The Impact of Adverse Childhood Experiences on Socioeconomic Status in Adulthood: A Scoping Review

Abstract

Exposure to adverse childhood experiences (ACEs) has been linked to socioeconomic disadvantages, yet no comprehensive synthesis has systematically summarized this association. This study conducted a scoping review on ACEs and adult socioeconomic outcomes, mapping existing research, identifying key gaps, and highlighting directions for future research, practice, and policy. Seven databases were searched: PubMed, APA PsycArticles (EBSCOhost platform), APA PsycInfo (EBSCOhost), CINAHL (EBSCOhost), Social Services Abstracts (ProQuest platform), Social Work Abstracts (ProQuest), and Sociological Abstracts (ProQuest). Additionally, Google Scholar and reference check were also used to identify additional articles. Inclusion criteria were: (1) English language; (2) peer-reviewed articles; (3) use of a cumulative measure of at least four ACEs; (4) examination of ACEs’ effects on education, employment, or income in adulthood. Thirty-five articles met inclusion criteria. Findings of the review indicated that individuals with higher ACEs were more likely to experience unemployment, work disability, and poverty in adulthood. Exposure to multiple ACEs was also associated with lower high school and college completion rates. Moreover, health-related factors, along with variables such as gender, were found to mediate or moderate the relationship between ACEs and socioeconomic outcomes in adulthood. Cumulative ACEs substantially undermine educational attainment, employment stability, and income levels, perpetuating cycles of poverty and economic disadvantage across the life course. Implications for research, practice, and policy were discussed in the study.

Keywords

adverse childhood experiences socioeconomic status educational attainment income poverty employment adulthood

Introduction

Adverse childhood experiences (ACEs) usually refer to exposure to traumatic events during childhood, including physical, emotional, and sexual abuse, as well as physical and emotional neglect. They also include household dysfunction, such as parental divorce or separation, domestic violence, and living with a caregiver experiencing mental illness, substance use, or incarceration (Felitti et al., 1998). ACEs are prevalent across diverse populations (Ports et al., 2020). In a meta-analysis of the prevalence of ACEs across 206 studies, encompassing 546,458 adult participants from 22 countries, results indicated that 6 out of 10 adults reported experiencing at least 1 ACE, while 1 in 6 reported exposures to 4 or more ACEs (Madigan et al., 2023). Specifically for the United States, findings from the Centers for Disease Control and Prevention (CDC)-Kaiser ACE Study revealed that 63.9% of American adults had at least one ACE, while 12.5% experienced four or more (Centers for Disease Control and Prevention & Kaiser Permanente, 2016).

Abundant evidence has demonstrated that exposure to ACEs is linked to adverse physical and mental health outcomes, as well as increased engagement in risk behaviors (Garrido et al., 2018; Sheffler et al., 2020; Vig et al., 2020). More recently, research has also highlighted the impact of ACEs on socioeconomic outcomes, showing that ACEs can reduce life opportunities and hinder long-term economic stability (Hansen et al., 2021; Testa & Jackson, 2020).

Socioeconomic status (SES) refers to an individual’s overall economic and social status (Galobardes et al., 2006; House, 2002). In research, SES is typically measured through educational attainment, income/poverty, and employment, or variation of these three factors (Antonoplis, 2023; Baker, 2014). For a long time, studies have indicated a link between exposure to certain types of ACEs and socioeconomic outcomes. For instance, various types of child abuse have been demonstrated to have a detrimental effect on adult employment status (Sansone et al., 2012; Zielinski, 2009). Survivors of childhood sexual and physical abuse are more likely to attain lower levels of education (Boden et al., 2007). Also, adults with a history of child abuse and neglect have been found to have reduced earnings and fewer assets (Currie & Spatz Widom, 2010). In addition, research suggests that exposures to household dysfunction (Parental unemployment, incarceration, mental disorders, death, divorce, and child’s foster care experience) at an early age are associated with lower levels of education and disconnection from the labor market in adulthood (Andersen, 2021).

While these research findings are informative and significant, adverse experiences tend to co-occur, and studies that focus on single types of adversity may fail to capture the broader impact of cumulative trauma (Dong et al., 2004; Felitti et al., 1998; Kessler et al., 1997; Lamers-Winkelman et al., 2012; McLaughlin et al., 2012). Therefore, a more comprehensive approach that considers the cumulative effects of childhood adversities is essential to fully understand their long-term socioeconomic impact and to guide effective interventions.

ACEs and Educational Attainment

Educational attainment, as an indicator of SES, serves as the primary marker of social status and plays a crucial role in shaping other SES components such as employment and income (Mirowsky, 2017). Recent research has examined the connection between the cumulative effects of ACEs and educational attainment. For example, Veldman et al. (2015) found that childhood adversities were linked to lower educational attainment in young adulthood. Otero (2021) examined the relationship between ACEs and the timely completion of a bachelor’s degree. The results suggested a dose-response relationship: each additional ACE reduced the odds of timely degree completion, even after controlling for other relevant factors.

ACEs and Employment

Employment is closely tied to income, which in turn influences social networks and contributes to a greater sense of control and autonomy (Baker, 2014). According to the International Labor Organization (ILO), employment status can be categorized into three domains: (1) employed, which includes employees, self-employed individuals, and unpaid family workers; (2) unemployed, referring to those currently without a job but seeking work; and (3) inactive, which includes retired individuals, full-time students, homemakers, and individuals with permanent disabilities (ILO, 2004a, 2004b). Many studies have examined the relationship between ACEs and employment status (de Vries et al., 2023; Fahy et al., 2017; Liu et al., 2013; Tam et al., 2003; Topitzes et al., 2016). For example, Topitzes et al. (2016) revealed that exposure to ACEs hindered men’s ability to secure employment. Liu et al. (2013) found that individuals with any ACEs exposure had significantly higher unemployment rates than those without ACEs. Some other studies have also explored the association between childhood adversities and work disability (Halonen et al.,2017; Harkonmäki et al., 2007; Laditka & Laditka, 2019; Schüssler-Fiorenza Rose et al., 2016). For example, both Harkonmäki et al. (2007) and Schüssler-Fiorenza Rose et al. (2016) found that individuals with multiple childhood adversities had a higher risk of work disability or disability retirement compared to those with no reported childhood adversities.

ACEs and Income/Poverty

Income generally refers to pre-tax wages from one’s occupation. It can be measured at the individual level, but it is also often assessed at the household or family level (Galobardes et al., 2006). Recent studies have examined the relationship between ACEs and income/poverty (Kim et al., 2020; Schurer et al., 2019; Shaefer et al., 2018; Smith et al., 2022; Xu et al., 2022). For example, Kim et al. (2020) found that, for both men and women, exposure to ACEs was significantly associated with increased risk of economic hardship in young adulthood. Evidence from Schurer et al. (2019) indicated that ACEs had a statistically significant effect on various economic outcomes in late middle age, including net income, welfare dependence, and subjective poverty. In addition, Xu et al. (2022) found that individuals with high adversity exposure demonstrated lower income attainment compared to those with low adversity exposure.

Mediation and Moderation Effects

Beyond the direct association between ACEs and SES outcomes, researchers have also explored the underlying mechanisms through which ACEs shape individuals’ SES trajectories. For example, Veldman et al. (2015) explored whether adolescent mental health issues mediate the relationship between childhood adversities and educational attainment in young adulthood, and whether gender also moderates this. Their findings showed that mental health issues during adolescence partially mediated the relationship, and that childhood adversities were strongly linked to lower educational attainment among boys only. Extending this line of inquiry, scholars like Petersen et al. (2022) investigated the moderating role of depression and found that depression significantly amplified the impact of ACEs on economic hardship.

To sum up, the relationship between childhood adversity and adult socioeconomic status has garnered increasing attention in recent years. However, no comprehensive synthesis has systematically reviewed this association. A deeper understanding of this body of research is crucial for informing policies and interventions aimed at preventing childhood adversity and mitigating its long-term socioeconomic consequences (Shaefer et al., 2018; Suglia et al., 2020). Therefore, the current study sought to conduct a scoping review on ACEs and adult SES outcomes to map the existing research, identify key research gaps, and highlight directions for future inquiry, practice and policy.

Methods

A scoping review is an effective tool for assessing the breadth of literature on a specific topic, offering insights into the volume and scope of existing research. This approach is particularly beneficial when evidence in a particular area is still emerging (Armstrong et al., 2011). This study was guided by Arksey and O’Malley (2005)’s methodological framework, which divides the scoping review process into five stages.

Stage 1: Develop the Research Questions

The research questions for this scoping review are as follows: (1) What evidence exists on the relationship between ACEs and socioeconomic status in adulthood? (2) What are the strengths, limitations and gaps in the current evidence base? (3) What are the research, practice, and policy implications of current evidence on ACEs and socioeconomic status in adulthood?

