.82) 1.25 (0.97–1.61) 1.96** (1.39–2.78)     Fe 24.61** 28.29** 7.42** 20.79** 16.52**     df 2, 51 2, 51 2, 51 2, 51 2, 51 Model 2: Race and predisposing factorsf     Non-Hispanic Blackd 1.70** (1.38–2.09) 1.98** (1.62–2.43) 1.45* (1.04–2.01) 1.61** (1.30–1.99) 2.25** (1.42–3.58)     Hispanicd 1.19 (0.92–1.53) 1.17 (0.85–1.61) 1.21 (0.87–1.68) 1.13 (0.86–1.48) 1.49* (1.07–2.07)     Fe 64.74** 26.55** 46.65** 68.28** 40.29**     df 12, 41 12, 41 12, 41 12, 41 12, 41 Model 3: Race, predisposing, and need factorsg     Non-Hispanic Blackd 1.53** (1.21–1.94) 1.81** (1.46–2.23) 1.23 (0.84–1.79) 1.55** (1.21–2.00) 2.17** (1.22–3.84)     Hispanicd 1.26 (0.94–1.69) 1.25 (0.88–1.79) 1.28 (0.89–1.85) 1.26 (0.93–1.72) 1.87** (1.23–2.86)     Fe 240.18** 176.72** 81.09** 187.88** 55.37**     df 8, 45 8, 45 8, 45 8, 45 8, 45 Model 4: Race, predisposing, need, and enabling factorsh     Non-Hispanic Blackd 1.42** (1.10–1.85) 1.68** (1.32–2.14) 1.12 (0.75–1.67) 1.44* (1.08–1.92) 2.00* (1.09–3.70)     Hispanicd 1.10 (0.80–1.51) 1.12 (0.77–1.64) 1.08 (0.71–1.65) 1.10 (0.78–1.54) 1.55 (0.97–2.49)     Fe 5.18** 2.16* 7.07** 5.45** 7.77**     df 12, 41 12, 41 12, 41 12, 41 12, 41 . . Mobility Device Use by Type of Devicea . . Mobility Device Use and Personal Carea . . Model . Uses any Device (vs No Device)b . Canes Only (vs No Device) . Walkers and/or Wheelchairsc (vs No Device) . Devices Only (vs No Devices or Personal Care) . Personal Care or Devices (vs No Devices or Personal Care) . Model 1: Race     Non-Hispanic Blackd 1.83** (1.52–2.21) 2.12** (1.74–2.59) 1.58** (1.18–2.12) 1.77** (1.48–2.12) 2.53** (1.64–3.90)     Hispanicd 1.33* (1.03–1.71) 1.31 (0.94–1.82) 1.35 (1.00–1.82) 1.25 (0.97–1.61) 1.96** (1.39–2.78)     Fe 24.61** 28.29** 7.42** 20.79** 16.52**     df 2, 51 2, 51 2, 51 2, 51 2, 51 Model 2: Race and predisposing factorsf     Non-Hispanic Blackd 1.70** (1.38–2.09) 1.98** (1.62–2.43) 1.45* (1.04–2.01) 1.61** (1.30–1.99) 2.25** (1.42–3.58)     Hispanicd 1.19 (0.92–1.53) 1.17 (0.85–1.61) 1.21 (0.87–1.68) 1.13 (0.86–1.48) 1.49* (1.07–2.07)     Fe 64.74** 26.55** 46.65** 68.28** 40.29**     df 12, 41 12, 41 12, 41 12, 41 12, 41 Model 3: Race, predisposing, and need factorsg     Non-Hispanic Blackd 1.53** (1.21–1.94) 1.81** (1.46–2.23) 1.23 (0.84–1.79) 1.55** (1.21–2.00) 2.17** (1.22–3.84)     Hispanicd 1.26 (0.94–1.69) 1.25 (0.88–1.79) 1.28 (0.89–1.85) 1.26 (0.93–1.72) 1.87** (1.23–2.86)     Fe 240.18** 176.72** 81.09** 187.88** 55.37**     df 8, 45 8, 45 8, 45 8, 45 8, 45 Model 4: Race, predisposing, need, and enabling factorsh     Non-Hispanic Blackd 1.42** (1.10–1.85) 1.68** (1.32–2.14) 1.12 (0.75–1.67) 1.44* (1.08–1.92) 2.00* (1.09–3.70)     Hispanicd 1.10 (0.80–1.51) 1.12 (0.77–1.64) 1.08 (0.71–1.65) 1.10 (0.78–1.54) 1.55 (0.97–2.49)     Fe 5.18** 2.16* 7.07** 5.45** 7.77**     df 12, 41 12, 41 12, 41 12, 41 12, 41 Notes: Data are odds ratios (95% confidence intervals), except where indicated. aFrom multinomial logistic regression models. bFrom logistic regression