 An international transition away from familially-arranged marriages toward participation in spouse choice has endured for decades and continues to spread through rural Asia today. Though we know this transformation has important consequences for childbearing early in marriage, we know much less about longer-term consequences of this marital revolution. This study draws upon theories of family and fertility change and a rural Asian panel study designed to investigate changes in both marital and childbearing behaviors to investigate these long-term consequences. Controlling for social changes that shape both marital practices and childbearing behaviors, and explicitly considering multiple dimensions of marital processes, we find evidence consistent with an independent, long-standing association of participation in spouse choice with higher rates of contraception to terminate childbearing. These results add a new dimension to the evidence linking revolutions in marital behavior to long-term declines in fertility, but also motivate new research to consider a broader range of long-term consequences of changing marital processes. Keywords: Marriage, Contraception, Arranged Mariage, Fertility, South Asia Social change worldwide is steadily eroding the practice of familially-arranged marriage. This is true in Asia, Africa, and Latin America, but most recently in rural South Asia (Ahearn 2004; Allendorf 2009, 2012; Ghimire et al. 2006; Hart 2007; Malhotra 1991; Pasupathi 2002; Thornton and Lin 1994). Nearly three decades ago, demographers began providing evidence of wide-ranging consequences of this revolutionary transition in marital behavior. The switch to participation in spouse choice speeds childbearing after marriage (Hong 2006; Rindfuss and Morgan 1983; Wang and Quanche 1996; Whyte 1990). Through the decades, we have learned more about the relationship between first birth and changing marital processes, but we have learned little about the longer-term consequences of this marital revolution. For example, though the transition away from arranged marriage speeds the first birth, we know little about how it shapes subsequent childbearing, especially the termination of childbearing. This question, however, is important because the answer speaks to the potential of these worldwide revolutions in marital processes to produce widespread fertility declines through greater use of contraception. Here we investigate this question and provide unique evidence of the independent influence of the transition away from arranged marriage on contraception to limit fertility. A key obstacle to investigating the independent influences of marital arrangement on fertility limitation is the empirical evidence this investigation demands. First, many of the same social and economic changes which stimulate widespread transitions in marital behavior also shape fertility limiting behaviors (Axinn and Yabiku 2001; Bloom and Reddy 1986; Ghimire et al. 2006; Hong 2006; Malhotra 1991; Thornton and Lin 1994). Therefore, investigating the independent consequences of the transition away from arranged marriage requires careful consideration of wide-ranging social and economic factors which may simultaneously shape both marital arrangement and contraception. Second, marital arrangements cannot be observed independent of marriage timing, and marriage timing is also known to have important consequences for subsequent childbearing behavior (Bloom and Reddy 1986; Bongaarts 1978; Hong 2006; Suwal 2001; Wang and Quanche 1996). Because of this, the empirical evidence needed to address these questions must combine detailed measures of marital arrangement with measures of marriage timing, as well as the social and economic factors that drive these dimensions of marital processes. To guide our empirical investigation of these important issues, we construct a theoretical framework that combines frameworks linking variations in marriage behavior to subsequent fertility with frameworks linking the influence of social changes on those same marriage and fertility behaviors. The framework we construct acknowledges the multidimensional nature of marital processes and the need to formulate hypotheses in relation to specific dimensions of marriage, rather than assuming marriage as a single discrete event (Thornton et al. 1994). Additionally, this framework emphasizes the importance of changes in local community context for both marriage processes and fertility limitation (Axinn and Yabiku 2001; Brauner-Otto et al. 2007; Ghimire and Axinn 2010; Yabiku 2004). Finally, this framework is constructed on a strong life course foundation—a foundation predicting that early life circumstances and experiences predict later life choices (Elder 1974, 1985, 1994, 1998). This emphasis leads us to incorporate premarital non-family experiences and marital experiences early in the life course into models of contraception later in the life course. To test hypotheses emerging from this framework, we use detailed data from Nepal that document local social and economic changes, parental family background, individual non-family experiences, marital experiences, and contraception for both husbands and wives. This study uses Life History Calendar (LHC) measures from 2,022 ever-married women to create measures of their premarital, marital, and contraception experiences matched with measures of community context and family background. Together these measures provide a unique opportunity to document both the overall influence of marital processes on contraception to limit fertility and the independent long-term consequences of familially-arranged marriage versus some degree of participation in spouse choice. Nepal is an ideal setting for this research because, until recently, fertility limitation was not an option for cultural reasons as well as the limited availability of modern contraceptive methods (Bennett 1983; Fricke 1986; Tuladhar 1987, 1989). Additionally, marriages were virtually all arranged by parents and relatives at very young ages (Ahearn 2004; Choe et al. 2004; Ghimire et al. 2006; Morgan and Niraula 1995). However, recent changes in social, economic, and institutional contexts have stimulated a rapid increase in both contraception and age at first marriage, as well as the participation of individuals in the selection of their own spouse (Axinn and Yabiku 2001; Ghimire et al. 2006; Morgan and Niraula 1995). This setting thus provides a crucial opportunity to examine the relationship between multiple dimensions of marital processes and contraception for