# The Role of Family Complexity in Mental and Physical Health in Mid-Adulthood

Philipp Dierker, Mine Kühn, Zachary van Winkle

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Philipp Dierker, Mine Kühn, Zachary van Winkle. The Role of Family Complexity in Mental and Physical Health in Mid-Adulthood. Journal of Marriage and Family, 2025, 10.1111/jomf.70019. hal-05510330

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# The Role of Family Complexity in Mental and Physical Health in Mid-Adulthood

Philipp Dierker<fnref n="1" />,²,³ ID | Mine Kühn<fnref n="1" />,³,⁴ ID | Zachary Van Winkle⁵,⁶,⁷ ID

**Correspondence:** Philipp Dierker (dierker@demogr.mpg.de)

**Received:** 18 January 2025 | **Revised:** 15 July 2025 | **Accepted:** 24 July 2025

**Deputy Editor:** Spencer Olmstead

**Funding:** This work was supported by the Strategic Research Council (SRC), FLUX consortium, decision numbers 364374 and 364375; by grants to the Max Planck—University of Helsinki Center from the Max Planck Society (5714240218), Jane and Aatos Erkko Foundation (210046), Faculty of Social Sciences at the University of Helsinki (77204227), and Cities of Helsinki, Vantaa and Espoo; and the European Union (ERC Synergy, BIOSFER, 101071773). Z.V.W. was supported by the European Research Council through the European Union's Horizon 2020 research and innovation programme under the Grant Agreement No. 101117173 (WIDOW).

**Keywords:** adult development and aging | demography | family | family policy | life events and/or transitions | longitudinal | mental health | method | midlife | well-being

## ABSTRACT

**Objective:** This study examines the association between accumulated family complexity and mental and physical health in mid-adulthood, with a focus on gender differences.

**Background:** While research on family and health often centers on the health effects of specific family transitions, the life course health development model emphasizes the cumulative influence of life experiences on health. Complex family trajectories, particularly those including episodes of singlehood or single parenthood, may have lasting implications for mental and physical health.

**Method:** Using data from the UK Household Longitudinal Study, differently weighted sequence complexity indices were applied to capture the number and the unpredictability of transitions in partnership and parenthood trajectories from ages 18 to 55 and health at age 55 (survey years 2009–2022) among men (N = 2638) and women (N = 3407).

**Results:** Accumulated family complexity is negatively associated with both women's and men's mental and physical health, but findings differ based on the specification of family complexity. Women's physical health appears to be particularly affected by the accumulation of family complexity following a separation involving children, whereas men's mental and physical health seem to be more affected by accumulated family complexity after any separation.

**Conclusion:** By uncovering substantial gender differences in patterns of associations between accumulated family complexity and health, this study highlights the importance of accounting for gender-specific dynamics in studies of family complexity. Our finding that long-term health disadvantages are associated with family complexity suggests that entire life course trajectories should be considered and quantified when examining long-term health outcomes.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2025 The Author(s). *Journal of Marriage and Family* published by Wiley Periodicals LLC on behalf of National Council on Family Relations.

<footnote n="1">¹Max Planck Institute for Demographic Research, Rostock, Germany | ²Helsinki Institute for Demography and Population Health, University of Helsinki, Helsinki, Finland | ³Max Planck—University of Helsinki Center for Social Inequalities in Population Health, Rostock, Germany and Helsinki, Finland | ⁴Department of Sociology, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, the Netherlands | ⁵Sciences Po, Centre for Research on Social Inequalities (CRIS), CNRS, Paris, France | ⁶Nuffield College, University of Oxford, Oxford, UK | ⁷The Einstein Center Population Diversity (ECPD), Berlin, Germany</footnote>
# 1 | Introduction

The link between family life events and health has been widely studied in family sociology and demographic research (Barban 2013; Carr and Springer 2010; O'Flaherty et al. 2016). Families are a key source of material and social support that foster well-being and buffer stress, explaining health differences between family arrangements (Thomas et al. 2017). Since the onset of the second demographic transition in the 1960s (Lesthaeghe 2010, 2014), family structures have changed substantially, marked by increases in cohabitation, divorce, and single parenthood, and a corresponding decline in marriage. Theoretical approaches link these family events to health as protective functions (Wu and Hart 2002) or as crises and chronic strains (Amato 2000; Booth and Amato 1991).

Longitudinal studies using fixed effects models linked union formation to improvements in mental health, while links to physical health were less consistent (Kalmijn 2017; Mikucka et al. 2021). Union dissolution was often linked to declines in mental and physical health (Leopold 2018; Metsä-Simola and Martikainen 2014), especially with young children present (Leopold and Kalmijn 2016). Re-partnering showed inconsistent effects, with some studies finding mental health improvements (Kühn et al. 2023), while others found inconsistent patterns for mental health across countries (Dierker et al. 2025) and no effects on physical health (Recksiedler and Bernardi 2019). Parenthood has been associated with improvements in mental health (Metzger and Gracia 2023) and short-term declines in physical health (Di Nallo 2025).

While these studies have examined single-family transitions and their association to well-being, they fall short in two ways. First, they overlook the growing complexity of contemporary family life courses, which is marked by a higher number of family events and greater unpredictability over time (Brückner and Mayer 2005). Second, they fail to capture the long-term health impacts of this complexity, which may differ depending on the specific outcome. This gap is crucial, as the life course health development model (Halfon and Hochstein 2002) conceptualizes health as the cumulative result of both health-threatening and health-promoting factors (Barban 2013).

While individual family events can define family complexity, this study focuses on the accumulation of family complexity over the life course. In line with previous research on family complexity (e.g., Van Winkle 2018; Winkle and Fasang 2021) our definition of family complexity includes both partnership transitions and information on parenthood (i.e., presence and number of children). Earlier research modeled the link between accumulated family complexity and health by counting transitions (Hughes and Waite 2009). More recent studies have used sequence analysis to identify various clusters of family trajectories and to examine the association between those family life course patterns and health at a certain age (Barban 2013; Jung 2023). As life courses become more diverse and fewer people follow the same typical patterns, clustering methods may become less effective in capturing this growing complexity. Measures like sequence complexity (Gabadinho

et al. 2010), the precarity index (Ritschard et al. 2018), and—derived from the precarity index—the weighted partnership index (Hiekel and Vidal 2020) quantify the cumulative effects of transitions. However, few studies have examined links between these flexible measures of family complexity and health in mid-adulthood.

In this study, we apply the sequence complexity index and differently weighted precarity indices to examine associations between family complexity and physical and mental health in mid-adulthood among men and women. We use family history and health data from the British Understanding Society study. These data allow us to examine complete family histories (partnership states and information on parenthood in each partnership state) of 3407 women and 2638 men and their physical and mental health at age 55, while controlling for childhood health diagnoses.

# 2 | Background

## 2.1 | Family Complexity Over the Life Course

Family complexity is central to the study of life course trajectories. It includes partnership dynamics, fertility histories, union sequencing, and diversity across populations (Sassler and Lichter 2020). Basic metrics to measure family complexity, such as the number of life course states or transitions (Hughes and Waite 2009), ignore the role of life course uncertainty. This encompasses economic uncertainty and so-called “temporal uncertainty” that restricts the willingness to make long-term commitments (Breen 1997; Mills and Blossfeld 2013). Another form of uncertainty is the unpredictability of family life courses, which can be attributed to the differentiation of life courses, describing the phenomenon of an increasing number of life course states in individual family life courses (Brückner and Mayer 2005).

