Sage Journals: Discover world-class research

Abstract

In this longitudinal study the author investigates the association among work-to-family conflict (WTFC) and family-to-work conflict (FTWC), gender, and the frequency of physical activity among Australian parents. On the basis of the stress process theory and the conservation of resources theory, higher work-family conflict will likely lead to decreased physical activity because of limited resources. Gender differences are hypothesized, reflecting gendered role identification with work and family. The analysis uses data from 6,370 employed parents in the Household, Income and Labour Dynamics in Australia Survey, using ordered logit regression models with fixed effects. The results show that both WTFC and FTWC are negatively associated with physical activity. Gendered patterns are observed: whereas WTFC is associated with reduced physical activity among fathers and mothers, FTWC is only negatively associated with physical activity among mothers. These findings emphasize the importance to consider conflict directions and gender when examining health behaviors. Physical activity might represent another competing domain, causing a work-family-health conflict.

Keywords

work-family conflict physical activity health-promoting behavior gender differences panel data

The increase in women’s labor market participation (Baxter 2023a), and thus the increase in dual-earner couples (Baxter 2023b), can lead to challenges in balancing conflicting demands from work and family roles, particularly among parents. This interrole conflict, which arises from the incompatibility of work and family demands, is also known as work-family conflict (Greenhaus and Beutell 1985). Work-family conflict can further be divided into two conflict directions, depending on the source of conflict: when work interferes with family, it is defined as work-to-family conflict (WTFC), and when family interferes with work, it is defined as family-to-work conflict (FTWC) (Greenhaus and Beutell 1985). Elevated work-family conflict has been demonstrated to have adverse health-related outcomes. This association has been found for mental and physical health as well as different health behaviors, with the latter being relevant for this study (Allen et al. 2000; Borgmann, Rattay, and Lampert 2019). Health behaviors can be divided into health-risk behaviors, such as drinking alcohol or smoking, and health-promoting behaviors, such as physical activity. However, rather than benefiting from health-promoting behavior during conflict, which requires resources, increased work-family conflict may limit resources necessary for other activities beyond work and family. This can lead to engaging less in health-promoting behaviors, such as physical activity, which is the focus of this study.

Research indicates that physical activity mitigates stress, improves physical and mental health, and reduces mortality (Nocon et al. 2008; Rebar et al. 2015). However, instead of benefiting from the stress-reducing effects of physical activity, increasing work-family conflict may limit resources, such as time and energy, that reduce the capacities available for physical activity. This study draws on the stress process theory (Pearlin 1989; Pearlin et al. 1981) and the conservation of resources theory (Hobfoll 1989; Hobfoll et al. 2018) to propose a decrease in physical activity due to a lack of resources. This reduction can become a health risk, as studies show that physical inactivity and sedentary behavior are associated with different health conditions and reduce longevity (Cunningham et al. 2020; Katzmarzyk et al. 2019).

Yet the allocation of resources, particularly time, is highly stratified in societies (Vagni 2020). This is also evident in regard to gender. The distribution between paid and unpaid (care) work for men and women remains unequal (OECD 2017). This holds particularly true for parents, who are the objects of research, with mothers spending more time on unpaid care work and fathers on paid work. Gender differences also manifest in physical activity and leisure time more broadly: studies show that leisure time, including physical activity, is unequally distributed between men and women, with men having more leisure time (Bittman and Wajcman 2000; Mattingly and Blanchi 2003). For parents, this leisure time is narrower and includes both leisure time with and without the child (Craig and Mullan 2013). Still, fathers have more child-free leisure time than mothers (Craig and Mullan 2013). This makes the distinction between fathers and mothers crucial when examining the association between work-family conflict and physical activity.

The few existing studies on work-family conflict and physical activity tend to show that higher conflict levels are associated with a decrease in physical activity (Allen and Armstrong 2006; Grzywacz and Marks 2001; Lallukka et al. 2010; Pagnan, Seidel and MacDermid Wadsworth 2017; Roos et al. 2007). Although studies distinguishing between the two conflict directions have produced inconsistent results (Allen and Armstrong 2006; Grzywacz and Marks 2001; Roos et al. 2007), others have used an overall measure of work-family conflict (Lallukka et al. 2010) or have examined only one conflict direction (Pagnan et al. 2017). However, the two conflict directions are correlated but distinct constructs, necessitating a separate examination (Bellavia and Frone 2005; Byron 2005). This is particularly important when examining working parents, who can be expected to have high work demands as well as high family demands, especially when the children are young (Reimann et al. 2022). Existing gender roles further support this, as fathers can be expected to react more strongly to FTWC and mothers to WTFC because of different vulnerabilities to conflict from either direction. However, studies examining gender disparities are scarce and inconsistent in their results (Lallukka et al. 2010; Roos et al. 2007). Furthermore, all studies examined this relationship using cross-sectional data and, except for the samples of Grzywacz and Marks (2001) and Pagnan et al. (2017), all other studies had small sample sizes and, or study specific groups such as municipal employees. However, cross-sectional data cannot capture the dynamic nature of work-family conflict or analyze changes in physical activity related to work-family conflict (Pearlin 1999). Following these methodological limitations and inconclusive results, in the present study I examine the association between WTFC and FTWC with physical activity by gender using panel data.

The present study makes three contributions to the literature. First, it distinguishes between the two conflict directions, acknowledging that WTFC and FTWC are distinct constructs with different outcomes. Second, it applies a gender lens to examine how social structure shapes the relationship between work-family conflict and physical activity. Gender norms and resource inequality are likely to affect this relationship, particularly in countries such as Australia. Like many industrialized nations, Australia still represents a male breadwinner culture that is evident in a much higher likelihood of women being in part-time employment compared with other Organisation for Economic Co-operation and Development (OECD) countries, the gender care gap, and work-family policies that support a male breadwinner model (Baxter and Hewitt 2013; OECD 2024b, 2024c). Thus, Australia is a particularly suitable context in which to study the role of gender in this relationship. Thirdly, the study draws on the Household, Income and Labour Dynamics in Australia (HILDA) Survey, a nationally representative household survey (Watson and Wooden 2021). The dataset allows the study of 19 waves between 2002 and 2023, and the sample includes 6,370 employed individuals with underage children. I use ordered logit regression models with fixed effects to account for within-individual heterogeneity, going beyond previous cross-sectional studies.

Background

Work-Family Conflict and Physical Activity

To explore the relationship between work-family conflict and physical activity among mothers and fathers, I draw on the stress process theory (Pearlin 1989; Pearlin et al. 1981) and the conservation of resources theory (Hobfoll 1989; Hobfoll et al. 2018) to propose a decrease in physical activity based on the role of chronic strains and limited resources. The stress process theory (Pearlin 1989; Pearlin et al. 1981) posits that stressors, such as life events or chronic stressors, accumulate over time and negatively influence health and health behaviors. One such chronic stressor is work-family conflict, which many individuals are likely to experience because of their engagement in the major social roles of work and family, which are part of everyday life (Pearlin 1983). Stressors in various forms, including work-family conflict, are associated with lower physical activity (Stults-Kolehmainen and Sinha 2014). Because work-family conflict can take various forms, different pathways are expected. Next to the two conflict directions, work-family conflict can be further distinguished into time-, strain-, and behavior-based conflict (Greenhaus and Beutell 1985). Time-based conflicts occur when time pressures in one role make it difficult or even impossible to meet the demands of the other role. Strain-based conflict refers to the strain, such as tension, fatigue, or irritability, that arises from one role and limits performance in the other role. Behavior-based conflict concerns incompatibilities in behavioral expectations across both roles, but is less central for this study. Both work and family have been described as a greedy institution, requiring significant time and energy commitments that compete with one another (Coser 1967). This shows that work-family conflict requires an individual’s finite physiological and psychological resources that cannot be devoted to other domains, such as physical activity.

This is further supported by the conservation of resources theory (Hobfoll 1989; Hobfoll et al. 2018), which proposes that individuals seek to gain, protect and maintain resources, such as time and energy. However, when resources are threatened with loss or are lost, stress occurs. In the context of work-family conflict, an individual might experience conflict when resources, such as time and energy, are devoted to one domain, which limits resources in the other domain, producing time- or strain-based work-family conflict. Work-family conflict is associated with exhaustion, distress, negative emotions, such as guilt, and resource loss, such as performance (Apostol, Iorga, and Rotariu 2025; Canivet et al. 2010; Cooklin et al. 2016; DeBaylo and Michel 2022; Judge, Ilies, and Scott 2006; Wang et al. 2021). To cope with this conflict and the (threatened) loss of resources, individuals may adopt different strategies: shifting the focus of attention or reevaluating resources (Hobfoll 1989). Consequently, as physical activity also requires finite resources such as time and energy, an individual might reevaluate these resources and postpone physical activity, as work and family take priority and seem less dispensable. Among the main barriers to physical activity are perceived time scarcity, lack of energy, fatigue, exhaustion, distress, a lack of self-regulation, negative emotions, such as guilt (Garcia et al. 2022; Ingram, McCormick, and Gibson 2021; Mailey et al. 2014; Pedersen, Hansen, and Elmose-Østerlund 2021). Therefore, when work-family conflict intensifies and resources become strained, individuals might reduce engagement in physical activity to conserve resources for major social roles. Thus, physical activity and health behaviors more broadly might represent another domain from which individuals may draw resources.

Previous research supports these theoretical arguments, showing that higher conflict levels are associated with decreased physical activity (Allen and Armstrong 2006; Grzywacz and Marks 2001; Lallukka et al. 2010; Pagnan et al. 2017; Roos et al. 2007). These associations are mainly robust across various measures and samples: a binary measure of any physical activity in the last month (Allen and Armstrong 2006), vigorous physical activity in the United States (Grzywacz and Marks 2001; Pagnan et al. 2017), and a measurement following the recommendation by the World Health Organization (2020) of seven hours per week, including two hours of vigorous physical activity (Roos et al. 2007). As an exemption, Lallukka et al. (2010) reported inconsistent and insignificant effects for physical inactivity among British, Japanese, and Finnish public sector employees. They found a higher likelihood of physical inactivity for men and women in the Finnish and Japanese samples with strong work-family conflicts, but a lower likelihood for men and women in the British sample (Lallukka et al. 2010). Yet this study used an overall measure of work-family conflict and did not differentiate by conflict directions.