Stage 2: Identify Relevant Studies

The scoping search was conducted in October 2024 across seven databases: PubMed, APA PsycArticles (EBSCOhost platform), APA PsycInfo (EBSCOhost), CINAHL (EBSCOhost), Social Services Abstracts (ProQuest platform), Social Work Abstracts (ProQuest), and Sociological Abstracts (ProQuest). Additionally, Google Scholar and reference check were used as complementary search sources to identify articles not indexed in the selected databases. The following search strategy was applied:

(("adverse childhood experiences"[Title/Abstract] OR "ACEs"[Title/Abstract] OR "childhood adversity"[Title/Abstract] OR "childhood trauma"[Title/Abstract] OR "cumulative trauma"[Title/Abstract] OR "cumulative adversity"[Title/Abstract])

And

("socioeconomic status"[Title/Abstract] OR "SES"[Title/Abstract] OR "employment"[Title/Abstract] OR "unemployment"[Title/Abstract] OR "occupation"[Title/Abstract] OR "job"[Title/Abstract] OR "education"[Title/Abstract] OR "academic achievement"[Title/Abstract] OR "income"[Title/Abstract] OR "poverty"[Title/Abstract] OR "financial hardship"[Title/Abstract] OR "financial security"[Title/Abstract] OR "economic instability"[Title/Abstract] OR "economic hardship"[Title/Abstract])

And

("adult"[Title/Abstract] OR "adulthood"[Title/Abstract]))

Since the first landmark study on ACEs was published in 1998, the search was limited to studies published between 1998 and October 2024. The initial search yielded a total of 1,946 articles, which were exported into a reference manager database (EndNote). After 1,058 duplicates were removed, 888 unique articles remained.

Stage 3: Select Articles Using Inclusion and Exclusion Criteria

The following inclusion criteria were applied at both title and abstract screening, and full-text review stages: (1) English language; (2) Peer-reviewed articles; (3) Use of a cumulative measure of at least four ACEs, to ensure a multidimensional assessment of childhood adversity consistent with the cumulative ACEs framework and prior ACEs scoping review methodology (Zhang et al., 2023); (4) Examination of the associations between ACEs and education, employment, or income/poverty in adulthood.

The first author reviewed the titles and abstracts of 888 articles without duplicates and identified 44 articles that met the inclusion criteria. An additional 16 relevant articles were identified through Google Scholar search, and 14 more were found through reference lists of included studies, resulting in a total of 74 articles for full-text review. Then, the first and second authors independently conducted full-text screening and identified 35 articles for inclusion in this review. Any discrepancies were discussed until consensus was reached. The detailed study selection process is presented in Figure 1.

Figure 1.

Search strategy and screening process.

Stage 4: Chart the Data

Data on study characteristics were extracted, including authors, year of publication, study location, characteristics of the sample, study design, ACEs measures, SES outcomes, control variables, mediators and moderators, statistical analysis methods, and key findings.

Stage 5: Summarize and Interpret Study Findings

In the “Results” section, we summarized the review findings and addressed Research Question 1. In the Discussion section, we interpreted the study findings and discussed the limitations and gaps in the current evidence base, along with the implications for research, practice, and policy, thereby addressing our Research Questions 2 and 3.

Results

Study Contexts

Characteristics of all included studies are summarized in Table 1, and detailed information for each study is presented in Table 2. The 35 studies reviewed were all published between 2003 and 2024, with 14 (40.0%) published in the most recent 5 years (2020–2024). Seventeen studies (48.6%) were conducted in the United States. Twenty-eight studies (80.0%) had a sample size larger than 1,000. Age composition varied across studies. Ten studies (28.6%) had a mean participant age below 30 years, 8 included participants aged 30 to 50 years, 5 focused on adults older than 50 years, and 12 studies (34.3%) included participants across multiple age groups. With respect to race and ethnicity, 17 (48.6%) included samples that were predominantly White, three studies (8.6%) primarily focused on African American participants (Giovanelli et al., 2016; Tam et al., 2003; Topitzes et al., 2016), and one (2.9%) focused on Indigenous populations (Lafrenaye-Dugas et al., 2024).

Table 1.

Characteristics of Included Studies.

Study characteristics	Number of studies	Percentage of included studies (N = 35; %)
Publication Year
2003–2013	4	11.43
2014–2019	17	48.57
2020–2024	14	40.00
Country
Australia	1	2.86
Canada	3	8.57
China	2	5.71
Finland	2	5.71
Germany	1	2.86
Netherlands	2	5.71
South Africa	1	2.86
Switzerland	1	2.86
United Kingdom	5	14.29
United States	17	48.57
Sample Size
<100	2	5.71
100–500	4	11.43
500–1,000	1	2.86
>1,000	28	80.00
Mean Age
<30	10	28.57
30–50	8	22.86
>50	5	14.29
Mixed Age Groups	12	34.29
Race and Ethnicity
Majority White	17	48.57
Majority African American	3	8.57
Indigenous Populations	1	2.86
Not Reported	14	40.00
Study Designs
Quantitative Study	33	94.29
Qualitative Study	2	5.71
Longitudinal Design	22	62.86
Cross-sectional Design	13	37.14
Measurement of ACEs
Original ACEs Checklist	7	20.00
ACEs Module from the BRFSS	7	20.00
Childhood Trauma Questionnaire	1	2.86
World Health Organization ACE International Questionnaire	2	5.71
Other Validated Measures or Combined Multiple Sources	18	51.43
Socioeconomic Status Outcomes
Education	5	14.29
Employment	9	25.71
Income	2	5.71
Education and Income	5	14.29
Education and Employment	5	14.29
Income and Employment	1	2.86
Employment, Education and Income	8	22.86

Note. ACEs = Adverse Childhood Experiences; BRFSS = Behavioral Risk Factor Surveillance System.

Table 2.

Data Charting of Selected Articles (N = 35).