The sequence complexity index (Gabadinho et al. 2010; Ritschard et al. 2018) is a useful tool for capturing this unpredictability of life courses. Several extensions of this index exist (Pelletier et al. 2020; Raab and Struffolino 2023). The precarity index (Ritschard et al. 2018) allows for differential weighting of transitions based on their potential advantages and disadvantages for individuals. In this study, we construct two weighted versions of this index that emphasize the vulnerability associated with experiencing a separation or a separation with a child.

While no prior research has examined health outcomes in relation to family complexity measured through sequence complexity indices, several studies have applied these indices to family trajectories. Hiekel and Vidal (2020) used the precarity index to analyze partnership trajectories, defining complexity as the accumulation of partnership episodes following union dissolution, though they did not include information on children. This lack of consideration of children was shared by other studies applying sequence-based measures to family complexity (Jung 2023). Van Winkle (2018) incorporated information on children when operationalizing family complexity
using the sequence complexity index, while Rowold and Van Winkle (2023) shifted the perspective from adults to children, examining childhood family complexity based on their parents' relationship trajectories.

A life course perspective offers a compelling framework for studying family complexity. Above all, it facilitates the study of extended partnership and fertility histories, as rather than focusing solely on individual transitions, it provides a unique perspective on how family states and transitions impact adult lives (Umberson et al. 2010). This perspective aligns with the concepts of cumulative advantage and disadvantage (Dannefer 2003; DiPrete and Eirich 2006). Thus, this approach enables us to examine how specific transitions can shape trajectories of increasing advantage or disadvantage over the life course. For instance, the challenges of single parenthood may result in additional disadvantages and increased parental distress, with potential long-term effects on an individual's physical and psychological well-being in later life (Umberson et al. 2010). Moreover, the life course perspective recognizes the complex interplay between family transitions and other life domains. Union status is inherently linked to various events that unfold throughout life. Some events, such as becoming a parent, are closely connected to the probability of transitioning from a cohabiting union to marriage (Groepler et al. 2021).

Prior research on marital biographies has examined transitions in and out of marriage and the duration in specific statuses (Hughes and Waite 2009). However, many studies rely on cross-sectional or age-restricted snapshots, which do not capture how family transitions accumulate and interact over time, making it difficult to assess the long-term consequences of family trajectories. A life course perspective considers the sequencing and duration of family states, allowing for a more comprehensive understanding of how partnership histories and parenthood shape health in midlife and beyond. This highlights the interdependencies between family transitions, offering a more holistic view of their cumulative effects (Umberson et al. 2010).

The life course approach highlights that individual development is a life-long process embedded in socio-historic contexts within a network of shared relationships (Bernardi et al. 2019; Elder et al. 2003). In addition, it postulates that the developmental consequences of life transitions vary according to when they occur and their developmental antecedents (Dannefer 2003; Fasang et al. 2024). Although studies that focus on more than one family transition and health are rare (see Montgomery et al. 2023), research has shown that the timing (early versus late transitions), quantity (number of transitions) and ordering (normative versus non-normative sequence of transitions) of family events has consequences for individual health as well as health behaviors, such as smoking and drinking (Barban 2013). By adopting this approach, we shift from a static to a dynamic perspective on families, acknowledging the continually evolving nature of these dynamics. This dynamic perspective enhances our understanding of family complexity and sheds light on the relationships between family transitions and health outcomes. Research on associations between specific family transitions and health is presented in the following section.

## 2.2 | Family Transitions and Health

### 2.2.1 | Union Formation

Both the marital protection model (Wu and Hart 2002) and the marital resource model (Williams and Umberson 2004) posit that union formation is generally linked to better mental and physical health, largely due to the social, financial, and emotional support that unions provide. Moreover, romantic partnerships provide social controls that reduce risky behaviors (Fleming et al. 2010; Hilz and Wagner 2018; Koball et al. 2010; Salvatore et al. 2020), which may, in turn, lead to better physical health outcomes. Economically, union formation improves stability through resource sharing and the marital wage premium (Killewald 2013; Ludwig and Brüderl 2018; McDonald 2020; Vespa and Painter II 2011), which can improve living conditions and, in some contexts, healthcare access (Devaux 2015). Emotional support promotes both physical and mental health by fostering intimacy, reducing loneliness, and increasing commitment (Barban 2013; Musick and Bumpass 2012; Stokes 2017; Uchino 2006).

Research on social networks and social support also demonstrated that close social ties—particularly within family and partnerships—can offer substantial emotional, instrumental, and informational support, all of which are critical for fostering well-being and buffering individuals against stress and adversity (Kawachi and Berkman 2001; Thoits 2011). These findings suggest that the benefits of union formation for mental and physical health are not only material but also deeply embedded in the social and emotional exchanges that intimate relationships facilitate.

For mental health, the results of recent studies on these associations have been mixed. Kravdal et al. (2022) found positive effects of union formation on mental health (operationalized with GP visits), while Mikucka et al. (2021) observed only weak effects of union formation on mental health. Also, Kalmijn (2017) observed only weak effects of union formation on mental health, but more pronounced positive effects on life satisfaction. However, all these studies found mainly short-term increases, followed by an adjustment to initial levels. This phenomenon is known as the set-point theory (Clark et al. 2008). Differences in the association between union formation and mental health have been found between cohabitation and marriage. Perelli-Harris and Styrc (2018) found minor mental health differences between cohabiting and married individuals in the UK, which disappeared after controlling for childhood background and union characteristics like duration and prior union dissolution. Similarly, Metsä-Simola and Martikainen (2014) observed short-term improvements in mental health following marriage, but no long-term differences in mental health between individuals in marital and cohabiting unions. Thus, we assume that while transitioning from cohabitation to marriage provides small short-term mental health gains, moving in with a new partner is the key mechanism for explaining the association between union formation and mental health. For re-partnering, studies have shown well-being benefits measured by life satisfaction (Dierker et al. 2025; Gloor et al. 2021). Regarding the mental health of parents following re-partnering, findings are mixed, with some studies reporting positive mental health outcomes (Kühn et al. 2023), and others finding inconsistent effects on mental health (Dierker et al. 2025).
Regarding physical health, Kalmijn (2017) observed almost no effects of union formation, while Mikucka et al. (2021) reported similar, albeit non-significant patterns of physical health compared with self-rated health. In older studies, Wu and Hart (2002) found no effects of union formation on mental and physical health, while Williams and Umberson (2004) found that differences in self-assessed health depending on marital status were less likely to reflect the protective or resource effects of union formation than the crisis-based effects of union dissolution. For re-partnering, evidence on physical health is limited. Examining the physical health of single mothers following re-partnering, Recksiedler and Bernardi et al. (2019) found no significant physical health improvements.

### 2.2.2 | Union Dissolution

While it is recognized that union dissolution may provide relief for individuals suffering in a relationship, potentially leading to improvements in mental and physical well-being over time (Williams and Umberson 2004), the prevailing literature suggests that the health effects of separation are generally negative. Two primary theoretical perspectives on the health effects of union dissolution dominate the literature. Both assume that union dissolution has a negative impact on mental and physical health, but they differ on the duration. The crisis perspective argues that stressors from separation are short-lived, leading to an initial health decline followed by a recovery (Booth and Amato 1991; Pearlin 2010; Stroebe et al. 2007). In contrast, the chronic strain perspective posits that such transitions have both short- and long-term effects, leading to persistent health disadvantages due to chronic strain (Barrett 2000; Halpern-Meekin and Turney 2022).

Particularly regarding mental health outcomes, longitudinal studies on union dissolution often align with the crisis perspective (Booth and Amato 1991; Carr and Springer 2010; Kalmijn 2017; Strohschein et al. 2005). Additionally, studies by Leopold and Kalmijn (2016) and Kühn et al. (2023) have shown that dissolutions involving children have a greater short-term negative impact on parents' well-being than separations among childless couples.