Regarding conflict directions, studies show mixed results. Allen and Armstrong (2006) found that FTWC was negatively associated with physical activity, but WTFC had no significant effect. Conversely, Grzywacz and Marks (2001) found that only WTFC was associated with a decrease in the frequency of vigorous physical activity but not FTWC. The only study also focusing solely on parents, which only examined WTFC, showed that parents with young children and higher levels of work-family conflict exercised more, whereas those with older children and higher conflict levels exercised less (Pagnan et al. 2017). This finding contradicts other studies and the expectation that parents with younger children have less leisure time and, thus, less time for physical activity (Martinez Mendiola and Cortina 2024; Simpson et al. 2022).

Overall, previous studies do not show a clear pattern regarding the conflict directions, but all studies support the theoretical consideration that work-family conflict reduces physical activity, even if this effect is sometimes observed for only one conflict direction. This study contributes to the literature by examining both conflict directions individually, addressing previous inconsistencies. Taking these considerations together, I hypothesize a decrease in physical activity for both conflict directions as individuals prioritize work and family over exercise:

Hypothesis 1a: Higher levels of WTFC are associated with a decrease in the frequency of physical activity.

Hypothesis 1b: Higher levels of FTWC are associated with a decrease in the frequency of physical activity.

Gender Differences, Conflict Directions and Physical Activity

Gender might influence how WTFC and FTWC are associated with physical activity differently for fathers and mothers. Time and energy are essential factors in balancing different demands and gaining more resources, such as benefiting from physical activity for later health, but women have fewer resources than men, leading to resource inequality (Vagni 2020). Despite a trend toward more egalitarian gender roles and more women participating in the labor market (OECD 2024a), women still bear a significantly higher share of unpaid care work, while men are overrepresented in paid work (OECD 2022b). Nevertheless, women have less leisure time than men, even when both work full-time, and this gap is more pronounced among parents (Bittman and Wajcman 2000; Craig and Mullan 2013). This is also the case in Australia (Baxter, Campbell, and Lee 2023), the focus of this study, where women are less likely to be employed full-time compared with women in other OECD countries (OECD 2024c), and are significantly more involved in care work than men (Australian Bureau of Statistics 2020–2021; Baxter et al. 2023). Australian work-family policies tend to support a traditional male breadwinner model, as evidenced by one of the shortest parental leave durations of 18 weeks and the lowest parental leave payment rate among OECD countries (OECD 2024b). Additionally, childcare costs in Australia are among the highest (OECD 2022a).

Thus, prevailing gender norms might influence not only the pathways into work-family conflict because of differences in resources and demands from work and family, but also how vulnerable men and women are to work-family conflict stemming from different directions (Thoits 1991). Thoits (1991) assumed that the stressors that become a threat to one’s identity are most relevant. Therefore, gender differences might exist because of different identifications with different roles. The norm of an ideal worker expects an employee to give priority to work and to keep work and family separate, which is primarily linked with the role of men, here fathers (Acker 2006). Women, in particular mothers, on the other hand, take more responsibility for family demands, and thus, might identify more with the family role. The norms of “intensive mothering” expect mothers to be fully focused on their children and to be the primary caregiver, which conflicts with their employment (Hays 1996). On the basis of these different norms, fathers might experience more conflict when family demands interfere with work, as the fulfillment of the work role is hindered. Correspondingly, WTFC might be more strongly associated with mother’s physical activity, as work demands hinder the ability to fulfill the family role. Greenhaus, Allen, and Spector (2006) also proposed that role salience plays a pivotal role in determining which conflict direction poses a greater threat to health. For women, the association of WTFC and health is stronger because their family role is hypothesized to be more salient, whereas the opposite is true for men. Therefore, fathers and mothers might prioritize different spheres over physical activity when experiencing time pressures or strains from work-family conflict, reducing physical activity. However, empirical evidence is mixed, with some studies finding (little) support for gender differences in vulnerability, whereas other studies find no support (Bilodeau, Marchand, and Demers 2020; Shockley et al. 2017). To determine whether it is vulnerability to stressors rather than gendered exposure, the models will control for these structural differences (e.g., time spent on paid and unpaid work).

The only study distinguishing between conflict directions and gender found that men and women with increased WTFC had a higher likelihood of not following the recommended guidelines on physical activity (Roos et al. 2007). This effect was stronger for women. For FTWC, associations were only found for women but not men. Comparing conflict directions, WTFC was more strongly associated with physical activity than FTWC. The authors discussed that the effects might be even stronger for parents with younger children, who were underrepresented because of the age restriction to 40- to 60-year-old respondents (Roos et al. 2007). These findings support the proposed mechanism for women, but not men. However, the sample was limited to municipal employees in Helsinki, Finland, and used only cross-sectional data. Although the study by Maciejewski and Tuppat (2025) examined work-family conflict and alcohol consumption, it used the same differentiation of work-family conflict, also applied a gender lens, and used the HILDA data. The authors showed that WTFC is related to an increase in drinking frequency among mothers, whereas FTWC is associated with an increase in drinking quantity among fathers, supporting the proposed mechanism.

On the basis of the theoretical argument of different vulnerabilities to conflict that hinders the ability to fulfill the role an individual identifies more with, I hypothesize as follows:

Hypothesis 2a: For fathers, FTWC is more strongly associated with a decrease in physical activity than WTFC.

Hypothesis 2b: For mothers, WTFC is more strongly associated with a decrease in physical activity than FTWC.

Data and Method

To analyze the relationship between work-family conflict and physical activity by gender, this study uses longitudinal data from the HILDA Survey (Watson and Wooden 2021). The survey has been conducted annually since 2001 and draws on a nationally representative sample of Australian households that has been selected through a multistage approach (Watson and Wooden 2012). Interviews are usually conducted face to face, but the pandemic prompted a shift to telephone interviews in waves 20 and 21, which did not influence data quality (Summerfield et al. 2024). The survey shows comparatively low attrition rates, with an average response rate of around 95 percent across waves (Summerfield et al. 2024). Additionally, respondents are also asked to complete a self-completion questionnaire (SCQ). The interviews and the SCQ include questions on all aspects of life, focusing on work, income, and family (Watson and Wooden 2021).

For this study, I include all waves in which work-family conflict and physical activity were surveyed, resulting in 19 waves from 2002 to 2023. The 2001, 2018, 2020, and 2022 survey years had to be excluded as work-family conflict and commuting time were not surveyed in these years. As questions about work-family conflict and physical activity are only a part of the SCQ, the sample is limited to respondents who completed the SCQ, which has a lower response rate of around 90 percent (Watson and Wooden 2021). Furthermore, this study’s sample consists of employed individuals with at least one child younger than 18 years in the household who are between 18 and 64 years old, resulting in 67,294 observations. This includes parents in two-parent families and single parents. I excluded respondents who only participated in one wave to be able to examine within change. Last, cases with missing values in the dependent, independent, and control variables are excluded. As the ordered logit regression with fixed effects only includes cases with variation in the dependent variable, more observations are dropped from the analysis, resulting in a final sample of 6,370 respondents and 40,138 observations.

Dependent Variable

Physical activity is measured by a single item asking about the frequency of moderate or intensive physical activity for at least 30 minutes per activity. Moderate and intensive physical activity is defined as activities that slightly increase heart rate and breathing. This variable is precoded in HILDA and categorized as follows 1 = “Not at all,” 2 = “Less than once a week,” 3 = “1 to 2 times a week,” 4 = “3 times a week,” 5 = “More than 3 times a week,” and 6 = “Every day.” This categorization is retained for the analysis.

Independent Variables

Work-family conflict is measured by items that are taken from Marshall and Barnett (1993) and that are based on respondents’ self-assessment. For each direction, four items are provided. For WTFC, the items are as follows: “Because of the requirements of my job, I miss out on home or family activities that I would prefer to participate in,” “Working leaves me with too little time or energy to be the kind of parent I want to be,” “Working causes me to miss out on some of the rewarding aspects of being a parent,” and “Because of the requirements of my job, my family time is less enjoyable and more pressured.” For FTWC, the items are “Because of my family responsibilities, I have to turn down work activities or opportunities that I would prefer to take on,” “I worry about what goes on with my children while I’m at work,” “Thinking about the children interferes with my performance at work,”¹ and “Because of my family responsibilities, the time I spend working is less enjoyable and more pressured.” The items range from 1 (“strongly disagree”) to 7 (“strongly agree”). To construct the scales, I take the average of the summed item responses for each scale, requiring valid responses to at least three items. Calculating Cronbach’s α for each wave results in coefficients ranging from .83 to .86 for WTFC and from .51 to .71 for FTWC. Despite being relatively low for FTWC, these coefficients are comparable with prior research using this scale (Yang et al. 2023; Yucel and Borgmann 2022). The correlation between the two scales is .56 in the overall sample, .52 for fathers, and .62 for mothers.

Control Variables

Several variables might affect work-family conflict and physical activity, which are controlled for in the multivariate regression models focusing on time-varying confounders. Age and having a work-limiting health condition are included as sociodemographic controls (Allen and Finkelstein 2014; Hallal et al. 2012; Marks-Vieveen et al. 2024). Age is categorized as 18 to 24, 25 to 34, 35 to 44, 45 to 54, and 55 to 64 years to avoid the age-period-cohort identification problem (Fosse and Winship 2019).

Furthermore, family-related variables that include age of the youngest child, number of children, and having a partner, are included because of evidence that parents, especially those with young children, more than one child, and single parents, tend to be less active (Bellows-Riecken and Rhodes 2008; Passias, Sayer, and Pepin 2017) and to experience more work-family conflict (Minnotte 2012; Reimann et al. 2022).