Author (Year)	Study location	Sample characteristics	Methods	ACEs measurement	SES outcomes	Covariates	Mediator/Moderator	Main analysis	Main findings
Barker et al. (2017)	Canada	N = 974; 31% females; median age = 22; 68% White; 100% street-involved youth	Quantitative; cross-sectional study	Childhood Trauma Questionnaire	Education (high school incompletion)	Gender, race/ethnicity, sexual orientation, age at first hard drug use, child welfare system involvement, history of homelessness, sex work before age 18, age at first sexual experience, parental substance use	None	Multivariable logistic regression model	Emotional abuse was the only type of maltreatment independently associated with high school incompletion in the full model (AOR = 2.08; 95% CI [1.51, 2.86]). A moderate dose-dependent trend was observed: individuals exposed to 4–5 forms of maltreatment had 2.7 times the odds of not completing high school compared to those with no maltreatment (AOR = 2.7 [1.6, 4.6]).
Bouvette-Turcot et al. (2017)	Canada	N = 230–243 mothers; Age ≥ 18; Race = NR; 119 held university degrees; 182 families were above low-income threshold	Quantitative; longitudinal cohort study	Childhood Trauma Questionnaire and the Parental Bonding Instrument, integrated into a single adversity score	Education (university degree or not); family income (low vs. high)	None	Maternal prenatal depression as moderator	Logistic regression models	A significant interaction between maternal childhood adversity and prenatal depressive symptoms predicted low family income (OR = 1.078, p = .002). Maternal childhood adversity significantly predicted lower educational attainment (OR = 0.86, p = .006).
Bouvette-Turcot et al. (2017)	Canada		Quantitative; longitudinal cohort study			None	Maternal prenatal depression as moderator	Logistic regression models	The association between childhood adversity and low family income was stronger among women with higher prenatal depressive symptoms. The moderation effect was significant only for income, not for maternal educational attainment.
de Vries et al. (2023)	Netherlands	N = 1,524; 56.3% female; Participants followed from age 11 to 22 across 4 waves (mean ages: 11.08, 13.53, 19.02, 22.26 years)	Quantitative; longitudinal cohort study	Adapted version of Adverse Childhood Experiences Scale (14 items) including typical ACEs and additional adversities such as peer bulling and parental unemployment	Education and employment status at age 22 (Classified into four mutually exclusive groups: students, workers, NEETs, inactive)	Parental educational	None	Wald tests; Benjamini-Hochberg correction for multiple testing; logistic regression and multinomial models for group comparisons	Individuals classified as “inactive” (n = 85, 5.6%) were more likely to have experienced multiple ACEs. These individuals often neither in education (77.4%) nor employment (98.6%) and mostly receiving benefits (94.4%).
Dosanjh et al. (2023)	USA	N = 79,303; 55.8% female, 0.4% transgender; 60.6% were over 54 years; 79.1% White	Quantitative; cross-sectional analysis of national survey data	The BRFSS ACEs module (11 items)	Education (high school or less vs. more than high school); income (<$25,000 vs. ≥$25,000)	Age, race/ethnicity, number of people in the household	Sexual and Gender Diverse (SGD) identity as moderator; analyses stratified by SGD vs. Cisgender Heterosexual (CGH) groups	Chi-square; logistic regression; moderation analyses	Higher ACEs scores were associated with lower income (AOR = 1.084, 95% CI [1.067, 1.102]) and lower education (AOR = 1.056 [1.041, 1.071]) in SGD and CGH groups.
Dosanjh et al. (2023)	USA			The BRFSS ACEs module (11 items)		Age, race/ethnicity, number of people in the household		Chi-square; logistic regression; moderation analyses	ACEs interacted significantly with SGD identity in relation to both income and education (low income: AOR = 0.921; low education: AOR = 0.911).
Fahy et al. (2017)	UK	N = 9,137; 51.5% female; Age 55	Quantitative; longitudinal study	Other (a custom 7-item set: illness in household, neglect, abuse, parental absence, divorce, and being in care)	Employment status	Gender, Internalizing and externalizing symptoms, childhood educational disadvantage, adult mental health issues, physical health, qualifications, SES	Gender as moderator	Multinomial logistic regression analyses	Two or more ACEs were significantly associated with males’ permanent sick (OR = 2.57, 95% CI [1.43, 4.61]) and females’ part-time employment (OR = 0.70 [0.50, 0.98]). Compared to women, men who had experienced abuse had higher odds of being permanently sick (not able to work) at age 55.
Frederick and Goddard (2007)	Australia	N = 20 adults; 10 females, 10 males; 19–51 years	Qualitative; cross-sectional study	Other (narrative interviews)	Education; employment status; financial hardship	None	None	Thematic analysis of semi-structured interviews	Participants’ narratives suggested childhood adversities initiated complex life trajectories marked by disrupted education, unstable employment, and financial insecurity in adulthood.
Giovanelli et al. (2016)	USA	N = 1,531; 50.3% female, Age 22–24, 26 years; 92.9% African American, 7.1% Hispanic, all born in high-poverty neighborhoods in Chicago	Quantitative; longitudinal study	Modified 9-items version of ACEs	Education (high school graduation); employment	Gender, race, CPC preschool participation, CPC school-age participation, family risk index	CPC intervention as moderator	Probit, multiple, and binary logistic regression analyses	Individuals with four or more ACEs had significantly lower odds of high school graduation (OR = 0.37, p < .001) and skilled employment (OR = 0.50, p = .001).
Giovanelli et al. (2016)	USA		Quantitative; longitudinal study	Modified 9-items version of ACEs	Education (high school graduation); employment		CPC intervention as moderator	Probit, multiple, and binary logistic regression analyses	CPC preschool participation moderated the effect of ACEs on education and employment.
Haahr-Pedersen et al. (2020)	USA	N = 1,839; 52% female; Mean age = 44.55 years; 63.8% White, 16.9% Hispanic, 11.8% Black, 6.3% Other, 1.3% ≥ 2 races; participants from low-income, urban area	Quantitative; cross-sectional surveys	10-item version of the ACE questionnaire (based on Felliti et al. [1998])	Education (finished college/university or not); income; employment status	None	Gender as moderator	T-tests; Chi-square tests; LCA; One-way ANOVA	High adversity was significantly related to all participants’ incomes below the median (Male: χ² = 14.59, p < .001; female: χ² = 23.54, p < .001). High adversity was also related to not attending college among males (χ² = 7.71, p < .05) and unemployment among females (χ² = 8.34, p < .05).
Haahr-Pedersen et al. (2020)	USA		Quantitative; cross-sectional surveys			None	Gender as moderator	T-tests; Chi-square tests; LCA; One-way ANOVA	Gender was examined using stratified analyses (no formal interaction terms were tested), suggesting potential moderation.
Halonen et al. (2017)	Finland	N = 31,473; 77.7% female; Mean age = 47.1 years	Quantitative; longitudinal study	Six adversities modified from the Survey of Living Conditions: parental divorce/separation, family financial difficulties, serious family conflicts, fear of family member, family member with chronic illness, alcohol problem in family	Employment status (work disability)	Age, sex, marital status, smoking, heavy alcohol use, physical activity, BMI, chronic disease, psychological distress, cancer, psychological distress, job strain, shift work, type of job contract	None	Cox proportional hazards models	Childhood adversity was associated with an increased risk of work disability (HR = 1.08, 95% CI [1.02, 1.14]).
Hardcastle et al. (2018)	UK	N = 2,881; 53.4% female; Age groups: 30–39 (31.9%), 40–49 (36.3%), 50–59 (31.7%); 93.9% White, 6.1% Black and Minority Ethnic	Quantitative; cross-sectional study	CDC short ACE tool (9-item scale)	Education (highest level of education); employment status	Age, sex, ethnicity, childhood affluence	Educational qualifications as moderator	Chi-squared test; Binomial and multinomial logistic regression; Generalized linear model function	High ACEs (≥4) were independently linked to greater odds of unemployment (AOR = 2.52, p < .001), long-term illness or disability (AOR = 3.94, p < .001), and no qualifications (AOR = 2.18, p < .001). Educational qualifications did not significantly moderate the relationship between ACEs and adult health/employment outcomes.
Harkonmäki et al. (2007)	Finland	N = 8,817; 58.4% female, Age groups: 40–44 (51.4%), 50–54 (48.6%)	Quantitative; longitudinal cohort study	Other (six ACEs items: parental separation, financial difficulties, conflicts, fear of family member, severe illness in the family, alcohol problem of family member)	Employment (disability retirement)	Age, sex, adulthood SES, health-related risk behaviors (smoking, drinking, obesity), depression and drug use for somatic diseases, job strain, interpersonal conflicts	Adulthood SES, health-related behaviors, depression, drug use for somatic diseases as mediators	Binary logistic regression models	Individuals exposed to multiple ACEs were 3.46 times more likely to retire due to disability (95% CI [2.09, 5.71]) than those who had not reported any such experiences.
Harkonmäki et al. (2007)	Finland		Quantitative; longitudinal cohort study		Employment (disability retirement)			Binary logistic regression models	Depression, health behaviors, and SES mediated the ACEs-disability retirement link.
Horan and Widom (2015)	USA	Wave 1: N = 1,196; 48.7% female, mean age = 29.2 years; 62.9% White, 34.9% Black, 1.2% Other, 0.3% Hispanic. Wave 2: N = 896, 51% female, mean age = 39.5 years; 62.2% White, 35.2% Black, 2.6% Other, 4% Hispanic. Wave 3: N = 808, 52.7% female, mean age = 41.2 years, 60.4% White, 37% Black, 2.6% Other, 4% Hispanic	Quantitative; longitudinal cohort study	Other (12 childhood adversities: parental divorce, arrest, substance use, sibling arrest/substance use, single-parent home, deceased parent, large family size, homelessness, removal from home, household economic stress, documented abuse/neglect)	Education (years of education)	Gender, age, ethnicity	Child abuse/neglect, gender as moderators	Hierarchical multiple regression models; Moderation analyses	Exposure to a greater number of childhood risk factors was significantly associated with fewer years of education (B = –0.26, SE = 0.02, p < .001). Gender moderated ACEs-education link (stronger for males). But no moderation effect by abuse/neglect.
