Breault ExplainingDivorceUnited 1987

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Explaining Divorce in the United States a Study of 3,111 Counties, 1980 Author(s): K. D. Breault and Augustine J. Kposowa

Source: Journal of Marriage and Family, Vol. 49, No. 3 (Aug., 1987), pp. 549-558 Published by: National Council on Family Relations

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Explaining Divorce in the United States A Study of 3,111 Counties, 1980

K. D. BREAULT

University of Cincinnati AUGUSTINE J. KPOSOWA*

Ohio State University

Three indicators of social integration-church membership, population change, and urbanity-are tested with a group of socioeconomic variables and median population age on rates of divorce for 3,111 U.S. counties, 1980. The study replicates findings of previous studies that have shown comparatively strong effects of social integration and weak socioeconomic effects on divorce. Urbanity was found to be most strongly related to divorce, with church membership and population change equally half as strong. Weaker correlates of divorce, in order of importance, are: median family income, median age, rate of unemployment, and percentage Hispanic. Percentage employed in professions, percentage high school graduates, and percentage black were found to be unrelated to divorce.

New discussion is offered on the hypothesized relationship between urbanity and low social integration.

Attention has been focused recently on social integration as an explanation of divorce (Glenn and Shelton, 1985; Glenn and Supancic, 1984). De- rived from the work of Emile Durkheim, in par- ticular, Suicide (1897/1951), this view holds that divorce will be high where social integration is low.' Glenn, Shelton, and Supancic's work, which has strongly upheld the link between social integration and divorce, has generally been based on survey data, although the most recent paper

The senior author is indebted to the Center for Ad- vanced Study in the Behavioral Sciences, Stanford, California, for the extraordinarily congenial and stimulating working environment. We are also indebted to the Department of Sociology, University of Cincin- nati, for research funds. We thank the anonymous reviewers, who provided helpful suggestions, and Gloria Valentine, who typed the manuscript.

Department of Sociology, University of Cincinnati, Cincinnati, OH 45221.

*Department of Sociology, 300 Bricker Hall, Ohio State University, Columbus, OH 43210.

also included census data. The present study is an attempt to replicate the findings of strong effects of social integration on divorce with a large sample of relatively small ecological units, namely, counties in the United States.

Prior work of a structural nature on social integration and divorce has generally involved small samples consisting of large ecological units. For example, important studies based on the United States and Canada have used states and provinces as the unit of analysis (Fenelon, 1971; Makabe, 1980; Stetson and Wright, 1975; Trovato, 1986;

Weed, 1974).2 One problem with highly ag- gregated data of this type is that they average or sum-over potentially important sources of nonrandom variation that may only be apparent at lower levels of analysis. For example, at the state level, high population movement character- izes western states, yet at the county level, rural western counties have low population movement:

this county-level rural-urban variation in population movement is not discernible at the level of the state. Another possible source of error is that while social-integration indicators may vary considerably across states and provinces, correlated with the often remarked upon east-west gradient in divorce, many socioeconomic indicators show Journal of Marriage and the Family 49 (August 1987): 549-558 549

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JOURNAL OF MARRIAGE AND THE FAMILY

much less variation at the state level than at lower levels of analysis. The adequacy of social integration as an explanation of divorce may depend to some degree, therefore, on the level of aggrega- tion used. In addition, the question of

methodological rigor is not a trivial one when samples of 50 or less are commonly used in

ecological studies.

One solution to these problems, attempted in related fields, is to use some set of large SMSAs.

In turn, this solution creates its own set of problems, especially in regard to certain variables, most notably urbanity. Because SMSAs are main- ly urban areas and because SMSAs allow for almost no variation in urbanity, they are less than desirable units of analysis. Alternatively, the U.S.

county may be an ideal unit of analysis for ecological studies (Bogue and Bogue, 1976).

Much county-level data are readily available, particularly the social-integration indicator of church membership (see below), which is not available by SMSA, and the use of American counties permits sample sizes that may often exceed those of survey studies.