models. cRespondents may also use a cane. dNon-Hispanic White is the omitted category. eF tests test for the significance of the block of variables added to the previous model. For Model 1, this is the null model. fPredisposing factors include age, gender, education, marital status, and number of living children. gNeed factors include number of upper body and lower body limitations and several chronic conditions (ever had hypertension, diabetes, heart disease, stroke, and/or arthritis). hEnabling factors include income, assets, health insurance, and health care utilization (in the past 2 years, any overnight hospitalizations, number of visits with medical professionals, and any stays at a nursing home or long-term care facility). *p <.05; **p <.01. Open in new tab Table 3. Effects of Race and Ethnicity on the Use of Mobility Devices Controlling for Predisposing, Need, and Enabling Factors (N = 10,101). . . Mobility Device Use by Type of Devicea . . Mobility Device Use and Personal Carea . . Model . Uses any Device (vs No Device)b . Canes Only (vs No Device) . Walkers and/or Wheelchairsc (vs No Device) . Devices Only (vs No Devices or Personal Care) . Personal Care or Devices (vs No Devices or Personal Care) . Model 1: Race     Non-Hispanic Blackd 1.83** (1.52–2.21) 2.12** (1.74–2.59) 1.58** (1.18–2.12) 1.77** (1.48–2.12) 2.53** (1.64–3.90)     Hispanicd 1.33* (1.03–1.71) 1.31 (0.94–1.82) 1.35 (1.00–1.82) 1.25 (0.97–1.61) 1.96** (1.39–2.78)     Fe 24.61** 28.29** 7.42** 20.79** 16.52**     df 2, 51 2, 51 2, 51 2, 51 2, 51 Model 2: Race and predisposing factorsf     Non-Hispanic Blackd 1.70** (1.38–2.09) 1.98** (1.62–2.43) 1.45* (1.04–2.01) 1.61** (1.30–1.99) 2.25** (1.42–3.58)     Hispanicd 1.19 (0.92–1.53) 1.17 (0.85–1.61) 1.21 (0.87–1.68) 1.13 (0.86–1.48) 1.49* (1.07–2.07)     Fe 64.74** 26.55** 46.65** 68.28** 40.29**     df 12, 41 12, 41 12, 41 12, 41 12, 41 Model 3: Race, predisposing, and need factorsg     Non-Hispanic Blackd 1.53** (1.21–1.94) 1.81** (1.46–2.23) 1.23 (0.84–1.79) 1.55** (1.21–2.00) 2.17** (1.22–3.84)     Hispanicd 1.26 (0.94–1.69) 1.25 (0.88–1.79) 1.28 (0.89–1.85) 1.26 (0.93–1.72) 1.87** (1.23–2.86)     Fe 240.18** 176.72** 81.09** 187.88** 55.37**     df 8, 45 8, 45 8, 45 8, 45 8, 45 Model 4: Race, predisposing, need, and enabling factorsh     Non-Hispanic Blackd 1.42** (1.10–1.85) 1.68** (1.32–2.14) 1.12 (0.75–1.67) 1.44* (1.08–1.92) 2.00* (1.09–3.70)     Hispanicd 1.10 (0.80–1.51) 1.12 (0.77–1.64) 1.08 (0.71–1.65) 1.10 (0.78–1.54) 1.55 (0.97–2.49)     Fe 5.18** 2.16* 7.07** 5.45** 7.77**     df 12, 41 12, 41 12, 41 12, 41 12, 41 . . Mobility Device Use by Type of Devicea . . Mobility Device Use and Personal Carea . . Model . Uses any Device (vs No Device)b . Canes Only (vs No Device) . Walkers and/or Wheelchairsc (vs No Device) . Devices Only (vs No Devices or Personal Care) . Personal Care or Devices (vs No Devices or Personal Care) . Model 1: Race     Non-Hispanic Blackd 1.83** (1.52–2.21) 2.12** (1.74–2.59) 1.58** (1.18–2.12) 