Kim et al. (2020)	USA	N = 10,091; 50.04% female, mean age at wave 1 = 15 years, Wave 4 = 28 years; 68.65% White, 10.9% Hispanic, 14.23% Black, 3.14% Asian, 3.07% Others	Quantitative; longitudinal study	Adapted version of Adverse Childhood Experiences Scale (9-items)	Income (economic hardship)	Age and race/ethnicity, education attainment, public assistance	None	LCA; path analysis	The likelihood of experiencing economic hardship was significantly higher for both men and women in the child maltreatment group (men: β = .12, p < .001; women: β = .18, p < .001) and the family dysfunction group (men: β = .08, p < .001; women: β = .09, p < .001), compared to those in the low adversity group.
Laditka and Laditka (2019)	USA	N = 6,045; 57.8% female, mean age at baseline: 29.5 years, mean age at follow-up: 48.7 years; 70.1% White, 29.9% African American	Quantitative; longitudinal cohort study	Other (A custom index of 9 childhood adversities: poor childhood health, parental divorce, low education, unemployment, unsafe neighborhood, bullying, school victimization, low SES etc.)	Employment (work disability)	Adult health, education, age, sex, race	Adult health conditions (diabetes, heart disease, obesity, and sedentary behavior) as mediators; Race and gender as moderators	T-tests and standard logistic regression	High adversity (4+ ACEs) was associated with 2 to 3 times higher rates of severe work disability compared to no adversity.
Laditka and Laditka (2019)	USA		Quantitative; longitudinal cohort study		Employment (work disability)	Adult health, education, age, sex, race		T-tests and standard logistic regression	Health conditions (especially diabetes and obesity) partially explained the ACEs-work disability link, but gender and race didn’t strongly moderate the ACEs-work disability association.
Lafrenaye-Dugas et al. (2024)	Nunavimmiut	N = 1,109; 50.9% female; 74.5% 18–49 years, 25.5% 50 years	Quantitative; cross-sectional study	Adverse Childhood Experiences Questionnaire (Felitti et al., 2019) 10-items	Education level, employment status, and income	Sex, age	Family cohesion and community involvement as mediators	LCA; Chi-square tests; analyses of variance (ANOVAs)	The multiple ACE profile was associated with a lower rate of employment (OR = 0.62) for the 18–49 age group, but no significant associations were found for the 50+ age group.
Lafrenaye-Dugas et al. (2024)	Nunavimmiut	N = 1,109; 50.9% female; 74.5% 18–49 years, 25.5% 50 years	Quantitative; cross-sectional study		Education level, employment status, and income	Sex, age	Family cohesion and community involvement as mediators	LCA; Chi-square tests; analyses of variance (ANOVAs)	Family cohesion and community involvement mediated the relationship between ACEs and SES outcomes (employment, income).
Lecy and Osteen (2022)	USA	N = 2, 917; 58.3% female, mean age = 26.9 years; 77.6% White, 22.4% Black; all participants entered four-year colleges; 49.2% first-generation college students	Quantitative; longitudinal study	17 items mirroring CDC’s ACE framework and BRFSS	Education (college completion)	Race, gender, first-generation status	None	A longitudinal binary logistic regression mediation path analysis, a subset of structural equation modeling	Higher childhood trauma significantly reduced odds of college graduation (b = −0.29, p < .001). The higher the number of ACEs, the less likely the participant was to graduate from college.
Lin and Chiao (2022)	Taiwan, China	N = 2,903; 51% female; Age at baseline = 14 years, age at follow-up = 20 years	Quantitative; longitudinal cohort study	World Health Organization’s ACE International Questionnaire	Education, employment (NEET status: not in Education, Employment, or Training)	Gender, cohort, survey site, family SES, family cohesion, parental control, early pubertal maturation, lack of sleep, class rank, educational aspiration, substance abuse, self-esteem, depression	None	Logistic regression models	ACEs were significantly associated with NEET status: Each ACE increased NEET odds by 27% (AOR = 1.27); ≥3 ACEs tripled odds (AOR = 2.95).
Liu et al. (2013)	USA	N = 17,469; 63.4% female, Age: 18–64 years; 72.9% non-Hispanic White, 11.4% non-Hispanic Black, 9.7% Hispanic, 6.1% Others; 63.2% men and 66.0% women had >12 years of education	Quantitative; cross-sectional surveys	BRFSS ACE Module (8 items: sexual/physical/verbal abuse, parental separation/divorce, domestic violence, household substance abuse/mental illness/incarceration)	Employment	Gender, age, race/ethnicity	Education, marital status, perceived social support as mediators	Multivariate logistic regression models	Four or more ACEs tripled unemployment odds for men (AOR = 3.6) and for women (AOR = 1.6).
Liu et al. (2013)	USA		Quantitative; cross-sectional surveys		Employment	Gender, age, race/ethnicity		Multivariate logistic regression models	Education, marital status, and social support mediated the relationship between ACEs and unemployment.
Mabhala and Yohannes (2019)	UK	N = 26; 15.4% female, mean age = 38.6 years; homeless	Qualitative; cross-sectional study	Other (Narrative interview)	Education, employment	N/R	None	Grounded theory	Participants reported that ACEs reduced their capacity to fully engage with the social institution for social goods, such as education, social services, and institutions of employment.
Metzler et al. (2017)	USA	N = 27,834; 45.4% female, mean age = 43.3 years; 84.9% White, 4.7% Black, 3.9% Latino, 2.9% Asian, 3.6% Others	Quantitative; cross-sectional study	BRFSS ACE Module	SES (Education; employment; Poverty Status)	Age, sex, race/ethnicity	None	Logistic regression models	Compared to those with no ACEs, participants with four or more ACEs were 2.34 times more likely to not complete high school; 2.3 times more likely to be unemployed, and 1.6 times more likely to live in a household reporting poverty.
Naicker et al. (2022)	South Africa	N = 1,436; 52.44% female; Age = 28 years	Quantitative; longitudinal cohort study	Other (13 types of ACEs: physical/emotional/sexual abuse, child separation, parental divorce, parental death, exposure to violence, exposure to IPV, household substance abuse, chronic unemployment, household legal trouble, household illness/disability, household death)	Education, employment, welfare receipt	Sex; socio-economic status at participant birth, age 12, and age 22; maternal age at birth; maternal and paternal years of schooling	None	Logistic regression models	Six or more ACEs were significantly associated with higher odds of incomplete secondary schooling (OR = 1.51, 95% CI [1.15, 1.99]) and unemployment (OR = 1.28 [1.10, 1.64]), but not with welfare receipt.
Otero (2021)	USA	N = 13,446; 50% female; mean age = 28.98 years; 67% White, 33% Nonwhite	Quantitative; longitudinal study	Adverse Childhood Experiences Questionnaire (Felitti et al., 1998) 10-items	Education (timely bachelor’s degree attainment)	Parental education, public assistance receipt, income in Wave I, adolescent’s aspiration, expectations for college attendance, students’ age, sex, race, vocabulary test scores, student learning disability	General health and depression as mediators	Logistic regression models	Each additional ACE decreased the odds of timely bachelor’s degree attainment by about 17%, even after accounting for covariates (p < .001).
Otero (2021)	USA		Quantitative; longitudinal study		Education (timely bachelor’s degree attainment)		General health and depression as mediators	Logistic regression models	Depression and general health partially mediated this link.
Petersen et al. (2022)	Germany	N = 2,288; 53.3% female, mean age = 53.3 years	Quantitative; cross-sectional study	German version of the ACE Questionnaire (10 items)	SES (education, employment, household income)	Gender, migration background	Depression as moderator	Logistic regressions; Structural equation modeling (SEM)	Participants who reported four or more ACEs had significantly lower levels of education (B = 0.097, p = .004, 95% CI [0.031, 0.163]), lower income (B = 0.108, p < 0.001 [0.058, 0.158]), and a higher risk of unemployment (B = 0.155, p < .001 [0.107, 0.203]). Depression significantly moderated the relationship between having 4 or more ACEs and current unemployment, amplifying this effect (B = 0.097, p < 0.001).
Schurer et al. (2019)	UK	N = 7,450; 55.5% female; age = 55 years at outcomes measurement	Quantitative; longitudinal cohort study	Other (6 types of ACEs: foster care experience, physical neglect, parental separation, family member mental illness, family member alcohol abuse, criminal offense in the household)	Income (log earnings, welfare dependence, subjective poverty)	Participants’ gender/birth weight/prematurity at birth/birth order, mother’s age at birth, parental education/occupation/income/household crowding	Cognitive and noncognitive skills; mental and physical health; education; family formation; labor force attachment as mediators	Linear regression model	A one-unit increase in ACE was associated with a 12.5% reduction in log net earnings at age 55, 4.5% increase in welfare dependence, and 3.3% increase in subjective poverty (p < .01).
Schurer et al. (2019)	UK		Quantitative; longitudinal cohort study					Linear regression model	The mediators (especially education and cognitive/noncognitive skills) mediated the relationship between neglect (the strongest ACEs component) and earnings penalty.
Schüssler-Fiorenza Rose et al. (2016)	USA	N = 13,309; 51.9% female; Age groups:18–29 years (11.3%), 30–44 years (31.3%), 45–54 years (28.6%), 55–64 years (28.8%); race = 81.9% non- Hispanic White, 8.5% non-Hispanic Black, 1.3% Asian/Nat Haw/PI, 4.6% Other	Quantitative; cross-sectional study	BRFSS ACE Module (8 items: physical/emotional/sexual abuse, domestic violence, parental substance abuse, incarceration, mental illness, divorce or separation)	Employment (work inability)	Age, sex, race, education, self-reported physical/mental health	Functional support (emotional/social) and structural support (cohabitation) as moderators	Logistic regression analyses	Participants with a high ACE burden had significantly greater odds of work inability compared to those with no ACEs (AOR = 1.90, 95% CI [1.50, 2.40]).
