Journal of Gerontology: SOCIAL SCIENCES 1992, Vol. 47, No. 6, S269-S278

Copyright 1992 by The Gemmologiail Society of America

Antecedents and Dimensions of Religious Involvement Among Older Black Adults Linda M. Chatters,1 Jeffrey S. Levin,2 and Robert Joseph Taylor3 'School of Public Health and Program for Research on Black Americans, Institute for Social Research, University of Michigan. department of Family and Community Medicine, Eastern Virginia Medical School. 3 School of Social Work and Program for Research on Black Americans, Institute for Social Research, University of Michigan.

concerning the significance of religious QUESTIONS involvement for older adults, particularly in relation to issues of overall health and personal adjustment (Levin, 1988), have had longstanding interest for students of religion and aging. However, a variety of conceptual, methodological, and analytical difficulties hinder an adequate specification of the nature of the religious variables under consideration, as well as of their independent relationships with both predictor and outcome measures (see Levin and Vanderpool, 1987, for a review of these issues). A strong program of research is needed on (a) the conceptualization and measurement of religious involvement as a multidimensional construct, (b) the validity of measurement models of religiosity in relation to theoretically hypothesized antecedent constructs, and (c) the confirmation of models within particular aging subpopulations at significantly higher risk of many deleterious health-related and psychosocial outcomes (e.g., older Black Americans). This study explored these issues and presents empirical findings relating to a multidimensional measurement model of religiosity for use with older Blacks. Religious Involvement as a Multidimensional Construct Although the use of single-item indicators to assess a particular aspect of.religiosity (e.g., religious attendance, subjective religiosity) provides a relatively simple method for measuring constructs like "religious involvement," this approach has been challenged on conceptual and methodological grounds (Levin, 1988). The concentration on singu-. lar aspects of religious involvement fails to adequately represent the character of the broader construct of religiosity (Levin and Vanderpool, 1987). As a consequence, religiosity is defined in relatively narrow terms (e.g., as a behavioral variable), and forms of religious involvement that occur in other domains (e.g., attitudes, beliefs, experience) are effec-

tively overlooked (Ainlay and Smith, 1984; Chatters and Taylor, 1989; Hunsberger, 1985). Research and theory addressing the general issue of religious involvement corroborate the conceptual and methodological utility of a multidimensional approach to religiosity (Levin and Vanderpool, 1987). d o c k and Stark (1965) suggested that religious involvement could be understood in terms of the five dimensions of belief, experience, ritual, knowledge, and consequences, while Moberg (1971) proposed that the two major components that underlie religiosity are the personal and the institutional. In recent years, the most popular conceptual frameworks among sociologists and psychologists of religion have been derivations of Allport's (1958) differentiation of interiorized and institutionalized religiosity, such as the various measurement indices used to distinguish intrinsic and extrinsic religiosity (Donahue, 1985; Kahoe, 1985). Research on both older adults (e.g., the work of Koenig, Smiley, and Gonzales, 1988, using the Springfield Religiosity Scale) and younger parents (e.g., the work of Strayhorn, Weidman, and Larson, 1990, using the Kauffman Religious Life Scale) has offered empirical confirmation of the importance of such a distinction. Work in the field of gerontology holds that religious involvement comprises separate dimensions that differ in relation to whether they address attitudinal, knowledge, experiential, belief, or behavioral (public and private) components (Hunsberger, 1985). Finally, various approaches have been used to define and measure religiosity within a multidimensional framework that incorporates actions or behaviors, as well as affective and cognitive or mental activities (Chatters and Taylor, 1989; Hunsberger, 1985; Levin and Vanderpool, 1989). Building upon a long legacy of work in sociology and psychology (see Levin and Schiller, 1987), religious behaviors and participation are seen to vary along a continuum S269

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This study proposed and tested a measurement model of religiosity among a sample of older (55 years of age and above) Black Americans. This model incorporates three correlated dimensions of religious involvement, termed organizational, nonorganizational, and subjective religiosity. Findings indicate that the proposed model provides a good fit to the data, is preferable to other alternative models, and exhibits convergent validity with respect to exogenous or antecedent variables (age, gender, marital status, income, education, urbanicity, and region) known to predict religious involvement. In addition, these antecedents exhibit stronger effects on subjective religiosity than on the two more behavioral dimensions of religiosity. Interpretation of these status-group differences in religiosity focuses on socialization experiences and social environment factors which may promote a religious world-view.

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Confirmatory Factor Models of Religious Involvement The precise operationalization of religious involvement is much more than an esoteric psychometric concern. Owing to the diverse nature of religious experience (i.e., attitudinal vs behavioral dimensions, public vs private behaviors, intrinsic vs extrinsic religiosity), antecedent influences such as social-structure factors bear unique and individual relation-

