Causation and Selection Perspectives on the Evolution of U.S. Marital Health Gaps

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Dmitry Tumin

Graduate Program in Sociology

The Ohio State University

2015

Dissertation Committee:

Professor Zhenchao Qian, Advisor

Professor Kristi Williams

Professor Hui Zheng ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! Copyrighted by

Dmitry Tumin

2015

! ! ! ! ! ! Abstract

Being married is associated with better health, but the reasons for this association are contested. The marital causation perspective argues that marriage protects health, and offers a rationale for promoting marriage to serve public health goals. The marital selection perspective counters that marital disparities in health are due to healthier people being more likely to marry. Recent changes in marital health disparities indicate that

Americans’ retreat from marriage is altering the way marriage relates to health. Yet, changes in marriage effects on health and health-based selection into marriage have not been studied. In this dissertation, I examine temporal changes in selection into marriage based on health characteristics, and in the protective marriage effect on general health.

These analyses reveal how marital disparities in health are changing during a time when marriage is becoming less common and increasingly concentrated among the socially advantaged. By considering change over time in relationships between marriage and health, this dissertation contributes to the literature investigating the role of health as cause and consequence of romantic relationships.

Marriage is tied to many facets of health, including health behaviors, health conditions or limitations, and overall health status. Not all aspects of health contribute equally to chances of marriage, or are equally affected by marital status. Accounting for this diversity in the links between marriage and health, this dissertation presents three

ii separate analyses of marital status and health factors: smoking history, disability status, and a measure of general health. In the case of lifetime smoking initiation and childhood- onset disability, disparities between the married and never married are increasing in a way consistent with growing selection on these health measures. Yet, in the case of general health, overall marital disparities and the estimated protective effect of marriage are declining in successive cohorts, suggesting that a weakening marriage effect is driving overall decline in health differences between the married and never married.

The general health of married and never married Americans has become more alike, and the decline in the causal effect of marriage appears to outweigh any increases in selection on the basis of health behaviors such as smoking, or health conditions captured by a measure of disability. Declining general health disparities between the married and never married call for reconsidering the theoretical relationship between marriage and health. Early work emphasized marriage as a determinant of health, but many of the social and economic benefits of marriage came into doubt as marriage became less common, and singlehood became less stigmatized. In the case of general health, the present findings suggest that the decline of protective marriage effects is essentially complete. Meanwhile, increases in marital selection on the basis of certain health characteristics point to circumstances where health stigma acts as a barrier to marriage. For people whose health behaviors or conditions are stigmatized in the marriage market, health may be considered as the determinant of marriage rather than its outcome in future work.

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Acknowledgments

I thank my advisor, Zhenchao Qian, for guiding my progress through the graduate program and my professionalization as a scholar. I thank the members of my dissertation committee, Kristi Williams and Hui Zheng, for their guidance and support. I have also benefited from the instruction and advice of Elizabeth Menaghan, who served on my

Masters thesis committee, and John Casterline, whose directorship of the Institute for

Population Research opened many opportunities for me in the field of population studies.

My research was enriched through collaborations with Daniel Lichter, Michael Nau, and

Siqi Han; and drew inspiration from department alumni, Beth Boettner, Adrianne Frech,

Rhiannon Kroeger, Jamie Lynch, Matthew Painter, and Jonathan Vespa. Lastly, I thank my family for their encouragement and understanding throughout the dissertation process.

Vita

2009 ...... B.A., Sociology and Economics,

University of Virginia

2011...... M.A., Sociology, The Ohio State University

Publications

Tumin, Dmitry, and Zhenchao Qian. Forthcoming. Unemployment and the transition from separation to divorce. Journal of Family Issues.

Lichter, Daniel T., Zhenchao Qian, and Dmitry Tumin. Forthcoming. Who do immigrants marry? Intermarriage and immigrant integration in the United States. Annals of the American Academy of Political and Social Science.

Zheng, Hui, and Dmitry Tumin. 2015. Variation in the effects of family background and birth region on adult obesity: Results of a prospective cohort study of a Great Depression-era American cohort. BMC Public Health, 15, 535.

Tumin, Dmitry, Siqi Han, and Zhenchao Qian. 2015. Meanings and measures of marital separation. Journal of Marriage and Family, 77, 313-323.

Zheng, Hui, Dmitry Tumin, and Zhenchao Qian. 2013. Obesity and mortality risk: New findings from BMI trajectories. American Journal of Epidemiology, 178, 1591- 1599.

Nau, Michael, and Dmitry Tumin. 2012. Wealth transfer receipt and later life wealth. Research in Social Stratification and Mobility, 30 (3), 233-245. v

Fields of Study

Major Field: Sociology

Table of Contents

Abstract ...... ii!

Acknowledgments ...... iv!

Vita ...... v!

List of Tables ...... viii!

List of Figures ...... x!

Chapter 1: Introduction ...... 1!

Chapter 2: Marital Status Disparities in Smoking, 1993-2012 ...... 10!

Chapter 3: Childhood-Onset Disability and Marital Status: Policy Effects and Period

Trends in the U.S., 1969-2013 ...... 44!

Chapter 4: Does Marriage Protect Health? A Birth Cohort Comparison...... 84!

Chapter 5: Conclusion ...... 119!

References ...... 125!

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List of Tables

Table 1. Weighted means or proportions of sociodemographic characteristics and smoking behavior among U.S. adults in the 1993-2012 BRFSS, by gender ...... 24!

Table 2. Results from a weighted multinomial logistic model regressing smoking status on marital status, survey year, and their interaction among men ...... 26!

Table 3. Results from a weighted multinomial logistic model regressing smoking status on marital status, survey year, and their interaction among women ...... 31!

Table 4. Results from weighted multinomial logistic regressions of smoking status on marital status, survey year, and their interaction, classifying cohabiters as never married

...... 36!

Table 5. Results from weighted multinomial logistic regressions of smoking status on marital status, survey year, and their interaction, classifying cohabiters as divorced ...... 37!

Table 6. Common conditions limiting activities among people with childhood-onset disabilities, 1977, 1994-1995, and 1997-2013 NHIS ...... 66!

Table 7. Logistic regression of ever marrying on survey year, disability laws, and covariates among young adults ...... 72!

Table 8. Logistic regression of spouse disability on survey year, disability laws, and covariates among young adults ...... 76!

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Table 9. Number of cases and observations in each combination of birth and marriage cohort, 1984-2011 PSID ...... 100!

Table 10. Descriptive statistics by birth cohort, 1984-2011 PSID ...... 102!

Table 11. Unstandardized coefficients from OLS, random effects and fixed effects regressions of respondent-rated health on marital status, by gender ...... 104!

Table 12. Unstandardized coefficients from OLS, random effects and fixed effects regressions of respondent-rated health on marital status interacted with birth cohort, by gender ...... 107!

Table 13. Unstandardized coefficients from fixed effects regressions of respondent-rated health on marital status interacted with birth cohort, by gender and race ...... 110!

Table 14. Unstandardized coefficients from fixed effects regressions of respondent-rated health on marital status interacted with birth cohort, by gender and educational attainment

...... 111!

List of Figures

Figure 1. Predicted probabilities of smoking status among men, by marital status and survey year ...... 29!

Figure 2. Predicted probabilities of smoking status among women, by marital status and survey year ...... 33!

Figure 3. Weighted proportions of young adults ages 18-35 with any disability and with a childhood-onset disability, 1969-2013 NHIS ...... 62!

Figure 4. Weighted proportions of young adults ages 18-23 with any disability and with a childhood-onset disability, 1969-2013 NHIS ...... 63!

Figure 5. Weighted proportion of young adults (ages 18-35) with disabilities who require help with one or more of five activities of daily living (ADLs), 1977-2013 NHIS ...... 64!

Figure 6. Weighted proportion of young adults (ages 18-35) who have ever married, by disability status, 1969-2013 NHIS ...... 68!

Figure 7. Smoothed trends of weighted proportions of married young adults (ages 18-35) with disabilities whose spouse is a person with disabilities, 1969-2013 NHIS ...... 70!

Figure 8. Odds ratios of having ever married associated with having a childhood-onset disability, before and after major disability rights legislation, 1969-2013 NHIS ...... 74!

Figure 9. Odds ratios of being married to a person with disabilities (among married adults) associated with having a childhood-onset disability, before and after major disability rights legislation, 1969-2013 NHIS ...... 77!

Chapter 1: Introduction

Historical change in the institution of marriage is a major theme in studies of the

American family. In the postwar years, each generation has found that their marriages were unlike the marriages of prior generations, and has puzzled over which way the institution of marriage would go (Cherlin 2010). Median age at first marriage has increased, a high divorce rate has become a permanent feature of the marital landscape, and marriage has been decoupled from the experience of a first union (being replaced in this role by cohabitation) and from the transition to parenthood (Qian 2013). Despite this evidence that marriage is changing, the sum of these changes remains controversial. In one narrative, marriage is declining, being replaced by cohabitation or simply by living alone for longer stretches of the life course (Waite and Gallagher 2000). In another narrative, marriage is being divided into stable (if delayed) marriages for the socially advantaged; and turbulent, often dysfunctional marriages for the rest, if they marry at all

(McLanahan 2004). In a third narrative, marriage is being reinvented—with marital norms, customs, and laws catching up to the growing diversity of American families

(Coontz 1992). So, for all the upheaval in specific indicators of marriage behavior, the implications of these changes remain unclear.

The evolution of marriage commands the attention of American society because of the great importance Americans place upon this institution. America cherishes marriage and Americans aspire to marry in ways that have few parallels in other Western countries (Cherlin 2010). In Europe, for example, a surge of cohabitation and a crisis of low fertility have led to policies encouraging childbearing and recognizing cohabitation as an alternative union form (Kiernan 2004; McDonald 2006). In the U.S., on the other hand, exhortations to marry and "marriage coaching" became objects of public policy as federal marriage promotion legislation was enacted in the early 2000s (Heath 2012;

Huston and Melz 2004). Surveys show that Americans continue to hold marriage in high esteem—even though they are increasingly tolerant of non-marital relationships; and a majority of American adolescents and young adults continue to express aspirations to marry (Thornton and Young-DeMarco 2001). Even members of a cohabiting couple, arguably already enjoying the benefits of an alternative to marriage, usually expect to marry their partners at some future point (Manning and Smock 2002). Clearly, marriage remains a major waypoint in the American life course, imbued with importance and regarded with respect (Cherlin 2010).

The importance of marriage to organizing American life is evident in the effects marriage has on individuals. Protective effects of marriage on people’s health and well- being are a key benefit ascribed to getting and staying married (Waite and Gallagher

2000). Marriage is associated with improved access to economic resources that can be used to protect health (Hughes and Waite 2009); social control exercised by one’s spouse to encourage healthy behavior (Umberson 1992); and greater access to social support that

2 can help married people cope with stress (Umberson and Montez 2010). Married people tend to live longer than single people (Liu 2009), tend to engage in fewer risky behaviors, such as drug use (Duncan, Wilkerson, and England 2006), and report better physical health compared to their single peers (Hughes and Waite 2009). These associations between marriage and better health have given new life to the folk wisdom that “marriage is good for you.” Indeed, evidence showing married people are healthier than their single peers has filtered through to policy debates and has been recruited in support of such disparate proposals as marriage promotion (Waite and Gallagher 2000) and the recognition of same-sex unions (King and Bartlett 2006). If marriage causes better health, the respective arguments go, then it is our collective responsibility to make these benefits available to as many people as possible, such as low-income couples who are unlikely to marry, or same-sex couples whose relationships have only recently been recognized by the state.

This invocation of the health benefits of marriage in policy debates assumes that the benefits of marriage are predictable—that the advantages of couples who have married in the past can be extrapolated to couples who will marry in the future (Huston and Melz 2004). Behind the scenes of political debate, however, the health benefits of marriage have come under academic scrutiny. For decades, careful scholarship has distinguished between marital protection—ways in which getting and staying married improve a person's health relative to remaining never married—and marital selection, or the tendency of people already in good health to get and stay married (Wood et al. 2007).

This distinction raises the question whether marriage itself improves health relative to

3 remaining never married, after controlling for social characteristics that predispose people to marry (Musick and Bumpass 2012). In the past two decades, increasingly sophisticated statistical techniques have been used to arrive at a consensus answer, a qualified yes. Adjusting for selection, marriage does appear to cause improvements in some measures of mental health, physical health, and health behaviors (Averett, Argys, and Sorkin 2012; Musick and Bumpass 2012; Wood et al. 2007). But, these improvements are qualified because not all health outcomes benefit from marriage

(Averett et al. 2012); not all people experience health benefits from marrying (Williams et al. 2011; Zheng and Thomas 2013); and any health benefits of marriage may fade away

(Musick and Bumpass 2012) or be undone by marital disruption (Dupre and Meadows

2007). Ultimately, the health effects of marriage are more complicated than the straightforward proposition that marriage improves all facets of health.

Even if the causal health effects of marriage are circumscribed, health disparities between the married and never married remain an important social fact. Such disparities reveal the roles of health status, health conditions, and health behaviors in determining who gets to marry and who marries whom (Banks, Kelly, and Smith 2014; Fu and

Goldman 1996; Meyler, Stimpson, and Peek 2007). Selection into marriage on the basis of health is likely positive—healthier people make for more attractive partners

(Chiapporri, Oreffice, and Quintana-Domeque 2012; Fu and Goldman 1996)—although some have identified a motive for adverse selection, whereby less-healthy people make greater efforts to marry in anticipation of the health benefits they would reap (Lillard and

Panis 1996). The corollary of positive selection, of course, is social exclusion: people

4 who are at some sort of health disadvantage may be less likely to marry, may face a more limited choice of partners, and may be at greater risk of divorce (Manning et al. 2010;

Teachman 2010). In this sense, the stigma attached to poor health carries over into the marriage market and ties the achievement of this important life event to an individual's health status.

Marriage may select for healthier people and may have some of its own benefits to people's health, but these conclusions rest on an understanding of marriage in a particular moment in time. Given the rapid upheavals in the institution of marriage during the postwar era, the marriages of the past may have related to health differently than the marriages of today (Liu and Umberson 2008). Historical change in the relationship between marriage and health has clear implications for debates over marriage policy. If marital benefits to health are a thing of the past, undone by the decline of marriage, then public health benefits of promoting marriage must be largely chimerical. On the other hand, if marital disparities in health have grown stronger along with marital disparities in socioeconomic status, health differences between the married and unmarried may become increasingly salient to health inequality as a whole. It is even possible that the growing diversity of American families has produced new relationship types—such as long-term cohabitations—which are just as beneficial to health as marriage was in the past, meaning policies that focus on marriage alone are too narrow in scope (Musick and Bumpass

2012).

Recent work on the links between marriage and health has found unmistakable evidence of historical changes in these associations, but no unifying pattern. Examining a

5 measure of self-rated general health, Liu and Umberson (2008) found convergence between married and never married men in the closing decades of the 20th century

(among women, by contrast, the married group did not have a self-rated health advantage even at the 1972 baseline). Although this finding suggests the health of the never married is holding stable or improving to match the health of the married, other outcomes, such as cardiovascular mortality and an index of instrumental activities of daily living, evince a growing disadvantage of the never married group across successive periods (Liu 2009;

Liu and Zhang 2013). And, comparing the divorced to the married, there is some evidence that the self-rated health advantage of the married group is increasing due to worsening health among the divorced (Liu and Umberson 2008), and potentially due to increasingly adverse health effects of divorce in more recent cohorts (Liu 2012). In short, there is tension between findings consistent with a declining salience of marital health disparities (e.g., the closing gap in self-rated health between married and never-married men) and findings consistent with robust or even increasing consequences of marriage for health inequality (e.g., growing disparities in self-rated health between the married and divorced).

Change in marital health disparities can include change in patterns of marital selection and change in the causal effects of marriage. It is important to distinguish between these two types of changes because they have different implications for our understanding of marriage in contemporary American society. Particularly, a weakening causal effect of marriage supports the "retreat from marriage" narrative, according to which marriage is losing its unique power to organize people's lives. If marriage is

6 becoming less beneficial compared to remaining never married, the wisdom of promoting marriage in cohorts now reaching marriageable age is thrown into question. Meanwhile, strengthening marital selection on the basis of health would reinforce the “diverging destinies” narrative, according to which marriage is becoming an exclusive capstone transition falling further out of reach for disadvantaged couples. A growing association between good health and the chances of marrying would give marriage further meaning as a signifier of health advantage, in the way that marriage has come to signify economic stability. In other words, it may be that people not only need to be economically secure enough to marry, but they may now need to be healthy enough to marry, too.

In this dissertation, I analyze historical changes in the relationship between marriage and health while emphasizing this distinction between changes in marital selection and changes in the causal effect of marriage. The relationship between marriage and each specific health outcome is clearly influenced by broad trends in the institution of marriage, but it must be understood in its own context, as it is shaped by unique social constraints, including policies, technological developments, and social trends. Moreover, to borrow an insight from fundamental cause theory (Phelan, Link, and Tehranifar 2010), a marital disparity in one health outcome may disappear only to be replaced by a marital disparity in another health outcome. Therefore, this dissertation is organized into three separate chapters, each using a different data set to focus on a different aspect of health in relation to marital status, and each containing a separate review of the pertinent literature to identify hypotheses about historical change in the links between marriage and that particular aspect of health.

The organization of the chapters is as follows. Chapter 2 examines period trends in the relationship between smoking behavior and marital status in an era of growing anti- smoking stigma. In this chapter, the contrast between marital selection and marital causation emerges when comparing having ever smoked to current smoking. As smoking initiation usually precedes the age at first marriage, marital differences in lifetime smoking initiation should reflect changes in patterns of selection more so than changes in marriage effects on smoking. Chapter 3 examines policy and period influences on the relationship between childhood-onset disability and marriage outcomes in adulthood. In this case, childhood-onset disabilities almost always emerge before the age at first marriage (if ever married), and are associated with greater risk of delaying or foregoing marriage. Although policies such as the Americans with Disabilities Act aimed to improve social integration of people with disabilities via increased access to participation in higher education and the labor force, this chapter tests whether such policies also had an eventual effect on improving chances of marriage among people with childhood-onset disabilities. Finally, Chapter 4 estimates the protective effect of marriage on general health, controlling for marital selection on all time-invariant characteristics, and tests how this effect differs across cohorts. This chapter illustrates how longitudinal data from multiple cohorts can be used to estimate whether marriage effects on health are truly diminishing after the consequences of selection are netted out. In the concluding Chapter

5, I gather the findings of each study to describe whether marriage is losing its protective effect on health, and whether good health is increasingly becoming a prerequisite for ever marrying.

By examining changes in marital selection on health characteristics and marriage effects on health, this dissertation contributes to the broader debate over the deinstitutionalization of marriage. Evidence of weakening health benefits from marriage would sharpen the critique of marriage as an outmoded institution with diminishing consequences for contemporary couples. Such evidence would put recent studies reporting negligible marital effects on health into a historical context where these effects have been weakening from cohort to cohort. Yet, evidence of resilient or growing selection into marriage on the basis of good health may signal a new role for marriage in society, notwithstanding any declines in the causal effects of marriage. In an era when marriage is held in high esteem, but fewer and fewer people actually marry, strengthening marital selection on health characteristics would mean that poor health early in the life course can disrupt young adults’ ideal relationship trajectory by reducing their chances of marriage and limiting their pool of potential partners. In this sense, health differences across marital status would increasingly signal a problem of social exclusion based on health status, rather than suggest a public health benefit attendant to marriage promotion.

Chapter 2: Marital Status Disparities in Smoking, 1993-2012

In the U.S., decreasing smoking initiation and increasing smoking cessation have been public policy goals since the 1964 Surgeon General’s Report on Smoking and

Health (Levy, Chaloupka, and Gitchell 2004). Anti-smoking policies are motivated by smoking’s association with increased risks for many diseases, including leading causes of death such as heart disease and lung cancer (Himes 2011; Tsai et al. 2010). In the late

1990s, anti-smoking policies adopted a strategy of “denormalization,” portraying smoking as irresponsible and immoral (Bayer and Stuber 2006; Bell et al. 2010a).

