Complex Life Course Patterns and the Risk of Divorce in Second Marriages

JAY TEACHMAN Western Washington University

Complex Life Course Patterns and the Risk

of Divorce in Second Marriages

In this article, I use data on women (N ¼ 655)from the 2002 National Survey of FamilyGrowth to examine the correlates of secondmarital dissolution. I update the limited numberof previous studies on this topic by focusing onthe relationships between divorce and the com-plex life course patterns that characterize re-spondents in second marriages. I pay particularattention to the roles played by stepchildrenand cohabitation. I find that women whobrought stepchildren into their second marriageexperience an elevated risk of marital disrup-tion. Premarital cohabitation or having a birthwhile cohabiting with a second husband did notraise the risk of marital dissolution, however. Inaddition, marrying a man who brought a childto the marriage did not increase the risk of mar-ital disruption.

Although rates of marital dissolution have re-mained constant or even declined over the pasttwo decades, nearly one in twofirstmarriages stillend in divorce (Raley & Bumpass, 2003).Accordingly, there continues to be a substantialpool of men and women who go on to form sec-ond marriages. Indeed, in recent years, over40% of all marriages formed in the United Statesinclude at least one partner who was previouslymarried (National Center for Health Statistics,1995). Thus, a substantial fraction of newly

formed marriages involve individuals who areat risk of a second marital disruption, and the rateat which these marriages dissolve is even higherthan for first marriages (Bramlett & Mosher,2002). Second marriages are likely to differ fromfirst marriages in that they often involve individ-uals with more complex life histories, includingmultiple spells of cohabitation, children fromprior relationships, and the continuing influenceof a previous spouse. Second marriages alsoinvolve individuals who have already learnedabout the process of divorce and likely includea greater fraction of spouses who are negativelyselected on characteristics linked to marital sta-bility. It is likely, therefore, that the factors linkedto the dissolution of second marriages are notthe same as those linked to the disruption of firstmarriages.

Yet the literature is mostly silent on factorslinked to the dissolution of second marriages. Inthis article, I use data on women taken from the2002 National Survey of Family Growth (NSFG)to examine the correlates of secondmarital disso-lution. I update the limited number of previousstudies on this topic by focusing on the relation-ships betweenmartial disruption and the complexlife course patterns that characterize women insecond marriages. I pay particular attention tothe roles played by stepchildren and cohabitation.

Previous Literature

One of the first studies to focus on second maritaldissolution using representative data and appro-priate statistical methodology was conducted byBecker, Landes, and Michael (1977), who notedthat second marriages are less stable than first

Department of Sociology, Western Washington University, 516High Street, Bellingham WA 98225-9081 ([email protected]).

Key Words: cohabitation, life course marital dissolution,second marriage.

294 Journal of Marriage and Family 70 (May 2008): 294–305

marriages. This finding has been replicated byseveral other researchers (Bramlett & Mosher,2002; McCarthy, 1978; Martin & Bumpass,1989). Rather than demonstrating the continuedimportance played by background factors (e.g.,relatively fixed parental and respondent charac-teristics such as race and religion), which are rel-atively strong predictors of first maritaldissolution but relatively weak if not nonexistentpredictors for disruption of second marriages(likely because of strong selectivity on factorsnegatively related to marital stability), the litera-ture on second marital dissolution points to linksbetween the complex life course patterns ofdivorced women and their risk of marital disrup-tion. Particular attention has been paid to the roleplayed by stepchildren in generating marital insta-bility in second marriages. Most studies find that,for women, children from a previous relationshipare associated with an increased risk of endinga second marriage (Becker et al.; Bramlett &Mosher; McCarthy). Children born betweenmarriages have also been linked to an increasedrisk of second marital disruption (Teachman,1986; Wineberg, 1991, 1992). This latter point isimportant given the fact that over 20% of womenmarrying for a second time have given birthbetween marriages, with nearly one third of non-marital births occurring to ever-married women(Bumpass & Sweet, 1989).

Despites its focus on complex life course pat-terning, a key element of the life course on whichprevious research has been silent is cohabitation,in part because most of the available research isdated and was conducted prior to the significantincrease in nonmarital cohabitation that hasoccurred over the past two decades. Althoughnumerous studies have linked premarital cohabi-tation to an increased risk of marital dissolutionin first marriages (Axinn & Thornton, 1992;Bramlett & Mosher, 2002; Teachman, 2003),no study to date has attempted to link intermaritalcohabitation to the risk of second marital disrup-tion. This oversight is critical given the substan-tial increase in cohabitation that has occurredover the past two decades (Bumpass & Lu,2000; Bumpass, Raley, & Sweet, 1995; Raley,2001) and the fact that second marriages are sub-stantially more likely to be preceded by a spell ofcohabitation than first marriages (Bramlett &Mosher).