The one county-level study we know of that failed to find support for the social-integration thesis (Wilkinson, Reynolds, Thompson, and Ostrech, 1983) was based on 292 counties in five western and midwestern states-Montana, Nebraska, North Dakota, South Dakota, and Wyoming. Because this area is largely rural and agricultural, the problem of insufficient variation across ecological units is relevant here also, this time in the opposite, rural direction. Further- more, it is reasonable to argue that divorce rates tend to be suppressed in rural and agricultural areas for the very reason of high social integration. Indeed, the present study suggests that if Wilkinson and his colleagues had compared their 292 counties with an equal number of urban and industrial counties, opposite results would have been obtained.

In addition to testing for social-integration variables, the present study employs a set of socioeconomic variables-income, unemployment, occupational status, and education. In general, socioeconomic indicators have failed to be powerful determinants of. divorce when they are matched with social-integration variables (e.g., Glenn and Supancic, 1984), but few studies, especially ecological studies, have rigorously explored the matter. Other studies that have failed to control adequately for social-integration variables have found significant relationships between divorce and socioeconomic variables (e.g., Burns, 1984).

Finally, one of the social-integration indicators used in the study, church membership, is a new

and relatively unknown measure of religious integration. We suggest it has the additional virtue of coming very close to what Durkheim had in mind when he spoke of the integrative effects of religious affiliation.

METHOD AND STUDY VARIABLES

Linear and nonlinear bivariate and multiple regression analyses were performed on the data.

The rate of divorce (per 1,000 population) is the dependent variable. Percentage holding church membership, percentage of population change, percentage of urbanity, median family income, rate of unemployment, percentage employed in professions, percentage of high school graduates, percentage black, percentage Hispanic, and median population age are the independent variables.

The year for the analysis is 1980; data for all variables were available for that year. The unit of analysis is the U.S. county. The sample includes 3,111 counties for which complete data were

available.3 The data on divorce rates come from the U.S. Bureau of the Census, County and City Data Book (1983).

Durkheim argues that religion by itself provides protection from suicide because it situates the individual in a social environment that promotes shared values, intense interaction, and strong social bonds. Religion, for Durkheim, is one of a number of social contexts in which people are physically, emotionally, and psychologically tied together. In order to test or operationalize his hypothesis of the integrative effects of religion on suicide rates, Durkheim differentiated the major European religions in terms of their integrative value for adherents. For example, Durkheim

argued that Catholics are more socially integrated than Protestants, and he therefore hypothesized that this difference would manifest itself in dif- ferential suicide rates. Recently, Durkheim's operationalization of his theory has been called into question for theoretical and methodological reasons (Pope, 1976), and his denominational propositions have been empirically challenged as well (e.g., Pope and Danigelis, 1981). As a result, researchers have increasingly focused on Durk- heim's basic thesis that religion itself is an important source of social integration, and they have sought indicators of religious integration that transcend denominationality, such as church attendance, religious publications, and church membership.

The indicator of religious integration for the present study is percentage of church membership. We use church membership rates that were compiled for all U.S. counties in a monumental 550

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DIVORCE IN THE UNITED STATES, 1980

effort by Quinn and his colleagues (1982). The Quinn et al. compilation represents an updated and improved version of the 1974 compilation (based on 1970 data) of Johnson, Picard, and Quinn. At the outset, it should be understood that church membership is not a perfect measure of Durkheim's religious-integration variable. An ideal measure would include not only church membership or affiliation, but a more complete measure of the degree of religiosity and extent of involvement in and commitment to church and church-related activities. Unfortunately, however, such data do not exist. Church membership is, perhaps, the next best choice. Alternative

measures such as attendance at religious services, which indicates actual religious behavior, are not available for U.S. states or counties. Another im-

portant point is that religious attendance also varies considerably by denomination. In general, individualistic denominations (e.g., Southern Baptists) tend to show lower rates of religious attendance. Since such individualistic denominations would be expected to afford less social integration, results based on religious attendance may be biased. Other measures, such as religious publications (see Wuthnow, 1977), are too indirect, removing us from Durkheim's basic view of the integrative power of group affiliation or membership, the very foundation of his theory of social integration (Breault, 1986).