ships with specific dimensions of religious involvement (Cornwall, 1989; Levin, 1988). Furthermore, as just noted, one might expect these dimensions to differentially impact specific outcomes. However, the tendency to view religiosity as a singular, monolithic construct and thus treat religious indicators as interchangeable, has obscured the separate and independent effects of social-status factors on specific aspects of religious involvement and thus has frustrated the development of a coherent and accurate assessment of their effects. These methodological and analytical difficulties are again evident in studies where religious factors are employed as independent (as opposed to dependent) variables. Findings for the effects of religious involvement on outcomes such as personal adjustment are potentially spurious given a lack of clarity on the nature of the religiosity variable examined and the absence of appropriate controls for factors known to be consequential to these relationships, notably health status (Levin and Vanderpool, 1989). Clearly, considerable work is required in order to delineate the separate and distinct dimensions of religious involvement and to determine their independent relationships with antecedent social-status indicators and relevant outcome measures. One key way in which these aims can be achieved is through the development and confirmation of multidimensional, structural measurement models of religious involvement. Such models can be of great benefit to nascent research programs such as this because they allow investigators to (a) posit a theoretically supported and empirically verifiable, latent-factor model for a particular construct (e.g., religiosity), and (b) subsequently use this measurement model in theoretically specified structural-equation (or "path") models in which similar models of both exogenous (antecedent) and endogenous (consequent) constructs are simultaneously examined in relation to the construct in question and to each other. In addition, these models allow for both measurement-error and residual-error terms to be built into models prior to estimation, thus accounting for two ubiquitous problems usually unaddressed in social science research (Martin, 1987). These powerful techniques, known collectively as covariance-structure-modeling (see Bollen, 1989b) are increasingly popular tools in gerontology (Alwin, 1988), but appear to have been applied to the confirmation of latent religious factor models on only two occasions (Ainlay and Smith, 1984; Krause and Tran, 1989). The Ainlay and Smith study confirmed a threedimensional model with public, private, and attitudinal factors, but the use of an exclusively Mennonite sample limits inferences as to the external validity of this model. In the second confirmatory factor analysis of religion in gerontological research (Krause and Tran, 1989), a national probability sample of Black Americans was used, but only a twodimensional model of religiosity was examined, with nonorganizational religious behaviors and subjective religious attitudes left undifferentiated. Unfortunately, these excellent studies have not been followed up by other researchers. This has resulted in a continued proliferation of "hodgepodge" measures of religiosity which erroneously lump together indicators of religious behaviors, beliefs, attitudes, values, identification, etc., in creating single summary scores (e.g., Zuckerman, Kasl, and Ostfeld, 1984). In

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from public to private activities, typically representing the distinction between formal organizational activities and private devotional practices. Formal or organizational religious behaviors occurring within the context of a religious institution include such activities as religious attendance and church or synagogue membership, participation in formal religious groups or organizations, and holding of positions or offices. Nonorganizational or private religious behaviors occur outside of the structure of the religious institution and include behaviors such as reading religious materials, private prayer, and listening to or watching religious programming. Finally, psychological aspects of religiosity emphasize beliefs, knowledge, and attitudes, as well as self-reports of religious experiences and self-attributions regarding the importance or centrality of religion in one's life. While the multidimensional nature of religiosity is now well accepted, a consensus is yet to emerge on the preferred or appropriate operational characteristics of religious measures (e.g., number of dimensions) within particular subpopulations (e.g., Black Americans) or for use in research programs within specific disciplines (e.g., gerontology). One reason for this has been a lack of useful theoretical frameworks for conceptualizing and specifying religious effects on specific outcomes such as health or well-being, popular measures in aging research. Recently, however, such frameworks have emerged (Levin and Vanderpool, 1989), encouraging and guiding the development and confirmation of religiosity measures which are both conceptually meaningful and theoretically appropriate. Levin and Vanderpool (1989) propose one such framework for studying the relationship between religion and health outcomes. Part of a larger, dynamic model of the interconnections between religion and medicine (Vanderpool and Levin, 1990), their framework differentiates the functional components of various forms of religious involvement and describes their potentially divergent effects on physical and mental health via several hypothesized mechanisms (e.g., biological, life-style, physiological, psychological, psychosocial). Further, these mechanisms are manifested in different religious dimensions (i.e., affiliation, belief, formal religious participation, private practices, and religious experiences). For example, membership in particular religious groups (i.e., faith traditions or denominations) may have an impact on physical or mental health by virtue of the particular life styles and health-related behaviors required of religious adherents (e.g., diet; use of alcohol, tobacco, and other drugs; physical exercise). In addition, behavioral indicators such as religious membership and participation may have beneficial effects on health or wellbeing by virtue of the salutary psychosocial effects which potentially result from such involvement (e.g., social cohesiveness, continuity, and social support).

RELIGIOUS INVOLVEMENT IN OLDER BLACKS

order to emphasize the operational and functional distinctions between religious dimensions, subsequent research should (a) precisely specify the various dimensions and forms of religious involvement, (b) examine possible differences in both the structural antecedents and underlying motivations for involvement in a variety of religious pursuits (Cornwall, 1989), and (c) explore the diverse and unique ways in which different dimensions of religious expression and involvement potentially impact on individual outcomes. The first and second of these charges are the focus of the analyses presented in this article.