The rise in cohabitation also means that not allintermarital fertility occurs outside of a stableunion. Indeed, a substantial portion of intermari-

tal fertility occurs within relatively stable cohab-iting unions (Bumpass&Lu, 2000; Raley, 2001),many of which are transformed into marriage.Previous research has been silent on the possibil-ity that intermarital fertility that occurs in a stableunion and which results in marriage is not asstrongly linked to subsequent marital dissolutionas other types of intermarital fertility.

Previous research has also failed to considerthe possibility that not all stepchildren have a uni-formly negative association with marital dissolu-tion. Often due to data limitations, previousresearch has assumed that stepchildren living inthe family are the wife’s biological children. Tosome extent, this assumption has reflected realityin that children of divorce have historicallyresided with their mothers, not their fathers.Yet, in recent decades, changes in child custodyhave meant that more children are spending time(via father custody or shared custody arrange-ments) residing with their fathers after divorce(Cancian &Meyer, 1998). Currently, there existsno information about the role played by the hus-band’s coresidential children in rates of secondmarital disruption.

In this article, using a sample of women takenfrom the most recent round of the NSFG, I repli-cate and expand prior research by examining therelationship between second marital dissolutionand several components of the life course, includ-ing the presence of stepchildren, intermarital fer-tility, and cohabitation. I provide an examinationof the role played by premarital cohabitation, aswell as separating intermarital fertility into thatwhich occurred in a cohabiting union leading tomarriage and that which did not. I also considerthe linkages between marital disruption andcoresidential stepchildren as they may vary ac-cording to whether the biological parent is thewife or the husband. Next, I outline several theo-retical rationales for expecting these complexitiesin the life course to be related to the risk of secondmarital dissolution.

Theoretical Considerations

Stepchildren from prior marriages. Cherlin(1978) argues that remarriage is an incompleteinstitution. According to this view, second mar-riages are more fragile than first marriagesbecause there are few institutionalized normsguiding individuals as they seek to negotiate themultiple roles (father, mother, wife, husband,former wife, former husband, stepfather,

Complex Life Course Patterns and Divorce 295

stepmother, and so on) that are often filled ina second marriage. The lack of firmly establishedroles increases uncertainty and tension in mar-riages that can act to destabilize them. The lackof institutionalization is particularly importantwith respect to children, because parents and step-parents lack clear norms delineating childrearingresponsibilities, leading to confusion and stressthat heighten marital conflict and the risk of mar-ital disruption (Coleman, Ganong,&Fine, 2000).In a related vein, Becker et al. (1977) argue thatchildren from a previous marriage are not mari-tal-specific capital in a secondmarriage (i.e., cap-ital that is created in a marriage and which one orboth spouses may have difficulty enjoying fol-lowing a divorce), and thus they do not representthe same barrier to divorce posed by childrenborn within a second marriage. A stepparentmay have less investment in a stepchild than doesa biological parent (Hofferth & Anderson, 2003)and therefore has less to lose if a divorce occurs.These arguments, consistent with the bulk ofprior research (Becker et al.; McCarthy, 1978),lead to my first hypothesis:

The presence of stepchildren increases the risk ofmarital dissolution in second marriages.

My next hypothesis conditions the relationshipbetween resident stepchildren and marital disso-lution according to gender of the biological par-ent. On one hand, some research suggests thatstepmothers have a more difficult time adjustingto the stepparent role than stepfathers (Cherlin &Furstenberg, 1994; Coleman et al., 2000),although stepparenting can be a difficult role tofulfill for both men and women. Difficulty in ad-justing to the stepparent role may decrease mari-tal satisfaction and thus increase the risk ofmarital dissolution for remarriedwomenwho livewith their stepchildren. On the other hand, remar-ried men who have their biological children liv-ing with them may be more actively involved inparenting, reducing friction between spouses overparenting and related household tasks, increas-ing positive marital functioning (Hofferth &Anderson, 2003) and reducing the risk of mar-ital disruption. Evolutionary psychologists arguethat biological fathers are much more willing toinvest resources in children than are stepfathers(Daly & Wilson, 2000; Hofferth & Anderson).It may also be the case that remarried men whohave their biological children living with themare selective of those who are more family-

oriented men and who would be less likely todivorce than other remarried men (Hofferth &Anderson). In support of this notion, Barre(1993) and Goldscheider and Sassler (2006)report that single men with coresident childrenaremore likely tomarry than are singlemenwith-out children. Finally, it may be the case that menwith coresident children may not be able to counton their former spouses for consistent parenting,increasing the pressure these men may feel forstaying married. Accordingly, I hypothesize thefollowing:

When compared to the presence of the wife’s bio-logical children from a previous relationship, thepresence of the husband’s biological childrenfrom a previous relationship is associated witha lower risk of marital dissolution.