terminating childbearing. Fertility transition has been such an important element of social change that numerous theorists have focused on aspects of fertility. Scholars have identified many individual-level factors that influence fertility such as education, employment, media exposure, religion, individuals' orientations about family, and family formation (Blossfeld and Huinink 1991; Brien and Lillard 1994; Caldwell 1982; Hirschman 1985; Hirschman and Rindfuss 1980; Notestein 1953). These also include family- and household-level factors such as parents’ education, work, media exposure, and fertility behavior (Axinn and Yabiku 2001; Caldwell et al. 1983, 1988). Finally, these factors also include various dimensions of social context, such as the spread of non-family services (Axinn and Yabiku 2001), mass education (Axinn and Barber 2001), family planning policy (Entwisle and Mason 1985), and family planning programs (Brauner-Otto et al. 2007; Entwisle et al. 1997; Knodel 1987). This body of literature has provided numerous insights regarding the factors affecting dimensions of fertility behavior and fueled theories designed to explain all or part of the transition from high fertility and no use of birth control to low fertility and widespread use of birth control. Research has also demonstrated the important influence of change and variation in individuals’ community context and non-family experiences on marital processes, including marital arrangement, age at marriage, and quality of the husband-wife relationship (Ghimire et al. 2006; Hoelter et al. 2004; Yabiku 2004, 2005). Theory suggests that change and variation in a wide array of family behaviors, including marital processes, have been important vehicles of worldwide fertility change (Caldwell 1982; Chesnais 1992; Freedman 1979, 1987; Lesthaeghe 1983; Thornton 2001). However, the influence of marital processes on childbearing outcomes may not be independent of the community, family, and individual factors that shape both marital processes and childbearing behaviors. A large body of literature has documented important contextual influences on marital and closely related behaviors (Axinn and Yabiku 2001; Brewster 1994; Crane 1991; Dyson and Moore 1983; Hirschman and Young 2000; Hogan and Kitagawa 1985; Rindfuss and Hirschman 1984; Yabiku 2004). Research in Asian settings demonstrates that new community services can have a substantial influence on marriage timing and marital relationships (Dyson and Moore 1983; Hirschman 1985; Hirschman and Rindfuss 1980; Rindfuss and Hirschman 1984; Thornton and Lin 1994; Yabiku 2004). In predominantly agrarian societies, in which most social and economic activities are organized by families, new access to non-family services in the local community can stimulate new marital expectations and behavior (Thornton and Fricke 1987; Thornton and Lin 1994). Proximity to non-family organizations such as schools, employers, health services, and transportation services encourages participation in spouse choice, later marriage, and stronger emotional bonds between husband and wife (Ghimire et al. 2006; Hoelter et al. 2004; Niraula 1994; Yabiku 2004, 2006). New early life course, non-family experiences also shape subsequent marital behaviors. Caldwell (1982) and Thornton (2005) argue that present-day schooling and mass media in many settings outside the West are crucial factors in changing cultures and values toward those in the West. This is likely to be particularly true in South Asia, where educational materials themselves often include British examples of family life and individual choice (Caldwell 1982; Caldwell et al. 1988). These are likely to include less positive attitudes toward arranged marriage, more positive attitudes toward later marriage, and greater emphasis on the emotional bond between husbands and wives (Ghimire et al. 2006; Hoelter et al. 2004; Yabiku 2004). In arranged marriage societies of South Asia and elsewhere, non-family experiences among youth are likely to create greater independence between youth and their parents (Fox 1975; Ghimire et al. 2006; Thornton et al.1994; Van Bavel and Kok 2009). Thus, new non-family experiences, exposure to new ideas about marriage that differ from historically common ideas in South Asia, and new independence from parents each work in the direction of less arranged marriage, later marriage, and more emphasis on the positive emotional bond between husbands and wives. Below we discuss the mechanisms likely to link these same dimensions of marital experience to contraception to terminate childbearing. Many dimensions of marital processes may influence key childbearing behaviors such as contraception. Perhaps the strongest and most obvious link between marital experiences and contraception to limit childbearing revolves around marriage timing. In settings like Nepal, where marriage remains the principal route to exposure to intercourse, changes toward later marriage have an immediate effect on childbearing, reducing fertility (Axinn and Yabiku 2001). There are two closely linked dimensions of marital experiences: 1) marriage timing (age at first marriage), and 2) marriage duration (number of years since first marriage). Delayed age at marriage and shorter marital duration both decrease exposure to the risk of childbearing by reducing exposure to sex, but these same factors may also influence the use of contraception to limit childbearing. Recent studies of marital dynamics provide evidence that an increase in age at marriage has consequences for childbearing intentions and behaviors, including greater contraception to achieve childbearing intentions (Hoelter et al. 2004; Hong 2006; Mason and Smith 2000; Niraula 1994; Satayavada and Adamchak 2000; Schuler et al. 2006; Thornton and Lin 1994; Wang and Quanche 1996; Yabiku 2004, 2006). Based on this evidence, we expect that those who marry at older ages will be more likely to use contraception to terminate childbearing when their family size goal has been met. Longer marital durations provide more exposure to the risk of childbearing no matter what the family size goal, so we expect longer marital durations to increase rates of contraception. A second potentially important dimension of marital processes is marital arrangement. Theories of family and demographic transition suggest that a shift from familially-arranged marriage to participation in spouse choice can bring about a fundamental change in family dynamics and fertility (Caldwell 1982; Fox 1975; Goode 1970, 1982; Macfarlane 1976, 1986; Mitchell 1971; Rindfuss