Policies treating tobacco use as a form of deviance were bolstered by the 1998 Tobacco

Master Settlement Agreement, which provided a new source of funds for a variety of anti-smoking initiatives (Schroeder 2004). Such policies, including a series of bans on smoking in public places, were widely adopted by many municipalities and the majority of U.S. states around the turn of the millennium (Farrelly et al. 2013). During this time, mass media have also come to portray smoking as unhealthy and deviant (Bell et al.

2010a; Cohen, Shumate, and Gold 2007).

From a public health perspective, the denormalization campaign against tobacco use is vindicated by continuing decreases in the prevalence of smoking among U.S. adults (Garrett et al. 2011). Yet, sociological critiques of smoking denormalization have

10 emphasized its tendency to stigmatize and marginalize smokers (Bell et al. 2010b;

Castro-Santos 2009; Stuber, Galea, and Link 2008, 2009). The stigmatization of smokers, in turn, contributes to widening social disparities in smoking behavior, as smokers withdraw from social activities and experience discrimination on the basis of their smoking behavior (Bell et al. 2010a; Graham 2012; Stuber et al. 2009). Such marginalization of smokers may extend to the marriage market. Smokers face worse prospects of marriage and a more limited choice of partners (Chiappori et al. 2012).

Smokers married to non-smokers also face pressure to quit, which may strain their relationship (Bottorff et al. 2006; Greaves et al. 2010). This marginalization of smokers in the arena of marriage may increase marital disparities in smoking behavior.

Smoking is less common among married adults than among never married, formerly married, or cohabiting adults (Averett et al. 2012; Green et al. 2012, Reczek,

Liu, and Brown 2014; Schoenborn 2004). This difference arises because non-smokers are more likely to marry (Ask et al. 2012); because some smokers who marry reduce their cigarette use (Merline et al. 2008); because leaving a marriage causes some former smokers to relapse (Japuntich et al. 2011); and because married adults differ from unmarried adults in other characteristics, such as higher educational attainment, which are correlated with low rates of smoking (Schoenborn 2004). Although smoking disparities between married and unmarried adults are well documented, it is unknown how these disparities have changed in response to the declining prevalence and increasing stigmatization of smoking. Increasing stigmatization of smoking may be intensifying selection of nonsmokers into marriage, and may also bolster the social control exerted by

11 non-smoking adults who want their smoking spouses to quit. Either development would contribute to an especially rapid decline in smoking among married adults, compared to a slower decline in smoking among unmarried adults. In this paper, I explore how marital disparities in smoking have changed in an era of growing stigma, and, particularly, if there is evidence for intensifying selection of non-smokers into marriage. Given the importance of smoking as a risk factor for later-life morbidity and mortality, I discuss how these findings relate to trends in health and mortality disparities between married and unmarried adults.

Marital Disparities in Smoking

Smoking is less common among married adults than single adults (Schoenborn

2004). Furthermore, among adults in romantic relationships, smoking is less common among those who are married than those who are cohabiting (Reczek et al. 2014). Marital selection is an important reason for these disparities. Smoking is perceived to be an undesirable characteristic on the marriage market (Manning et al. 2010), and is subject to assortative mating, such that smokers disproportionately marry other smokers (Ask et al.

2012, Banks et al. 2014). The decline of smoking prevalence in the overall population means that smokers’ tendency to marry other smokers restricts their pool of likely mates.

In addition, marriage selects for socioeconomic characteristics that are correlated with smoking. For example, smoking is correlated with low socioeconomic status (Garrett et al. 2011), which, in turn, predicts lower chances of marriage (Shafer and James 2013).

The concentration of smoking among socioeconomically disadvantaged individuals means that preferences for non-smoking partners may dovetail with preferences for well-

12 educated or economically stable partners. Therefore, the rapid retreat from marriage among people with low socioeconomic status (Harknett and Kuperberg 2011), who are more likely to smoke, may have a side effect of widening smoking disparities between people who marry and people who do not. In other words, selection may lead to a greater smoking disparity between the married and unmarried because of the composition of the married group changing to include more socioeconomically advantaged people who are least likely to smoke.

In addition to selection mechanisms, marital disparities in smoking may also arise from causal influences of marriage and divorce (or widowhood) (Japuntich et al. 2011).

Marriage is accompanied by a set of social norms that shape health behaviors, including the norms of behaving responsibly and avoiding risk, which are violated by the smoking spouse (Duncan et al. 2006). Furthermore, the direct monitoring and control of their spouse may pressure married smokers to quit or reduce smoking (Umberson, Crosnoe, and Reczek 2010). Consistent with this theory, some studies find that getting married leads to smoking cessation or a decline in the number of cigarettes smoked (Merline et al.

2008; Weden and Kimbro 2007). When a marriage ends, on the other hand, withdrawal of this social control and the stress of marital dissolution may lead to smoking being used as a coping mechanism (Carr and Umberson 2013; Japuntich et al. 2011). Indeed, women who divorced or widowed experienced double the odds of starting or relapsing into smoking than women who remained married over a period of four years (Lee et al. 2005).

These causal explanations, however, are predicated on some baseline level of smoking prior to marriage: potentially, as the married group includes fewer and fewer lifetime

13 smokers, there would be fewer married adults to quit smoking while married, or to relapse into smoking (rather than initiate smoking for the first time) after having been divorced or widowed.

The balance between selection and causation mechanisms contributing to marital disparities in smoking likely varies depending on how smoking behavior is measured.

Marital disparities in smoking initiation (i.e., having ever smoked) should be primarily if not exclusively driven by selection mechanisms. In recent years, the median age at first marriage has been in the mid-20s (Cherlin 2010), whereas the median age of smoking initiation has been below 18 years (National Cancer Institute 2012). Therefore, most smokers have their first experience with regular smoking well before they marry, and their marriage could not have retroactively caused their smoking initiation (Banks et al.

2014; Waldron and Lye 1989). A study following 468 newlywed couples found only 3 first-time smoking initiators (0.3% of spouses) in the first two years of marriage, compared to 280 people (29.9% of spouses) who reported smoking at the time they were married (Homish and Leonard 2005). By contrast, current smoking status among people who have ever smoked should be more sensitive to causal effects of marital status.

Marriage may discourage current smoking by pressuring smokers to quit (Merline et al.

2008; Weden and Kimbro 2007), and being divorced or widowed may encourage smoking continuation or relapse as a coping mechanism (Japuntich et al. 2011). Thus, differentiating between disparities in lifetime smoking initiation and disparities in current smoking status is an initial step in distinguishing between selection and causation as reasons for changing marital disparities in smoking behavior.

Smoking Disparities in a Period of Growing Stigma

Mass media campaigns seeking to “denormalize” smoking behavior and smoking bans excluding smokers from public places have contributed to the stigmatization of smokers in recent decades (Stuber et al. 2008, 2009). The strengthening of this stigma may exacerbate marital disparities in smoking in several ways. First, increasing stigmatization of smokers may imply increased selection of non-smokers into marriage.

Whereas research in the 1990s found smoking did not decrease the odds of marriage

(Chassin et al. 1992; Fu and Goldman 1996), recent studies have argued that smoking is a handicap in the marriage market (Chiappori et al. 2012; Manning et al. 2010). Thus, the rise of anti-smoking stigma may have changed marital selection mechanisms such that smokers have become less likely to marry. Intensified marital selection on characteristics predicting smoking behavior, such as educational attainment, may have similarly made smokers less likely to marry not necessarily because of their smoking history itself, but rather because of other attributes (e.g., low educational attainment) that increase chances of smoking but decrease chances of marriage.

The stigmatization of smoking may have also changed the effects of marital status on smoking behavior. Smoking is considered to violate the norm of responsible and healthy behavior in marriage (Duncan et al. 2006). The growing stigmatization of smoking may have caused such violation to be taken more seriously. Indeed, married smokers report a strong internal conflict between their smoking behavior and their ideal role in their family (Bottorff et al. 2006; Greaves et al. 2010). The stigmatization of smoking may have also caused non-smoking spouses of smokers to redouble their efforts

15 to get their partners to quit. Despite the addictive nature of tobacco use (Duncan et al.

2006) and resistance to smoking cessation among dual-smoker couples (Lipkus et al.

2013), spouses’ social control may have become more effective at encouraging married smokers to quit, as it draws on increasingly popular ideas about the undesirability of smoking and smokers. Thus, protective effects of marriage may have been reinforced by the growth of anti-smoking stigma. Of course, the protective effects of marriage only affect married adults who have ever smoked. Intensified selection of never-smokers into marriage may potentially mean that marital benefits to smoking cessation—however potent—would apply to a narrower and narrower slice of the married group.

Historical trends in the prevalence of smoking and attitudes toward smoking suggest evolution in both marital selection on smoking history and marital influences on present smoking. Yet, the selection and causal pathways linking smoking to marriage are gendered, potentially implying gender differences in the historical evolution of these pathways. Anti-smoking stigma underpinning the selection mechanism has been more salient for women than for men. The stigmatization of women’s smoking is well- established (Nichter et al. 2006), whereas among men, this behavior has in the past been met with greater tolerance (Greaves et al. 2010). Meanwhile, women have been more likely than men to exercise the kind of social control over a spouse’s health behaviors that is implied in the marital effect on smoking cessation (Umberson 1992). Yet, the rising tide of anti-smoking stigma may have evened out past gender differences in attitudes towards potential partners’ or current spouses’ smoking. This development

16 would suggest convergence between men’s and women’s experiences of marital selection on smoking history, or marital influences on current smoking.

Current Study

Smoking has become increasingly stigmatized in recent decades. Although this has contributed to an overall trend of reduced smoking prevalence, the stigmatization of smoking has also meant that new social disparities in smoking behavior have emerged, such as the concentration of smoking among people with low educational attainment

(Escobedo and Peddicord 1996). The stigmatization of smoking may have similarly amplified marital disparities in smoking behavior, with smoking becoming a liability on the marriage market. In this study, I test whether marital disparities in smoking have widened over the years 1993-2012, such that smoking has decreased most rapidly among married adults, and less rapidly among unmarried adults. I expect that marital selection on smoking behavior has increased, leading to widening marital disparities in lifetime smoking initiation. Specifically, I hypothesize that fewer married adults have ever smoked than unmarried adults, and that this difference has increased over time.

Furthermore, I anticipate that growing anti-smoking stigma may have strengthened the effect of spousal encouragement to quit smoking. Whereas the denormalization of smoking exposes all smokers to the norm that smoking is undesirable, among married smokers this norm dovetails with the belief that smoking violates the norm of responsible behavior in marriage. This confluence of anti-smoking norms affecting married smokers means that non-smoking spouses may be more likely to try to get their smoking partners

17 to quit, or may be more successful in doing so. Therefore, I hypothesize that the prevalence of current smoking is lower among married adults than unmarried adults, and that this difference has increased over time.

Data and Methods

Data

I use data from the Behavioral Risk Factor Surveillance System (BRFSS). The

BRFSS is a yearly cross-sectional telephone survey administered by each U.S. state and supervised by the Centers for Disease Control and Prevention. In comparison to the longer-running National Health Interview Survey series, the BRFSS interviews a larger number of respondents each year, representing a much larger number of households, and obtains similar prevalence estimates of risk factors such as cigarette smoking (Nelson et al. 2003). This makes the BRFSS the largest U.S. survey data set available to study marital disparities in smoking behavior in recent decades, a period characterized by campaigns to denormalize and stigmatize smoking. The BRFSS sampled only landline telephone users until 2010, and both landline and cellphone users thereafter. The first

BRFSS surveys were fielded in the 1980s, but states’ staggered entry into the BRFSS meant the survey did not gain a national scope until 1993 (CDC 2013). I analyze data from the years 1993-2012 collected from all 50 states and the District of Columbia. The combined sample originally included 5,381,998 adult respondents age 18 or older. Forty- eight states were surveyed continuously over this period, accounting for 96% of respondents, whereas Hawaii, Rhode Island, and the District of Columbia were surveyed discontinuously, but with no more than 2 years of data missing in each case. I restrict the

18 sample to 5,160,629 adults who have complete data on marital status, age, educational attainment, race and ethnicity, and smoking. At later ages, the prevalence of current smoking declines rapidly among all marital groups, obscuring differences in smoking behavior that may have been apparent earlier in the life course (Schoenborn 2004;

Schoenborn, Vickerie, and Powell-Griner 2006). Therefore, I restrict the sample further to 3,880,495 adults ages 18-65. I analyze the data using survey weights to adjust for the stratified sampling design of the BRFSS (Mokdad, Stroup, and Giles 2003).

Smoking Behavior

Measures of smoking in the BRFSS are self-reported and encompass both past smoking and current smoking behaviors. Respondents in each year are asked if they have ever smoked 100 cigarettes in their lifetime. Those who answer yes to this question are asked whether they currently smoke (Arday et al. 1997; Tsai et al. 2010). Self-reported current smoking status correlates well with biomarkers of exposure to smoking, with no evident differences in misreporting of smoking behavior across marital status (Vartiainen et al. 2002). I create a categorical measure of smoking behavior, distinguishing among never smokers (respondents who did not smoke 100 cigarettes in their lifetime); former smokers (have smoked 100 cigarettes in their lifetime, but are not currently smoking); and current smokers. The contrast between ever smoking (i.e., current smoking or former smoking) and never smoking reflects selection into marriage on the basis of lifetime smoking behavior, although, as discussed in more detail below, it may also reflect a few cases in which people initiate smoking for the first time after marriage. The contrast

19 between current smoking and former smoking reflects causal effects of marital status

(i.e., marriage causing smoking cessation and divorce causing smoking relapse).

However, limited data on marital history and timing of smoking initiation and cessation preclude a strictly causal interpretation of findings for this contrast. Because of this limitation, the results and intrepretation focus on the first contrast—ever smoking as opposed to never smoking—which plausibly represents selection into marriage on the basis of smoking or its sociodemographic predictors. Nevertheless, by retaining a distinction between current smokers and former smokers, the three-fold operationalization of smoking behavior parsimoniously addresses the hypotheses that married adults are becoming increasingly unlikely to have ever smoked (as opposed to being current or former smokers), relative to other groups; and that married adults are becoming increasingly unlikely to currently smoke (as opposed to being former smokers), relative to other groups.

Marital Status and Sociodemographic Covariates

I compare the prevalence of ever smoking and current smoking across the following marital status categories: never married; currently married; divorced or separated; widowed; and cohabiting (“member of an unmarried couple” in the original question text, without further information on the respondent’s partner’s gender). The

BRFSS does not collect marital history data, meaning that the legal marital status of cohabiters is unknown. Due to the ambiguity of cohabiters’ marital status in these data

(never married vs. formerly married), I do not focus on this group in discussing the main

20 results, but report sensitivity analyses in which cohabiters are combined with either never married or divorced respondents, respectively.

To distinguish marital disparities in smoking from smoking disparities across other sociodemographic factors, I include control variables identifying the age, race and ethnicity, and educational composition of respondents. I code race as non-Hispanic

White, non-Hispanic Black, Hispanic, Asian or Pacific Islander, Native American, or other (including multiracial). I code educational attainment as not attending school or completing elementary school only; completing some high school; completing high school or a graduation equivalency degree (GED); completing some college or a technical school; or completing four years of college.

Analytic Strategy

I model linear period trends in ever smoking and current smoking for each marital status group from 1993 until 2012, stratified by gender and adjusted for any concurrent changes in sociodemographic characteristics. By testing for a difference in the slopes of the linear trends across each pair of marital status groups, I examine whether the corresponding disparity in smoking has diverged or converged. I use multinomial logistic regression to model smoking status as a function of respondent marital status, respondent sociodemographic characteristics, survey year, and interactions between each marital status variable and survey year. As smoking behavior may vary curvilinearly with age, I include both linear and quadratic age variables. Survey year is treated as a continuous variable, and is centered at 1993, the first year covered by the data. Beginning in 2011, the introduction of cellphone sampling to the BRFSS may have increased the estimated

21 prevalence of smoking by improving coverage of people who are more likely to smoke, such as people living in poverty or people with low levels of educational attainment

(CDC 2012). To correct for a possible increase in smoking prevalence attributable to the introduction of the cellphone sample, I add a binary variable that equals 1 if the survey year is greater than 2010, and 0 otherwise.

Results

In Table 1, I present weighted proportions describing smoking prevalence and sociodemographic composition in 1993 and 2012 among men and women ages 18-65 who were surveyed by the BRFSS in those years. Over this period, the prevalence of ever smoking declined by about 6% among both men and women. Among ever smokers, the prevalence of current smoking increased by 1% among men and decreased by 3% among women. These changes are consistent with the long-term decrease in smoking prevalence

(Garrett et al. 2011); and with the finding that the declining prevalence of current smoking is primarily driven by lower initiation rates rather than higher cessation rates

(National Cancer Institute 2012). The downward trend in smoking prevalence is also consistent with the success of local and state laws enacted over this period to discourage smoking (Farrelly et al. 2013).

Meanwhile, the sociodemographic characteristics of the 1993 and 2012 samples reveal a substantial retreat from marriage. The proportion of adults who had never married increased by 7% among men and 8% among women, and the proportion of adults who were currently married fell by 14% among men and 12% among women.

Respondents in the 2012 sample were also more likely to be divorced, widowed, or

22 cohabiting than respondents in the 1993 sample. Other sociodemographic trends include a slight increase in the mean age; a decline in the proportion of non-Hispanic White adults; and increases in the proportions of non-Hispanic Black, Hispanic, and Asian/Pacific

Islander adults. Educational attainment above the high school level remained roughly constant among men, but increased from 54% to 62% among women.

Table 1. Weighted means or proportions of sociodemographic characteristics and smoking behavior among U.S. adults in the 1993-2012 BRFSS, by gender

Men Women 1993 2012 1993 2012 (n = 35,542) (n = 129,585) (n = 45,029) (n = 175,845)

b (SE) B (SE) b (SE) b (SE) Marital status Married 0.629 (0.004) 0.492 (0.006) 0.636 (0.004) 0.520 (0.005) Never married 0.260 (0.004) 0.333 (0.005) 0.195 (0.003) 0.276 (0.005) Divorced 0.074 (0.002) 0.101 (0.002) 0.105 (0.002) 0.114 (0.001) Widowed 0.009 (0.001) 0.011 (0.001) 0.038 (0.001) 0.033 (0.001) Cohabiting 0.028 (0.001) 0.062 (0.002) 0.026 (0.001) 0.057 (0.002) Age 38.12 (0.110) 40.72 (0.210) 38.78 (0.097) 41.34 (0.220) Race/ethnicity Non-Hispanic White 0.789 (0.004) 0.638 (0.006) 0.787 (0.003) 0.631 (0.006) Non-Hispanic Black 0.082 (0.002) 0.113 (0.003) 0.094 (0.002) 0.127 (0.003) Hispanic 0.087 (0.003) 0.167 (0.005) 0.083 (0.003) 0.161 (0.004) Asian/Pacific Islander 0.026 (0.001) 0.051 (0.002) 0.023 (0.001) 0.051 (0.002) Native American 0.008 (0.001) 0.011 (0.001) 0.008 (0.001) 0.010 (0.001) All others 0.008 (0.001) 0.021 (0.001) 0.006 (0.001) 0.020 (0.001) Educational attainment Elementary or less 0.035 (0.002) 0.042 (0.002) 0.031 (0.001) 0.039 (0.002) Some high school 0.008 (0.002) 0.106 (0.003) 0.079 (0.002) 0.086 (0.002) High school only 0.322 (0.004) 0.298 (0.003) 0.355 (0.003) 0.259 (0.002) Some college 0.267 (0.004) 0.294 (0.003) 0.291 (0.003) 0.338 (0.003) Four-year college 0.298 (0.004) 0.260 (0.004) 0.244 (0.003) 0.279 (0.004) Smoking behavior Ever smoked 0.523 (0.004) 0.468 (0.003) 0.428 (0.004) 0.366 (0.003) Currently smokinga 0.483 (0.005) 0.494 (0.005) 0.529 (0.005) 0.498 (0.005) a Among respondents who have ever smoked.