Work-related control variables encompass working hours per week in all jobs (1 = part-time, 2 = full-time, 3 = long working hours [>40 hours]), shift work (0 = regular daytime schedule, 1 = shift work), occupation, schedule control, commuting time per week, and household income (in A$10,000). Schedule control is a scale composed of the average of three items that ask about the freedom to decide when to work and when to take a break, as well as the flexibility of working times (ranging from 1 [“strongly disagree”] to 7 [“strongly agree”]). Prior research shows that full-time employees, individuals working long work hours, shift workers, low schedule control, and individuals with long commuting times exercise less (Mattingly and Blanchi 2003; Moen et al. 2011; Nomaguchi and Bianchi 2004; Raza et al. 2021; Vandelanotte et al. 2015), and that they have higher levels of work-family conflict (Bai et al. 2021; Byron 2005; Hokke et al. 2024; Wöhrmann, Müller, and Ewert 2020). Occupation and household income have been also identified as important factors for both (Byron 2005; Grzywacz and Marks 2001; Hämmig 2014; Vandelanotte et al. 2015). Income is adjusted for inflation by using the Consumer Price Index and measured by the equivalized disposable household income using the modified OECD scale (OECD 2013). On the basis of the unequal time distribution between fathers and mothers, time spent on unpaid work is also controlled for. Unpaid work was a combined measure of the hours spent on housework, childcare, household errands, outdoor tasks, and caring for disabled persons per week.

Analytical Strategy

To test the association between work-family conflict and physical activity, I apply ordered logit regressions with fixed effects (Baetschmann et al. 2020). Although the parallel line assumption was violated in the pooled sample (not shown, available on request), the user-written Stata command feologit allows for individual-specific thresholds (Baetschmann et al. 2020). This method uses the blow up and cluster estimator to create multiple clones of each individual’s observations and then dichotomizes these clones at different cutoff points (Baetschmann et al. 2020). Using multiple thresholds captures more information and improves efficiency.

Fixed effects regression accounts for within-individual heterogeneity, controlling for time-invariant unobserved characteristics, such as gender, and only examining intra-individual change (Allison 2009). Thus, cases are excluded by design where no change occurs and are eliminated in the models. However, the potential for bias from time-varying unobserved heterogeneity and reverse causality remains (Collischon and Eberl 2020). This study is able to draw conclusions only about individuals who reported changes, potentially limiting external validity, a problem with almost any other model (Collischon and Eberl 2020). Still, fixed-effects models have, in most cases, more advantages over other models by coming closer to identifying a causal link by accounting for time-constant unobserved factors.

In the following, I run an overall model, and separate models for fathers and mothers for each conflict direction. Because of the comparatively high correlation between WTFC and FTWC, particularly among mothers, I conducted some postestimation tests for a joint model that revealed that multicollinearity might be a problem with a variance inflation factor greater than 5. Thus, I run separate models for each conflict direction. Models with interaction terms for each conflict direction and gender are also included in the Appendix (Table A1) to test statistically significant gender differences. The odd ratios are calculated and presented for all models.

To check the robustness of the results, models are also estimated with only person- and wave-specific fixed effects (Table A2), but the results remained consistent. Additionally, models were estimated with a sample restricted to respondents that participated in all 19 waves to account for attrition. However, this did not change the results (Table A3).

Results

Descriptive Results

Table 1 presents the descriptive results of the pooled sample by gender. The results show that most respondents are physically active one or two times per week (27.3 percent), followed by less than once a week (19.6 percent) and more than three times per week (19.4 percent). More than 50 percent of the respondents are physically active less than one or two times a week. The recommended amount from the World Health Organization (WHO) is 150 to 300 minutes per week (WHO 2020), which is likely not achieved by being physically active for less than one or two times per week. Consistent with the gender leisure gap, the descriptive results show that fathers are more likely to be physically active: whereas 48.6 percent of fathers are at least three times per week physically active, only 41.4 percent of mothers are.

Table 1.

Descriptive Results of the Pooled Sample for the Overall Sample and Separated by Gender.

Variable	Overall	Fathers	Mothers
Frequency physical activity
Not at all	7.9	6.5	9.4
Less than once a week	19.6	17.9	21.4
One or two times a week	27.3	26.9	27.8
Three times a week	16.8	16.6	17.1
More than three times a week	19.4	20.8	17.9
Every day	8.9	11.2	6.4
WTFC
Mean	3.767	3.933	3.591
SD	1.466	1.381	1.532
FTWC
Mean	3.112	3.047	3.181
SD	1.485	1.119	1.205
Mothers	48.5
Age of respondent
18–24 years	1.5	1.3	1.7
25–34 years	21.3	21.3	21.3
35–44 years	45.5	43.3	47.8
45–54 years	28.7	29.6	27.7
55–64 years	3.1	4.6	1.5
Work-limiting health condition	6.5	6.0	7.1
Age of youngest own child in household
0–3 years	32.7	38.9	26.1
4–6 years	16.9	16.6	17.1
7–12 years	29.9	27.0	32.8
13–17 years	20.6	17.4	24.0
Number of resident children
Mean	2.023	2.037	2.008
SD	.874	.90	.846
Having a partner	87.3	94.6	79.2
Hours in unpaid work per week
Mean	36.197	27.069	45.902
SD	26.022	16.429	24.975
Working hours in all jobs
Part-time	28.6	5.7	52.9
Full-time	36.0	38.9	32.9
Long working hours	35.5	55.4	14.2
Shift work	20.0	19.8	20.1
Commuting time per week
Mean	4.239	5.093	3.331
SD	3.906	4.196	3.341
Occupation
Managers	16.8	22.2	11.1
Professionals	29.5	25.4	33.8
Technicians and trade workers	12.5	21.0	3.5
Community and personal service workers	10.0	5.5	14.9
Clerical and administrative workers	14.7	6.6	23.3
Sales workers	5.3	3.4	7.4
Machinery operators and drivers	5.3	9.4	0.9
Laborers	5.8	6.5	5.1
Schedule control
Mean	4.285	4.39	4.119
SD	1.783	1.695	1.862
Equivalized disposable household income
Mean	5.050	5.062	5.038
SD	3.138	3.25	3.015
Number of waves
Mean	15.720	15.573	15.877
SD	4.331	4.396	4.255
Observations	40,138	20,684	19,454

Source: Author’s calculations based on the Household, Income and Labour Dynamics in Australia Survey.

Note: N = 47,878 observations. Shown are the descriptive results of the pooled sample. FTWC = family-to-work conflict; WTFC = work-to-family conflict.

The average score for WTFC is 3.8 and for FTWC is 3.1 (both on a scale ranging from 1 to 7). Individuals report lower levels of FTWC than WTFC, indicating that conflict stemming from the family is less common than conflict from work. By gender, more fathers than mothers report higher levels of WTFC, whereas mothers report higher conflict levels with FTWC than fathers.

Multivariate Results

The results of the odds ratios of the multivariate models show that both WTFC and FTWC are negatively associated with being physically activity overall (Table 2, model 1). For both directions, higher levels of conflict are associated with reduced physical activity.

Table 2.

Odds Ratios of the Fixed-Effects Ordered Logistic Regression Results of the Effects of WTFC and FTWC on the Frequency of Physical Activity.

