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. Author manuscript; available in PMC: 2025 Jan 1.
Published in final edited form as: Am J Orthopsychiatry. 2023 Dec 7;94(2):212–221. doi: 10.1037/ort0000716

Relationships between Sleep Duration and Health among US Adults with a History of Household Incarceration during Childhood

Elizabeth B Jelsma 1, Fatima A Varner 2, Aprile D Benner 3
PMCID: PMC10922323  NIHMSID: NIHMS1948062  PMID: 38059994

Abstract

The rate of incarceration in the United States has increased at an alarming rate in the past 30 years, and thus so has the number of children having a household member incarcerated (referred to as household incarceration). Associations between experiencing household incarceration in childhood and later negative health and developmental outcomes are well-documented, however the underlying mechanisms linking this childhood stressor and adult outcomes have been less well-studied. Using state Behavioral Risk Factor Surveillance System (BRFSS) survey data (N=145,102), this study examines how experiencing household incarceration during childhood is associated with mental and physical health in adulthood and mediational pathways through suboptimal sleep (short or long sleep). Results indicate there were significant indirect effects of household incarceration to physical and mental distress through short sleep (≤6 hours per 24 hours) and long sleep (10≥hours per 24 hours), and a significant indirect effect of household incarceration to body mass index (BMI) through short sleep. Findings from the current study highlight indirect pathways through which household incarceration in childhood is linked with sleep health in adulthood, and, in turn, to negative mental and physical health.

Keywords: household incarceration, childhood adversity, sleep, body mass index, mental distress, physical distress, mediation

The rate of incarceration in the United States has increased at an alarming rate in the past 30 years. Currently, the American criminal justice system holds more than 1.8 million people in prison and detention facilities (Carson & Kluckow, 2023). As a result, the number of children with an incarcerated parent or family member has also increased. Specifically, 9% of people born between 1999 and 2005 in the United States have had a parent or adult household member incarcerated during their childhood (Finlay et al., 2023). The trauma and loss associated with having a household member incarcerated (henceforth referred to as household incarceration) during one’s childhood has consequences in both childhood and adulthood (Arditti, 2016; Mihalec-Adkins & Shlafer, 2022), including childhood obesity (Turney, 2014), risky health behaviors and problem behaviors (Emory, 2018; Haskins & McCauley, 2019; Heard-Garris et al., 2018; Le et al., 2019), psychological distress and substance use (Fleming & Nurius, 2019; Heard-Garris et al., 2018; Johnson et al., 2019; Khan et al., 2018), poor cognitive and academic outcomes (Finlay et al., 2023; Haskins & McCauley, 2019), poorer diet and less sleep (Gavrieli et al., 2015; Jackson & Vaughn, 2017), posttraumatic stress symptomatology and dysregulated stress responses (Bocknek et al., 2009; Roettger & Boardman, 2012), low expectations for one’s own future (Brumley et al., 2017), and poor overall health (Dallaire et al., 2018; Finlay et al., 2023; Haskins & McCauley, 2019; Hiolski et al., 2019). While the associations between experiencing household incarceration in childhood and later negative health and developmental outcomes are well-documented, the underlying mechanisms linking this childhood stressor and adult outcomes have been less well-studied.

Sleep is an important intermediate link between exposure to stress and various health and developmental outcomes (Goosby et al., 2017; Lo Martire et al., 2020; Slopen et al., 2016). The sleep process is highly responsive to stress by way of increased arousal and endocrine reactions. Experiencing trauma and stress is related to sleeping shorter durations and with more disruptions, which has negative short- and long-term consequences for health (Goosby et al., 2017). Multiple previous studies have looked at cumulative childhood trauma, such as Adverse Childhood Experiences (ACE) scores, finding that more cumulative childhood trauma is directly related to less optimal sleep in adulthood (Tomlinson et al., 2022). However, fewer studies have examined how suboptimal sleep resulting from childhood adversity may, in turn, relate to other health issues later in life. Household incarceration may be a uniquely stressful experience for a child when contrasted with other forms of childhood adversity, as family incarceration involves not only physical separation from a family member/attachment figure, but it can also be particularly ambiguous and stressful given the stigma surrounding incarceration (Emory, 2018). Therefore, within a life-course framework (Braveman & Barclay, 2009; Elder et al., 2003), the current study aims to identify the sleep-related mechanisms by which experiencing household incarceration in childhood may lead to mental and physical health issues in adulthood.