The findings on physical health are mixed. Some studies have observed long-term disadvantages, consistent with the chronic strain perspective (Lorenz et al. 2006), while others have found no significant differences in physical health outcomes (Kalmijn 2017; Williams and Umberson 2004). As most research indicates that union dissolution tends to negatively affect health, we classify it as a transition that increases family complexity.

Similar to research on union formation, studies on the association between union dissolution and health often do not distinguish between the termination of a cohabiting relationship and the dissolution of a marriage. Most studies focus primarily on the loss of a partner with whom an individual has shared a household, rather than on the specific legal status of the union. Some studies have suggested that marital divorce has more severe detrimental effects on well-being than the dissolution of a cohabiting union.

One explanation for this difference is that cohabitation is often viewed as a preliminary phase before marriage, with lower levels of commitment and institutionalization, which may reduce the psychological impact of its dissolution (Kalmijn 2017; Kamp Dush 2013). Empirical studies support this distinction: Kravdal and Wörn (2023) found that divorce had more pronounced negative effects on both mental and physical health compared with the dissolution of a cohabiting union, and Kalmijn (2017) observed stronger impacts of divorce on mental health but no significant difference for physical health. Kamp Dush (2013) found no significant differences in the extent to which depressive symptoms increased after cohabitation dissolution versus divorce.

However, some findings suggest that the dissolution of cohabiting unions may be more consequential than marital separations. Differences in legal protections, particularly regarding the division of property, may create additional financial and logistical challenges for individuals ending a cohabiting relationship, as discussed by Kravdal and Wörn (2023). This has, however, not been shown often for mental or physical health in previous research. However, Kalmijn (2017) found that declines in life satisfaction were more pronounced following the dissolution of a cohabiting union than after divorce.

### 2.2.3 | Childbirth

The baseline hypothesis on the impact of childbirth suggests that while parents experience a short-term well-being increase, their well-being eventually returns to previous levels (Clark et al. 2008; Clark and Georgellis 2013). Research found short-term well-being increases after childbirth, supporting the baseline hypothesis (Clark and Georgellis 2013; Myrskylä and Margolis 2014), but also uncovered sustained positive trends (Mikucka 2016; Radó 2020). However, evidence on childbirth effects on non-cohabiting parents' health remains inconclusive. Research on parenthood has suggested negative effects can be expected in such cases (Evenson and Simon 2005).

The impact of parenthood on health may be different for separated parents, who face social and economic challenges that can intensify the stressors associated with raising children. Following separation, single parents—especially mothers—often experience financial strain (Leopold and Kalmijn 2016), which is a critical factor in mental and physical health outcomes. Separated parents may lack the shared responsibilities and emotional support that partnered parents typically benefit from, making the demands of parenting more isolating and exhausting. The absence of co-parenting support has been linked to heightened psychological distress, as single parents often have to manage their child-rearing responsibilities alone, and with more constrained resources and limited social support (Nomaguchi and Milkie 2020).

## 2.3 | Accumulated Family Complexity and Health

In our study, we move beyond individual family transitions to examine how accumulated family histories shape health in mid-adulthood. Guided by the life course health development
model (Halfon and Hochstein 2002), we conceptualize health
as the outcome of cumulative life experiences (Barban 2013).
This extends to the cumulative disadvantage theory, describing
a “systemic tendency for interindividual divergence in a given
characteristic (...) with the passage of time” (Dannefer 2003,
p. S327). This perspective suggests that repeated experiences
of family complexity—such as multiple union dissolutions or
re-partnerships—may intensify health disparities over time.
Individuals in poorer health may be more likely to enter lower-
quality partnerships that dissolve early (Mastekaasa 1992), po-
tentially reinforcing disadvantage across the life course.

To clarify the relevance of studying health outcomes separately,
we distinguish between mental and physical health outcomes.
Most studies on well-being and mental health in the context of
family transitions support the set-point theory (Clark et al. 2008;
Lucas 2007), emphasizing short-term declines followed by ad-
aptation. However, patterns of repeated instability may have
longer-lasting effects. For example, Jung (2023) found union in-
stability was linked to higher depression probability at age 45,
while stable relationships were linked to lower risk. By contrast,
Halpern-MEEKIN and Turney (2022) found no substantial men-
tal health difference between individuals with a single union
dissolution and those with on-off relationships.

Findings on physical health are also mixed, yet they point to
distinct mechanisms. Chronic strains from union dissolution
and the absence of a partner's social control have been linked
to a higher number of chronic conditions and mobility limita-
tions (Hughes and Waite 2009). Some studies suggest that sta-
ble relationships promote physical health over time (Rapp and
Stauder 2020), whereas others find little evidence of lasting
effects. For instance, Williams and Umberson (2004) reported
no significant midlife differences in self-rated physical health
across consistently married, divorced, or never-married individ-
uals. Yet, O'Flaherty et al. (2016) showed that certain complex
family trajectories—especially those involving repeated union
transitions and childrearing—were associated with poorer
physical health. Notably, they also observed that some complex
trajectories without children were linked to better health than
the married-with-children pattern, underscoring the need to
disentangle these effects.

## 2.4 | Gender Differences in Health Implications of Complexity

Prior theoretical and empirical work suggests that men and
women respond differently to family transitions in terms of
health changes. While both genders' health has shown to be
affected by family transitions, differences exist in how mental
and physical health changed. Generally, it is suggested that ad-
verse and beneficial family experiences have a greater impact on
women's mental health. After marriage, women have reduced
depressive symptoms while men use alcohol less frequently
(Simon 2002). After union dissolution, women are more prone
to internalizing stress, increasing depression risk, whereas men
tend to exhibit externalizing behaviors, such as a heightened
risk of alcoholism (Wu and Hart 2002). One explanation is that
after separation, women are more affected by resource loss,
especially by the loss of economic stability, which can worsen

mental health (Leopold 2018). This gender difference may ex-
plain why re-partnering offers women, especially mothers, a
potential recovery route (Jansen et al. 2009). However, research
for the UK showed that while women's life and financial satis-
faction improved after re-partnering, their mental health did not
(Dierker et al. 2025).

Research indicates that childbirth has greater mental health
benefits for women than for men (Metzger and Gracia 2023).
However, single mothers, especially those experiencing union
dissolution, remain a vulnerable group for mental health issues
(Burstrom et al. 2010; Crosier et al. 2007). Generally, women's
mental health seems more affected by unstable family histories
than men's (Jung 2023).

In contrast, family transitions often have stronger physi-
cal health effects for men. Marriage provides more physical
health protection for men than for women (Kiecolt-Glaser and
Newton 2001), and union transitions have stronger effects on
men's physical health (Leopold 2018; Wu and Hart 2002). Men
also benefit more from union stability, as O'Flaherty et al. (2016)
found that family life course trajectories affect men's physical
health more than women's. Another study showed that men
experience health improvements only after marriage, not after
cohabitation (Rapp and Stauder 2020). However, none of these
studies investigated the role of accumulated family complexity
and its long-term impact on physical health.

In summary, gender differences in the implications of family
complexity may reflect how stress is experienced and expressed.
These differences underline the importance of examining men's
and women's mental and physical health outcomes separately
when studying long-term associations between family complex-
ity and health.