Intermarital cohabitation and fertility. Althoughprevious research has been consistent in linkingpremarital cohabitation to a higher risk of maritaldisruption in first marriage, it is an open questionwhether cohabitation prior to a second marriagewould have the same relationship. With respectto first marriages, Axinn and Thornton (1992)find evidence that premarital cohabitation is bothselective of individualswho are less committed tothe institution of marriage and acts to increase anindividual’s acceptance of divorce (see alsoAxinn & Thornton, 1992; Axinn & Thornton,1993; Cunningham & Thornton, 2005). By defi-nition, however, individuals in second marriageshave all had at least one terminated intimate,coresidential relationship, reducing the likeli-hood that subsequent cohabitation would repre-sent further selectivity or further changeattitudes toward cohabitation and divorce. Thissupposition is consistent with subsequent levelsof marital happiness (but see Xu, Hudspeth, &Bartkowski, 2006, for contrary evidence). Thus,my next is hypothesis is the following:

Premarital cohabitation before a second mar-riage is not related to the risk of subsequent mar-ital dissolution.

Previous research has found that premarital fertil-ity increases the risk of marital disruption in firstmarriages (Raley & Bumpass, 2003; Teachman,2002). Other research has found that intermaritalfertility generates a higher risk of marital disrup-tion for second marriages (Teachman, 2003;Wineberg, 1991, 1992). However, these latterstudies have ignored the context within which

296 Journal of Marriage and Family

intermarital fertility occurs, specifically cohabita-tion.With the rise in nonmarital cohabitation, it isincreasingly likely that an intermarital birth willoccur in a cohabiting union (Raley, 2001) andthus this child is not a stepchild. Because theyare the biological children of both spouses, thesebirths are not subject to the same ill-definednorms surrounding the childrearing of stepchil-dren and represent relationship marital-specificcapital that is most easily enjoyed when the cou-ple is stable. Thus, my last hypothesis is this:

Intermarital births that occur within a cohabitingunion that leads to marriage are less likely thanstepchildren to be positively related to the risk ofmarital dissolution in second marriages.

In my analysis, I examine the relationshipsbetween second marital dissolution and stepchil-dren, cohabitation, and intermarital fertility whilecontrolling for a number of variables that previ-ous research indicates could confound thehypothesized relationships. These control varia-bles include age at second marriage, race/ethnic-ity, two-parent childhood family status, religion,mother’s education, respondent’s education,childhood family size, relative age of spouses,and spouse’s previous marital status. These areall variables that have been linked to the risk ofsecond marital dissolution in prior research(Bramlett & Mosher, 2002; Teachman, 1986;Wineberg, 1991, 1992).

METHOD

Data

The data are taken from the 2002 round of theNational Survey of Family Growth. The NSFGis a national area probability survey, a cross-sec-tional sample of 12,571 civilian noninstitutional-ized respondents ages 15 – 44 (N ¼ 7,643women and 4,928 men) residing in the UnitedStates (Groves, Benson, & Mosher, 2005). TheNSFG collected extensive life history data fromrespondents that detail the dates of their premar-ital, marital, and intermarital relationships, aswell as the dates of their premarital, marital, andintermarital births. I focus on information pro-vided by women in order to avoid recall biaseslinked to marital and fertility histories providedby men (Bumpass, Martin, & Sweet, 1991;Rendall, Clarke, Peters, Ranjit, & Verropoulou,1999), although I make use of information from

men to corroborate results based on reports fromwomen (note that these men are not the spousesof the women interviewed, however). I selecta subset of Black, White, and Hispanic womenmarried at least two times. The resulting samplesize is 655 women who have had a second mar-riage. I do not examine higher-order marriages(i.e., third, fourth, or fifth marriages), because ofsmall sample sizes and the fact that in a samplewith a relatively low upper age limit such as theNSFG, higher-order marriages are increasinglyselective of individuals who marry and divorcequickly (thus yielding increasing negative selec-tivity with respect to marital stability).

The NSFG data have historically been of veryhigh quality (the 2002 NSFG is the sixth cycle ofthe survey with each cycle interviewing a differ-ent sample). Unfortunately, an error in interviewspecifications resulted in many divorced, wid-owed, and separated women in the 2002 surveybeing skipped past questions asking when andhow their marriages ended (National Center forHealth Statistics, 2004). Of the 655 womenexamined in this article, 118 (18% of all womenand 51% of women whose second marriageshad ended) were affected by the faulty skip pat-tern. Of particular note is the fact that the faultyskip pattern did not occur randomly. Womenwhose husbands had children from previousrelationships were disproportionately affected.Indeed, all of the women whose husbands hadchildren from a previous relationship were routedpast questions ascertaining how and when theirmarriages ended.

