Perceived Benefits of Using Complementary and Alternative Medicine by Race/Ethnicity Among Midlife and Older Adults in the United States

Abstract

Objective: To describe, for a national sample of midlife and older adults, the types of complementary and alternative medicine (CAM) used for health and wellness and the perceived benefits of CAM use by race/ethnicity. Method: Using data from the 2012 National Health Interview Survey, we ran multiple logistic regression models to estimate the odds of each perceived benefit among adults ages 50 and older. Results: More than 38% of midlife and older adults used CAM in the past year. For six of seven perceived benefits examined, we found significant differences by race/ethnicity, with each group having higher odds of two or more perceived benefits compared with non-Hispanic Whites. Discussion: Although racial/ethnic minority groups are less likely to use CAM compared with non-Hispanic Whites, those who use CAM perceive great benefit. Future research should examine the potential contribution of evidence-based CAM to promoting health and well-being in a diverse aging population.

Keywords

complementary therapies healthy aging midlife race/ethnicity well-being

Introduction

Nearly 20% of the U.S. population is midlife (ages 50 to 64), a group at high risk for future disease and disability. Some 70% of U.S. adults reach age 60 with at least one chronic condition, and more than half have two or more (Smolka, Purvis, & Figueiredo, 2009). The burden of chronic disease falls disproportionately on communities of color and the socially disadvantaged, as they are more exposed to social stressors that can compromise health, accelerate aging, and reduce quality of life (Hill, Perez-Stable, Anderson, & Bernard, 2015; National Center for Chronic Disease Prevention and Health Promotion, 2015). There is a critical need to identify factors that maximize wellness for diverse midlife and older adults during this important window of opportunity, when lifestyle changes may still contribute to healthy aging.

Complementary and alternative medicine (CAM) such as chiropractic, yoga, nutritional supplements, and meditation are now used by 33% of all U.S. adults, 37% of adults 45 to 64 years, and 29% of those 65 and older (Clarke, Black, Stussman, Barnes, & Nahin, 2015). Prevalence of individual types of CAM used in the past year varies. The most commonly used types are nonvitamin/nonmineral dietary supplements (18%), deep-breathing exercises as a part of another practice such as meditation, yoga, or guided imagery (11%), and the grouping of yoga, tai chi, or qi gong (10%). Some modalities are used infrequently, such as energy healing, naturopathy, hypnosis, biofeedback and Ayurveda, all of which were used by less than 1% of U.S. adults (Clarke et al., 2015). In addition to accessing needed health care and adopting health-promoting behaviors, using CAM may encourage midlife adults to support their health and well-being, motivate pursuit of other health behaviors, help manage stress, and contribute to a salutary health trajectory into older age.

Growing evidence supports the efficacy of CAM for specific health conditions, and recent studies document increased use of CAM for general wellness (Arcury et al., 2015; Davis, West, Weeks, & Sirovich, 2011; Grzywacz et al., 2005; Grzywacz et al., 2007; Johnson, Jou, Rhee, Rockwood, & Upchurch, 2016; Upchurch & Rainisch, 2015). Yet, population estimates from national surveys consistently indicate that CAM are used less by racial/ethnic minorities (Barnes, Bloom, & Nahin, 2008; Graham et al., 2005; Kronenberg, Cushman, Wade, Kalmuss, & Chao, 2006). Many CAM address balance in physical, mental, and spiritual aspects of one’s life and have origins in various cultural traditions (Engebretson, 2002; Struthers, Eschiti, & Patchell, 2004); as such, they provide additional opportunities for lifestyle intervention in diverse groups. CAM may also provide a form of self-care for racial/ethnic minorities, who are more likely to encounter discrimination or other negative experiences within the conventional medical system (Shippee et al., 2013; Shippee, Schafer, & Ferraro, 2012). In addition, CAM modalities that can be practiced individually or without a provider may be more accessible to socially or economically disadvantaged individuals. Assessing current patterns of CAM use and its perceived benefits in diverse racial/ethnic groups is a crucial first step toward identifying populations for whom greater access to CAM could provide the most benefit.

The objective of this study was to examine the use of CAM, as well as the perceived benefits of using CAM, among a national sample of midlife and older U.S. adults and to identify differences across race/ethnicity groups. Specifically, we sought to answer the following research questions:

Research Question 1: How do characteristics of midlife and older adult CAM users differ by race/ethnicity?

Research Question 2: How does the use of specific types of CAM differ by race/ethnicity?

Research Question 3: What are the perceived benefits of using CAM among midlife and older adults by race/ethnicity?

Method

Data Source and Sample

We used 2012 National Health Interview Survey (NHIS) data for adults ages 50 and older (n = 14,849 unweighted) to examine CAM use and perceived benefits of CAM use by race/ethnicity. The NHIS is an annual household survey of the health and health care of the U.S. noninstitutionalized, civilian population (Gentleman & Pleis, 2002). In addition, the NHIS includes an alternative health supplement fielded every 5 years. The 2012 data are the most current nationally representative data available on complementary and alternative health practices in the United States. The NHIS uses a multistage probability sample design with clustering and stratification, and the sample is drawn so that data analyzed using the sampling weights are representative of the U.S. population (National Center for Health Statistics, 2013).

Measures

CAM use

Types of CAM represent past year use of any of 35 of 36 types reported in the NHIS (excluding multivitamin/mineral supplement use; see the appendix; Barnes et al., 2008; Clarke et al., 2015). Indicator variables for the specific types of CAM used in the past year were created for each of the 35 types. For presentation, six specific traditional healers, four types of movement therapies, three types of meditation, and five specific diets were collapsed by category. Number of CAM used was calculated from reports for each of the 35 types. Specific types of CAM are organized according to whether each is provider-, product-, or practice-based (Upchurch & Wexler Rainisch, 2013).