ties on a more frequent basis than do urban residents (Taylor, 1986). Considerably less research has examined degrees of nonorganizational religious involvement, or those religious activities which occur outside of the context of a religious institution (Chatters and Taylor, 1989). Available evidence indicates that women demonstrate higher levels of involvement in private religious behaviors than do men (de Vaus and McAllister, 1987; Koenig, Kvale, and Ferrel, 1988) and that age has a positive association with participation in nonorganizational behaviors (Levin, 1988; Moberg, 1971; Young and Dowling, 1987). The effects of marital status, education, income, region, and urbanicity on nonorganizational religious participation are less clear. Evidence for an inverse effect of income and education on private religious behaviors (Stark, 1972), as well as positive associations (Taylor and Chatters, 1991) and no effects (Young and Dowling, 1987) for these factors have been reported. Expectations for positive effects for being married (Cornwall, 1989), a Southerner (Glenn, Gotard, and Simmons, 1977), and a rural resident (Taylor, 1986) are suggested in the literature. Finally, greater levels of subjective religiosity among women (de Vaus and McAllister, 1987) and older persons (Chatters and Taylor, 1989; Hunsberger, 1985; Markides, 1983; Young and Dowling, 1987) have been found. Consistent with the characterization of the South as the "Bible Belt," it is expected that Southerners will demonstrate greater levels of subjective religiosity. Beyond these distinctions, no clear assessment of the relationship between subjective aspects of religious involvement and other socialstatus positions emerges. Tentative findings suggest that married persons (Taylor, 1986) report higher levels of subjective religiosity. Persons of lower socioeconomic status are thought to display greater subjective religiosity, while those of higher status are involved in more public or formal religious pursuits (Stark, 1972). However, null effects for income, education, urbanicity, and region have been reported (Taylor, 1986).

Religious Involvement and Black Americans Historical (Frazier, 1974) and contemporary (Morris, 1981) evidence demonstrates that religious institutions and concerns have had a special prominence in the lives of African Americans. Historical and ethnographic characterizations of the nature and attributes of Black religious experience correspond with multidimensional conceptualizations of religious involvement that are found in the research literature (Cone, 1985). In addition, the social welfare, political, and civic and community functions of Black churches are dominant characteristics of these institutions (Frazier, 1974; Taylor and Chatters, 1986, 1988). Overall, there is little empirical research on the religious experiences of Black Americans (Beeghley, Van Velsor, and Bock, 1981; Heisel and Faulkner, 1982), and available work is predominated by racial-comparative studies of religious involvement. This literature suggests that Blacks are involved in religious pursuits to a greater degree than are Whites (Gallup, 1984), and this is evident across a variety of

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Correlates of Religious Involvement There is general debate as to whether religious involvement, in its diverse forms, varies in a systematic and appreciable manner with sociodemographic characteristics (Cornwall, 1989). Theoretical models that address the relationship between religious involvement and social status (Glock, Ringer, and Babbie, 1967) suggest that religious activities compensate or substitute for social and material deprivations that are associated with occupying lower status positions (e.g., lower income and education, unmarried status). However, published research findings generally have failed to support a deprivation-compensation model of religious involvement (Taylor, 1986, 1988a, 1988b) and suggest more complex relationships among demographic factors and religious involvement (Beeghley, Van Velsor, and Bock, 1981; Cornwall, 1989). Undoubtedly, the largest body of literature concerning the religious involvement of older persons focuses on the behavioral dimension and on formal or organizational religious involvement, in particular. Again, this is due to the relative ease of assessment of formal participation in activities such as religious attendance, religious affiliation, and church or synagogue membership. Findings that indicate a decline in formal participation with increased age are noted in the literature (Markides, 1983). However, other investigations indicate that, independent of health, the relationship between age and formal religious participation is positive or that age status does not emerge as a significant predictor of these behaviors (Chatters and Taylor, 1989; Levin, 1988). Women (Cornwall, 1989; de Vaus and McAllister, 1987; Koenig, Kvale, and Ferrel, 1988) and persons residing in the South (Glenn, Gotard, and Simmons, 1977) report consistently higher levels of formal participation than do their nonSouthern counterparts. Being married (as opposed to unmarried) has been associated with both higher (Beeghley, Van Velsor, and Bock, 1981; Cornwall, 1989; Taylor, 1986, 1988b) and lower (Glock, Ringer, and Babbie, 1967) levels of formal religious participation. Findings for income (Beeghley, Van Velsor, and Bock, 1981) and education (Cornwall, 1989; Taylor, 1988a) in relation to formal religious activities indicate that these factors are positively related and may reflect generally higher levels of social integration among more advantaged persons (Stark, 1972). Null effects for income and education on formal religious activities have been reported as well (Taylor, 1986, 1988b). Finally, effects for urbanicity suggest that rural residents participate in formal religious activi-

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METHODS

Data. — Data for this study come from the National Survey of Black Americans (NSBA), a nationally representative cross-section of the adult (18 years and older) Black population living in the continental United States. The NSBA is a part of an ongoing series of research studies conducted by the Program for Research on Black Americans at the Institute for Social Research of the University of Michigan. The NSBA sample was drawn through a multistage, area-probability procedure which ensured that each Black household had an equal likelihood of being selected. Based upon the 1970 Census distribution of Blacks, 76 primary sampling units were selected for interviewing. These areas were stratified by racial composition, with smaller geographical clusters then randomly selected. Professionally trained interviewers then visited each cluster in order to identify each habitable, occupied household, using special screening procedures developed to locate Black homes. Within each selected household, one member was randomly chosen for interview. In all, 2,107 interviews were completed in 1979 and 1980—a response rate of 68 percent. In this particular analysis, only respondents 55 years of age or older were selected (N = 581). After listwise deletion of missing values, this resulted in a final sample size of 446. A