The missing data on how and when a marriageendedwere imputedbyNSFGstaffusinga sequen-tial multiple regression imputation procedure(National Center for Health Statistics, 2006). AsI indicate later, the imputed values appear to yieldestimates of the overall rate of second divorce thatare reasonable and comparable with other datasources. This consistency in overall rates, how-ever, does notmean that biaswill not result inmul-tivariate models seeking to obtain estimates of theeffects of individual variables on the risk ofmaritaldisruption. To overcome this problem, I analyzethe data using event-history procedures that allowinclusion of left censored data (the type of cen-soring created when an end date is not known),providing unbiased, if not the most efficient, esti-mates of regression coefficients (compared to esti-mates that would result if the exact dates ofmaritaldissolution were known). This procedure isdescribed in more detail later.


Another limitation of the NSFG data is relatedto the age range of the sample. Because the oldestrespondents in the NSFG are age 44, remarriagesat older ages are necessarily excluded. The extentto which age at remarriage may modify the rela-tionships between observed covariates and mari-tal dissolution may bias the results presentedhere. Unfortunately, there is no other large-scale,nationally representative, and contemporary sur-vey effort with a broader range of ages that can beused to generate benchmarks for comparisonswith results obtained from the NSFG.

Measures

Dependent variable. The dependent variable (asexpressed in the multivariate models) is the oddsthat a second marriage will survive beyond a cer-tain marital duration and is estimated using infor-mation on the duration of second marriages(measured in months). Marriages are consideredto be disrupted at either the date of divorce orthe date of separation, whichever came first. Fol-lowing common practice, I censor stable mar-riages at the date of the survey (Bumpass,Martin, & Sweet, 1991).

Independent variables. I include two variablesthat indicate the wife’s prior fertility history.The first variable is a count of the number ofbirths she had in prior relationships. I assume thatthese children lived with their mother in her sec-ond marriage, although I cannot determine fromthe available data whether they also spent sometime residing with their fathers. If my hypothesesare correct, then the coefficient of this variableshould be less than one and statistically signifi-cant (because I estimate a multiplicative model,coefficients equal to one signify no relationshipbetween the covariate in question and maritaldissolution). The second variable indicateswhether the woman had a birth between mar-riages while cohabiting with her second husband(0 ¼ no, 1 ¼ yes). If my hypothesis is correct,the coefficient for this variable should be closerto one (and likely nonsignificant) compared tothe coefficient for the woman’s fertility in priorrelationships.

The NSFG data also contain information aboutthe husband’s prior fertility. I include a variableindicating the number of births he had in prior re-lationships. This variable may be subject to mea-surement error, however, given the fact that mentend to underreport prior children (Rendall et al.,

1999). A second indicator of the husband’s priorfertility is whether any of his children from a priorrelationship ever lived with the couple in mar-riage (coded as 0 ¼ no, 1 ¼ yes). This variableis less likely to be subject to measurement errorbecause it represents an experience directly ob-servable by the wife and is based on her report.If my hypothesis is correct, then the coefficientfor having children from the husband’s previousrelationships living with the family should becloser to one (and likely nonsignificant) com-pared to the coefficient for the woman’s numberof children from a previous marriage.

The NSFG contains information about thebeginning and ending dates for each nonmarital,cohabiting union experienced by women in thesample and whether these unions ended in dis-ruption or marriage (unfortunately, there is noinformation about her husband’s previous rela-tionships). From this information, I created sev-eral dummy variables categorizing a woman’shistory of cohabitation. The first variable isa dichotomy indicating whether the woman co-habited with her first husband only. The secondvariable is also a dichotomy and indicateswhether a woman cohabited with her second hus-band only. The third variable is another dichot-omy indicating whether a woman cohabitedwith both her first and second husbands. Twoadditional variables indicate whether a womancohabited prior to her first marriage with some-one other than her first husband and whethershe cohabited prior to her second marriage withsomeone other than her second husband. In all in-stances 0 ¼ no, 1 ¼ yes. If my hypothesis iscorrect, the coefficients for these variables willnot be statistically significant.