Household Incarceration and the Life Course Perspective

The life course perspective emphasizes the roles of timing of events and transitions, historical events and the social milieu, the experiences of proximal others (i.e., linked lives), and human agency in shaping developmental trajectories (Elder et al., 2003). The roles of event timing and linked lives are particularly salient to this study, as we explored mechanisms linking the incarceration of other household members during childhood and adolescence to later health outcomes. According to the life course perspective, childhood experiences are likely to set in motion life-course consequences characterized by accumulating advantages or disadvantages (Elder et al., 2003), and thus childhood is a sensitive period which has many effects on later life health. Indeed, advances in the biological, developmental, and social sciences provide evidence of causal mechanisms between childhood adversity and adult health impairment, specifically by way of disrupting the stress response system (Fleming & Nurius, 2019; Nelson et al., 2020; Shonkoff et al., 2012). Such disruptions experienced early in life foster vulnerability to biological, cognitive, and socio-emotional dysregulation later in life (Braveman & Barclay, 2009; Shonkoff et al., 2012; Wesarg et al., 2020).

As such, early life adversity is viewed as a “risk factor for the genesis of health-threatening behaviors, as well as a catalyst for physiologic responses that can lay the groundwork for chronic, stress-related diseases later in life” (Shonkoff et al., 2012, p. 235). Stressful early life experiences and environments burden overall physiologic and psychological functioning, causing disruptions in physiological adaptations, as well as learning, behavior, and physical and mental well-being in the short- and long-term (Abajobir et al., 2017; Brown et al., 2022; Elder et al., 2003; Shonkoff et al., 2012). Having a family or household member incarcerated during one’s childhood is a form of early life adversity, and the potential consequences of this are considerable. Household incarceration causes family disruption and instability by disrupting linked lives, changing children’s relationships with their incarcerated family member. Incarceration also reduces resources within the family, increases caregiver stress, and often results in increased scrutiny from external institutions such as schools or police due to associated stigma or labeling (Emory, 2018). These family-level challenges and their co-occurrence with the child-level strain of losing a parent or family member to incarceration during a sensitive developmental period may explain the abundance of evidence showing that experiencing household incarceration in childhood increases risks for a myriad of lifelong mental and physical health concerns, including physical and mental distress (Gjelsvik et al., 2014; Lee et al., 2013).

As discussed above, early life trauma can shape the brain systems that manage stress responsivity and can affect sympathetic nervous system (SNS) functionality years later (Azza et al., 2020; Malave et al., 2022; Shonkoff et al., 2012). Stress-related pathology and cardiovascular over-activity can be potential consequences of experiencing childhood trauma, as the brain is still developing the brain circuits and neural connections which govern the sympathetic nervous system (Azza et al., 2020; Malave et al., 2022; Shonkoff et al., 2012). In addition to physical health implications, childhood adversity increases the risk of developing a range of poor mental health outcomes in adulthood, such as anxiety disorders (Lähdepuro et al., 2019; Phillips et al., 2005), mood disorders (Hayward et al., 2020; Raposa et al., 2014), substance use disorders (Green et al., 2010), psychosis (Trotta et al., 2015), and suicide attempts (Dube et al., 2005). It has been well documented that stress and its neurobiological consequences largely explain the association between early adversity and later mental and physical health outcomes (Hayward et al., 2020; Shonkoff et al., 2012).