more detailed description of the NSBA can be found in Neighbors and Jackson (1984). Model specification. — Figure 1 represents a diagram of the fully correlated, three-factor measurement model of religiosity for the 55 and older age group in the NSBA. In this model, the r\s (etas) represent the endogenous latent constructs underlying 12 observed indicators (Ys). Specifically, T), is organizational religiosity, y\2 is nonorganizational religiosity, and T^ is subjective religiosity. Organizational religiosity (nq,) comprises five behavioral items reflecting formal institutional activities such as official membership in a church, religious attendance, participation in organized church activities or church clubs, and holding church offices or positions. Nonorganizational religiosity (T|2) comprises four behaviors that occur outside the formal structure of the church, such as prayer activities and perusal of written and electronic media presentations. Subjective religiosity (T|3) comprises three indicators of religious attributions and attitudes such as self-rated "religiousness," perceived centrality of religion when growing up, and beliefs concerning the importance of religious service attendance for children. The wording of specific items is included in Table 1. The \ y (lambda-y) coefficients are the factor loadings of each observed indicator (Y) on its respective latent construct On). Each indicator has a factor complexity of one, meaning that it is affected directly by exactly one latent construct. The es (epsilons) are the measurement errors associated with the observed indicators. The respective measurement-error variances are denoted by 0£s (theta-epsilons). In the proposed model, four correlated measurement-error variances in organizational religiosity (xi,) (0e32, 0%3, 0e52, and 6eS4) were also estimated for both theoretical and empirical reasons. The freeing of correlated-error terms should always be done judiciously and not solely on the basis of an empirical criterion such as the modification indices produced by a LISREL run. In this case, responses to most of the items pertaining to organizational religiosity (T^,) were not necessarily independent of each other, conceptually speaking. For example, 0£52 was estimated because no respondent who was not a church member (Y2) could have answered affirmatively

Figure 1. Three-factor measurement model of religiosity.

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organizational, nonorganizational, and subjective indicators. Similarly, investigations of religious involvement within the gerontological literature suggest that older Blacks demonstrate higher levels of religiosity than do older Whites (Jackson and Wood, 1976). A developing body of empirical studies of religious involvement among Black Americans is moving beyond rudimentary Black-White comparisons to consider the manifest diversity in the nature and determinants of Black religious experiences (Beeghley, Van Velsor, and Bock, 1981; Chatters and Taylor, 1989; Taylor, 1986, 1988a, 1988b; Taylor and Chatters, 1986, 1988, 1991). Of particular importance in this regard is the investigation of within group differences in the antecedents (e.g., social-status factors) and consequences (e.g., health and personal adjustment) of religious involvement among Black Americans. The research agenda for the study of Black religious involvement is considerable, requiring a concerted program of work beyond the scope of a single study (Levin and Schiller, 1987). However, an appropriate and preliminary task involves an examination of the antecedents and dimensions of religious involvement within this population group. The purpose of the present study was to examine social status antecedents of religious involvement and to propose and test a measurement model of religiosity incorporating the three dimensions of religious involvement that have received attention in the aging literature. These dimensions, reviewed above, have been variously termed formal, public, or organizational religious behavior; informal, private, or nonorganizational religious behavior; and, subjective religiosity. These analyses are conducted within a sample of older Black adults and represent the first comprehensive attempt to explore the antecedents and multidimensional nature of religious involvement within this population.

RELIGIOUS INVOLVEMENT IN OLDER BLACKS

Table 1. Religiosity Indicators by Dimensions Variables Tj, Y, Y2 Y3 Y4 Y5 T) 2 Y6 Y7

T|3 Y 10 Y,, Y, 2

"Coded: I = never, 2 = less than once a year, 3 = a few times a year, 4 = a few times a month — 1 to 3 times, 5 = at least once a week — 1 to 3 times, 6 = nearly every day — 4 or more times a week. b Coded: 0 = no, 1 = yes. c The exact number is coded. d Coded: 1 = never, 2 = a few times a year, 3 = a few times a month — 1 to 3 times, 4 = at least once a week — 1 to 3 times, 5 = nearly every day — 4 or more times a week. c Coded: I = not religious at all, 2 = not too religious, 3 = fairly religious, 4 = very religious. 'Coded: 1 = not important at all, 2 = not too important, 3 = fairly important, 4 = very important.

