***ACE and Opioid Use Landmarks – Study Notes
Abstract
Topic: Adverse childhood experiences (ACEs) and three landmarks of opioid use among people with opioid use disorder (OUD): age of opioid initiation, injection drug use (IDU), and lifetime overdose.
Design: Cross-sectional study of consecutive inpatients seeking detoxification at a single center (SSTAR, Fall River, MA) during May–December 2015.
Sample: n = 457 completed interviews; mean age 32.2 years; 71.3% male; 82.5% non-Hispanic White (abstract) with Table 1 reporting White 86.9% in the full sample.
ACE measure: 10-item Adverse Childhood Experience questionnaire; internal consistency in this sample:
\alpha = 0.79Key metrics collected: age of opioid initiation, last month IDU, lifetime overdose; ACE score (sum of 10 items).
Main findings (adjusted for age, gender, race/ethnicity):
ACE score is inversely related to age of opioid initiation:
b = -0.50,\quad 95\%\ CI [-0.70, -0.29],\ p < 0.001.Each additional ACE point increases the likelihood of recent IDU by:
OR = 1.11,\quad 95\%\ CI [1.02, 1.20],\quad p = 0.014.Each additional ACE point increases the odds of lifetime overdose by:
OR = 1.10,\quad 95\%\ CI [1.02, 1.20],\quad p = 0.015.
Additional details: an auxiliary analysis (n = 321) restricted to those initiating opioid use at age 18 or older showed a significant but attenuated association:
b = -0.31,\quad 95\%\ CI [-0.51, -0.11],\quad p = 0.003.nConclusion: Higher ACE exposure is associated with earlier opioid initiation, ongoing IDU, and overdose history in this detox-seeking OUD population; ACE screening could help identify high-risk subgroups.
Introduction
Background:
Opioid use disorder is a major US public health issue with rising morbidity and mortality, including overdoses that have increased dramatically.
ACEs are linked to the development of substance use disorders (SUDs) and various adult health problems; ACEs include abuse, neglect, and household dysfunction.
Prior studies show ACEs relate to earlier onset of drug use and to recent illicit drug use, including parenteral use and overdose risk.
The ACE questionnaire assesses 10 childhood adversities and has demonstrated dose–response relationships with multiple health and behavioral outcomes.
Rationale and aims:
In OUD, ACEs might correlate with three developmental milestones: age of opioid initiation, IDU, and lifetime overdose.
Study goals: test whether higher ACE scores are associated with earlier opioid initiation, recent IDU, and lifetime overdose in a detox population.
Definitions and context:
Age of opioid initiation: developmental milestone linked to later risk for dependence (literature: Anthony & Petronis, 1995; Baldwin et al., 2013; Chen et al., 2009; King & Chassin, 2007).
IDU: transition to injection heroin, with risks for HIV, HCV, and overdose.
ACE: ten-item index covering abuse, neglect, and household dysfunction; higher scores reflect greater childhood adversity.
Conceptual framework:
ACEs contribute to genetic, modeling, and environmental pathways affecting risk behaviors and health outcomes (e.g., parental substance use, mental health, poverty, and social disruption).
Possible neurobiological mechanisms include epigenetic changes and altered stress response, impacting cognitive, emotional, and behavioral development.
Methods
Design and setting:
Cross-sectional survey of consecutive patients admitted for inpatient opioid detoxification at SSTAR in Fall River, MA.
Recruitment window: May–December 2015.
Facility details: 38 beds, 24-hour medically supervised detoxification with evaluation and withdrawal management, followed by referral to outpatient treatment.
Participants:
Eligibility: age ≥ 18, English-speaking; approached within 24 hours of admission after withdrawal relief; informed consent approved by Butler Hospital IRB.
Enrollment: 530 approached; 42 refused or were missed; 488 consented; 457 completed the interview.
Measures:
Demographics: age, gender, race, ethnicity.
Opioid use landmarks:
Age of opioid initiation.
Past 30-day IDU (yes/no).
Lifetime history of overdose (yes/no).