Measures of religious integration have figured in a number of recent studies on divorce. Some studies that have explored denominational variables (usually the percentage Roman Catholic) are Fenelon (1971), Weed (1974), Makabe (1980), Thornton (1985), and Trovato (1986). In general, the data suggest that Catholics have lower divorce rates than non-Catholics, although the effect may now be declining somewhat (Thornton, 1985), and it is typically less powerful than that obtained with indicators of population change (see below).

A few studies have gone beyond denomination and have analyzed more general indicators of religious integration. For example, Glenn and Supancic (1984) found frequency of religious attendance to be one of the strongest correlates of divorce and separation. Similarly, Fergusson, Horwood, and Shannon (1984) found that fre- quent church attendance was associated with lower rates of marital breakdown.

The second social-integration indicator used in this study is the percentage of population change (U.S. Bureau of the Census, 1983). Presumably, counties that have a stable membership are more highly integrated than those made up of new- comers and temporary residents. On the other hand, "High rates of geographic movement

should tend to disrupt social relationships, create anonymity, and impede enforcement of at least the norms that pertain to the more private aspects of behavior" (Glenn and Shelton, 1985: 643). In fact, high rates of population change are related to the weakening of many kinds of voluntary organizations, including churches; to various forms of criminal deviance; and to suicide (Breault, 1986; Crutchfield, Geerken, and Gove, 1982; Stark, Doyle, and Rushing, 1983). For example, Stark et al. (1983) used population change as a measure of social integration in their study of U.S. suicide rates. Crutchfield et al. (1982) also used the population change indicator in their study of social integration and crime rates. Both of these studies found strong correlations of suicide and crime with the population change indicator. The central theoretical rationale behind the use of the variable is that high population change indicates less stable social relationships.

High divorce rates are most likely to be found in these contexts of low social integration. At the same time, however, there is some anecdotal evidence to suggest that moving itself is a direct cause of divorce, and that movers have higher divorce rates than nonmovers.

The divorce literature has also explored population change as an indicator of social integration.

Fenelon (1971) found significant effects of migration on divorce in an ecological study of American states. In a later study, similarly based on states, Week (1974) found significant bivariate correlations between population mobility and divorce.

When age at marriage was controlled, however, population mobility became insignificant. As Glenn and Shelton (1985) point out, this result is not inconsistent with social integration explana- tions of the distribution of divorce. Low age at marriage may well indicate low social integration to the extent that social integration is a function of social control or regulation. The implication is that other more suitable control variables are

needed if the social-integration hypothesis is to be tested adequately. In a 1980 article by Makabe, divorce rates were analyzed across ten Canadian

provinces. Highly significant population change effects on divorce rates were found in Makabe's study. Very different results were offered by Wilkinson et al. (1983) in a study of 292 counties in five western and midwestern states. The

authors of this study found that net immigration had little influence on divorce rates between 1970

and 1975. Glenn and Shelton (1985) found strong support for their mobility index in a study of nine census regions of the United States. Finally, in a recent study, Trovato (1986) extended the earlier work of Makabe by showing that the provincial 551

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TABLE 1. RATES OF DIVORCE, CHURCH MEMBERSHIP, AND POPULATION CHANGE FOR THE SAMPLE COUNTIES WITH THE 25 HIGHEST AND 25 LOWEST DIVORCE RATES, 1980

County, State Washoe, Nevada Clark, Nevada Ormsby, Nevada Scott, Indiana Tipton, Tennessee Hendry, Florida Hardin, Texas Fairbanks, Alaska Natrona, Wyoming Geary, Kansas Anchorage, Alaska Ector, Texas

Jefferson, Indiana Juneau, Alaska Vanderburgh, Indiana Franklin, Washington Bay, Florida