Reason for use

NHIS also asks respondents to identify up to three CAM used in the past year perceived as being most important to their health. For each of these CAM types, respondents were asked whether it was used: to improve energy, for general wellness, to enhance immune function, to improve athletic or sports performance, or to improve memory. We aggregated “yes” responses for any of these five reasons to create an indicator variable representing past year use of CAM for wellness. Respondents were also asked whether each CAM type was used to treat one or more specific health problems, symptoms, or conditions. We aggregated “yes” responses to create an indicator variable representing past year use of CAM for treatment. Using the two indicator variables, we created a categorical response to classify each respondent as having used CAM for wellness only, for treatment only, or for a combination of wellness and treatment (Upchurch & Rainisch, 2015).

Benefits of CAM

Outcomes of interest were indicators of perceived benefit of using CAM. For each of the top three CAM used in the past year, respondents were asked whether or not each CAM type provided each of seven specific benefits, including the following: (a) better sense of control over health, (b) reduced stress/relaxation, (c) better sleep, (d) feeling better emotionally, (e) made it easier to cope with health problems, (f) improved overall health/feeling better, and (g) improved relationships.

Race/ethnicity

Race and ethnicity were based on self-report and classified according to the U.S. Office of Management and Budget (OMB) groupings of each single race: White only, Black only, American Indian/Alaska Native (AIAN) only, and Asian only. Those who reported multiple races and specified a preferred race were allocated to their preferred race group by the National Center for Health Statistics. We cross-classified race with a Hispanic indicator variable to create the race/ethnicity categories: non-Hispanic White, non-Hispanic Black, non-Hispanic AIAN, non-Hispanic Asian, and Hispanic. Those who reported multiple races with no preferred race were excluded, along with those who reported “other,” due to heterogeneity and small sample size.

Covariates

Covariates represented demographic factors, socioeconomic factors, and health-related factors. Demographic factors included age groups (50-59, 60-64, 65-74, 75+ years) and sex. Socioeconomic factors included marital status (married vs. others), educational attainment (no college vs. 2-year college degree or more), and poverty status (below 200% of the federal poverty level [FPL]; 200%-399%, and 400% or more). Health-related factors included health insurance coverage, self-reported health status (excellent health vs. less than excellent health), and functional limitations (limited in any way vs. not limited). All models additionally included, as a covariate, the number of CAM used by each respondent.

Analysis

First, we examined whether background characteristics of CAM users differed by race/ethnicity. Next, we classified the intent of CAM use, the types of CAM used, and the percentage of respondents reporting each perceived benefit by race/ethnicity. We used cross-tabulations and design-based F tests to test for differences by race/ethnicity. Finally, in separate multivariable logistic regression models, we estimated the odds of reporting each benefit of CAM by race/ethnicity. All models were adjusted for age, sex, marital status, educational attainment, poverty status, health insurance coverage, self-reported health status, mental health, functional limitations, and number of CAM used in the past year. Our final descriptive sample included adults, ages 50 years and older, who used CAM in the past year, and had complete data for all covariates (n = 5,304 unweighted). Our final analytic sample included the subset that reported at least one type of CAM as being most important to their health during the past year (n = 4,767). All analyses were conducted with Stata statistical software (SE version 13.1) and used techniques to account for the complex sample design of the NHIS (StataCorp, 2011, 2013).

Results

Table 1 shows the characteristics of midlife and older CAM users by race/ethnicity (n = 5,304 unweighted). CAM users were statistically significantly different by race/ethnicity across all demographic, socioeconomic, and health-related characteristics, with the exception of sex.

Table 1.

Selected Characteristics (Weighted Percent) of Noninstitutionalized U.S. Adults Ages 50 Years and Older, Who Used CAM in the Past Year (n = 5,304) by Race/Ethnicity, NHIS 2012.

	White (%)	Black (%)	AIAN (%)	Asian (%)	Hispanic (%)	Total (%)	p value
Demographic
Age
50-59 years	43.9	54.6	59.6	44.1	51.5	45.1	.005
60-64 years	19.8	16.4	9.6	17.8	21.4	19.6
65-74 years	23.7	20.5	23.1	29.1	19.2	23.5
75+ years	12.6	8.5	7.8	9.0	7.8	11.9
Sex
Female	57.6	60.3	80.4	56.9	60.1	58.0	.331
Male	42.4	39.7	19.6	43.1	39.9	42.0
Socioeconomic
Marital status
Married	66.9	45.6	33.3	72.7	58.4	65.2	<.001
Other	33.1	54.4	66.7	27.3	41.6	34.8
Educational attainment
No college degree	47.0	55.6	80.0	38.3	69.1	48.6	<.001
≥2 year College Degree	53.0	44.4	20.0	61.7	30.9	51.4
Poverty status
Below 200% FPL	15.8	33.6	40.0	22.5	41.1	18.8	<.001
200%-399% of FPL	29.0	30.4	34.1	22.7	28.3	28.7
400%+ of FPL	55.2	36.0	26.0	54.8	30.6	52.5
Health
Health insurance
Uninsured	5.7	9.9	11.0	11.6	19.6	7.1	<.001
Insured	94.3	90.1	89.0	88.4	80.5	92.9
Self-reported health
Excellent health	24.0	11.9	3.0	17.2	17.1	22.5	<.001
Less than excellent	76.0	88.1	97.0	82.8	82.9	77.5
Functional limitations
Not limited	45.4	40.4	21.0	63.0	46.6	45.8	<.001
Limited, any way	54.6	59.6	79.0	37.0	53.4	54.2

Note. The p values are from design-based F tests comparing percentages across race/ethnicity. Some columns do not add up to 100% due to rounding. CAM = complementary and alternative medicine; NHIS = National Health Interview Survey; AIAN = American Indian/Alaska Native; FPL = federal poverty level.

