Social Science & Medicine 108 (2014) 60e67
Contents lists available at ScienceDirect
Social Science & Medicine journal homepage: www.elsevier.com/locate/socscimed
Early life conditions, partnership histories, and mortality risk for Swedish men and women born 1915e1929 Robyn Donrovich a, *, Sven Drefahl b, Ilona Koupil c a
Family and Population Studies (FaPOS), Centre for Sociological Research, KU Leuven, Parkstraat 45-Box 3601, 3000 Leuven, Belgium Demography Unit, Department of Sociology, Stockholm University, Stockholm, Sweden c Center for Health Equity Studies, Stockholm University/Karolinska Institutet, Stockholm, Sweden b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 28 August 2013 Received in revised form 18 February 2014 Accepted 21 February 2014 Available online 24 February 2014
This paper investigates the relationship between early life biological and social factors, partnership history, and mortality risk. Mortality risks for Swedish men and women over age 50 in the Uppsala Birth Cohort born 1915e1929 were estimated using survival analysis. Relative mortality risk was evaluated through nested multiplicative Gompertz models for 4348 men and 3331 women, followed from age 50 to the end of 2010. Being born to an unmarried mother was associated with higher mortality risk in later life for men and women, and relative to married individuals, being unmarried after age 50 was associated with elevated mortality risk. Single women and divorced men were the highest risk groups, and women were negatively impacted by a previous divorce or widowhood, while men were not. Both genders showed direct effects of early life variables on later life mortality and were vulnerable if unmarried in later life. However, in this study, previous marital disruptions appeared to have more (negative) meaning in the long-term for women. Ó 2014 Elsevier Ltd. All rights reserved.
Keywords: Survival analysis Mortality risk Marital transitions Partnership history Early life conditions Sweden Life course
1. Introduction
2. Theoretical framework
Numerous studies have shown that an individual’s marital status, along with socioeconomic variables, is often a strong explanatory indicator of health and mortality later in life (Goldman et al., 1995; Johnson et al., 2000; Lillard and Waite, 1995; Valkonen et al., 2004). Studies have also shown that early life characteristics may have a lasting effect on the health and mortality of individuals later in life (Ben-Shlomo and Kuh, 2002; Smith et al., 2009). The association between these factors and mortality has become increasingly complex with great changes, not only in early life conditions, but also in regard to partnership formations throughout the 20th century, characterized by the emergence of cohabitation, later age at marriage, increase in divorces, and re-partnering after separation and widowhood. In this study, a cohort of Swedish individuals were followed through their life course in order to investigate the way in which early life circumstances and later life partnership history relate to their mortality risk in late adulthood and old age, and assess the importance of each set of factors in the presence of the other.
2.1. Early life
* Corresponding author. E-mail address: [email protected] (R. Donrovich). http://dx.doi.org/10.1016/j.socscimed.2014.02.036 0277-9536/Ó 2014 Elsevier Ltd. All rights reserved.
