Religious Affiliation and Major Depression Keith G. Meador, M.P.H. Harold
G.
with other affiliations. Carefully designed studies are needed to Un-
M.D.,
Koenig,
derstand ofreilgion
M.D.,
M.Sc. Dana
C. Hughes,
Ph.D.
the
complex
and
interactions
mental
health.
professor of psychiatry and preventive medicine at Vanderbilt University Medical Center, Nashville, Tennessee 37232. Drs. Koenig, Hughes, Blazer, and George are affiliated with the department of psychiatry at Duke University Medical Center in Durham, North Carolina. Dr. Turnbull is affiliated with the Western Psychiatric Institute and Clinic in Pittsburgh.
Although writers and researchers in several disciplines have subjected religious belith and practices to scientific inquiry, the literature on the association between religion and mental health treatment outcomes is sparse (1). Religion as a legitimate research variable has been largely ignored by psychiatric researchers. In addition, a lack ofnosological clarity within psychiatry has inhibited systematic research efforts. Despite advances in psychiatric research methodologies, the complexity of measuring psychiatric phenomena coupled with measurement difficulties inherent in research on religious beliefs and practices necessitates caution. Consideration ofany religious factor as an independent variable requires acceptance ofa paradigm of illness and health in which psychosocial factors operate. Both Cassel (2) and Engel (3) have described models with different but complementary emphases that provide a theoretical basis for acceptance of such a paradigm. In the study reported here, we used an adaptational-functional paradigm that allows one to assume that religious affiliations most likely serve as proxies for more elemental factors in depressive illness. Religious affiliation often reflects a discrete set of beliefs on which a person’s view of the world is based. Attitudes and patterns of behaviors-both interpersonal and intrapersonal-often arise from the particular belief system prescribed by one’s religious affiliation. Religious affiliation may also act as a proxy for other variables that affect
1204
December
Dan
G. Blazer,
Joanne Linda
M.D.,
Turnbull, K. George,
Ph.D.
Ph.D. Ph.D.
the Duke Epidemiologic Catchment Area survey were used to examine the relationship between religious affiliation and
Datafrom
major
depression
among
2,850
adults in the community. Religious affiliations were categorized into six groups: mainline Protestant (27
percent),
conservative
Protes-
tant (59 percent), Pentecostal (4.2 percent), Catholic (2.4 percent), other religions (2.6 percent), and no affiliation (4.4 percent). The six-month prevalence of major depression among Pentacostals was 5.4percent, comparedwith 1 .7 percent for the entire sample. Even after psychosocial factors such as gender, age, race, socioeconomic status, negative life events, and social support were controlled for, the likelihood of major depression
among times
Dr.
Pentecostals greater
Meador
than
was among
is assistant
three persons
clinical
1992
VoL 43
No.
12
mental health, such as socioeconomic status or perhaps social support. Affiliation with well-established denominations that are firmly rooted in the culture ofa society may be indicative of emotional stability, whereas involvement in religious groups that run counter to the prevailing culture may reflect or engender discontent, isolation, or rebellion against societal norms. Thus religious affiliation may affect mental health for better or for worse in many ways. The study reported here examined the simplest of religious variables-religious affiliationand its relationship to a discrete psychiatric disorder-major depression-in a large sample of adults in the community. It used data from the Piedmont Health Survey in North Carolina, part of the Epidemiologic Catchment Area project. Methods
Sample.