Schüssler-Fiorenza Rose et al. (2016)	USA		Quantitative; cross-sectional study		Employment (work inability)			Logistic regression analyses	Functional support buffers work inability only when physical health is good (p = .038), structural support is universally protective but most effective for those with good mental health (p = .026).
Schwartz et al. (2019)	USA	National Longitudinal Study of Adolescent to Adult Health (Add Health) Sample: N = 3,112 twins/siblings; 50% female, mean age = 16.08 years; 63.21% Caucasian, 36.79% all other races, MIDUS Sample: N = 862 twins; 54.2% female; 54.2 years;94.78% Caucasian, 5.22% all other races	Quantitative; longitudinal cohort study	Other; For the MIDUS sample, ACEs were measured using 17 items categorized into 3 domains (9 stressful events, 2 parent-relationship, 6 abuse). For Add Health sample, ACEs were measured by 11 items over same domains (7 stressful events, 1 parental-warmth, 3 abuse)	Education (high school diploma or higher); income (above vs. below poverty line)	Lifestyle (smoking, diet, physical activity), stress (daily stress, perceived stress), age, sex, race	Genetic relatedness as moderator	Logistic regression model	In the MIDUS sample, greater exposure to ACEs was significantly associated with lower odds of obtaining a high school diploma (b = –1.99, p < .001), but not significantly related to income attainment (b = 0.55, p = .115). Similarly, in the Add Health sample, higher ACE exposure was linked to a decreased likelihood of completing high school (b = –0.71, p < .001).
Schwartz et al. (2019)	USA		Quantitative; longitudinal cohort study				Genetic relatedness as moderator	Logistic regression model	Genetic relatedness did not significantly moderate the association between ACEs and educational or income attainment.
Shaefer et al. (2018)	USA	N = 2,687; mean age = 45.9 years; 51.9% female; 85%White, 13.2% Black, 0.6% Asian, 3% Hispanic	Quantitative; longitudinal cohort study	Childhood Retrospective Circumstances Supplement (4 items: physical abuse, domestic violence, parental depression, parental drug use)	Education (less than high school education) and poverty	Sex, race, Hispanic origin, age, average number of siblings	Childhood income as moderator	Regression model	Each additional ACE increased the probability of living in poverty by 4.17 percentage points (b = 0.0417, SE = 0.0105, p < .001), of being uninsured by 2.84 pp (b = 0.0284, SE = 0.0096, p < .01), and of not completing high school by 1.66 pp (b = 0.0166, SE = 0.0065, p < .05).
Shaefer et al. (2018)	USA		Quantitative; longitudinal cohort study		Education (less than high school education) and poverty	Sex, race, Hispanic origin, age, average number of siblings	Childhood income as moderator	Regression model	Higher childhood income weakened the link between ACEs and education attainment.
Smith et al. (2022)	UK	ACEs subsample: N = 2,707; 70.6% female, mean age = 29 years; 95.2% White, 4.8% non-white. Socioeconomic Position (SEP) subsample: N = 2,557; 71.0% female, mean age = 23 years; 95.8% White, 4.2% non-white	Quantitative; longitudinal cohort study	World Health Organization ACE International Questionnaire (10 items)	Income, Employment	Participant’s ethnicity, age, home ownership, mother’s marital status, parity, and age at the participant’s birth, educational qualifications of the mother and their partner	None	Multinominal regression model	Individuals with 4 or more ACEs faced elevated risks of adverse financial and employment outcomes during the COVID-19 lockdown, including higher odds of being furloughed or placed on leave (OR = 1.92, 95% CI [1.35, 2.74]) and experiencing financial decline (OR = 1.42 [1.00, 2.02]).
Stevens et al. (2018)	USA	N = 457; 46% female, Mean age = 36 years (range 31–41); 80.7% White, 11.2% more than one race, 5.3% Black or African American, 2.8% other	Quantitative; longitudinal cohort study	Cumulative childhood household adversity (21 items: conflict with neighbors, relatives, and between parents, break-up of marriage/family, dissatisfaction with marital relationship, problems with other adults in the home, child behavior problems at home or in school, insufficient income, crowding in the home, lack of home conveniences, responsibility of child care, unemployment, trouble with police, mental or physical illness, chronic fatigue, pregnancy, unfulfilled ambitions, lack of friends, and substance problems)	SES (education, income, employment)	Gender	Caregiver relationship quality as moderator	Multiple group path analysis	Among non-maltreated participants, greater cumulative household adversity predicted lower educational attainment (b = −0.48, p < .004) and more income problems (b = 0.28, p < .004), whereas these associations were non-significant in the maltreated group. Total household adversity was not associated with unemployment in either maltreated or non-maltreated groups.
Stevens et al. (2018)	USA		Quantitative; longitudinal cohort study		SES (education, income, employment)	Gender	Caregiver relationship quality as moderator	Multiple group path analysis	The moderation effect of caregiver relationship quality was not significant.
Suglia et al. (2022)	USA	N = 6,844; Wave 1: age = 12–18; Wave 2: mean age = 16; Wave 3: mean age = 22; Wave 4: mean age = 29; Wave 5: mean age = 37; Race = 68% White	Quantitative; longitudinal cohort study	Adapted version Adverse Childhood Experiences Scale (9-items)	SES (Adulthood SES was characterized as the average of the sum of participant’s education, occupation and household income with a higher score representing greater SES)	Age, sex, race/ethnicity	None	Chi-square tests, ANOVA; multivariable linear regression models; multinomial logistic regression models; mediation path analysis model	A dose-response relationship was reported between cumulative childhood adversities (CAs) and lower adult SES. CAs partially mediated the link between childhood SES and adult SES, independent of age, sex, and race/ethnicity.
Tam et al. (2003)	USA	N = 376; sex = 25.3% female, Age: >35(61.0%); 66.9% African American	Quantitative; longitudinal study	ACEs were measured by 8 items: a history of living in a foster care, group home or other out-of-home placement, sexual abuse, physical abuse, running away from home for seven nights or more, being arrested, homelessness, and early regular alcohol or drug use.	Employment (Labor force participation)	Gender, age, chronic homelessness, lifetime substance uses and mental disorder, and perceived disability	Adulthood substance use and service use as mediators	Chi-square test, Fisher’s exact test, Bonferroni correction, and path analysis	Adverse childhood events did not directly affect labor force participation, but ACEs were significantly associated with consistent substance use (b = 0.09), which was significantly related to labor-force participation (b = –0.14). In a word, consistent substance use mediated ACEs- employment link, but not service utilization.
Topitzes et al. (2016)	USA	N = 199; 100% male; mean age = 34.2 years; 94.5% African American, 3.5% Multiracial, 0.5% Hispanic and other; 76.8% single	Quantitative; cross-sectional study	10-item version of the ACE questionnaire (Felliti et al., 1998)	Employment (history of employment problems)	Age; race; marital status; number of children; educational attainment; and past year’s income	Drug problems, depression as mediators	Bivariate correlations, OLS, logistic regressions, mediation analysis	The ACE index was significantly associated with history of employment problems (b = 0.149, p = .001). As individuals reported more ACEs, their likelihood of experiencing employment problems also increased. This relationship was mediated by drug problems but not by depression.
Veldman et al. (2015)	Netherlands	N = 2,230; 49.2% female, mean age = 19.1 years	Quantitative; longitudinal study	Other (11 items: family poverty, parental divorce, death of parents/siblings, serious illness of parents/siblings, not living at home for more than 3 months, hospitalization, having an injury, serious illness of a friend, being bullied)	Education (the highest level of education)	Sex, parental education level, intelligence of the child	Mental health problems as mediators	Chi-square tests, Structural equation models (SEMs)	Childhood adversities were associated with educational attainment in in young adulthood (b = −0.45, p < .001).
Veldman et al. (2015)	Netherlands	N = 2,230; 49.2% female, mean age = 19.1 years	Quantitative; longitudinal study		Education (the highest level of education)	Sex, parental education level, intelligence of the child	Mental health problems as mediators	Chi-square tests, Structural equation models (SEMs)	Mental health problems, particularly externalizing problems, partially mediated the association between childhood adversities and the education outcome.
Wang (2024)	China	N = 11,544; 45.33% female; birth cohorts: 1930–1939 (3.32%), 1940–1949 (17.68%), 1950–1959 (31.08%), 1960–1969 (39.56%), 1970–1979 (8.36%)	Quantitative; longitudinal cohort study	Twenty Items from CHARLS questionnaire: parental divorce, family conflict, physical abuse, parental bias, emotional neglect, parent’s substance abuse, parental incarceration, parental physical illness, parental mental illness, sibling death, experience of starvation, family economic hardship, feeling lonely, having no close friends, bullying, feeling unhappy/insecure/unhygienic/unharmonious community	Employment	Gender, urban–rural residence, birth cohorts, ethnic, and political status	None	Multinominal logistic models	Participants with high levels of ACEs had increased risk of unemployment. Specifically, those with 4–5 ACEs were less likely to belong to the clusters “military service & stable employment” (b = −0.026, p < .05) and “long studies & stable employment” (b = −0.036, p < .05), and more likely to be classified in the “unemployment” cluster (b = 0.068, p < .01).
Xu et al. (2022)	Switzerland	N = 5,111; 53.6% female; mean age = 54.7 years	Quantitative; cross-sectional study	Modified Schedule for Affective Disorders and Schizophrenia-Lifetime Version (9 items: Overall childhood happiness, not raised by both biological parents, divorced/separated parents, placed in foster home, loss of significant others, depressed father, depressed mother, interparental violence, child abuse)	Education (highest level of education); income	None	None	LCA; Logistic regression; Kruskal-Wallis H tests	Compared to the low adversity class, the high adversities class showed overall worse outcomes in education (p = .002) and income (p = .001).