Piatt, Illinois Bell, Texas Elko, Nevada Union, Arkansas Comanche, Oklahoma Johnson, Indiana Potter, Texas Curry, New Mexico Blackford, Indiana

Means

Benton, Minnesota Nicollet, Minnesota Starr, Texas Worth, Georgia Greenup, Kentucky Breathitt, Kentucky Warren, Kentucky Grayson, Kentucky Henderson, Kentucky Jones, Georgia Webb, Texas Kenton, Kentucky Whitley, Kentucky Calaveras, California Pulaski, Kentucky Hidalgo, Texas Paulding, Ohio Warren, Pennsylvania Mahoning, Ohio Pointe Coupee, Louisiana Wilcox, Alabama Plumas, California

Williamsburg, South Carolina Franklin, Virginia

Rhea, Tennessee Means

Divorce 20.2 18.1 17.3 14.9 13.8 12.8 12.5 12.1 12.0 11.6 11.6 11.2 11.2 11.2 11.2 11.1 10.9 10.9 10.8 10.8 10.8 10.6 10.5 10.5 10.4 10.4 12.3 0.0 0.0 0.0 0.0 .1 .2 .2 .3 .3 .3 .3 .4 .4 .5 .5 .6 .6 .6 .7 .7 .7 .8 .9 1.0 1.1 .4

Church Membership 25.4 29.7 32.2 42.8 61.1 52.5 51.5 28.5 42.2 37.1 28.4 61.0 47.9 37.4 58.0 44.5 43.5 56.4 40.6 40.6 66.7 50.6 38.2 88.7 71.1 40.5 46.8 77.0 65.7 99.9 70.6 32.1 21.0 51.0 44.8 62.8 34.8 58.0 55.4 68.7 28.7 60.7 66.7 50.3 57.0 76.4 99.9 99.9 26.7 99.9 47.8 45.1 60.0

Population Change 36.4 35.4 36.2 8.0 9.0 12.8 6.4 37.8 28.9 46.3 36.1 11.5 12.3 27.3 7.8 20.4 23.1 3.8 32.4 25.2 8.6 38.7 8.0 12.1 27.3 3.1 21.3 4.9 7.5 5.3 6.3 9.7 6.6 12.0 4.9 10.3 5.9 8.6 10.4 13.5 4.7 9.0 11.5 5.6 6.9 4.2 3.7 2.2 10.6 5.6 5.2 15.0 7.6

distribution of divorce in Canada is largely explained by population migration patterns.

Table 1 presents data on divorce, church membership, and population change for selected counties from our study sample of 3,111 U.S.

counties. This selection illustrates the major geographic trends in divorce, church membership, and population change.

The third social-integration variable used in this study is percentage of urbanity (percentage of county population living in urban areas; U.S.

Bureau of the Census, 1983). Urbanity has long been associated with a variety of social problems, such as suicide (Halbwachs, 1930/1978; Morselli, 1903/1930), but in general, empirical results have been quite mixed. Important discussions of a 552

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general nature on urbanity are those by Wirth (1938), Gans (1962), and Fischer (1975). A

number of arguments have been put forth for the hypothesized link between urbanity and low social integration. The view we wish to offer is that for reasons having to do with the heightened impact of economic relations on social life, derived main- ly from the economically competitive and ration- alistic work environment as well as the reduced in- sulation people have from that environment, urban areas have tended to sustain a relatively low level of moral or social control. To a greater degree than that which exists in rural areas, economic relations diminish mechanisms of social control that are based on moral or social con-

siderations. The result is a general lowering of the cost of marital dissolution. We therefore

hypothesize that diminished levels of moral or social control generate higher-than-usual divorce rates for urban areas.

