Abstract
Context
Prior studies suggest that terminally ill patients who use religious coping are less likely to have advance directives and more likely to opt for heroic end-of-life measures. Yet, no study to date has examined whether end-of-life practices are associated with measures of religiosity and spirituality.
Objectives
To assess the relationship between general measures of patient religiosity and spirituality and patients’ preferences for care at the end of life.
Methods
We examined data from the University of Chicago Hospitalist Study, which gathers sociodemographic and clinical information from all consenting general internal medicine patients at the University of Chicago Medical Center. Primary outcomes were whether the patient had an advance directive, a do-not-resuscitate (DNR) order, a durable power of attorney for health care, and an informally designated decision maker. Primary predictors were religious attendance, intrinsic religiosity, and self-rated spirituality.
Results
The sample population (n=8,308) was predominantly African American (73%) and female (60%). In this population, 1.5% had advance directives and 10.4% had DNR orders. Half (51%) of patients had specified a decision maker. White patients were more likely than African-American patients to have an advance directive (adjusted odds ratio [OR] 2.1; 95% confidence interval [CI] 1.1, 4.0) and a DNR order (OR 1.7; 95% CI 1.0, 2.9). Patients reporting high intrinsic religiosity were more likely to have specified a decision maker than those with low intrinsic religiosity (OR 1.3; CI 1.1, 1.6). The same was true for those with high compared to low spirituality (OR 1.3; CI 1.1, 1.5). Religious characteristics were not significantly associated with having an advance directive or DNR order.
Conclusion
Among general medicine inpatients at an urban academic medical center, those who were highly religious and/or spiritual were more likely to have a designated decision-maker to help with end-of-life decisions, but did not differ from other patients in their likelihood of having an advance directive or DNR order.
Keywords: Advance directive, DNR order, religiosity, spirituality, end-of-life care, medical inpatient
Introduction
A growing body of research suggests that religion and spirituality are associated with patients’ medical decision making in many domains (1). In turn, it has been argued that physicians should pay attention to the spiritual concerns that emerge in the clinical encounter (2-6). Such concerns may be particularly salient in the context of end-of-life care (2, 5, 7-10). Prior studies have found that among patients with terminal illness, black patients are more likely than white patients to report having religious or spiritual needs (11-14) and are less likely to have an advance directive (15-17). Several studies have also examined the role of religious coping in patients’ responses to terminal illness (11, 15, 16, 18, 19). These studies have found that religion and spirituality are sources of hope for many patients, and that among patients with advanced illness, those who receive greater spiritual support report a higher quality of life (11, 15). At the same time, religious coping has been associated with a preference for using heroic, life-sustaining technologies at the end of life, and with less frequent use of formal advance directives (15, 16, 18-20).
Prior studies have yielded important insights regarding religion and end-of-life care preferences, but they nevertheless have had significant limitations. Most studies of religion and end-of-life decisions have focused only on patients with advanced cancer (15, 16, 19) who have less than a year of life expectancy or in patients undergoing life-threatening surgical procedures (21). Others have had disproportionately small numbers of racial and ethnic minorities in their study populations (19) or did not determine what types of end-of-life care directives their patients had chosen (21). Moreover, prior studies of religiosity and end-of-life care decisions have focused on religious coping as the religiosity construct of interest. However, as Pargament has argued, religious coping should not be conflated with more general measures of religiosity (5, p. 132). Therefore, in this study, we assessed the relationship between general measures of religiosity or spirituality and preferences for care at the end of life among inpatients on the general medicine service, the majority of whom were not in the palliative phase, at an urban academic hospital that serves a predominantly African-American patient population. We hypothesized that, in keeping with the findings from previous studies of terminal cancer patients (15, 16, 18, 19), general medicine inpatients who were more religious and/or spiritual would be less likely to have a Do Not Resuscitate (DNR) order or advance directive in their charts while in the hospital, and would be less likely to have a durable power of attorney for health care.