1.77** (1.48–2.12) 2.53** (1.64–3.90)     Hispanicd 1.33* (1.03–1.71) 1.31 (0.94–1.82) 1.35 (1.00–1.82) 1.25 (0.97–1.61) 1.96** (1.39–2.78)     Fe 24.61** 28.29** 7.42** 20.79** 16.52**     df 2, 51 2, 51 2, 51 2, 51 2, 51 Model 2: Race and predisposing factorsf     Non-Hispanic Blackd 1.70** (1.38–2.09) 1.98** (1.62–2.43) 1.45* (1.04–2.01) 1.61** (1.30–1.99) 2.25** (1.42–3.58)     Hispanicd 1.19 (0.92–1.53) 1.17 (0.85–1.61) 1.21 (0.87–1.68) 1.13 (0.86–1.48) 1.49* (1.07–2.07)     Fe 64.74** 26.55** 46.65** 68.28** 40.29**     df 12, 41 12, 41 12, 41 12, 41 12, 41 Model 3: Race, predisposing, and need factorsg     Non-Hispanic Blackd 1.53** (1.21–1.94) 1.81** (1.46–2.23) 1.23 (0.84–1.79) 1.55** (1.21–2.00) 2.17** (1.22–3.84)     Hispanicd 1.26 (0.94–1.69) 1.25 (0.88–1.79) 1.28 (0.89–1.85) 1.26 (0.93–1.72) 1.87** (1.23–2.86)     Fe 240.18** 176.72** 81.09** 187.88** 55.37**     df 8, 45 8, 45 8, 45 8, 45 8, 45 Model 4: Race, predisposing, need, and enabling factorsh     Non-Hispanic Blackd 1.42** (1.10–1.85) 1.68** (1.32–2.14) 1.12 (0.75–1.67) 1.44* (1.08–1.92) 2.00* (1.09–3.70)     Hispanicd 1.10 (0.80–1.51) 1.12 (0.77–1.64) 1.08 (0.71–1.65) 1.10 (0.78–1.54) 1.55 (0.97–2.49)     Fe 5.18** 2.16* 7.07** 5.45** 7.77**     df 12, 41 12, 41 12, 41 12, 41 12, 41 Notes: Data are odds ratios (95% confidence intervals), except where indicated. aFrom multinomial logistic regression models. bFrom logistic regression models. cRespondents may also use a cane. dNon-Hispanic White is the omitted category. eF tests test for the significance of the block of variables added to the previous model. For Model 1, this is the null model. fPredisposing factors include age, gender, education, marital status, and number of living children. gNeed factors include number of upper body and lower body limitations and several chronic conditions (ever had hypertension, diabetes, heart disease, stroke, and/or arthritis). hEnabling factors include income, assets, health insurance, and health care utilization (in the past 2 years, any overnight hospitalizations, number of visits with medical professionals, and any stays at a nursing home or long-term care facility). *p <.05; **p <.01. Open in new tab This research was funded by Grant R03 AG026110 from the National Institute on Aging. The views expressed are ours alone and not those of our institutions or the funding agency. We thank Emily Agree and Lisa Iezzoni for helpful suggestions. Both Jennifer C. Cornman and Vicki A. Freedman conceptualized and planned the study, and both contributed to the writing and revising of the article. 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TI - Racial and Ethnic Disparities in Mobility Device Use in Late Life
JF - The Journals of Gerontology Series B: Psychological Sciences and Social Sciences
DO - 10.1093/geronb/63.1.S34
DA - 2008-01-01
UR - https://www.deepdyve.com/lp/oxford-university-press/racial-and-ethnic-disparities-in-mobility-device-use-in-late-life-kQ0QXHSTyh
SP - S34
VL - 63
IS - 1
DP - DeepDyve
ER -