Control variables. A number of commonly usedfamily background, life course, and socioeco-nomic variables pertaining to women are avail-able in the NSFG, and I use them in order tolimit the likelihood that any associations linkedto the focal variables are confounded with thesevariables. Each of these control variables hasbeen identified in prior research as being linkedto the risk of second marital dissolution (Bram-lett & Mosher, 2002; Teachman, 1986; Wine-berg, 1991, 1992). The control variables that Iuse are mother’s education (1 ¼ less than highschool, 2 ¼ high school graduate or GED, 3 ¼some college, 4 ¼ bachelor’s degree or high-er); number of siblings while growing up; twodummy variables indicating whether the


respondent is Black or Hispanic (White servesas the baseline); two dummy variables indicat-ing whether the respondent is Catholic or hasno religion (Protestant and other religionsserve as the baseline); a dummy variable indi-cating whether the woman grew up in a two-parent family until age 18 (having grown up ina two-parent family serves as the baseline); thewoman’s level of education measured in years;and her age at second marriage measured inyears. I use information about the husband’s ageat marriage to create two additional dummy vari-ables indicating whether the wife was at leasttwo years older than the husband or the husbandwas at least 5 years older than the wife. Finally,a dummy variable is included that indicateswhether the husband had been married before.All dummy variables are coded as 0 ¼ conditionnot present, 1 ¼ condition is present.

Model

To deal with right censoring (i.e., respondentswho had not experienced marital dissolution asof the date of the survey), the normal procedureis to use a hazard rate model. Most commonly,social scientists use a Cox proportional hazardsmodel or a discrete-time hazard rate model. Forthe NSFG data, I employ a relatively less usedparametric hazard rate model (also known as anaccelerated failure time model). In contrast tothe Cox and discrete-time models, parametrichazard rate models require the user to specifya particular functional form for the baseline haz-ard rate (e.g., how the hazard rate is assumed tovary over time). I chose a log-logistic parametricmodel because this parametric form can fit mostobserved patterns of hazards for marital dissolu-tion (i.e., either an inverted-U shape or a mono-tonically declining hazard rate). As noted later,the log-logistic specification also has a particu-larly appealing interpretation as a proportionalodds model.

For my purposes, an attractive feature of para-metric hazard rate models (as they are estimatedin SAS) is their ability to incorporate left-cen-sored data into the likelihood function (Allison,1995). Left-censored data occur when all oneknows about the timing of an event is that it isless than some value (contrast this to left trunca-tion where the origin time, here entry into sec-ond marriage, is not known); this is exactly thesituation that presents itself in the 2002 NSFGwherein women were not properly asked ques-

tions about the date at which their secondmarriage ended. Far from being useless, left-censored data provide considerable informationabout the process under study by allowing theresearcher to know that an event (here, maritaldissolution) has occurred prior to some (marital)duration. For example, consider the secondmarriages of two women, one married in 1998and the other married in 2000, both of whomhave experienced marital disruption at someunknown marital duration (fortunately, there isno evidence of a relationship between marriagecohort and the risk of second marital disruptionamong the marriage cohorts represented in the2002 NSFG). We know for the first woman thather marital duration must be less than 4 years,while marital duration for the second womanmust be less than 2 years. Heuristically, left-censored data allow the researcher to know thatindividuals with a particular covariate profile dis-solve their marriages at some duration earlierthan individuals with a different covariate profile,even if the exact timing of the event is unknown.The resulting parameter estimates using left-censored data are unbiased, albeit less efficientthan the case would be if exact dates were known.

The model I estimate using SAS takes the fol-lowing form:

logTi ¼ b0 1 b1x11 1.1 bkxik 1re ð1Þ

where Ti is the failure time (or censored time) ofthe ith individual (here, marital duration), e isa random disturbance term, and b0 1 . 1 bkand r are parameters to be estimated. Becausethe model can be specified as a log-durationmodel (the dependent variable is the log of mar-ital duration), it is often called an accelerated-failure time model (i.e., the model for maritalduration itself is multiplicative). Although themodel implies a hazard rate model, the log-logistic functional form is somewhat complex,and there is a more attractive alternative forinterpretation. Specifically, assuming a log-logistic distribution for survival time, the fol-lowing transformation of the model is possible(Allison, 1995):

loghS�t�=�1� S

�t��i

¼ b�0 1 b�1x11

1.1 bk � xik1 clogt

ð2Þ


where S(t) is the probability of surviving to mar-ital duration t and bi* ¼ bi/r for i ¼ 1, ., k(note that r is the error term parameter fromequation 1).

The exponentiated coefficients, exp(bi*), pro-vide the multiplicative effect of a covariate onthe odds of surviving to marital duration t, thusmaking it a proportional odds model. Exponen-tiated coefficients less than 1.0 can be thoughtof as negative effects, reducing the odds of sur-vival to marital duration t. Exponentiated coeffi-cients greater than 1.0 can be thought of aspositive effects, increasing the odds of survivalto marital duration t. Note that the direction ofrelationship is opposite to that commonly asso-ciated with hazard rate models that predict therate of marital disruption (e.g., a higher rate ofmarital disruption leads to a lower probabilityof a marriage surviving to any point in time andvice versa). In the multivariate results shownlater, I present these exponentiated coefficients.A further transformation, [exp(bi*) � 1]* 100,yields the percent change in the odds of surviv-ing to marital duration t associated with a oneunit change in a variable.