and Morgan 1983; Shorter 1975). The effect of this change on fertility may be quite different for the initiation of childbearing than for the termination of childbearing. Rindfuss and Morgan’s (1983) influential study of four Asian countries suggests that a shift from arranged marriage to participation in spouse choice dramatically increases coital frequencies early in marriage, leading to higher fertility. Previous studies have found similar evidence in Nepal (Ahearn 2004; Fricke and Teachman 1993). On the other hand, courtship-driven marriage, or arranged marriages that involve some courtship period, may be characterized by higher levels of husband-wife communication and cooperation than typically arranged marriages (Adams 2000; Blood 1967; Xiahoe and Whyte 1990). This may make couples more efficient at arriving at joint childbearing goals, obtaining contraception with the aim of meeting those goals, and using contraceptive methods consistently to achieve those goals. Again, given the context of new preferences for smaller families in Nepal, we expect individual participation in spouse choice to increase rates of contraception to terminate childbearing. A third important dimension of marital processes is marital cohabitation. Unlike settings such as the United States in which cohabitation often precedes marriage (Bumpass and Sweet 1989; Bumpass et al. 1991; Smock 2000; Thornton, Axinn, and Xie 2007), in a setting like Nepal with early age at marriage, cohabitation often begins later than marriage. Particularly in very young marriages, delayed cohabitation may delay exposure to sex and the risk of pregnancy independent of age at marriage, and those who are not co-residing will have little motivation to contracept (Basu 1993; Bloom and Reddy 1986; McCarthy 1982). Even at older ages, temporary labor migration that physically separates spouses also reduces exposure to sex and the motivation to use contraception to avoid pregnancies. For these reasons, we expect co-residing with a spouse to increase rates of contraception. A fourth key dimension of marital processes is childbearing. In the vast majority of settings marriage and childbearing are closely linked (Cherlin 1992; Thornton and Lin 1994; Thornton 2005), and regardless of family size goal, as the number of children ever born increases, the desire to limit fertility is expected to increase (Bulatao and Lee 1983; Easterlin and Crimmins 1985). In rural South Asia, the number of children ever born is known to be an especially strong predictor of the desire to terminate childbearing (Axinn and Yabiku 2001). Therefore, we expect more children ever born to increase rates of contraception. Variations in both marital cohabitation and childbearing happen after the marital event, so they may be considered mechanisms through which marital arrangement and marriage timing shape subsequent fertility limitation. Because of this, we model the effects of marital arrangement and marriage timing on subsequent contraception both with and without measures of marital cohabitation and childbearing in order to determine the extent to which those marital events shape subsequent contraception independent of variations in marital cohabitation and childbearing. This study uses data collected by the Chitwan Valley Family Study (CVFS) beginning in 1996. Data from the Chitwan Valley in rural Nepal provide a unique opportunity to test the theoretical framework outlined above. The data captured a unique time period characterized by dramatic changes in marital processes and behavior within the lifetimes of its residents, including dramatic increases in youth involvement in courtship in terms of participation in spouse selection and marriage timing (Axinn and Yabiku 2001; Ghimire et al. 2006; Mitchell 1971; Mitchell 2010; Yabiku 2004). The average age at first marriage increased from 13.5 years for those who married between 1950–1959, whereas those who married between 1980–1989 married at a mean age of 19 years (Ghimire 2003; Yabiku 2004). The proportion of individuals in each marriage cohort who participated in the choice of a spouse rose from virtually zero in the 1936–1945 marriage cohort to approximately 50% in the 1986–1995 marriage cohort (Ghimire et al. 2006). The patterns of contraception are even more dramatic in Chitwan. Among women born between 1942–1951, less than 5% used permanent methods of contraception before they reached age 25. However, among the women born between 1962–1971, more than 35% used those methods by age 25 (Axinn and Barber 2001). The CVFS selected a systematic probability sample of 171 neighborhoods in Western Chitwan and defined a neighborhood as a geographic cluster of five to fifteen households. Once a neighborhood was selected, all individuals aged 15–59 residing in the sampled neighborhood were interviewed. If any of the respondents had a spouse living elsewhere, that spouse was interviewed as well. A total of 5,271 individuals were interviewed with a 97% response rate. This study provides rich retrospective measurement of the occurrence and timing of individual life events, including marital events collected using a LHC and linked measures of the characteristics of those events using a structured questionnaire. The LHC method provides more accurate retrospective measurement of life events than alternative measurement techniques (Belli 1998; Freedman et al. 1988). Moreover, the LHC used in the CVFS was specifically designed to use local events to help respondents recall the timing of personal events and to allow respondents to report their recall of marital events in a manner most consistent with local practices (Axinn et al. 1999). For this study, we analyzed data gathered from 2,022 women1 in the CVFS who were between the ages of 15–59 in 1996, were ever married, and had not used permanent contraception prior to marriage. We limit the sample to married women because in this setting premarital sex is extremely rare, thus never-married women are extremely unlikely to use contraceptive methods (Acharya and Bennett 1981; Axinn 1992; Tuladhar 1987, 1989). ContraceptionOur main objective is to examine the influence of variation in marital processes on the transition from no contraception to widespread contraception to limit childbearing. Substantial ethnographic and survey research demonstrates that in the period of time we studied (up to 1996), Nepalese women use some reversible contraceptive methods (Norplant, Depo-Provera, and IUDs) to stop childbearing (Axinn 1992; Link 2011; Satayavada and Adamchak 2000; Sharan and Valente 