The descriptive results show that the trend in smoking among married adults is situated in a context where both smoking and marriage are becoming less common. To test whether marital disparities in smoking have significantly changed over the period

1993-2012, I fit regression models in which marital status categories are interacted with survey year, centered in 1993. Results from a multinomial logistic regression model fitted to the men’s subsample are presented in Table 2, with separate columns showing the relative risks of former smoking vs. never smoking; current smoking vs. never smoking; and current smoking vs. former smoking. The main effect of survey year represents the linear trend across survey years for married men. Both current smoking and former smoking have become less prevalent among married men, with the relative risk of being a former smoker (vs. never smoking) falling by 2.5% each year (RRR = 0.975, p < .001) and their relative risk of being a current smoker (vs. never smoking) falling by 2.6% each year (RRR = 0.974, p < .001). On the other hand, married men’s risk of current smoking relative to former smoking did not significantly change across survey year (RRR = 0.999, p > .05). Thus, the smoking decline among married men over the years 1993-2012 can be attributed only to lower lifetime smoking initiation and not to increasing odds of smoking cessation.

Table 2. Results from a weighted multinomial logistic model regressing smoking status on marital status, survey year, and their interaction among mena

Former smoker Current smoker Current smoker vs. never smoked vs. never smoked vs. former smoker RRR SE RRR SE RRR SE Marital status Married ref. ref. ref. Never married 0.727*** 0.018 1.151*** 0.024 1.582*** 0.043 Divorced 1.138*** 0.031 2.123*** 0.054 1.865*** 0.050 Widowed 1.038 0.084 1.660*** 0.136 1.599*** 0.113 Cohabiting 1.104 0.070 1.960*** 0.103 1.775*** 0.103 Survey yearb 0.975*** 0.001 0.974*** 0.001 0.999 0.001 Survey year interactions Never married 1.003 0.002 1.023*** 0.002 1.020*** 0.002 Divorced 1.000 0.002 1.013*** 0.002 1.013*** 0.002 Widowed 1.004 0.006 1.027*** 0.006 1.023*** 0.006 Cohabiting 1.015** 0.005 1.016*** 0.004 1.000 0.005 Survey year > 2010 1.079*** 0.014 0.919*** 0.014 0.851*** 0.013 Age 1.065*** 0.002 1.097*** 0.002 1.030*** 0.003 Age squared 0.999*** 0.0003 0.991*** 0.0003 0.992*** 0.0003 Race/ethnicity Non-Hispanic White ref. ref. ref. Non-Hispanic Black 0.535*** 0.008 0.682*** 0.009 1.276*** 0.021 Hispanic 0.795*** 0.013 0.564*** 0.009 0.710*** 0.013 Asian/Pacific Islander 0.734*** 0.020 0.751*** 0.023 1.024 0.036 Native American 1.143*** 0.042 1.531*** 0.054 1.340*** 0.050 All others 1.020 0.030 1.262*** 0.035 1.238*** 0.039 Educational attainment Elementary or less ref. ref. ref. Some high school 1.336*** 0.043 1.727*** 0.051 1.293*** 0.040 High school only 0.995 0.028 0.887*** 0.023 0.892*** 0.025 Some college 0.886*** 0.025 0.583*** 0.016 0.658*** 0.019 Four-year college 0.540*** 0.015 0.212*** 0.006 0.392*** 0.011 a N = 1,584,300. A single multinomial logistic regression model was fitted, with relative risk ratios shown separately for each pairwise comparison of the three smoking categories. b Centered at 1993. * p < .05; ** p < .01; *** p < .001, two-tailed tests.

The main effects of marital status represent marital disparities as they existed in

1993. For example, in 1993, the relative risk of current smoking, compared to never smoking, was lowest among married men, and higher among never married, divorced, widowed, or cohabiting men. Yet, the relative risk of being a former smoker, compared to never smoking, was higher among married men than among never married men. This suggests that, in 1993, more married men than never married men had ever smoked, but, among men who had ever smoked, the chances of being current smoker were lowest in the married group—consistent with the expectation that marriage contributes to smoking cessation. The interaction terms between marital status and survey year indicate how these marital disparities in smoking behavior changed between 1993 and 2012. For example, the interaction term between year and being never married in the model of current smoking compared to never smoking (RRR = 1.023, p < .001) suggests that trends in current smoking are significantly different between married and never married men. Each year, the risk of current smoking compared to having never smoked decreased by 2.6% among married men (RRR = 0.974, p < .001) but by only 0.4% among never married men (RRR = 0.974 * 1.023 = 0.996, p < .05). Likewise, the risk of current smoking compared to never smoking decreased faster among married men than among divorced, widowed, or cohabiting men. These findings show that married men were not only least likely to be current smokers in 1993, but they also experienced the greatest decline in smoking initiation out of all marital status groups between 1993 and 2012, net of changes in age, racial/ethnic, or educational composition.

Figure 1 illustrates how men’s predicted probabilities of never smoking, former smoking, and current smoking changed across survey years, stratified by marital status.

The predicted probabilities in this Figure are based on the model presented in Table 2.

Figure 1 reveals that, among men, there is a general increase in the share of those who never smoked, and this increase is especially steep among married men. Lifetime smoking initiation became increasingly rare among married men, consistent with the hypothesis that marriage is increasingly selecting for non-smokers. Whereas smoking initiation has declined, there appears to be no evidence of improved smoking cessation rates among men in any marital category. Among married men, the breakdown of ever smokers into current and former smokers is stable between the years 1993 and 2012; whereas among never married, divorced, and widowed men, current smokers have increasingly displaced former smokers during this time. These results are consistent with a persistent pattern of men quitting smoking either during marriage or in anticipation of marriage, but they do not evince any change in this pattern. Furthermore, these results reveal a surprising increase in smoking continuation or relapse among single men who have ever smoked. It is unclear if this increase is due to persistent smokers being increasingly left out of the marriage market, or if, conversely, prolonged singlehood has increasingly caused men to continue smoking.

Married Men Never Married Men 1 1

.8 .8

.6 .6

Probability .4 Probability .4

.2 .2

0 0 1995 2000 2005 2010 1995 2000 2005 2010 Year Year

Divorced Men Widowed Men 1 1

.8 .8

.6 .6

Probability .4 Probability .4

.2 .2

0 0 1995 2000 2005 2010 1995 2000 2005 2010 Year Year

Never smoked Former smoker Current smoker

Figure 1. Predicted probabilities of smoking status among men, by marital status and survey year

Table 3 presents a multinomial logistic regression model fitted to the subsample of women. In 1993, married women were less likely to currently smoke (compared to never smoking) than never married, divorced, widowed, or cohabiting women. Married women’s risk of current smoking, compared to never smoking, decreased by 1.1% each year (RRR = 0.989. p < .001). The risk of current smoking relative to never smoking remained stable among divorced women (RRR = 0.989 * 1.009 = 0.998, p > 0.05), and increased among widowed women (RRR = 0.989 * 1.025 = 1.014, p < .001). Married women were also less likely than unmarried women to be current smokers rather than former smokers. Over the years 1993-2012, the risk of current smoking compared to former smoking remained constant among married, never married, and cohabiting women, but increased among divorced women by about 0.4% per year (RRR = 1.000 *

1.004 = 1.004; p < .05); and among widowed women by about 0.7% per year (RRR =

1.000 * 1.009 = 1.009; p < .01). These results show that, between 1993 and 2012, divorced and widowed women became increasingly likely to continue or relapse into smoking, compared to married women. As in the case of single men (Figure 1), this finding may be due to increased selection of persistent smokers into divorce, or a stronger effect of marital disruption on smoking relapse.

Table 3. Results from a weighted multinomial logistic model regressing smoking status on marital status, survey year, and their interaction among womena

Former smoker Current smoker Current smoker vs. never smoked vs. never smoked vs. former smoker RRR SE RRR SE RRR SE Marital status Married ref. ref. ref. Never married 0.871*** 0.022 1.685*** 0.033 1.934*** 0.054 Divorced 1.339*** 0.029 2.438*** 0.052 1.821*** 0.043 Widowed 1.018 0.036 1.773*** 0.060 1.743*** 0.067 Cohabiting 1.663*** 0.082 2.828*** 0.114 1.700*** 0.087 Survey yearb 0.988*** 0.001 0.989*** 0.001 1.000 0.001 Survey year interactions Never married 0.999 0.002 1.001 0.002 1.001 0.002 Divorced 1.005** 0.002 1.009*** 0.002 1.004* 0.002 Widowed 1.018*** 0.003 1.025*** 0.003 1.007* 0.003 Cohabiting 0.999 0.004 0.991** 0.003 0.993 0.004 Survey year > 2010 1.040*** 0.012 0.936*** 0.012 0.900*** 0.013 Age 1.093*** 0.002 1.130*** 0.002 1.034*** 0.003 Age squared 0.993*** 0.0002 0.985*** 0.0002 0.992*** 0.0003 Race/ethnicity Non-Hispanic White ref. ref. ref. Non-Hispanic Black 0.438*** 0.006 0.460*** 0.005 1.052** 0.016 Hispanic 0.465*** 0.007 0.267*** 0.005 0.575*** 0.012 Asian/Pacific Islander 0.292*** 0.010 0.262*** 0.009 0.898* 0.041 Native American 0.977 0.033 1.247*** 0.037 1.276*** 0.048 All others 0.844*** 0.023 1.005 0.025 1.190*** 0.037 Educational attainment Elementary or less ref. ref. ref. Some high school 2.112*** 0.067 2.621*** 0.063 1.241*** 0.043 High school only 1.799*** 0.051 1.386*** 0.032 0.770* 0.025 Some college 1.846*** 0.052 0.934** 0.022 0.506*** 0.016 Four-year college 1.351*** 0.038 0.348*** 0.008 0.258*** 0.009 a N = 2,296,195. A single multinomial logistic regression model was fitted, with relative risk ratios shown separately for each pairwise comparison of the three smoking categories. b Centered at 1993. * p < .05; ** p < .01; *** p < .001, two-tailed tests.

Figure 2 illustrates trends in the predicted probabilities of never smoking, former smoking, and current smoking among women, stratified by marital status. These predicted probabilities are based on the model presented in Table 3. Figure 2 shows that married women were by far the least likely to have ever smoked in 1993, and became even less likely to smoke by 2012. Yet, lifetime smoking initiation declined at a similar rate among never married women, failing to support the hypothesis that marriage is increasingly selecting for never-smokers. Among women who ever smoked, the share of current smokers remained steady in the married and never married groups, but increased among divorced and widowed women. Given the general trend towards lower smoking prevalence, it is particularly unusual and concerning that both lifetime smoking initiation and current smoking increased among widowed women.

Married Women Never Married Women 1 1

.8 .8

.6 .6

Probability .4 Probability .4

.2 .2

0 0 1995 2000 2005 2010 1995 2000 2005 2010 Year Year

Divorced Women Widowed Women 1 1

.8 .8

.6 .6

Probability .4 Probability .4

.2 .2

0 0 1995 2000 2005 2010 1995 2000 2005 2010 Year Year

Never smoked Former smoker Current smoker

Figure 2. Predicted probabilities of smoking status among women, by marital status and survey year

Together, Figures 1 and 2 reveal growing disparities in smoking across marital status among both men and women. Over the two decades during which public policy has sought to “denormalize” smoking, married adults experienced the greatest decline in current smoking, relative to unmarried men and women. The accelerated decline of smoking initiation among married as compared to never married men also suggests increasing selectivity of marriage favoring non-smoking men. Particularly, similar proportions (about 25%) of married and never married men had never smoked in 1993; yet the share of never smokers increased to over 40% among married men in 2012

(Figure 1). Among women, on the other hand, the proportion of never smokers was almost 40% in 1993, and, in that year, was already substantially higher than proportions of never smokers in other marital status groups (Figure 2). Thus, selection of non- smoking women into marriage appears to have already been strong at the beginning of the study period, whereas this pattern of selection did not emerge among men until the

2000s.

In the BRFSS data, the legal marital status of cohabiters (i.e., respondents who report being a “member of an unmarried couple”) is unknown. Therefore, I considered whether combining this group with either never married or divorced adults would alter the findings reported above. Additional tables show key results from models in which all cohabiters are assumed to have never married (Table 4) or assumed to be divorced (Table

5), with relative risk ratios for control variables not shown. Table 4 shows the more plausible set of results, as other studies report that over two-thirds of cohabiters in a given year have never married (Casper and Bianchi 2002, p. 57). Results from both tables are

34 consistent with the main analysis, and among men, indicate that counting cohabiters as never married or divorced would show accelerated growth in the smoking initiation disparity between each unmarried group and the married group. For example, Table 4 shows that adding cohabiting men to the never married group makes the interaction between being never married and survey year significant and positive when comparing current smoking to never smoking (RRR = 1.008, p < .001).

Table 4. Results from weighted multinomial logistic regressions of smoking status on marital status, survey year, and their interaction, classifying cohabiters as never marrieda

Former smoker Current smoker Current smoker vs. never smoked vs. never smoked vs. former smoker RRR SE RRR SE RRR SE Men (N = 1,584,300) Marital status Married ref. ref. ref. Never marriedb 0.771*** 0.018 1.242*** 0.025 1.611*** 0.041 Divorced 1.137*** 0.031 2.120*** 0.054 1.864*** 0.050 Widowed 1.038 0.084 1.659*** 0.136 1.599*** 0.113 Survey yearc 0.975*** 0.001 0.974*** 0.001 0.999 0.001 Survey year interactions Never marriedb 1.008*** 0.002 1.024*** 0.002 1.016*** 0.002 Divorced 1.000 0.002 1.013*** 0.002 1.013*** 0.002 Widowed 1.005 0.006 1.028*** 0.006 1.023*** 0.006

Women (N = 2,296,195) Marital status Married ref. ref. ref. Never marriedb 0.974 0.022 1.832*** 0.034 1.882*** 0.048 Divorced 1.338*** 0.029 2.437*** 0.052 1.821*** 0.043 Widowed 1.020 0.036 1.777*** 0.061 1.743*** 0.067 Survey yearc 0.988*** 0.001 0.989*** 0.001 1.000 0.001 Survey year interactions Never marriedb 1.002 0.002 1.001 0.002 0.998 0.002 Divorced 1.005** 0.002 1.009*** 0.002 1.004* 0.002 Widowed 1.018*** 0.003 1.025*** 0.003 1.007* 0.003 a Relative risk ratios (RRR) for control variables are not shown. b Including cohabiters. c Centered at 1993. * p < .05; ** p < .01; *** p < .001, two-tailed tests.

Table 5. Results from weighted multinomial logistic regressions of smoking status on marital status, survey year, and their interaction, classifying cohabiters as divorceda

Former smoker Current smoker Current smoker vs. never smoked vs. never smoked vs. former smoker RRR SE RRR SE RRR SE Men (N = 1,584,300) Marital status Married ref. ref. ref. Never married 0.722*** 0.018 1.155*** 0.024 1.599*** 0.043 Divorcedb 1.117*** 0.030 2.077*** 0.051 1.859*** 0.048 Widowed 1.041 0.085 1.657*** 0.135 1.592*** 0.113 Survey yearc 0.975*** 0.001 0.974*** 0.001 0.999 0.001 Survey year interactions Never married 1.004 0.002 1.023*** 0.002 1.019*** 0.002 Divorcedb 1.005* 0.002 1.014*** 0.002 1.008*** 0.002 Widowed 1.004 0.006 1.027*** 0.006 1.023*** 0.006

Women (N = 2,296,195) Marital status Married ref. ref. ref. Never married 0.864*** 0.022 1.689*** 0.033 1.956*** 0.054 Divorcedb 1.393*** 0.029 2.530*** 0.050 1.815*** 0.041 Widowed 1.021 0.036 1.769*** 0.060 1.732*** 0.066 Survey yearc 0.988*** 0.001 0.989*** 0.001 1.000 0.001 Survey year interactions Never married 0.999 0.002 1.001 0.002 1.001 0.002 Divorcedb 1.004* 0.002 1.004* 0.002 1.000 0.002 Widowed 1.018*** 0.003 1.025*** 0.003 1.007* 0.003 a Relative risk ratios (RRR) for control variables are not shown. b Including cohabiters. c Centered at 1993. * p < .05; ** p < .01; *** p < .001, two-tailed tests.

Discussion

In the decades after the 1964 Surgeon General’s report on smoking, the smoking rate in the general population has steadily declined, but the “denormalization” of smoking behavior has had some unintended consequences. First, smokers became stigmatized and excluded from many aspects of social life (Stuber et al. 2008, 2009). Second, some sociodemographic disparities in smoking, such as the educational gradient, persisted or even widened (Pampel 2009). In this study, I connect these two consequences of smoking denormalization by examining how marital disparities in smoking behavior have changed in a period marked by growing anti-smoking stigma. Prior research has shown that married adults are less likely to smoke compared to unmarried adults. My findings build upon this literature by showing that, over the past two decades, the disparity in current smoking has increased between married and unmarried (never married or formerly married) men; and between married women and formerly married women. This increase in marital smoking disparities may be another unintended consequence of smoking denormalization, and may contribute to increases in other health disparities across marital status, such as disparities in overall health and mortality.

Among men, increasing marital disparities in smoking initiation point to strengthening selection mechanisms over this period. Relative to never married men, married men became less likely to have ever smoked between 1993 and 2012. The age at which people begin regular smoking usually precedes the age of marriage (Banks et al.

2014), and very few newlyweds begin smoking for the first time after getting married

(Homish and Leonard 2005), Therefore, this trend is unlikely to have been caused by

38 changing effects of marriage on smoking. Rather, this trend suggests that men who have ever smoked are facing increasing disadvantages in the marriage market, consistent with recent research describing smoking as a “handicap” on men’s marriageability (Chiappori et al. 2012). The increasing handicap on smoking men’s marriageability may be explained by the rise of stigma against smoking (Stuber et al. 2008, 2009). Marital selection was observed among women over the course of the entire period, as evinced by a stable difference in lifetime smoking initiation between married and never married women. Among men, this difference in lifetime smoking initiation was not evident at the

1993 baseline, but developed over the period of study and clearly emerged by the mid-

2000s. Therefore, increased marital selection on lifetime smoking initiation among men implies that men have become increasingly similar to women in the disadvantages they face in the marriage market if they smoke. This interpretation is consistent with studies of gender and smoking norms, which have argued that the stigmatization of women’s smoking is well entrenched (Nichter et al. 2006) whereas the stigmatization of men’s smoking is an emerging phenomenon (Greaves et al. 2010).

Among both men and women, the married group has become less likely to have ever smoked than the divorced or widowed groups. If the age at smoking initiation usually precedes the age at first marriage, then it must also precede the age at divorce or widowhood. It is unlikely, however, that either divorce or widowhood directly select for smoking before marriage. Rather, both divorce and widowhood may have become increasingly selective for current smoking habits, or sociodemographic factors that correlate with smoking. For example, smoking has remained more prevalent among

39 adults with lower educational attainment (Pampel 2009), and the selection of adults with lower educational attainment into divorce has grown stronger over time (Ono 2009). The latter trend towards increasing selection into divorce on the basis of low educational attainment could imply an increasing disparity between married and divorced adults in the prevalence of smoking. In this analysis, educational attainment was included as a control variable, but intensifying selection into divorce or widowhood on other sociodemographic factors (e.g., family income) could similarly explain the widening disparity in smoking initiation between married and formerly married adults.

Marital disparities in current smoking, relative to former smoking, may reflect two kinds of causal effects—smoking cessation after marriage (Merline et al. 2008), and smoking continuation or relapse after divorce or widowhood (Japuntich et al. 2011; Lee et al. 2005)—as well as marital selection on smoking behavior (e.g., selection into marriage favoring former smokers over persistent smokers). This analysis shows that former smokers did not displace current smokers among married men or women, meaning that there is no evidence of marriage becoming more protective against smoking. On the other hand, the share of current smokers among those who have ever smoked increased among both men and women who were divorced or widowed. One explanation for this finding may be that divorce and widowhood increasingly trigger smoking relapse (or continuation of smoking) as compared to earlier periods. Another explanation for this finding may be that married smokers are increasingly selected into divorce (Fu and Goldman 2000), although it is unclear why the same would be true for widowhood. Future research should investigate if the causal effects of divorce and

40 widowhood have indeed changed to increasingly promote smoking, and if this change signifies a broader increase in the stresses of divorce or widowhood, for which smoking is considered to be a coping mechanism (Carr and Umberson 2013).