DESCRIPTIVE STATISTICS

Descriptive statistics based on weighted data forthe covariates in the sample are provided inTable 1. The average age at second marriage inthis sample is nearly 29 years. A majority of thewomen are White, grew up in two-parent fami-lies, express some religion other than Catholi-cism, have reasonably well-educated mothers(at least a high school degree), are high schoolgraduates, come from moderate size families,and are approximately the same age as their hus-bands (although if there is an age difference, hus-bands are more likely to be older). Nearly half thehusbands have been married before; the averagenumber of children husbands had from previousrelationships is 0.77, and 18% of husbandsbrought children to the marriage. About 11% ofthe women in the sample had cohabited priorto their first marriage only, about 37% hadcohabited prior to their second marriage only,and 23% had cohabited with both spouses. About3% of women had cohabited prior to first mar-riage with someone other than their first husband,and nearly 9%had cohabited prior to secondmar-riage with someone other than their second hus-band. The average number of children broughtto a second marriage by these women was just

less than 1 (0.95), and about 11% of womenhad a birth while cohabiting premaritally withtheir second husbands.

Shown in Table 2 are the proportions of secondmarriages intact at various durations based on lifetable estimates. Values are shown for women inthe 1995 NSFG, women in the 2002 NSFG, andmen in the 2002 NSFG. For women in the 2002NSFG who were part of the faulty skip pattern,I used imputed dates of marital dissolution inthe life table calculations. If they are not biased

Table 1. Descriptive Statistics for Covariates Used in

the Analysis of Second Marital Dissolution: 2002 National

Survey of Family Growth

Variable M or % SD

Age at second marriage 29.43 5.75

Race/ethnicity

Hispanic 10.83

Black 6.90

White (baseline) 82.27

Two parent childhood family

until age 18

61.02

Religion

Catholic 35.77

No religion 5.38

Other religion (baseline) 58.85

Mother’s educational attainment 2.11 0.97

Respondent’s educational attainment 12.88 2.32

Number of siblings 2.72 1.60

Wife at least two years older 0.64

Husband at least five years older 20.61

Husband married before 49.66

Cohabitation history

Cohabited with first husband only 11.35

Cohabited with second husband only 36.83

Cohabited with both husbands 23.35

Cohabited with other than

first husband

3.43

Cohabited with other than

second husband

8.62

Never cohabited 16.42

Husband’s fertility

Number of children from

prior relationships

0.77 1.14

Husband’s children lived with family 18.00

Respondent’s fertility

Number of births from prior

relationships

0.95 0.92

Intermarital birth while cohabiting

with second husband

10.76

Note: All values are weighted. N ¼ 655 women.


in the aggregate, these imputed dates should yieldapproximately the same proportions surviving asnoted forwomen in the 1995NSFG (assuming nolarge-scale period changes in marital dissolutionin the 7 years separating the two surveys) andmen in the 2002 NSFG. I also show values for1995 women and 2002 women stratified by thepresence of stepchildren. Again, values acrossthis stratification variable for 1995 and 2002should be approximately the same in the absenceof bias introduced by the faulty skip pattern in the2002 NSFG. Indeed, this is the case; women inthe 2002 NSFG evidence rates of marital stabilityvery similar to those registered for the two com-parison groups, as well as across the stratificationvariable (stepchildren).

MULTIVARIATE RESULTS

Multivariate results based on unweighted data(significance levels are adjusted for clusteringin the NSFG sample) are shown in Table 3. Mod-els 1 and 2 are estimated using the correction forleft censoring rather than the imputed dates ofmarital dissolution. Excluded from Model 1 arevariables pertaining to husband’s prior fertility,which are included in Model 2. Because allwomen who married men who had children froma previous relationship were involved in thefaulty skip pattern, comparing Models 1 and 2allow some indication of whether including hus-band’s fertility in the model substantially altersconclusions reached for other variables in themodel (the results suggest that this is not thecase).Model 3 is estimatedwithout the correctionfor left censoring by using imputed values fordates of marital dissolution.