Childhood Adversity, Reactivity, and Sleep in Adulthood

Sleep is widely recognized as critical to maintaining health due to its links with psychological and biological regulatory systems such as the cardiometabolic system, circadian rhythm, and sympathetic nervous system (SNS) (Azza et al., 2020; Bellatorre et al., 2017; Branger et al., 2016; Cespedes et al., 2016; Cespedes Feliciano et al., 2018; Goosby et al., 2017). Stress can disrupt sleep health by stimulating increased arousal and a release of endocrine reactions that worsen sleep (Azza et al., 2020). Total sleep time is one index that is sensitive to stress. Both short sleep (less than 6 hours per night) and long sleep (more than 10 hours per night) are associated with a host of health problems, including obesity (Chaput et al., 2008, 2013; Jike et al., 2018), cardiovascular risk (Cappuccio et al., 2011; Jike et al., 2018), depression (Zhai et al., 2015), and premature mortality (Cappuccio et al., 2010; Chaput et al., 2013; Jike et al., 2018). Although links between short sleep and health have been more extensively studied than long sleep, studies indicate that long sleep is more prevalent worldwide (Bin et al., 2013), and meta-analytic studies have also linked long sleep with metabolic syndrome, diabetes, and stroke, but not hypertension (Jike et al., 2018). Short sleep has been linked to oxidative stress, changes in metabolic processes, depression, and inflammation, which may link it to long term health outcomes (Namsrai et al., 2023). Long sleep may be related to health outcomes because of several mechanisms including depression, fatigue, underlying disease, and sedentary behaviors (Grandner & Drummond, 2007). Overall, the link between sleep and health appears to be U-shaped but the mechanisms that link short and long sleep to poor health need to be further explored. While some cross-sectional studies have investigated the role of sleep as a mediator of the association between current stress and health in adult samples (Bishop et al., 2019), very few studies have taken a life-course approach to answer how current sleep may mediate the influence of early life adversity for later-life health. Experiencing household incarceration in childhood may initiate an early trajectory of suboptimal sleep, or lay the foundation for future sleep problems, which may in turn explain poorer mental and physical health outcomes in adulthood, the focus of the current study.

Studies have indicated that parental incarceration is linked to sleep outcomes in childhood and adolescence. For example, research with the Future of Families and Child Wellbeing Study has linked parental incarceration to sleep problems, inconsistent sleep schedules, and short sleep duration during early childhood and elementary school (Branigan & Meyer, 2021; Jackson & Vaughn, 2017). Cross-sectional data has shown that adolescents in Minnesota with a formerly or currently incarcerated parent were significantly less likely to get at least eight hours of sleep than adolescents with no history of parental incarceration (Hiolski et al., 2019). Recent research from the 2020 Behavioral Risk Factor Surveillance System (BRFSS) Survey, the data used in the current study, shows a direct link between household incarceration in childhood and short and long sleep in adulthood, as well as mediation via poor mental and physical health and socioeconomic disadvantage (Jackson et al., 2023). In this study, we investigate whether sleep also can mediate the link between household incarceration during childhood and mental and physical health outcomes in adulthood. Previous research shows adolescents with a history of parental incarceration had lower odds of depression and substance use disorders when they got sufficient sleep (Bomysoad & Francis, 2021). Given that sleep is potentially modifiable (Espie et al., 2019), highly responsive to stress (Goosby et al., 2017), and an important intermediate link between exposure to stress and various health and developmental outcomes (Goosby et al., 2017; Lo Martire et al., 2020; Slopen et al., 2016), the current study examines the mediating role of sleep between household incarceration in childhood and later health outcomes.

The Present Study

The present study extends the existing literature by using path analysis in a structural equation modeling framework to test how sleep quality in adulthood may mediate the relationship between experiencing household incarceration in childhood and mental and physical health issues in adulthood. First, we hypothesized that household incarceration in childhood would predict increased physical distress, body mass index (BMI), and mental distress in adulthood (Hypothesis 1). Second, we hypothesized that suboptimal sleep (short or long) in adulthood would mediate the associations between household incarceration in childhood and the three health outcomes in adulthood (Hypothesis 2).