2002; Stash 2005; Tuladhar 1987). For example, data from the CVFS reveal that 98.8% of the married women aged 25–54 who had at least one child and who had ever used any of these contraceptive methods said that they wanted no more children. Consequently, we consider sterilization, Norplant, Depo-Provera, and IUDs to be contraceptive methods used to stop childbearing in this setting at this time period. This specification has been used in previous studies that examines the influence of individual- and community-level factors on fertility limitation (Axinn and Barber 2001; Axinn and Yabiku 2001; Barber and Axinn 2004; Brauner-Otto et al. 2007; Link 2011). The key dependent variable is beginning use of any of the five contraceptive methods: (1) injectables (e.g. Depo-Provera), (2) IUDs, (3) Norplant, (4) husband sterilization, or (5) wife sterilization, measured annually by the LHC. Using information from the LHC interview, we operationalize the timing of the transition from never having used any of the permanent contraceptive methods to ever having used any of those methods, ignoring distinction among methods. We code a time-varying dichotomous variable: “0” for all the years the respondent did not use any of the five contraceptive methods, and “1” for the first year that a respondent uses any of these methods. The variable coded “1” was used to estimate the hazard of any contraception to terminate childbearing. As shown in Table 1, 44% of ever-married women used these contraceptive methods to limit childbearing in our study period. Definition, mean, standard deviation, minimum, and maximum values of measures used in the analysis of hazard of contraception among ever-married women aged 15–59 in 1996 from the Western Chitwan Valley of Nepal (N=2,022).
We also investigate the use of any contraceptive methods. This broader definition includes temporary methods often used to delay births such as condoms, spermicidal foam, or oral contraception pills. This definition also includes withdrawal to avoid pregnancy. We use this broad definition of contraception as a dependent variable to compare our results against the more narrow definition of contraceptive methods used to stop childbearing. Table 1 presents descriptive statistics for all measures used in these analyses. The distributions refer to the respondent’s last person-year contributed to the analysis; for women who used any contraceptive methods this is the first year they used the method, for women who did not use any contraceptive methods this is the final year of data collection. Marital experiencesAs discussed above, multiple dimensions of marital experiences may influence contraception. Below we describe the measurement of each of those theoretical dimensions.
Using the respondent’s complete history of living arrangements from the LHC we code marital cohabitation (living with husband) as a time-varying dichotomous variable: “1” if a woman was living with her husband for more than six months in a particular year and “0” if otherwise. Childbearing experienceUsing the complete history of the respondent’s childbearing experiences, we calculated a time-varying interval-level measure of number of children born. Non-family experiencesIn order to capture the multidimensional nature of non-family experiences, we focus on three non-family experiences: schooling, work, and media exposure. Because non-family experiences are likely to influence and be influenced by marital experiences, we limited our measures of non-family experiences to premarital experiences and describe the measurement of these experiences below.
Childhood community contextGuided by the mode of social organization framework (see Axinn and Yabiku 2001), we define childhood community context as childhood access to non-family services such as schools, modern health services, employment centers, markets, and bus services that are directly related to an individual’s daily social life. In 1996, individual interview respondents were asked a series of questions about whether there was a specific service within a one-hour walk from their place of residence at any time before age 12. From the responses to these questions, we constructed dichotomous variables for whether each of these specific non-family services existed within a one-hour walk from the place of the respondent’s residence at any time before age 12. Moreover, to avoid problems of multicollinearity, we sum these five variables to a scale with values ranging from 0 to 5. These measures of childhood context have been tested for external validity and reliability using a series of ethnographic and archival techniques (Axinn and Pearce 2006) and have been extensively used in previous research (Axinn and Yabiku 2001; Axinn and Barber 2001; Barber and Axinn 2004; Yabiku 2004, 2005).3 Parental experiencesThe intergenerational transmission literature suggests that there is a significant parental influence on child outcomes. Parental resources (both economic and human capital resources) during their children’s childhood are positively related to children’s psychological and behavioral outcomes later in life (Axinn et al. 1994; Bengtson 1975; Cooksey et al. 1997; Sewell et al. 1980). Because parental experiences may affect both children’s non-family experiences and their contraception, we controlled for a number of parental characteristics in our multivariate models. These include parents’ education, contraception, and mother’s total number of children. The measure of parental education comes from the response to the question: “Did your father ever go to school?” A positive response was coded as “1” and a negative response as “0.” The same question was asked regarding the mother’s education, and responses were coded in the same way. To create the measure of parental education we then summed these two measures, which resulted in a value ranging from 0 to 2, where “0” means neither parent went to school, “1” means either parent went to school, and “2” means both parents went to school. The measure of parents’ contraception comes from the response to the question, “Did your parents ever use any contraceptive methods before you were 12 years old?” We code positive responses as “1” and negative responses as “0.” The total number of mother’s children comes from the response to the question, “How many children did your mother have?” The responses to this question were then coded in numbers as an interval-level variable. Birth cohortPrevious studies suggest significant differences between birth cohorts both in terms of marital behaviors and contraception (Axinn and Yabiku 2001; Axinn and Barber 2001; Ghimire et al. 2006; Thornton et al. 1994). Compared to older cohorts, younger cohorts participate more in the choice of their spouses, marry at older ages, and use contraception (Axinn and Yabiku 2001; de Jong et al. 2006; Ghimire et al. 2006). Therefore, we include a control for the respondent’s birth cohort. Respondent’s birth cohort is coded in four categories: (1) cohort 1 born between 1972–1981, (2) cohort 2 born between 1962–1971, (3) cohort 3 born between 1952–1961, and (4) cohort 4 born between 1937–1951. We coded individuals as “1” if they were born in a given cohort and “0” if not, and treated the oldest cohort (cohort 4, born between 1937–1951) as the reference group in our analyses. EthnicityNepalese society consists of many ethnic and linguistic subgroups (Bista 1972; Dahal 1993; Gurung 1980, 1998). These subgroups differ in many respects that have important consequences for both marital experiences and childbearing behavior. Although ethnicity in Nepal is complex, scholars have often categorized ethnicity into five major groups for analytical purposes: Brahmin/Chhetri (high caste Hindus), Dalit (low caste Hindus), Hill Janajati (Hill Indigenous), Newar, and Terai Janajati (Terai Indigenous) (Axinn and Yabiku 2001; Blaikie et al. 1980). We adopted the same categories in this analysis (for details about ethnicity in Nepal see Bista 1972; Fricke 1986; Guneratne 1994; Gurung 1980; Macfarlane 1976). We coded individuals as “1” if they are members of a given ethnic category and “0” if not, and treated Brahmin/Chhetri as the reference group. Analytical strategyThe breadth of the CVFS data allows us to simultaneously estimate the effects of multiple dimensions of marital behavior on contraception to stop childbearing. First, we estimated a model with basic controls for premarital factors (such as respondent’s non-family experiences, childhood community context, and parental experiences), and marriage duration. Second, we estimated the total effects of marital processes—arrangement and timing— controlling for premarital factors. Note that in this second step we add marital arrangement and timing simultaneously because they occur simultaneously (Ghimire et al. 2006). Finally, we added the measures of two post-marital experiences—marital cohabitation and number of children born—both as time-varying measures in a single model. This third step adds two of the most powerful influences on childbearing behavior, both of which occur temporally and causally after marital arrangement and timing. We also consider multiple views of the life course after marriage. First, we investigate contraception at any time after marriage, focusing on the long-term consequences of marital processes. Second, we investigate contraception after marriage, but before the first birth (treating first births as a censoring event), focusing on contraception in the first birth interval. Third, we investigate contraception after the first birth (treating first birth as the start of the hazard), but before the second birth (treating second births as a censoring event), focusing on contraception in the second birth interval. Finally, we investigate contraception after the first and second births (two different options for starting the hazard, now ignoring subsequent births as censoring events), focusing on long-term consequences of marital processes again, but now after births rather than in total. These alternative views largely yield identical results, though contraception in the first birth interval is rare—we discuss in more detail below as relevant to the interpretation of our findings. We use event history methods to model the risk of adopting contraception methods. Because the data are precise to the year, we use discrete-time methods to estimate these models (Allison 1984; Petersen 1991). Person-years of exposure are the unit of analysis4. We limit our sample to consider women to be at risk of using permanent contraception as they start living with their husband after first marriage. To estimate the discrete-time hazard models, we use this logistic regression: ln(p1−p)=a+∑(βk)(Xk), where p is the yearly probability of using any contraception method, p/1-p is the odds of using any contraception method, a is a constant term, βk represents the effects parameters of the explanatory variables, and Xk represents the explanatory variables in the model. This approach to estimating the discrete-time hazard model is described in detail elsewhere (see Allison 1982, 1984; Petersen 1986, 1991). Our time-varying measures of marital cohabitation and number of children born are measured in the year prior to the current year of contraception. Because the individuals in our study are clustered with others living in the same community who all have the same community characteristics, we estimate these models taking this data structure into account. Specifically, we use the GLIMMIX macro for SAS. The results presented in the tables below have all been calculated using GLIMMIX and therefore properly specify the multilevel nature of the data. Estimating multilevel discrete-time hazard models depends upon assumptions about modeling, conditional independence, non-informative covariates, and coarsening at random (for a detailed discussion see Barber et al. 2000). In Models 1 – 4 of Table 2, we present estimates of the effects of marital processes— marital arrangement and timing on contraception to stop childbearing. We transformed the raw coefficients by exponentiating them. The coefficients we present are estimates of the multiplicative effects on the hazard of using contraception. A coefficient of 1.00 represents no effect, a coefficient greater than 1.00 represents a positive effect, and a coefficient less than 1.00 represents a negative effect. Because the frequency of events in any time interval is quite small, the odds of transition from never having used any of the contraception methods to using any method are similar to the rate of contraception (Axinn and Yabiku 2001; Brauner-Otto et al. 2007). We discuss our results in terms of rates. Multilevel discrete-time hazard model estimates of impact of marital arrangement and marriage timing on the hazard of first permanent contraception among ever-married women aged 15–59 in 1996 from the Western Chitwan Valley of Nepal (N=2,022).