The data used in this study were collected as part of the Piedmont Health Survey or Duke Epidemiologic Catchment Area (ECA) project, which was part ofthe multisite ECA collaborative program sponsored by the National Institute of Mental Health. Five sites geographically distributed throughout the continental United States were randomly sampled to yield interviews from approximately 3,000 households in each community. At all of the sites, a core database of sociodemographic information was established, and the prevalence of mental disorders as diagnosed by the Diagnostic Interview Schedule (DIS) was determined for each site. The Piedmont site was the only one where data about religious affiliation were collected. In the Piedmont Health Survey,
Hospital
and Community
Psychiatry
one urban and four rural counties in central North Carolina were initially stratified into segments based on racia!, rural-urban, and economic characteristics. Segments were randomly sampled, and all housing units from the selected segments were listed. Housing units were then randomly selected. Eligible participants in each household were listed, and one potential participant from each dwelling was selected using a predetermined method (4). This procedure ensured that regardless of size and composition of the household, a random selection of respondents was obtained. Persons over the age of 60 were oversampled in the survey, requiring that all analyses be weighted (see below). The response rate was 75 to 80 percent ofeligible respondents. The findings presented here are based on a sample of 2,993 community respondents participating in both wave I and wave II interviews (conducted in 1981-82 and 198384, respectively) during the Piedmont Health Survey. Some persons were excluded from the sample due to missing data, leaving a final sampie of 2,850. A bivariate analysis showed no significant differences in the variables of interest between the excluded subjects and the rest of the sample. Religious affiliation was recorded during wave I; more detailed information on religious characteristics was collected during wave II. To maintain continuity between this report and future reports on the religious and mental health characteristics of this cohort, we chose to examine diagnoses of depression obtamed during wave II. Given the stability of religious affiliation, the likelihood ofits changing during the one to two years that separated waves I and II is quite low. Diagnosis. Information was gathered through the Diagnostic Interview Schedule (DIS), administered to respondents in interviews that lasted approximately two hours. The DIS is a highly structured interview designed to be administered by lay interviewers and capable of generating computer-based diagnoses for selected DSM-IlI disorders (5). The DIS elicits information about
both current and lifetime prevalence of the disorders. This study focused on major depression experienced during the six months before the interview. Religious affiliation. Information about religious affiliation was elicited by the question “Is your church preference Protestant, Catholic, Jewish, or something else?” Interviewers were instructed to inquire about a specific denomination if the affiliation was Protestant. Based on responses to these questions, respondents were placed in one of six groups for analysis. Although Roof and McKinney’s classifications (6) of religious groups were used as a reference, further aggregation of groups was needed for analytic purposes. The six groups were mainline Protestants (Presbyterian, Lutheran, Congregational, Reformed, United Church of Christ, Episcopal, United Methodist, African Methodist Episcopal, Disciples ofChrist, Christian Church, Salvation Army, Quaker, Community Church, and other Protestant), conservative Protestants (Baptist, United Missionary, Nazarene, Church of Christ, Primitive Baptist, Freewill Baptist, Seventh Day Adventist, Southern Baptist, Christian and Missionary Alliance, and other fundamentalists), Pentecostals (Church of God, Assembly ofGod, Church ofGod in Christ, and Holiness), Catholics, all other religions (Latter Day Saints, Unitarian, Jehovah ‘s Witnesses, J ewish, Greek Orthodox, Muslim, Black Muslim, Buddhist, Hindu, agnostic, atheist, and other religions), and no religious preference or refused to answer. (In our estimation, atheism involves a belief systemthat of not believing-and thus it was regarded as a religious affihiation.) Social support and other vanables. Independent variables other than religious affiliation and demographic characteristics were psychosocial variables that have been determined to be risk factors for major depression (for example, in the study by Crowell and associates [7]). Social support was measured using the subjective support subscale of the Duke Social Support Index, which consists
Hospital
December
and
Community
Psychiatry
1992
Vol.
43
No.
12
Table 1 Demographic and psychosocial characteristics of 2,850 adults participating in the Piedmont Health Survey Weighted %
Characteristic Age (years) 18 to 24
8.8 32.9
25 to44 45 to 64
28.7
18.0 41.5
29.6
27.0 13.5
Male Female Race
39.5 60.5
45.4 54.6
Black White
35.3 64.7
64.1
65 and over Gender
or other Socioeconomic status (quartile)1
35.9
First
27.7
Second
29.6
18.2 31.4
Third
27.9
32.9
Fourth
14.8
17.6
Residence Urban
46.8
53.0
Rural
53.2
47.0
Married
52.9
59.5
Widowed
20.7
status
Marital