	Model 1		Model 2		Model 3		Model 1		Model 2		Model 3
	WTFC Overall		WTFC Fathers		WTFC Mothers		FTWC Overall		FTWC Fathers		FTWC Mothers
WTFC	.91***	(.01)	.93***	(.02)	.89***	(.01)
FTWC							.95***	(.01)	.97⁺	(.02)	.93***	(.02)
Age of respondent (reference: 18–24 years)
25–34 years	.75*	(.09)	.67*	(.12)	.75⁺	(.12)	.73**	(.08)	.66*	(.12)	.72*	(.11)
35–44 years	.74*	(.10)	.68⁺	(.14)	.69*	(.13)	.71*	(.10)	.67*	(.13)	.65*	(.12)
45–54 years	.82	(.12)	.74	(.16)	.78	(.16)	.79	(.12)	.72	(.16)	.73	(.16)
55–64 years	.97	(.19)	.86	(.23)	1.03	(.30)	.93	(.18)	.84	(.22)	.98	(.29)
Work-limiting health condition	.68***	(.04)	.69***	(.06)	.67***	(.06)	.68***	(.04)	.69***	(.06)	.66***	(.06)
Age of youngest child (reference: 0–3 years)
4–6 years	1.33***	(.06)	1.26***	(.07)	1.47***	(.09)	1.31***	(.06)	1.26***	(.07)	1.43***	(.09)
7–12 years	1.54***	(.09)	1.48***	(.12)	1.67***	(.15)	1.52***	(.09)	1.48***	(.12)	1.63***	(.15)
13–17 years	1.52***	(.14)	1.44**	(.18)	1.66***	(.22)	1.53***	(.14)	1.45**	(.18)	1.65***	(.22)
Number of resident children	1.04	(.03)	.97	(.04)	1.17***	(.05)	1.03	(.03)	.96	(.04)	1.15**	(.05)
Having a partner	.87⁺	(.06)	.83	(.11)	.91	(.08)	.87*	(.06)	.82	(.11)	.90	(.08)
Hours in unpaid work per week	1.00⁺	(.00)	1.00	(.00)	1.00⁺	(.00)	1.00*	(.00)	1.00	(.00)	1.00*	(.00)
Working hours (reference: part-time)
Full-time	.99	(.04)	1.01	(.09)	.97	(.05)	.94	(.04)	.99	(.09)	.92⁺	(.05)
Long work hours	.93	(.05)	.97	(.09)	.83*	(.06)	.86**	(.05)	.93	(.09)	.76***	(.06)
Shift work	1.01	(.04)	1.01	(.06)	1.03	(.06)	1.01	(.04)	1.00	(.06)	1.02	(.06)
Commuting time	1.00	(.00)	1.00	(.00)	1.00	(.01)	1.00	(.00)	1.00	(.00)	.99	(.01)
Occupation (reference :managers)
Professionals	1.03	(.06)	1.02	(.08)	1.03	(.08)	1.04	(.06)	1.03	(.08)	1.04	(.09)
Technicians and trade workers	1.27***	(.09)	1.28**	(.11)	1.18	(.17)	1.28***	(.09)	1.28**	(.11)	1.20	(.18)
Community and personal service workers	1.10	(.09)	.92	(.14)	1.14	(.12)	1.10	(.09)	.91	(.14)	1.15	(.12)
Clerical and administrative workers	.98	(.06)	1.08	(.10)	.93	(.08)	.99	(.06)	1.08	(.10)	.95	(.08)
Sales workers	.99	(.08)	.88	(.12)	1.05	(.12)	.99	(.09)	.87	(.12)	1.06	(.12)
Machinery operators and drivers	1.22⁺	(.13)	1.24⁺	(.14)	1.06	(.31)	1.23⁺	(.13)	1.24⁺	(.14)	1.09	(.33)
Laborers	1.60***	(.14)	1.55***	(.18)	1.63***	(.23)	1.61***	(.14)	1.56***	(.18)	1.66***	(.23)
Schedule control	1.02⁺	(.01)	1.03⁺	(.02)	1.01	(.02)	1.03**	(.01)	1.04*	(.02)	1.02	(.02)
Equivalized disposable income in A$10,000	1.01	(.01)	1.01	(.01)	1.01	(.01)	1.00	(.01)	1.00	(.01)	1.01	(.01)
Panel wave (reference: 2)
3	.96	(.06)	.89	(.08)	1.07	(.10)	.96	(.06)	.90	(.08)	1.06	(.10)
4	1.00	(.07)	.87	(.08)	1.21⁺	(.12)	1.00	(.07)	.88	(.08)	1.20⁺	(.12)
5	.99	(.07)	.79*	(.08)	1.34**	(.14)	.98	(.07)	.78*	(.08)	1.31**	(.14)
6	1.05	(.09)	.84	(.10)	1.41**	(.17)	1.03	(.08)	.84	(.10)	1.36*	(.16)
7	1.11	(.09)	.89	(.10)	1.52***	(.17)	1.10	(.09)	.89	(.10)	1.47***	(.17)
8	.98	(.08)	.92	(.11)	1.13	(.14)	.97	(.08)	.92	(.11)	1.10	(.13)
9	1.16⁺	(.10)	1.03	(.12)	1.43**	(.18)	1.16⁺	(.10)	1.04	(.13)	1.41**	(.18)
10	.94	(.09)	.87	(.11)	1.10	(.15)	.94	(.09)	.88	(.11)	1.09	(.15)
11	.87	(.08)	.83	(.11)	.98	(.14)	.87	(.08)	.84	(.11)	.98	(.14)
12	.90	(.09)	.81	(.11)	1.10	(.16)	.90	(.09)	.82	(.11)	1.09	(.16)
13	1.00	(.11)	.91	(.13)	1.21	(.19)	1.00	(.11)	.93	(.13)	1.19	(.19)
14	.80*	(.09)	.76⁺	(.11)	.93	(.15)	.80*	(.09)	.77⁺	(.11)	.91	(.15)
15	.84	(.10)	.75⁺	(.12)	1.07	(.18)	.86	(.10)	.76⁺	(.12)	1.07	(.18)
16	.89	(.11)	.73⁺	(.12)	1.23	(.22)	.89	(.11)	.74⁺	(.12)	1.21	(.21)
17	.87	(.11)	.77	(.13)	1.12	(.21)	.88	(.11)	.79	(.14)	1.11	(.21)
19	.87	(.12)	.76	(.14)	1.15	(.23)	.88	(.12)	.78	(.15)	1.14	(.23)
21	1.02	(.16)	.78	(.16)	1.55⁺	(.35)	1.04	(.16)	.81	(.17)	1.55⁺	(.35)
23	.87	(.14)	.69⁺	(.15)	1.28	(.31)	.89	(.15)	.71	(.16)	1.31	(.32)
Observations (including copies)	104,483		54,799		49,684		104,483		54,799		49,684
Observations	40,138		20,684		19,454		40,138		20,684		19,454
Number of individuals	6,370		3,135		3,235		6,370		3,135		3,235

Source: Author’s calculations based on the Household, Income and Labour Dynamics in Australia Survey.

Note: Values in parentheses are clustered standard errors. FTWC = family-to-work conflict; WTFC = work-to-family conflict.

p < .10. *p < .05. **p < .01. ***p < .001.

The findings support the first hypothesis, that WTFC and FTWC are associated with a decrease in physical activity. More precisely, a unit increase in WTFC decreases the odds of falling into the highest category of physical activity by 9 percent, whereas a unit increase in FTWC decreases the odds by 6 percent. For a better interpretation of results and following Baetschmann et al. (2020), Figure 1 presents the marginal effects at the average on the probability to fall in each category of physical activity (see also Table A4). The figure shows that every unit increase in both conflict directions decreases the likelihood of falling into the three highest categories (three times a week or more) and increases the likelihood of falling into the three lowest categories (one or two times or less). For example, with increasing WTFC the probability of falling into the third category (three times a week) decreases by 0.4 percentage points and increases the probability of falling into the lowest category (not at all) by 0.7 percentage points for this average person, when everything else is equal. Looking at the effect sizes, a unit increase in WTFC is associated with larger shifts in the probability distributions compared with FTWC: for example, the probability of being physically active more than three times per week decreases by 1.1 percentage points for WTFC compared with 0.7 percentage points for FTWC. It appears that the association between WTFC and physical activity might be stronger than that of FTWC with physical activity.

Figure 1.

Marginal effects at the average of increases in WTFC and FTWC on physical activity.

Looking at this relationship by gender, the results are similar as in the overall model (Table 2, models 2 and 3): the effects of WTFC are significant and negative for both fathers and mothers, indicating that elevated WTFC is associated with a decrease in physical activity. In contrast, FTWC is not significant for fathers, but for mothers. Thus, the second hypothesis has to be rejected with the data for fathers, as only WTFC is significantly associated with physical activity, but not FTWC (hypothesis 2a). For mothers, the findings are consistent with hypothesis 2b, as WTFC is significantly associated with physical activity, suggesting that vulnerability matters among mothers. Comparing the marginal effects at the average shows the same pattern as in the overall model. It appears that, for mothers, WTFC has larger shifts in the probability distributions than FTWC (Figure 2; also see Table A4). For example, the probability of not being physically active increases by 1 percentage point for a unit increase in WTFC compared with 0.7 percentage points for FTWC.

Figure 2.

Marginal effects at the average of increases in WTFC and FTWC on physical activity by gender.

To test for the statistical significance of gender differences, interaction terms were included (Table A1). It shows that each interaction terms for WTFC and FTWC are statistically significant, indicating that fathers and mothers are statistically different. The results show that individuals tend to decrease their physical activity mainly when conflict from work interferes with the family. When family interferes with work, only mothers reduce their physical activity, whereas fathers, contrary to expectation, do not.

Additional Analyses

To test the sensitivity of the results, additional analyses were performed (Table A5). First, physical activity was categorized into a binary measure of being less than three times per week active versus three times per week or more, aligning with the WHO’s guideline of a minimum of 150 minutes per week of moderate activity (WHO 2020). Studies show that this categorization best reflects the guideline as the guideline is in minutes and the HILDA measure is in days (Bauman and Richards 2022; Haskell et al. 2007). However, the results remain consistent with the main findings for both conflict directions and by gender, indicating that individuals experiencing WTFC and FTWC are less likely to meet the WHO recommendation for physical activity.

Second, waves 2021 and 2023 were excluded, as the pandemic might have influenced the results. During the pandemic, physical activity among Australians, especially women, increased (Australian Institute of Health and Welfare 2024), whereas work-family conflict decreased for parents (Wilkins, Vera-Toscano, and Botha 2024). However, excluding these two waves did not change the results.

Third, parents of younger children face greater family demands, potentially resulting in less exercise because of reduced child-free leisure time. Among parents with preschool children, the results align with the main findings. However, the effect of WTFC is now only significant at the 10 percent level among fathers (p = .07), potentially because of their lower involvement in unpaid care work (Baxter et al. 2023) and their responsibility for more flexible and nondaily family-related tasks (Kan, Sullivan, and Gershuny 2011). Consequently, conflict from both directions does not result in less physical activity among fathers of preschool children.

Discussion

This study investigated gender differences in the influence of WTFC and FTWC on the frequency of physical activity among employed parents in Australia, using 19 waves of the HILDA data. Few studies distinguished between conflict directions and gender, and examined this relationship longitudinally. By applying the conservation of resources theory, this study hypothesized a decrease in physical activity due to limited resources and argues that gender is a factor that may shape how fathers and mothers experience and react to conflict differently.

This study contributes to the existing literature by examining how changes in both conflict directions of work-family conflict are associated with changes in physical activity levels in fathers and mothers. This study provides longitudinal evidence of the negative association between WTFC and FTWC with physical activity, as has been expected. The effects seem to be more pronounced for WTFC, aligning with Roos et al. (2007). In contrast, two other studies (Allen and Armstrong 2006; Grzywacz and Marks 2001) found associations for only one conflict direction. These findings suggest that conflict from work interfering with family life reduces physical activity, potentially because of time pressures or a lack of capacities. However, these interpretations that it is a lack of resources driving the results remain speculative, as it was not possible to test whether time or strain is the driving factor. Objective time demands were controlled for by including hours in paid and unpaid work, commuting time, and schedule control. Thus, it seems that objective time is less relevant, whereas perceived time pressures or strains might better explain why physical activity is reduced. Work-family conflict is based on a subjective assessment, meaning that individuals may perceive the same situation differently (Moen, Kelly, and Huang 2008), potentially explaining why WTFC and FTWC still matter for physical activity despite controlling for relevant time and other scarcity factors. This is supported by prior research showing that perceptions of time constraints may be more important than objective time constraints (Heesch and Mâsse 2004; Rebar et al. 2019). Still, these mechanisms need to be explored further in future studies. As the descriptive analysis showed higher levels of WTFC than FTWC, the overall effect on the population is likely greater for WTFC. This is supported by Frone, Russell, and Cooper’s (1992) finding that family boundaries are more permeable than work boundaries. Additionally, family demands can be more easily shared with other actors, such as a partner, or can be outsourced compared with work demands (Craig et al. 2016; Reimann et al. 2022). This might explain why WTFC seems to be more strongly associated with physical activity than FTWC.