Widening disparities in smoking between married and unmarried adults reinforce the findings of recent studies that identify widening marital disparities in health and mortality risk. The increasing disparity in smoking initiation between married and never married men is consistent with the ongoing increase in the longevity advantage of married relative to never married adults (Roelfs et al. 2011). Increasing disparities in current smoking between married and formerly married adults are consistent with growing disadvantages of formerly married adults in self-rated health (Liu and Umberson

2008; Liu 2012) and longevity (Liu 2009), relative to the married group. As the time periods covered by prior studies and by the current analysis do not entirely overlap, it is unclear if widening marital disparities in smoking were the reason why marital disparities in health and mortality risk have grown wider. Yet, the strong relationship between smoking and various diseases, including leading causes of death such as heart disease and lung cancer (Himes 2011; Tsai et al. 2010), suggests that widening marital disparities in smoking augur future growth in the health and longevity advantages of married adults, relative to their unmarried peers.

The constraints of the data and analytic approach used in this study suggest several research questions meriting attention in future work. The repeated cross-sectional design of the BRFSS means these data cannot be used to estimate changes in the causal effects of marriage, divorce, or widowhood. Estimation of the causal effects of marriage

41 across multiple cohorts is a promising direction for further research on health disparities between married and unmarried adults (Liu 2012). Furthermore, the lack of data on the marital status of cohabiting respondents in the BRFSS complicates the interpretation of results obtained for this group. Treating cohabiting respondents as never married strengthens the divergence in smoking behavior between this group and married adults

(Appendix). Future research should explore whether there are additional distinctions in smoking trends among cohabiters across legal marital status (never married vs. formerly married). Finally, although there is a consensus in the literature that the period being studied has witnessed a rise in anti-smoking stigma (Bayer and Stuber 2006; Bell et al.

2010b), research has only recently begun to examine how increasing stigma has influenced smokers’ participation in social activities (Stuber et al. 2008, 2009). Findings from the present analysis are consistent with a growing disadvantage in the marriage market for smokers, and future qualitative research should explore whether smokers indeed perceive themselves to be limited in their chances of marriage or choice of partners.

The decline of smoking has been a landmark public health achievement, but this achievement has been qualified by intense stigmatization of smokers and expansion of some sociodemographic disparities in smoking. This study contributes to the literature on the social determinants of smoking by showing that disparities in smoking between married and unmarried adults have increased in the last two decades, such that married adults have become increasingly unlikely to smoke relative to unmarried adults. Among widowed women in particular, smoking initiation and current smoking have become

42 more prevalent, deviating from the decline of smoking in the general population. Steady or increasing smoking rates among unmarried adults appear to be due to intensifying selection of non-smokers into marriage, and potentially also due to greater chances of smoking relapse among the divorced and widowed. These increasing marital disparities in smoking may augur future growth of marital disparities in outcomes such as general health and mortality risk. Furthermore, increases in current smoking among unmarried adults indicate that public health interventions encouraging smoking cessation should be targeted at and tailored to this group.

Chapter 3: Childhood-Onset Disability and Marital Status: Policy Effects and Period

Trends in the U.S., 1969-2013

Social integration of people with disabilities has been a focus for activism, research, and legislation in recent decades (Albrecht 2010; Lang 2009; Pelka 2012). The experience of growing up with a disability shapes a person’s transition through the life course stage of emerging adulthood, which is characterized by attaining financial independence, entering a committed romantic relationship, and having children (Arnett

2000). For young people growing up with a disability, this attainment of adult social roles is delayed and often foregone, due to physical and social barriers limiting participation in higher education and work (Janus 2009). In particular, for people growing up with a disability, the period of emerging adulthood is much less likely to entail marriage as compared to their able-bodied peers (Clarke and McKay 2014; MacInnes 2011). This pattern means that many young adults with disabilities who aspire to marry do not fulfill this aspiration (Nosek et al. 2001). Furthermore, young adults who do not marry risk foregoing the economic, social, and health benefits associated with the married state

(Waite and Gallagher 2000). Among young adults with disabilities who remain single, disadvantages associated with being unmarried may compound the disadvantages

44 experienced due to disability status, and may jeopardize entry into other adult roles, such as parenthood and employment (Janus 2009; Scott-Marshall et al. 2013).

The low likelihood of marriage among young adults with disabilities arises from a wide range of barriers to forming romantic relationships. People with physical disabilities report aspiring to marry, but finding these aspirations thwarted by limited opportunities to interact with potential partners in public and private spaces, discrimination by potential partners, and low self-esteem or a negative body image (Nosek et al. 2001). These barriers dovetail with societal expectations that people with physical disabilities will not date or marry (Howland and Rintala 2001). Furthermore, assortative mating on disability status may limit the marriage market of potential partners for people with disabilities. In other contexts, assortative mating or endogamy reflects the extent to which a dominant group (e.g. non-Hispanic Whites) maintains social distance from minority groups (e.g., non-Hispanic Blacks) (Qian and Lichter 2007). Persistent social distance between the able-bodied and people with disabilities may be expressed not only in low marriage rates among the latter group, but also in the tendency of people with disabilities to disproportionately marry other people with disabilities, limiting their pool of potential partners in the marriage market.

The exclusion of young adults with physical disabilities from the marriage market is attributed to inaccessible environments and discriminatory practices in schools, workplaces, and other institutions (Nosek et al. 2001; Wells, Sandefur, and Hogan 2003), which have become increasingly regulated by disability laws such as the 1975 Education for All Handicapped Children Act and the 1990 Americans with Disabilities Act

(Albrecht 2010; Jeon and Haider-Markel 2001; Lester 2014). By protecting educational and work opportunities for young adults with disabilities, these laws may have improved their chances of marriage in several ways. First, these laws may have helped young adults with disabilities achieve traits such as higher educational attainment and full-time employment that would be attractive to potential partners. Second, these laws may have given young adults with disabilities more opportunities to interact with potential partners

(e.g., in colleges or workplaces). Third, by bringing the issue of disability rights to the public’s attention, these laws may have shifted perception of people with disabilities in ways that have lessened the stigma of disability (Pelka 2012). Despite promising signs that disability legislation has improved the social integration of people with disabilities

(National Council on Disability 2010), no research has tested whether the effects of this legislation have included improving marital prospects among people with disabilities. In this paper, I examine how the marital status composition of Americans with childhood- onset physical disabilities has changed in response to landmark disability legislation and over the long run from 1969 until 2013. This analysis will reveal whether young

Americans with physical disabilities are becoming increasingly socially integrated, or are experiencing ongoing social exclusion, as reflected in their chances of marriage.

Barriers to marriage among young adults with physical disabilities

The aspiration to marry reflects the great cultural value placed on marriage in

American society (Cherlin 2010), and cuts across disability status (Nosek et al. 2011).

Yet, entering a first marriage has become an ideal rather than a reality for many

American young adults. During the life course stage of emerging adulthood, young

46 people may go through several long-term romantic relationships before settling on a partner whom they will marry (Arnett 2000). Even among young adults in committed cohabiting relationships, marriage is often delayed or foregone (Lichter, Qian, and

Mellott 2006), leading an increasing share of adults to remain never married as they reach their 30s (Qian 2013). Young adults who do marry typically experience marriage as part of a broader trajectory of entry into adult roles, including completion of higher education, attainment of full-time employment, and childbearing (Oesterle et al. 2010). By the same token, young adults who remain unmarried tend to remain economically dependent on their parents and to have not formed a family of their own (Janus 2009). Young people with disabilities are overrepresented in the never-married group, suggesting that they face a variety of barriers to completing this and other transitions to adulthood (MacInness

2011; Nosek et al. 2001).

For young people with physical disabilities, the built environment presents logistical barriers to meeting and interacting with potential partners. For example, many physical spaces are difficult to access for people who have mobility limitations (Pierce

1998). The inaccessibility of public and private spaces is echoed in the narratives of people with disabilities describing the barriers they face to meeting potential partners and dating (Nosek et al. 2001). People with disabilities also face institutional discrimination on the basis of their disability, which lessens their chance of participating in social activities where they might meet potential partners. For example, discrimination by employers may prevent people with disabilities from participating in the workforce

(Moore et al. 2011) and from meeting people in the context of working together.

Whereas some obstacles to marriage arise from institutional actions, people with disabilities also face discrimination from individual potential partners. People with physical disabilities are stereotyped as asexual, dependent, and incompetent (Coleman,

Brunell, and Haugen 2015; Nosek et al. 2001). These stereotypes contribute to reluctance among the able-bodied towards forming romantic relationships involving people with disabilities (Miller et al. 2009). Furthermore, negative stereotypes of people with disabilities intersect with gender stereotypes, leading people with disabilities to experience discrimination based on their perceived inability to fulfill gendered roles

(Coleman et al. 2015). For example, stereotypes of women with disabilities portray them as unfit for or incapable of caring for others, thereby deviating from the norm of female nurturing (Nosek et al. 2001); and stereotypes of men with disabilities portray them as weak and impotent, thereby deviating from the norms of male strength and virility

(Shakespeare 1999). These stereotypes may be internalized by some people with disabilities as expectations that, despite their aspirations to form romantic relationships, they will not be able to date or marry (Howland and Rintala 2001).

Discrimination against people with disabilities in the marriage market may also take the form of assortative mating on disability status. Previous research has shown that poor health, which may arise from disability, a chronic condition, or disease, makes people less attractive to potential spouses (Fu and Goldman 1996), and that people whose health is poor tend to choose a spouse who also has poor health, presumably reflecting a narrower range of potential partners from which to choose (Banks et al. 2013; Meyler et al. 2007). Preferences for good health in the marriage market mean that actual or

48 perceived health problems of people with disabilities will segregate them in marriages to other people with disabilities rather than marriages to able-bodied peers. In other contexts, assortative mating reproduces the exclusion of a marginalized population from intermarriage with the dominant group (Qian and Lichter 2007). Likewise, assortative mating on disability status may reflect the social isolation of people with disabilities if their marriages are disproportionately contracted with other people with disabilities, rather than the able-bodied.

Disability law and barriers to marriage

For young adults growing up with a physical disability, institutional discrimination, physical barriers to participation in daily activities, and individual stereotyping are key barriers to ever marrying, because these barriers are experienced at a time when most people meet and marry their first spouse (Janus 2009). Some of these barriers, particularly institutional discrimination and physical inaccessibility of social spaces, have been targeted by a growing body of disability rights legislation over the course of several decades. In the U.S., legislation protecting the rights of people with disabilities was first enacted in the late 1960s (National Council on Disability 2010).

Since then, four high-profile laws formed the legal nucleus of equal opportunity for people with disabilities, targeting discrimination against people with disabilities and physical barriers limiting access to public and private spaces. These were the 1973

Rehabilitation Act, the 1975 Education for All Handicapped Children Act, the 1990

Individuals with Disabilities Education Act (IDEA; a reform of the 1975 act), and the

1990 Americans with Disabilities Act (ADA) (Lester 2014; Moore et al. 2011). The

IDEA and ADA were also revised in the 2000s, with the Individuals with Disabilities

Education Improvement Act passed in 2004 and the Americans with Disabilities Act

Amendments Act passed in 2008. These six acts may be considered turning points in disability rights legislation, rising above other court cases and laws in their impact on the history of disability rights (National Council on Disability 2010).

Each of these laws has sought in some way to enhance the social integration of people with disabilities, but research evaluating this legislation has found that the results achieved were mixed. For example, in the decades following the ADA, more and more people with disabilities successfully transitioned from secondary education to college

(Katsiyannis et al. 2009), but the employment of men with disabilities declined (DeLeire

2000; Jolls 2004). Chronicles of the disability rights movement suggest that, taking a broad view of its effects, disability rights legislation, and especially the high-profile enactment of the ADA, accelerated the closing of social distance between people with disabilities and their able-bodied peers (Pelka 2012; Wright 1973). A shift in public attitudes towards greater empathy with people with disabilities, and the resulting erosion of disability stigma are important consequences of disability rights activism that may not be reflected in purely economic assessments of disability law (Pelka 2012). Despite these successes, discrimination and stigma against people with disabilities still linger (Roux et al. 2007; Salmon 2013; Werner 2015), and disability laws continue to be contested in the courts (Karger and Rose 2010).

Whereas landmark disability rights legislation was intended to improve the prospects of completing school and obtaining employment among young adults growing

50 up with physical disabilities, the consequences of disability rights activism and legislation for marriage among people with disabilities are unclear. Some studies suggest that the prevalence of marriage among people with a specific type of disabling condition (spinal cord injury) have remained relatively low over the last quarter-century (Brown and Giesy

1986; DeVivo and Richards 1996; Vogel et al. 2011), even as major legal strides were made in securing disability rights. These prior studies, however, provided snapshot estimates of marriage among people with disabilities at different times using different methodologies. Therefore, the effects of specific policies on the marriage rate of people with disabilities, as well as long-term trends in marriage among this population, are unknown. Prior literature has also not examined how assortative mating on disability status changed in response to the accumulation of disability rights activism and legislation, meaning that it is unknown if marriages between the able-bodied and people with disabilities have become more common in recent years.

The enactment of landmark disability rights laws (e.g., the ADA) resulted in wide-reaching changes to physical and social barriers faced by people with disabilities.

As the crumbling of these barriers has signaled greater social integration of people with disabilities (Pelka 2012), it is likely that young people with disabilities have experienced increasing opportunities in the marriage market, whether through an increased chance of ever marrying or through an increased chance of marrying a partner without disability

(i.e., through the decline of assortative mating on disability status). On the other hand, despite positive changes in the landscape of disability rights, institutional noncompliance with disability legislation and ongoing stigmatization of people with disabilities may

51 have continued to limit people with disabilities in their opportunities to date and marry.

By examining how marriage patterns among people with disabilities have developed in response to specific laws and over the long term, this study will show whether a key facet of social exclusion of people with disabilities has been mitigated or remains entrenched.

Current study

Physical and social barriers complicate the transition to adulthood among people with childhood-onset physical disabilities, and limit their opportunities to interact with their peers and form romantic relationships. Legislation protecting disability rights has targeted barriers to participation in educational and employment institutions, but the ultimate effects of this legislation on social integration of young people with disabilities remain unclear. Particularly, it is unknown if each landmark law protecting disability rights, and the accumulation of such legislation over the course of several decades, has increased chances of marriage among people with physical disabilities or eroded assortative mating on disability status.

In this study, I aim to estimate policy effects on two aspects of marriage among people with disabilities—whether they ever marry, and whom they marry—while accounting for long-term trends in these outcomes. Specific policies may have accelerated the social integration of people with disabilities, but their effects on marriage outcomes likely developed over time, rather than instantaneously. Consequently, I test the following two hypotheses:

H1. From the late 1960s onwards, there has been an increase in the proportion of people with disabilities who ever married, and an increase in the proportion of people with disabilities who married people without disabilities.

H2. The passage of disability-rights legislation in the 1970s, 1990s, and 2000s accelerated the increase in the proportion of people with disabilities who ever married, and the increase in the proportion of married people with disabilities whose spouse was able-bodied.

Hypothesis 1 addresses gradual change in marriage rates and chances of out- marriage among people with disabilities, emerging before the passage of specific disability legislation. Hypothesis 2 proposes that, in the wake of disability rights legislation, upward trends in marriage rates and out-marriage among people with disabilities were amplified from year to year as the effects of this legislation (e.g., increased participation in higher education) reshaped marriage market opportunities for people with disabilities.

Furthermore, as disability activism and legislation focused on specific institutions where people with disabilities faced discrimination and barriers to access, I explore whether increasing participation of people with disabilities in such institutions accounts for their expected greater chances of marriage and out-marriage. Specifically, I hypothesize that the findings anticipated by Hypotheses H1 and H2 would be explained by increased educational attainment or labor force participation among people with disabilities:

H3. The long-term trends (H1) in marriage among people with disabilities are attributable to increasing educational attainment and employment among people with disabilities.

H4. The acceleration of marriage and out-marriage trends among people with disabilities due to disability rights legislation (H2) is attributable to increasing educational attainment and employment among people with disabilities.

Data and Methods

Data

I use data from the National Health Interview Survey (NHIS), a repeated cross- sectional survey of non-institutionalized civilians in the U.S. conducted annually by the

Centers for Disease Control and Prevention. NHIS data on physical disabilities and marital status span all major disability rights laws enacted since 1968. I focus on NHIS data collected from 1969 to 2013, as in these years, childhood-onset physical disabilities were identifiable among adults of marriageable age. The pooled 1969-2013 sample contains records for 4,760,979 individuals. To identify the relationship between childhood-onset disability and marital status among young adults, I restrict this sample to

1,236,724 people aged 18-35 years at the time of the interview, among whom 1,161,539 have data on disability status and marital status at the time of the interview. As physical and mental disabilities may have different implications for young adults’ chances of marriage, I exclude from the sample 11,018 people whose activities were limited by any chronic mental health condition. I then exclude 21,038 people missing data on covariates,

54 reaching a final analytic sample size of 1,129,483 individuals, or 91% of all age-eligible cases.

Marital status

The outcomes of interest are having ever married and, among married adults, marriage to a person with disabilities. Marital status was originally coded as never married, married, separated, divorced, or widowed. In 1997, “living with partner” was added as an answer choice, with a follow-up question assessing whether the respondent had ever married. The lack of data on unmarried partners prior to 1997 precluded an analysis of cohabitation trends paralleling trends in the marriage outcomes of interest.

NHIS data included both same-sex and different-sex relationships since 1997 (Heck, Sell, and Gorin 2006), although same-sex marriages were not legally recognized until recent years, and not universally recognized in the U.S. until 2015, past the period from which data are available. Marital status was dichotomized to compare respondents who had ever married (i.e., the currently married, separated, divorced or widowed) to respondents who had never married. Comparing ever-married respondents to never-married respondents accounts for higher chances of marital disruption among people with disabilities

(Teachman 2010) by including marriages disrupted before the date of the interview. Data on the exact date of the first marriage, however, were not available, and so the category of “ever married” includes people whose first marriage was recent at the time of the interview (and therefore likely shaped by recent policies and social trends) as well as people whose first marriage had occurred at a much earlier date, and could not have been retroactively shaped by recently enacted legislation.

Because of limited data on marital history, the effects of disability rights legislation on the composition of the ever-married group (with respect to disability status) are likely to become apparent gradually rather than suddenly. Early in the post-legislation period, the presence of people with disabilities among the ever married is driven primarily by marriage market conditions that existed before the passage of a given law.

As years pass, more people with disabilities who have ever married would have done so under (hypothetically) different marriage market conditions prevailing in the post- legislation period. Over time, marriages formed in the post-legislation period would crowd out pre-legislation marriages in the ever married group. Uncertain marriage timing among ever-married NHIS respondents means that that legislation effects on specific marriage cohorts (e.g., cohorts entering the marriage market immediately after a law’s passage) cannot be identified.

Among married people, marriage to a person with disabilities was coded as 1 if the spouse had a chronic condition limiting their usual activity or other activities, and as 0 otherwise. Due to the lack of information about past spouses, the measure of out- marriage (people with disabilities marrying a person without disabilities) indicates the prevalence rather than incidence of such marriages. This is a potential source of bias, as couples in which one spouse has a disability may be at greater risk of marital disruption than couples in which both spouses are able-bodied. Therefore, the measure of out- marriage may underestimate the extent to which people with disabilities marry people without disabilities, if such marriages are disproportionately likely to end before one of the spouses is interviewed by the NHIS. Yet, although this pattern may bias estimates of

56 out-marriage in a given year, it would not bias estimates of change in the likelihood of out-marriage across successive years, as long as the relationship between disability status and chances of marital disruption remained stable across survey years.

Disability status

The primary independent variable is childhood-onset disability. From 1969 until

2013, the NHIS identified conditions limiting the respondent’s activities (being unable to perform one’s usual activity, being limited in amount or kind of usual activity, or being limited in other activities), and the duration of such limitations, although wording of these questions was changed in 1997, and the duration of limitations was top-coded at 5 years from 1982 until 1996. Specifically, data on disability were collected as follows in

1969 (through 1981), 1982 (through 1996), and 1997 (through 2013):

1969: Interviewer records if the respondent is unable to perform usual activity, can

perform usual activity but limited in amount and kind, can perform usual activity but

limited in outside activities, not limited by chronic conditions, or if this question is not

applicable (i.e., no chronic condition present). Interviewer records the duration of the

limitation as a number of months or years.