Methods
Study Population
Data for this study were drawn from the University of Chicago Hospitalist Study. This project seeks to include all patients admitted to the general internal medicine service at the University of Chicago Medical Center (22). Hospitalized patients are asked to consent to a 15-minute interview to collect detailed health and socioeconomic information and contact information for a follow-up telephone interview conducted one month after discharge. Attempts are made to identify proxy respondents for those unable to respond directly. Chart abstraction provides data about patients’ end-of-life care directives. In January 2006, three measures of religion and spirituality were added to the inpatient interview.
Primary Measures
The primary outcomes were whether patients had documentation in the chart of three different types of end-of-life care directives: 1) an advance directive (AD) or living will, 2) a DNR order, or 3) a durable power of attorney for health care (DPAHC). Hospitalized patients also were asked whether they had (informally) designated a family member or friend as a surrogate decision maker (yes/no). The direction of association between religious measures and having a DPAHC was the same as those for having an informally designated decision maker. Therefore, for further analyses, we created one indicator variable for having a specified proxy decision maker, whether designated formally (DPAHC) or informally.
Three validated measures of religiosity and spirituality were used in the survey. Religious attendance was measured with the question, “How often do you attend church, synagogue, or other religious meetings?” This question is a part of the Duke Religion Index (DUREL) (23). Responses were categorized as: “never,” “less than once a week,” and “once a week or more.” Intrinsic religiosity, the extent to which religion guides or gives purpose to one’s life (24), was measured by agreement or disagreement with the statement, “I try hard to carry my religious beliefs over into all my other dealings in life.” Intrinsic religiosity was classified as low if patients disagreed, moderate if they agreed, and high if they strongly agreed. We also asked, “To what extent do you consider yourself a spiritual person?” Spirituality was categorized as low if a patient answered “slightly” or “not at all” spiritual, moderate if they answered “moderately” spiritual, and high if they answered “very” spiritual. Both of these measures have been validated within the General Social Survey (GSS) and in a large national survey of physicians (23, 24).
Other demographic characteristics included age, race/ethnicity, marital status, and education level. Self-rated health status was assessed using a question from the Medical Outcomes Study 12-Item Short Form (SF-12®), in which patients were asked to rate their own health on a scale from 1 to 100. In addition, Charlson Comorbidity Index (CCI) scores were calculated from hospital administrative data using a one-year look back (25).
Finally, to explore possible explanations for relationships between religious characteristics and having a specified decision maker, we examined two self-reported measures of trust (trust in physicians and trust in the hospital care team) as well as two proxies for being embedded in a caring community (having a caregiver at home and being discharged to home).
Statistical Analysis
We first used the Chi-squared test to examine bivariate associations between patients’ end-of-life care preferences and each predictor measure. We then used multivariate logistic regression to determine whether bivariate relationships remained significant after controlling for relevant covariates. “Does not apply” and “do not know” responses were treated as missing. All statistical analyses were performed using Stata/SE10.0 (StataCorp, LP, College Station, TX).
Ethics Committee Review
This study was conducted with the approval of the University of Chicago, Biological Sciences Division Institutional Review Board under Protocol 9967.
Results
Study Participants
We looked at the first admissions of 11,620 patients who were approached to be enrolled in the Hospitalist Study between January 2006 and June 2009. Among these patients, 1671 (14%) declined to participate. Of the 9949 patients enrolled during that period, 8308 completed at least one religious measure and constitute the population for this analysis.
Patient characteristics are described in Table 1. Of note, 73% of patients were African American, 60% were female, 43% were 61 years of age or older, and 14% had a CCI score of four or greater, indicating that a majority were not terminally ill. Participants were fairly religious, with 35% attending services once a week or more, 50% endorsing high intrinsic religiosity, and 40% having high spirituality.
Table 1.