Table 2 shows the number of CAM used, the reason for CAM use, and the specific types of CAM used by race/ethnicity. Overall, 35% of midlife and older adults in our sample used CAM in the past year, while 55% reported having ever used some form of CAM (data not shown). Non-Hispanic Blacks and AIANs had the lowest rates of past year use, while non-Hispanic Whites had the highest rate of use (data not shown). More than 40% of midlife and older CAM users used more than one CAM in the past year. However, this ranged from 50% of AIANs to only 31% of Hispanics.

Table 2.

Types of CAM Used in the Past Year by Race/Ethnicity Among CAM Users 50 Years and Older (n = 5,304), NHIS 2012.

	White (%)	Black (%)	AIAN (%)	Asian (%)	Hispanic (%)	Total (%)	p value
Number of CAM used
Used only one CAM	57.9	66.9	50.7	60.4	68.3	59.1	.001
Used two CAM	21.8	15.4	35.5	24.4	16.1	21.3
Used three or more CAM	20.3	17.8	13.8	15.3	15.6	19.6
Intent for use
Treatment	14.7	8.6	8.0	15.9	12.7	14.3	.002
Wellness	38.8	47.8	23.1	50.9	47.3	40.2
Treatment and wellness	46.5	43.6	69.0	33.2	40.0	45.5
Percentage of each column group using specific types of CAM
Providers
Acupuncture	4.7	4.2	0.0	12.6	6.6	5.1	<.001
Ayurveda	0.7	1.3	0.0	2.0	0.1	0.7	.310
Biofeedback	1.4	1.1	0.0	0.0	0.4	1.2	.391
Chiropractic	29.4	14.5	15.1	13.4	19.7	27.1	<.001
Craniosacral therapy	1.1	0.2	1.5	0.4	0.3	0.9	.256
Energy therapies	2.3	2.0	5.3	1.4	1.9	2.2	.795
Hypnosis	1.0	0.1	3.4	0.4	0.0	0.9	.048
Massage therapy	22.4	23.5	20.3	20.8	21.2	22.3	.845
Movement therapies	4.8	3.4	2.0	2.2	3.1	4.5	.163
Naturopathy	2.1	2.3	5.3	1.4	2.8	2.1	.607
Traditional healers	0.4	1.0	11.7	1.2	5.7	0.9	<.001
Products
Diet-based therapies	9.0	9.9	14.3	8.7	9.7	9.1	.779
Herbal supplements	58.9	59.7	68.3	50.8	55.9	58.4	.041
Homeopathy	5.9	6.0	3.5	4.2	3.5	5.7	.301
Practices
Meditation practices	13.8	14.7	16.9	8.3	9.5	13.4	.036
Yoga	17.2	15.5	10.6	21.8	14.4	17.2	.204
Tai chi	3.5	5.4	4.8	8.6	3.4	3.9	.003
Qi gong	1.2	2.3	0.0	3.2	2.1	1.4	.091

Note. The p values are from design-based F tests comparing percentages across race/ethnicity. Specific CAM types are not mutually exclusive. CAM = complementary and alternative medicine; NHIS = National Health Interview Survey; AIAN = American Indian/Alaska Native.

Overall, 14% of CAM users used it for treating a health condition only, 40% used it for wellness only, and 46% used CAM for both treatment and wellness. However, reasons for CAM use varied significantly by race/ethnicity, with over 90% of non-Hispanic Blacks and AIANs using CAM for wellness alone or in combination with medical treatment. Among CAM users, herbal supplements (58%), chiropractic (27%), massage therapy (22%), yoga (17%), and meditation (13%) were the most commonly used, but only herbal and nutritional (nonvitamin/mineral) supplements, chiropractic, and meditation use were significantly different by race/ethnicity. Although not as often used among midlife and older adults, there were significant differences by race/ethnicity in use of acupuncture, hypnosis, traditional healers, meditation practices, and tai chi. Asians had the highest use of acupuncture, and AIANs had the highest use of traditional healers and meditation.

Table 3 presents the percentage of midlife and older CAM users reporting specific types of benefits of using CAM by race/ethnicity. Overall, nearly three quarters of CAM users reported that using CAM in the past year resulted in improved overall health and feeling better, but this did not differ by race/ethnicity. Half of CAM users reported that using CAM resulted in reduced stress and relaxation. This differed significantly by race/ethnicity (p = .002) and ranged from 49% of non-Hispanic Whites to 82% of AIANs. All other perceived benefits also differed by race/ethnicity. Non-Hispanic Blacks and AIANs had the highest reports of increased sense of control over health; AIANs had the highest reports of all of the other perceived benefits with the exception of improved relationships; non-Hispanic Blacks had the highest reports of improved relationships. The least often reported benefit was improved relationships as a result of using CAM, with only 24% reporting this benefit overall.

Table 3.

Perceived Benefit of Using CAM by Race/Ethnicity Among Adults Ages 50 Years and Older Who Used CAM (n = 4,767), NHIS 2012.

	White (%)	Black (%)	AIAN (%)	Asian (%)	Hispanic (%)	Total (%)	p value
Improved health and feeling better
Yes	74	75	77	72	72	74	.899
Reduced stress/relaxation
Yes	49	60	82	51	52	50	.002
Sense of control over health
Yes	46	59	59	46	55	48	.001
Feeling better emotionally
Yes	42	59	65	49	48	44	<.001
Easier to cope with health problems
Yes	41	53	63	49	50	43	<.001
Better sleep
Yes	41	49	72	48	49	42	.002
Improved relationships with others
Yes	23	34	29	31	30	24	<.001

Note. The p values are from design-based F tests comparing percentages across race/ethnicity. CAM = complementary and alternative medicine; NHIS = National Health Interview Survey; AIAN = American Indian/Alaska Native.