According to life course epidemiology, early life characteristicsdincluding both biological and social determinantsdcan influence health and mortality later in one’s life (Ben-Shlomo and Kuh, 2002). There are two models widely used to explain the relationship between early life characteristics, health, and subsequent mortality in later life. The first model, the latency or critical period model, asserts that early life variables have a direct effect on health in later life; in other words, biological determinants that occur at birth (or in gestation) will have an independent effect on morbidity and mortality (Power and Hertzman, 1997). A strong proponent of this model was David Barker who hypothesized that an individual’s chronic health is predetermined in utero. Following this hypothesis, early biological factors, such as gestational age, birth weight, and placenta size, can determine the onset of chronic health conditions in later life (Barker, 1994). The idea that one’s intrauterine health may have lasting implications on the quality of health in later life is referred to as programming, or “[the process] whereby a stimulus or insult at a “sensitive” or “critical” period of development has lasting effects on the structure or function of the body” (Barker, 2004). Coronary heart disease, stroke, and
R. Donrovich et al. / Social Science & Medicine 108 (2014) 60e67
hypertension, in particular, have been linked to early health predictors (Barker, 1998). The second model, an accumulation of risk model, proposes that early life experiences are linked with health and well-being in later life through an accumulation of risks during one’s life course. Accumulated risk can be a product of independent insults (a series of unrelated events or circumstances) or through correlated insults in a ‘chain of risk’ model, wherein one stimulus triggers the occurrence of another, and so forth, leading to a later life outcome shaped by a lifetime of accumulating risks (BenShlomo and Kuh, 2002). For example, those born into a lower class at birth often exhibit poorer childhood health, which may ultimately lead to inferior educational outcomes and economic position in adulthood (Curie, 2009; Haas, 2006; Palloni, 2006). In contrast, those with a higher economic standing at birth do not have negative health consequences due to financial constraints, and further, may have better access to quality education, job connections, and eventually access to better careers. Both frameworks can be used to understand the mechanisms through which adult health is negatively (or positively) impacted by early life experiences, either directly through programming during critical periods or through a lifetime of accumulated experiences, which may or may not be related to each other, or by some combination of both direct and indirect processes. Few studies establish a link between early life characteristics and subsequent probability of marriage or between parental marital status at birth and one’s own mortality. Goodman and Koupil (2009), using the Uppsala Birth Cohort data, found that early biological determinants such as low birth weight for gestational age and pre-term birth had negative consequences on marriage probabilities for the same Swedish population. Phillips et al. (2001) found that prenatal growth can have implications for a man’s propensity to marry, and that this may, in turn, affect mortality. Results from a study of Finnish men born between 1924 and 1933 found that marriage rates were positively correlated to biological birth variables such as weight, height, and gestational age, as well as, parent’s social class at birth and mother’s age at birth. Mother’s relationship status at birth was shown to be an important indicator for the offspring’s future mortality risk, in Lund et al. (2006) which found that Danish men born to unmarried mothers experienced double the mortality risk compared to those with married mothers. Even after controlling for sons’ own marital statuses, there was still an effect from mother’s marital status, though the strength had weakened. Further, Modin et al. (2009) found that never-married Swedish men born out of wedlock had significantly higher risk for heart disease related mortality, compared to nevermarried men born to married mothers, using the Uppsala Birth Cohort Data. The way in which relationship status affects health and mortality risk will be further explained in the following sections. 2.2. Later life In later life, the role of relationships provides a strong indicator in health and mortality studies. The positive association between marriage and health has been theoretically attributed to three mechanisms. First, the protection model assumes that people in unions are encouraged by their partners to retain health promoting habits such as regular medical checkups, engaging in preventative healthcare, moderating diet and exercise, and reporting potential health problems promptly (Verbrugge, 1979; Wyke and Ford, 1992). Next, the social relations or networks theory relates to the size of one’s social network and the frequency of contact among members and its connection to health and mortality (Avlund et al., 1998). The networks created by marriage (spouse’s relatives and friends, neighbors, etc.), could provide lifelong companionship and a