to a question inquiring about holding a church office (Y5). Therefore, it was reasonable to believe these two items' error terms would be related. Out of all the possible such correlated-error terms, preliminary findings revealed that estimating four of these improved the overall fit of iq, considerably. There were no grounds, theoretical or empirical, for freeing any correlated-error terms in the other two religious constructs. Finally, the £s (zetas) denote the disturbance terms or residual errors in the structural equations associated with each of the three latent constructs (iqs). The i|is (psis) are the variances of these residual-error terms. In the proposed model, these vji parameters are inherently equal to zero for each construct (v|in, i|/22, u)33), but three additional error variances are estimated (\\i2l, u)31, v|i32). These represent the correlated structural errors among the three dimensions of religiosity. Data analysis. — Before examining the entire model, each of the three latent factors was developed separately in the entire sample (listwise N = 1636) in order to establish a satisfactory fit. Indeed, the resultant fit for each dimension of religiosity was excellent. For organizational religiosity (x2 = 1.17, df = 1, x2/df = 1.17, GFI = 1.000, AGFI = .996) and nonorganizational religiosity (x2 = 4.10, df = 2, X2/df = 2.05, GFI = .999, AGFI = .994), the overall fit of

these models is as high as can reasonably be expected. For subjective religiosity, overall fit indices cannot be evaluated due to the just-identification of the model, an inherent characteristic of a three-item, first-order construct. However, examination of loadings, errors, explained variances, and other parameters indicates that this factor, too, fits quite acceptably. All analyses were conducted using the maximum-likelihood (ML) fitting function in LISREL VI (Joreskog and Sorbom, 1986), a statistical package for structural-equation-modeling and confirmatory factor analysis. Covariance matrices are typically used as input in LISREL analyses, but, until the recent release of LISREL VII, correlation matrices had to be used in analyses seeking to obtain completely standardized coefficient estimates for model parameters (as in Tables 2 and 4). RESULTS

As suggested recently by Liang, Levin, and Krause (1989), the confirmation of a particular measurement model should extend beyond an examination of internal structure, which is typically the only step taken. In order to more fully test the plausibility of a measurement model, at least four steps are required. These include examination of internal structure, testing of alternative models, investigation of effects of exogenous constructs, and, where applicable, analysis of factorial invariance. First, a proposed model's internal structure should be examined. This answers the question, "How well does the theoretically posited model fit the data?" Table 2 presents the completely standardized ML estimates of parameters in the proposed model. In terms of parameter estimates and goodness-of-fit indices, these results entirely confirm the model. All 12 factor loadings (\ys) are statistically significant, and, with one exception, exceed .400, ranging as high as .782. The concomitant measurement-error variances (6£s) are also all significant, as are the four posited correlated measurement-error variances. Finally, each of the three correlated residual-error variances (u)s) among the three religiosity constructs is statistically significant and of high magnitude, ranging from .598 to .863. In simple terms, these results confirm the interrelation of the three factors posited in the model. The results presented in Table 3 are assessments of fit for the proposed model (M2), whose parameter estimates were just discussed. Several measures of fit were used, as each index describes a different aspect of "fit" and, thus, no single indicator can fully characterize how well a model reproduces a given matrix of data (Alwin, 1988; Bollen and Liang, 1988). According to the fit indices used, the proposed model provides a more than satisfactory fit to the data. The relative likelihood ratio (x2/df) is 2.27, and ratios less than 3.0 are considered indicative of a good fit (Carmines and Mclver, 1981). The GFI and AGFI measures are .961 and .935, and a score of over .900 is considered a prerequisite of a well-fitting model (Joreskog and Sorbom, 1981). Finally, the BBI, TLI, A2, and p, indices are .927, .940, .958, and .897, respectively, also signs of good fit. These latter indices (Bollen, 1989a, 1989b) are calculated by comparing the fit of a proposed model to a "null model" — a no-factors model (Mo) which assumes that each observed indicator (Y)

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Y8 Y9

Item Descriptions Organizational Religiosity How often do you usually attend religious services?" Are you an official member of a church or other place of worship? 1 " How many church clubs or organizations do you belong to or participate in? c Besides regular service, how often do you take part in other activities at your place of worship? d Do you hold any positions or offices in your church or place of worship? 6 Nonorganizational Religiosity How often do you read religious books or other religious materials? d How often do you watch or listen to religious programs on TV or radio?" How often do you pray? d How often do you ask someone to pray for you? d Subjective Religiosity How religious would you say you are?' How important was religion in your home when you were growing up? f How important is it for Black parents to send or take their children to religious services?'

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Table 2. Completely Standardized Maximum Likelihood Parameter Estimates for the Three-Correlated-Factors (M2) Model of Religiosity (N = 446) Parameter"

8£33 0%4 8*55 8*66 8€88 8 € io io 6'u ii 8'l2 12

.782 + .650 .703 .536 .407

.550 + .354 .550 .484 .719 + .208 .477 .388 .562 .505 .719 .835 .698 .875 .698 .766 .483 .957 .772

Correlated measurement-error (e) variances: 8*32

6%3 822 = - .01).

Correlated residual-error (£) variances between latent constructs (T\S): ^21 ^31 ^32

.716 .598 .863

"All estimates are standardized and are significant at a = .05. The symbol + indicates a constrained parameter.