Table 4 presents the results of seven separate multiple logistic regression models estimating the odds of perceived benefits of using CAM in the past year by race/ethnicity. For six of seven benefits, we found statistically significant differences (of at least 1.4 times higher odds or more) by race/ethnicity, with each group having higher odds of two or more of the perceived benefits compared with non-Hispanic Whites. For example, AIANs had 4.1 times higher odds of reduced stress and 3.3 times higher odds of better sleep, while Blacks had twice the odds of feeling better emotionally, Asians had 1.7 times higher odds of improved relationships, and Hispanics had 1.6 times higher odds of improved sense of control over health. There were no significant differences in reporting that CAM improved overall health.

Table 4.

Odds of Reporting Perceived Benefit of Using CAM by Race/Ethnicity Among CAM Users 50 Years and Older (n = 4,767), NHIS 2012.

	Odds of reporting each benefit
	OR	LCI	UCI	p value
Improved overall health and feeling better
White, non-Hispanic	1.0
Black, non-Hispanic	1.1	0.79	1.51	.595
AIAN, non-Hispanic	1.1	0.32	3.60	.906
Asian, non-Hispanic	0.9	0.61	1.35	.637
Hispanic	1.0	0.69	1.38	.874
Reduced stress/relaxation
White, non-Hispanic	1.0
Black, non-Hispanic	1.7	1.21	2.32	.002
AIAN, non-Hispanic	4.1	1.45	11.80	.008
Asian, non-Hispanic	1.3	0.82	1.92	.304
Hispanic	1.4	0.98	1.93	.064
Gave sense of control over health
White, non-Hispanic	1.0
Black, non-Hispanic	1.8	1.27	2.46	.001
AIAN, non-Hispanic	1.5	0.60	3.64	.398
Asian, non-Hispanic	1.1	0.75	1.50	.726
Hispanic	1.6	1.19	2.21	.003
Better sleep
White, non-Hispanic	1.0
Black, non-Hispanic	1.4	1.03	1.89	.033
AIAN, non-Hispanic	3.3	1.45	7.71	.005
Asian, non-Hispanic	1.5	1.04	2.24	.031
Hispanic	1.6	1.13	2.20	.007
Feeling better emotionally
White, non-Hispanic	1.0
Black, non-Hispanic	2.0	1.49	2.76	<.001
AIAN, non-Hispanic	2.0	0.73	5.58	.176
Asian, non-Hispanic	1.5	0.99	2.28	.054
Hispanic	1.4	1.02	1.97	.040
Made it easier to cope with health problems
White, non-Hispanic	1.0
Black, non-Hispanic	1.5	1.08	2.10	.016
AIAN, non-Hispanic	1.8	0.66	4.90	.249
Asian, non-Hispanic	1.5	1.06	2.18	.024
Hispanic	1.5	1.06	2.01	.020
Improved relationships with others
White, non-Hispanic	1.0
Black, non-Hispanic	1.8	1.33	2.56	<.001
AIAN, non-Hispanic	1.3	0.44	3.72	.652
Asian, non-Hispanic	1.7	1.13	2.45	.010
Hispanic	1.7	1.15	2.36	.006

Note. Results of seven separate logistic regression models. All models adjusted for sex, age, marital status, educational attainment, poverty status, insurance status, health status, functional limitations, and number of CAM used. CAM = complementary and alternative medicine; NHIS = National Health Interview Survey; OR = odds ratio; LCI = lower level confidence interval; UCI = upper level confidence interval; AIAN = American Indian/Alaska Native.

Overall, non-Hispanic Blacks had the highest number of perceived benefits of using CAM, with five of the six benefits significantly higher than non-Hispanic Whites. Of the perceived benefits of using CAM, improved sleep was significantly higher for each of the race/ethnicity groups compared with non-Hispanic Whites. Although only 24% of midlife and older CAM users reported improved relationships due to CAM use, three of the four racial/ethnic groups had significantly higher odds of reporting this benefit compared with non-Hispanic Whites.

Discussion

To our knowledge, this study is the first to document race/ethnicity differences in perceived benefits of using CAM, in addition to differences in prevalence and patterns of CAM use, in a national sample of midlife and older adults. We find that midlife and older adults are high users of CAM, and they use CAM primarily for either wellness or combined treatment and wellness. We also find that there are significant differences in the types of CAM used by race/ethnicity. Although racial/ethnic minority groups are less likely to use CAM overall, those that do use CAM perceive greater benefit compared with non-Hispanic Whites. Our findings align with previous studies, which suggest use and type of CAM vary along racial/ethnic lines (Chao, Wade, & Kronenberg, 2008; Chao, Wade, Kronenberg, Kalmuss, & Cushman, 2006; Cherniack et al., 2008; Grzywacz et al., 2005; Keith, Kronenfeld, Rivers, & Liang, 2005; Kronenberg et al., 2006; Mikuls, Mudano, Pulley, & Saag, 2003; Rhee, Evans, McAlpine, & Johnson, 2017; Upchurch & Wexler Rainisch, 2012). However, no previous studies have addressed racial/ethnic differences in the perceived benefits of CAM use.