1982: Interviewer records if the respondent is unable to perform major activity, limited in

kind/amount of major activity, limited in other activities, or not limited. Interviewer

codes onset of condition as during the past 2 weeks, over 2 weeks to 3 months, over 3

months to 12 months, over 1 year to 5 years, or over 5 years.

1997: Interviewer asks the following: "Are you limited in any way in any activities

because of physical, mental or emotional problems? What conditions or health problems

cause your limitations?" Interviewer hands card with limitation categories to the

respondent and codes the response. "How long have you had [this condition]?"

Interviewer codes number of days, weeks, months, or years, or notes condition present

since birth.

In all years, I define disability as having a physical condition limiting any activity or the kind or amount of an activity (e.g. work). Although 1996 and earlier years distinguished between limitations on one’s main activity and limitations on other activities, it is unclear that this distinction captured the severity of the disability, as the relative physical demands of respondents’ primary and other activities were not assessed. Therefore, disabilities are not stratified by severity in this analysis.

A childhood-onset disability is defined as having a disabling condition that emerged before age 18. From 1982 until 1996, when the duration of limitations was top- coded at 5 years, I define childhood-onset disability as having a physical condition limiting the respondent’s activities that had begun over 5 years ago. To describe typical limitations experienced by people with disabilities (as measured above), I examine whether people with disabilities needed help with one or more of five activities of daily living (ADLs), including eating, dressing, bathing, getting around the house, and using the toilet. Data on ADLs were collected in 1977, in 1994-1995, and every year since

1997. In the years when these data were available, I also identify the five most common types of disabling conditions at ages 18-23 and 24-35, to characterize the nature of the limitations and the persistence of limitations from the late teens and early 20s until the mid-20s through the early 30s.

Educational attainment and employment

Educational attainment and employment potentially mediate the effects of disability rights legislation on the chances of marriage among young people with childhood-onset disabilities. Educational attainment was standardized across survey years to the following 4 categories: less than high school (or 0-11 years of schooling), high school or equivalent (12 years of schooling), some college or an associate’s degree (13-

15 years of schooling), and a four-year college degree (16 or more years of schooling).

Employment status was dichotomized as employed (including respondents who had a job but were not currently working) and not employed (including respondents out of the labor force for any reason).

Control variables

Changes in the demographic composition of people with disabilities may confound the relationship between the implementation of disability rights legislation and the change in the odds of ever marrying. Therefore, I include control variables for gender, age (in years) and race/ethnicity. In the 1979 and earlier NHIS, race was reported by the interviewer, whereas from 1980 onwards race was self-reported. I combine race and ethnicity into one variable, distinguishing among non-Hispanic White, non-Hispanic

Black, Hispanic, and other respondents.

Plan of analysis

I calculate weighted proportions of disability status, ADL limitations, having ever married (by disability status and timing of disability onset), and being married to a person

59 with disabilities to describe the relationship between disability and marital outcomes in the 1969-2013 NHIS. Next, I use logistic regression to model long-term trends and policy effects in the two marriage outcomes (ever marrying, and, among married people, marrying a person with disabilities). Due to data differences, I fit regression models separately for three time series: 1969-1981, 1982-1996, and 1997-2013. I regress the log odds of each outcome on survey year, a binary indicator of having childhood-onset disabilities, and the interaction of these two variables. The year variable captures the trend in each outcome, and the interaction indicates whether this trend is different for people with childhood-onset disabilities, testing Hypothesis 1.

I also include an interaction between childhood-onset disability and years since the enactment of major disability laws. This interaction term is always zero for people without childhood-onset disabilities. For people with childhood-onset disabilities, it equals zero before the legislation is passed, and equals the number of years since the legislation (e.g., 1 in the first year post-legislation, 2 in the second year post-legislation) thereafter. Among people with disabilities, this variable captures deviation from the longer-term trend from the passage of disability laws onwards, as expected in Hypothesis

2. This analysis focuses on the following turning points in disability law: 1973-1975

(Rehabilitation Act and Education for All Handicapped Children Act), 1990 (ADA and

IDEA), and 2004-2008 (amendments to ADA and IDEA).

For both outcomes, I estimate models with and without controls for educational attainment and employment, to test if these variables mediate the policy or time effects on marriage odds among people with disabilities (Hypotheses 3 and 4). Demographic

60 covariates (gender, age, and race/ethnicity) are included in all models, with a quadratic age term added to account for a nonlinear relationship between age and marital outcomes.

All models are weighted to account for unequal probability of being selected into the

NHIS sample, and the standard errors are adjusted for the stratified sampling design of the NHIS.

Results

Figure 3 illustrates weighted proportions of young adults (ages 18-35) with any disabilities and with childhood-onset disabilities in the 1969-2013 NHIS. The prevalence of childhood-onset disabilities among young adults was approximately 2% at the beginning of this period, and remained at that level in the most recent years. A stable minority of young adults experienced activity limitations due to a chronic condition other than mental illness or developmental disability, with most of these disabilities beginning before age 18. In 1982-1996, the estimated prevalence of childhood-onset disabilities was inflated due to topcoding of disability duration at 5 years. Consistent with this explanation, an analysis of adults no older than 23 (Figure 4) in each time series, among whom any disability beginning more than 5 years ago is a childhood-onset disability, eliminates the trend break in childhood-onset disabilities that appears in Figure 3.

Although limiting the sample to ages 18-23 in Figure 4 does not solve the problem of top- coded time since onset in the 1982-1996 data series, it clarifies the reason for the apparent temporary rise in childhood-onset disabilities seen during this period.

.1 Any disability Childhood-onset disability

.08 1969-1981 NHIS 1982-1996 NHIS 1997-2013 NHIS

.06

Proportion .04

.02

0 1970 1980 1990 2000 2010 Year

Figure 3. Weighted proportions of young adults ages 18-35 with any disability and with a childhood-onset disability, 1969-2013 NHIS

.1 Any disability Childhood-onset disability

.08 1969-1981 NHIS 1982-1996 NHIS 1997-2013 NHIS

.06

Proportion .04

.02

0 1970 1980 1990 2000 2010 Year

Figure 4. Weighted proportions of young adults ages 18-23 with any disability and with a childhood-onset disability, 1969-2013 NHIS

Limitations in activities of daily living (ADLs) and specific conditions diagnosed among young adults with disabilities give more detail about how such disabilities may thwart meeting and marrying potential partners. Figure 5 illustrates the proportion of young adults with any disabilities and with childhood-onset disabilities who require help with one or more of the following activities of daily living (ADLs): eating, dressing, bathing, getting around the house, or using the toilet. In the 1977 and 1994-1995 disability supplements, fewer than 5% of young adults with disabilities required help with one or more of these ADLs. From 1997 onwards, between 5% and 10% of young adults with disabilities required help with one or more ADLs. Thus, whereas the disabilities

63 captured in these data limit respondents’ usual activities, such as working or going to school, they are usually not severe enough to limit basic activities of daily living, suggesting that severe physical impairment, in itself, is not a primary reason why young adults with disabilities are excluded from the marriage market.

.15 1969-1981 NHIS 1982-1996 NHIS 1997-2013 NHIS

.1 Proportion

.05

Any disability Childhood-onset disability 0 1970 1980 1990 2000 2010 Year

Figure 5. Weighted proportion of young adults (ages 18-35) with disabilities who require help with one or more of five activities of daily living (ADLs), 1977-2013 NHIS

For the periods in which ADL data were available, I calculate the five most common types of disabling conditions among people with childhood-onset disabilities ages 18-23 and 24-35. Each respondent may have had multiple conditions, and some

64 conditions were coded in residual categories such as “other impairment” that are not shown. Furthermore, different coding schemes were used in each of the three periods, resulting in somewhat different category names. The most common specific conditions limiting activities among people with childhood-onset disabilities are summarized in

Table 6 for each period. Two clear patterns emerge. First, despite changes in the coding schemes over the years, all periods show respiratory, musculoskeletal, and congenital problems as major contributors to activity limitations among people with childhood-onset disabilities. Second, the top five categories of limitations are remarkably consistent between ages 18-23 and ages 24-35, with only one condition (chronic musculoskeletal disorders in 1977) showing up in the earlier age range but not in the later age range. This suggests that the composition of conditions limiting activity does not change between these age ranges, implying that the most common childhood-onset limitations at ages 18-

23 are not due to conditions that can be cured by the time a person reaches ages 24-35.

Table 6. Common conditions limiting activities among people with childhood-onset disabilities, 1977, 1994-1995, and 1997-2013 NHIS

Ages 18-23 Ages 24-35 1977 Impairments, lower extremities and hips 13% Visual impairments 12% Asthma 12% Asthma 11% Impairments, back or spine 9% Impairments, lower extremities and hips 8% Chronic musculoskeletal disorders 5% Paralysis 7% Visual impairments 5% Impairments, back or spine 7%

1994 -1995 Diseases of the respiratory system 33% Diseases of the musculoskeletal system 45% Diseases of the musculoskeletal system 25% Diseases of the nervous system 14% Diseases of the nervous system 13% Diseases of the respiratory system 14% Congenital anomalies 8% Endocrine and metabolic diseases, immunity disorders 5% 66 Endocrine and metabolic diseases, immunity disorders 5% Congenital anomalies 5%

1997 -2013 Developmental problems 17% Back or neck problems 16% Lung/breathing problems 17% Developmental problems 15% Back or neck problems 13% Nervous system/sensory organ problems 15% Nervous system/sensory organ problems 12% Lung/breathing problems 14% Birth defects 9% Birth defects 10%

The relationship between disability status and marital outcomes is illustrated in

Figure 6, which shows weighted proportions of ever marrying among young adults with disabilities, young adults with childhood-onset disabilities, and young adults without disabilities. Over the years 1969-2013, there was little difference in chances of ever marrying between young adults with any disability and young adults with no disabilities, with the majority of both groups marrying between ages 18 and 35. (The same was true when restricting the sample to ages 18-23 to account for inaccurate data on disability onset in the 1982-1996 data.) In the two time series with accurate data on disability duration, 1969-1981 and 1997-2013, the proportion ever marrying was less than 50% among young adults with childhood-onset disabilities, and declined from 2000 onwards.

Therefore, young adults with childhood-onset disabilities are atypical, compared to their peers, in that they are more likely to remain single than to ever marry, even in the early

1970s and 1980s, when the general retreat from marriage was still in its infancy.

Furthermore, the chances of ever marrying among young adults with disabilities did not increase in the wake of disability rights legislation passed in the 1970s or later decades.

1 Any disability Childhood-onset disability No disability .8

.4 Proportion ever married ever Proportion

1969-1981 NHIS 1982-1996 NHIS 1997-2013 NHIS 0 1970 1980 1990 2000 2010 Year

Figure 6. Weighted proportion of young adults (ages 18-35) who have ever married, by disability status, 1969-2013 NHIS

Low and declining marriage rates among young adults with childhood-onset disabilities are intertwined with the broader trend of marriage becoming delayed or deferred. Therefore, a declining marriage rate among young adults with disabilities does not in itself signify growing social exclusion. On the other hand, the trend in assortative mating on disability status should reveal changes in the social integration of young adults with disabilities independently of broader changes in marriage rates. Figure 7 shows that, among married young adults, those who had any disabilities were married to another person with disabilities in 15% to 20% of cases, despite young adults with disabilities constituting only 4% to 6% of the 18-35 age group. (Trends shown in Figure 7 are

smoothed in each data series due to higher volatility of this outcome compared to outcomes shown in earlier figures.) Young adults with disabilities were disproportionately likely to marry one another rather than a person without disabilities, and the extent of this assortative mating showed no sign of declining from the 1970s onwards. Together, Figures 3-7 suggest that young adults with disabilities have continued to be at a disadvantage in the marriage market, and have continued to disproportionately in-marry within the disabled group, despite disability rights legislation passed in the

1970s, 1990s, and 2000s. In the most recent period (1997-2013), young adults with disabilities have been increasingly unlikely to have ever married, both in absolute terms and relative to their able-bodied peers (Figure 6).

.4 Smoothed trends: Any disability Childhood-onset disability

.2 Proportion

1969-1981 NHIS 1982-1996 NHIS 1997-2013 NHIS

0 1970 1980 1990 2000 2010 Year

Figure 7. Smoothed trends of weighted proportions of married young adults (ages 18-35) with disabilities whose spouse is a person with disabilities, 1969-2013 NHIS

To elaborate on this descriptive analysis, I use logistic regression to estimate overall trends and policy consequences for marital outcomes among young adults with childhood-onset disabilities. Table 7 shows results from models predicting the odds of having ever married. The odds ratio (OR) for the main effect of the linear trend represents change in the odds of ever marrying among people without childhood-onset disabilities.

In every model, this OR is less than 1 and statistically significant, indicating a general decline in the marriage rate among young adults without disabilities. The OR for the main effect of childhood-onset disability indicates the extent to which people with childhood-onset disabilities were less likely to marry than other young adults at the

beginning of each data series (i.e., in 1969, 1982, and 1997, respectively). In every model, this OR is less than 1 and statistically significant, indicating that childhood-onset disabilities have been associated with 28-56% lower odds of ever marrying among young adults surveyed in 1969, 1982, and 1997. The interaction between childhood-onset disability and the linear trend tests the extent to which the trend in odds of ever marrying was different by disability status. As this interaction term is less than 1 in every model, it implies that among young adults with childhood-onset disabilities, the decline in marriage was steeper in each period than the corresponding decline in marriage in the reference group. This finding fails to support Hypothesis 1, as it points to a growing disparity in ever marrying by disability status, rather than a convergence in this outcome.

Table 7. Logistic regression of ever marrying on survey year, disability laws, and covariates among young adults

1969-1981 NHIS 1982-1996 NHIS 1997-2013 NHIS Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 OR OR OR OR OR OR Survey year Linear trend, 1969-1981 (centered at 1969) 0.95*** 0.95*** Linear trend, 1982-1996 (centered at 1982) 0.98*** 0.98*** Linear trend, 1997-2013 (centered at 1997) 0.95*** 0.96*** Disability status Childhood-onset disabilitya 0.48*** 0.44*** 0.72*** 0.69*** 0.53*** 0.49*** Childhood-onset disability x Linear trend 0.99 0.99 0.97** 0.97** 0.98 0.97* Childhood-onset disability x Years since legislation Legislation passed in 1973-1975b 1.04 1.03 Legislation passed in 1990c 1.05* 1.06* Legislation passed in 2004-2008d 0.96 0.96

72 Demographic covariates e

Female 2.07*** 2.06*** 1.88*** 2.02*** 1.74*** 1.78*** Age 3.19*** 3.84*** 2.75*** 2.97*** 2.73*** 2.87*** Age squared 0.98*** 0.98*** 0.99*** 0.98*** 0.99*** 0.99*** Non-Hispanic Blackf 0.53*** 0.43*** 0.39*** 0.35*** 0.36*** 0.34*** Hispanicc 0.54*** 0.61*** 0.61*** 0.68*** 0.81*** 0.84*** Educational and work outcomes Completed high schoolg 0.71*** 0.76*** 0.90*** Completed some collegeg 0.34*** 0.45*** 0.72*** Completed 4-year collegeg 0.26*** 0.32*** 0.62*** Employedh 1.06*** 1.25*** 0.95*** * p < .05; ** p < .01; *** p < .001 (two-tailed tests) a Reference group includes adults with no disabilities or adults with adult-onset disability. b Coded 0 for all years before 1975, 1 for 1976, 2 for 1977 and so on. Coded 0 for all years among adults with no disabilities. c Coded 0 for all years before 1990, 1 for 1991, 2 for 1992 and so on. Coded 0 for all years among adults with no disabilities. d Coded 0 for all years before 2008, 1 for 2009, 2 for 2010 and so on. Coded 0 for all years among adults with no disabilities. e Reference group includes males. f Reference group includes non-Hispanic Whites. (Hispanic origin was not assessed in pre-1982 data.) g Reference group includes people who did not graduate from high school and did not obtain an equivalency degree. h Reference group includes people who are unemployed or out of the labor force.

Table 7 also shows interactions between childhood-onset legislation and time since the enactment of major disability rights laws. In Models 3 and 4, this interaction is statistically significant and greater than 1, suggesting that, among people with childhood- onset disabilities, the decline in odds of ever marrying was attenuated in the wake of the

1990 Americans with Disabilities Act. This finding partially supports Hypothesis 2, as it indicates a narrowing disparity in ever marrying across disability status after the enactment of disability rights legislation. In Models 2, 4, and 6, respectively, controlling for work status and educational attainment fails to explain any difference in the overall trend of ever marrying across disability status, or any policy effect on the odds of marriage in the childhood-onset disability group. This fails to support Hypotheses 3 and

4. Using the full model from each data series (Models 2, 4, and 6, respectively), Figure 8 plots the odds ratios of having ever married associated with a childhood-onset disability in each year. In every period, there is an initial downward trend in the odds ratio, illustrating divergence in the chances of marriage across disability status. Yet, in the middle data series, there is a clear upswing in the odds ratio towards 1 after the passage of the ADA, indicating convergence of the marriage gap across disability status, as expected by Hypothesis 2.

Odds Odds Ratio .4

1969-1981 NHIS 1982-1996 NHIS 1997-2013 NHIS 0 1970 1980 1990 2000 2010 Year

Figure 8. Odds ratios of having ever married associated with having a childhood-onset disability, before and after major disability rights legislation, 1969-2013 NHIS

In Table 8, I explore overall trends and consequences of disability rights legislation for assortative mating by disability status. This table models the odds of having a spouse with disabilities among young adults who were married at the time of the survey. The main effects of survey year suggest that people without disabilities became slightly more likely to marry people with disabilities from 1969 until 1996 (Models 1 and

3), but slightly less likely to marry people with disabilities from 1997 onwards (Model 5,

OR = 0.98, p < 0.001). Interactions between childhood-onset disability and survey year are greater than 1 but are not statistically significant, suggesting that, among people with

childhood-onset disabilities, chances of out-marriage to people without disabilities remained stable or potentially increased. Furthermore, there were no apparent effects of disability legislation towards reducing endogamy among people with childhood-onset disabilities, as shown by non-significant interactions between disability status and time since disability law enactment. These findings are illustrated as odds ratios of marriage to a person with disabilities, based on the full model in each time period, in Figure 9.

Table 8. Logistic regression of spouse disability on survey year, disability laws, and covariates among young adults

1969-1981 NHIS 1982-1996 NHIS 1997-2013 NHIS Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 OR OR OR OR OR OR Survey year Linear trend, 1969-1981 (centered at 1969) 1.01** 1.01*** Linear trend, 1982-1996 (centered at 1982) 1.01** 1.01*** Linear trend, 1997-2013 (centered at 1997) 0.98*** 0.98*** Disability status Childhood-onset disabilitya 2.54*** 2.55*** 2.86*** 2.72*** 5.66*** 5.27*** Childhood-onset disability x Linear trend 1.01 1.01 1.03 1.03 1.03 1.03 Childhood-onset disability x Years since legislation Legislation passed in 1973-1975b 1.01 1.01 Legislation passed in 1990c 1.00 0.99 Legislation passed in 2004-2008d 1.03 1.02

76 Demographic covariates e

Female 1.68*** 1.63*** 1.29*** 1.25*** 0.98 1.00 Age 0.89*** 0.93** 0.93* 1.00 0.81*** 0.89* Age squared 1.003*** 1.002*** 1.002** 1.00 1.004*** 1.003** Non-Hispanic Blackf 1.03 0.99 1.02 0.99 1.08 1.03 Hispanicc 0.71*** 0.73*** 0.81*** 0.83** 0.58*** 0.63 Educational and work outcomes Completed high schoolg 0.72*** 0.77*** 1.00 Completed some collegeg 0.73*** 0.67*** 0.85** Completed 4-year collegeg 0.59*** 0.50*** 0.43*** Employedh 0.96 0.89*** 0.95 * p < .05; ** p < .01; *** p < .001 (two-tailed tests) a Reference group includes adults with no disabilities or adults with adult-onset disability. b Coded 0 for all years before 1975, 1 for 1976, 2 for 1977 and so on. Coded 0 for all years among adults with no disabilities. c Coded 0 for all years before 1990, 1 for 1991, 2 for 1992 and so on. Coded 0 for all years among adults with no disabilities. d Coded 0 for all years before 2008, 1 for 2009, 2 for 2010 and so on. Coded 0 for all years among adults with no disabilities. e Reference group includes males. f Reference group includes non-Hispanic Whites. (Hispanic origin was not assessed in pre-1982 data.) g Reference group includes people who did not graduate from high school and did not obtain an equivalency degree. h Reference group includes people who are unemployed or out of the labor force.