The coefficients shown represent multiplica-tive relationships between the covariates andthe odds of surviving to marital duration t.Thus, the coefficient of 1.107 for age at secondmarriage in Model 1 indicates that the odds of‘‘surviving’’ marital dissolution to a given mari-tal duration are about 11 percent higher ((1.107� 1.0) * 100 ¼ 11.0%) for each additional yearage at second marriage is delayed. This relation-ship is statistically significant. Age at secondmarriage is also statistically significant in Mod-els 2 and 3, although the estimate in Model 3 issomewhat smaller. There are only relativelyminor differences in coefficient estimatesbetween Models 1 and 3. This consistency inparameter estimates increases confidence in theobserved results despite the presence of thefaulty skip pattern in the 2002 NSFG.

Other than age at second marriage, only His-panic origin has a statistically significant relation-ship (at the .10 level) with marital dissolution(indicating a positive relationship between His-panic origin and marital stability). The generallack of statistically significant coefficients forthe background factors (in contrast to the situa-tion normally found for first marriages) is consis-tent with previous research on the topic (Clark &Crompton, 2006; Teachman, 1986; Wineberg,1991, 1992). As I hypothesized, premaritalcohabitation is generally not related to the riskof second marital disruption. Only women whocohabited with both their first and second hus-bands are more likely to end their second mar-riages than other women. In particular, womenwho only cohabited with their second husbandare not more likely to experience divorce thanwomen who never cohabited (although thisresult should be interpreted with some cautiondue to the fact that the estimator used is not fullyefficient).

Consistent with my hypotheses is the coeffi-cient for the woman’s prior fertility. In parti-cular, the coefficient for her prior fertility isnegative (here, less than 1.0) and statisticallysignificant, indicating that for each additionalchild there is about a 45% reduction in the oddsthat a marriage will survive to a given maritalduration (using the coefficients from Models 1and 2). As I hypothesized, marital dissolutionis not related to the husband’s prior fertility.Also consistent withmy expectations, births thatoccur while a woman cohabits with her husbandprior to secondmarriage are not related to subse-quent marital dissolution.

Table 2. Life Tables Estimates of the Proportion of Second

Marriages Intact at Various Months: 1995 and 2002

National Surveys of Family Growth

1995 NSFG 2002 NSFG

Stepchildren

Present

Stepchildren

Present

Months

Since

Marriage No Yes

All

Women No Yes

All

Women

All

Men

12 .97 .96 .95 .97 .95 .96 .95

36 .87 .85 .86 .85 .82 .86 .82

60 .82 .74 .77 .80 .72 .73 .71

Note: All values are weighted.


Additional Checks

I also investigated second marital dissolutionusing data provided by men in the 2002 NSFG.Due the smaller sample size formen, there are on-ly 281 second marriages. More important, thereare only 81 second marital dissolutions. Thus,even though the data for men do not suffer fromthe faulty skip pattern found in the data forwomen, the sample size is small. As a conse-quence, the data for men are subject to muchgreater sensitivity tomodel specification, particu-larly as the number of parameters estimated in-creases (estimated parameter estimates tend toshift dramatically with the addition and deletionof variables). The data for men are also limitedby the fact that the NSFG did not ascertain

whether his spouse’s children ever lived withhim (as was the case for data collected fromwomen). With these restrictions in mind, it isinteresting to note that the only consistently sig-nificant effect found in models estimated frommale data pertains to the number of children hiswife had in prior relationships (results notshown). The average coefficient estimate for thenumber of his wife’s children from prior relation-ships indicates a 36% reduction in the odds ofa marriage surviving to a given marital duration(results not shown) for each additional child. Thisis about the same magnitude of the coefficient forthe woman’s prior fertility shown in Models 1and 2 in Table 3, providing additional supportfor the notion that a wife’s prior fertility is related

Table 3. Odds Ratios From Log-Logistic Accelerated Failure Time Hazards Models Predicting Survival of Second Marriages:

2002 National Survey of Family Growth

Variable

Model 1

(without imputed values)

Model 2

(without imputed values)

Model 3

(with imputed values)

Age at second marriage 1.107* 1.111* 1.062*

Race/ethnicity

Hispanic 1.683y

1.718y

1.497

Black .723 .806 1.130

Two parent childhood family until age 18 1.253 1.249 1.319

Religion

Catholic 1.201 1.178 1.438

No religion .795 .792 .769

Mother’s educational attainment 1.180 1.178 1.114

Respondent’s educational attainment .941 .938 .956

Number of siblings 1.030 1.036 1.056

Wife at least 2 years older .245 .238 .444

Husband at least 5 years older 1.429 1.427 1.409

Husband married before .856 .942 1.184

Cohabitation history

Cohabited with first husband only .669 .656 .529y

Cohabited with second husband only .843 .826 .808

Cohabited with both husbands .590* .590* .537*

Cohabited with other than first husband 1.196 1.179 1.040

Cohabited with other than second husband .915 .922 .845

Husband’s prior fertility

Number of children from prior relationships .873 1.024

Husband’s children lived with family 1.297 1.562

Wife’s prior fertility

Number of births from prior relationships .755* .758* .763*

Intermarital birth while cohabiting

with second husband

.911 .889 .845

Log-likelihood �513.29 �512.276 �564.314

Degrees of freedom 19 21 21

yp, .10; *p, .05.


to secondmarital dissolution (negatively), but nota husband’s prior fertility.