Method

Sample

Data came from the 145,102 respondents to the 2020 Behavioral Risk Factor Surveillance System (BRFSS) Survey—a state-level implementation of a national survey conducted in collaboration with the Centers for Disease Control and implemented through state health departments. The BRFSS has three overall components: core modules (sets of questions consistently administered to all states and territories to establish national estimates), optional modules (Centers for Disease Control and Prevention-developed questions that states can include in the BRFSS survey depending on their priorities), and state-added questions (state-customized items) (White et al., 2016). Twenty-eight states included the optional adverse childhood experiences (ACEs) survey module in 2020, which includes parent incarceration, and, as such, the current study only includes participants from those states. Of note, the survey was designed prior to 2020, and data collection had started before the COVID-19 pandemic began, so there are no COVID-related variables in the 2020 dataset. BRFSS is administered over the phone in both English and Spanish and to noninstitutionalized adults 18 years or older who reside in households with working telephone landlines and cellular phones (Fleming & Nurius, 2019), and therefore the 2020 administration was in accordance with COVID-19 social distancing practices instituted at the time. Random digit dialing and a disproportionate stratified random sampling of households identified respondents for the survey. Only those respondents with valid responses to the main exogenous variable (household incarceration in childhood from the ACEs module) were included in the present analyses.

Based on these inclusion/exclusion criteria, the sample size for the current study is N = 145,102 (55% female; Mage = 55.28 SD = 17.69). The majority of the sample was White (75%). A small percentage of the sample (6.79%) did not graduate high school, while 26.56% of the sample’s highest education was graduating high school, 29.06% attended college or technical school, and 37.59% graduated from college or technical school. More than half of the sample reported an annual household income over $50,000 (52.84%). The mean number of ACEs (besides household incarceration) within the sample was slightly under two (SD = 2.04, range = 0–10), which is consistent with other studies using non-clinical subsamples of BRFSS data (Fleming & Nurius, 2019).

Measures

Household incarceration.

Household incarceration was assessed with the dichotomized (yes/no) item, “Did you live with anyone who served time or was sentenced to serve time in a prison, jail, or other correctional facility?” The survey assessed this as part of the ACEs module referring to experiences before age 18.

Sleep duration.

Sleep duration was based on the response to the question, “On average, how many hours of sleep do you get in a 24-hour period? Think about time you actually spend sleeping or napping, not just the amount of sleep you think you should get.” Duration of sleep was reported as whole numbers rounded to the nearest hour. Multiple health and medical institutes (e.g., National Sleep Foundation; National Heart Lung, and Blood Institute; Institute of Medicine) recommend between 7–9 hours of sleep per night for adults (Liu et al., 2013). Therefore, problematic sleep duration for these analyses was defined as short (≤ 6 hours/night) or long sleep (≥ 10 hours/night) (Liu et al., 2013).

Body mass index (BMI).

To minimize measurement error and maximize statistical power (Altman & Royston, 2006), we modeled continuous individual-level BMI as opposed to BMI categories. Previous research has demonstrated greater bias from self-reported height and weight when using discrete BMI categories as compared to continuous BMI measures (Preston et al., 2015). Therefore, aligned with contemporary studies, we use a continuous measure of BMI (Rummo et al., 2020; Soeroto et al., 2020). BRFSS collects self-reported data for height and weight and provides computed BMI scores from weight in kilograms (kg) divided by the square of the height in meters (m2) (Obesity Expert Panel & US Department of Health and Human Services, 2013). BRFSS also provides sampling weights to correct for bias/underestimation in self-reports (Pierannunzi et al., 2013).

Physical distress.