Population studies using NHIS data have documented who uses CAM and, to some extent, reasons for use. Previous studies using older NHIS data report the growing use of CAM for wellness in general adult populations, women, and older adults (Arcury et al., 2006; Davis et al., 2011; Grzywacz et al., 2005; Grzywacz et al., 2007; Upchurch & Rainisch, 2015). Fewer studies have explicitly focused on midlife and older adults. One recent study documented perceived benefits of CAM by reason for use among midlife and older adults (Johnson et al., 2016). Specifically, the authors found that, compared with midlife and older adults who used CAM for treatment only, those who used it for wellness only or for both wellness and treatment had significantly higher odds of reporting benefits (Johnson et al., 2016). The current study extends this work by further showing that, among midlife and older adults, perceived benefits of using CAM differ by race/ethnicity and that Black, AIAN, Asian, and Hispanic CAM users all have higher odds of reporting multiple benefits compared with non-Hispanic White users.

We found notable differences in the use of CAM, the types of CAM, and the intent for using CAM by race/ethnicity. Racial/ethnic minorities are most likely to have used a single type of CAM in the past year, with the exception of AIAN of whom half used two or more types. AIAN are the most likely to report using meditation practices, which includes “spiritual meditation,” and to use herbal supplements. Asians, on the contrary, are more likely to use acupuncture and Tai chi. Racial/ethnic differences in types of CAM used may reflect varying cultural preferences among each racial/ethnic group, as well as knowledge and acceptability of specific approaches that are historically part of each group’s heritage.

Racial/ethnic minorities also tend to use CAM more for wellness alone than non-Hispanic Whites (with the exception of AIAN). Interestingly, over two thirds of AIAN used CAM for both wellness and treatment combined, which may be a result of the significantly higher proportion that use traditional healers whose practices are more holistic. Wellness is a concept that goes beyond the standard public health definitions of “health promotion and disease prevention” or disease management in that it incorporates the concept of well-being in addition to health status and quality of life. Described by the Centers for Disease Control and Prevention (CDC) as “the presence of positive emotions and moods. . .the absence of negative emotions . . . satisfaction with life, fulfillment, and positive functioning,” well-being is a broad construct that has multiple dimensions, including physical, emotional and psychological, social, and economic well-being (CDC, 2016). This suggests to us that CAM is not used just as “medicine” to treat or manage disease, but it is also used holistically for overall health and well-being.

Overall, we found that adults ages 50 and older who use CAM, regardless of race/ethnicity, uniformly believed their CAM use improved their overall health and helped them feel better. This may be related, in part, to the high proportion of all races (>85%) that reported that their intent for using CAM was “wellness,” either alone or in combination with treatment, which as noted above, is a more holistic health concept. “Overall health” and “feeling better” may more loosely represent a state of being well, or well-being, which is the overarching intention of CAM.

Non-Hispanic Blacks had higher odds of experiencing five of the six benefits as a result of their CAM use. Higher odds of perceived benefit of CAM use for all race/ethnicity groups may be due, in part, to more frequent negative encounters with conventional medical providers/systems compared with non-Hispanic Whites (Shippee et al., 2013; Shippee et al., 2012). This may be especially true for the benefits “gave sense of control over health” and “easier to cope with health problems,” as this reflects the importance of self-efficacy and better self-care and coping in improving outcomes. These responses also align with many of the basic tenets of CAM with respect to a holistic approach to health, which also includes empowerment of patients. In addition, all four racial/ethnic minority groups have higher odds of reporting better sleep, which can be especially important for midlife and older adults.

CAM can be a “lifestyle choice” with potential benefit even if practiced in a limited capacity. Some CAM have been linked to motivating other healthy behaviors such as increased exercise and healthy eating (Stussman, Black, Barnes, Clarke, & Nahin, 2015). Adopting a healthy lifestyle, even in midlife, has demonstrated health benefits (King, Mainous, & Geesey, 2007). Yet, adherence to these lifestyle habits among U.S. adults is on the decline (King, Mainous, Carnemolla, & Everett, 2009). Incorporating CAM into self-care practices may empower midlife adults to proactively support their own health and well-being, motivate them to pursue other healthy behaviors, help them manage stress, and overall contribute to a positive health trajectory into older age.

Many CAM are lower cost to deliver and can be offered in community and residential senior living, as well as clinical settings, making them particularly valuable to communities that face greater barriers to accessing conventional health care services. CAM practitioners can be a complementary source of health promotion messaging and support for lifestyle change, as they often see patients over a series of visits (Hawk, Ndetan, & Evans, 2012). CAM used either on its own or in an integrative health care setting may be an untapped resource for engaging diverse midlife adults in health-promoting behavior that offers tools to help manage unique stressors.

Implications for Policy, Practice, Research

One of the largest barriers to accessing CAM is the economic cost and lack of health insurance coverage for CAM therapies that already have a strong evidence base (e.g., acupuncture, yoga, mindfulness-based stress reduction). Expanding insurance coverage to evidence-based CAM can help ameliorate the economic barriers to CAM use that most people face. Although chiropractic is covered by most health insurance plans and by Medicare, and is an optional benefit for Medicaid recipients, it is reimbursed at a lower rate and may be limited to a certain number of visits that may not be a therapeutic dose. Other CAM are covered (partially or not at all) by health insurance, but this varies by plan and by type of CAM (e.g., acupuncture, therapeutic massage).

In response to the opioid crisis, the Centers for Medicare and Medicaid Services (CMS) is collaborating with National Institutes of Health (NIH) on opioid research to identify nonpharmaceutical alternatives to opioid prescribing. One of their priority actions is to identify alternative treatments that have a sufficient evidence base to quickly expand coverage of those alternative therapies (CMS, 2017). As these federal agencies undergo rigorous research and large-scale implementation, there is precedent for additional policies expanding coverage.