Note. ACEs = Adverse Childhood Experiences; BRFSS = Behavioral Risk Factor Surveillance System; NEET = Not in Education, Employment, or Training; CPC = Child-Parent Center; CDC = Centers for Disease Control and Prevention; SES = Socioeconomic Status; LCA = Latent Class Analysis; MIDUS = Midlife Development in the United States; AOR = Adjusted Odds Ratio; IPV = Intimate Partner Violence.

Study Designs

Of the 35 included studies, 33 (94.3%) were exclusively quantitative, and 2 (5.7%) were qualitative (Frederick & Goddard, 2007; Mabhala & Yohannes, 2019). Moreover, 22 studies (62.9%) adopted a longitudinal design, while 13 (37.1%) conducted a cross-sectional study.

Measurement of ACEs

Measurement of ACEs also varied across studies (See Table 1). Fourteen studies (40%) used either the original ACE checklist or the CDC Behavioral Risk Factor Surveillance System (BRFSS) ACE module. One study (2.9%) used the Childhood Trauma Questionnaire to measure five types of child maltreatment (Barker et al., 2017). Two studies (5.7%) used the World Health Organization ACE international questionnaire (Lin & Chiao, 2022; Smith et al., 2022). Eighteen studies (51.4%) used other validated measures (Fahy et al., 2017; Halonen et al., 2017; Harkonmäki et al., 2007) or combined multiple sources (Bouvette-Turcot et al., 2017) to measure ACEs.

Socioeconomic Status Outcomes

In this review, SES outcomes are categorized into three domains: employment status, income/poverty, and educational attainment. Five studies (14.3%) exclusively assessed the impact of ACEs on education (Barker et al., 2017; Horan & Widom, 2015; Lecy & Osteen, 2022; Otero, 2021; Veldman et al., 2015). Nine studies (25.7%) focused on employment outcomes (Fahy et al., 2017; Halonen et al., 2017), and two studies (5.7%) focused exclusively on income (Kim et al., 2020; Schurer et al., 2019). Nineteen studies (54.3%) assessed either two or all three SES domains (Bouvette-Turcot et al., 2017; de Vries et al., 2023; Dosanjh et al., 2023). The following sections present the review results for each individual SES domain as well as studies examining multiple SES outcomes.

Education

Among the five studies that examined the relationship between ACEs and education attainment, all confirmed a significant negative association (Barker et al., 2017; Horan & Widom, 2015; Lecy & Osteen, 2022; Otero, 2021; Veldman et al., 2015). For example, Barker et al. (2017) found that compared to those with no ACEs, individuals with four or more ACEs were more likely to not complete high school.

Regarding postsecondary outcomes, Lecy and Osteen (2022) reported that a higher number of ACEs reduced the likelihood of college graduation. In addition, Otero (2021) specifically examined timely bachelor’s degree attainment and identified a graded relationship, with each additional ACE associated with lower odds of graduating on time.

Consistent with the above findings, two studies examined the impact of ACEs on overall educational attainment and confirmed that individuals with higher ACEs scores were more likely to report lower levels of education (Horan & Widom, 2015; Veldman et al., 2015).

Employment

Among the nine studies that focused on the impact of ACEs on employment, the findings consistently indicated a significant relationship between ACEs exposure and employment outcomes (Fahy et al., 2017; Halonen et al., 2017; Harkonmäki et al., 2007; Laditka & Laditka; 2019; Liu et al., 2013; Schüssler-Fiorenza et al., 2016; Tam et al., 2003; Topitzes et al., 2016; Wang, 2024). Three studies found that individuals with higher ACEs scores were at greater risk of being unemployed compared to those with no ACEs (Liu et al., 2013; Topitzes et al., 2016; Wang, 2024). Notably, Lafrenaye-Dugas et al. (2024) reported that this association was only significant among individuals aged 18 to 49, but not among those aged 50 and older. Additionally, Liu et al. (2013) found that the odds of unemployment were higher for women with greater exposure of ACEs.

Five studies specifically examined the relationship between ACEs and work disability, which refers to self-reports of physical or psychological conditions that impair the ability to work or make it unfeasible (Jette & Badley, 2000). These studies found that ACEs might increase the likelihood of work disability across the lifespan (Fahy et al., 2017; Halonen et al., 2017; Harkonmäki et al., 2007; Laditka & Laditka, 2019; Schüssler-Fiorenza Rose et al., 2016). Particularly, a dose-response relationship was also observed: individuals with higher exposure to ACEs had greater odds of experiencing work disability (Halonen et al., 2017; Harkonmäki et al., 2007; Laditka & Laditka, 2019; Schüssler-Fiorenza Rose et al., 2016). Furthermore, Fahy et al. (2017) found that experiencing two or more ACEs was significantly associated with being permanently sick, but only among men.

Income/Poverty

Both studies that examined the impact of ACEs on income/poverty reported a consistent relationship between ACEs and income/poverty (Kim et al., 2020; Schurer et al., 2019). Kim et al. (2020) found that the likelihood of experiencing economic hardship was significantly higher for both men and women who had experienced child maltreatment or family dysfunction, compared to individuals in the low adversity group. Similarly, Schurer et al. (2019) found that a one-unit increase in ACE was associated with a reduction in log net earnings at age 55, as well as increased welfare dependence and subjective poverty.

Multiple SES Outcomes

Education and Income

Among the five studies that examined the impact of ACEs on both education and income, four studies confirmed that exposure to ACEs was related to both reduced education and income (Bouvette-Turcot et al., 2017; Dosanjh et al., 2023; Shaefer et al., 2018; Xu et al., 2022). The remaining study (Schwartz et al., 2019) found no independent relation with income once covariates were controlled for the Midlife Development in the United States sample, although the authors still observed lower odds of high school graduation among participants with elevated ACEs scores.

Education and Employment

All the five studies that paired education and employment outcomes reported significant negative associations with ACEs. Two studies focused on “not in education, employment, or training” (NEET) status: individuals with higher ACEs exposure had greater odds of being classified as NEET (de Vries et al., 2023; Lin & Chiao, 2022). Giovanelli et al. (2016) found that individuals with four or more ACEs had significantly lower odds of high school graduation and skilled employment. Hardcastle et al. (2018) linked high ACEs exposure to unemployment, long-term illness or disability, and lack of qualifications. A qualitative study (Mabhala & Yohannes, 2019) echoed these findings, describing disrupted engagement with educational and labor-market institutions following childhood adversity.

Income and Employment

Smith et al. (2022) investigated the impact of ACEs on both employment and economic status of adults during the COVID-19 pandemic and showed that individuals with four or more ACEs faced elevated risks of adverse financial and employment outcomes, including higher odds of being furloughed or placed on leave and experiencing financial decline during COVID-19 lockdown.

Education, Employment, and Income

Seven studies evaluated all three SES domains simultaneously. Consistently, high ACEs exposure (generally four or more ACEs) predicted unfinished schooling, unemployment, and lower income or poverty (Frederick & Goddard, 2007; Haahr-Pedersen et al., 2020; Metzler et al., 2017; Petersen et al., 2022; Stevens et al., 2018). However, two exceptions emerged: Naicker et al. (2022) found that six or more ACEs were significantly associated with higher odds of incomplete secondary schooling and unemployment, but not with welfare receipt. Lafrenaye-Dugas et al. (2024) observed lower rate of employment for adults aged 18 to 49 in the multiple ACEs profile, yet no independent association with income or education.

Composite SES Index

Using a standardized SES score averaging education, occupation, and household income, Suglia et al. (2022) found a clear dose-response gradient: greater childhood adversity corresponded to lower adult SES.

Mediation and Moderation Effects

Mediating Mechanisms

Among the 35 articles, 11 studies (31.4%) examined mediating mechanisms through which ACEs influence socioeconomic outcomes. Seven studies particularly focused on health-related pathways. Depression and general health partially explained lower odds of timely bachelor’s degree attainment (Otero, 2021), while externalizing problems partially accounted for reduced educational attainment (Veldman et al., 2015). Young adult health bridged the link between ACEs and later subjective poverty, though not earnings or welfare dependence (Schurer et al., 2019). Diabetes and obesity partially explained work disability (Laditka & Laditka, 2019). Consistent substance uses mediated poorer labor-force participation (Tam et al., 2003). Depression and health behaviors connected ACEs with disability retirement (Harkonmäki et al., 2007). In contrast, only drug problems, but not depression, mediated the relationship between ACEs and employment difficulties (Topitzes et al., 2016).