Odds Odds Ratio 4

2 1969-1981 NHIS 1982-1996 NHIS 1997-2013 NHIS 1 1970 1980 1990 2000 2010 Year

Discussion

Disability rights activists have achieved major policy shifts with the passage of the Americans with Disabilities Act (ADA) and other laws prohibiting institutional discrimination against people with disabilities and requiring accessibility of public and private spaces (National Council on Disability 2010; Pelka 2012). Yet, people growing up with disabilities remain less likely than their able-bodied peers to achieve milestones in the transition to adulthood, such as becoming employed, living independently, or getting married (Janus 2009; MacInnes 2011). The chances of marriage and the choice of a partner among young people with disabilities depend on their accumulated experience 77

of discrimination and social isolation. Disability rights legislation and disability activism had broken down barriers to participation in education and the labor force, and had engendered greater acceptance of people with disabilities, but it is unknown if these advancements have affected the position of people with disabilities in the marriage market.

This paper is the first to estimate policy consequences and long-term trends in marriage outcomes of young adults with childhood-onset disabilities. Young adults who have had disabilities since childhood are, in principle, the group most likely to have benefited from the reforms introduced by disability legislation. Specifically, they would have benefited both from laws easing their participation in educational institutions, such as the 1990 Individuals with Disabilities Education Act, and broader laws prohibiting institutional discrimination and physical barriers to accessibility, such as the ADA.

Certainly, these laws have led to concrete initiatives to integrate people with disabilities into educational and work environments (Butterworth et al. 2011; Katsiyannis et al.

2009), and, in the case of education, have led to substantial increases in the proportion of young adults with disabilities entering and graduating from college (Katsiyannis et al.

2009). In the case of employment, the outcomes of disability legislation were mixed, with overall employment rates among people with disabilities showing no improvement after the passage of the ADA (Jolls 2004), but with some gains in employment observed among people whose disabilities limited them in activities unrelated to their ability to work (Kruse and Schur 2003).

In any case, the intention of disability legislation was to ease participation of people with disabilities in institutions such as universities and workplaces, from which they had previously been excluded (National Council on Disability 2010). By being better able to complete their schooling and find employment, young adults with disabilities should have also become better positioned to find and marry a romantic partner. Nevertheless, aside from a brief upswing in the chances of ever marrying in the immediate post-ADA period, the marriage prospects of young adults with childhood- onset disabilities did not seem to respond to any of the major disability laws passed in recent decades. Furthermore, considering long-term trends in marriage that spanned the introduction of specific disability laws, the proportion of young adults who had ever married declined just as fast if not faster among young adults with childhood-onset disabilities as among their able-bodied peers. Therefore, the data largely do not support hypotheses that disability legislation has improved chances of marriage among young adults with childhood-onset disabilities, or weakened assortative mating on disability status.

Whereas specific policies appeared to have weak or null effects on marriage outcomes among people with disabilities, analysis of long-term trends in revealed that, in the last two decades, the retreat from marriage has been especially strong among young adults with disabilities (i.e., marriage has declined more rapidly among young adults with disabilities than among their able-bodied peers), and that assortative mating on disability status may have become more commonplace. These trends are all the more remarkable because only about 40% of young adults with childhood-onset disabilities had ever

married in 1969 (the beginning of the study period), suggesting many of them had unrealized marriage expectations relative to the able-bodied group, of whom approximately 70% had ever married as of 1969.

The combination of these trends points to a surprising intensification of social exclusion of people with disabilities in the post-ADA era. Quantitative evidence of growing exclusion of people with disabilities from the marriage market (and their concentration in marriages to other people with disabilities) is consistent with recent qualitative evidence revealing individual discrimination and stigma experienced by people growing up with disabilities (Roux et al. 2007; Salmon 2013). A further reason for falling marriage rates among people with disabilities may be due to growing interdependence between the labor market and the marriage market. The recasting of marriage as a capstone transition has meant that young adults increasingly perceive economic security to be a prerequisite for marriage (Cherlin 2010). The association of disabilities with lower participation in the labor force (Janus 2009) may have become a stronger barrier to marriage because of this growing emphasis on attaining economic stability before marrying. More work is needed to understand if the accelerated decline of marriage among people with disabilities is primarily underpinned by their economic disadvantages, or by a recrudescence of stigma and discrimination by their peers and potential partners.

In other contexts, research on intermarriage describes it as the final frontier of social integration. For example, racial/ethnic intermarriage shows the extent of social integration of racial and ethnic minority populations (Qian and Lichter 2007). Among

people with childhood-onset disabilities, the persistently high tendency to be married to another person with disabilities hints at a marriage market segmented by disability status.

People without disabilities may be wary of marrying a person with disabilities due to stereotypes linking disability to asexuality, dependence, and other unfavorable characteristics (Nosek et al. 2001; Shakespeare 1999). On the other hand, people growing up with disabilities may be likely to seek out peers with disabilities who can relate to the challenges they experience (Salmon 2013). The resulting segregation of people with disabilities within peer networks may increase their exposure to potential partners who also have a disability, but decrease their exposure to potential partners who are able- bodied.

Thus, people with disabilities may be disproportionately unlikely to marry an able-bodied person because they are excluded from the peer networks formed by their able-bodied peers, even if they are able to participate in the same educational and work institutions as able-bodied people. Furthermore, marriages in which one spouse has a disability are more likely to be disrupted, as disability contributes to marital tension and the risk of divorce (Singleton 2012; Teachman 2010). Higher chances of divorce among marriages including one spouse with a disability may contribute to the disproportionate likelihood of people with disabilities to be married to another person with disabilities in a cross-sectional sample of currently married couples. Future work should clarify if this relationship between disability status and marital disruption has intensified in recent years, explaining the increased assortative mating on disability status apparent in this study.

The strengths and limitations of the present study indicate important opportunities for further research. First, the NHIS is uniquely valuable as a source of historical data on the relationship between disability status and marriage. These data, however, do not include information on the timing of marriages, meaning that some marriages contracted before disability laws took effect are included in analyses of post-legislation periods. In the 21st century, the introduction of questions about the timing of marriage to the

American Community Survey offers the chance to assess trends in marital formation and partner choice among recently married people with disabilities. These data could be used to replicate and extend the present findings of growing exclusion of people with disabilities from the contemporary marriage market. Second, the definition of disability used in this study captures a wide range of chronic physical conditions limiting respondents’ activities, but offers little detail about the severity of disability. Therefore, future work should consider how the severity of physical impairment moderates the relationship between disability and marriage outcomes. Finally, the present study has analyzed marriage outcomes in early adulthood among people with childhood-onset disabilities. As such disabilities may have a cascading effect on life course transitions, an important extension of this work will be to consider how patterns of marriage have changed among older adults who had grown up with disabilities.

Studies of disability in society have found mixed trends in the social integration of people with disabilities. Whereas landmark disability legislation has achieved positive trends, such as increased college enrollment among people with disabilities (Jolls 2004), other objectives, such as increased participation in the labor force, were not achieved

(DeLeire 2000); and people with disabilities have continued to experience discrimination and social exclusion in high school (Salmon 2013), college (Dowrick et al. 2005), and the workforce (Moore et al. 2011). This study demonstrates that marriage continues to be an institution in which people with disabilities experience social exclusion, notwithstanding the successes of disability activists in achieving legal protection for disability rights. The cultural significance of marriage as a capstone event in the transition to adulthood means that the accelerated retreat from marriage and increasing endogamy among young adults with disabilities signals a recent increase in the social exclusion of people with disabilities. Understanding the causes of these recent trends will clarify how future policies may secure equal opportunity across disability status.

Chapter 4: Does Marriage Protect Health? A Birth Cohort Comparison.

Married people are healthier, on average, than the unmarried (Schoenborn 2004).

This difference has sparked controversy over the contribution of marriage to population health disparities (Wood, Goesling, and Avellar 2007). On one hand, the health advantage of the married may be attributed to the health benefits of getting and staying married, making marriage an important determinant of social inequalities in health (Waite

1995). In the new millennium, the marriage promotion movement has taken this reasoning further to argue that encouraging marriage will serve the public health, because more people will reap the health benefits of marriage (Huston and Melz 2004; Waite and

Gallagher 2000; Wilcox et al. 2005). On the other hand, recent scholarship has approached the health benefits of marriage with increasing skepticism (Musick and

Bumpass 2012). These studies show that causal effects of marriage are underwhelming in magnitude, inconsistent across outcomes, or simply absent (Averett et al. 2012; Musick and Bumpass 2012; Wu and Hart 2002). Such findings suggest that marriage itself— compared to remaining never married—does little to influence social inequalities in health, even if other marital transitions, such as divorce or widowhood, remain important determinants of health and well-being.

Weak health benefits for people who marry, relative to their never married counterparts, may reflect social trends that have altered the role of marriage in American society (Liu and Umberson 2008). Recent studies have suggested that the demographic retreat from marriage and the cultural deinstitutionalization of marriage may be weakening the protective effects of marriage (Liu 2009; Musick and Bumpass 2012). The rate of marriage has declined in recent decades, with the retreat from marriage being most acute in socioeconomically disadvantaged groups (Cherlin 2010; McLanahan 2004).

Therefore, married people are increasingly those most likely to be in good health regardless of marriage—for example, college graduates. Furthermore, the transition to marriage no longer means a shift from living alone to living together. People who get married today most commonly do so after cohabitation, rather than after dating without cohabitation (Cherlin 2010). Many of the mechanisms by which marriage protects health, including social support and the sharing of economic resources, are present in cohabiting relationships, too. Therefore, the transition to marriage may lead to fewer changes in health in recent cohorts because it increasingly implies a change from cohabiting to married, rather than from single to married (Musick and Bumpass 2012).

Limited evidence on period differences in marital health disparities suggests that the protective effects of marriage have eroded in recent decades. For example, differences in self-rated health between married and never-married men have grown smaller in successive cross-sectional surveys between 1972 and 2003 (Liu and Umberson 2008).

Yet, this research has focused on describing changes in the association between marriage and health in cross-sectional data, and has not estimated how causal effects of marriage

have changed over time. To understand whether marriage benefits have weakened over time, I consider the cumulative protective effect of marriage on general health, and test the hypothesis that this effect of marriage has declined in successive cohorts, as predicted by Americans’ retreat from marriage. I then explore whether declines in the marriage effect were shared broadly, or limited to groups defined by race or educational attainment. This analysis will reveal whether the conclusions of early studies about the health benefits of marriage are out of step with recent cohorts' experience, and whether a downward trend in marriage effects on health stands to make marriage irrelevant to health disparities in future cohorts.

Protective influences of marriage on health

Married adults are healthier than unmarried adults in several ways, with the married group being advantaged with respect to general health (Dupre and Meadows

2007; Hughes and Waite 2009), specific health conditions such as hypertension

(McFarland, Hayward, and Brown 2013), and mortality (Dupre, Beck, and Meadows

2009; Liu 2009). A provocative interpretation of health disparities between married and unmarried people is that marriage causes better health (Ross, Mirowsky, and Goldsteen

1990; Waite and Gallagher 2000). This causal relationship reflects a mix of social and economic mechanisms (Wood et al. 2007) that activate biological pathways of stress response (Robles and Kiecolt-Glaser 2003) or define exposure to health risk behaviors, such as smoking (Himes 2011). For example, according to social control theory, marriage benefits people because they gain a partner who will monitor their behavior (Umberson

1992), encouraging healthy behaviors over unhealthy ones—eating fruits and vegetables

over smoking, for example (Duncan et al. 2006; Merline et al. 2008). This monitoring is performed both because spouses are invested in one another’s health (Bolin, Jacobson, and Lindgren 2002), and because spouses perceive the married role to be incompatible with risky and unhealthy behaviors (Duncan et al. 2006). For this reason, social control exercised by a spouse is a common and effective source of social influence on health behaviors among adults (Umberson 1992).

The social benefits of marrying extend beyond being monitored by one’s spouse, and include the enlarged network of social support accessed by marriage (Ross et al.

1990). Marriage joins two families together, and gives spouses a wider network from which to seek emotional support in times of crisis and material support in times of need

(Umberson and Montez 2010). Evidence on social networks and health finds that the more social ties a person has, the better their health and the longer their lifespan (Cohen

2004; Cornwell and Waite 2012; Kawachi and Berkman 2001). Indeed, within the intimate context of the marital relationship, a spouse’s support for coping with stress may improve health above and beyond any active, deliberate monitoring of health behaviors

(Umberson and Montez 2010).

Marriage may also confer financial resources that can be used to protect and improve the spouses’ health. An obvious benefit of marriage takes the form of economies of scale, such that the resources of two people are combined to maintain one household

(Waite and Gallagher 2000). Other economic perspectives on marriage have stressed financial benefits from specialization (i.e., husbands specializing in paid labor while wives specialized in housework) (Becker 1981); motivation to be more productive and

earn higher wages (Gorman 2000); signaling to employers, resulting in preferential treatment for married as opposed to unmarried workers (Hersh and Stratton 2000); and access to a spouse’s employer-provided health insurance for people who lack their own coverage (Sohn 2015). These financial advantages may be leveraged to engage in behaviors that protect health, such as purchasing costly nutritious food; or to seek treatment for health problems, preventing further health deterioration.

Estimating the protective marriage effect

The research on marriage and health acknowledges that any effect of marriage must be distinguished from selection into marriage on the basis of health or other characteristics (Musick and Bumpass 2012; Waite 1995). Early studies have analyzed cross-sectional associations between marriage and health (Ross et al. 1990; Umberson

1992), but this method is not sufficient to support a causal interpretation (Wood et al.

2007). Recently, studies have used within-person analyses of longitudinal data to obtain more valid estimates of the health effects of getting and staying married, relative to remaining single (Dupre and Meadows 2007; Guner, Kulikova, and Llul 2014; Williams et al. 2011). Their findings add important qualifiers to earlier reports of a health advantage accruing to married adults. For example, considering self-rated health, some studies taking advantage of longitudinal data report no benefit from the transition to marriage (Kohn and Averett 2014; Williams and Umberson 2004), whereas one study reports a marriage benefit that becomes apparent only around mid-life, but not earlier in the life course (Guner et al. 2014). Several studies point to duration in the married state and the number of marital disruptions as important moderators of the association between

marriage and health. Particularly, a history of divorce and shorter tenure in the married state detract from the marriage advantage of currently married adults, relative to their never-married peers (Dupre and Meadows 2007; Hughes and Waite 2009). Clearly, such analyses of longitudinal data counterweigh enthusiastic reports of a protective marriage effect (relative to remaining single) that were based on cross-sectional data (Waite 1995).

Estimation of the causal effect of marriage requires isolating this effect from marital selection on observed and unobserved characteristics, such as prior health (Fu and

Goldman 1996) or socioeconomic status (Shafer and James 2013). Recent studies have used longitudinal data to account for marital selection in several ways: with random- effects models (Guner et al. 2014); fixed-effects models (Musick and Bumpass 2012); and propensity score matching, which compares married people to their unmarried peers who had a similar likelihood of getting married (Williams et al. 2011). In this paper, I focus on the two methods that attempt to adjust for both observed and unobserved predictors of marriage. The first method is random-effects regression, which adjusts for a time-constant unobserved distribution of health across individuals. This method adjusts for selection in the narrow sense of selection on time-constant unobserved health characteristics that vary normally across the population (Guner et al. 2014). The second method is analysis of within-person change using fixed-effects regression, which nets out all influences of time-invariant characteristics, observed or not. This method takes a broader approach to the problem of selection on omitted variables, although at the cost of lower efficiency in model estimation (Musick and Bumpass 2012). By incorporating the possibility of selection on unobserved variables, both random-effects and fixed-effects

regression models lead to estimates of the marriage effect (relative to remaining never married) that tend to be more conservative than estimates obtained using ordinary regression models with panel data (Averett, Sikora, and Argys 2009; Averett et al. 2012;

Guner et al. 2014). Therefore, change in the marriage effect as estimated using random- effects or fixed-effects models is more plausibly due to a true change in the causal mechanisms linking marriage to health than the same change identified using other techniques.

In sum, studies of marriage effects on health have achieved increasing methodological sophistication over the past two decades. Contemporary work has attempted to isolate causal effects of marriage from selection into marriage, and has reported marriage has weak protective effects at best, and sometimes even adverse effects, depending on the health outcome being analyzed (Averett et al. 2012; Musick and

Bumpass 2012). For example, marriage does not benefit several measures of mental health (Musick and Bumpass 2012), and has an adverse effect on body mass and the risk of obesity (Averett et al. 2009). Other research notes that health benefits of marriage, relative to remaining never married, are attenuated for people in dysfunctional relationships (Hawkins and Booth 2005), single mothers (Williams, Sassler, and

Nicholson 2008), and people whose health is poor to begin with (Zheng and Thomas

2013). Despite many theoretical reasons for expecting a protective effect of marriage on health, recent studies are circumspect about the potential of marriage to protect health from declining over the life course (Guner et al. 2014; Kohn and Averett 2014).

Cohort change in the protective marriage effect

Recent studies’ mixed findings of health benefits from marriage may reflect demographic and cultural trends that have undermined the protective effects of marriage.

The first trend potentially undermining the marriage effect is the retreat from marriage

(Cherlin 2010). Fewer Americans than ever are getting married, and the age at first marriage is steadily rising (Qian 2013). This deferment of marriage means that young adults increasingly look to parents, friends, or their extended family to obtain the resources they might have gotten through marriage. For example, rather than moving in with a spouse, young adults increasingly live with their parents (South and Lei 2015) or unrelated roommates (Kreider and Vespa 2015), and may be exposed to other kinds of social control and social support that would protect health. Similarly, rather than relying on a spouse for the economic resources that may be used to protect health, young adults in recent cohorts are increasingly benefiting from the financial support of their parents

(Wightman et al. 2013). These trends show that singlehood is becoming more common— and arguably more normative—among young adults, and may not require foregoing social and economic advantages that have been ascribed to marriage.

The demographic retreat from marriage has been intertwined with a cultural shift in attitudes towards marriage, described as the deinstitutionalization of marriage (Cherlin

2004). Marriage has lost its monopoly on union formation, and indeed has been replaced by cohabitation as the usual type of first union (Cherlin 2010; Qian 2013). Cohabitation with a romantic partner offers some of the same benefits of social support and social control that previously were exercised most commonly in the institution of marriage

(Musick and Bumpass 2012). Not surprisingly, cohabiters’ health is often intermediate between single, non-cohabiting adults and married adults (Averett et al. 2012; Musick and Bumpass 2012). Although cohabiters account for few of the never-married at any given time, the transition to marriage has increasingly become a transition from cohabitation, compared to a transition from singlehood in past cohorts. This implies that becoming married is now a gradual process of couples moving in together and then deciding to get married. The drawn-out nature of this transition may be associated with more gradual changes in health as compared to the abrupt transition from single to married that was typical in past cohorts.

Importantly, these changes in the role of marriage in the life course have affected some groups more than others. Chances of marriage have been increasingly stratified by socioeconomic status, with the retreat from marriage being most acute among racial/ethnic minorities and people with low socioeconomic status (e.g., low educational attainment) (Cherlin 2010; McLanahan 2004). Reinforcing the concentration of marriage among the socioeconomically advantaged, economic security is increasingly seen as a prerequisite to marriage, and couples often delay marriage until they are confident in crossing this financial hurdle (Smock, Manning, and Porter 2005). The economic precariousness experienced by disadvantaged groups leads to particularly high skepticism about the wisdom of marrying, and is a major source of strains in marriages that are formed (Gibson-Davis, Edin, and McLanahan 2005). This exacerbation of the retreat from marriage among socially disadvantaged groups suggests that they have experienced a more rapid decline in the benefits of marriage to health, although this expectation

assumes some initial marital benefit to health—an assumption questioned by studies concentrating on marriage in disadvantaged populations (Harris, Lee, and DeLeone

2010).