The copious research findings of a wealth of personal ties in urban areas (see review, Gulick, 1973) do not damage the position presented here because we are suggesting that the quality and not the quantity of social ties is affected by economic relations to a degree not experienced in rural areas. Indeed, the quantity of significant social ties may be greater in urban areas, simply as an effect of population size and density. In addition to the divorce effects of diminished social control, marital stability may be adversely influenced for derivative reasons. For example, as social relations become more and more determined by economic factors, and thus less satisfying, people may search for social ties that are qualitatively different. This would either contribute to divorce

directly or add to people's existing store of social ties, the increased size of which is made more manageable with economistic, nonmoral interac- tions that further exacerbate the difficulty of social relations in dense urban contexts. These trends appear to transcend unconventional subcultures, which suggests that some of the "deviance" found in urban areas is not covered by Fischer's (1975) theory. Few would argue that a significant portion of divorce is dependent upon the existence of subcultures.

In the divorce literature, a number of studies have included the urbanity variable (Fenelon, 1971; Glenn and Supancic, 1984; Makabe, 1980;

Trovato, 1986; Weed, 1974). In general, urbanity has been found to be a somewhat less important determinant of divorce, particularly when population change is controlled. In the 1984 study by Glenn and Supancic, which was based on seven U.S. national surveys and included urbanity, the strongest correlates of divorce were race, age at

marriage, and frequency of religious attendance.

In addition, as control variables, the present study tests socioeconomic indicators-median family income, rate of unemployment, percentage employed in professions, and percentage of high school graduates; two race categories-percentage black and percentage Hispanic; and median population age. The data for these variables come from the County and City Data Book (U.S.

Bureau of the Census, 1983). The first economic variable to be considered is median family income. In general, economists link low income with marital instability (e.g., Becker, Landes, and Michael, 1977). In the empirical literature, lower socioeconomic levels have been related to divorce and separation (e.g., Burns, 1984; Cutright, 1971;

Glick and Norton, 1979), and the hypothesized relationship between SES and marital instability has at times seemed to take on a law-like quality.

As mentioned above, this work has usually been conducted without sufficient controls for social

integration. Some recent work suggests that SES variables, including income, are weaker determinants of marital instability than some social- integration variables (Glenn and Supancic, 1984).

In order to understand better the relationship between SES variables and divorce, we use three

other variables-rate of unemployment, percentage employed in professions, and percentage of high school graduates. Unemployment has been found to be positively related to divorce in several studies (e.g., Coombs and Zumeta, 1970; South, 1985). Occupational status or prestige and education have also been related to divorce, but in the expected negative direction (e.g., Fergusson, Hor- wood, and Shannon, 1984; Glenn and Supancic, 1984; Glenn and Shelton, 1985; Teachman, 1982).4

The study also includes two race categories, percentage black and percentage Hispanic. In his state-level study, Fenelon (1971) failed to find a race effect, but other researchers have reported a significant relationship between percentage non- white and divorce (e.g., Glick and Norton, 1979).

Finally, it has been observed that in addition to the east-west gradient in divorce, there may be a similar geographic distribution of population age:

western states generally have younger populations than eastern states (e.g., Pang and Hanson, 1968).

Methodologically, there are basically two ways to deal with what is an apparent conflation of age with divorce. One strategy would be to (indirectly) age-standardize divorce rates for ecological units, as did Weed (1974). A better way, perhaps, would not only to control for the effects of divorce and age (as in age-standardization) but to determine the degree to which these variables are supposedly

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TABLE 2. MATRIX OF ZERO-ORDER AND PARTIAL CORRELATION COEFFICIENTS FOR U.S. COUNTIES, 1980

Variable Da C Po Ur I Un Pr HS B H A Da 1.0 -.242* .240* .359* .145* .083* 1.50* .046* -.014 .006 -.070*