Patient Characteristics (n =8,308).
| Demographic Characteristics | n (%) |
|---|---|
| Sex | |
| Men | 3,338 (40) |
| Women | 4,959 (60) |
| Age | |
| 30 or younger | 708 (13) |
| 31-40 | 645 (12) |
| 41-50 | 821 (15) |
| 51-60 | 989 (18) |
| 61-70 | 857 (15) |
| 71-80 | 829 (15) |
| 81 or older | 697 (13) |
| Race/Ethnicity | |
| Black/African American | 6,066 (73) |
| White | 1,644 (20) |
| Hispanic/Latino | 201 (2) |
| Other | 348 (4) |
| Married | |
| No | 5,794 (70) |
| Yes | 2,461 (30) |
| Education Level | |
| No high school degree | 1,791 (22) |
| High school degree | 2,535 (32) |
| Some college | 2,180 (27) |
| College degree | 1,535 (19) |
| Religious Characteristics | |
| Attendance at Religious Services | |
| Never | 1,720 (22) |
| Less than once a week | 3,491 (44) |
| Once a week or more | 2,767 (35) |
| Intrinsic Religiosity | |
| Low | 1,171 (15) |
| Moderate | 2,720 (35) |
| High | 3,914 (50) |
| Spirituality | |
| Low | 1,578 (20) |
| Moderate | 3,211 (40) |
| High | 3,206 (40) |
| Measures of Health Status | |
| Charlson Comorbidity Index | |
| 0 | 2,770 (35) |
| 1 | 1,456 (18) |
| 2 | 1,316 (17) |
| 3 | 1,246 (16) |
| 4+ | 1,126 (14) |
| Self-Reported Health (0-100) | |
| 81-100 | 978 (12) |
| 61-80 | 2,250 (29) |
| 41-60 | 2,587 (33) |
| 21-40 | 1,149 (15) |
| 0-20 | 906 (12) |
Note: n counts vary somewhat because of partial non-response.
End-of-Life Care Preferences
As seen in Table 2, few patients in this population had formal end-of-life care directives; only 1.5% had an advance directive, 10.4% had DNR orders, and 3% had a DPAHC. Half of patients (51%) reported that they had informally designated a family member or friend as a decision maker.
Table 2.
Prevalence of End-of-Life Care Directives (n=8308)
| n (%) | |
|---|---|
| Advance Directive | 91 (1.5) |
| DNR order | 214 (10.4) |
| Specified decision-maker a | 2,835 (53) |
Includes both formally designated (Durable Power of Attorney for Health Care) and informally designated decision makers.
Religious Characteristics as Predictors of End-of-Life Care Preferences
Religious characteristics, in multivariate analysis, were not significantly associated with having a DNR order . In multivariate analysis (but not bivariate analysis), advance directives were slightly more common among patients with moderate spirituality than among those with low spirituality (1.1% vs. 2.0%, P=0.15, odds ratio [OR] 0.5, 95% confidence interval [CI] 0.2, 0.9). Compared with those with low intrinsic religiosity, patients were more likely to have a specified decision maker if they had high intrinsic religiosity (54.6% vs. 47.6%, P=0.003; OR 1.3, 95% CI 1.1, 1.6). Similarly, compared with those with low spirituality, those with high spirituality were more likely to have a specified decision maker (56.0% vs. 49.3%, P<0.001, OR 1.3, 95% CI 1.1, 1.5). (Table 4)
Table 4.