As part of the Health-Related Quality of Life (HRQOL) module, physical distress was measured with the question “about your physical health, which includes physical illness and injury, for how many days during the past 30 days was your physical health not good?”. The “healthy days” questions have been included in the BRFSS since 1995 and have shown good measurement properties (construct, criterion, and known-groups validity) in multiple populations, languages, and settings (Chowdhury et al., 2008; Newschaffer, 1998; Slabaugh et al., 2017). Higher values indicate more frequent physical distress.

Mental distress.

Mental distress (also part of HRQOL) was measured with the question “about your mental health, which includes stress, depression, and problems with emotions, for how many days during the past 30 days was your mental health not good?”. Higher values indicate more frequent mental distress. See above for more information about the validity of this measure.

Control variables.

Analyses control for age, state, sex (male or female), education (less than high school, high school graduate, some college, college graduate), race (coded as White or non-White due to small cell sizes of non-White categories), current cigarette smoking (yes or no), number of days consuming at least one drink of alcohol during the past 30 days, and summed ACE score (excluding household incarceration; range 0–10). The ACE module asks about childhood exposure to abuse and family dysfunction that occurred prior to 18 years of age, such as household mental illness, household substance use, parental divorce, and witnessing domestic violence as well as physical, emotional, and sexual abuse. The responses to the items are then summed, and scores reflect how many adverse events an individual has been exposed to before age 18.

Analytic Plan

Variables were prepared in Stata/MP 16 (StataCorp, 2007), and path analyses were conducted in Mplus 8.1 (Muthén & Muthén, 2017) using robust maximum likelihood (MLR) estimation with Monte Carlo integration (required when there is missing data on the mediator). Of note, MLR with dichotomous outcomes (which the mediators are) provides odds ratios, and these analyses do not provide model fit indices and do not allow for bootstrapping. The main study outcomes (BMI, physical distress, and mental distress) were continuous. Analyses used BRFSS recommended sampling weights (by state) that are based on the demographic characteristics of the state and which survey version was administered to provide more accurate and representative estimates. Full-information maximum likelihood (FIML) estimation was used to handle missing data, enabling us to include all available data (Enders, 2022). FIML does not estimate the missing data, as is the case with mean- or regression-based imputation methods. Instead, it fits the covariance structure model directly to the observed (and available) raw data for each participant (Enders, 2022).

To test whether household incarceration in childhood was related to BMI, physical distress, and mental distress in adulthood indirectly through sleep, we analyzed a path model shown in Figure 1. Although the data used were cross-sectional, and therefore do not allow for strict longitudinal assessment, each variable was modeled relative to the timeframe of its assessment (Fleming & Nurius, 2019). For example, the main predictor (household incarceration) was based on childhood experiences, and the mediators (short and long sleep) reflect the respondents’ average hours of sleep per night at the time of the survey. Outcomes were also answered for current conditions at the time of the survey (e.g., current BMI, mental and physical distress in the past 30 days).

Figure 1.

Figure 1.

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Conceptual model linking household incarceration during childhood, short and long sleep in adulthood, and BMI, physical distress, and mental distress in adulthood.

Results

Descriptive Results

Table 1 presents the sample characteristics, and Table 2 presents correlations among all study variables. All correlations were observed to be in the predicted directions, with household incarceration being positively correlated with short and long sleep, physical distress, and mental distress. Only 7.19% of the sample experienced household incarceration before the age of 18 (N = 10,438). Thirty-one percent of the entire sample reported short sleep (i.e., six hours or less) and 3.94% reported long sleep (i.e., 10 hours or more). Within those who experienced household incarceration, 45.18% reported short sleep and 4.40% reported long sleep. In contrast, among those who did not experience household incarceration, only 29.76% reported short sleep, and 3.92% reported long sleep. The average BMI of the sample was 28.44 (SD = 6.46), the average physical distress was 3.62 days/month (SD = 8.25), and the average mental distress was 3.89 days/month (SD = 8.05).

Table 1.