C -.166* 1.0 -.332* .104* -.141* -.254* .104* -.016 -.120* .142* .206*

Po .167* -.383* 1.0 .058* .147* .098* .103* -.067* -.095* .052* -.168*

Ur .348* -.029 -.110* 1.0 .465* -.078* .363* .075* .008 .180 -.266*

I -.076* -.094* .123* .373* 1.0 -.176* .408* .395* -.233* -.080* -.216*

Un .049* -.233* -.101 -.031 -.198* 1.0 -.124* -.025 .052* .021 -.174*

Pr .024 -.065* .050* .231* .258* -.031 1.0 .009 .014 .013 .124*

HS .023 -.067* -.209* -.011 .341* .070* -.099 1.0 -.490* -.258* .067*

B -.021 -.168* -.210* .109* -.128* -.027 -.515* 1.0 -.097* -.218*

H -.046* .131* .057* .221* -.140* .047* .047* -.233* -.278* 1.0 -.171*

A -.078* .106* -.089* -.154* -.241* -.169* -.048* .121 -.214* -.151* 1.0 Mean 4.46 54.66 15.42 34.59 16,797.55 7.34 2.84 34.71 8.57 3.81 31.02 SD 2.08 18.02 17.54 28.59 3,641.93 3.39 1.11 7.26 14.38 10.23 3.93

Note: Zero-order correlations are found above the 1.0 matrix diagonal and partial correlations below. All coefficients represent linear relationships.

aVariables are as follows:

D = divorces per 1,000

C = rate of church membership

Po = percentage population change, 1970-1980 Ur = percentage urban

I = median income

Un = unemployment rate

Pr = percentage professional employment HS = percentage high school graduates B = percentage black

H = percentage Hispanic A = median age

*Correlations are significant at the .05 level or better.

L/I A-

(-1

0 C

r

> 0

C:

3

r

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related in the first place-to determine the extent to which divorce rates and age of population are confounded. Given the large sample size of the present study, this latter strategy is easily ac- complished with standard regression techniques.

In the present study, data on median population age are analyzed for each of the entire set of 3,111 counties.5

ANALYSIS AND RESULTS

Table 2 presents the matrix or zero-order bivariate correlation coefficients as well as partial correlation coefficients for the 3,111 U.S. counties in the study.6 The zero-order coefficients are located above the 1.0 matrix diagonal, while the partials are found below the diagonal. The partial correlation coefficients represent the relationships between every two variables when the effects of all the other variables in the study are controlled. For example, the zero-order bivariate correlation between divorce and church membership is -.242, while the relationship between these two variables when the effects of all the other variables are con-

trolled is -.166. The figures in the matrix represent linear relationships, as no significant nonlinear ones were found.7

Table 2 shows that three of the variables in the study-percentage employed in professions, percentage of high school graduates, and percentage of black-are unrelated to divorce. Rate of

unemployment and percentage Hispanic are mar- ginally related to divorce, with Hispanics enjoying some divorce protection, as the negative direction of the coefficient indicates (the result of high rates of church membership, i.e., Roman Catholic).

Median family income and median population age are about twice as robust as unemployment and percentage Hispanic, with both showing negative effects on divorce, as expected. In turn, two of the social-integration indicators-population change and church membership-are twice as strong as income or age, both in the expected direction.

Finally, urbanity is about twice as strong as the other two social-integration indicators.

Some of the relationships between the independent variables are worth noting. Population change is strongly related to church membership in the expected negative direction. Urbanity is strongly related to median family income, as expected. Some of the socioeconomic variables are highly related to each other. Median family income is strongly related to percentage of high school graduates and percentage employed in professions. In turn, the highest partial correlation coefficient obtained in the study is that between percentage of high school graduates and percentage black, in the negative direction.

Turning next to the multiple regression analysis (Table 3), we see that the social-integration indicators remain the strongest factors in divorce.

Beta values for urbanity, church membership, and population change are .411, -.174, and .171,

respectively. Median income and median age are less strongly related, with beta values of .096 and -.08. Weaker still are the remaining significant variables-rate of unemployment and percentage Hispanic-with beta values of .047 and -.046.

Again, no support was found for the socioeconomic indicators of percentage employed in professions and percentage high school graduates, or for percentage black. The overall multiple correlation is .473, with something more than 22% of the total variance in county divorce rates explained by the significant independent variables. Finally, in an attempt to determine if important variables had been overlooked, we studied all residuals carefully, and the results were negative.