ACEs: ten-item ACE questionnaire (Felitti et al., 1998).
ACE score = sum of 10 yes/no items; internal consistency in this sample: \alpha = 0.79.
Analytic approach:
Descriptive statistics to characterize the sample.
Between-sex comparisons: t-tests for means, chi-square tests for counts.
Multivariate linear regression to estimate the association between ACE score and age of opioid initiation, adjusting for age, gender, and race/ethnicity; statistical tests use heteroskedastic robust (Huber-White) SEs.
Multivariate logistic regression to estimate the association of ACEs with recent IDU and lifetime overdose.
Auxiliary analysis for the subset initiating opioids at age ≥18 (n = 321).
Ethics:
Informed consent and IRB approval were obtained; the study was conducted in accordance with ethical guidelines.
Descriptive statistics and ACE distribution
Sample demographics (n = 457):
Mean age: \text{Age} = 32.2\pm 8.64\text{ years}; range 18–64.
Sex: 71.3\% male (n = 326).
Hispanic ethnicity: 8.8\%.
Race: White 86.9\%, Black 5.5\%, Other 7.7\%.
Age at opioid initiation: mean 21.7\pm 7.12 years; range 12–54; median 20.
ACE score: mean 3.64\pm 2.75; median 3.0.
Past 30-day IDU: 68.7\%.
Lifetime overdose: 39.0\%.
ACE distribution (mean, spread):
Mean ACE score: 3.64\pm 2.75; median 3.0; distribution across categories:
0 ACEs: 14.7\%
1–3 ACEs: 36.8\%
4+ ACEs: 48.6\%
Item-level ACE endorsements (top items):
Parents separated/divorced: 59.5\% endorsed.
Living with a problem drinker or someone who used drugs: 51.4\%.
An adult in the household who often swore at or humiliated them: 47.5\%.
Sex differences in ACE items (select findings):
Females showed higher endorsement for several items overall and had higher mean ACE scores than males:
Females: 4.39\pm 2.92; Males: 3.33\pm 2.63; p < 0.001.
Item 3 (sexual touching/being touched in a sexual way) and other sexual and emotional abuse items showed sex differences in endorsement.
ACE and age of initiation context:
ACE score is associated with earlier age of opioid initiation in adjusted analyses.
Adjusted associations with three landmarks (Table 3)
Age of initiating opioids (continuous outcome, OLS):
Age of initiation increases with participant age: \text{Years Age} = 0.40\,***\ (p<0.001), 95% CI [0.30, 0.50].
Gender (Male vs Female) effect: -2.14\,**\ (p<0.001); non-Hispanic White: -1.96\,\ (p<0.05).
ACE effect: b = -0.50\,***\ (95\%\ CI [-0.70, -0.29])\, (p<0.001).
Recent injection drug use (binary outcome, logistic):
Intercept-adjusted odds ratios for ACE: OR = 1.11\,**\ (95\% CI [1.02, 1.20])\, (p<0.01).
Age, gender, and race/ethnicity effects also reported in the table (see notes above for direction).
Lifetime history of overdose (binary outcome, logistic):
ACE effect: OR = 1.10\,**\ (95\% CI [1.02, 1.20])\, (p<0.01).
Other covariates also presented in the table.
Subgroup analysis (initiated at age ≥18; n = 321):
ACE effect on age of initiation remains significant but attenuated: b = -0.31\,**\ (95\% CI [-0.51, -0.11], p = 0.003).
Overall interpretation of Table 3:
After adjusting for demographic variables, higher ACE scores are associated with earlier opioid initiation, and higher odds of recent IDU and lifetime overdose among people entering detox.
Discussion
Main findings:
In a detox-seeking OUD sample, ACEs show a graded, dose–response association with three key risk markers: earlier opioid initiation, current IDU, and lifetime overdose.
The observed relationships align with prior research linking ACEs to illicit drug use and to more severe patterns of substance use.
Mechanisms and interpretation:
ACEs may influence opioid use trajectory via multiple pathways:
Genetic and familial risk (heritable factors related to substance use and mental health).