Analyzing how gender norms and role identification might shape the association between work-family conflict and physical activity reveals slightly different patterns for fathers and mothers. Although WTFC is associated with decreased physical activity among both fathers and mothers, FTWC is only among mothers. Testing gender differences, it shows that mothers decrease their physical activity more strongly. The findings only partly support what was theoretically expected, as FTWC is not significant for fathers. This is consistent with the study by Roos et al. (2007), who also found that WTFC reduces physical activity in both men and women, and FTWC only in women. This suggests that fathers may be more susceptible to conflicts arising from work, limiting their time for physical activity. Additionally, fathers are less likely to be primarily responsible for time-dependent family demands and tasks, so that FTWC might play less of a role among fathers and does not result in less time or energy for physical activity, as these tasks are undertaken by the other parent, typically mothers, and can be more easily postponed or delegated. This is supported by a study showing that only women’s physical activity is restricted by paid and unpaid work hours, whereas men’s is not (Doan et al. 2022). Furthermore, only women’s physical activity is negatively associated with their partners working time, whereas men’s is not (Fan et al. 2015).

For mothers, significant associations are found for both conflict directions. The results of WTFC give support to the expectation that gender norms may lead to different vulnerabilities, as WTFC is significantly associated with physical activity. The significant association of WTFC might indicate that mothers are particularly vulnerable to conflict stemming from the work sphere, because this might hinder their ability to fulfill their family roles and create tension with societal ideals of being a “good” mother. This is further supported by the lesser permeability of work boundaries (Frone et al. 1992), leading to more conflict from work and less from family, as shown by the descriptive findings of a higher prevalence of WTFC compared with FTWC. However, all mothers in the sample are employed, which makes their work role equally important and also comes with expectations of being a “good” worker, potentially explaining significant associations for both conflict directions. Nevertheless, mothers are still more involved in unpaid (care) work, particularly in countries with more traditional gender norms, such as Australia. Their unpaid work is also less flexible and more time dependent, such as preparing meals, than that of fathers, leaving them with fewer opportunities and time and energy resources with which to juggle competing demands and to delegate tasks (Kan et al. 2011; Moreno-Colom 2017). Therefore, mothers may sacrifice self-care activities and shift toward more family-centered activities to handle increasing work-family conflict, aligning with norms on intensive mothering. This might explain why both conflict directions appear to be associated with decreased physical activity among mothers compared with fathers. Additionally, work-family conflict elicits guilt (Apostol et al. 2025; Livingston and Judge 2008), and more mothers than fathers report the emotion of guilt and putting their needs aside as barriers to physical activity (Ingram et al. 2021), which may make it harder for mothers to prioritize leisure-time physical activity and spend time away from the family. All in all, mothers seem to be more vulnerable to conflict from WTFC and FTWC. However, differences in exposure to stressors were not taken into account in this study, which may further contribute to differences in pathways into conflict and in the availability of resources to manage it.

As mothers spend more time on care work, they generally have less time for physical activity and child-free leisure time than fathers. Only 40 percent of mothers in the sample meet the WHO guideline on physical activity compared with fathers, 50 percent of whom are physically active three times per week or more, as recommended. This study shows that mothers, in particular, reduce their physical activity the most with conflict from work and family. Thus, mothers seem to have fewer opportunities to benefit from moderate to vigorous physical activity, and their resources seem more constrained, especially when conflict intensifies. However, active leisure activities, like physical activity, provide significant health benefits (WHO 2020). To counteract the potential risks associated with decreased physical activity, this study implies that working parents, particularly mothers, could greatly benefit from interventions that promote physical activity. As an important part of adults’ daily lives, the workplace might be a promising setting to offer such interventions (WHO 2018), even more so given that nearly half of Australian employees report spending much of their workday sitting (Australian Bureau of Statistics 2022). Prior research has identified workplace health promotion as an effective tool for encouraging physical activity (Moroni et al. 2023; Proper and van Oostrom 2019), which could help working parents maintain their physical activity levels, even with heightened work-family conflict. At the same time, certain working conditions are more favorable than others for health-promoting behaviors, for example, greater schedule control or short commute time (Moen et al. 2011; Raza et al. 2021). Such conditions could have the potential to reduce work-family conflict (Bai et al. 2021; Laß and Wooden 2023) and mitigate the negative relationship of work-family conflict on health (Badawy and Schieman 2020), making them worthy of further investigation. Additionally, mothers continue to shoulder the lion’s share of unpaid work, leaving them with less time for child-free leisure activities and physical activity (Doan et al. 2022), becoming even more evident when conflict levels intensify, as indicated by this study’s findings. A more equal division of unpaid work could therefore support mothers to stay physically active, potentially reducing health disparities.

Moreover, the findings of this study may widen the theoretical understanding of work-family conflict and health behaviors. Instead of just focusing on the two domains of work and family, physical activity, or more broadly health, might be another domain. Resource-consuming activities offer valuable resources for managing work-family conflict, but this might also come at the cost of creating a new conflict between work, family, and physical activity. Instead of work-family conflict, this might be better described as a work-family-health conflict, where individuals manage competing demands by engaging less in health-promoting activities, such as physical activity. Physical activity seems to be the least prioritized domain among the three, which is also supported by a study by Doan et al. (2022). Other researchers refer to this as a work-life conflict to highlight that other nonwork domains can also lead to conflicting role demands (Kossek and Lee 2017). However, this broader term might obscure the fact that some nonwork domains also compete, which is highlighted by the current study’s findings. Additionally, gendered patterns need to be taken into account, as mothers are inherently more time-pressured than fathers (Craig and Brown 2017) and also seem to sacrifice their time at the expense of their health more than men (Doan et al. 2022) or fathers, which is also supported by my findings.

This study, however, is not without limitations. First, one item only measured physical activity, lacking differentiation between various types or durations, potentially causing measurement errors or similar issues, while also neglecting its complexity. Thus, this measure might not only measure leisure time physical activity, and should be considered when interpreting the results. However, when examining gender differences, previous research shows that it is important to distinguish among different forms of activity and to include activities beyond leisure, as gendered patterns emerge (Huang et al. 2023; Saint-Maurice et al. 2021). Mothers engage in more second-shift physical activity, such as playing with children or household tasks (Huang et al. 2023; Saint-Maurice et al. 2021), which might not be captured by the measure of the present study, as respondents were not primed to include other activities beyond leisure and might not have recalled these secondary activities (Cusatis and Garbarski 2018). With these activities, mothers may still be meeting the WHO guidelines (Smith, Ng, and Popkin 2014).

Second, the dependent and independent measures of work-family conflict and physical activity are based on self-reports. This could lead to under- or overestimation of their perceived conflict and physical activity because of memory bias or social desirability. Despite this, this study focuses on intraindividual change by applying fixed effects regressions; thus, interindividual differences are controlled for, and differences in the assessment do not bias the results. Still, future studies might make use of more objective measures of physical activity, for example, accelerometers, that also allow the examination of less visible or unconscious activities, such as secondary or second-shift activities. However, these are limited by the use of nonstandardized measures, which should be taken into account (WHO 2024).

Third, this study examines only employed parents as the items were solely asked to this group, excluding other groups with work-family conflict, such as informal caregivers. Future surveys should ask these questions to a broader group of respondents to explore the relationship of work-family conflict with physical activity in these other populations.

Fourth, this study extends previous research by employing panel data to examine the association over time. Nevertheless, the results may still be influenced by reverse causation, meaning that not only could work-family conflict affect physical activity, but reduced physical activity might also create stress or increased physical activity might lower work-family conflict (Clayton et al. 2015), potentially biasing the results. This could particularly affect women, who already have less time for physical activity. Additionally, reciprocal effects might be possible, as shown by Schultchen et al. (2019). Thus, more research is needed that applies methods that allow for causal conclusions.

Fifth, Australia is a country with conservative gender norms, and differences in time commitments between men and women are large (Australian Bureau of Statistics 2020–2021). Further research is needed to determine how widely these conclusions apply to other countries and to more representative samples, as the conclusions drawn from this study apply only to Australian parents who reported a change between waves. Moreover, as fixed effects regressions only examine within change, individuals who experience constantly high or low levels of conflict are not captured by this study.

Last, nonresponse may have biased the results, as high levels of work-family conflict and time pressures may have led individuals not to respond to the survey (Vercruyssen, Roose, and van Putte 2011).

Conclusion

These results emphasize the importance of considering the bidirectionality of work-family conflict and gender when examining its association with physical activity. WTFC is negatively associated with physical activity among both fathers and mothers, whereas FTWC is associated with a decrease in physical activity only among mothers. As mothers are still primarily responsible for unpaid care work, they generally have less time for physical activity, and as WTFC and FTWC become higher, they do not benefit from the stress-reducing effects of physical activity. In contrast, when FTWC arises, fathers might better cope with conflict because of their lower share of unpaid care work. Fathers only reduce physical activity during conflict from work. Resource-consuming health behaviors appear to provide resources that help working parents deal with increasing conflict. Thus, mothers and fathers seem to be experiencing more of a work-family-health conflict. However, fathers may be more privileged than mothers in managing their physical activity in times of conflict and may be able to use physical activity as a coping mechanism that benefits their health, in particular when family demands interfere with work; mothers’ conflict may actually increase when they do not have time for physical activity. This study assumes that perceived time pressures and strain explain the negative relationship between work-family conflict and physical activity, but these mechanisms could not be directly tested. Thus, it is important to identify factors that lead to reduced physical activity to develop strategies that support health-promoting behaviors among working parents, helping them use physical activity to manage work-family conflict rather than allowing it to become a health risk.