Historical changes in the marriage rate and the cultural meaning of marriage in

American society have coincided with changes in health disparities between the married and never married. For example, Liu and Umberson (2008) report that the self-rated health of never-married men has improved in successive periods until it matched the health of married men, potentially due to improved access to economic resources among the never married, or the declining stigma of remaining single. Yet, temporal changes in marital health disparities have been analyzed predominantly using repeated cross- sectional data (Liu and Umberson 2008; Liu and Zhang 2013). Accounting for changing patterns of selection into marriage will clarify whether the causal effect of marriage on general health has in fact declined. I estimate the causal effect of marriage net of marital selection, and, building upon prior work, compare this effect across birth cohorts.

Specifically, I test for a decline in the protective effect of marriage on general health in more recent cohorts. Recognizing the uneven retreat from marriage, I then test whether the protective effect of marriage has declined more among racial minorities or people with low educational attainment, who had experienced especially rapid declines in chances of marriage. The findings of this study will establish a historical context for contemporary conclusions that there is little difference in general health between married and never married adults (Averett et al. 2012; Guner et al. 2014; Musick and Bumpass

2012). By explicitly testing for a change in the marriage effect across cohorts, I aim to

show whether a weak marriage effect on general health has emerged in recent cohorts, and whether it has weakened more dramatically for some socioeconomic groups than others.

Current study

Given the changing demographic and cultural contexts of marriage in the postwar period, and evidence of converging health disparities between married and never-married adults, I consider how the effect of first marriage (stratified by marital duration) on general health has changes across successive cohorts. Recognizing that marriage may take time to establish a protective effect on general health (Guner et al. 2014; Hughes and

Waite 2009), I test the following hypothesis:

H1: Marriage protects general health relative to remaining never married, with a stronger protective effect emerging at longer marital durations.

I elaborate on this hypothesis by considering how the marriage effect has changed over successive birth cohorts:

H2: In successive cohorts, the effects of marriage on general health, relative to remaining never married, have become weaker.

The retreat from marriage has been uneven in American society, and has been concentrated among racial minorities and people with low socioeconomic status. To examine if these groups also experienced the most rapid decline in the health benefits of marriage, I test the following hypotheses:

H3: In successive cohorts, the effect of marriage on general health, relative to remaining never married, declined more rapidly among non-Whites as compared to

Whites.

H4: In successive cohorts, the effect of marriage on general health, relative to remaining never married, declined more rapidly among people who did not complete a college degree as compared to college graduates.

Data and Methods

Data

I use data from the Panel Study of Income Dynamics (PSID). The PSID is a longitudinal survey of households that began in 1968 and continued yearly until 1997, when it switched to a bi-yearly interview schedule. It is unique in tracking members of respondent households after they leave to form their own households (e.g., an adult child moving out), and adding the new households to the sample. Consequently, the PSID covers many overlapping cohorts over a long period of time, in contrast to longitudinal surveys such as the National Longitudinal Surveys, which cover only a few cohorts, or surveys such as the 2006-2010 National Survey of Family Growth, which has followed respondents for less than a decade. For the purposes of this study, only 59,424 respondents related to people in the original PSID sample (i.e., core respondents) were considered for inclusion in the analysis. I constrain the analysis to 25,598 primary respondents (heads of household) and their spouses or partners who contributed data on respondent-rated health between 1984 and 2011. To analyze equally-spaced birth cohorts,

I exclude 11,508 individuals born before 1955 or after 1984. I also exclude 594

respondents who were only observed after their first marriage had already ended; 877 respondents who contributed no data on general health; and 246 respondents with missing data on covariates. Thus, the analytic sample included 12,373 individuals (6,222 men and

6,151 women) who contributed data on general health while being never married or in a first marriage. There were 85,118 observations in the person-year data set, indicating an average of over six observations of general health contributed by each respondent.

Outcome

The main dependent variable is respondents’ general health as measured on a five-point scale: 1 = excellent, 2 = very good, 3 = good, 4 = fair, and 5 = poor. In studies of marriage and health, this scale is commonly used as a holistic measure of general health that is highly predictive of later morbidity and mortality (Guner et al. 2014;

Hughes and Waite 2009; Williams and Umberson 2004). In the 1984-2011 interviews, the PSID asked the head of household to rate both their own and their spouse’s health.

Spouse-rated health has not been evaluated as extensively as self-rated health, but some evidence suggests it is as predictive of mortality as self-rated health (Ayalon and

Covinsky 2009).

Marital status

The main independent variable is marital status at each interview, as calculated from marriage dates in the 1985-2011 PSID marital history file. Using the start and end dates for the first marriage and censoring observations after the end of a first marriage, I construct a time-varying measure of marital status. This variable distinguishes between being never married; being in a first marriage formed 0-4 years ago; being in a first

marriage formed 5-9 years ago; and being in a first marriage formed 10 or more years ago. This measure addresses Hypothesis 1 by distinguishing between recent and established marriages, such that the protective effect of marriage (relative to remaining never married) may be cumulative over the duration of the marriage (Dupre and

Meadows 2007). An alternative specificaiton of the marriage variable as a continuous measure of duration in the first marriage (equaling zero in never-married observations) led to the same findings as the analysis reported below.

Birth and marriage cohorts

Birth cohorts from 1955-1984 are adequately represented in the sample of PSID respondents observed to enter a first marriage (or remain never married) between 1984 and 2011. I divide the sample into three birth cohorts in ten-year increments: 1955-1964;

1965-1974; and 1975-1984. To illustrate the timing of marriage in each birth cohort, I divide the sample into four marriage cohorts based on the date of the first marriage: earlier than 1985; 1985-1994; 1995-2004; and 2005 or later. As birth cohort and marriage cohort are strongly correlated, I focus on changes in the marriage effect across birth cohorts in the regression analysis.

Plan of analysis

I analyze the data by first describing the distribution of birth and marriage cohorts in the sample, and by describing the distribution of general health status, marital status, and covariates across gender and birth cohort. Next, I fit random-effects and fixed-effects regression models estimating general health (rated on a five-point scale) as a function of time-varying marital status and control variables. Time-invariant covariates include birth

cohort and race, coded as White, Black, or other. Time-varying covariates include linear and quadratic age terms, representing a potentially non-linear relationship between age and respondents’ rating of their health (Chen, Cohen, and Kasen 2007); educational attainment, operationalized as a dichotomous measure of college completion by a given year; and fertility, operationalized as a dichotomous measure of having had any children by a given year.

The random-effects model includes an “innate permanent component” of the error term that is assumed to be normally distributed among individuals. This portion of the error may be correlated with marital status in a way that captures some aspects of self- selection into marriage (Guner et al. 2014). The fixed-effects model nets out all observed and unobserved differences between respondents, and estimates within-person change in general health as a function of change in marital status. As respondents who never marry during the course of the study do not contribute to the estimation of the marriage coefficients in the fixed-effects models, I excluded them from the estimation sample for the fixed-effects analysis. Both the random-effects and fixed-effects models test

Hypothesis 1 by estimating whether increased time spent in a first marriage implies a slower decline in general health over the life course, relative to remaining never married.

I also estimate ordinary least squares (OLS) models with robust standard errors to offer a point of comparison by assessing marital disparities and cohort trends in general health without adjusting for selection.

These analyses capture the average marriage effect across all cohorts, and set the stage for examining cohort variation in the marriage effect. Interactions between birth

cohort and marital status are added to each random-effects or fixed-effects model, with the earliest birth cohort as the reference group. Therefore, in the models including birth cohort interactions, the main effects of marital status now represent the relationship between marriage and health in the earliest cohort, whereas interactions between marital status and birth cohort describe how this relationship changes in subsequent cohorts.

Comparisons between the first and middle cohort and the first and last cohort are done separately because results for the most recent birth cohort may be confounded by the lack of data on long-term marriages in this cohort. These models test whether successive cohorts exhibit diminished health benefits of accumulating time in a first marriage, relative to remaining never married (Hypothesis 2). To test for heterogeneity in the decline of marriage benefits to health (Hypotheses 3 and 4), I repeat the fixed-effects models for subgroups defined by race (White vs. non-White) or educational attainment

(college graduates vs. others). All models are estimated separately by gender, to account for a potentially steeper decline in the marriage effect among men (Liu and Umberson

2008).

Results

Table 9 summarizes birth and marriage cohorts represented in the analytic sample.

In each ten-year birth cohort, most first marriages fall within a 20-year span, with a few very late first marriages in the 1955-1964 birth cohort, and a few early first marriages in the 1975-1984 birth cohort. Despite historical trends towards increasing age at first marriage in the postwar era (Cherlin 2010), there is clear clustering of cases in the analytic sample on the diagonal beginning with pre-1985 marriages among the 1955-

1964 birth cohort. In other words, the modal year range of marriage increases by about ten years for each ten-year increment in birth cohort, implying strong correlation between birth cohort and marriage cohort in this sample. Table 9 also shows a growing proportion of each cohort remaining never married: from 24% in the earliest cohort to 38% in the most recent cohort. Although this increase is partially due to lack of information about later marriages in the most recent cohort, additional analyses find a more pronounced increase among racial minorities. Specifically, comparing the 1975-1984 cohort to the

1955-1964 cohort, the percent remaining never married increased by 10 points among

Whites and 23 points among non-Whites. Furthermore, the decline in the proportion of never married across cohorts was more pronounced among people who did not graduate from college (16 points) than among people who completed a college degree (14 points).

Table 9. Number of cases and observations in each combination of birth and marriage cohort, 1984-2011 PSIDa

Marriage cohort Never Birth cohort < 1985 1985-1994 1995-2004 ≥ 2005 married Total 2,052 1,407 265 49 1,187 4,960 1955-1964 (23,524) (13,574) (2,275) (390) (9,242) (49,005)

82 1,426 1,160 179 1,030 3,877 1965-1974 (584) (10,558) (6,614) (887) (5,330) (23,973)

0 44 1,116 1,023 1,353 3,536 1975-1984 (0) (178) (4,747) (2,933) (4,282) (12,140)

2,134 2,877 2,541 1,251 3,570 12,373 Total (24,108) (24,310) (13,636) (4,210) (18,854) (85,118) a Each cell contains the number of cases followed by the number of observations in parentheses.

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Table 10 describes the characteristics of each birth cohort separately for men and women in the sample. In all cohorts, the mean and median values of general health correspond to a health rating of “very good,” or the second-best possible rating on the five-point scale. The distributions of responses to the general health question are likewise similar across birth cohorts among both men and women. Importantly, Table 10 does not show health disparities between the married and never married, or how these disparities have changed across birth cohorts—these questions are answered below using regression analysis. In later birth cohorts, fewer respondents are observed to marry, although this is likely due to the most recent cohort being censored before some delayed first marriages could be observed. Table 10 shows an increase in the percent of respondents who have ever completed a college education across birth cohorts, reflecting a broader trend of increasing participation in higher education.

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Table 10. Descriptive statistics by birth cohort, 1984-2011 PSID

Men Women Birth cohort Birth cohort 1955-1964 1965-1974 1975-1984 1955-1964 1965-1974 1975-1984 (n = 2,529) (n = 1,959) (n = 1,734) (n = 2,431) (n = 1,918) (n = 1,802) Mean Mean Mean Mean Mean Mean % (SD) % (SD) % (SD) % (SD) % (SD) % (SD) General health 2.0 2.0 2.0 2.2 2.1 2.2 1-5 scalea (1.0) (0.9) (0.9) (1.0) (0.9) (0.9) Excellent 36.8 38.1 36.7 29.2 33.4 27.7 Very good 35.3 34.9 35.2 35.5 35.0 38.4 Good 21.1 21.7 22.4 27.0 25.4 25.8 Fair 5.7 4.3 4.9 7.5 5.4 7.4 Poor 1.2 1.0 0.8 0.8 0.7 0.8 102 Marital status

Entered first marriage 73.3 71.0 58.7 78.9 75.9 64.7 26.0 26.2 25.3 24.7 24.4 24.2 Age at first marriageb (5.6) (5.0) (3.5) (6.3) (5.0) (3.7) 22.9 13.9 6.9 23.0 14.3 6.9 Years in first marriageb (9.0) (6.7) (3.9) (9.9) (7.4) (4.3) Race White 58.5 62.8 63.1 54.8 60.9 61.4 Black 39.0 33.7 34.3 42.7 36.4 36.0 Other 2.5 3.5 2.6 2.5 2.7 2.6 Ever completed college 21.0 23.1 28.0 23.2 28.9 36.1 Ever had children 72.2 69.8 62.7 82.4 79.1 70.9 a 1 = Excellent, 2 = Very good, 3 = Good, 4 = Fair, 5 = Poor b Among respondents who have ever entered a first marriage.

In Table 11, the relationship between marital status and health is estimated for all cohorts together. The OLS models show that any duration of marriage is significantly associated with a better (i.e., lower) score on the general health scale. Among both men and women, random-effects models also find that any duration of a first marriage is associated with improved general health (i.e., a negative coefficient) relative to remaining never married, but the magnitude of the marriage effects is one-third to one-half smaller than the OLS estimates. This means that failing to account for selection into marriage inflates the observed disparity in general health between the married and never married.

Furthermore, the strongest protective effect of marriage is seen in the category of being married for 10 or more years, supporting Hypothesis 1 by showing that the protective effect of marriage on general health accumulates over time. Yet, the protective effect of marriage does not imply that general health actually improves over the course of a marriage. For example, among men, a ten-year increase in age is associated with an 0.30 increase in the general health scale (where higher values indicate worse health), and is only partially counteracted by a 0.12 decrease in this scale associated with being married for 10 or more years. Among women, there is a non-linear relationship between age and general health, such that health declines faster at older ages, but the same pattern holds: health gets worse with age at a rate outpacing any protective effect of remaining in a first marriage.

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Table 11. Unstandardized coefficients from OLS, random effects and fixed effects regressions of respondent-rated health on marital status, by gender

Men Women

Random Fixed Random Fixed OLS effects effectsa OLS effects effectsa Marital statusb Never married (ref.) ------Married 0-4 years -0.16*** -0.08*** 0.02 -0.14*** -0.08*** -0.04 Married 5-9 years -0.16*** -0.09*** 0.03 -0.10** -0.05** 0.00 Married 10+ years -0.21*** -0.12*** 0.03 -0.15*** -0.11*** -0.06*

Birth cohort 1955-1964 (ref.) ------1965-1974 0.00 0.01 - 0.00 0.01 - 1975-1984 0.07** 0.08** - 0.11*** 0.11*** -

Race White (ref.) ------Black 0.18*** 0.15*** - 0.29*** 0.25*** - Other -0.04 0.00 - 0.12 0.08 -

Age Linear term 0.03*** 0.03*** 0.02*** 0.00 0.01* 0.01 Squared term 0.00 0.00 0.00 0.0003** 0.0002** 0.0002*

Completed collegeb -0.41*** - 0.31*** 0.03 -0.34*** - 0.25*** - 0.08* Had childrenb -0.04 0.00 0.01 0.04 0.03 0.00

Rho 0.46 0.54 0.47 0.73 Cases 6,222 6,222 4,262 6,151 6,151 4,541 Observations 41,143 41,143 32,032 43,975 43,975 34,232 a Fixed effects models are limited to respondents who ever married during the study. b Time-varying covariate. * p < .05; ** p < .01; *** p < .001, two-tailed tests.

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Whereas random-effects models in Table 11 suggest that a first marriage is protective of health, and more so at longer durations of marriage, the fixed-effects models only partially support this finding. Among men who have ever married, there are no statistically significant differences in general health across time-varying marital status, implying that when all time-invariant differences are held constant, married men are not healthier than if they would have remained unmarried. Importantly, only respondents who eventually married in the course of the study contributed never-married observations to the reference group in the fixed effects model, whereas never-married observations from respondents who were never observed to marry were excluded from this model.

Among women, the fixed-effects model finds no statistically significant protective effect of being married for 0-9 years, but a modest protective effect of being married for 10 years or more. For both men and women, the fixed effects results suggest that the random-effects model does not fully account for marital selection, and that the within- person effects of marriage on general health are substantially more modest when selection on all time-invariant characteristics is taken into account.

Other results in Table 11 show that general health is slightly worse in the most recent birth cohort than in the earliest birth cohort, as indicated by positive coefficients on the 1975-1984 birth cohort in the OLS and random effects models for both men and women. This decline in general health represents an average including both people who married and people who remained never married, and does not address different trends in general health between these groups, which are estimated below. It may also reflect period trends in general health, which are not considered here. In the entire sample,

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sociodemographic disparities in health are as expected, with Black respondents having significantly worse general health than White respondents, and with college completion being associated with a statistically significant improvement in general health.

The health disparity between the married and never married is evident in the pooled sample of three birth cohorts when estimated using OLS, but using random effects or fixed effects models shows that the marriage effect on general health accounts for only a fraction of this disparity. Table 12 investigates how general health in the married and never married groups changes across birth cohorts, and what this implies for cohort change in the protective effect of marriage. This table adds interactions between birth cohort and marital status to the models estimated in Table 11. Now, the main effect of birth cohort reflects change in mean general health among the never-married group. OLS regression suggests that there are no significant differences in the health of the never married across birth cohorts, although random effects regression suggests that among both men and women, the never married were slightly less healthy in the 1975-1984 birth cohort than in the 1965-1974 birth cohort.

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Table 12. Unstandardized coefficients from OLS, random effects and fixed effects regressions of respondent-rated health on marital status interacted with birth cohort, by gender

Men Women Random Fixed Random Fixed OLS effects effectsa OLS effects effectsa Marital statusb Never married (ref.) ------

Married 0-4 years -0.19*** -0.08*** 0.05 -0.18*** -0.08*** -0.02 x born 1965-1974 0.05 -0.01 -0.05 0.08 0.00 -0.03 x born 1975-1984 0.04 0.00 -0.03 0.10* 0.01 -0.01

Married 5-9 years -0.18** -0.08** 0.06 -0.14*** -0.05* 0.01 x born 1965-1974 0.04 -0.02 -0.06 0.09 0.00 -0.03 x born 1975-1984 0.04 0.00 -0.03 0.07 0.00 -0.01

Married 10+ years -0.25*** -0.14*** 0.03 -0.20*** -0.15*** -0.08* x born 1965-1974 0.16** 0.10** 0.05 0.16** 0.11** 0.08 x born 1975-1984 -0.01 -0.01 -0.06 0.11 0.14* 0.15*

Birth cohort 1955-1964 (ref.) ------1965-1974 -0.05 0.00 - -0.08 -0.01 - 1975-1984 0.04 0.07* - 0.04 0.09** -

Race White (ref.) ------Black 0.18*** 0.15*** - 0.29*** 0.25*** - Other -0.04 0.00 - 0.12 0.08 -

Age Linear term 0.02** 0.03*** 0.02** -0.01 0.00 0.00 Squared term 0.00 0.00 0.00 0.0003*** 0.0002*** 0.0002**

Completed collegeb -0.41*** -0.32*** 0.03 -0.34*** -0.26*** -0.09* Had childrenb -0.04 0.00 0.00 0.03 0.02 0.00

Rho 0.46 0.54 0.47 0.56 Cases 6,222 6,222 4,262 6,151 6,151 4,541 Observations 41,143 41,143 32,032 43,975 43,975 34,232 a Fixed effects models are limited to respondents who ever married during the study. b Time-varying covariate. * p < .05; ** p < .01; *** p < .001, two-tailed tests.

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Interactions between marital status and birth cohort describe the extent to which the married group’s cohort trend in general health deviates from the trend observed in the never married group. For example, summing the main effect for the 1965-1974 birth cohort with the interaction between this cohort and the long-term married group shows the extent to which general health in this group changed from the earliest to the middle cohort. Among long-term married men and women, general health declined from the first to the second cohort, with corresponding increases in the general health scale of 0.10 (p <

0.01) and 0.09 (p < 0.01) points. This decline in the general health of the long-term married outpaced the change in general health estimated for the never married group, meaning that the married group became less healthy whereas the never married group’s health remained the same or declined at a slower rate.