Two studies (5.7%) explored social support as a mediator. Family cohesion and community involvement transmitted ACEs effects to both employment and income (Lafrenaye-Dugas et al., 2024), and perceived social support mediated the association between ACEs and unemployment (Liu et al., 2013).

Three studies (8.6%) examined education-related factors as mediators. Harkonmäki et al. (2007) found that low occupational training mediated the link between ACES and disability retirement, with those at the lowest levels of occupational training having a 4.5-fold higher risk of disability retirement compared to those with the highest training. Liu et al. (2013) also found that educational attainment partially mediated the relationship between ACEs and unemployment among women. Similarly, Schurer et al. (2019) found that education mediated the relationship between ACEs and reduced earnings.

Other mediators investigated less frequently include marital status and cognitive/noncognitive skills. Liu et al. (2013) found that marital status partially mediated the relationship between ACEs and unemployment among women, while Schurer et al. (2019) reported that cognitive and noncognitive skills significantly mediated the relationship between ACEs and income, although marital status did not significantly explain the earnings gap.

Moderating Factors

Thirteen studies (37.1%) explored moderation effects. Of these, Gender or gender identity was the most common moderator (five studies, 14.3%). ACEs effects were stronger for males on educational attainment (Horan & Widom, 2015) and permanent sickness, but stronger for females on part-time employment (Fahy et al., 2017). High adversity predicted unemployment only among females (Haahr-Pedersen et al., 2020). No significant moderation was observed for work disability (Laditka & Laditka, 2019). Additionally, Sexual and Gender Diverse (SGD) identity significantly mitigated the relationship between ACEs and income and education (Dosanjh et al., 2023).

Two studies (5.7%) examined the moderation role of social support. Participation in the Child-Parent Center preschool program, a combined educational and family support intervention, moderated the effect of ACEs on education and employment (Giovanelli et al., 2016). Functional support (emotional/social) mitigated work inability only when physical health was good, while structural support (e.g., cohabitation) was universally protective, particularly for those with good mental health (Schüssler-Fiorenza Rose et al., 2016).

Two studies (5.7%) identified the moderation effect of depression. Bouvette-Turcot et al. (2017) reported that depression amplified ACEs effects on maternal family income but not on maternal educational attainment. Petersen et al. (2022) found that depression significantly amplified the association between having four or more ACEs and current unemployment.

One study tested the moderation effect of educational qualifications and found it did not moderate the ACEs-employment association (Hardcastle et al., 2018). Also, higher childhood income weakened the link between ACEs and educational attainment (Shaefer et al., 2018), whereas genetic relatedness did not moderate the association between ACEs and educational or income attainment (Schwartz et al., 2019). Finally, the participant’s relationship quality with their caregivers did not moderate the relationship between ACEs and all the three domains of SES (Stevens et al., 2018).

Discussion

This scoping review synthesizes the existing scholarly literature on the impact of ACEs on socioeconomic outcomes in adulthood. Nearly half of the reviewed studies were conducted in the United States. Most studies employed quantitative longitudinal designs with relatively large samples and focused primarily on young and middle-aged adults. Across study designs and SES indicators, the evidence overwhelmingly indicates that cumulative exposure to ACEs is significantly associated with diminished educational attainment, weaker labor-market attachment, and reduced economic resources in adulthood. Exceptions were sparse and typically limited to one SES dimension or emerged only after extensive covariate adjustment, underscoring the robustness of the ACEs-SES gradient. Additionally, the review evidence indicates that ACEs-related socioeconomic disadvantage operates partly through compromised health, limited social and educational resources, and reduced psychosocial supports. Moderator findings emphasize the contingent roles of gender, social programs, and mental health, although inconsistencies across studies highlight the need for further replication and nuanced investigation.

From the perspective of cumulative inequality theory, the overall association between ACEs and adverse SES outcomes is not surprising. Early life disadvantages can accumulate over time, exerting lasting negative impacts on individuals and shaping their life trajectories (Aquilino, 1996; Crystal & Shea, 1990; Dannefer, 2003; DiPrete & Eirich, 2006; Ferraro & Shippee, 2009; Gilligan et al., 2018). Exposure to ACEs is associated with a wide range of adverse physical, mental, behavioral, cognitive, and other outcomes. For example, ACEs may impair cognitive functioning (Hawkins et al., 2021; Ren et al., 2023), contribute to adverse psychological outcomes (Sheffler et al., 2020), and disrupt stress-response functioning (Essex et al., 2011), all of which may, in turn, increase the risk of unfavorable SES outcomes in adulthood.

The reviewed studies also generally suggest that ACEs are associated with SES disadvantages across adulthood, from emerging adulthood to later life. One exception was reported by Lafrenaye-Dugas et al. (2024), who found that the association between multiple ACEs and unemployment was significant only among Inuit adults aged 18 to 49, but not among those aged 50 and older. This age difference may reflect cohort variation in ACEs exposure linked to historical and political changes in Inuit family life under settler-colonial policies, as well as differences in relationship stability and family cohesion (Kral, 2016; Lafrenaye-Dugas et al., 2024). In addition, without considering ACEs exposure, researchers found that age is typically positively associated with earning ability, although the relationship is nonlinear, with the squared term of age showing a negative association with earnings (Fingleton & Longhi, 2013). It is possible that the lack of observed age-related patterns may reflect methodological limitations in the existing literature rather than the true absence of age differences, as most included studies did not conduct age-group analyses or formally test variation across adulthood. At the same time, it is also possible that ACEs exposure exerts persistent and cumulative effects on SES that remain evident across the adult life course, regardless of life stage. Future research should examine age-specific and cohort-specific patterns more explicitly to clarify whether the effects of ACEs on SES vary across stages of adulthood.

Strengths, Limitations, and Research Gaps in the Existing Evidence Base

The included studies have made important contributions to research on ACEs and SES outcomes. Collectively, they have extended the study of ACEs beyond physical, mental, and behavioral problems to include socioeconomic outcomes, thereby emphasizing the overall well-being of individuals. Methodologically, most studies used large sample sizes, which enhance the generalizability of their findings. Furthermore, in addition to investigating the direct associations between ACEs and adult SES outcomes, many studies have explored potential mediation and moderation mechanisms underlying these relationships. Identifying these mechanisms provides valuable insight into how early adversity translates into later life socioeconomic disadvantages and helps inform more targeted interventions and policy responses.

Our review study also identified several methods limitations in the existing literature. A major limitation of the included studies is their heavy reliance on quantitative methods, which may overlook individuals’ lived experiences and the specific contexts in which adversities occur. Also, all included studies adopted the cumulative ACEs score, which overlooks the frequency, intensity, chronicity, and complexity of individual experiences (Anda et al., 2020). Additionally, ACEs were predominantly measured retrospectively, which may introduce recall bias (Hardt & Rutter, 2004). Furthermore, the measurement of ACEs was not consistent across studies, which may limit comparability and contribute to variation in research findings. Equally problematic is that most studies examined only one or two domains of SES outcomes, with only eight studies (22.9%) assessing overall SES (Frederick & Goddard, 2007; Haahr-Pedersen et al., 2020; Lafrenaye-Dugas et al., 2024; Metzler et al., 2017; Naicker et al., 2022; Petersen et al., 2022; Stevens et al., 2018; Suglia et al., 2022). Because SES is a multidimensional construct (Braveman et al., 2005), a more comprehensive examination of different SES domains may provide a clearer understanding of how ACEs influence each dimension of SES and the potential interactions among them. Finally, although previous studies have shown that childhood SES is associated with adulthood SES (Currie & Spatz Widom, 2010; Nagaraju et al., 2019), most of the reviewed studies did not control for childhood SES, with the exception of the 11 studies (31.4%) by de Vries et al. (2023), Fahy et al. (2017), Giovanelli et al. (2016), Hardcastle et al. (2018), Lecy and Osteen (2022), Lin and Chiao (2022), Naicker et al. (2022), Otero (2021), Schurer et al. (2019), Smith et al. (2022), and Veldman et al. (2015).This omission may confound the observed relationships between ACEs and adulthood socioeconomic outcomes.

In terms of research gaps in the current evidence base, variations in age, race, and neighborhood characteristics associated with ACEs and SES have largely been overlooked. Most studies have focused on young or middle-aged adults and predominantly White populations. This sample composition may obscure the experiences of older adults and other racial groups. In addition, different racial populations may face distinct levels of ACE exposure, particularly children and families from historically marginalized groups often face elevated risks due to systemic inequalities (Camacho & Henderson, 2022; Maguire-Jack et al., 2020; Mersky et al., 2021). Further examining the moderating effects of age and race could provide a more nuanced understanding of how ACEs are associated with SES outcomes. From a social determinants of health perspective (World Health Organization, 2008), neighborhood characteristics may also play a significant role in unpacking the mechanisms through which ACEs influence SES (Skiendzielewski et al., 2024). For instance, examining neighborhood characteristics could situate the association between ACEs and SES within broader social contexts and help identify potential moderating factors at the neighborhood level.