Prevalence and Likelihood of End-of-Life Directives, Stratified by Patients’ Religious Characteristics
| DNR Order | Advance Directive | Specified Decision Maker | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Bivariate | Multivariate b | Bivariate | Multivariate b | Bivariate | Multivariate b | ||||
| % | p (χ2) | OR (95%CI) | % | p(χ2) | OR (95%CI) | % | p(χ2) | OR (95% CI) | |
| Religious Characteristics (n a) | |||||||||
| Attendance at Religious Services | |||||||||
| Never (1103) | 11.9 | 1.2 (0.7, 2.0) | 1.6 | 1.0 (Referent) | 50.6 | 1.0 (Referent) | |||
| Less than once a week (2225) | 7.5 | 0.002 | 1.0 (Referent) | 1.5 | 0.69 | 1.0 (0.5, 2.0) | 51.0 | 0.002 | 1.0 (0.9, 1.2) |
| Once a week or more (1826) | 12.5 | 1.3 (0.8, 2.1) | 1.3 | 0.7 (0.4, 1.5) | 56.1 | 1.1 (1.0, 1.4) | |||
| Intrinsic Religiosity | |||||||||
| Low (769) | 11.9 | 1.6 (0.8, 3.2) | 2.0 | 1.0 (Referent) | 47.6 | 1.0 (Referent) | |||
| Moderate (1737) | 7.4 | 0.013 | 1.0 (Referent) | 1.1 | 0.21 | 0.5 (0.2, 1.2) | 53.3 | 0.003 | 1.3 (1.1, 1.6) c |
| High (2550) | 11.5 | 1.6 (1.0, 2.6) | 1.6 | 0.8 (0.4, 1.7) | 54.6 | 1.3 (1.1, 1.6) c | |||
| Spirituality | |||||||||
| Low (1015) | 9.4 | 1.0 (Referent) | 2.0 | 1.0 (Referent) | 49.3 | 1.0 (Referent) | |||
| Moderate (2083) | 10.2 | 0.607 | 1.1 (0.6, 2.1) | 1.1 | 0.15 | 0.5 (0.2, 0.9) c | 51.2 | <0.001 | 1.1 (0.9, 1.3) |
| High (2086) | 11.2 | 1.4 (0.7, 2.6) | 1.6 | 0.7 (0.4, 1.4) | 56.0 | 1.3 (1.1, 1.5) c | |||
n counts vary slightly by analysis because of partial non-response.
Odds ratios (95% confidence intervals) from multivariate logistic regression, after adjustment for sex, age, race/ethnicity, marital status, education level, and self, rated health score.
P<0.05.
Other Predictors of End-of-Life Care Directives
In multivariate analysis, several demographic characteristics were associated with having an advance directive, a DNR, or a specified proxy decision maker. After adjustment for other demographic characteristics, religious characteristics and self-rated health, older patients were more likely to have all three directives. Compared with black patients, white patients were more likely to have a DNR order (OR 1.7; 95% CI 1.0, 2.9) and an advance directive (OR 2.1; 95% CI 1.1, 4.0). Married patients were more likely to have an advance directive (OR 2.8; 95% CI 1.5, 5.0) and a specified decision maker (OR 1.3; 95% CI 1.1, 1.5), and those with at least a high school degree were more likely than those without to have an advance directive. Sex was not associated with any end-of-life directives.
With respect to measures of health status, those with the lowest self-rated health (0-20) were more likely than those with the highest to have an advance directive (OR 5.3; 95% CI 1.5, 19). CCI scores were not associated with any end-of-life directives.
In analyses to explore possible explanations for relationships between religious characteristics and having a specified decision maker, religious characteristics were not associated with levels of trust in physicians or in the hospital care team, nor with having a caregiver at home or being discharged to home. Nor were any of these associations significant in analyses limited to patients with more severe illness, measured either by CCI score or self-rated health.
Discussion
In a large sample of general medicine inpatients in an urban academic medical center, we found that highly religious and spiritual patients did not differ from other patients in their likelihood of having an advance directive or DNR order, but they were modestly more likely to designate someone to help make end-of-life care decisions. To our knowledge, this study is the first to examine general measures of religiosity and spirituality as predictors of patients’ end-of-life decisions, rather than the more behaviorally specific measures of religious coping. In addition, to our knowledge no study has yet demonstrated that religious and spiritual patients are more likely to specify a decision maker. Some of our results differ from those of prior studies. Unlike studies of terminally ill cancer patients (15, 16, 18, 19), we did not find that patients who are more religious or spiritual are less likely to have an advance directive—even among those patients who are the most severely ill. Perhaps general medicine inpatients are less likely to have given much thought to their preferences for end-of-life care, because many do not have illnesses that are as obviously life-threatening as cancer. Or perhaps, given the often predictable and severe courses of many cancers, oncologists more often encourage patients to think through and to formalize their end-of-life care preferences, making end-of-life directives more common among cancer patients (15, 16, 18) than general medicine patients.