Environmental pathways (modeling of drug use, chronic stress, poverty, family dysfunction).
Neurodevelopmental and neurobiological changes (stress-response systems, memory, attention, emotion regulation) that affect coping and learning, potentially increasing the likelihood of early initiation, escalation to IDU, and overdose risk.
The literature suggests cumulative effects of adversity on health risk behaviors across a range of outcomes; the current study extends this to specific opioid-use milestones.
Demographic patterns and implications:
Men tended to have earlier initiation and higher rates of recent IDU/overdose, whereas women reported more ACEs overall and higher rates of childhood sexual abuse, consistent with prior research.
Given rising opioid-related harms among women, further research should clarify ACE–opioid links in women and tailor prevention and treatment approaches accordingly.
Strengths and consistency with prior work:
Large sample within a detox setting; use of a validated ACE measure; robust adjustment for key sociodemographic factors.
Findings echo dose–response patterns seen in community samples and other substance-use contexts.
Limitations (see below) and cautions:
The cross-sectional design precludes causal inferences about ACEs causing earlier initiation or overdose risk.
Retrospective recall of childhood adversity may introduce misclassification; interviewer-administered surveys may incur social desirability bias.
Single-site, predominantly White and male sample; results may not generalize to other regions, treatment modalities, or more diverse populations.
The ACE measure covers a subset of childhood challenges; other unmeasured adversities may contribute to risk.
Although most participants were detoxing from heroin, age of first heroin use or first opioid injection was not assessed; timing of ACEs relative to milestones could vary.
Practical implications:
ACE screening in clinical settings could help identify opioid users at higher risk for early initiation, ongoing IDU, and overdose, enabling targeted prevention and intervention.
ACE-informed approaches could be integrated into community-based prevention and early intervention programs for adolescents.
Future directions:
Longitudinal studies to establish causal pathways linking ACEs to opioid-use trajectories.
Exploration of sex- and gender-specific mechanisms and interventions.
Limitations
Key limitations enumerated by authors:
Retrospective recall of childhood adversity may be fallible.
In-person interviews could induce response bias or underreporting of ACEs and drug-use behaviors.
Sample drawn from a single detoxification program in the northeastern United States; predominantly White and male; may limit generalizability to other regions, treatment settings, or female-dominated samples.
ACE measurement captures 10 predetermined experiences and may miss other relevant adversities.
The study did not collect data on age of first heroin use or first opioid injection; timing of ACEs relative to milestones may differ.
Temporal ordering between ACEs and milestones cannot be definitively established in a cross-sectional design.
Conclusions and implications
Core conclusion:
There is a significant, additive (graded) negative impact of multiple adverse childhood experiences on three opioid-related milestones (earlier initiation, current IDU, lifetime overdose) in this detox-in patient population.
Implications for practice and policy:
ACE screening could be incorporated into assessments for individuals with OUD to identify those at heightened risk for injection and overdose.
Early prevention strategies could leverage ACE data to identify adolescents at risk for early opioid initiation and implement targeted interventions.
Screening and addressing ACEs in treatment settings may improve risk stratification and inform integrated care approaches.
Highlights
Adverse Childhood Experiences (ACE) were associated with earlier age of initiating opioid use.
ACE were associated with recent injection drug use and lifetime overdose.
About half of respondents experienced four or more of the ten assessed ACE.
Tables and key numbers to remember
Sample size: n = 457.
Demographics (from Table 1):
Age: 32.2\pm 8.64 years; range 18–64.
Sex: 71.3\% male (n = 326).
Race: White 86.9\%; Black 5.5\%; Other 7.7\%.
Age at opioid initiation: 21.7\pm 7.12 years; range 12–54; median 20.
ACE score: 3.64\pm 2.75; median 3.0.
Past 30-day IDU: 68.7\%.
Lifetime overdose: 39.0\%.