Implications for Future Research, Practice, and Policy

The findings of this scoping review have significant implications for future research, practice, and policy. Methodology, future research should incorporate more qualitative approaches, as social inequalities are embedded in broader social and cultural contexts (Mabhala et al., 2017). Qualitative research methods can provide richer narratives of complex experiences and help ensure that the voices of marginalized groups are heard (Sofaer, 1999). Future research should also pay greater attention to population heterogeneity. Given that socioeconomic status can change over the life course, more research is needed on older populations along with longitudinal studies to track how ACEs impact the SES developmental trajectories over time. Greater attention is also needed for indigenous and other underrepresented populations. Among the 35 articles reviewed, only one specifically focused on SGD population (Dosanjh et al., 2023), and another study examined the indigenous populations (Lafrenaye-Dugas et al., 2024). Yet indigenous populations are at increased risk for unstable housing and lower socioeconomic status (Statistics Canada, 2017, 2018), they and other marginalized groups are often overlooked or labeled as “other” in current literature (Schultz & Spencer, 2023). In addition, greater standardization and stronger measurement approaches are needed to improve comparability and validity in research findings. Future research should more consistently account for childhood SES to reduce potential confounding and better isolate the unique contribution of ACEs to adult socioeconomic outcomes. Furthermore, future research should also adopt a more comprehensive approach to SES. Because education, employment, and income/poverty are interrelated domains of SES (Liberatos et al., 1988; Winkleby et al., 1992), a broader assessment of overall socioeconomic well-being may provide a clearer understanding of how ACEs shape socioeconomic disadvantage across adulthood. Finally, neighborhood characteristics warrant greater examination. Future research should investigate how neighborhood conditions may shape the mechanisms linking ACEs to SES and whether neighborhood-level resources or risks moderate these associations.

Based on the findings of this scoping review, several key implications for practice emerge. To begin with, financial assistance and employment training programs may be more effective when they integrate trauma-informed support services that address individuals’ exposure to ACEs (Subramaniam et al., 2023; Testa & Jackson, 2020). These services can help mitigate barriers to economic participation and promote long-term self-sufficiency. In addition, given that mental health conditions have been found to mediate the relationship between ACEs and SES in adulthood (Harkonmäki et al., 2007; Otero, 2021; Schurer et al., 2019; Veldman et al., 2015), implementing psychological resilience programs such as enhancement of positive emotions may be especially beneficial for individuals with high ACEs exposure (Poole et al., 2017). Moreover, some studies have identified gender differences in how ACEs impact SES (Haahr-Pedersen et al., 2020). Therefore, gender-based services may be helpful to address the distinct needs and challenges faced by males and females, ultimately improving the effectiveness of targeted interventions.

Finally, this review also provides implications for policy. At the educational level, policies should prioritize not only expanding access to basic education and supporting academic achievement, but also incorporating skill development, mental health supports, and social-emotional learning, to accommodate the complex needs of individuals with high ACEs exposure (Hardcastle et al., 2018). At the structural level, policymakers should address the structural determinants that contribute to ACEs, including systemic racism, concentrated poverty, residential segregation, and the unequal distribution of resources. While many existing interventions emphasize individual-level interventions, these efforts alone are insufficient (Crowley et al., 2022). At the economic level, expanding and strengthening economic safety net programs, such as child tax credits, food assistance, subsidized childcare, paid family leave, can buffer the compounding effects of ACEs on employment and income in adulthood. These policies can play a crucial role in stabilizing families, reducing stress, and improving long-term socioeconomic outcomes for both children and adults.

Limitations and Implications of the Current Review

Although a few systematic reviews have examined the association between childhood maltreatment and specific socioeconomic outcomes such as poverty or educational attainment in adulthood (Bunting et al., 2018; Yeo et al., 2024), this is the first study to systematically review the literature on the cumulative impact of ACEs on a broad range of SES outcomes in adulthood. However, this review study is not without limitations. One of the limitations is that this scoping review only included English-language, peer-reviewed articles, thereby excluding gray literature and studies published in other languages. This may limit the global scope and inclusiveness of the findings. Additionally, this review exclusively focused on studies with a cumulative measure of at least four ACEs. Therefore, studies examining individual ACEs or those using alternative scoring methods may have been excluded, potentially overlooking important nuances in how specific ACEs impact SES outcomes. Finally, while our search strategy was comprehensive in its use of multidisciplinary databases and well-defined keywords, this review focused specifically on standardized SES outcomes: education, employment, and income/poverty to maintain a focused and manageable scope. Broader indicators of SES, such as welfare receipt, housing insecurity, and food insecurity (Baker, 2014), were not included as search terms. As a result, studies addressing these dimensions were excluded from this review. This exclusion may potentially limit our understanding of the multifaceted ways in which ACEs influence adult income and material hardship.

Based on these limitations, future review studies may consider including non-English language articles and gray literature to improve the comprehensiveness and inclusiveness of the evidence base. Future reviews may also consider examining both cumulative ACEs and specific types of ACEs, as well as alternative ACEs scoring approaches, to capture greater nuance in how childhood adversity is associated with adult SES outcomes. Furthermore, broader indicators of socioeconomic status, such as housing insecurity, food insecurity, and welfare receipt, should be incorporated into future evidence syntheses to better reflect the multidimensional nature of socioeconomic disadvantage. Finally, future reviews could extend this line of work by mapping interventions and policies responses related to ACEs and adult socioeconomic outcomes, thereby generating more actionable evidence for practitioners and policymakers.

Conclusion

This scoping review mapped the existing literature examining the association between ACEs and adult socioeconomic outcomes. Across the 35 included studies, findings consistently suggested that exposure to ACEs was associated with lower educational attainment, including reduced rates of high school and college completion, as well as increased risks of unemployment, work disability, and poverty in adulthood. The review also identified several potential mechanisms linking ACEs to adult socioeconomic disadvantage, including health-related factors such as diabetes, heart disease, obesity, depression, and substance use. In addition, factors such as gender, social support, childhood income, and educational attainment appeared to moderate these associations. Taken together, these findings suggest that ACEs are not only a public health issue but also an economic and social justice concern. The consequences of ACEs extend beyond health outcomes and may contribute to long-term socioeconomic inequalities across the life course. These findings underscore the importance of coordinated prevention, intervention, and policy efforts aimed at reducing childhood adversity and mitigating its long-term social and economic consequences (Table 3).

Table 3.

Summary of Critical Findings and Implications.

Summary of critical findings
• Exposure to multiple ACEs was associated with lower completion rates for high school and college, particularly reducing timely college graduation. • Higher ACEs exposure increased the likelihood of unemployment and work disability in adulthood. • ACEs significantly heightened the risk of poverty, with financial difficulties accumulating throughout the life course. • Health-related factors such as diabetes, heart disease, obesity, depression, and substance use mediated the relationship between ACEs and adult socioeconomic outcomes. • Gender or gender identity, social support, childhood income, educational qualifications, and depression moderated the relationship between ACEs and adult socioeconomic outcomes.
Key implications for research, practice, and policy
Research Implications: • Future research should incorporate more qualitative methods. • Future research should examine the impact of ACEs on older populations and employ longitudinal designs to track how ACEs shape socioeconomic trajectories over time. • Future research should pay more attention to ACEs and SES outcomes among indigenous and other underrepresented populations. • Future research should further explore resilience-building mechanisms that may buffer the effects of ACEs and promote SES outcomes across life course. Practice Implications: • Integrate financial assistance and employment training with trauma-informed support services that aim to address individuals’ childhood trauma. • Implement psychological resilience programs (e.g., positive emotion training) to mitigate mental health related pathways linking ACEs and SES outcomes. • Develop gender-responsive services to address distinct needs and improve intervention effectiveness. Policy Implications: • Expand access to education while integrating skill development, mental health supports, and social-emotional learning. • Address structural determinants of ACEs and SES outcomes, including systemic racism, concentrated poverty, residential segregation, and resources inequalities. • Strengthen economic safety nets (e.g., child tax credits, food assistance, subsidized childcare, paid family leave) to buffer the long-term socioeconomic effects of ACEs.

Note. ACEs = Adverse Childhood Experiences; SES = socioeconomic status.

Footnotes

ORCID iDs

Yuqing Chen

Lixia Zhang

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Author Biographies

Yuqing Chen, MSW, is a PhD student at the Raymond A. Kent School of Social Work and Family Science at the University of Louisville. Her research focuses on adverse childhood experiences (ACEs) and its long-term effects in adulthood.

Lixia Zhang, PhD, is an assistant professor at the Raymond A. Kent School of Social Work and Family Science at the University of Louisville. Her research examines how adverse family environments shape individual health and well-being across the life course. She focuses particularly on the long-term consequences of adverse childhood experiences (ACEs), including their effects on psychological wellbeing, family relationships, and broader social outcomes.

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