taps exactly one of a pool of separate, unrelated constructs (TJS). This is always the most restrictive model possible for a given set of variables, and scores on these four indices of over .900 are considered signs of meaningful improvement (Bentler and Bonett, 1980). Second, the proposed model's fit should be compared to the fit of alternative models. This answers the question, "Do other models fit the data better than the theoretically posited model?" In this analysis, in addition to the null model (Mo), a model of three uncorrelated religiosity factors (M,) was examined, along with a model positing a single, higherorder religiosity factor (M3). As shown in Table 3, the proposed model (M2) is a considerable improvement over the uncorrelated-factors model, and differs very little from the higher-order model, as would be expected given the similar specifications. For empirical purposes, a correlated-factors

model is preferable to a higher-order model on theoretical grounds — the three factors are expected to relate differentially to both predictors (e.g., age, sex, education) and outcomes (e.g., health and well-being), and recent data support the obliqueness (i.e., intercorrelation) of religious dimensions in both Blacks and Whites (Jacobson, Heaton, and Dennis, 1990). Therefore, this second-order model is not used in subsequent analyses, although these results are considered to offer additional confirmation of the interrelatedness of the three dimensions in the proposed model. Third, one should examine the proposed model's relationships with exogenous variables found in prior research to exert significant effects on its endogenous constructs. This answers the question, "Do known predictors have expected effects on the theoretically posited model?" For organizational, nonorganizational, and subjective religiosity, the literature discussed earlier suggests that one or more of these constructs are predicted by age, sex, education, marital status, income, region, and urbanicity. To examine these effects, the three correlated religiosity factors were simultaneously regressed on the seven uncorrelated exogenous variables, again using LISREL VI. If the religiosity model is valid, we will expect most of these exogenous variables to be significantly associated with one or more of the religiosity

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Factor loadings (\ys) of observed indicators (Ys) on organizational religiosity (T|,): Y,: religious attendance Y2: church membership Y3: participation in church organization Y4: participation in other church activities Y5: church officer Factor loadings (\ys) of observed indicators (Ys) on nonorganizational religiosity (T^): Y6: read religious books Y7: listen to religious TV/radio Yg: prayer Y9: ask others for prayer Factor loadings (X.ys) of observed indicators (Ys) on subjective religiosity (%): Y10: self-rated religiosity Y,,: importance of religion when young Y12: importance of religious attendance to Black children Measurement-error (e) variances in observed indicators (Ys): 6',,

Estimate

Table 3. Measures of Fit for Alternative Models

RELIGIOUS INVOLVEMENT IN OLDER BLACKS

Table 4. Completely Standardized Regression Coefficients (7s) for Effects of Exogenous Variables (£s) on Latent Religiosity Constructs (m,s) in the Three-Correlated-Factors (M2) Model of Religiosity (N = 446)"" Latent Religiosity Constructs Exogenous Variables

Organizational Religiosity (r\x)

Nonorganizational Religiosity (T]2)

Subjective Religiosity (1^)

.023 .283*** .130 .049 .008 .061 -.081 .110

.060 .420*** -.038 -.104 -.217* .086 -.037 .248

.237*** .248*** -.238** -.021 -.312*** .188** -.097 .317

Age (£,) Female (£2) Education (£3) Married (£4) Family Income (£5) Southern (£s) Urban (&) R1

"Measures of fit for the fully correlated, three-factor religiosity model including the above uncorrelated exogenous variables: x2 = 253.81, df = 120, x2/df = 2.12,GFI = .944, AGFI = .921, BBI = .884, TL1 = .905, A2 = .935, p, = .834. b In this model, the following 0R parameters were freed, allowing for the correlation of selected measurement errors (8s) in the exogenous variables As

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"

nally, Southerners are more subjectively religious. In all, these seven constructs explain 11.0 percent, 24.8 percent, and 31.7 percent of the variance, respectively, in organizational, nonorganizational, and subjective religiosity. It is not surprising to find that these sociodemographic factors are less predictive of organizational religiosity than of nonorganizational and especially subjective religiosity, constructs which are not defined by outside activity. This stems from the observation that, among older respondents, organizational religiosity seems to be a function of physical health or disability (Levin and Markides, 1986). Fourth, and finally, the factorial invariance of a model ought to be analyzed when subgroup differences in model structure are hypothesized. This answers the question, "Does the theoretically posited model's internal structure vary depending upon characteristics of respondents?" In this case, there is little a priori reason to expect that the structure of religiosity should vary within this sample. Structural variation by race or ethnicity or by age (e.g., older vs younger subjects) is quite plausible, but in this study these variables are constant, as this is an examination of older Blacks. Nor are gender differences expected, although gender differences in the structural effects of religiosity constructs on certain outcomes (e.g., health and well-being) have been observed (Levin and Markides, 1988). In such analyses, an examination of the structural invariance of linkages within a proposed "causal" model might be informative. DISCUSSION

The proposed measurement model of religious involvement incorporating three dimensions of religiosity — organizational, nonorganizational, and subjective — was confirmed in this analysis. To a great extent, the latent religiosity constructs performed as expected with regard to the exogenous variables. Of particular note is the finding that background factors were differentially predictive of the dimensions of religiosity. Although there were few differences among older Black adults in relation to organizational and nonorganizational religious involvement, the effects of age, gender, region, income, and education were each predictive of the subjective dimension of religiosity. Further, comparisons of/?2 for the religiosity constructs demonstrated that exogenous factors explained greater variance in subjective religiosity than in either the formal or informal behavioral components of religious involvement. Age emerged as a significant and positive predictor of subjective religiosity as in previous studies (Hunsberger, 1985; Markides, 1983; Young and Dowling, 1987), but failed to predict organizational and nonorganizational behaviors among this sample of older Black adults. Relatively older Black adults reported greater subjective religiosity, but were no different from their younger counterparts with respect to participation in either organizational or nonorganizational religious activities. This absence of age effects on religious behavior may reflect a normative standard for these activities among older Black adults. Because of the cross-sectional nature of the data, the positive effect of age on subjective religiosity is difficult to interpret and could be attributed to aging, cohort, and/or