Implications for practice are broad and some efforts are underway to integrate CAM into conventional medical practice settings. Veterans Health Administration (VHA) offers many CAM types in their hospitals and clinics. VHA is heavily invested in research to evaluate both efficacy and effectiveness. Numerous reports on efficacy and effectiveness of various CAM types have been documented through their rigorous Evidence Synthesis Program. A survey of VHA facilities revealed that 125 (82%) provided CAM services and/or referred patients to CAM service providers. 80% cited patient demand as the reason for offering CAM (Hammond & Vandenberg, 2011).

CAM providers can be integrated into ambulatory clinics to increase awareness, facilitate referral, and coordinate care. For example, chiropractors, acupuncturists, and therapeutic massage practitioners can be embedded in primary care or multispecialty care clinics. This can increase conventional providers’ awareness of CAM therapies and provide CAM practitioners opportunities for employment as part of a health care team in integrative health care settings, as well as facilitate referrals and coordinated care. Standalone ambulatory alternative medicine clinics have, for example, been implemented targeting both veterans in VHA settings (Hull et al., 2015) and socially disadvantaged patients in a public, safety-net health care delivery system (Bracha, Svendsen, & Culliton, 2005). Inpatient integrative health care models, some with no additional cost to patients, have also been growing (Knutson, Johnson, Sidebottom, & Fyfe-Johnson, 2013). CAM is also now being offered in some senior or assisted living facilities. In some cases, the services are integrated as part of the “rent” package. In others, they are offered as a la carte services for a fee. Finally, incorporating evidence-based CAM into public health and wellness promotion activities targeting traditionally underserved groups in community-based settings (e.g., local Y organizations, community education offerings, or church activities) may go a long way toward providing accessible and acceptable programming.

In addition to ongoing trials on the efficacy of specific CAM types for specific health conditions, future mixed methods research should seek to understand access to, reasons for, and outcomes of using evidence-based CAM. Our current study documents the prevalence of use among racially and ethnically diverse midlife and older adults and, among those who use CAM, the reasons for and perceived benefits (broadly construed) of using CAM. Next steps might include a more thorough understanding of each aspect, perhaps using qualitative methods. Studies aiming to understand the barriers and facilitators to using CAM, as well as reasons for not using CAM, will be important to develop strategies for improving access taking account of the impact of social and economic disadvantage. More research is needed on better understanding how lifestyle beliefs and more specifically, health beliefs, influence CAM use and CAM outcomes. Future research should also examine the value-added of evidence-based CAM, in addition to necessary medical care and a healthy lifestyle, targeted to improve both health and well-being. It will be particularly important to take a life course approach to understanding the impact of CAM use in midlife and health and well-being outcomes over time in a diverse aging population.

Limitations

Findings should be considered in light of limitations. First, the classification of race/ethnicity used in this paper may oversimplify the experiences of the identified “race” groups. Reporting results for single-race categories may not fully capture the experiences of different subgroups within each racial category, due to the intersectionality of race and ethnicity as well as gender, socioeconomic status, and culture. Due to small sample size, we also excluded those who did not identify with a single race or who reported “other race,” yet they are a growing group in the United States about whom little is known. More nuanced efforts to unpack race/ethnicity differences in CAM use and health, drawing on established frameworks such as critical race theory, should be incorporated into future data collection and research. Second, CAM use is based on self-report, which relies upon accurate recall about what was used, why it was used, and what benefits may have accrued. Third, perceived benefits are subjective outcomes based on yes/no questions and may be the result of a placebo effect. Those who are “true believers” may report that using CAM led to beneficial outcomes, whether or not there was real change. However, if respondents perceived improvement in their health and well-being, that is a positive outcome by itself. Finally, we aggregated perceived benefits of using CAM into a single category. Thus, we can only determine overall perception that at least one type of CAM used conferred some benefit, rather than the perceived benefits of each specific CAM type.

Conclusion

As preventing illness has the most potential for reducing health disparities and the need for expensive medical care in an aging population, evidence-based CAM provides one hypothesized path for wellness promotion and disease prevention. As communities of color often see the highest rates of chronic stress, chronic disease, and disability, understanding individuals’ use of CAM and the perceived benefits of CAM provides initial insight as to for whom and what type of CAM might contribute to promoting healthy aging. Future research to elucidate the role of CAM, in addition to needed medical care and a healthy lifestyle, on both health and well-being outcomes among diverse midlife and older adults will be critical to informing elements of practice and policy. There is a strong evidence base for some types of CAM. Efforts to integrate these evidence-based CAM into conventional medical practice referral patterns, inpatient integrative medicine departments, senior living facilities, and community-based settings are a first step to reducing structural barriers to CAM use. Extending insurance coverage to evidence-based CAM types will reduce economic barriers. Incorporating CAM in health education and wellness promotion activities targeting traditionally underserved groups may be a promising approach to improving overall health and well-being in a diverse aging population.

Footnotes

Appendix

Classification of CAM Includes 35 of 36 Specific CAM Therapies,^a NHIS 2012.

CAM group	NHIS question	Specific CAM therapies
Providers	Saw practitioner for . . .	Acupuncture Ayurveda Biofeedback Chiropractic or osteopathic Manipulation Craniosacral therapy Energy Healing Hypnosis Massage Movement therapies^b (i.e., Feldenkrais, Alexander Technique, Pilates, Trager Psychophysical Integration) Naturopathy
Providers	Saw. . .	Traditional healers^b (i.e., Curandero or Parchero; Hierbista or Yerbero; Shaman; Native American Healer/Medicine Man; Sobador; Huesero)
Practices	Used or practiced . . .	Meditation^b (i.e., mantra, mindfulness, spiritual) Guided Imagery, Progressive Relaxation Yoga, Tai Chi, Qi Gong
Products	Used . . .	Diet-based therapies^b (i.e., vegetarian, macrobiotic, Atkins, Pritikin, Ornish), Herbal or Nonvitamin Supplements (in past 30 days), Homeopathic Remedies

Note. CAM = complementary and alternative medicine; NHIS = National Health Interview Survey.