## 2.5 | The Present Study

In this study, we build on a life course approach to investigate
how accumulated family complexity in mid-adulthood is associ-
ated with men's and women's mental and physical health. Given
the theoretical considerations presented above, several hypoth-
eses can be derived from the literature and tested in this study.
For mental health, we draw on research suggesting unstable re-
lationship patterns are linked to worse mental health than stable
patterns (Halpern-MEEKIN and Turney 2022; Jung 2023). This
may be reinforced by the presence and birth of new children
(Leopold and Kalmijn 2016). We therefore hypothesize that *ac-
cumulated family complexity in mid-adulthood is negatively asso-
ciated with mental health (Hypothesis 1a)*. Although findings are
mixed, literature suggests unstable family patterns are linked to
worse physical health, possibly due to chronic strains and risky
health behavior (Hughes and Waite 2009; O'Flaherty et al. 2016;
Rapp and Stauder 2020; Williams et al. 2008). We therefore hy-
pothesize that *accumulated family complexity in mid-adulthood
is negatively associated with physical health (Hypothesis 1b)*.

Studies on health trajectories around transitions and sequence
analyses have increasingly focused on gender differences
in links between family complexity and health (Jung 2023;
Leopold 2018). Findings indicate that for certain transitions
or family histories, association strength or direction differs by gender. For mental health, prior research mainly suggests that women's responses to both positive and negative family events are more pronounced than men's (Jung 2023; Metzger and Gracia 2023; Simon 2002). Given this, we hypothesize that *the negative association between family complexity and mental health is stronger for women than for men (Hypothesis 2a).* For physical health, previous research shows men benefit more from union formation and suffer more from union dissolution. However, it has not been examined how associations between accumulated family complexity and physical health differ by gender. This study is the first to compare this. Based on the theoretical considerations and findings of previous research, we hypothesize that *the negative association between family complexity and physical health is stronger for men than for women (Hypothesis 2b).*

Overall, this study's theoretical and methodological approach provides deeper insights into the link between family complexity and health. (1) Our design allows investigation of long-term effects of family transitions and accumulated complexity on physical and mental health. Prior findings for physical health have been mixed. While previous mental health findings have consistently reported short-term changes, less is known about long-term consequences. Furthermore, while previous research has often focused on well-being factors that change dynamically in response to life events, such as life satisfaction, we measure mental and physical health using the short form questionnaire score (SF-12). The SF-12 subscales, derived from the widely used SF-36 survey, provide validated, standardized measures of both dimensions of health, allowing consistent examination of both health outcomes. (2) We do not focus on the association between health and specific family states or transitions, but instead examine how the accumulated family transitions over the life course shape mid-adulthood health, adjusting for the current family state. (3) Lastly, flexible weighting of transitions, for example defining only transitions after a separation or a separation with children as complex, enables the investigation of accumulated family trajectories following these transitions and their association with health in mid-adulthood.

# 3 | Method

## 3.1 | Sample

We use data from the UK Household Longitudinal Study (UKHLS), a nationally representative, household-based longitudinal survey (University of Essex 2023). The survey began in 2009 and is conducted annually as a follow-up to the British Household Panel Study (BHPS). We obtained family histories from the Marital and Cohabitation Histories, 1991–2021 dataset, which includes the start and end dates for partnerships, including marriages, civil partnerships, and cohabitations, reported by adult respondents in all survey samples. Additionally, we included information on the number and the ages of biological children, as well as information on mental and physical health and basic demographics from the individual respondent datasets.

The Marital and Cohabitation Histories dataset initially contained 66,671 individuals (36,597 women, 29,965 men, and 109

with missing sex). We first removed records with missing sex (109), missing birth year (21) or unrealistic combinations of survey year and birth year that indicate negative age values (26), resulting in a refined dataset of 66,515 individuals (36,571 women and 19,944 men). Next, we considered individuals with 37 years of documented partnership history between the ages of 18 and 55, resulting in a sample of 27,002 individuals (14,757 women and 12,245 men).

Finally, to analyze the association between family trajectories and health outcomes, we selected a subset of 6045 individuals (3407 women and 2638 men) with data on mental and physical health (assessed using the SF-12) and relevant control variables at age 55. The age cutoff of 55 years was chosen because we need a sample with consistent family trajectories from early to mid-adulthood for comparable analyses, and because widowhood is less relevant in this age group (Rashid et al. 2021). Previous research has also defined a mean age of 55 as “mid-life” (Hughes and Waite 2009). All individuals in this analytical sample were born between 1954 and 1967.

## 3.2 | Measures

### 3.2.1 | Family Complexity

We use three different independent variables in our analyses that capture different variations of family complexity. To estimate the impact of family complexity on health at age 55, we quantify complexity into individual scores using sequence analysis. In total, we consider 12 different states covering all combinations of the four partnership states (single, cohabiting, married, previously partnered) and the three child information states (no children, youngest child 0–17 years old, youngest child 18 years old or older). Figure 1 shows the relative frequencies of these states from age 18 to age 55. A visualization of the transition rates, also showing all potential states preceding and following a specific state, is presented in the Supporting Information.

Our first outcome variable is the sequence complexity index. It measures variability within sequences by calculating the geometric mean of normalized transitions and normalized longitudinal entropy in a sequence (Gabadinho et al. 2010, 2011; Van Winkle 2018). Formally, the complexity $C$ of a sequence $x$ is defined as

$$C(x) = \sqrt{\frac{q(x)}{q_{\max}} \times \frac{h(x)}{h_{\max}}}$$

where the number of transitions within a sequence $q(x)$ is divided by the theoretical maximum number of transitions possible $q_{\max}$ and the longitudinal entropy of a sequence $h(x)$ is divided by the theoretical maximum $h_{\max}$ of longitudinal entropy. The longitudinal entropy represents the degree of unpredictability of a sequence and is defined as

$$h(x) = - \sum_{i}^{s} \pi_{i} \log \pi_{i}$$
<figure><img src="image_3.png" /><figcaption>FIGURE 1 | State frequencies. [Color figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

where $\pi_i$ is the proportion of occurrences in a given state $i$ of the sequence alphabet $s$. Accordingly, the theoretical maximum $h_{max}$ is given when each state occurs an equal number of times. This is defined as

$$h_{max} = -\log \frac{1}{A}$$

where $A$ is the size of the sequence alphabet. The sequences we focus on encompass 12 possible elements in 38 consecutive years for all individuals in our sample, which is why $h_{max}$ is $-\log \frac{1}{12} = 2.485$.

A detailed applied example on the construction of the sequence complexity index is presented in the Supporting Information. Overall, the sequence complexity index $C(x)$ is based on the number of different life course states and the unpredictability of individual partnership life courses.

Our two other independent variables are extensions of the sequence complexity index. We call these weighted complexity indices. These are based on the precarity index (Ritschard et al. 2018), where the sequence complexity index is weighted with a correction factor based on the share of potentially negative transitions (Raab and Struffolino 2023, p. 47). This enables us to consider whether certain transitions in the sequence complexity index are potentially advantageous or disadvantageous. The precarity index increases with the number of negative transitions and the degree of complexity. It is defined as

$$wC(x) = C(x)^{\alpha}(1+d(x))^{\beta}$$

where $(1+d(x))$ is a non-negative correction factor for the non-weighted sequence complexity $C(x)$. The difference between the

proportion of potentially disadvantageous and advantageous transitions in a sequence is represented by $d(x)$. Additionally, $\alpha$ and $\beta$ are exponential weights that adjust the relative influence of the non-weighted sequence complexity index and the correction factor. The correction factor adjusts for the way complexity is calculated, ensuring that transitions are not overly down-weighed when they are infrequent in a given time frame. A $\beta$ value greater than 1 increases the influence of this correction, which can be useful when the number of partnership transitions is relatively low (Hiekel and Vidal 2020). In our analyses, we set $\alpha$ to 1 and $\beta$ to 1.5, following previous studies that found these and similar values to yield stable results (Hiekel and Vidal 2020; Ritschard et al. 2018). Importantly, analyses using smaller or larger $\beta$ produced similar results, confirming the robustness of our findings to this choice.