61
support system, even in the case of divorce or widowhood. Last, the selection model asserts that healthy individuals are selected into the marriage pool, while those who are unhealthy often exit (or never enter) the marriage market due to physical or mental illness (Goldman, 1993; Manzoli et al., 2007; Schone and Weinick, 1998). This theory can help explain why those in marriages typically have better health than the unmarried, as those who are in good health are more likely to find, and keep, a partner than those who are not in good health. The association between marital status and mortality has been studied rather extensively in recent decades, finding that married individuals generally enjoy a longer life span than their unmarried, divorced or separated, and widowed counterparts (Goldman et al., 1995; Hemström, 1996; Johnson et al., 2000; Lillard and Waite, 1995; Rogers, 1995; Valkonen et al., 2004; Wyke and Ford, 1992). While both genders often benefit from being married, men may benefit more, in terms of health and longevity, than women (Avlund et al., 1998; Johnson et al., 2000; Scafato et al., 2008; Schone and Weinick, 1998; Shumaker and Hill, 1991; Shye et al., 1995; Williams and Umberson, 2004). One possible explanation can be that men benefit more from the social support they receive from their wives within a marriage (Uchino et al., 1996; Umberson et al., 1996), as women tend to have a larger social circle, and may receive more support outside of the marriage (Turner and Marino, 1994). Another can be that men benefit more from the marriage protection model, in that women encourage their partners to engage in healthier living habits (Umberson, 1992) since women are more likely to engage in medical check-ups, such as regularly checking blood pressure (Schone and Weinick, 1998). The effect of widowhood on health and mortality has been examined by several studies, which show that the widowed have higher mortality risk than those who are married, but often less than the divorced (Goldman et al., 1995; Neale et al., 1986). In Schone and Weinick (1998) widows and widowers had engaged in less healthy habits than those married, indicating that those experiencing grief or loss may undertake more risky behaviors. Some research suggests that for those who are above retirement age, widowhood may have less of an effect on mortality risk than for their younger counterparts (Johnson et al., 2000; Hu and Goldman, 1990), while another found that the widowed had elevated risks across all cohorts aged over 40 in the U.S. in a longitudinal study conducted from 1986 to 2000 (Liu, 2009). Martikainen and Valkonen (1996) also found that for both genders, mortality after a death of a spouse was highly elevated within the first week and then decreases slowly over the next 6 months. This can be due to the effects of common accidents and violence (in which one partner dies from the same accident before the other), common socioeconomic environment (inadequate housing, financial stresses) and similar lifestyles (health behaviors); however, even when limiting these biases in the analysis, there was still significant excess mortality. Divorce is a relationship event that has dramatically increased over the past few decades in nearly all Western countries. Many studies show that those who are divorced or separated have higher mortality risk than those of their married counterparts (Manzoli et al., 2007). Divorced men are often most negatively affected at older ages, while for women it is not as clear-cut (Hu and Goldman, 1990). Johnson et al. (2000) also concluded that divorce seemed to affect older age groups more than younger age groups. However, because divorcing in older ages is rarer than at younger ages, those who divorced at older ages may have not been able to find a partner and remarry from an earlier divorce. Liu (2009) found that (white) women had elevated risk of mortality from external causes (homicide, suicide, accidents) following separation or divorce, and also, women had exhibited careless health behavior in times of
62
R. Donrovich et al. / Social Science & Medicine 108 (2014) 60e67