Excluded multivitamin/mineral supplements.

Each of the specific types in the parentheses were asked individually but were collapsed for presentation in Table 2.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors gratefully acknowledge support from the Minnesota Population Center, University of Minnesota (P2C HD041023) funded through a grant from the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD).

ORCID iD

Pamela Jo Johnson

References

Arcury

T. A.

Nguyen

H. T.

Sandberg

J. C.

Neiberg

R. H.

Altizer

K. P.

Bell

R. A.

. . . Quandt

S. A.

(2015). Use of complementary therapies for health promotion among older adults. Journal of Applied Gerontology, 34, 552-572. doi:10.1177/0733464813495109

Arcury

T. A.

Suerken

C. K.

Grzywacz

J. G.

Bell

R. A.

Lang

Quandt

S. A.

(2006). Complementary and alternative medicine use among older adults: Ethnic variation. Ethnicity & Disease, 16, 723-731.

Barnes

P. M.

Bloom

Nahin

R. L.

(2008). Complementary and alternative medicine use among adults and children: United States, 2007 (National Health Statistics Report, Vol. 12). Hyattsville, MD: National Center for Health Statistics.

Bracha

Svendsen

Culliton

(2005). Patient visits to a hospital-based alternative medicine clinic from 1997 through 2002: Experience from an integrated healthcare system. Explore: The Journal of Science & Healing, 1, 13-20. doi:10.1016/j.explore.2004.10.004

Centers for Disease Control and Prevention. (2016). Well-being concepts: Health-related quality of life. Retrieved from https://www.cdc.gov/hrqol/wellbeing.htm

Centers for Medicare & Medicaid Services. (2017). Opioid misuse strategy. Retrieved from https://www.cms.gov/Outreach-and-Education/Outreach/Partnerships/Downloads/CMS-Opioid-Misuse-Strategy-2016.pdf

Chao

M. T.

Wade

Kronenberg

(2008). Disclosure of complementary and alternative medicine to conventional medical providers: Variation by race/ethnicity and type of CAM. Journal of the National Medical Association, 100, 1341-1349.

Chao

M. T.

Wade

Kronenberg

Kalmuss

Cushman

L. F.

(2006). Women’s reasons for complementary and alternative medicine use: Racial/ethnic differences. Journal of Alternative and Complementary Medicine, 12, 719-720. doi:10.1089/acm.2006.12.719

Cherniack

E. P.

Ceron-Fuentes

Florez

Sandals

Rodriguez

Palacios

J. C.

(2008). Influence of race and ethnicity on alternative medicine as a self-treatment preference for common medical conditions in a population of multi-ethnic urban elderly. Complementary Therapies in Clinical Practice, 14, 116-123. doi:10.1016/j.ctcp.2007.11.002

10.

Clarke

T. C.

Black

L. I.

Stussman

B. J.

Barnes

P. M.

Nahin

R. L.

(2015). Trends in the use of complementary health approaches among adults: United States, 2002-2012 (National Health Statistics Report, Vol. 79). Hyattsville, MD: National Center for Health Statistics.

11.

Davis

M. A.

West

A. N.

Weeks

W. B.

Sirovich

B. E.

(2011). Health behaviors and utilization among users of complementary and alternative medicine for treatment versus health promotion. Health Services Research, 46, 1402-1416. doi:10.1111/j.1475-6773.2011.01270.x

12.

Engebretson

(2002). Culture and complementary therapies. Complementary Therapies in Nursing and Midwifery, 8, 177-184. doi:10.1054/ctnm.2002.0638

13.

Gentleman

J. F.

Pleis

J. R.

(2002). The National Health Interview Survey: An overview. Effective Clinical Practice, 5(3, Suppl.), E2. Retreived from http://ecp.acponline.org/mayjun02/gentleman.htm

14.

Graham

R. E.

Ahn

A. C.

Davis

R. B.

O’Connor

B. B.

Eisenberg

D. M.

Phillips

R. S.

(2005). Use of complementary and alternative medical therapies among racial and ethnic minority adults: Results from the 2002 National Health Interview Survey. Journal of the National Medical Association, 97, 535-545.

15.

Grzywacz

J. G.

Lang

Suerken

Quandt

S. A.

Bell

R. A.

Arcury

T. A.

(2005). Age, race, and ethnicity in the use of complementary and alternative medicine for health self-management: Evidence from the 2002 National Health Interview Survey. Journal of Aging and Health, 17, 547-572. doi:10.1177/0898264305279821

16.

Grzywacz

J. G.

Suerken

C. K.

Neiberg

R. H.

Lang

Bell

R. A.

Quandt

S. A.

Arcury

T. A.

(2007). Age, ethnicity, and use of complementary and alternative medicine in health self-management. Journal of Health and Social Behavior, 48, 84-98.

17.

Hammond

Vandenberg

(2011). 2011 Complementary and Alternative Medicine Survey. Washington, DC: Department of Veterans Affairs, Office of the Assistant Deputy Under Secretary for Health for Policy and Planning.

18.

Hawk

Ndetan

Evans

M. W.

Jr. (2012). Potential role of complementary and alternative health care providers in chronic disease prevention and health promotion: An analysis of National Health Interview Survey data. Preventive Medicine, 54, 18-22. doi:10.1016/j.ypmed.2011.07.002

19.

Hill

C. V.

Perez-Stable

E. J.

Anderson

N. A.

Bernard

M. A.

(2015). The national institute on aging health disparities research framework. Ethnicity & Disease, 25, 245-254. doi:10.18865/ed.25.3.245

20.