Sample statistics (N = 145,102)

N % Min Max M(SD)
Household incarceration
 No (= 0) 134.664 92.81
 Yes (= 1) 10,438 7.19
Short sleep (≤ 6 hours/night)
 No (= 0) 99,098 69.13
 Yes (= 1) 44,255 30.87
Long sleep (≥ 10 hours/night)
 No (= 0) 137,686 96.05
 Yes (= 1) 5,667 3.95
BMI (cont.) 135,643 12.02 93.86 28.44(6.46)
Physical Distress (cont.) 142,156 0 30 3.62(8.25)
Mental Distress (cont.) 142,450 0 30 3.89(8.05)
Age (years) 145,102 18 99 55.28(17.69)
Sex
 Female 79,641 54.89
 Male 65,461 45.11
Race
 White 108,319 74.65
 Other 36,783 25.35
Education
 Did not graduate high school 9,825 6.79
 Graduated high school 38,435 26.56
 Attended college or technical school 42,057 29.06
 Graduated from college or technical school 54,388 37.59
Annual household income
 Less than $15,000 9,902 8.19
 $15,000 – 24,999 18,323 15.15
 $25,000 – 34,999 12,066 9.98
 $35,000 – 49,999 16,734 13.84
 $50,000 or more 63,890 52.84
Current smoker
 No (= 0) 124,259 86.29
 Yes (= 1) 19,741 13.71
# of days in past 30 had alcoholic beverage 123,612 0 30 3.58(7.65)
ACE Score (w/o house. incarceration) 134,174 0 10 1.61(2.04)
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Table 2.

Correlations among study variables.

1. 2. 3. 4. 5. 6.
1. Household incarceration --
2. Short sleep .08*** --
3. Long sleep .04* −.14** --
4. Body mass index .02 .09*** .01 --
5. Physical distress .04*** .12*** .07*** .10*** --
6. Mental distress .12*** .18*** .03*** .04*** .29*** --
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*

p < .05

**

p < .01

***

p < .001

Direct and indirect links among central study constructs

When testing the direct effect of household incarceration for health (Hypothesis 1), household incarceration during childhood was not directly related to BMI (b = −.48, p = .210), physical distress (b=.−.15, p=.536), or mental distress (b=−.02, p=.943) in adulthood. However, when examining short and long sleep as mechanisms linking household incarceration and well-being (Hypothesis 2), there were significant indirect effects for all three outcomes. Table 3 summarizes the indirect paths from household incarceration to physical distress, BMI, and mental distress through sleep. Specifically, there were significant indirect effects of household incarceration to physical distress through short sleep (p < .001) and long sleep (p = .002), and the magnitude of the indirect effect corresponded to 55% of the total effects of household incarceration on physical distress. Next, there was a significant indirect effect of household incarceration to BMI through short sleep (p < .001), and the magnitude of the indirect effect corresponded to 74% of the total effects of household incarceration on BMI. Finally, there were significant indirect effects of household incarceration to mental distress through short sleep (p < .001) and long sleep (p = .002), and the magnitude of the indirect corresponded to 99% of the total effects of household incarceration on mental distress. We also ran a supplemental analysis switching short sleep (≤6 hours per 24 hours) with very short sleep (≤5 hours per 24 hours), which rendered similar results (see eTable 1 in the Supplement). To stay consistent with the health and medical institutes (e.g., National Sleep Foundation; National Heart Lung, and Blood Institute; Institute of Medicine) which consider 6 hours or less to be insufficient sleep, we retained 6 hours or less for the main analyses.

Table 3.