stress after divorce/widowhood by altering eating habits, having more than a twofold increase in beginning (or relapsing) to smoking, and lessening their vegetable intake compared to their married counterparts (Lee et al., 2005). While widowhood and divorce both typically have negative effects on health, age and gender are important factors for mortality risk. Widowhood and divorce, while both resulting in the loss of a spouse, do not have the same toll on health and well-being for different genders and age groups. It is important to distinguish between the act of being in a certain status versus the effect of transitioning from one status to another. By monitoring one’s transitions, the importance of accumulation and attenuation come into play. The duration of an event, or accumulation of time, in a relationship state can have important implications. More time spent in a marriage can yield a greater benefit to health, and a subsequent reduction of mortality risk, suggesting that marriage has positive long-term effects (Lillard and Waite, 1995). Over time, people know more about their partner’s health histories and behaviors which can help them identify potential health problems for their spouse. Also, a couple’s social network will more than likely expand the more years they are together, which is important for older adults and the elderly to combat loneliness and isolation. Further, the more time accumulated in a marriage can be beneficial to health and mortality because it can possibly be an indicator of ‘happiness’, as marital quality has a positive association with health (Umberson et al., 2006). For individuals who are widowed or divorced, attenuation, or the decreasing negative effects from these events, is also addressed in previous studies. Studies have shown that the negative effects of widowhood may diminish over time (Martikainen and Valkonen, 1996; Williams and Umberson, 2004) and that negative effects of divorce may increase with age (Williams and Umberson, 2004), and further, the effect of this event is most detrimental until 2 years after. In the case of widowhood, those in the grieving process may have an elevated mortality risk soon after spousal death, but these effects are just short-term. In contrast, other studies have found that previous disruptions have a longterm association with health and mortality in later life. Hughes and Waite (2009) found that currently married individuals, who had been previously divorced or widowed, had poorer health in mid-life than the married who never experienced divorce or widowhood. This suggests that the continuously married have an advantage over the remarried, and that long-term health consequences may result from the stress of a previous marital loss. Further, Zhang and Hayward (2006) found that marital loss related to a higher incidence of cardiovascular disease in late midlife for women and was largely explained by emotional distress and socioeconomic position. This paper seeks to add to the growing body of research that studies the way in which later life partnership histories relate to mortality for men and women, controlling for important social and biological factors observed both in early and later life. Previous studies have used the Uppsala Birth Cohort Study for related research questions. Modin (2003) and Modin et al. (2009) highlighted the importance of marriage with respect to mortality risk, particularly in the scope of being born in and out of wedlock. Modin (2003) focused on the cause-specific mortality from ischemic heart disease (IHD) for men. Modin et al. (2009) focused on the impact of illegitimacy on the individual’s mortality risk (and on health disadvantages in two successive male generations). The period of follow-up for the cohort was considerably shorted in both papers. Our paper adds to this research in some important ways. First, we wish to include analysis for both men and women and for all-cause mortality risk, using more detailed information on partnership histories. As a novelty we also study the effect of remarriage from a
previous divorce or widowhood. As the data has been recently updated to the end of 2010, we are also able to extend the follow-up period by 15 and 8 more years, respectively, compared to the previous studies. The latest born (1929) and earliest born (1915) study participants will have reached ages 81 and 95, respectively, at the end of follow-up. With the inclusion of both genders, mortality from all causes, more detailed partnership histories, and the benefit of additional years of follow-up, we aim to further analyze the effect of partnership history, and previous marital disruptions (divorce or widowhood) and remarriage, on mortality risk over age 50 for both men and women, and to build upon these previous studies. 3. Materials and methods The aim of this study was to investigate the association between partnership history and mortality risk, controlling for early life conditions and later life circumstances during one’s life course. For our analysis, we used the Uppsala Birth Cohort Multigeneration Study, which is one of the few data sources that includes social and medical data for a study population over a very long period of time (UBCoS Multigen: www.chess.su.se/ubcosmg). The UBCoS Multigen provides detailed socioeconomic, demographic, and health information for the original cohort and their descendants from several Swedish sources (Koupil, 2007; Koupil and Goodman, 2011). Our study population is the first generation which consisted of 12 168 live births of men and women during 1915e1929 in Uppsala Academic Hospital. Individuals enter the study at age 50 and are followed to the end of 2010. Individuals are censored if they emigrated during the observation period. 