SUMMARY AND DISCUSSION With a large sample of U.S. counties as ecological units, this study replicates recent findings that social-integration variables are important factors in divorce. This relationship holds true even when various socioeconomic indicators

TABLE 3. SUMMARY OF MULTIPLE REGRESSION ANALYSIS FOR U.S. COUNTIES, 1980

Regression Standard Error t Probability Variable Coefficient Beta of Beta Statistic Level Church membership -.199 -.174 .018 -9.35 .000 Population change, 1970-1980 .209 .171 .018 9.40 .000 Percentage urban .297 .411 .020 20.68 .000 Median income -.001 -.096 .022 -4.27 .000 Unemployment .284 .047 .017 2.70 .007 Professional employment .473 .351 .018 1.35 .177 High school graduates .079 .028 .022 1.29 .197 Percentage black -.034 -.024 .020 -1.16 .248 Percentage Hispanic .093 -.046 .018 -2.56 .011 Median age -.422 -.080 .018 4.38 .000

Note: R2 = .224, F = 81.3, p < .000, N = 3,111.

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and median population age are statistically controlled. All three indicators of social integration-church membership, population change, and urbanity-are stronger factors in divorce than any of the socioeconomic variables, two of which are found to be unrelated to divorce. Urbanity, by far the strongest variable, explains more variance in divorce rates than the two other social integration indicators put together.8 Moreover, each of the less important social integration indicators-church membership and population

change-separately account for significantly more variance than all of the socioeconomic variables

put together. The two socioeconomic variables that are significant are income and unemployment, in the expected directions. Together, the socioeconomic variables explain about 3% of the variance in county divorce rates across the coun- try in 1980. In comparison, the social-integration indicators explain 16.5% of the variance in county divorce rates.

How should we interpret these results? One way would be to start with the observation that almost 78% of the variation in divorce rates remains un- explained in this analysis. Arguably, this is not unusually high by social scientific standards (especially for samples of this size), but it seems reason- ably clear that progress will not be made if we are satisfied to leave the matter at this point. How then might we proceed?

First, it is important to note that Durkheim was not primarily interested in the explanation of rates of behavior. His goal was to demonstrate the importance of social factors in why people commit suicide. In the field of marriage and the family, a major goal is to explain why individuals divorce.

In principle, this does not mean that aggregate- level analyses as a class are any less useful than individual-level studies (e.g., Bogue and Bogue, 1976). However, the aggregate-level study of divorce is perhaps uniquely handicapped because many of the variables that have been predictive of divorce in studies at the individual level are not available or are of poor quality for ecological units such as counties. A short list of such

variables would include (in random order): liberal attitudes (e.g., Jorgensen and Johnson, 1980;

Pang and Hanson, 1968); age at marriage (e.g., Glenn and Supancic, 1984); premarital pregnancy (e.g., Furstenberg, 1976); wife's income relative to husband's (e.g., Becker et al., 1977); wife's employment experience (e.g., Booth, Johnson, White, and Edwards, 1984; Huber and Spitze, 1980); marital alternatives (Udry, 1981); divorced parents' antagonistic attitudes toward marriage (Greenberg and Nay, 1982); depressive symptomatology (e.g., Vega, Warheit, and Meinhardt,

1984); cohabitation (DeMaris and Leslie, 1984);

short spacing between pregnancies (e.g., LaRossa and LaRossa, 1981); "de facto" marriage type

(Fergusson et al., 1984); parental disapproval (e.g., Burns, 1984). Such a list could easily be extended. The point is that much of what is understood to play an important role in divorce, separation, and marital instability cannot be accessed by aggregate-level studies. The study of divorce at the aggregate level cannot, therefore, yield definitive results; such studies can only be sug- gestive.9

At the same time, individual-level studies of divorce do not in the main represent an ideal to be emulated on this score. As the above citations will suggest, the determined effort to control sys- tematically for a sufficient number of relevant variables is differentially distributed across the divorce literature. More important for present purposes, with the notable exception of a few recent studies, the individual-level study of divorce has either ignored or paid insufficient attention to social-integration variables. Therefore, we think the primary value of the present research is that it strongly suggests that social integration variables should be investigated rigorously at the individual level of analysis, which, at least in principle, allows for a more definitive understanding of the role of social integration in divorce. The message from the aggregate-level study of divorce, as well as from some recent survey research, is that social integration matters, but to what degree is still quite open to question.