Path Model Indirect Effects from Household Incarceration to Mental and Physical Health Outcomes

Paths Est. SE p-value
Household Incarceration → Physical Distress
 House. Incarceration → Short Sleep → Physical Distress .095 .010 .000
 House. Incarceration → Long Sleep → Physical Distress .092 .030 .002
 Total indirect effects .186 .028 .000
 Total direct effects −.150 .237 .527
 Total effects .037 .242 .880
Household Incarceration → Body Mass Index
 House. Incarceration → Short Sleep → Body Mass Index .094 .011 .000
 House. Incarceration → Long Sleep → Body Mass Index .047 .030 .118
 Total indirect effects .140 .032 .000
 Total direct effects −.048 .021 .240
 Total effects .093 .046 .045
Household Incarceration → Mental Distress
 House. Incarceration → Short Sleep → Mental Distress .095 .010 .000
 House. Incarceration → Long Sleep → Mental Distress .092 .030 .002
 Total indirect effects .186 .028 .000
 Total direct effects −.002 .030 .940
 Total effects .184 .038 .000
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Unstandardized path parameters are presented, and significant indirect pathways are bolded.

*

p < .05.

**

p < .01.

***

p < .001

Discussion

Exposure to a wide range of adverse early environments has been consistently linked to mental and behavioral health issues in adulthood (Braveman & Barclay, 2009; Shonkoff et al., 2012). This study extends the current research base by applying a life-course framework to elucidate one mechanism linking a specific childhood stressor, household incarceration, to poorer mental and behavioral health outcomes in adulthood, specifically via undermining optimal sleep. Results show the effects of household incarceration on short and long sleep indirectly leads to more frequent mental and physical distress, as well as the indirect effect of incarceration leading to higher BMI through short sleep.

Prior studies that have identified bivariate relationships of household incarceration in childhood with mental and physical health issues in adulthood typically have not substantially assessed other disrupted health processes that could play mediating or moderating roles (Fleming & Nurius, 2019; Jackson & Vaughn, 2017; Lee et al., 2013). Sleep is an under-researched mechanism through which experiencing childhood trauma such as household incarceration may contribute to dysregulated patterns of stress reactivity later in life. The theoretical rationale for these associations is that incarceration represents a major stressor in a household that increases the probability of poor health and well-being for all members of the household (Del Toro et al., 2022; Fleming & Nurius, 2019; Jackson & Vaughn, 2017; Shonkoff et al., 2012). In general, empirical evidence that family incarceration may influence aspects of child health and well-being across life stages is well-documented (Jackson & Vaughn, 2017). For example, researchers have found that family incarceration during childhood can elevate the risk of posttraumatic stress symptomatology and dysregulated stress responses (Bocknek et al., 2009; Roettger & Boardman, 2012), as well as fewer hours of resting and sleeping (Gavrieli et al., 2015). Synthesizing these previous findings, the current study will be the first to dynamically link childhood household incarceration, disrupted sleep, and adult mental and physical health issues.

Theorized paths from household incarceration to short and long sleep, and in turn to BMI, physical distress, and mental distress were evident here. However, whereas household incarceration was indirectly related to all three health outcomes through sleep, there were no direct links between household incarceration and the outcomes. The current findings provide evidence of sleep being an important mechanism by which household incarceration during childhood predicts health and well-being in adulthood. Interestingly, while both short and long sleep linked household incarceration to higher physical and mental distress in adulthood, only short sleep linked household incarceration with higher BMI. It is possible that short sleep rather than long sleep may be more salient for weight gain by way of daytime fatigue and therefore reduced activity (Patel et al., 2006), dysregulated hormone levels which affect hunger and appetite (Spiegel et al., 2004), or even increased caloric intake at nighttime when unable to sleep (Benca, 2005). Future research should investigate further for these possible mechanisms which might explain the link between childhood adversity, short sleep, and BMI.