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constructs, and in the expected directions. This analysis, then, represents a test of a sort of convergent validity, the results of which are presented in Table 4. Before examining the findings, a brief description of the exogenous measures is provided. All seven constructs were operationalized as single measures. Age was coded in years, not categories, and ranged from 55 to 101. Sex was coded 1 = male, 2 = female. Education was coded as years of schooling. For marital status, categories were collapsed to create a dummy variable coded 0 = unmarried, 1 = married. Income was operationalized as total family income, coded in 17 discrete categories. Region was a dummy variable coded 0 = non-South, 1 = South, as was urbanicity, coded 0 = rural or suburban, 1 = urban. Because, in theory, it may be erroneous to assume that these single items are perfect indicators of their respective constructs, factorloading and measurement-error coefficients for five of these constructs were fixed according to known reliabilities derived from the 1970 Census' Index of Inconsistency (U.S. Bureau of the Census, 1975). These reliabilities, when plugged into an algorithm, produce factor loadings that are used in lieu of 1.0. For this analysis, these (standardized) adjusted loadings were used for age (.938), sex (.995), education (.714), marital status (.943), and income (.742). Where possible, these values were derived from reliabilities obtained from Black populations, although racial differences here are typically small (U.S. Bureau of the Census, 1975). Findings presented in Table 4 reveal that, in addition to its sound internal structure, the religiosity model performs mostly as expected with regard to its relationships with known predictors. Older subjects are more subjectively religious. Females score higher on all three constructs. More highly educated subjects are less subjectively religious. Wealthier respondents are less subjectively religious and exhibit lower levels of nonorganizational religiosity. Fi-

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sive among persons of higher socioeconomic status (Stark, 1972). With regard to marital status, the expectation that unmarried persons participate in religious pursuits, and particularly organizational aspects of religious involvement, as a substitute (i.e., family surrogate) for the marital relationship (Glock, Ringer, and Babbie, 1967) was not supported. Further, in contrast to previous work (Cornwall, 1989), being married was not associated with greater integration within religious institutions, involvement in informal religious behaviors, or heightened subjective religiosity. This pattern of findings suggests that the conceptually based distinction made between behavioral (i.e., organizational and nonorganizational) and subjective dimensions of religiosity indeed has very real empirical consequences. The subjective component of religious involvement, as operationalized in this study, included self-attributions as to degree of religiousness, as well as attitudes regarding the importance and salience of religious concerns. In particular, attitudes concerning the religious socialization of children and self-reports on the saliency of religion in respondents' background were included in this construct — items that are not typically associated with subjective religiosity. As such, observed relationships to status group factors might be expected to be greater than is the case when subjective religiosity incorporates beliefs about religion only. Positive endorsement of these religious sentiments was found to be distinctive of older persons, women, persons with lower levels of income and education, and those residing in the South, consonant with various attributes and characteristics that are associated with occupying these status positions. In particular, women may exhibit greater subjective religiosity than men as a consequence of (a) childhood socialization practices for females emphasizing specific traits and values that are consistent with a religious world-view, and (b) the relatively greater involvement of mothers in the religious socialization of young children (de Vaus and McAllister, 1987). The characterization of the South as particularly imbued with religious content (Glenn, Gotard, and Simmons, 1977) would suggest that holding these beliefs would be more normative and accepted than in other regions. Further, the influence of Southern residency on subjective religiosity may operate by way of the personal and social networks and relationships which obtain in these environments and which sustain a religious viewpoint (Cornwall, 1989). Subjective aspects of religion were salient for persons who possessed relatively fewer material and social resources (i.e., lower income and education). One possible explanation is that greater access to social and material resources (embodied in higher status positions) provides alternative sources of values, identities, and commitments that potentially conflict with a religious identity (de Vaus and McAllister, 1987). As a consequence, members of high-status groups invest in an explicitly religious world-view (i.e., subjective religiosity) to a lesser degree than do their counterparts. The recognition of the limitations of material and social resources in dealing with the more intractable problems and questions of life (i.e., personal aging and death, bereavement, physical suffering, incurable disease) may encourage and underpin a religious perspective among per-