Supplemental Material

sj-docx-1-srd-10.1177_23780231261429664 – Supplemental material for Work-Family Conflict and Physical Activity: Exploring Gender Differences among Australian Parents

Supplemental material, sj-docx-1-srd-10.1177_23780231261429664 for Work-Family Conflict and Physical Activity: Exploring Gender Differences among Australian Parents by Linda Maciejewski in Socius

Footnotes

Acknowledgements

Supported by the Open Access Publishing Fund of Leipzig University.

ORCID iD

Linda Maciejewski

Data Availability

This research uses unit record data from release 23 of the HILDA Survey conducted by the Australian government’s Department of Social Services (DSS) (doi:10.26193/NBTNMV). The findings and views reported in this article, however, are those of the author and should not be attributed to the Australian government, DSS, or any of DSS’s contractors or partners. Restrictions apply to the availability of these data, which were used under license for this study. The data are available through the DSS Longitudinal Studies Dataverse ().

Supplemental Material

Supplemental material for this article is available online.

1

Given that the item “Thinking about the children interferes with my performance at work” was only introduced to the survey in 2005, a robustness check was conducted using a scale for FTWC that included only the other three items that were surveyed in all waves. However, this did not alter the results.

Author Biography

Linda Maciejewski is a doctoral researcher at the Institute of Sociology at Leipzig University. Her research interests include work-life interdependencies, health, family, gender inequalities, migration and integration.

References

Acker

Joan

. 2006. “Inequality Regimes: Gender, Class, and Race in Organizations.” Gender & Society 20(4):441–64.

Allen

T. D.

Herst

D. E.

Bruck

C. S.

Sutton

2000. “Consequences Associated with Work-to-Family Conflict: A Review and Agenda for Future Research.” Journal of Occupational Health Psychology 5(2):278–308.

Allen

Tammy D.

Armstrong

Jeremy

. 2006. “Further Examination of the Link between Work-Family Conflict and Physical Health.” American Behavioral Scientist 49(9):1204–21.

Allen

Tammy D.

Finkelstein

Lisa M.

2014. “Work-Family Conflict among Members of Full-Time Dual-Earner Couples: An Examination of Family Life Stage, Gender, and Age.” Journal of Occupational Health Psychology 19(3):376–84.

Allison

Paul D.

2009. Fixed Effects Regression Models. Thousand Oaks, CA: Sage.

Apostol

Maria-Manuela

Iorga

Magdalena

Rotariu

Mariana

. 2025. “Guilt in the Context of Work-Family Conflict, Partner Support, and Life Satisfaction among Health Professionals.” Healthcare 13(17). doi:10.3390/healthcare13172145.

Australian Bureau of Statistics. 2020–2021. “How Australians Use Their Time.” Retrieved June 1, 2024. https://www.abs.gov.au/statistics/people/people-and-communities/how-australians-use-their-time/latest-release#cite-window1.

Australian Bureau of Statistics. 2022. “National Health Survey.” Retrieved November 13, 2024. https://www.abs.gov.au/statistics/health/health-conditions-and-risks/national-health-survey/latest-release#cite-window1.

Australian Institute of Health and Welfare. 2024. “Physical Activity.” Retrieved January 9, 2025. https://www.aihw.gov.au/reports/physical-activity/physical-activity.

10.

Badawy

Philip

Schieman

Scott

. 2020. “Control and the Health Effects of Work-Family Conflict: A Longitudinal Test of Generalized versus Specific Stress Buffering.” Journal of Health and Social Behavior 61(3):324–41.

11.

Baetschmann

Gregori

Ballantyne

Alexander

Staub

Kevin E.

Winkelmann

Rainer

. 2020. “feologit: A New Command for Fitting Fixed-Effects Ordered Logit Models.” Stata Journal 20(2):253–75.

12.

Bai

Bing

Gopalan

Neena

Beutell

Nicholas

Ren

Fang

. 2021. “Impact of Absolute and Relative Commute Time on Work-Family Conflict: Work Schedule Control, Child Care Hours, and Life Satisfaction.” Journal of Family and Economic Issues 42(4):586–600.

13.

Bauman

Adrian E.

Richards

Justin A.

2022. “Understanding of the Single-Item Physical Activity Question for Population Surveillance.” Journal of Physical Activity & Health 19(10):681–86.

14.

Baxter

Janeen

Hewitt

Belinda

. 2013. “Negotiating Domestic Labor: Women’s Earnings and Housework Time in Australia.” Feminist Economics 19(1):29–53.

15.

Baxter

Janeen

Campbell

Alice

Lee

Rennie

. 2023. “Gender Gaps in Unpaid Domestic and Care Work: Putting the Pandemic in (a Life Course) Perspective.” Australian Economic Review 56(4):502–15.

16.

Baxter

Jennifer

. 2023a. “Employment of Men and Women across the Life Course.” Retrieved October 2, 2024. https://aifs.gov.au/research/facts-and-figures/employment-men-and-women-across-life-course.

17.

Baxter

Jennifer

. 2023b. “Employment Patterns and Trends for Families with Children.” Retrieved March 9, 2026. https://aifs.gov.au/all-research/research-reports/employment-patterns-and-trends-families-children.

18.

Bellavia

Gina M.

Frone

Michael K.

2005. “Work-Family Conflict.” Pp. 113–48 in Handbook of Work Stress, edited by Barling

Kelloway

Frone

Thousand Oaks, CA: Sage.

19.

Bellows-Riecken

Kai H.

Rhodes

Ryan E.

2008. “A Birth of Inactivity? A Review of Physical Activity and Parenthood.” Preventive Medicine 46(2):99–110.

20.

Bilodeau

Jaunathan

Marchand

Alain

Demers

Andrée

. 2020. “Work, Family, Work-Family Conflict and Psychological Distress: A Revisited Look at the Gendered Vulnerability Pathways.” Stress and Health 36(1):75–87.

21.

Bittman

Michael

Wajcman

Judy

. 2000. “The Rush Hour: The Character of Leisure Time and Gender Equity.” Social Forces 79(1):165–89.

22.

Borgmann

Lea-Sophie

Rattay

Petra

Lampert

Thomas

. 2019. “Health-Related Consequences of Work-Family Conflict from a European Perspective: Results of a Scoping Review.” Frontiers in Public Health 7:189.

23.

Byron

Kristin

. 2005. “A Meta-Analytic Review of Work–Family Conflict and Its Antecedents.” Journal of Vocational Behavior 67(2):169–98.

24.

Canivet

Catarina

Ostergren

Per-Olof

Lindeberg

Sara I.

Choi

BongKyoo

Karasek

Robert

Moghaddassi

Mahnaz

Isacsson

Sven-Olof

. 2010. “Conflict between the Work and Family Domains and Exhaustion among Vocationally Active Men and Women.” Social Science & Medicine 70(8):1237–45.

25.

Clayton

Russell W.

Thomas

Christopher H.

Singh

Barjinder

Winkel

Doan E.

2015. “Exercise as a Means of Reducing Perceptions of Work-Family Conflict: A Test of the Roles of Self-Efficacy and Psychological Strain.” Human Resource Management 54(6):1013–35.

26.

Collischon

Matthias

Eberl

Andreas

. 2020. “Let’s Talk about Fixed Effects: Let’s Talk about All the Good Things and the Bad Things.” KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie 72(2):289–99.

27.

Cooklin

A. R.

Dinh

Strazdins

Westrupp

Leach

L. S.

Nicholson

J. M.

2016. “Change and Stability in Work-Family Conflict and Mothers’ and Fathers’ Mental Health: Longitudinal Evidence from an Australian Cohort.” Social Science & Medicine 155:24–34.

28.

Coser

Lewis A.

1967. “Greedy Organisations.” European Journal of Sociology 8(2):196–215.

29.

Craig

Mullan

2013. “Parental Leisure Time: A Gender Comparison in Five Countries.” Social Politics: International Studies in Gender, State & Society 20(3):329–57.

30.

Craig

Lyn

Brown

Judith E.

2017. “Feeling Rushed: Gendered Time Quality, Work Hours, Nonstandard Work Schedules, and Spousal Crossover.” Journal of Marriage and Family 79(1):225–42.

31.

Craig

Lyn

Perales

Francisco

Vidal

Sergi

Baxter

Janeen

. 2016. “Domestic Outsourcing, Housework Time, and Subjective Time Pressure: New Insights from Longitudinal Data.” Journal of Marriage and Family 78(5):1224–36.

32.

Cunningham

Conor

O’ Sullivan

Roger

Caserotti

Paolo

Tully

Mark A.

2020. “Consequences of Physical Inactivity in Older Adults: A Systematic Review of Reviews and Meta-analyses.” Scandinavian Journal of Medicine & Science in Sports 30(5):816–27.

33.

Cusatis

Rachel

Garbarski

Dana

. 2018. “Which Activities Count? Using Experimental Data to Understand Conceptualizations of Physical Activity.” SSM – Population Health 6:286–94.

34.

DeBaylo

Paige

Michel

Jesse S.

2022. “Identifying Energy and Emotion-Based Conflict: Development of a Refined Work-Life Conflict Scale.” Stress and Health 38(5):961–77.

35.

Doan

Tinh

Peng

LaBond

Christine

Gong

Cathy

Strazdins

Lyndall

. 2022. “Time for Physical Activity: Different, Unequal, Gendered.” Journal of Health and Social Behavior 63(1):37–54.

36.

Fan

Wen

Lam

Jack

Moen

Phyllis

Kelly

Erin

King

Rosalind

McHale

Susan

. 2015. “Constrained Choices? Linking Employees’ and Spouses’ Work Time to Health Behaviors.” Social Science & Medicine 126:99–109.

37.

Fosse

Ethan

Winship

Christopher

. 2019. “Analyzing Age-Period-Cohort Data: A Review and Critique.” Annual Review of Sociology 45:467–92.

38.

Frone

Michael R.