Separated or divorced Never married Negative unexpected life event in past six months
9.1
12.8
11.0
13.6
20.3
None
89.2
88.8
One or more
10.8
11.2
Unimpaired
87.5
88.2
Imparied
12.5
11.8
27.4
26.1
58.9
57.1
Social
support
Religious
affiliation
Mainline tant
Protes-
Conservative
Protestant
1
Pentecostal Catholic Other
4.2 2.4 2.6
4.3
None
4.4
5.6
3.7 3.2
=poorest quartile
of ten items eliciting respondents’ perceptions ofthe adequacy of their social support (8). Subjective perception ofsupport was the variable most strongly related to mental health measures in two previous studies (9,10). Data were weighted to account for oversampling ofelderly persons,
1205
Results Table 1 shows the sociodemographic characteristics of the 2,850 respondents. The unweighted distributions were skewed by the oversampling of
elderly persons, which inflated the proportions of persons who were female, white, widowed, and of low socioeconomic status. The weighted distributions are representative of the adult population of the catchment area. The age and gender distributions are consistent with those in the general populations of North Carolina and the U.S. Approximately one-third of the respondents were black, and the socioeconomic distnibution reflected that in the general population. The sample was approximately halfurban and half rural by design. Sixty percent of the respondents were married; about 20 percent had never been married. Approximately 1 1 percent of the sample had experienced one or more very negative, unexpected life events during the past year, and about 12 percent described social supports that would be classified as impaired. The prevalence of current major depression in the total sample was 1.7 percent based on weighted data. The distribution of religious offihiations in the sample was as follows: mainline Protestants, 747; conservative Protestants, 1,631; Pentecostals, 122; Catholics, 91 ; all other religions, 91 ; and no religious preference or refused to answer, 160. About 26 percent of the Piedmont Health Survey sample were mainline Protestants compared with 33 percent of the General Social Survey (GSS), the national sample used by Roofand McKinney (6). Fifty-seven percent ofthe Piedmont sample were conservative Protestants; approximately 16 percent ofthe GSS sample would be considered members of this group. About 4.3 percent of the Piedmont sample were Pentecostals, compared with 3.8 percent of the GSS sample. This minimal difference appears to indicate that Pentecostal groups are more evenly distributed in the U.S. than other conservative Protestant groups . Catholics were markedly less common in the Piedmont sample (3.7 percent, compared with 25 percent ofthe GSS sample). Only 3.2 percent of the Piedmont sample fell into the category ofother religions, with the majonity giving Judaism as a religious
affiliation; 5 .6 percent claimed no religious preference or refused to answer. Fifty-one persons in the sample were diagnosed as having major depression (based on weighted data). Table 2 shows the prevalence of major depression in the previous six months by religious affiliation. Of note is the increased prevalence of depression among Pentecostals; 5.4 percent of Pentecostals (N=7) had this diagnosis, compared with 1.7 percent of the total sample (MantelHaenszel X2=9#{149}37, df=1, p
G.
with other affiliations. Carefully designed studies are needed to Un-
M.D.,
Koenig,
derstand ofreilgion
M.D.,
M.Sc. Dana
C. Hughes,
Ph.D.
the
complex
and
interactions
mental
health.
professor of psychiatry and preventive medicine at Vanderbilt University Medical Center, Nashville, Tennessee 37232. Drs. Koenig, Hughes, Blazer, and George are affiliated with the department of psychiatry at Duke University Medical Center in Durham, North Carolina. Dr. Turnbull is affiliated with the Western Psychiatric Institute and Clinic in Pittsburgh.
Although writers and researchers in several disciplines have subjected religious belith and practices to scientific inquiry, the literature on the association between religion and mental health treatment outcomes is sparse (1). Religion as a legitimate research variable has been largely ignored by psychiatric researchers. In addition, a lack ofnosological clarity within psychiatry has inhibited systematic research efforts. Despite advances in psychiatric research methodologies, the complexity of measuring psychiatric phenomena coupled with measurement difficulties inherent in research on religious beliefs and practices necessitates caution. Consideration ofany religious factor as an independent variable requires acceptance ofa paradigm of illness and health in which psychosocial factors operate. Both Cassel (2) and Engel (3) have described models with different but complementary emphases that provide a theoretical basis for acceptance of such a paradigm. In the study reported here, we used an adaptational-functional paradigm that allows one to assume that religious affiliations most likely serve as proxies for more elemental factors in depressive illness. Religious affiliation often reflects a discrete set of beliefs on which a person’s view of the world is based. Attitudes and patterns of behaviors-both interpersonal and intrapersonal-often arise from the particular belief system prescribed by one’s religious affiliation. Religious affiliation may also act as a proxy for other variables that affect
1204
December
Dan
G. Blazer,
Joanne Linda
M.D.,
Turnbull, K. George,
Ph.D.