3.1. Variables Main exposures under study were early life variables (gestational age, mother’s marital status, social class at birth, and sibling order) and later life semi-time-varying civil status. The main outcome variable was the risk of death for those over age 50. In our analysis, we also controlled for the effect of later life socioeconomic variables (education level and semi-time-varying employment status). All fixed variables were measured at birth, with the exception of education level, which was taken from the 1970 census. All semi-time-varying variables have been taken from 4 census years: 1960, 1970, 1980, and 1990, are linked to each individual in the study, and reflect changes once every 10 years. Gestational age was calculated as the reported time since index person’s mother’s last day of menstruation until birth, and defined as premature (36 weeks), full-term (37e41 weeks), and post-term (42þ weeks). Index person’s social class at birth is based on father’s occupation, or mother’s if the mother is unmarried, and analyzed as: higher and mediate non-manuals, lower non-manuals, entrepreneurs, skilled manuals, farmers and farm laborers, unskilled manuals, and house daughters (unmarried women living in their parental home). Mother’s marital status at birth was coded as married and unmarried (including single, divorced or widowed). Sibling order was a summary of previous still and live births for the index person’s mother (pregnancies over 20 weeks) and was based on mother’s parity recorded in obstetric data. It ranged from 1 to 16 children and was categorized as 1, 2, 3, 4þ in our analysis. Highest level of education was based on data from the 1970 census and analyzed as: elementary school, senior high school,
Contents lists available at ScienceDirect
Social Science & Medicine journal homepage: www.elsevier.com/locate/socscimed
Early life conditions, partnership histories, and mortality risk for Swedish men and women born 1915e1929 Robyn Donrovich a, *, Sven Drefahl b, Ilona Koupil c a
Family and Population Studies (FaPOS), Centre for Sociological Research, KU Leuven, Parkstraat 45-Box 3601, 3000 Leuven, Belgium Demography Unit, Department of Sociology, Stockholm University, Stockholm, Sweden c Center for Health Equity Studies, Stockholm University/Karolinska Institutet, Stockholm, Sweden b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 28 August 2013 Received in revised form 18 February 2014 Accepted 21 February 2014 Available online 24 February 2014
This paper investigates the relationship between early life biological and social factors, partnership history, and mortality risk. Mortality risks for Swedish men and women over age 50 in the Uppsala Birth Cohort born 1915e1929 were estimated using survival analysis. Relative mortality risk was evaluated through nested multiplicative Gompertz models for 4348 men and 3331 women, followed from age 50 to the end of 2010. Being born to an unmarried mother was associated with higher mortality risk in later life for men and women, and relative to married individuals, being unmarried after age 50 was associated with elevated mortality risk. Single women and divorced men were the highest risk groups, and women were negatively impacted by a previous divorce or widowhood, while men were not. Both genders showed direct effects of early life variables on later life mortality and were vulnerable if unmarried in later life. However, in this study, previous marital disruptions appeared to have more (negative) meaning in the long-term for women. Ó 2014 Elsevier Ltd. All rights reserved.
Keywords: Survival analysis Mortality risk Marital transitions Partnership history Early life conditions Sweden Life course
1. Introduction
2. Theoretical framework
Numerous studies have shown that an individual’s marital status, along with socioeconomic variables, is often a strong explanatory indicator of health and mortality later in life (Goldman et al., 1995; Johnson et al., 2000; Lillard and Waite, 1995; Valkonen et al., 2004). Studies have also shown that early life characteristics may have a lasting effect on the health and mortality of individuals later in life (Ben-Shlomo and Kuh, 2002; Smith et al., 2009). The association between these factors and mortality has become increasingly complex with great changes, not only in early life conditions, but also in regard to partnership formations throughout the 20th century, characterized by the emergence of cohabitation, later age at marriage, increase in divorces, and re-partnering after separation and widowhood. In this study, a cohort of Swedish individuals were followed through their life course in order to investigate the way in which early life circumstances and later life partnership history relate to their mortality risk in late adulthood and old age, and assess the importance of each set of factors in the presence of the other.
2.1. Early life
* Corresponding author. E-mail address: [email protected] (R. Donrovich). http://dx.doi.org/10.1016/j.socscimed.2014.02.036 0277-9536/Ó 2014 Elsevier Ltd. All rights reserved.