Russell

Marcia

Cooper

M. L.

1992. “Prevalence of Work-Family Conflict: Are Work and Family Boundaries Asymmetrically Permeable?” Journal of Organizational Behavior 13(7):723–29.

39.

Garcia

Leandro

Mendonça

Gerfeson

Benedetti

Tânia R. B.

Borges

Lucélia J.

Streit

Inês A.

Christofoletti

Marina

, et al. 2022. “Barriers and Facilitators of Domain-Specific Physical Activity: A Systematic Review of Reviews.” BMC Public Health 22(1):1964.

40.

Greenhaus

Jeffrey H.

Beutell

Nicholas J.

1985. “Sources of Conflict between Work and Family Roles.” Academy of Management Review 10(1):76–88.

41.

Greenhaus

Jeffrey H.

Allen

Tammy D.

Spector

Paul E.

2006. “Health Consequences of Work–Family Conflict: The Dark Side of the Work–Family Interface.” Pp. 61–98 in Research in Occupational Stress and Well Being, Vol. 5: Employee Health, Coping and Methodologies. Amsterdam, the Netherlands: Elsevier JAI.

42.

Grzywacz

Joseph G.

Marks

Nadine F.

2001. “Social Inequalities and Exercise during Adulthood: Toward an Ecological Perspective.” Journal of Health and Social Behavior 42(2):202–20.

43.

Hallal

Pedro C.

Andersen

Lars B.

Bull

Fiona C.

Guthold

Regina

Haskell

William

Ekelund

Ulf

. 2012. “Global Physical Activity Levels: Surveillance Progress, Pitfalls, and Prospects.” Lancet 380(9838):247–57.

44.

Hämmig

Oliver

. 2014. “Prevalence and Health Correlates of Work-Life Conflict among Blue- and White-Collar Workers from Different Economic Sectors.” Frontiers in Public Health 2:221.

45.

Haskell

William L.

Lee

I-Min

Pate

Russell R.

Powell

Kenneth E.

Blair

Steven N.

Franklin

Barry A.

Macera

Caroline A.

, et al. 2007. “Physical Activity and Public Health: Updated Recommendation for Adults from the American College of Sports Medicine and the American Heart Association.” Medicine and Science in Sports and Exercise 39(8):1423–34.

46.

Hays

Sharon

. 1996. The Cultural Contradictions of Motherhood. New Haven, CT: Yale University Press.

47.

Heesch

Kristiann C.

Mâsse

Louise C.

2004. “Lack of Time for Physical Activity: Perception or Reality for African American and Hispanic Women?” Women & Health 39(3):45–62.

48.

Hobfoll

S. E.

1989. “Conservation of Resources. A New Attempt at Conceptualizing Stress.” American Psychologist 44(3):513–24.

49.

Hobfoll

Stevan E.

Halbesleben

Jonathon

Neveu

Jean-Pierre

Westman

Mina

. 2018. “Conservation of Resources in the Organizational Context: The Reality of Resources and Their Consequences.” Annual Review of Organizational Psychology and Organizational Behavior 5(1):103–28.

50.

Hokke

Stacey

Mason

Simon

Crawford

Sharinne B.

Cooklin

Amanda R.

Giallo

Rebecca

Bennetts

Shannon K.

2024. “Flexible Work Patterns and Experiences of the Work-Family Interface among Australian Parents.” Journal of Industrial Relations 66(2):161–85.

51.

Huang

Wenxuan

Hao

Lingxin

Xingyun

Xiao

Cui

Erjia

Leroux

Andrew

. 2023. “Gender Difference in ‘Second-Shift’ Physical Activity: New Insights from Analyzing Accelerometry Data in a Nationally Representative Sample.” SSM – Population Health 24:101536.

52.

Ingram

George

McCormick

Alister

Gibson

Kass

. 2021. “Parents’ Experiences of Starting and Maintaining Exercise: A Qualitative Systematic Review.” Psychology of Sport and Exercise 57:102058.

53.

Judge

Timothy A.

Ilies

Remus

Scott

Brent A.

2006. “Work–Family Conflict and Emotions: Effects at Work and at Home.” Personnel Psychology 59(4):779–814.

54.

Kan

Man Y.

Sullivan

Oriel

Gershuny

Jonathan

. 2011. “Gender Convergence in Domestic Work: Discerning the Effects of Interactional and Institutional Barriers from Large-Scale Data.” Sociology 45(2):234–51.

55.

Katzmarzyk

Peter T.

Powell

Kenneth E.

Jakicic

John M.

Troiano

Richard P.

Piercy

Katrina

Tennant

Bethany

. 2019. “Sedentary Behavior and Health: Update from the 2018 Physical Activity Guidelines Advisory Committee.” Medicine and Science in Sports and Exercise 51(6):1227–41.

56.

Kossek

Ellen E.

Lee

Kyung-Hee

. 2017. “Work-Family Conflict and Work-Life Conflict.” In Oxford Research Encyclopedia of Business and Management, edited by Kossek

E. E.

Lee

K.-H.

Oxford, UK: Oxford University Press.

57.

Lallukka

Chandola

Roos

Cable

Sekine

Kagamimori

Tatsuse

Marmot

Lahelma

2010. “Work-Family Conflicts and Health Behaviors among British, Finnish, and Japanese Employees.” International Journal of Behavioral Medicine 17(2):134–42.

58.

Laß

Inga

Wooden

Mark

. 2023. “Working from Home and Work–Family Conflict.” Work, Employment and Society 37(1):176–95.

59.

Livingston

Beth A.

Judge

Timothy A.

2008. “Emotional Responses to Work-Family Conflict: An Examination of Gender Role Orientation Working Men and Women.” Journal of Applied Psychology 93(1):207–16.

60.

Maciejewski

Linda

Tuppat

Julia

. 2025. “Unraveling Gender Dynamics in the Impact of Work-Family Conflict on Alcohol Consumption among Australian Parents.” Community, Work & Family. doi:10.1080/13668803.2025.2509032.

61.

Mailey

Emily L.

Huberty

Jennifer

Dinkel

Danae

McAuley

Edward

. 2014. “Physical Activity Barriers and Facilitators among Working Mothers and Fathers.” BMC Public Health 14:657.

62.

Marks-Vieveen

Jenny M.

Uijtdewilligen

Léonie

Motazedi

Ehsan

Stijnman

Dominique P.M.

van den Akker-Scheek

Inge

Bouma

Adrie J.

Buffart

Laurien M.

, et al. 2024. “Physical Activity Levels, Correlates, and All-Cause Mortality Risk in People Living with Different Health Conditions.” Journal of Physical Activity & Health 21(4):394–404.

63.

Marshall

Nancy L.

Barnett

Rosalind C.

1993. “Work-Family Strains and Gains among Two-Earner Couples.” Journal of Community Psychology 21(1):64–78.

64.

Martinez Mendiola

Anna

Cortina

Clara

. 2024. “Leisure Time and Parenting in Europe: A More Difficult Equation for Mothers?” Family Relations 73(4):2823–45.

65.

Mattingly

M. J.

Blanchi

S. M.

2003. “Gender Differences in the Quantity and Quality of Free Time: The U.S. Experience.” Social Forces 81(3):999–1030.

66.

Minnotte

Krista L.

2012. “Family Structure, Gender, and the Work–Family Interface: Work-to-Family Conflict among Single and Partnered Parents.” Journal of Family and Economic Issues 33(1):95–107.

67.

Moen

Phyllis

Kelly

Erin

Huang

Reiping

. 2008. “‘Fit’ inside the Work-Family Black Box: An Ecology of the Life Course, Cycles of Control Reframing.” Journal of Occupational and Organizational Psychology 81(3):411–33.

68.

Moen

Phyllis

Kelly

Erin L.

Tranby

Eric

Huang

Qinlei

. 2011. “Changing Work, Changing Health: Can Real Work-Time Flexibility Promote Health Behaviors and Well-Being?” Journal of Health and Social Behavior 52(4):404–29.

69.

Moreno-Colom

Sara

. 2017. “The Gendered Division of Housework Time: Analysis of Time Use by Type and Daily Frequency of Household Tasks.” Time & Society 26(1):3–27.

70.

Moroni

Alessia

Degan

Raffaella

Martin

Barbara

Sciannameo

Veronica

Berchialla

Paola

Gilli

Giorgio

Cremasco

Margherita Micheletti

. 2023. “Effectiveness of Workplace Health Promotion (WHP) Interventions in University Employees: A Scoping Review.” Health Promotion International 38(1):daac171.

71.

Nocon

Marc

Hiemann

Theresa

Müller-Riemenschneider

Falk

Thalau

Frank

Roll

Stephanie

Willich

Stefan N.

2008. “Association of Physical Activity with All-Cause and Cardiovascular Mortality: A Systematic Review and Meta-analysis.” European Journal of Cardiovascular Prevention and Rehabilitation 15(3):239–46.

72.

Nomaguchi

Kei M.

Bianchi

Suzanne M.

2004. “Exercise Time: Gender Differences in the Effects of Marriage, Parenthood, and Employment.” Journal of Marriage and Family 66(2):413–30.

73.

OECD (Organisation for Economic Co-operation and Development). 2013. “OECD Framework for Statistics on the Distribution of Household Income, Consumption and Wealth.” Paris: OECD Publishing.

74.

OECD (Organisation for Economic Co-operation and Development). 2017. “Gender Inequality in Unpaid Work.” Pp. 189–97 in The Pursuit of Gender Equality, edited by the Organisation for Economic Co-operation and Development. Paris: OECD Publishing.

75.

OECD (Organisation for Economic Co-operation and Development). 2022a. “Childcare Support.” Retrieved June 2, 2024. https://www.oecd.org/els/soc/PF3-4-Childcare-support.pdf.

76.

OECD (Organisation for Economic Co-operation and Development). 2022b. “LMF1.6: Gender Differences in Employment.” https://www.oecd.org/content/dam/oecd/en/data/datasets/family-database/lmf_1_6_gender_differences_in_employment_outcomes.pdf.

77.