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period effects (Chatters and Taylor, 1989). The greater levels of subjective religiosity among the very oldest may be a reflection of aging effects whereby these aspects of religion intensify with advancing age. Alternatively, members of this age group could have been exposed to distinctive religious socialization experiences that differentiate young-old from old-old respondents with respect to subjective aspects of religiosity (i.e., cohort influences). Finally, interactions between period and cohort effects suggest that distinct birth cohorts are differentially sensitive to period influences (Bengtson et al., 1985). The development of prospective panel data sources on religious involvement will provide greater understanding of the relative contributions of aging, period, and cohort influences on subjective religiosity. In the meantime, religious data from independent, annually drawn samples (e.g., NORC's General Social Survey) or from multigenerational studies can help begin to disentangle these effects. Consistent with prior research (Cornwall, 1989; Koenig, Kvale, and Ferrel, 1988), women were more involved in religious pursuits than were men, regardless of the religious dimension examined. A recent study (de Vaus and McAllister, 1987) found that differences in social-structure location as manifested in social and work roles (i.e., higher labor force participation) were important in explaining consistent gender differences in religious involvement. In this connection, differential rates of labor force participation helped to explain women's greater involvement in religious concerns. Among this sample, however, there were no differences between older women and men in rates of working, and gender was not a significant predictor of retirement status (Gibson, 1982), making a labor-force participation explanation less tenable. Recent work examining regional and urban-rural variations in religious involvement suggests that these social environments have significance for shaping patterns of religious participation and expression (Cornwall, 1989; Veroff, Douvan, and Kulka, 1981). Although subjective motivations and feelings regarding religiosity were greater in this study among Southerners, there were no significant regional differences in relation to either organizational or nonorganizational religious behaviors. Given previous findings for a pervasive regional effect (Glenn, Gotard, and Simmons, 1977), it is surprising that Southern residency failed to predict religious behavior. In addition, urbanicity did not predict any of the three religiosity constructs. At best, the findings provide modest support for a deprivation-compensation perspective (Glock, Ringer, and Babbie, 1967) on the relationship between social-status factors and religious involvement. Indicators of socioeconomic status (i.e., income and education) failed to significantly predict organizational participation, while only income predicted nonorganizational activities. These findings are consistent with a deprivation-compensation perspective only with regard to the finding that lower levels of income and education were associated with a higher degree of subjective religiosity (Stark, 1972). In addition, these results do not support the expectation deriving from a socialintegration view that organizational religious activity, as a form of voluntary association participation, is more exten-

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older Black adults, in particular, are not easily characterized. Although the present findings demonstrate both differences and similarities with previous research, it is difficult to reconcile these disparities and develop a comprehensive picture of religious involvement and its relevant predictors. In particular, an assessment of the differential significance of sociodemographic predictors among Blacks vs Whites (i.e., Black-White differences) and speculations as to their origins are problematic and likely premature. Extant limitations in the literature mitigate against a satisfactory assessment of the effects of sociodemographic factors on religious involvement among the general population (i.e., Whites), as well as among identified subgroups. Specifically, the use of nonprobability samples (Ainlay and Smith, 1984; Hunsberger, 1985; Young and Dowling, 1987), low response rates (e.g., Jacobson, Heaton, and Dennis, 1990), the failure to utilize multivariate analysis techniques (Levin and Vanderpool, 1989), and the use of samples representing active members of a single religious affiliation (e.g., Cornwall, 1989, Mormons; Ainlay and Smith, 1984, Mennonites), reflect identified weaknesses in these literatures. Continuing research is needed on the conceptualization and measurement of religiosity, as well as on its antecedents and consequences. Efforts of this sort that have been initiated by the present authors include: (a) confirmation of the structural invariance of measurement models such as the one presented here for use among older Black adults across strata of race, ethnicity, age, gender, denomination, generation, social class, and time; (b) identification of the antecedents of dimensions of religious involvement in non-Black populations with comparisons to the findings presented here; and

ability to participate in formal activities. Since health status

(c) assessment of the effects among Black Americans of

may be conceived of as both an antecedent and consequence of religiosity, however, examination of the relationship between religious and health constructs is best reserved for studies based on fully specified structural-equation models, preferably of panel design (Levin, 1988). The relationships of the sociodemographic factors to the three religiosity constructs suggest possible differences in the antecedent conditions for these dimensions of religious involvement. These analyses demonstrated that, in contrast to previous research, higher-status groups were largely similar to their lower-status counterparts with regard to organizational and nonorganizational religious behaviors (exceptions being gender differences in both types of religious behaviors and income differences in nonorganizational activities). The greater levels of subjective religiosity for particular groups of older Black adults (i.e., women, older persons, those of lower SES, and Southerners) suggest that this internalized component of religiosity may arise out of the particular circumstances of belonging to these status positions. Further, because the construct of subjective religiosity incorporated self-perceptions of religiousness, as well as more generalized attitudes regarding religious concerns as they relate to socialization efforts, status-group differences might be anticipated. Several possible mechanisms by which these differences might be manifested (e.g., socialization effects, social-environment factors) were proposed. As these and other efforts illustrate, the nature of religious involvement, in general, and the religious experience of

religious involvement on key gerontological outcomes such as physical health, depression, psychological well-being, and the utilization of support networks. ACKNOWLEDGMENTS

Data collection for this study was supported by the National Institute on Aging (AGO 1294) and the National Institute of Mental Health (Center for Minority Group Mental Health) (MH30706), Drs. James S. Jackson, M. Belinda Tucker, and Gerald Gurin, co-principal investigators. The preparation of this manuscript was supported by the National Institute on Aging under grants R29 AG07179 (Dr. Chatters), T32 AG00114 and R29 AG09462 (Dr. Levin), and R29 AG06856 (Dr. Taylor). The authors thank Keith Hersh and Phyllis White for their assistance in the preparation of this manuscript. Address correspondence to Dr. Linda M. Chatters, Department of Health Behavior and Health Education, School of Public Health, University of Michigan, Ann Arbor, MI 48109-2029. REFERENCES

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Received November 13, 1990 Accepted December 23, 1991

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