The need now is for individual-level studies of divorce, based on large samples, that test in detail for a much broader set of relevant divorce correlates, including social-integration indicators.

Researchers should also move beyond the religion variable of the percentage Roman Catholic and employ a wider group of indicators that tap other forms of social integration in areas such as the family, occupation, residence, and political be-

havior.

FOOTNOTES

1. While controversy still surrounds what Durkheim meant by social integration (Pope, 1976), the defini- tion used here is that social integration refers to the degree in magnitude and intensity to which people are tied or connected to one another, shared values being an important element in such integration.

2. Another study of divorce that used the American state as the unit of analysis, but did not consider social integration, is Wright and Stetson (1978). One study that used region to study east-west differences in divorce is Pang and Hanson (1968).

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3. Several counties were eliminated because of in-

complete data. The total number of independent ob- servations = 11 variables x 3,111 counties

34,221, with no missing data.

4. Some of the non-social-integration variables used in the study may be interpreted as social-integration variables. For example, unemployment is often thought to be a Durkheimian variable related to anomie. In addition, some of the other variables, such as age and race, are often linked to status integration theory. In terms of unemployment, however, it is clear that Durkheim is not talking about chronic unemployment, but catastrophic unemployment associated with such events as the Great Depression (Breault, 1986). In addition, we distinguish the present approach from that of status integration theory. Originally, status integration theory was an attempt to allow indirect testing of Durkheim's theory of social integration. More recently, researchers have focused on direct testing of that theory (using Durkheim's own variables and indicators), and this is the course that is generally followed in the present study. At the same time, while direct tests of Durkheim's theory have tended to be positive, the most recent large-scale test of status integration theory has failed to find support for the theory (Stafford and Gibbs, 1985).

5. Median population age is not an ideal control variable; an ideal measure would be proportion of married persons in their early, and therefore more divorce-prone, years of marriage. Unfortunately, such data do not exist at the county level. On the basis of regional data we are familiar with, however, it does seem likely that median population age would be strongly correlated with the more ideal measure suggested here.

6. There is still some debate as to whether significance levels have any meaning when entire universes are analyzed. The present study "samples" 99.2% of U.S. counties. Significance levels were added for the convenience of the reader, but the correlation coefficients (both zero-order and partial) are perhaps better understood as indicating actual relationships between the variables, not ones meant to be generalized to a much larger universe. For example, the partial correlation coefficient between unemployment and population change (-.01) is very close to the "true"

relationship that exists between these variables (in the present set of variables) for U.S. counties in 1980, not one that is merely "insignificant." In such a case, significance levels provide us little useful information.

7. Nonlinear and interaction (cross-product) relationships were investigated, including logarithmic trans- formations, exponential functions, and power curves, with negative results.

8. The strong findings of urban effects on divorce with the large sample used here should alert researchers to

a possible error in previous studies of urbanity.

Numerous studies based on smaller samples have failed to find strong urban effects on a large variety of social problems. Commonly, these studies use some set of largest SMSA's or counties--ecological units that are highly urban to begin with. The present study suggests the possibility that when more variation on urbanity is introduced by increasing sample size, strong urban effects may be revealed-that real urban effects are masked when studies are based on small samples of the largest SMSAs or counties.

There is a real question whether the variable of urbanity is meaningful when, say, the largest 100 or so SMSAs are used.

9. This is particularly the case with Becker's (1973, 1974) theory of marriage, where so much depends on the individual maximization of unobservable the-

oretical quantities, that is, utilities. Definitive work on Becker's theory must await the development of techniques to measure utility satisfactorily, as well as an experimental framework for comparing individual utility functions to subsequent behavior.

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