For partnership histories, Hiekel and Vidal (2020) introduced a weighted complexity index, where the first episode of union instability is the starting point of a complex partnership trajectory. Extending this weighting scheme, we have constructed two weighted complexity indices: one where the first separation is the starting point of complexity, and the other where the first separation with a child is the starting point of complexity. Detailed information on how the weightings are applied is presented in the Supporting Information.

While all three indices (non-weighted sequence complexity index and the two weighted complexity indices) address the same overarching hypotheses regarding the impact of accumulated family complexity on health outcomes, differentiating the starting points allows us to explore potential nuances in how the experience of separation (with the presence of children) might influence this association. More specifically, while the non-weighted complexity index counts all family transitions between states presented in Figure 1 towards
increasing family complexity, the weighted indices count (1) all transitions following a separation and (2) all transitions following a separation with a minor child as increasing complexity. These alternative starting points capture the notion that separation, especially when children are involved, may mark a shift towards trajectories characterized by heightened stress, economic disadvantage, and caregiving strain, which could amplify the negative health implications of subsequent family complexity. If, for example, the expected negative association between complexity and health is stronger for the weighted indices compared with the non-weighted complexity index, this would imply that the accumulation of family transitions after a separation (with children) is more detrimental to health compared with family histories that do not include separation experiences.

### 3.2.2 | Physical and Mental Health

We measure our outcome variables as physical and mental health at age 55. We use the six-item physical health and mental health subscales of the SF-12 as indicators. The Short Form Survey SF-12 contains six items related to physical and mental health problems. These items are self-assessed with varying response options. A standard norm-based algorithm is employed to combine item scores into a total physical and mental health score (Ware et al. 1996, 1995). Both scores are continuous, ranging from 0 to 100, where higher scores indicate better health. More detailed information on the individual items and the construction of the scales is provided, among others, by Turner-Bowker and Hogue (2014).

### 3.2.3 | Controls

Focusing on health and family complexity at age 55 for all individuals, adjusting for the calendar year accounts for both cohort and period effects. This is crucial, as family complexity has been demonstrated to change across different cohorts and time periods (Van Winkle 2018). Furthermore, we control for any health conditions diagnosed during childhood for each individual. In the UKHLS individual respondent questionnaire, participants are asked to indicate the age at which they were first informed that they had a specific health condition with the following question: "What age were you when you were first told you had [condition]?" We generate a binary variable with a value of one for respondents who reported being diagnosed with any health condition before the age of 18. Additionally, we include controls for the highest educational or vocational qualification at age 55 based on six categories: "Degree," "Other higher degree," "A-level and so forth," "GCSE and so forth," "Other qualification," and "No qualification." The specific educational and vocational qualifications falling into each category are detailed in the Supporting Information. We do not adjust for employment status because labor market decisions can be determined by certain transitions in family histories, which casts doubt on the confounding effect of employment status on the relationship between family complexity and health we seek to examine (Riekhoff and Järnefelt 2017). We also control for the current family status at age 55, that is, the combination between partnership state and child information, as presented in Figure 1.

## 3.3 | Analytic Approach

We estimate the association between family complexity and mental and physical health using OLS regressions. Additional models with standard errors clustered at the household level yielded almost identical results, accounting for the nesting of 6045 individuals aged 55 within 5864 households. For all models, we estimate the association of family complexity with health at age 55 separately for physical and mental health. Gender is included as an interaction variable and a main covariate in all models, and we present marginal effects by gender in the results section.

For the non-weighted sequence complexity index, we estimate three models. First, we run a base model without any control variables. Second, we include calendar year, health conditions during childhood, and education as control variables. Third, we extend the second model by adding the current family status as a control variable. Controlling for current family status in an additional model allows us to assess whether the associations between family complexity and health in mid-adulthood primarily reflect the current family status. Moreover, controlling for this status enables us to examine whether accumulated family complexity is independently associated with health, beyond the potential impact of the current marital status.

For the weighted complexity indices, we also estimate three models. First, we include calendar year, health conditions during childhood, and education in addition to the respective weighted complexity index as covariates. Second, we add a dummy variable that takes a value of one if the complexity of the respondent is zero, and a value of zero if the respondent has experienced any transition defined as complex. This approach aligns with He et al.'s (2014) recommendations for addressing zero-inflated independent variables in regression analyses. This is done to capture the association among individuals who have experienced any complex transition. Third, we also include the current family status.

# 4 | Results

## 4.1 | Descriptive Results

Descriptive characteristics of the analytical sample are presented in Table 1. The sample consists of 2638 men and 3407 women with an average birth year of 1960. The family complexity score is 0.19 (SD: 0.07) for men, and is slightly higher for women, at 0.20 (SD: 0.08). A greater proportion of women (46.2%) than of men (36.9%) have experienced union dissolution between the ages of 18 and 55. The weighted family complexity following union dissolution is also higher for women (mean: 0.11, SD: 0.15) than for men (mean: 0.09, SD: 0.15). The share of respondents who have experienced union dissolution with a minor child between the ages of 18 and 55 is 9.3% for men and 22.9% for women. However, we are not able to differentiate according to custody arrangements due to data limitations. The weighted family complexity following union dissolution with a minor child is lower for men (mean: 0.01, SD: 0.05) than for women (mean: 0.03, SD: 0.08). Regarding health outcomes, men have a mean physical health score of 49.7 (SD: 10.6) on the SF-12 scale, while women have a slightly lower mean health score of 48.3 (SD: 11.9). In terms of mental health, men have a mean score of 50.2 (SD: 9.7), while women have a mean score of 48.0 (SD: 10.5).
Additionally, 29.0% of men and 24.5% of women hold a university degree, and 5.5% of men and 5.6% of women report having a health condition diagnosed during childhood.

## 4.2 | Multivariate Results

### 4.2.1 | Family Complexity and Physical and Mental Health in Mid-Adulthood

The association between accumulated family complexity in mid-adulthood and health outcomes is illustrated in Figure 2, in which three models progressively add control variables. Model 1 includes only the standardized sequence complexity index as the

independent variable; Model 2 controls for calendar year, childhood health conditions, and education; and Model 3 adds current family status at age 55. Regression tables with full interaction models by gender are presented in the Supporting Information, while the figures in this section show marginal effects by gender derived from these models. The models show the association between health and z-standardized family complexity. To facilitate interpretation, one standard deviation difference in family complexity is associated with a difference of approximately 1.5 family transitions experienced between ages 18 and 55.