ACE distribution (mean, spread):
Mean ACE score: 3.64\pm 2.75; median 3.0; 0 ACEs = 14.7%; 1–3 ACEs = 36.8%; 4+ ACEs = 48.6%.
Key adjusted associations (Table 3):
Age of opioid initiation (continuous):
\text{ACE effect} = b = -0.50\,***\ (95\% CI [-0.70, -0.29]).Recent IDU (OR):
OR_{ACE} = 1.11\,**\ (95\% CI [1.02, 1.20]).Lifetime overdose (OR):
OR_{ACE} = 1.10\,**\ (95\ CI [1.02, 1.20]).
Subgroup (initiated ≥18 years):
ACE effect on initiation: b = -0.31\,**\ (95\ CI [-0.51, -0.11], p = 0.003).
Quick takeaway for exam prep
ACEs show a dose–response relationship with three opioid-use milestones in a detox-seeking sample:
1) Earlier initiation of opioid use, 2) Higher likelihood of current IDU, and 3) Greater odds of lifetime overdose.Each additional ACE increases risk for IDU and overdose by about 10–11%; increases the speed of progression to opioid use (earlier initiation) by a small but meaningful amount.
Screening for ACEs in clinical and community settings can help identify high-risk individuals and guide targeted prevention and treatment efforts.
IDU (Injection Drug Use)
: This signifies the transition to injecting heroin or other opioids intravenously. This route of administration carries substantially higher risks, including the transmission of blood-borne infections such as HIV and Hepatitis C Virus (HCV), as well as an increased likelihood of overdose. It represents a more severe and dangerous pattern of drug use.
ACE (Adverse Childhood Experience)
: This refers to a ten-item index that quantifies exposure to various forms of childhood adversity, including different types of abuse (emotional, physical, sexual), neglect (emotional, physical), and household dysfunction (e.g., parental mental illness, substance abuse, divorce, incarcerated household member, domestic violence). A higher score on this index reflects a greater cumulative burden of childhood adversity.
Conceptual framework
: The theoretical framework proposes that ACEs contribute to the development of risk behaviors and negative health outcomes through a combination of genetic, modeling, and environmental pathways. These pathways can include factors such as inherited predispositions to substance use or mental health issues, observing drug use within the family or community, and exposure to chronic stressors, poverty, and social disruption.
: Additionally, possible neurobiological mechanisms are implicated, including epigenetic changes (alterations in gene expression without changes to the underlying DNA sequence) and an altered stress response system. These biological changes can profoundly impact cognitive, emotional, and behavioral development, potentially leading to maladaptive coping strategies and increasing the vulnerability to early substance initiation, escalation to IDU, and higher overdose risk.
Methods
Design and setting
: This study employed a cross-sectional survey design, meaning data was collected at a single point in time from each participant. The research was conducted on consecutive patients who were admitted for inpatient opioid detoxification services at SSTAR (Stanley Street Treatment and Resources), a facility located in Fall River, Massachusetts.
: The data collection period spanned eight months, from May to December 2015.
: SSTAR is equipped with 38 inpatient beds and provides 24-hour medically supervised detoxification services. This includes comprehensive evaluation, management of withdrawal symptoms, and subsequent referral to appropriate outpatient treatment programs upon discharge.
Participants
: Eligibility criteria for participants included being at least 18 years of age and being English-speaking. Potential participants were approached within 24 hours of their admission, after their acute withdrawal symptoms had been sufficiently managed to ensure comfort and capacity for informed consent.
: All participants provided informed consent, which was approved by the Butler Hospital Institutional Review Board (IRB), ensuring ethical conduct of the study.
: A total of 530 individuals were approached for participation. Of these, 42 either refused to participate or were missed during the recruitment window. 488 individuals consented to participate, and 457 ultimately completed the full interview, forming the final sample size for the study.
Measures
: Demographics: Basic demographic information collected included the participant's age, self-identified gender, race, and ethnicity.
: Opioid use landmarks: Specific indicators of opioid use history were gathered:
Age of opioid initiation: The age at which the participant reported their first use of an opioid.