The current study found that experiencing household incarceration in childhood elevates the risk of dysregulated sleep during adulthood, which in turn elevates risk of downstream mental and physical health concerns. Our findings underscore the importance of considering the unintended long-term health consequences for children with incarcerated household members and minimizing their occurrence and persistence over time (Jackson & Vaughn, 2017). The strong association between this childhood stressor and negative health in adulthood suggests preventive practice and policy approaches that support the household members of those who are incarcerated. While this study contributes to the growing literature examining sleep as a critical mediating factor between early life stress and later negative mental and physical health outcomes (Abajobir et al., 2017; Azza et al., 2020; Brown et al., 2022), it does, however, have limitations that must be acknowledged. First, the measure of household incarceration in this study was not able to tap into some of the cascading events that might follow an acute household incarceration event, such as repeated incarceration (recidivism), familial financial challenges due to home displacement or unemployment, loss of an attachment figure, or less attention and adult monitoring (Wakefield & Wildeman, 2011). It would have been preferable, for example, to have additional details regarding the extent and nature of household incarceration, such as which household member was incarcerated (e.g., mother, father, sibling, non-relative, etc.), the duration of incarceration, and the exact age of the child when the household member was incarcerated. Such work is critical as research points to potential sensitive periods in the early life course wherein household incarceration can be particularly detrimental (Gaston, 2016). Second, this survey was cross-sectional, and recall error regarding the childhood experiences are possible. Unfortunately, there is no way to assess whether there is indeed substantial recall error, although given that incarceration is a major life event, other published studies have similarly expected that parental incarceration would be more accurately recalled than other general childhood experiences (Porter & King, 2015). Third, while the BRFSS provided a breadth of relevant measures spanning household incarceration to BMI and mental and physical distress to sleep, the depth of measures was limited. Having a larger number of items covering a broader array of mental health issues could have strengthened these outcome measures. Future studies should consider these measurement issues when replicating and expanding on the work presented here. Finally, the data did not permit an examination of whether the influence of household incarceration on sleep began in childhood, or only emerged later in adulthood, necessitating a need for future longitudinal research to examine developmental timing issues.

These findings suggest several possible leverage points of intervention. First is reducing the rates of incarceration in the United States, which is among the highest in the world (Finlay et al., 2023). Restorative justice programs and policies that divert people from prison and reduce recidivism have been shown to be effective (Bonta et al., 2002), and widespread implementation could drastically reduce incarceration rates and the consequences that incarceration has for those within the household. Second, given that sleep patterns are potentially modifiable (Espie et al., 2019), this highlights the potential utility of prevention and intervention measures that target reductions in stress-related sleep dysregulation for those who have experienced household incarceration. The pathways identified here provide a specific target point for intervention (promoting an optimal 7 to 9 hours of sleep nightly), which can be achieved by evidence-based and accessible behavioral interventions such as cognitive-behavioral therapy, sleep hygiene, and relaxation/mindfulness/hypnotherapy (Friedrich & Schlarb, 2018). Providing sleep interventions specifically for household members of incarcerated individuals might prevent future downstream health consequences for those who experience this adverse childhood experience.

Supplementary Material

Supplemental Material

Figure 2.

Figure 2.

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Mediation model linking household incarceration, sleep, and health in adulthood. Unstandardized path parameters are presented. Significant paths are shown in solid line and non-significant paths are shown in dashed line. Note: the value between household incarceration and sleep are odds ratio (due to short and long sleep being binary variables), while the rest are unstandardized regression coefficients (betas). *p < .05, ***p < .001.

Public Policy Relevance Statement:

Mass incarceration in the United States has far-reaching health implications, including for the family and household members of those who are incarcerated. Healthy sleep functioning is known to buffer effects of stress for health. Findings from the current study highlight that suboptimal sleep is one explanatory pathway linking household incarceration in childhood and diminished health in adulthood. Those who have experienced household incarceration in childhood should be targeted for preventive and interventive measures that optimize sleep duration, thus promoting overall mental and physical health.

Acknowledgments

This research was supported by grant, P2CHD042849, Population Research Center, awarded to the Population Research Center at The University of Texas at Austin by the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

The authors of this paper report no conflicts of interest or financial disclosures.

Contributor Information

Elizabeth B. Jelsma, University of Houston

Fatima A. Varner, University of Texas at Austin

Aprile D. Benner, University of Texas at Austin

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