According to life course epidemiology, early life characteristicsdincluding both biological and social determinantsdcan influence health and mortality later in one’s life (Ben-Shlomo and Kuh, 2002). There are two models widely used to explain the relationship between early life characteristics, health, and subsequent mortality in later life. The first model, the latency or critical period model, asserts that early life variables have a direct effect on health in later life; in other words, biological determinants that occur at birth (or in gestation) will have an independent effect on morbidity and mortality (Power and Hertzman, 1997). A strong proponent of this model was David Barker who hypothesized that an individual’s chronic health is predetermined in utero. Following this hypothesis, early biological factors, such as gestational age, birth weight, and placenta size, can determine the onset of chronic health conditions in later life (Barker, 1994). The idea that one’s intrauterine health may have lasting implications on the quality of health in later life is referred to as programming, or “[the process] whereby a stimulus or insult at a “sensitive” or “critical” period of development has lasting effects on the structure or function of the body” (Barker, 2004). Coronary heart disease, stroke, and
R. Donrovich et al. / Social Science & Medicine 108 (2014) 60e67
hypertension, in particular, have been linked to early health predictors (Barker, 1998). The second model, an accumulation of risk model, proposes that early life experiences are linked with health and well-being in later life through an accumulation of risks during one’s life course. Accumulated risk can be a product of independent insults (a series of unrelated events or circumstances) or through correlated insults in a ‘chain of risk’ model, wherein one stimulus triggers the occurrence of another, and so forth, leading to a later life outcome shaped by a lifetime of accumulating risks (BenShlomo and Kuh, 2002). For example, those born into a lower class at birth often exhibit poorer childhood health, which may ultimately lead to inferior educational outcomes and economic position in adulthood (Curie, 2009; Haas, 2006; Palloni, 2006). In contrast, those with a higher economic standing at birth do not have negative health consequences due to financial constraints, and further, may have better access to quality education, job connections, and eventually access to better careers. Both frameworks can be used to understand the mechanisms through which adult health is negatively (or positively) impacted by early life experiences, either directly through programming during critical periods or through a lifetime of accumulated experiences, which may or may not be related to each other, or by some combination of both direct and indirect processes. Few studies establish a link between early life characteristics and subsequent probability of marriage or between parental marital status at birth and one’s own mortality. Goodman and Koupil (2009), using the Uppsala Birth Cohort data, found that early biological determinants such as low birth weight for gestational age and pre-term birth had negative consequences on marriage probabilities for the same Swedish population. Phillips et al. (2001) found that prenatal growth can have implications for a man’s propensity to marry, and that this may, in turn, affect mortality. Results from a study of Finnish men born between 1924 and 1933 found that marriage rates were positively correlated to biological birth variables such as weight, height, and gestational age, as well as, parent’s social class at birth and mother’s age at birth. Mother’s relationship status at birth was shown to be an important indicator for the offspring’s future mortality risk, in Lund et al. (2006) which found that Danish men born to unmarried mothers experienced double the mortality risk compared to those with married mothers. Even after controlling for sons’ own marital statuses, there was still an effect from mother’s marital status, though the strength had weakened. Further, Modin et al. (2009) found that never-married Swedish men born out of wedlock had significantly higher risk for heart disease related mortality, compared to nevermarried men born to married mothers, using the Uppsala Birth Cohort Data. The way in which relationship status affects health and mortality risk will be further explained in the following sections. 2.2. Later life In later life, the role of relationships provides a strong indicator in health and mortality studies. The positive association between marriage and health has been theoretically attributed to three mechanisms. First, the protection model assumes that people in unions are encouraged by their partners to retain health promoting habits such as regular medical checkups, engaging in preventative healthcare, moderating diet and exercise, and reporting potential health problems promptly (Verbrugge, 1979; Wyke and Ford, 1992). Next, the social relations or networks theory relates to the size of one’s social network and the frequency of contact among members and its connection to health and mortality (Avlund et al., 1998). The networks created by marriage (spouse’s relatives and friends, neighbors, etc.), could provide lifelong companionship and a
61