In Model 1 of Table 2, we estimated a base model with a wide range of social and economic factors which may simultaneously shape marital arrangement, marriage timing, and contraception. These factors include respondent’s non-family experiences, childhood community context, parental experiences, birth cohort, and ethnicity. In general, we find the parameter estimates in our base model consistent with findings from previous studies of this setting5 (Axinn and Yabiku 2001; Axinn and Barber 2001; Barber and Axinn 2004; Brauner-Otto et al. 2007; Link 2011). Model 2 of Table 2 presents estimates of the effects of marital processes—arrangement and timing—on contraception. Because neither participation in spouse choice nor age at first marriage can be observed without the occurrence of the other, we added both measures simultaneously. We find both participation in spouse choice and age at first marriage have strong, statistically significant effects on the rate of permanent contraception independent of other factors in the model. In Row 1 of Model 2, we estimated the effect of participation in spouse choice. The odds multiplier of 1.28 suggests that those women who had some participation in their spouse choice use contraception to limit childbearing at rates 28% higher than women who did not participate in their spouse selection. In Row 2 of Model 2, we find that age at first marriage has a strong, positive statistically significant effect on the rate of using contraception to limit childbearing. The odds multiplier of 1.06 for age at first marriage means that a one-year increase in age at first marriage increases the rate of contraception by 6%. This means an age at first marriage that is five years later would increase the long-term hazard of contraception by 34%. Finally, these two strong, statistically significant effects of marriage are also independent, meaning that both the level of participation in spouse choice and the timing of marriage shape long-term contraception behaviors. These two dimensions of variation in marital processes also improve the overall model fit. We use a −2 log-likelihood ratio as a measure of model fit. This statistic increased from 172,664 to 172,845—an increase of 181 points with 2 degrees of freedom. This is a statistically significant and substantively important improvement in model fit. Similarly, the model deviance value decreased from 6681 to 6646—a decrease of 35 points with 2 degrees of freedom. Re-estimating Models 1 and 2 of Table 2 using any contraception rather than contraception to end childbearing produces similar results (not shown in tables). For example, when we switch to the hazard of any contraception for Model 2, the estimated effect for participation in spouse choice is 1.24 (a 24% increase in the hazard of contraception) and the estimated effect for age at first marriage is 1.08 (an 8% increase in the hazard of contraception for each year of age). Once again, both effects are statistically significant, substantively important, and independent. With this alternative specification model fit, statistics also demonstrate these two measures improve our overall model—an increase in the −2 log-likelihood of 181 for an increase of 2 degrees of freedom (also not shown in tables). Thus, both approaches to measuring contraception after marriage yield the same substantive conclusions—more involvement in spouse choice and older ages at first marriage both increase the use of contraception to avert births, and these two influences are independent of one another. In addition to contraception at any time after marriage, we also investigate contraception after marriage but before the first birth (treating first births as a censoring event), focusing on contraception in the first birth interval. In contrast to the results presented in Table 2, in the first birth interval, participation in spouse choice does not have any significant effect on contraception (not shown in tables). Next, we investigate contraception after the first birth (treating first birth as the start of the hazard), but before the second birth (treating second birth as a censoring event), focusing on contraception in the second birth interval. In the second birth interval, both participation in spouse choice and age at first marriage raise the hazards of contraception, and the effects are even larger than those presented in Table 2 (not shown in tables). Finally, we investigate contraception after the first and second births (two different options for starting the hazard, now ignoring subsequent births as censoring events), focusing on long-term consequences of marital processes again, but now after births rather than in total. These alternative views largely yield identical substantive results, with empirical estimates of the effects of participation in spouse choice and age at first marriage in the same direction as shown in Table 2, but somewhat smaller effects (not shown in tables). Though contraception to avert births in the first birth interval is rare, after the first birth interval the long-term consequences of participation in spouse choice and age at first marriage are similar to those presented in Table 2 in each of these later portions of the marital life course. We investigate the role of post-marital cohabitation and childbearing in two steps. Before we estimate our final model, we estimated a model of these post-marital experiences, without participation in spouse choice and age at first marriage. To accomplish this, we added time-varying measures of marital cohabitation and childbearing experience to Model 1. The results are presented in Model 3 of Table 2. We find that cohabitation with husband and number of children born both have a strong, statistically significant effect increasing the rate of using contraception to limit childbearing. The odds multiplier of 1.60 for cohabitation with husband means that women who live with their husband use contraception at rates 60% higher than those women who do not live with their husband. Likewise, the odds multiplier of 1.65 for number of children born means that having an additional child increases the rate of contraception by 65%. To get a sense of the magnitude of this effect, this means that a woman with four children is four and a half times more likely to use contraception to limit her future childbearing than a woman with one child. Thus, as expected, both of these post-marital dimensions of marital experiences have substantial consequences for contraception. In this setting, it is not at all surprising that both marital cohabitation and number of children born drive contraception to avoid births. The contribution of these two factors to model fit is substantial. Relative to Model 1, the Model 3 –2 log-likelihood ratio increased