Our findings are consistent with the results of a prior study showing that higher private religiosity was associated with having “set [one’s] affairs in order” (21). Our results have implications for end-of-life care planning. Whereas most patients in this study did not appear to have terminal illnesses, almost half were older than 60 years, and one in seven were severely ill as measured by the CCI. These patients, who are either vulnerable to or directly experiencing severe illness, may benefit from thinking about end-of-life care preferences before they develop terminal illnesses. Indeed, it would seem that end-of-life care preferences should be considered before patients are suddenly overwhelmed with a life-threatening illness, or have lost the capacity to make such preferences known. Along these lines, Schwartz et al. (26) observed that physicians can help patients define and document their end-of-life care preferences by starting end-of-life care discussions in the outpatient setting. They speculated that this would decrease the gap between patients’ wishes and what actually happens with respect to medical care at the end of life (26).
Our study corroborates other findings from prior studies. The generally high level of religiosity and spirituality among this patient population is consistent with studies of patients with terminal cancer (15, 16, 19) and with the finding that 83% of Americans believe in God (24). In our population, advance directives were markedly uncommon among all races/ethnicities, but consistent with multiple prior studies (14-16, 19), African-American patients were less likely to have an advance directive than white patients. Several explanations for this difference have been advanced. For example, evidence indicates that, on average, African Americans more commonly request life-sustaining treatments, have less trust in the medical profession, are less comfortable discussing death, and are more likely to have spiritual beliefs that may conflict with limiting life-sustaining care (14, 17). Balboni et al. have suggested that the relationship between religiousness and having an advance directive may be confounded somewhat by non-white race/ethnicity, as minorities tend to be more religious and also less likely to have an advance directive (15)—a pattern we also found in our patient population.
Why religious and spiritual patients would be more likely to designate a proxy decision maker is not entirely clear. Jenkins and Pargament have suggested that religion may help preserve a connection to others, particularly during illness (27). Thus, we hypothesized that patients who attend religious services frequently would be more likely to have such connections and, therefore, to have a specified decision maker. However, among the three measures of religion and spirituality, religious attendance was the least associated with having a designated decision maker. Furthermore, no associations were found between any of the religious characteristics and other expected effects of having a supportive community, such as having a caregiver at home. Another possible explanation is that self-rated religiosity and spirituality are proxies for seeing oneself as relational and more trusting of others, and, therefore, of having entrusted one’s end-of-life decisions to another specified person (28). However, none of the religious measures was associated with other possible indicators of trust, such as reporting trust in physicians or in the hospital care team.
We did not detect any independent association of religiosity or spirituality with having a DNR order while in the hospital. In fact, the relationship between religiosity/spirituality and having DNR orders and advance directives was nonlinear: Patients with high or low religious attendance, religiosity, and spirituality were slightly more likely than those with moderate religion/spirituality scores to have a DNR order or an advance directive. A similar pattern was found in one study of buffering against fear of death, which may be associated with having a DNR order (29). Some educational groups have reached out to religious congregations in an effort to encourage end-of-life planning (30-32), perhaps influencing the most religious or spiritual patients. Alternatively, the religious patients in our sample may have been part of religious communities that encourage such planning. On the other end of the spectrum, patients with low religiosity and spirituality tended to be more educated and wealthier, two factors that are associated with having formal end-of-life care directives (33).