The coefficients of Models 1 and 2 show a negative association between family complexity and mental health, particularly for women. Women's mental health scores significantly decrease in

<table><caption>TABLE 1 | Descriptive sample characteristics.</caption><thead><tr><th rowspan="2"></th><th>All</th><th colspan="2">Men</th><th colspan="2">Women</th><th colspan="2">Gender diff.</th></tr><tr><th>Mean/%</th><th>SD</th><th>Mean/%</th><th>SD</th><th>Mean/%</th><th>SD</th><th>p</th></tr></thead><tbody><tr><td>Family complexity (range: 0–1)</td><td>0.19</td><td>0.07</td><td>0.19</td><td>0.07</td><td>0.20</td><td>0.08</td><td>0.000</td></tr><tr><td>Ever experienced union dissolution (%)</td><td>42.2</td><td></td><td>36.9</td><td></td><td>46.2</td><td></td><td>0.000</td></tr><tr><td>Weighted family complexity following union dissolution (range: 0–1)</td><td>0.10</td><td>0.15</td><td>0.09</td><td>0.15</td><td>0.11</td><td>0.15</td><td>0.002</td></tr><tr><td>Ever experienced union dissolution with a minor child (%)</td><td>17.0</td><td></td><td>9.3</td><td></td><td>22.9</td><td></td><td>0.000</td></tr><tr><td>Weighted family complexity following union dissolution with a minor child (range: 0–1)</td><td>0.03</td><td>0.07</td><td>0.01</td><td>0.05</td><td>0.03</td><td>0.08</td><td>0.000</td></tr><tr><td>Physical health (SF-12) (range: 0–100)</td><td>48.9</td><td>11.3</td><td>49.7</td><td>10.6</td><td>48.3</td><td>11.9</td><td>0.000</td></tr><tr><td>Mental health (SF-12) (range: 0–100)</td><td>49.0</td><td>10.2</td><td>50.2</td><td>9.7</td><td>48.0</td><td>10.5</td><td>0.000</td></tr><tr><td>University degree (%)</td><td>26.5</td><td></td><td>29.0</td><td></td><td>24.5</td><td></td><td>0.000</td></tr><tr><td>Health condition diagnosed during childhood (%)</td><td>5.6</td><td></td><td>5.5</td><td></td><td>5.6</td><td></td><td>0.865</td></tr><tr><td>Birth year (1954–1964)</td><td>1959.6</td><td>3.4</td><td>1959.7</td><td>3.4</td><td>1959.6</td><td>3.5</td><td>0.293</td></tr><tr><td>N</td><td>6045</td><td></td><td>2638</td><td></td><td>3407</td><td></td><td></td></tr></tbody></table>

### Associations between family complexity and health at age 55

<figure><img src="image_4.png" /><figcaption>FIGURE 2 | Regression coefficients showing the associations between the sequence complexity index and physical and mental health among men and women. [Color figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>
both Model 1 (−0.57) and Model 2 (−0.58) with each additional standard deviation in family complexity, indicating that complex family histories have adverse mental health implications. However, this association loses significance after controlling for current family status in Model 3, which suggests that women's mental health is more sensitive to recent family circumstances than it is to cumulative complexity alone. For men, no significant association between family complexity and mental health emerges in any model, which implies that men's mental health is less influenced by accumulated family transitions.

In contrast, the coefficients show no significant association between family complexity and physical health across the models for either men or women. This lack of association indicates that in this sample, accumulated family complexity in mid-adulthood does not appear to impact physical health. These results imply that while family complexity affects mental health selectively among women, it does not affect physical health outcomes in mid-adulthood among either men or women.

## 4.2.2 | Family Complexity Following a Separation and Physical and Mental Health in Mid-Adulthood

Figure 3 presents the association between family complexity and health outcomes, focusing on family transitions occurring after an initial separation. Model 1 includes controls for calendar year, education, and childhood health diagnoses. Model 2 introduces a zero-dummy to account for individuals who have not experienced separation, while Model 3 further controls for current family status. The models also show the association between health and z-standardized weighted family complexity. To facilitate interpretation, one standard deviation difference in family complexity following a separation, if this complexity is not zero, is associated with a difference of approximately 0.9 post-separation family transitions experienced between ages 18 and 55.

Increased family complexity following a separation is significantly associated with poorer mental health outcomes, particularly for men. Men's mental health scores show consistent

reductions across all models, with declines of −0.79 in Model 1, −0.74 in Model 2, and −0.87 in Model 3. These findings suggest that accumulated transitions post-separation have a long-term negative association with men's mental health. Women also experienced a significant decline in mental health in Model 1 (−1.02), although the association became non-significant after additional controls are applied in Models 2 and 3. These results highlight that while both men and women experience mental health declines with increased family complexity after separation, the associations among men appear to be more robust across different model specifications. For women, the reduction after adding the zero dummy suggests that the association between family complexity and mental health primarily reflects differences between women who have experienced any separation and those who have not. Among women who have separated, additional complexity beyond the initial separation does not further explain differences in mental health.

The coefficients show that family complexity following separation is significantly associated with poorer physical health in both men and women. For men, each additional standard deviation in family complexity is linked to consistent reductions in physical health across all models, with significant declines of −0.77 in Model 1, −0.89 in Model 2, and −0.94 in Model 3. Similarly, among women, there is a significant reduction in physical health scores in Models 1 and 3 (−0.80 and −0.77, respectively), although this association is non-significant in Model 2. These findings indicate that family complexity following separation negatively impacts physical health for both women and men, though the association is somewhat stronger for men.

## 4.2.3 | Family Complexity Following a Separation With a Minor Child and Physical and Mental Health in Mid-Adulthood

In Figure 4, we explore the association between family complexity and health outcomes in cases of a separation involving a minor child. Model 1 controls for calendar year, education, and childhood health diagnoses. Model 2 includes a zero dummy for individuals without separation experience, and Model 3 adds

<figure><img src="image_5.png" /><figcaption>Associations between family complexity following separation and health at age 55</figcaption></figure>

**FIGURE 3** | Regression coefficients showing the associations between the weighted complexity index (all transitions following an initial separation add complexity) and physical and mental health among men and women. [Color figure can be viewed at wileyonlinelibrary.com]
controls for current family status. The models also show the as-
sociation between health and z-standardized weighted family
complexity. To facilitate interpretation, one standard deviation
difference in family complexity following a separation with a
minor child, if this complexity is not zero, is associated with a
difference of approximately 0.4 family transitions experienced
after the separation with a minor child between ages 18 and 55.

The results show that family complexity following a separation with a minor child is significantly associated with poorer mental health, especially for women. For women, each standard deviation increase in family complexity results in a significant reduction in mental health in Model 1 (−0.88); although this association becomes non-significant in Models 2 and 3. For men, a significant negative association with mental health is found only in Model 1 (−0.47) and becomes non-significant with the addition of further controls. These findings imply that family complexity following a separation with a minor child has a limited but notable impact on mental health, primarily among women.

We also observe that family complexity following a separation with a minor child significantly reduces physical health across all models. Women's physical health scores decrease by -0.89 in Model 1, -0.77 in Model 2, and -1.03 in Model 3, suggesting a sustained adverse impact of family complexity on physical health in this context. For men, physical health declines significantly only in Model 1 (-0.65), and the association becomes non-significant in subsequent models. These results indicate that family complexity following a separation with a minor child more consistently affects the physical health of women than of men.

When linking these findings to the hypothesis, the evidence
provides partial support for all hypotheses. However, the extent
of support is highly contingent on the type of complexity spec-
ification. Hypothesis 1a, which states that accumulated family
complexity in mid-adulthood is negatively associated with men-
tal health, is supported based on the results of all three spec-
fications of family complexity, with some differences between
women and men. Hypothesis 1b, which states that accumulated

family complexity in mid-adulthood is negatively associated
with physical health, is only supported when family complexity
following either a separation or a separation with an underage
child is examined.

Regarding the gender-specific hypotheses, there is also some
variation across specifications of family complexity. Hypothesis
2a, which states that the negative association between fam-
ily complexity and mental health is stronger for women than
for men, is partially supported regarding the association be-
tween the non-weighted family complexity and mental health.
However, these findings are sensitive to the inclusion of current
family status, which renders the association non-significant
for women as well. For complexity after separation, there is
no support for Hypothesis 2a, while it is supported when com-
plexity after a separation with an underage child is considered.
Regarding physical health and gender differences, Hypothesis
2b states that the negative association between family complex-
ity and physical health is stronger for men than for women. This
hypothesis is supported only by the results from the models in-
vestigating the association between family complexity follow-
ing a separation and physical health, with the association being
stronger among men.