Ph.D. Ph.D.
the Duke Epidemiologic Catchment Area survey were used to examine the relationship between religious affiliation and
Datafrom
major
depression
among
2,850
adults in the community. Religious affiliations were categorized into six groups: mainline Protestant (27
percent),
conservative
Protes-
tant (59 percent), Pentecostal (4.2 percent), Catholic (2.4 percent), other religions (2.6 percent), and no affiliation (4.4 percent). The six-month prevalence of major depression among Pentacostals was 5.4percent, comparedwith 1 .7 percent for the entire sample. Even after psychosocial factors such as gender, age, race, socioeconomic status, negative life events, and social support were controlled for, the likelihood of major depression
among times
Dr.
Pentecostals greater
Meador
than
was among
is assistant
three persons
clinical
1992
VoL 43
No.
12
mental health, such as socioeconomic status or perhaps social support. Affiliation with well-established denominations that are firmly rooted in the culture ofa society may be indicative of emotional stability, whereas involvement in religious groups that run counter to the prevailing culture may reflect or engender discontent, isolation, or rebellion against societal norms. Thus religious affiliation may affect mental health for better or for worse in many ways. The study reported here examined the simplest of religious variables-religious affiliationand its relationship to a discrete psychiatric disorder-major depression-in a large sample of adults in the community. It used data from the Piedmont Health Survey in North Carolina, part of the Epidemiologic Catchment Area project. Methods
Sample.
The data used in this study were collected as part of the Piedmont Health Survey or Duke Epidemiologic Catchment Area (ECA) project, which was part ofthe multisite ECA collaborative program sponsored by the National Institute of Mental Health. Five sites geographically distributed throughout the continental United States were randomly sampled to yield interviews from approximately 3,000 households in each community. At all of the sites, a core database of sociodemographic information was established, and the prevalence of mental disorders as diagnosed by the Diagnostic Interview Schedule (DIS) was determined for each site. The Piedmont site was the only one where data about religious affiliation were collected. In the Piedmont Health Survey,
Hospital
and Community
Psychiatry
one urban and four rural counties in central North Carolina were initially stratified into segments based on racia!, rural-urban, and economic characteristics. Segments were randomly sampled, and all housing units from the selected segments were listed. Housing units were then randomly selected. Eligible participants in each household were listed, and one potential participant from each dwelling was selected using a predetermined method (4). This procedure ensured that regardless of size and composition of the household, a random selection of respondents was obtained. Persons over the age of 60 were oversampled in the survey, requiring that all analyses be weighted (see below). The response rate was 75 to 80 percent ofeligible respondents. The findings presented here are based on a sample of 2,993 community respondents participating in both wave I and wave II interviews (conducted in 1981-82 and 198384, respectively) during the Piedmont Health Survey. Some persons were excluded from the sample due to missing data, leaving a final sampie of 2,850. A bivariate analysis showed no significant differences in the variables of interest between the excluded subjects and the rest of the sample. Religious affiliation was recorded during wave I; more detailed information on religious characteristics was collected during wave II. To maintain continuity between this report and future reports on the religious and mental health characteristics of this cohort, we chose to examine diagnoses of depression obtamed during wave II. Given the stability of religious affiliation, the likelihood ofits changing during the one to two years that separated waves I and II is quite low. Diagnosis. Information was gathered through the Diagnostic Interview Schedule (DIS), administered to respondents in interviews that lasted approximately two hours. The DIS is a highly structured interview designed to be administered by lay interviewers and capable of generating computer-based diagnoses for selected DSM-IlI disorders (5). The DIS elicits information about
both current and lifetime prevalence of the disorders. This study focused on major depression experienced during the six months before the interview. Religious affiliation. Information about religious affiliation was elicited by the question “Is your church preference Protestant, Catholic, Jewish, or something else?” Interviewers were instructed to inquire about a specific denomination if the affiliation was Protestant. Based on responses to these questions, respondents were placed in one of six groups for analysis. Although Roof and McKinney’s classifications (6) of religious groups were used as a reference, further aggregation of groups was needed for analytic purposes. The six groups were mainline Protestants (Presbyterian, Lutheran, Congregational, Reformed, United Church of Christ, Episcopal, United Methodist, African Methodist Episcopal, Disciples ofChrist, Christian Church, Salvation Army, Quaker, Community Church, and other Protestant), conservative Protestants (Baptist, United Missionary, Nazarene, Church of Christ, Primitive Baptist, Freewill Baptist, Seventh Day Adventist, Southern Baptist, Christian and Missionary Alliance, and other fundamentalists), Pentecostals (Church of God, Assembly ofGod, Church ofGod in Christ, and Holiness), Catholics, all other religions (Latter Day Saints, Unitarian, Jehovah ‘s Witnesses, J ewish, Greek Orthodox, Muslim, Black Muslim, Buddhist, Hindu, agnostic, atheist, and other religions), and no religious preference or refused to answer. (In our estimation, atheism involves a belief systemthat of not believing-and thus it was regarded as a religious affihiation.) Social support and other vanables. Independent variables other than religious affiliation and demographic characteristics were psychosocial variables that have been determined to be risk factors for major depression (for example, in the study by Crowell and associates [7]). Social support was measured using the subjective support subscale of the Duke Social Support Index, which consists
Hospital
December
and
Community
Psychiatry
1992
Vol.