Interactions between marital status and birth cohort also reveal how marital status effects vary across cohorts. There are no significant variations in the effects of being in a first marriage for 0-4 or 5-9 years across cohorts, although, in the fixed-effects models, these marital durations were not associated with a protective health effect even in the earliest birth cohort. Among both men and women, the random-effects models show that the initial protective effect of long-term marriage (10 or more years) is significantly attenuated in later cohorts, particularly the 1965-1974 birth cohort for men and the 1965-

1974 and 1975-1984 birth cohorts for women. Likewise, the fixed-effects model fitted to the women’s subsample shows a statistically significant protective effect of long-term marriage in the earliest cohort, but a statistically significant and complete attenuation of this effect in the most recent cohort. The decline in the protective effects of marriage in

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later birth cohorts is another way of interpreting the earlier observation that general health is declining across cohorts faster in the married group than among the never married.

Table 12 suggests that protective effects of marriage—particularly, long-lasting first marriage—are declining across cohorts, but this decline may be more pronounced in groups that experienced a more rapid retreat from marriage. In Table 13, I fit fixed effects models identifying cohort change in the marriage effect separately for White and non-

White men and women. The only protective effect of marriage is evident in the earliest cohort among White women, when comparing being married for 10+ years to remaining single. This effect disappears in the most recent cohort, as indicated by the positive and significant interaction term. Taken literally, Hypothesis 3 is not supported—a decline in the marriage effect is observed among White women but not non-White women. But, putting this finding in the context of marriage effects in the earliest cohort, it is clear that the health of non-White women did not improve due to marriage in any of the cohorts in this study. Among White men, non-White men, and non-White Women, there is no evidence of statistically significant marriage benefits in the earliest cohort, making it implausible that the protective effect of marriage should have declined across successive cohorts in these groups.

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Table 13. Unstandardized coefficients from fixed effects regressions of respondent-rated health on marital status interacted with birth cohort, by gender and racea

Men Women

White Non-White White Non-White Marital statusb Never married (ref.) - - - -

Married 0-4 years 0.06 0.02 - 0.03 - 0.02 x born 1965-1974 -0.06 -0.04 -0.05 0.01 x born 1975-1984 -0.06 0.04 -0.03 0.03

Married 5-9 years 0.07* 0.03 - 0.01 0.04 x born 1965-1974 -0.07 -0.05 -0.05 0.04 x born 1975-1984 -0.05 0.01 0.02 -0.08

Married 10+ years 0.05 0.00 - 0.09* - 0.07 x born 1965-1974 0.08 -0.04 0.09 0.05 x born 1975-1984 -0.06 -0.09 0.20* -0.07

Age Linear term 0.01* 0.03** 0.00 0.02 Squared term 0.00 0.00 0.0003*** 0.00

Completed collegeb 0.04 - 0.06 - 0.05 - 0.18* Had childrenb 0.02 -0.07 -0.01 0.07

Rho 0.56 0.50 0.57 0.51 Cases 2,849 1,413 3,026 1,515 Observations 22,637 9,395 23,526 10,706 * p < .05; ** p < .01; *** p < .001, two-tailed tests. a Fixed effects models are limited to respondents who ever married during the study. b Time-varying covariate.

Lastly, I examine if fixed-effects estimates of the marriage effect declined across cohorts faster among people who did not attend college as compared to college graduates.

The results in Table 14 suggest that among women, this was indeed the case, supporting

Hypothesis 4. Considering the earliest birth cohort, the only protective effects of marriage were evident for recent and long-term marriages among women who did not complete college. Yet, in the most recent cohort, there was a statistically significant attenuation of 110

the benefit of long-term marriage, as indicated by the statistically significant interaction between long-term marriage (being married 10+ years vs. remaining never married) and the 1975-1984 birth cohort.

Table 14. Unstandardized coefficients from fixed effects regressions of respondent-rated health on marital status interacted with birth cohort, by gender and educational attainmenta

Men Women Ever Did not Ever Did not completed complete completed complete college college college college Marital statusb Never married (ref.) - - - -

Married 0-4 years 0.00 0.08* 0.11* - 0.08* x born 1965-1974 -0.06 -0.05 -0.04 -0.05 x born 1975-1984 0.07 -0.07 -0.10 0.00

Married 5-9 years - 0.01 0.10* 0.14** - 0.04 x born 1965-1974 -0.05 -0.06 -0.08 -0.03 x born 1975-1984 0.02 -0.05 -0.15 0.05

Married 10+ years - 0.01 0.07 0.08 - 0.15** x born 1965-1974 0.01 0.07 0.02 0.09 x born 1975-1984 0.11 -0.12 -0.01 0.19*

Age Linear term 0.03** 0.01 0.00 0.00 Squared term 0.00 0.0002* 0.0003* 0.0002**

Had childrenb 0.03 0.00 0.01 0.01

Rho 0.53 0.52 0.56 0.55 Cases 1,151 3,111 1,434 3,107 Observations 9,546 22,486 10,884 23,348 * p < .05; ** p < .01; *** p < .001, two-tailed tests. a Fixed effects models are limited to respondents who ever married during the study. b Time-varying covariate.

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In sum, long-term marriage had some protective effects, compared to remaining never married, in an early cohort of Baby Boomers. But, the protective effects of marriage weakened in more recent cohorts, particularly in the case of the difference in health between people in long-term marriages and people who remain never married.

Further analysis by race and educational attainment revealed that declines in the marriage effect were concentrated among White women and women without a college degree. In other subgroups, there were no protective effects of marriage even in the earliest cohort.

Although the trend in the marriage effect among cohorts preceding the Baby Boom can only be speculated on, it is clear that birth cohorts younger than those included in this study start from a baseline where marriage has weak if any protective effects on general health.

Discussion

Theoretical expectations that marriage should protect health, relative to remaining never married, have motivated many studies to use increasingly sophisticated methods to isolate causal effects of marriage from marital selection processes (Wood et al. 2007). In the case of general health, as rated by respondents themselves, recent studies have found the marriage effect to be weak or absent (Averett et al. 2012; Guner et al. 2014). These findings of a modest marital effect on general health must be understood in the historical context of the deinstitutionalization of marriage. The institution of marriage has been dramatically altered by declining marriage rates, the concentration of marriage among the affluent, and changing cultural ideas about how married people should behave and be treated by others (Cherlin 2004, 2010). In this paper, I have argued that these trends all

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ultimately suggest a weakening of the causal effect of marriage. Using random effects and fixed effects regression to estimate the protective marriage effect, I found that this effect was strongest for long-standing marriages lasting 10 or more years in the earliest cohort (Americans born between 1955 and 1964). Yet, this protective effect of long-term marriage was undone in later birth cohorts (1965-1974 and 1975-1984) among both men and women. This finding was consistent with the hypothesized decline of the protective marriage effect across successive cohorts.

Weak or null marital effects on general health have precedent in prior work.

Several studies have reported that, compared to remaining single, getting and staying married does not improve self-rated general health (Kohn and Averett 2014; Musick and

Bumpass 2012; Williams and Umberson 2004). Guner and colleagues (2014), using the same PSID data set as the present study, find that insofar as marriage has a protective effect on general health, this effect does not emerge until people are well into middle age, consistent with the present findings that the most beneficial marriages appear to be the longest-lasting ones. Findings from the present study link this corpus together by showing that the protective effect of marriage on general health has declined over the past four decades, and, when estimated using fixed-effects models, may have been largely chimerical in even the earliest of these birth cohorts.

What may explain the absence of a protective marriage effect in recent cohorts?

Prior work has discussed declining stigma of remaining never married and greater resources available to the unmarried as potentially driving a weakening association between marriage and self-rated health (Liu and Umberson 2008). Other reasons for a

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weakening marriage effect may be related to a secular decline in marital quality between

1980 and 2000, stemming from the deinstitutionalization of marriage and greater economic strains placed on couples expected to maintain dual incomes (Amato et al.

2003). Certainly, perceived work-family conflict has increased in the closing decades of the 20th century (Jacobs and Gerson 2001; Nomaguchi 2009), and spouses’ actual time spent together has decreased over the same period (Dew 2009). Against a backdrop of greater demands at home and at work, and less time spent together, today’s married couples may indeed experience marriage more as a source of conflict and stress than as a

“haven in a heartless world” (Lasch 1977) that safeguards their health.

The heterogeneity of the marriage effect has received some attention in recent studies, which emphasize the uncertain benefits of marriage among racial/ethnic minorities and socioeconomically disadvantaged groups (Harris et al. 2010; Kroeger-

D’Souza 2012; Williams et al. 2011). As these groups experienced the most rapid retreat from marriage, I examined if they had also experienced more pronounced declines in the health benefits of getting married, as compared to remaining never married. In fact, the pattern that emerged was that whichever subgroup exhibited a protective marriage effect in the earliest cohort also exhibited a decline in the marriage effect across cohorts. For example, the retreat from marriage was more rapid among non-White women, but only

White women exhibited a protective marriage effect in the early cohort—and a decline in this effect in subsequent cohorts. By the same token, only women without a college education had an estimated marriage benefit to health in the early cohort, and this group was also the only one (when dividing the sample by gender and educational attainment)

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to experience a decline in the marriage effect. Thus, despite increasing socioeconomic disparities in chances of marriage, the present study suggests that recent cohorts experience convergence to a weak if non-existent marriage effect across all groups.

The protective effect of marriage represents only one possible explanation for marital health disparities. In this study, the health advantages of the married groups relative to the never married were substantially greater when estimated using OLS regression without adjustment for selection into marriage. Consistent with prior work, this implies that marital selection accounts for a substantial share of the marital disparity in general health (Guner et al. 2014; Kohn and Averett 2014). Yet, the role of marital selection in creating health disparities between married and never married adults raises the question of whether these selection processes are growing stronger or weaker.

Although prior studies have demonstrated that health problems and unhealthy behaviors limit the prospects of marriage (Fu and Goldman 1996; MacInnes 2011), it is unknown whether the role of health factors in predicting marriage has changed over time. The accelerated retreat from marriage among socioeconomically disadvantaged groups

(Cherlin 2010) suggests a pattern of intensifying marital selection (on socioeconomic status, a correlate of good health) across successive cohorts. Yet, stronger marital selection may not be enough to counter the weakening marriage effect. Therefore, overall disparities in general health between the never married and married would decline over time, as reported in prior research (Liu and Umberson 2008) and as shown in this study using OLS regression.

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When the health benefits of marriage are narrowly defined as benefits to respondent-rated general health, the picture is bleak: marriage had modest (if any) protective effects for early cohorts, and the marriage effect has weakened to the point of vanishing in recent cohorts. It is possible that the particular outcome studied here, or the methods used to estimate the marriage effect, makes this conclusion unduly pessimistic.

Marriage benefits some aspects of health more than others, and if it does not benefit physical health (as rated by respondents), it may still benefit mental health (Averett et al.

2012; Musick and Bumpass 2012), health behaviors (Merline et al. 2008) or objective measures of specific health conditions (McFarland et al. 2013). Yet, weak effects of marriage on general health temper any benefit it may have for other dimensions of health.

Furthermore, married adults tend to over-estimate their own general health (Zheng and

Thomas 2013). Thus, marriage should at least predict better respondent-rated health owing to this response bias. The absence of such a protective effect means that any overestimation of general health in the married group, or any benefits of marriage accruing to other health-related outcomes, are not strong enough to overcome the lack of a marriage benefit to this holistic measure of health.

A related concern is whether fixed-effects analysis is overly biased against finding a protective effect of marriage. Certainly, fixed-effects estimates of marriage influences on health tend to be more conservative and less efficient than OLS estimates

(Averett et al. 2009, 2012). But the lack of evidence for a protective marriage effect on general health is not unique to studies using fixed-effects regression. Other analytical approaches have also found no such effect (Kohn and Averett 2014; Williams and

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Umberson 2004). In the present study, random-effects estimates of marriage benefits in the early cohort were indeed larger than estimates of the protective marriage effect from fixed-effects regression, but the pattern of a weakening marriage effect was observed with either modeling strategy. Indeed, as marriage initially appeared to have a stronger protective effect in the random-effects models, the decline in the marriage effect across successive cohorts was more pronounced with this model specification than in fixed- effects regression. Therefore, a variety of analytic techniques have converged on the conclusion that, in recent cohorts, general health is largely unresponsive to getting and staying married.

In the U.S., change in the institution of marriage has been both swift and far- reaching. With marriage effects on health being a flashpoint for debates over marriage promotion policy, recent research has investigated how marital disparities in various dimensions of health have evolved across successive decades (Liu 2009; Liu and

Umberson 2008; Liu and Zhang 2013). Marital selection poses a difficulty in interpreting these findings, as it is unclear whether changing health disparities across marital status are due to changing patterns of selection or changes in the causal effects of marriage. The present study addresses this uncertainty by applying methodological insights from recent work on the causal health effect of marriage (Guner et al. 2014; Musick and Bumpass

2012) to the problem of identifying historical trends in the relationship between marriage and health. In an analysis of cohorts marrying between the 1980s and the 2000s, overall disparities in general health between the married and never married groups were shown to be declining, even before accounting for selection. The effect of marriage on general

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health has also declined over time, and has been modest even in the earliest cohort in the analysis. In short, the declining protective effect of marriage is driving the convergence between the married and never married with respect to general health, and appears to be overwhelming any concurrent increase in marital selection on the basis of health status or health-related characteristics. These findings give further reason for skepticism about marriage promotion and the role of marriage as an instrument of enhancing the public health. If marriage has ceased to protect Americans’ health in the past, there is little reason to expect it will do so in the future.

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Chapter 5: Conclusion

Declining marriage rates and changing cultural perceptions of marriage in

American society have sparked debate over whether and how marriage matters in people's lives (Waite 1995). The association between marriage and improved health, relative to remaining never married, figures prominently in arguments for the continued importance of marriage and justifications for marriage promotion initiatives (Waite and

Gallagher 2000). Yet, associations between marital status and health have changed as marriage has become deinstitutionalized (Liu and Umberson 2008). For some aspects of health, the disparity between married and never married is growing, but for other aspects of health, this gap is shrinking (Liu and Umberson 2008; Liu 2009; Liu and Zhang 2013).

In this dissertation, I explored trends in the relationship between marriage and health with an emphasis on distinguishing between changes in marital selection and changes in the protective effects of marriage. Synthesizing the analyses of Chapters 2-4, the results show that the protective effect of marriage (relative to being never married) on general health is growing weaker, although marital selection on some health characteristics has increased.

These conclusions contradict the public-health rationale for marriage promotion, and suggest that disparities in relationship formation by health status may be a concern in recent cohorts.

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This dissertation contributes to the literature on marriage and health by joining recent work on trends in the relationship between marriage and health (Liu and

Umberson 2008; Liu and Zhang 2013) with a corpus of studies pursuing increasingly sophisticated approaches to isolate causal effects of marriage from patterns of marital selection (Averett et al. 2012; Musick and Bumpass 2012; Williams et al. 2011).

Throughout this dissertation, I have pursued multiple strategies of teasing out selection or causal effects, as appropriate. For example, a theoretical emphasis on marital selection informed the choice of dependent variable in Chapter 2 and the operationalization of the independent variable in Chapter 3, as both smoking initiation and childhood-onset disability tend to occur prior to a person's first marriage. In Chapter 4, on the other hand, a theoretical emphasis on the causal effects of marriage justified using fixed-effects regression to net out selection into marriage on time-invariant characteristics. Although these strategies have not completely separated selection from causation in each analysis, the findings of the three chapters suggest novel conclusions about historical change in marital selection on smoking behavior (Chapter 2) and disability status (Chapter 3), and historical change in the protective effect of marriage on general health (Chapter 4).

In the case of smoking, stigmatization of this behavior—spurred by public health campaigns in recent decades—has turned it into a social liability (Stuber et al. 2008,

2009). Smokers feel excluded from public spaces and report experiencing the disapproval of others (Bell et al. 2010a,b). As Chapter 2 shows, this exclusion extends to the marriage market, with an increasing disparity in lifetime smoking initiation between the married and never married. While antismoking campaigns have succeeded in reducing the

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prevalence of smoking (Farrelly et al. 2013), this reduction was more pronounced in the married group relative to the never married. Data limitations precluded a strict test of marital selection on the basis of lifetime smoking initiation, but these results were consistent with exacerbated delay of marriage among people who have ever smoked. In other words, the encouragement of anti-smoking stigma may have had an unintentional side effect of amplifying marital disparities in smoking by making smokers less likely to marry.

Chapter 3 addresses a different kind of stigma in the marriage market—the stigmatization of people with disabilities (MacInnes 2011). Focusing on childhood-onset disabilities to establish causal order between disability onset and first marriage, this chapter finds that from the 1970s onwards, people with childhood-onset disabilities became less likely to marry—at a rate outpacing the overall decline in marriage during these years. There was a slight reversal of this trend following the 1990 enactment of the

Americans with Disabilities Act, but in the most recent decade there continued a clear divergence in marriage odds between young adults with childhood-onset disabilities and their peers. In this case, despite major policy efforts to improve the social integration of people with disabilities (National Council on Disability 2010), childhood-onset disability appears to have become a greater liability on the marriage market than it had been four decades ago. This finding again shows an unintended and unforeseen divergence in chances of marriage according to a marker of health status.

In Chapter 4, I turn to the question of change in the causal effect of marriage. I examine how time spent in a first marriage protects the general health of three cohorts

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relative to remaining never married. Taking advantage of longitudinal data available for multiple birth cohorts, I use random-effects and fixed-effects models to estimate the causal effect of marriage (Guner et al. 2014; Musick and Bumpass 2012). Among both men and women, protective effects of marriage diminish in more recent cohorts, relative to an early cohort of Baby Boomers. This decrease in the protective effect of marriage appears to be driving an overall convergence in general health between the married and never married, as estimated using OLS regression. Whereas results from Chapters 2 and 3 suggests marital disparities in health may have increased due to intensifying selection, the findings of Chapter 4 indicate a contrary pattern of diminishing marital disparities in health due to weakening health effects of marriage. Recent studies have argued that a weak effect of marriage on health undermines the rationale for using marriage promotion to improve public health (Liu and Umberson 2008; Musick and Bumpass 2012). Chapter

4 lends further support to this conclusion, and places it in the context of historical decline in the marriage effect coinciding with the deinstitutionalization of marriage.

Together, Chapters 2-4 indicate that marriage no longer appears to protect general health, but marital selection on some health characteristics is becoming stronger. The latter finding notwithstanding, selection on general health status has not become strong enough to outweigh the diminished protective effects of marriage on this outcome, resulting in a net convergence in general health between married and never married adults. The concurrent decline of the protective effect and rise of selection mechanisms calls for reconsidering the theoretical relationship between marriage and health. Early work in this area emphasized health outcomes of marriage (Umberson 1987). This

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framing reflects the expectation that marriage offers a variety of benefits over remaining never married (Lasch 1977). The deinstitutionalization of marriage has confounded this expectation by making the never married status more common and less stigmatized

(Cherlin 2010), and by offering never-married people other ways to reap the benefits of a romantic relationship (Musick and Bumpass 2012), including cohabitation and living apart together. Furthermore, the deinstitutionalization of marriage has turned it into a capstone transition that is seen as contingent on certain prerequisites such as economic security (Smock et al. 2005). In this sense, marriage is a “prize,” and characteristics such as college completion and stable employment increase the chances of winning it.

According to the findings of Chapters 2-3, health behaviors and health characteristics increasingly figure in the quest for marriage (Janus 2009). Growing exclusion of less- healthy people from marriage suggests that the roles of marriage and health have switched, with good health primarily relating to marriage as its determinant, not its consequence.

The conclusions of this dissertation are limited in ways that point towards future research opportunities. First, the trends described above apply to different aspects of health, and were identified using different data sets, each differing in its sampling strategy, question wording, and availability of data on confounding characteristics. The synthesis of these findings—that marital selection has overtaken protective health effects of marriage as a source of marital disparities in health—should be tested for a single health outcome across as broad a time span as feasible. Second, Chapters 2 and 3 pointed out the effects public policy may have on health disparities across marital status, but did

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not take advantage of state or local variation in the implementation of these policies to better estimate their consequences for the relationship between marriage and health.

Third, the results of this dissertation have focused on the comparison between married and never married adults, but (particularly in Chapters 3 and 4) gave less attention to trends in the relationship between divorce and health. As prior work shows that divorce is becoming more strongly associated with poor health (Liu and Umberson 2008; Liu

2012), future research should examine if this trend is due to increased adverse effects of divorce, or increasing selection of less-healthy people out of marriage.

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