4.3 | Sensitivity Tests on Sample Selection

As presented in the data section, the sample size was substan-
tially reduced after excluding individuals with incomplete rela-
tionship histories and those with missing health information.
To assess whether these exclusions may have introduced bias,
we compared key characteristics across three groups: the final
sample, individuals excluded due to incomplete relationship his-
tories, and individuals excluded due to missing health informa-
tion, as presented in Table 2.

The comparison indicates that the main reason for exclusion
due to incomplete relationship histories was that most of these
individuals had not yet reached age 55 at their last recorded in-
terview. This is reflected in the mean age of 42 in this group

<figure><img src="image_6.png" /><figcaption>Associations between family complexity following separation with a child and health at age 55</figcaption></figure>

**FIGURE 4** | Regression coefficients showing the associations between the weighted complexity index (all transitions following an initial separation with an underage child add complexity) and physical and mental health among men and women. [Color figure can be viewed at wileyonlinelibrary.com]
compared with 59 in the final sample. Specifically, 36,026 out of 39,669 individuals excluded for incomplete relationship histories were younger than 55 at their last interview. Conversely, those with valid relationship histories but missing health information were significantly older, with a mean age of 73. While this seems to indicate that the respondents without health information are exceptionally old, the reason for this is that those who were too young in the last survey year to be included in the sample (i.e., younger than 55) have already been removed from this sample. Therefore, we also looked at the respondents with missing health information from the total sample, and the mean age in this sample is approximately 49 years, which is substantially younger.

Differences in the calendar year of the last interview further show that the average last interview year was earlier among excluded individuals. However, in all three groups, the largest share of participants had their last interview in 2020 or 2021. To explore whether relationship disruption contributed to survey attrition, we examined relationship status at the last interview. The proportion of participants in an ongoing relationship was highest in the final sample (76%), compared with 71% among those with incomplete relationship histories and 67% among those with missing health information. Additionally, 6% of individuals in the final sample had been diagnosed with a health condition in childhood, compared with 10% in the incomplete relationship history sample.

Other sociodemographic comparisons show that household income in the last interview year was higher in the final sample than in the excluded groups. While university degree attainment (also measured in the last interview year) was similar between the final sample and those removed due to incomplete

relationship histories, it was substantially lower in the group excluded for missing health information.

Overall, these comparisons highlight potential selection effects related to relationship status, childhood health conditions, and socioeconomic factors. However, the primary reason for exclusion was insufficient data for constructing relationship histories from ages 18 to 55, as many individuals had not yet reached 55 at their last interview.

## 5 | Discussion

This study aimed to enhance our understanding of how family complexity, viewed through a life course perspective, influences long-term physical and mental health in mid-adulthood for both men and women. We examined whether complexity, that is, unpredictability and uncertainty, in family life courses between ages 18 and 55 is associated with health outcomes and whether patterns of accumulation following certain transitions have particularly strong health impacts.

Our analysis of family complexity and health outcomes in mid-adulthood produced three main findings. First, the non-weighted sequence complexity index showed a negative association with mental health for mid-aged women, which indicates that complexity is detrimental to mental health. Weaker and non-significant associations with men's mental health were found, which suggests that family complexity has larger negative impacts on women's mental health than on men's mental health. However, this association disappeared when controlling for the current family status, which suggests that current circumstances may reflect the current mental

<table><caption>TABLE 2 | Descriptive information on sample selection.</caption><thead><tr><th rowspan="2"></th><th colspan="2">Final sample</th><th colspan="2">Incomplete relationship history</th><th colspan="2">Missing health information (complete relationship history)</th></tr><tr><th>Mean</th><th>SD</th><th>Mean</th><th>SD</th><th>Diff. from final sample (p-values)</th><th>Diff. from final sample (p-values)</th></tr></thead><tbody><tr><td>Age at last interview</td><td>59.4</td><td>3.4</td><td>42.3</td><td>12.0</td><td>0.000</td><td>73.2</td><td>9.3</td><td>0.000</td></tr><tr><td>Calendar year at last interview</td><td>2019.0</td><td>2.8</td><td>2015.6</td><td>4.5</td><td>0.000</td><td>2015.6</td><td>4.5</td><td>0.000</td></tr><tr><td>Birth year</td><td>1959.6</td><td>3.4</td><td>1966.9</td><td>113.0</td><td>0.000</td><td>1942.5</td><td>9.8</td><td>0.000</td></tr><tr><td>Women (%)</td><td>56.4</td><td></td><td>55.1</td><td></td><td>0.057</td><td>54.2</td><td></td><td>0.002</td></tr><tr><td>Ongoing relationship at last interview (%)</td><td>76.0</td><td></td><td>70.6</td><td></td><td>0.000</td><td>66.6</td><td></td><td>0.000</td></tr><tr><td>Health condition diagnosed during childhood (%)</td><td>5.6</td><td></td><td>10.1</td><td></td><td>0.000</td><td>3.5</td><td></td><td>0.000</td></tr><tr><td>HH income at last interview</td><td>3856.3</td><td>5720.9</td><td>3589.5</td><td>6633.2</td><td>0.004</td><td>2614.4</td><td>2148.5</td><td>0.000</td></tr><tr><td>University degree (%)</td><td>26.8</td><td></td><td>29.8</td><td></td><td>0.000</td><td>13.8</td><td></td><td>0.000</td></tr><tr><td>N</td><td>6045</td><td></td><td>39,669</td><td></td><td></td><td>20,957</td><td></td><td></td></tr></tbody></table>
health status more strongly than accumulated family com-
plexity. Second, for men, the association between complexity
following separation and health was found to be consistently
significant, which indicates that complexity is detrimental to
physical health. For women, health disparities were linked
primarily to whether or not they have experienced separa-
tion, and not to the accumulation of complexity beyond sep-
aration. The more substantial negative associations observed
between physical health and men's family complexity support
Hypothesis 2b. Third, we found that transitions following a
separation with children do not significantly impact men's
health, but negatively affect mothers' physical health, which
indicates that accumulated complexity after a separation with
children impacts mothers in particular, an outcome that was
not anticipated by the gender-specific hypotheses.

We make three main contributions to the literature in this
study. First, we are the first to use family complexity mea-
sures (Gabadinho et al. 2010) to demonstrate that accumu-
lated family complexity negatively impacts both mental and
physical health in mid-adulthood. This finding holds even
when going beyond current health status as well as adjusting
for the current family state. Although these long-term and
cumulative impacts of family complexity are relatively mod-
est, we were able to show that family complexity is especially
consequential in the long-term for physical health. Second,
we have applied flexible weighting techniques (Hiekel and
Vidal 2020; Ritschard et al. 2018) to highlight the increased
vulnerability of individuals who experience separation, espe-
cially with children, showing that accumulated complexity
following a separation is associated with a further deteriora-
tion of health outcomes. Third, while previous research has
primarily observed gender differences when comparing indi-
viduals in different living arrangements (Kiecolt-Glaser and
Newton 2001; Simon 2002) or within individual family tran-
sitions (Leopold 2018; Myrskylä and Margolis 2014; Rapp and
Stauder 2020), we have revealed that there are also gender dif-
ferences in the impact of accumulated family complexity on
health, thus shedding light on the long-term impact of complex
family histories. Our results largely support the life course
health development model (Halfon and Hochstein 2002) by
indicating that health in mid-adulthood reflects not only the
specific family status but also the cumulative impact of family
transitions over time.