support system, even in the case of divorce or widowhood. Last, the selection model asserts that healthy individuals are selected into the marriage pool, while those who are unhealthy often exit (or never enter) the marriage market due to physical or mental illness (Goldman, 1993; Manzoli et al., 2007; Schone and Weinick, 1998). This theory can help explain why those in marriages typically have better health than the unmarried, as those who are in good health are more likely to find, and keep, a partner than those who are not in good health. The association between marital status and mortality has been studied rather extensively in recent decades, finding that married individuals generally enjoy a longer life span than their unmarried, divorced or separated, and widowed counterparts (Goldman et al., 1995; Hemström, 1996; Johnson et al., 2000; Lillard and Waite, 1995; Rogers, 1995; Valkonen et al., 2004; Wyke and Ford, 1992). While both genders often benefit from being married, men may benefit more, in terms of health and longevity, than women (Avlund et al., 1998; Johnson et al., 2000; Scafato et al., 2008; Schone and Weinick, 1998; Shumaker and Hill, 1991; Shye et al., 1995; Williams and Umberson, 2004). One possible explanation can be that men benefit more from the social support they receive from their wives within a marriage (Uchino et al., 1996; Umberson et al., 1996), as women tend to have a larger social circle, and may receive more support outside of the marriage (Turner and Marino, 1994). Another can be that men benefit more from the marriage protection model, in that women encourage their partners to engage in healthier living habits (Umberson, 1992) since women are more likely to engage in medical check-ups, such as regularly checking blood pressure (Schone and Weinick, 1998). The effect of widowhood on health and mortality has been examined by several studies, which show that the widowed have higher mortality risk than those who are married, but often less than the divorced (Goldman et al., 1995; Neale et al., 1986). In Schone and Weinick (1998) widows and widowers had engaged in less healthy habits than those married, indicating that those experiencing grief or loss may undertake more risky behaviors. Some research suggests that for those who are above retirement age, widowhood may have less of an effect on mortality risk than for their younger counterparts (Johnson et al., 2000; Hu and Goldman, 1990), while another found that the widowed had elevated risks across all cohorts aged over 40 in the U.S. in a longitudinal study conducted from 1986 to 2000 (Liu, 2009). Martikainen and Valkonen (1996) also found that for both genders, mortality after a death of a spouse was highly elevated within the first week and then decreases slowly over the next 6 months. This can be due to the effects of common accidents and violence (in which one partner dies from the same accident before the other), common socioeconomic environment (inadequate housing, financial stresses) and similar lifestyles (health behaviors); however, even when limiting these biases in the analysis, there was still significant excess mortality. Divorce is a relationship event that has dramatically increased over the past few decades in nearly all Western countries. Many studies show that those who are divorced or separated have higher mortality risk than those of their married counterparts (Manzoli et al., 2007). Divorced men are often most negatively affected at older ages, while for women it is not as clear-cut (Hu and Goldman, 1990). Johnson et al. (2000) also concluded that divorce seemed to affect older age groups more than younger age groups. However, because divorcing in older ages is rarer than at younger ages, those who divorced at older ages may have not been able to find a partner and remarry from an earlier divorce. Liu (2009) found that (white) women had elevated risk of mortality from external causes (homicide, suicide, accidents) following separation or divorce, and also, women had exhibited careless health behavior in times of
62
R. Donrovich et al. / Social Science & Medicine 108 (2014) 60e67
stress after divorce/widowhood by altering eating habits, having more than a twofold increase in beginning (or relapsing) to smoking, and lessening their vegetable intake compared to their married counterparts (Lee et al., 2005). While widowhood and divorce both typically have negative effects on health, age and gender are important factors for mortality risk. Widowhood and divorce, while both resulting in the loss of a spouse, do not have the same toll on health and well-being for different genders and age groups. It is important to distinguish between the act of being in a certain status versus the effect of transitioning from one status to another. By monitoring one’s transitions, the importance of accumulation and attenuation come into play. The duration of an event, or accumulation of time, in a relationship state can have important implications. More time spent in a marriage can yield a greater benefit to health, and a subsequent reduction of mortality risk, suggesting that marriage has positive long-term effects (Lillard and Waite, 1995). Over time, people know more about their partner’s health histories and behaviors which can help them identify potential health problems for their spouse. Also, a couple’s social network will more than likely expand the more years they are together, which is important for older adults and the elderly to combat loneliness and isolation. Further, the more time accumulated in a marriage can be beneficial to health and mortality because it can possibly be an indicator of ‘happiness’, as marital quality has a positive association with health (Umberson et al., 2006). For individuals who are widowed or divorced, attenuation, or the decreasing negative effects from these events, is also addressed in previous studies. Studies have shown that the negative effects of widowhood may diminish over time (Martikainen and Valkonen, 1996; Williams and Umberson, 2004) and that negative effects of divorce may increase with age (Williams and Umberson, 2004), and further, the effect of this event is most detrimental until 2 years after. In the case of widowhood, those in the grieving process may have an elevated mortality risk soon after spousal death, but these effects are just short-term. In contrast, other studies have found that previous disruptions have a longterm association with health and mortality in later life. Hughes and Waite (2009) found that currently married individuals, who had been previously divorced or widowed, had poorer health in mid-life than the married who never experienced divorce or widowhood. This suggests that the continuously married have an advantage over the remarried, and that long-term health consequences may result from the stress of a previous marital loss. Further, Zhang and Hayward (2006) found that marital loss related to a higher incidence of cardiovascular disease in late midlife for women and was largely explained by emotional distress and socioeconomic position. This paper seeks to add to the growing body of research that studies the way in which later life partnership histories relate to mortality for men and women, controlling for important social and biological factors observed both in early and later life. Previous studies have used the Uppsala Birth Cohort Study for related research questions. Modin (2003) and Modin et al. (2009) highlighted the importance of marriage with respect to mortality risk, particularly in the scope of being born in and out of wedlock. Modin (2003) focused on the cause-specific mortality from ischemic heart disease (IHD) for men. Modin et al. (2009) focused on the impact of illegitimacy on the individual’s mortality risk (and on health disadvantages in two successive male generations). The period of follow-up for the cohort was considerably shorted in both papers. Our paper adds to this research in some important ways. First, we wish to include analysis for both men and women and for all-cause mortality risk, using more detailed information on partnership histories. As a novelty we also study the effect of remarriage from a
previous divorce or widowhood. As the data has been recently updated to the end of 2010, we are also able to extend the follow-up period by 15 and 8 more years, respectively, compared to the previous studies. The latest born (1929) and earliest born (1915) study participants will have reached ages 81 and 95, respectively, at the end of follow-up. With the inclusion of both genders, mortality from all causes, more detailed partnership histories, and the benefit of additional years of follow-up, we aim to further analyze the effect of partnership history, and previous marital disruptions (divorce or widowhood) and remarriage, on mortality risk over age 50 for both men and women, and to build upon these previous studies. 3. Materials and methods The aim of this study was to investigate the association between partnership history and mortality risk, controlling for early life conditions and later life circumstances during one’s life course. For our analysis, we used the Uppsala Birth Cohort Multigeneration Study, which is one of the few data sources that includes social and medical data for a study population over a very long period of time (UBCoS Multigen: www.chess.su.se/ubcosmg). The UBCoS Multigen provides detailed socioeconomic, demographic, and health information for the original cohort and their descendants from several Swedish sources (Koupil, 2007; Koupil and Goodman, 2011). Our study population is the first generation which consisted of 12 168 live births of men and women during 1915e1929 in Uppsala Academic Hospital. Individuals enter the study at age 50 and are followed to the end of 2010. Individuals are censored if they emigrated during the observation period. 3.1. Variables Main exposures under study were early life variables (gestational age, mother’s marital status, social class at birth, and sibling order) and later life semi-time-varying civil status. The main outcome variable was the risk of death for those over age 50. In our analysis, we also controlled for the effect of later life socioeconomic variables (education level and semi-time-varying employment status). All fixed variables were measured at birth, with the exception of education level, which was taken from the 1970 census. All semi-time-varying variables have been taken from 4 census years: 1960, 1970, 1980, and 1990, are linked to each individual in the study, and reflect changes once every 10 years. Gestational age was calculated as the reported time since index person’s mother’s last day of menstruation until birth, and defined as premature (36 weeks), full-term (37e41 weeks), and post-term (42þ weeks). Index person’s social class at birth is based on father’s occupation, or mother’s if the mother is unmarried, and analyzed as: higher and mediate non-manuals, lower non-manuals, entrepreneurs, skilled manuals, farmers and farm laborers, unskilled manuals, and house daughters (unmarried women living in their parental home). Mother’s marital status at birth was coded as married and unmarried (including single, divorced or widowed). Sibling order was a summary of previous still and live births for the index person’s mother (pregnancies over 20 weeks) and was based on mother’s parity recorded in obstetric data. It ranged from 1 to 16 children and was categorized as 1, 2, 3, 4þ in our analysis. Highest level of education was based on data from the 1970 census and analyzed as: elementary school, senior high school,