Past 30-day IDU: A dichotomous (yes/no) question assessing whether the participant had engaged in injection drug use within the 30 days prior to admission.
Lifetime history of overdose: A dichotomous (yes/no) question inquiring if the participant had ever experienced an opioid overdose in their lifetime.
: ACEs: The study utilized the well-established ten-item Adverse Childhood Experience questionnaire, originally developed by Felitti et al. (1998).ACE score: This was calculated as the sum of 'yes' responses to the 10 items, where each 'yes' counts as one point. The internal consistency of this measure within the study's sample was assessed and found to be good, with a Cronbach's alpha of \alpha = 0.79. This indicates that the items on the questionnaire consistently measure the same underlying construct of childhood adversity.
Analytic approach
: Descriptive statistics: Initially, descriptive statistics (e.g., means, standard deviations, frequencies, percentages) were used to characterize the overall sample in terms of demographics and key study variables.
: Between-sex comparisons: To identify potential differences between male and female participants, independent t-tests were employed for comparing means (e.g., age, ACE scores), and chi-square tests were used for comparing categorical variables (e.g., prevalence of IDU, overdose history).
: Multivariate linear regression: This statistical method was utilized to estimate the association between the ACE score (independent variable) and the age of opioid initiation (continuous dependent variable). The models were adjusted for potential confounders including participant’s age, gender, and race/ethnicity to isolate the specific effect of ACEs. Statistical tests for regression coefficients used heteroskedastic robust (Huber-White) standard errors to account for potential violations of homoscedasticity assumptions.
: Multivariate logistic regression: This approach was used for binary outcomes. Separate logistic regression models were conducted to estimate the association of ACE scores with recent IDU (yes/no) and with lifetime overdose (yes/no). These models also controlled for participant age, gender, and race/ethnicity.
: Auxiliary analysis: A supplementary analysis was performed on a subset of the sample (n = 321) comprising only those individuals who initiated opioid use at or after the age of 18 years. This aimed to examine if the association between ACEs and age of initiation persisted and how its magnitude might differ in this specific subgroup.
Ethics
: Prior to data collection, comprehensive informed consent was obtained from all participants, ensuring they understood the study's purpose, procedures, risks, and benefits. The study protocol, including consent procedures, was reviewed and approved by the Butler Hospital Institutional Review Board (IRB), affirming that all research activities adhered to established ethical guidelines and protections for human subjects.
Yes, this article will likely be helpful for your project, though not in providing direct intervention strategies for caregivers. Instead, it offers crucial foundational knowledge and empirical justification for the importance of your project.
Here’s how it can be relevant:
Justifying the Problem: Your project addresses the long-term effects of trauma on children due to the opioid crisis. This article provides strong empirical evidence, demonstrating a clear association between Adverse Childhood Experiences (ACEs)—which are a form of childhood trauma—and specific, severe opioid use milestones in adulthood (earlier initiation, injection drug use, and overdose). This connection powerfully underscores why mitigating these early traumas is critical, as it directly impacts the future vulnerability to substance use disorders.
Understanding the Impact of Trauma (ACEs): The article deeply explores ACEs as a quantifiable measure of childhood adversity. It explains that higher ACE exposure is associated with poorer outcomes related to opioid use. This can inform the educational component of your program by providing caregivers with a robust, evidence-based understanding of the profound and lasting effects of the trauma their children have experienced.
Context of the Opioid Crisis: The article is explicitly set within the context of opioid use disorder, aligning perfectly with the focus of your project on children separated from parents due to the opioid crisis. It helps highlight the intergenerational cycle of trauma and addiction.
Identifying High-Risk Individuals: The article's conclusion that "ACE screening could help identify high-risk subgroups" for severe opioid-related outcomes indirectly supports the need for early intervention and support for children, as they are a population likely to have experienced high ACEs. Your program for caregivers can be seen as an essential part of such early intervention.
While this article doesn't give you a blueprint for a caregiver educational program or support group, it provides the significant empirical and conceptual background necessary to strengthen the rationale and understanding behind your intervention.