OECD (Organisation for Economic Co-operation and Development). 2024a. “OECD Employment Rate Remains at Record High in the Fourth Quarter of 2023.” Retrieved May 7, 2025. https://www.oecd.org/en/data/insights/statistical-releases/2024/04/labour-market-situation-updated-april-2024.html.

78.

OECD (Organisation for Economic Co-operation and Development). 2024b. “Parental Leave Systems.” Retrieved June 2, 2024. https://webfs.oecd.org/els-com/Family_Database/PF2_1_Parental_leave_systems.pdf.

79.

OECD (Organisation for Economic Co-operation and Development). 2024c. “Part-Time Employment Rate (Indicator).” Retrieved June 1, 2024. https://data.oecd.org/emp/part-time-employment-rate.htm#indicator-chart.

80.

Pagnan

Colleen E.

Seidel

Amber

Wadsworth

Shelley MacDermid

. 2017. “I Just Can’t Fit It In! Implications of the Fit between Work and Family on Health-Promoting Behaviors.” Journal of Family Issues 38(11):1577–1603.

81.

Passias

Emily J.

Sayer

Liana

Pepin

Joanna R.

2017. “Who Experiences Leisure Deficits? Mothers’ Marital Status and Leisure Time.” Journal of Marriage and Family 79(4):1001–22.

82.

Pearlin

Leonard I.

Menaghan

Elizabeth G.

Lieberman

Morton A.

Mullan

Joseph T.

1981. “The Stress Process.” Journal of Health and Social Behavior 22(4):337–56.

83.

Pearlin

Leonard I.

1983. “Role Strains and Personal Stress.” Pp. 3–32 in Psychosocial Stress: Trends in Theory and Research, edited by Kaplan

H. B.

London: Academic Press.

84.

Pearlin

Leonard I.

1989. “The Sociological Study of Stress.” Journal of Health and Social Behavior 30(3):241–56.

85.

Pearlin

Leonard I.

1999. “The Stress Process Revisited.” Pp. 395–415 in Handbook of the Sociology of Mental Health, edited by Kaplan

H. B.

Aneshensel

C. S.

Phelan

J. C.

Boston: Springer.

86.

Pedersen

Marlene R. L.

Hansen

Anne F.

Elmose-Østerlund

Karsten

. 2021. “Motives and Barriers Related to Physical Activity and Sport across Social Backgrounds: Implications for Health Promotion.” International Journal of Environmental Research and Public Health 18(11):5810.

87.

Proper

Karin I.

van Oostrom

Sandra H.

2019. “The Effectiveness of Workplace Health Promotion Interventions on Physical and Mental Health Outcomes—A Systematic Review of Reviews.” Scandinavian Journal of Work, Environment & Health 45(6):546–59.

88.

Raza

Auriba

Pulakka

Anna

Hanson

Linda L. Magnusson

Westerlund

Hugo

Halonen

Jaana I.

2021. “Commuting Distance and Behavior-Related Health: A Longitudinal Study.” Preventive Medicine 150:106665.

89.

Rebar

Amanda L.

Johnston

Renee

Paterson

Jessica L.

Short

Camille E.

Schoeppe

Stephanie

Vandelanotte

Corneel

. 2019. “A Test of How Australian Adults Allocate Time for Physical Activity.” Behavioral Medicine 45(1):1–6.

90.

Rebar

Amanda L.

Stanton

Robert

Geard

David

Short

Camille

Duncan

Mitch J.

Vandelanotte

Corneel

. 2015. “A Meta-meta-analysis of the Effect of Physical Activity on Depression and Anxiety in Non-clinical Adult Populations.” Health Psychology Review 9(3):366–78.

91.

Reimann

Mareike

Schulz

Florian

Marx

Charlotte K.

Lükemann

Laura

. 2022. “The Family Side of Work-Family Conflict: A Literature Review of Antecedents and Consequences.” Journal of Family Research 34(4):1010–32.

92.

Roos

Eva

Sarlio-Lähteenkorva

Sirpa

Lallukka

Tea

Lahelma

Eero

. 2007. “Associations of Work-Family Conflicts with Food Habits and Physical Activity.” Public Health Nutrition 10(3):222–29.

93.

Saint-Maurice

Pedro F.

Berrigan

David

Whitfield

Geoffrey P.

Watson

Kathleen B.

Patel

Shreya

Loftfield

Erikka

Sampson

Joshua N.

, et al. 2021. “Amount, Type, and Timing of Domain-Specific Moderate to Vigorous Physical Activity among US Adults.” Journal of Physical Activity & Health 18(S1):S114–22.

94.

Schultchen

Dana

Reichenberger

Julia

Mittl

Theresa

Weh

Tabea R. M.

Smyth

Joshua M.

Blechert

Jens

Pollatos

Olga

. 2019. “Bidirectional Relationship of Stress and Affect with Physical Activity and Healthy Eating.” British Journal of Health Psychology 24(2):315–33.

95.

Shockley

Kristen M.

Shen

Winny

DeNunzio

Michael M.

Arvan

Maryana L.

Knudsen

Eric A.

2017. “Disentangling the Relationship between Gender and Work-Family Conflict: An Integration of Theoretical Perspectives Using Meta-analytic Methods.” Journal of Applied Psychology 102(12):1601–35.

96.

Simpson

Rachel F.

Hesketh

Kathryn R.

Crozier

Sarah R.

Baird

Janis

Cooper

Cyrus

Godfrey

Keith M.

Harvey

Nicholas C.

, et al. 2022. “The Association between Number and Ages of Children and the Physical Activity of Mothers: Cross-Sectional Analyses from the Southampton Women’s Survey.” PLoS One 17(11)e0276964.

97.

Smith

Lindsey P.

Shu W.

Popkin

Barry M.

2014. “No Time for the Gym? Housework and Other Non–labor market Time Use Patterns Are Associated with Meeting Physical Activity Recommendations among Adults in Full-Time, Sedentary Jobs.” Social Science & Medicine 120:126–34.

98.

Stults-Kolehmainen

Matthew A.

Sinha

Rajita

. 2014. “The Effects of Stress on Physical Activity and Exercise.” Sports Medicine 44(1):81–121.

99.

Summerfield

Michelle

Garrard

Brooke

Kamath

Roopa

Macalalad

Ninette

Nesa

Kamrun M.

Watson

Nicole

Wilkins

Roger

, et al. 2024. HILDA User Manual—Release 23. Retrieved January 13, 2025. https://melbourneinstitute.unimelb.edu.au/__data/assets/pdf_file/0006/5166807/HILDA-User-Manual-Release-23.0.pdf.

100.

Thoits

Peggy A.

1991. “On Merging Identity Theory and Stress Research.” Social Psychology Quarterly 54(2):101–12.

101.

Vagni

Giacomo

. 2020. “The Social Stratification of Time Use Patterns.” British Journal of Sociology 71(4):658–79.

102.

Vandelanotte

Corneel

Short

Camille

Rockloff

Matthew

Millia

Lee Di

Ronan

Kevin

Happell

Brenda

Duncan

Mitch J.

2015. “How Do Different Occupational Factors Influence Total, Occupational, and Leisure-Time Physical Activity?” Journal of Physical Activity & Health 12(2):200–207.

103.

Vercruyssen

Anina

Roose

Henk

de van Putte

Bart

. 2011. “Underestimating Busyness: Indications of Nonresponse Bias Due to Work–Family Conflict and Time Pressure.” Social Science Research 40(6):1691–1701.

104.

Wang

I-An

Tsai

Hung-Yu

Lee

Meng-Hsiu

Ren-Chang

. 2021. “The Effect of Work–Family Conflict on Emotional Exhaustion and Job Performance among Service Workers: The Cross-Level Moderating Effects of Organizational Reward and Caring.” International Journal of Human Resource Management 32(14):3112–33.

105.

Watson

Nicole

Wooden

Mark P.

2012. “The HILDA Survey: A Case Study in the Design and Development of a Successful Household Panel Survey.” Longitudinal and Life Course Studies 3(3):369–81.

106.

Watson

Nicole

Wooden

Mark

. 2021. “The Household, Income and Labour Dynamics in Australia (HILDA) Survey.” Jahrbücher für Nationalökonomie und Statistik 241(1):131–41.

107.

WHO (World Health Organization). 2018. “More Active People for a Healthier World: Global Action Plan on Physical Activity 2018–2030.” Geneva, Switzerland: World Health Organization.

108.

WHO (World Health Organization). 2020. “WHO Guidelines on Physical Activity and Sedentary Behavior: At a Glance.” Retrieved June 6, 2024. https://iris.who.int/bitstream/handle/10665/337001/9789240014886-eng.pdf?sequence=1.

109.

WHO (World Health Organization). 2024. “Physical Activity Measurement and Surveillance in Adults: Report of a Scoping and Planning Meeting: 27–28 November 2023.” Retrieved February 2, 2026. https://iris.who.int/server/api/core/bitstreams/03f33b6a-0bae-4140-8087-499b8c3ffaf9/content.

110.

Wilkins

Roger

Vera-Toscano

Esperanza

Botha

Ferdi

. 2024. “The Household, Income and Labour Dynamics in Australia Survey: Selected Findings from Waves 1 to 21.” Melbourne, Australia: Melbourne Institute of Applied Economic and Social Research.

111.

Wöhrmann

Anne M.

Müller

Grit

Ewert

Kathrin

. 2020. “Shift Work and Work-Family Conflict: A Systematic Review.” sozialpolitik.ch (3/2020). Retrieved March 9, 2026. https://www.sozialpolitik.ch/article/view/3733.

112.

Yang

Duanyi

Kelly

Erin L.

Kubzansky

Laura D.

Berkman

Lisa

. 2023. “Working from Home and Worker Well-being: New Evidence from Germany.” ILR Review 76(3):504–31.

113.

Yucel

Deniz

Borgmann

Lea-Sophie

. 2022. “Work-Family Conflict and Depressive Symptoms among Dual-Earner Couples in Germany: A Dyadic and Longitudinal Analysis.” Social Science Research 104:102684.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.04 MB

0.00 MB