This study has important limitations. We have no information regarding patients’ religious denominations. Therefore, we cannot speculate about what particular religious values or practices may drive patients’ decisions in this arena, nor can we determine the specific religious communities to which our conclusions are applicable. The predominantly African-American patient population allows insight into this community, but cannot be easily generalized to society as a whole. Furthermore, the patients were drawn from a single urban hospital that is not necessarily representative of patients elsewhere. Further studies might include patients’ religious denominations in analyses of their end-of-life care preferences. They also might assess to what extent patients would like physicians to ask them about their religious and spiritual concerns as part of discussions about end-of-life care preferences. As reported recently, patients who are able to talk with someone in the hospital about their religious and spiritual concerns tend to be more satisfied with the care they receive (34). What is not known is whether such discussions potentially change the sorts of end-of-life care choices that patients make. In addition, future studies might use multi-item measures of spirituality such as the Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale (FACIT-Sp) to assess spirituality. Finally, in the future, we hope to examine whether the relationship between religiosity and end-of-life care preferences is different for patients with different clinical diagnoses.
Despite these limitations, this study indicates a general preference among religious patients for personal/informal over impersonal/formal methods of making end-of-life care decisions. These findings highlight the need for further study of patient religiosity and spirituality in order to understand and respect patients’ preferences for care at the end of life.
Table 3.
Prevalence and Likelihood of End-of-Life Directives, by Patient Demographic Characteristics and Self-Rated Health
| DNR Order | Advance Directive | Specified Decision Maker | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Bivariate | Multivariate b | Bivariate | Multivariate b | Bivariate | Multivariate b | ||||
| % | P(χ2) | OR (95% CI) | % | P (χ2) | OR (95%CI) | % | p (χ2) | OR (95% CI) | |
| Patient Characteristics (n a) | |||||||||
| Sex | |||||||||
| Men (2128) | 7.6 | 0.001 | 1.0 (Referent) | 1.5 | 0.73 | 1.0 (Referent) | 50.9 | 0.03 | 1.0 (Referent) |
| Women (3254) | 12.3 | 1.2 (0.7, 2.1) | 1.4 | 1.3 (0.7, 2.4) | 53.8 | 1.1 (1.0, 1.3) | |||
| Age | |||||||||
| 30 or younger (569) | 0.9 | 1.0 (Referent) | 0.4 | 1.0 (Referent) | 49.7 | 1.0 (Referent) | |||
| 31-40 (499) | 0.8 | 1.7 (0.2, 20) | 0.4 | 0.8 (0.1, 5.8) | 51.7 | 1.0 (0.8, 1.3) | |||
| 41-50 (662) | 2.6 | 5.1 (0.6, 44) | 0.8 | 1.5 (0.3, 8.1) | 49.7 | 0.9 (0.7, 1.1) | |||
| 51-60 (772) | 3.1 | <0.001 | 5.5 (0.7, 44) | 1.4 | <0.001 | 2.5 (0.5, 12) | 57.9 | <0.001 | 1.2 (1.0, 1.6) |
| 61-70 (675) | 6.9 | 13 (1.7, 100) c | 2.2 | 3.1 (0.6, 15) | 58.5 | 1.2 (0.9, 1.6) | |||
| 71-80 (678) | 12.3 | 23 (3.0, 170) c | 2.4 | 6.6 (1.4, 30) c | 59.9 | 1.4 (1.1, 1.8) c | |||
| 81 or older (596) | 27.0 | 51 (6.9, 383) c | 3.4 | 7.5 (1.6, 35) c | 58.2 | 1.3 (1.0, 1.8) c | |||
| Race/Ethnicity | |||||||||
| Black/African-Amer. (4081) | 9.9 | 1.0 (Referent) | 0.8 | 1.0 (Referent) | 51.4 | 1.0 (Referent) | |||