from 172,664 to 179,462—an increase of 6,798 points with 2 degrees of freedom. This substantial improvement in model fit is quite a bit larger than the overall contribution of participation in spouse choice and age at first marriage. Of course, both participation in spouse choice and age at marriage not only come first, they also shape the subsequent marital life course of these couples. In Model 4 of Table 2, we present estimates of the effects of both marital arrangement and marriage timing, now including marital cohabitation and childbearing in the models. As expected, the effects of both participation in spouse choice and age at first marriage are somewhat reduced as important indirect effects of these two dimensions of marriage shape contraception via marital cohabitation and childbearing. The reduction in the odds multiplier from 1.28 (Model 2) to 1.20 (Model 4) for participation in spouse choice suggests that a substantial portion, almost 29%, of the effect of participation in spouse choice works through the two post-marital experiences. Likewise, the reduction in the odds multiplier for age at first marriage from 1.06 (Model 2) to 1.03 (Model 4) again indicates that almost half of the effect of age at first marriage works through the two post-marital experiences. Also important, the remaining effects of variation in participation in spouse choice and age at first marriage are independent of the large effects of marital cohabitation and childbearing. This is somewhat surprising. Marital cohabitation and childbearing after marriage are more proximate to the decisions to use contraception than marital arrangement and timing, but clearly some portion of the total effects of marital arrangement and timing shape decisions to contracept through other mechanisms. These independent effects of marital arrangement and timing mean that these features of marital experiences have long-term implications for contraception to avert births in addition to the long-term consequences for marital cohabitation and childbearing. Relative to Model 3, the Model 4 −2 log-likelihood ratio increased from 179,462 to 179,539—an increase of 77 points with 2 degrees of freedom. This improvement in model fit is statistically significant with 2 degrees of freedom. The widespread erosion of familially-arranged marriage probably does have a significant independent influence on the widespread increase in the use of contraception to limit fertility, at least in settings like Nepal. Demographers have provided decades of evidence that this marital revolution shapes the timing of first births (Feyisetan and Bankole 1991; Fricke and Teachman 1993; Hong 2006; Rindfuss and Morgan 1983; Wang and Quanche 1996). But the measurement demands have limited what we know about the longer-term consequences of this marital revolution, so that until now we have had relatively little evidence about how the erosion of arranged marriage has affected the use of contraception. The unique evidence provided here uses a long-term South Asian panel study of couples, their families, and their communities to demonstrate the possibility of an independent influence of the transition away from arranged marriage on the use of contraception. A key issue is that the same set of community, family, and individual social changes that promote changes in marital processes are also expected to alter childbearing behavior, increasing contraception. Because the Chitwan Valley Family Study (CVFS) was specifically designed to investigate community, family, and individual influences on both marital processes and contraception, it provides an unusually rich set of measures of these factors corresponding to a portion of the life course before marriage. These rich measures include those presented in the tables here, as well as others examined over more than a decade of investigation with these data but not included here (Axinn and Barber 2001; Axinn and Yabiku 2001; Barber and Axinn 2004; Barber et al. 2002; Brauner-Otto et al. 2007; Ghimire et al. 2006; Link 2011; Yabiku 2004, 2005, 2006). Altogether, this set of measures is among the most comprehensive available for studying the influences of marital processes on fertility limiting behaviors. Another important aspect of this study is that it is impossible to observe marital arrangements without also observing the timing of marriage, but the timing of marriage is expected to influence contraception to limit childbearing through mechanisms that are independent of marital arrangement (Bongaarts 1978; Ghimire et al. 2006; Hong 2006; Suwal 2001; Thornton and Lin 1994; Wang and Quanche 1996). Fortunately, the CVFS measured both marital arrangement and marriage timing. Also fortunately, the rural Nepalese setting from which these data were collected included high variance in both dimensions of marriage, such that all combinations of arrangement and timing can be observed. Of course, there is no random assignment of individuals to marriage arrangements or ages, but given that such random assignment is not likely to ever be available to the social sciences, the measurement and design of the CVFS provides an unusually powerful tool for investigating this topic. The findings are simple to report: participation in spouse choice is associated with subsequent higher rates of contraception to limit childbearing, often many years later. This strong, statistically significant association is independent of many other key associations. First, older ages at marriage and longer marital durations are associated with higher rates of contraception, but these factors do not diminish the association with marital arrangement. Second, marital cohabitation and the number of children born both have exceptionally strong associations with use of permanent contraception, as expected in this setting. But even though these occur after marriage, and are therefore subsequent to the observation of marital arrangement, these strong associations do not diminish the association between participation in spouse choice and subsequent contraception either. Third, other known sources of variation in subsequent marital and childbearing behaviors, including premarital non-family experiences, childhood community context, parental experiences, birth cohort, and ethnicity also all shape contraception as expected, but do not remove the association of participation in spouse choice with subsequent childbearing behavior. The strong, statistically significant association between the decline in marital arrangement and the increase in marital contraception appears to