Summary and Conclusion

Although a substantial fraction of all marriagescontracted each year in the United States includesat least one partner who was previously married,we have very little information about factorslinked to the disruption of these marriages. Usingdata from the 2002 National Survey of FamilyGrowth, I investigated the covariates of secondmarital dissolution for women, focusing on thecomplex life course patterns that so often charac-terize these unions, with particular emphasis onpatterns of cohabitation and fertility. Althoughage at marriage continued to exhibit a significantrelationship to the risk of second marital dissolu-tion, many of the background factors linked tofirst divorce in previous research were not oper-ant (e.g., race, status of childhood family, age dif-ference of spouses). The lack of significantpredictors of secondmarital dissolution is consis-tent with the notion that individuals in secondmarriages are selective with respect to unmea-sured characteristics positively linked to maritaldisruption.

Other than age at second marriage, only twocovariates were consistently related to the riskof second marital disruption at the conventionallevel of statistical significance (p , .05). In par-ticular, women who brought children into theirsecond marriage experienced an elevated risk ofmarital disruption (had marriages that endedsooner). In contrast, women who had an inter-marital birth while cohabiting with their even-tual husbands did not experience an increasedrisk of second marital dissolution. Similarly,there was no increase in the risk of second mari-tal dissolution associated with marrying a manwho brought a child to the marriage from a priorrelationship. Finally, there is only limited evi-dence that premarital cohabitation is linked tothe risk of second marital disruption. The effectof premarital cohabitation (an increased risk ofmarital disruption) was restricted to womenwho cohabited with both their first and secondhusbands.

The results pertaining to intermarital cohabita-tion and fertility are consistent with findings pre-sented by Teachman (2003), who found thatpremarital cohabitation and premarital sexrestricted to a woman’s first husband are notrelated to the risk of first marital dissolution. Inti-

mate, nonmarital relationships have apparentlybecome generally accepted patterns of courtshipand do not reflect selectivity on characteristicspositively related to marital disruption. Nor isthere evidence that these relationships generatecircumstances that lead to a weakening of mar-riages. On the other hand, previous entangle-ments involving more than a woman’s secondhusband are positively related to the likelihoodof marital dissolution. In particular, having chil-dren with other men substantially raises the riskof divorce. The fact that the same is not necessar-ily true for men (e.g., the lack of a relationshipbetween the husband’s children living in the fam-ily and marital disruption) indicates the genderednature of life course complexities. Apparently,gender sets the context within which life coursepatterns are evaluated and subsequently exertsinfluence on second marriages (and on first mar-riages, as well; see Kalmijn & Poortman, 2006).

Subsequent research needs to pay attention toseveral new lines of inquiry. First, better informa-tion is needed about both partners in the relation-ship. The current project was only able to assess(primarily) the characteristics of women. Thepotentially gendered nature of relationships indi-cates the need to pay attention to the characteris-tics of husbands. For example, nothing is knownabout the relationship between husbands’ historyof nonmarital cohabitation and marital stability.Second, because relationship processes are gen-dered (Kalmijn & Poortman, 2006), informationon couples should be considered. The NSFG in-terviewedmen andwomen in differentmarriages,not couples. Thus, there is extremely limitedinformation about spouses in the NSFG, and allof this information is reported by proxy. Third,the domain of life course patterns consideredneeds to be extended. Important components ofthe life course that come to mind include laborforce participation and schooling, as well asextended kin relationships that may include car-ing for elder parents. A search for extended pre-dictors of second marital dissolution may showthat the determinants ofmarital stability in secondmarriages may be quite different from thoselinked to marital stability in first marriages.Fourth, subsequent research needs to further con-sider the fact that the association between maritaldissolution and various characteristics that mayshift over a marriage, such as income and thepresence of children.

Finally, data that better measure the exact tim-ing of marital dissolution are needed. Although I


was able to employ a log-logistic acceleratedfailure time model to make best use of the left-censored data contained in the 2002 round ofthe NSFG, the results obtained are not the mostefficient. Data with precise dates would lead tomore efficient parameter estimates and mightallow researchers to ascertain statistically signif-icant covariates that are not apparent with the dataused in this article.

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Complex Life Course Patterns and the Risk of Divorce in Second Marriages