Hull

Holliday

S. B.

Eickhoff

Rose-Boyce

Sullivan

Reinhard

(2015). The integrative health and wellness program: Development and use of a complementary and alternative medicine clinic for veterans. Alternative Therapies in Health and Medicine, 21(6), 12-21.

21.

Johnson

P. J.

Jou

Rhee

T. G.

Rockwood

T. H.

Upchurch

D. M.

(2016). Complementary health approaches for health and wellness in midlife and older US adults. Maturitas, 89, 36-42. doi:10.1016/j.maturitas.2016.04.012

22.

Keith

V. M.

Kronenfeld

J. J.

Rivers

P. A.

Liang

S. Y.

(2005). Assessing the effects of race and ethnicity on use of complementary and alternative therapies in the USA. Ethnicity & Disease, 10, 19-32. doi:10.1080/1355785052000323010

23.

King

D. E.

Mainous

A. G.

III Carnemolla

Everett

C. J.

(2009). Adherence to healthy lifestyle habits in US adults, 1988-2006. The American Journal of Medicine, 122, 528-534. doi:10.1016/j.amjmed.2008.11.013

24.

King

D. E.

Mainous

A. G.

III Geesey

M. E.

(2007). Turning back the clock: Adopting a healthy lifestyle in middle age. The American Journal of Medicine, 120, 598-603. doi:10.1016/j.amjmed.2006.09.020

25.

Knutson

Johnson

P. J.

Sidebottom

Fyfe-Johnson

(2013). Development of a hospital-based integrative healthcare program. Journal of Nursing Administration, 43, 101-107. doi:10.1097/NNA.0b013e31827f2229

26.

Kronenberg

Cushman

L. F.

Wade

C. M.

Kalmuss

Chao

M. T.

(2006). Race/ethnicity and women’s use of complementary and alternative medicine in the United States: Results of a national survey. American Journal of Public Health, 96, 1236-1242.

27.

Mikuls

T. R.

Mudano

A. S.

Pulley

Saag

K. G.

(2003). The association of race/ethnicity with the receipt of traditional and alternative arthritis-specific health care. Medical Care, 41, 1233-1239. doi:10.1097/01.MLR.0000093422.67436.E5

28.

National Center for Chronic Disease Prevention and Health Promotion. (2015). Racial and Ethnic Approaches to Community Health (REACH): Finding solutions to health disparities. Retrieved from http://www.cdc.gov/chronicdisease/resources/publications/aag/reach.htm

29.

National Center for Health Statistics. (2013). Data file documentation: National Health Interview Survey, 2012 [Machine readable data file and documentation]. Retrieved from http://www.cdc.gov/nchs/nhis/nhis_2012_data_release.htm

30.

Rhee

T. G.

Evans

R. L.

McAlpine

D. D.

Johnson

P. J.

(2017). Racial/Ethnic differences in the use of complementary and alternative medicine in US adults with moderate mental distress: Results from the 2012 National Health Interview Survey. Journal of Primary Care & Community Health, 8, 43-54. doi:10.1177/2150131916671229

31.

Shippee

T. P.

Henning-Smith

Shippee

Kemmick Pintor

J. B.

Call

K. T.

McAlpine

Johnson

P. J.

(2013). Discrimination in medical settings and attitudes toward complementary and alternative medicine: The role of distrust in conventional providers. Journal of Health Disparities Research and Practice, 6, 30-45.

32.

Shippee

T. P.

Schafer

M. H.

Ferraro

K. F.

(2012). Beyond the barriers: Racial discrimination and use of complementary and alternative medicine among Black Americans. Social Science & Medicine, 74, 1155-1162. doi:10.1016/j.socscimed.2012.01.003

33.

Smolka

Purvis

Figueiredo

(2009). Health care reform: What’s at stake for 50- to 64-year-olds? (Insight on the issues). Retrieved from http://assets.aarp.org/rgcenter/health/i24_hcr.pdf

34.

StataCorp. (2011). Survey data reference manual. College Station, TX: Stata Press.

35.

StataCorp. (2013). Stata statistical software: Release 13.0 [Computer program]. College Station, TX: StataCorp LP.

36.

Struthers

Eschiti

V. S.

Patchell

(2004). Traditional indigenous healing: Part I. Complementary Therapies in Nursing and Midwifery, 10, 141-149. doi:10.1016/j.ctnm.2004.05.001

37.

Stussman

B. J.

Black

L. I.

Barnes

P. M.

Clarke

T. C.

Nahin

R. L.

(2015). Wellness-related use of common complementary health approaches among adults: United States, 2012 (National Health Statistics Report, Vol. 85). Hyattsville, MD: National Center for Health Statistics.

38.

Upchurch

D. M.

Rainisch

B. W.

(2015). The importance of wellness among users of complementary and alternative medicine: Findings from the 2007 National Health Interview Survey. BMC Complementary and Alternative Medicine, 15(1), Article 362. doi:10.1186/s12906-015-0886-y

39.

Upchurch

D. M.

Wexler Rainisch

B. K.

(2012). Racial and ethnic profiles of complementary and alternative medicine use among young adults in the United States: Findings from the national longitudinal study of adolescent health. Journal of Evidence-Based Complementary & Alternative Medicine, 17, 172-179. doi:10.1177/2156587212450713

40.

Upchurch

D. M.

Wexler Rainisch

B. K.

(2013). A sociobehavioral model of use of complementary and alternative medicine providers, products, and practices: Findings from the 2007 National Health Interview Survey. Journal of Evidence-Based Complementary & Alternative Medicine, 18, 100-107.