be independent of other key factors. Though the findings are straightforward, their implications are wide ranging. First, documentation of this important relationship between marital arrangement and contraception means that other dimensions of marital processes may also be important both as predictors of fertility behavior and as mechanisms linking non-family changes to fertility behaviors. Detailed investigation demonstrates that the spread of education in schools and mass media both promote a transition away from arranged marriage (Ghimire et al. 2006; Thornton and Lin 1994). If greater participation in spouse choice promotes contraception, then it is quite likely that greater participation in spouse choice links education and media exposure to contraception (Axinn and Barber 2001; Barber and Axinn 2004). A wealth of previous research demonstrates that high levels of communication between husbands and wives increase contraception to limit childbearing (Beckman 1983; Hill et al. 1959; Link 2011; Sharan and Valente 2002). Communication between spouses may work like marital arrangement to connect other non-family factors to contraception via marital processes. Other marital processes may also work to shape fertility limitation behaviors. Both positive and negative dimensions of the emotional bond between husbands and wives are identified by fertility theory as potential influences on fertility limitation (Caldwell 1982). Empirical evidence suggests that premarital non-family experiences, especially education in Western-oriented schools, increase positive dimensions of this emotional bond and reduce criticisms and conflict (Hoelter et al. 2004). Potentially, many different dimensions of the marital relationship may influence contraception and act as mechanisms linking other non-family changes to fertility limitation. The potential for future research to investigate these possibilities is extremely high. The association between participation in spouse choice and contraception documented here also means high potential for future research on other long-term consequences of change or variation in marital processes. Beginning with Rindfuss and Morgan’s (1983) breakthrough study, demographic research on the revolution away from arranged marriage has focused on relatively short-term outcomes, such as first birth timing. Use of contraception to limit childbearing is a much longer-term outcome usually reserved for the very end of childbearing in a setting like rural Nepal (Axinn and Yabiku 2001). Other longer-term outcomes including divorce, labor force participation, migration, retirement, childrearing practices, health related behaviors, morbidity and mortality all deserve attention. The evidence presented here is consistent with the possibility that revolutionary changes in the processes of getting into marriage, such as the move away from arranged marriage and the transition toward older age at marriage, can be associated with other substantial long-term changes in demographic behaviors. This research was jointly supported by generous grants from the National Institute of Child Health and Human Development (R03HD055976, R01HD032912, and R24HD041028) and by a grant from the Fogarty International Center to the University of Michigan’s Population Studies Center. We thank Cathy Sun at the Population Studies Center for her assistance with creating analysis files, constructing measures and conducting analyses; the staff at the Institute for Social and Environmental Research - Nepal (ISER-N) for data collection; and the Western Chitwan Valley residents for their valuable contributions to this research. The authors alone remain responsible for any errors or omissions. Dr. Ghimire also serves as the Director of ISER-N. 1While the vast majority of research on fertility has focused on women only, a small and growing body of research conceptualizes childbearing behavior at the couple level (Axinn and Barber 2001; Thomson 1997). The empirical evidence from this work demonstrates that both husbands’ and wives’ characteristics have separate, independent effects on the couples’ fertility and contraception. Because wives’ characteristics maintain separate and independent effects, we follow the majority of the literature on childbearing transitions and focus on women only. 2Living together as husband/wife in Western culture may not necessarily be considered marriage. However, Hindu society places a very high value on female virginity, and in Nepal if a woman spends a night with a man and this is publicly known she becomes impure and is considered to be married to that man. Therefore, we use a very restrictive definition of marriage (Bennett 1983; Gray 1991, 1995; Majupuria and Majupuria 1989). 3This study made special investment in designing contextually appropriate measures of social change. Because Nepal as a whole, and the study area more specifically, had very few non-family services in the early period of its settlement history, the measure of access to childhood non-family services is measured within an hour of walking distance. Additionally, in a rural context like Nepal which has a rugged topography and almost no access to transportation services, the measure of access to non-family services in terms of time to walk to the service is more relevant than spatial distance. Therefore, access to non-family services is measured in time rather than distance. 4Although it may appear that the discrete-time method of creating multiple person-years for each individual inflates the sample size resulting in artificially deflated standard errors, this is not the case (Allison 1982, 1984; Petersen 1986, 1991). In fact, the estimated standard errors are consistent estimators of the true standard errors (Allison 1982). 5Although we parameterized marriage duration (the baseline hazard) in quadratic form, we also tested three other functional forms: a log function, a linear function, and a series of six-month increment dichotomous indicators. The results vary only slightly across these four alternative functional forms. Because it provided the strongest overall model fit, we chose the quadratic functional form. This form is also consistent with previously published discrete-time models of contraception from this study setting (Axinn and Yabiku 2001; Axinn and Barber 2001; Barber and Axinn 2004; Brauner-Otto et al. 2007).
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In a study of satisfied couples in arranged marriages was identified as the most important factor
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