| White/Caucasian (973) | 12.8 | <0.001 | 1.7 (1.0, 2.9) c | 4.0 | <0.001 | 2.1 (1.1, 4.0) c | 56.3 | 0.006 | 1.0 (0.9, 1.3) |
| Hispanic/Latino (139) | 6.7 | 1.5 (0.5, 4.4) | 2.2 | 3.4 (1.0, 12) | 61.2 | 1.3 (0.9, 2.0) | |||
| Other (168) | 11.5 | 0.7 (0.2, 3.4) | 2.4 | 2.1 (0.5, 9.8) | 55.4 | 1.4 (0.9, 2.3) | |||
| Married | |||||||||
| No (3865) | 11.4 | 0.038 | 1.0 (Referent) | 0.8 | <0.001 | 1.0 (Referent) | 51.0 | <0.001 | 1.0 (Referent) |
| Yes (1479) | 8.4 | 0.6 (0.4, 1.1) | 3.1 | 2.8 (1.5, 5.0) c | 57.2 | 1.3 (1.1, 1.5) c | |||
| Education Level | |||||||||
| No high school degree (1188) | 9.3 | 1.0 (Referent) | 0.5 | 1.0 (Referent) | 50.8 | 1.0 (Referent) | |||
| High school degree (1639) | 10.5 | 0.044 | 1.2 (0.7, 2.2) | 1.4 | <0.001 | 3.8 (1.1, 13) c | 52.8 | 0.045 | 1.0 (0.9, 1.2) |
| Some college (1391) | 6.7 | 1.2 (0.6, 2.4) | 1.2 | 4.7 (1.3, 17) c | 51.8 | 1.1 (0.9, 1.3) | |||
| College degree (969) | 11.9 | 1.7 (0.9, 3.2) | 3.4 | 8.3 (2.4, 29) c | 56.6 | 1.2 (1.0, 1.5) | |||
| Self-Reported Health (0-100) | |||||||||
| 81-100 (635) | 6.4 | 1.0 (Referent) | 0.8 | 1.0 (Referent) | 51.8 | 1.0 (Referent) | |||
| 61-80 (1498) | 6.3 | 0.6 (0.3, 1.3) | 1.0 | 1.8 (0.5, 6.3) | 51.4 | 0.9 (0.7, 1.1) | |||
| 41-60 (1654) | 9.3 | <0.001 | 1.0 (0.5, 1.7) | 1.3 | 0.017 | 2.2 (0.6, 7.8) | 53.5 | 0.51 | 1.0 (0.8, 1.2) |
| 21-40 (754) | 15.4 | 1.3 (0.6, 2.8) | 1.6 | 2.1 (0.5, 8.0) | 55.0 | 1.0 (0.8, 1.3) | |||
| 0-20 (574) | 17.5 | 1.7 (0.8, 3.7) | 2.8 | 5.3 (1.5, 19) c | 52.4 | 1.0 (0.7, 1.3) | |||
n counts vary slightly by analysis because of partial non-response.
Odds ratios (95% confidence intervals) from multivariate logistic regression, after adjustment for sex, age, race/ethnicity, marital status, education level, self-rated health score, and religious characteristics.
P<0.05.
Acknowledgments
Financial support for this work was provided by the Agency for Healthcare Quality and Research through the Hospital Medicine and Economics Center for Education and Research in Therapeutics (CERT) (U18 HS016967-01, D.O. Meltzer, PI), a Midcareer Career Development Award from the National Institute of Aging (1K24AG031326-01, D.O. Meltzer, PI) and the Robert Wood Johnson Investigator Program, (RWJF Grant ID 63910, D.O. Meltzer, PI). Dr. Curlin was supported by a career development award from the national Center for Complementary and Alternative Medicine (1 K23 AT002749-01A1). Mr. Karches’ effort was supported by the Pritzker School of Medicine Summer Research Program and a Ruth L. Kirschstein National Research Service Award Short-Term Institutional Research Training Grant (T35) from the National Institutes of Health, Bethesda, MD. The study’s contents are solely the responsibility of the authors and do not represent the official views of the funding agencies. The authors had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
We gratefully acknowledge Caleb Alexander, William Meadow, Ryan Lawrence and Manuel Diaz for their insightful comments on early drafts of this manuscript, and Andrea Flores, Benjamin Vekhter, and Ainoa Mayo for their help with data cleaning and analysis.
Footnotes
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Disclosures There were no potential conflicts of interest in the research reported or the development of the submission. The funding source/sponsor was not involved in the conduct of the study or development of the submission.
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