Our findings highlight important gender differences in the
health implications of family complexity. For women, the associ-
ations for mental health appeared to be primarily linked to their
current family status. Significant negative associations were ob-
served only when neither the current family status nor the accu-
mulation of complexity beyond an initial separation event was
considered. These associations disappeared when controlling
for current family status, in line with theories and previous find-
ings suggesting that after union dissolution, individuals experi-
ence short-term mental health declines, followed by adjustment
(Kravdal and Wörn 2023; Kühn et al. 2023; Leopold 2018). In
contrast, physical health impacts among women emerged only
when complexity arose from transitions related to separation,
particularly with children. These associations were negatively
significant after controlling for the current family status, which
suggests that the long-term accumulation of complexity is more

consequential for physical health. This aligns with research
demonstrating that there are long-term changes in physical
health after separation, at least for certain indicators (Kravdal
and Wörn 2023). It is also consistent with the life course health
development model, which posits that (physical) health reflects
cumulative experiences over time (Barban 2013; Halfon and
Hochstein 2002). For men, accumulated family complexity fol-
lowing a union dissolution was found to have consistent and
enduring negative associations with both mental and physical
health that persisted even after controlling for current family
status. This pattern suggests that while mental health may ini-
tially return to baseline after union dissolution (Kalmijn 2017;
Leopold 2018), accumulated complexity in an individual's fam-
ily history throughout the life course may translate into adverse
health outcomes by mid-adulthood.

5.1 | Implications for Policy and Future Research

Our findings regarding the cumulative impact of family com-
plexity highlight the need for policies that support individuals
who experience complex family transitions in order to mitigate
long-term health disparities. For example, these policies could
combine our findings with previous research that showed that
single mothers in the UK—a welfare state context with rather
weak support for vulnerable families compared with other
OECD countries (OECD 2021)—are more likely to end up in un-
stable relationship patterns that can be detrimental for health
(Dierker et al. 2025). Future research could further investigate
nuances in our findings to inform targeted interventions aimed
at reducing health inequalities linked to family complexity.

While previous research showed that family transitions have
short-term associations with health and well-being, our results
highlight the importance of considering family dynamics over a
longer period when conducting research on cumulative health
disadvantages over the life course. Interestingly, we found that
this pattern mainly applies to physical health, while mental
health tends to reflect the current family state. This aligns with
literature suggesting that mental health, as an affective indica-
tor (Diener 1984; Diener et al. 1999), is more sensitive to short-
term dynamics, whereas physical health often develops over
time; and with a study by Hughes and Waite (2009), who found
that physical health is more influenced by marital history while
mental health is more affected by the current status, because
physical health conditions tend to develop gradually while men-
tal health reactions tend to be rapid. One potential explanation
for these differences is that mental health, being more sensitive
to daily stressors and relationship context, may fluctuate with
immediate family circumstances, while physical health deterio-
ration often results from the cumulative impact of chronic stress
and reduced health behaviors associated with the experience of
accumulated family complexity.

Taken together, these findings suggest that family complexity
should be conceptualized within the life course framework as
a process that shapes health trajectories through both cumu-
lative and short-term dynamic pathways for mental and phys-
ical health. More specifically, especially among women, mental
health appears to reflect immediate relational contexts, while
physical health is more strongly shaped by the accumulation of
stress and disadvantage over time. These findings also indicate that gender is a key dimension in these processes, with women's physical health appearing particularly vulnerable to accumulated family complexity following separation from children. One potential explanation is that mothers may experience prolonged stress and constrained opportunities to recover due to caregiving responsibilities and financial strain after separation, while men's health may be affected differently due to variations in social support, health behaviors, and economic consequences following family transitions that do not necessarily involve parenthood.

Future research should further examine the mechanisms behind the observation that women who experience a period of single motherhood are especially likely to suffer from the additional accumulation of family complexity. In particular, the potentially detrimental effects on physical health of unstable patterns of new family formations (Recksiedler and Bernardi 2019) should be considered. Our findings also call for a deeper examination of the question of why accumulated complexity has a stronger impact on the physical health of mothers than of fathers, which contradicts the theoretical assumption that the impact of single life events on physical health is larger for men than for women (Simon 2002).

## 5.2 | Limitations

Several limitations of this study merit consideration. First, while our models account for health diagnoses during childhood, our analytical approach based on retrospective family history information does not permit any causal conclusions. Selection into family arrangements is a major topic in family and health research (Carr and Springer 2010), and we fully acknowledge that our findings show only associations between family complexity and health in mid-adulthood. More specifically, health conditions emerging after childhood may affect the likelihood and stability of family transitions and can therefore contribute to the observed associations between more complex family trajectories and poorer health outcomes. Descriptive analyses of missing data in partnership histories show that individuals with missing information have nearly double the prevalence of childhood health conditions compared with those with complete histories (10.1% vs. 5.6%). If individuals with missing partnership histories indeed experienced more unstable family trajectories, this would suggest that poorer health may precede and contribute to family instability. More broadly, the findings may reflect selection processes whereby individuals with poorer health are more likely to enter complex and unstable family trajectories.

Second, our lack of data on custody arrangements—relying on retrospective partnership histories and birth years of biological children—limits the interpretation of models examining complexity after a separation with children. It is known that most separations of parents in the UK lead to households where the child resides with the mother (Office for National Statistics 2021). However, analytically differentiating households according to custody arrangements could clarify whether single mothers' (physical) health disadvantages stem

from mothers typically having the primary care responsibilities after a separation.

Additionally, a substantial reduction in the sample size occurred due to the requirement for complete partnership histories and health information between ages 18 and 55. However, this reduction primarily affects individuals who had not yet reached the age of 55 by the time of the last available data, and thus, we do not believe that it introduces selection bias to our models. Sensitivity analyses comparing individuals with missing data to those who remained in the final sample found no substantial differences in key sociodemographic characteristics. While caution is always necessary with sample reductions, we believe that the findings remain robust, as the excluded individuals are likely to be younger and not yet experienced the health impacts linked to family complexity in mid-adulthood.

# 6 | Conclusion

In conclusion, our study has shown for the first time that family complexity, characterized by the accumulation of family transitions and the unpredictability of family life courses, is associated with health outcomes in mid-adulthood, with notable gender differences. Specifically, we found that while women's physical health is particularly vulnerable to the accumulation of family complexity following a separation with children, men's mental and physical health seems to be more affected by accumulated family complexity following any separation. These findings highlight the importance of considering both the type and the sequence of family events when examining their long-term and accumulated health impacts. Importantly, our study has revealed that physical health inequalities are not solely a consequence of experiencing a particular family status (such as single parenthood) but are also related to the broader life course trajectory and accumulated family complexity.

## Acknowledgments

P.D. was supported by the Strategic Research Council (SRC), FLUX consortium, decision numbers 364374 and 364375; by grants to the Max Planck—University of Helsinki Center from the Max Planck Society (5714240218), Jane and Aatos Erkko Foundation (210046), Faculty of Social Sciences at the University of Helsinki (77204227), and Cities of Helsinki, Vantaa and Espoo; and the European Union (ERC Synergy, BIOSFER, 101071773). Views and opinions expressed are, however, those of the author only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them. Further support provided from the International Max Planck Research School for Population, Health and Data Science (IMPRS-PHDS) is gratefully acknowledged. Z.V.W. was supported by the European Research Council through the European Union's Horizon 2020 research and innovation programme under the Grant Agreement No. 101117173 (WIDOW). Open Access funding enabled and organized by Projekt DEAL.

## Data Availability Statement

The data that support the findings of this study are available from the UK Data Service. Restrictions apply to the availability of these data, which were used under license for this study.
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## Supporting Information

Additional supporting information can be found online in the Supporting Information section. **Data S1:** Supporting Information.