43
No.
12
Table 1 Demographic and psychosocial characteristics of 2,850 adults participating in the Piedmont Health Survey Weighted %
Characteristic Age (years) 18 to 24
8.8 32.9
25 to44 45 to 64
28.7
18.0 41.5
29.6
27.0 13.5
Male Female Race
39.5 60.5
45.4 54.6
Black White
35.3 64.7
64.1
65 and over Gender
or other Socioeconomic status (quartile)1
35.9
First
27.7
Second
29.6
18.2 31.4
Third
27.9
32.9
Fourth
14.8
17.6
Residence Urban
46.8
53.0
Rural
53.2
47.0
Married
52.9
59.5
Widowed
20.7
status
Marital
Separated or divorced Never married Negative unexpected life event in past six months
9.1
12.8
11.0
13.6
20.3
None
89.2
88.8
One or more
10.8
11.2
Unimpaired
87.5
88.2
Imparied
12.5
11.8
27.4
26.1
58.9
57.1
Social
support
Religious
affiliation
Mainline tant
Protes-
Conservative
Protestant
1
Pentecostal Catholic Other
4.2 2.4 2.6
4.3
None
4.4
5.6
3.7 3.2
=poorest quartile
of ten items eliciting respondents’ perceptions ofthe adequacy of their social support (8). Subjective perception ofsupport was the variable most strongly related to mental health measures in two previous studies (9,10). Data were weighted to account for oversampling ofelderly persons,
1205
Results Table 1 shows the sociodemographic characteristics of the 2,850 respondents. The unweighted distributions were skewed by the oversampling of
elderly persons, which inflated the proportions of persons who were female, white, widowed, and of low socioeconomic status. The weighted distributions are representative of the adult population of the catchment area. The age and gender distributions are consistent with those in the general populations of North Carolina and the U.S. Approximately one-third of the respondents were black, and the socioeconomic distnibution reflected that in the general population. The sample was approximately halfurban and half rural by design. Sixty percent of the respondents were married; about 20 percent had never been married. Approximately 1 1 percent of the sample had experienced one or more very negative, unexpected life events during the past year, and about 12 percent described social supports that would be classified as impaired. The prevalence of current major depression in the total sample was 1.7 percent based on weighted data. The distribution of religious offihiations in the sample was as follows: mainline Protestants, 747; conservative Protestants, 1,631; Pentecostals, 122; Catholics, 91 ; all other religions, 91 ; and no religious preference or refused to answer, 160. About 26 percent of the Piedmont Health Survey sample were mainline Protestants compared with 33 percent of the General Social Survey (GSS), the national sample used by Roofand McKinney (6). Fifty-seven percent ofthe Piedmont sample were conservative Protestants; approximately 16 percent ofthe GSS sample would be considered members of this group. About 4.3 percent of the Piedmont sample were Pentecostals, compared with 3.8 percent of the GSS sample. This minimal difference appears to indicate that Pentecostal groups are more evenly distributed in the U.S. than other conservative Protestant groups . Catholics were markedly less common in the Piedmont sample (3.7 percent, compared with 25 percent ofthe GSS sample). Only 3.2 percent of the Piedmont sample fell into the category ofother religions, with the majonity giving Judaism as a religious
affiliation; 5 .6 percent claimed no religious preference or refused to answer. Fifty-one persons in the sample were diagnosed as having major depression (based on weighted data). Table 2 shows the prevalence of major depression in the previous six months by religious affiliation. Of note is the increased prevalence of depression among Pentecostals; 5.4 percent of Pentecostals (N=7) had this diagnosis, compared with 1.7 percent of the total sample (MantelHaenszel X2=9#{149}37, df=1, p
