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. Author manuscript; available in PMC: 2023 Nov 23.
Published in final edited form as: J Am Geriatr Soc. 2019 Jun 17;67(10):2085–2093. doi: 10.1111/jgs.16032

Associations of Adverse Childhood Experiences with Past-year DSM-5 Psychiatric and Substance Use Disorders in Older Adults

T Greg Rhee 1,2,3,4, Lisa C Barry 4,5, George A Kuchel 5, David C Steffens 5,6, Samuel T Wilkinson 2,3
PMCID: PMC10666528  NIHMSID: NIHMS1943253  PMID: 31206597

Abstract

Objectives:

To examine prevalence of adverse childhood experiences (ACEs) and the associations of ACEs with psychiatric and substance use disorders among older adults in the US.

Design:

Cross-sectional analysis of the 2012-2013 National Epidemiological Survey on Alcohol and Related Conditions Wave III (NESARC-III).

Setting:

Nationally representative drug-related health interview survey in the US.

Participants:

Survey respondents aged 65 or older (n=5,806 unweighted).

Measurements:

ACEs, the key independent variable, were assessed using validated measures. Outcome variables consisted of past-year psychiatric disorders (e.g., major depressive disorder and generalized anxiety disorder) and substance use disorders (e.g., alcohol use disorder) using DSM-5 criteria. We estimated national prevalence of ACEs in older adults and used multivariable-adjusted logistic regression analyses to assess the association between ACEs and the outcomes after adjusting for socio-demographics and clinical co-morbidities.

Results:

Overall, 35.9% of older adults, representative of 14.8 million older adults nationwide, reported some form of ACEs. The most common types were parental psychopathology (20.3%), other traumatic events (14.0%) and physical/psychological abuse (8.4%). Having experienced any ACEs was associated with higher odds of having a past-year psychiatric disorder (adjusted odds ratio [aOR]=2.11; 95% confidence intervals [CI]=1.74, 2.56). Similar results were found for substance use disorders (p<0.01).

Conclusion:

ACEs are linked to an increased risk for past-year psychiatric and substance use disorders in older adults. ACEs may have long-term effects on older adults’ mental well-being. While further research is needed, preventing ACEs may lead to large improvements in public mental health that persist well into older age.

Keywords: adverse childhood experiences, psychiatric disorder, substance use disorder, mental health, older adults

INTRODUCTION

About 15% of adults aged 60 and over suffer from a mental disorder,1 with the most common mental health conditions including anxiety, severe cognitive impairment, and other mood disorders (e.g., depression and bipolar disorders).2 Numerous epidemiologic studies have identified risk factors and protective factors for late-life mental disorders. For example, complex interactions of genetic vulnerabilities (e.g., heritability), cognitive dysfunction and coping skills, age-related neurobiological changes, medical morbidities, and/or other stressful events (e.g., bereavement and social isolation) can be risk factors for mental disorders.3–6 On the other hand, a higher educational level, better socio-economic status, engagement of other psycho-social activities and physical activities are often referred to as protective factors.7–9

Yet, few studies have examined the association of adverse childhood experiences (ACEs) with mental disorders in older adults. ACEs include a wide range of traumatic events (e.g., neglect, sexual or physical abuse, domestic violence, and parental psychopathology) that one may experience in his/her childhood. According to a lifespan developmental theory,10–12 ACEs are considered a strong predictor for disrupted neuro-development, cognitive, emotional or social impairment, risky health behaviors, chronic medical and psychiatric conditions, and/or premature mortality.13

In particular, earlier studies show that exposure to ACEs is linked to the risk of depressive disorders and other mental health conditions.14–19 However, these studies have several limitations. First, they often excluded older adults, as they focused on pediatric, adolescent, or young adult populations.16,19–22 Second, the definition of mental disorders was not based on clinical diagnoses, but instead relied on self-reported depressive symptoms or other screening questionnaires.14,15,22 Third, some studies were conducted in a local clinical setting (e.g., primary care or inpatient) or conducted outside the US, and thus have limited generalizability across the country.14,15 Fourth, the definitions of mental disorders have evolved over time, and several changes were made between fourth and fifth editions of Diagnostic and Statistical Manuel of Mental Disorder (DSM).23,24 While there is only one study17 that used DSM-5 criteria, this study did not consider past-year psychiatric or substance use disorders, nor did it take any medical and behavioral co-morbidities into consideration as key covariates. Lastly, many of these studies are outdated as they used data prior to 2008.14–16,21

To our knowledge, this is the first study to investigate prevalence of ACEs and associations of ACEs with past-year DSM-5 psychiatric and substance use disorders among older adults in the US. Addressing potential limitations from previous studies, we sought to examine the following questions in this study: 1) What is the prevalence of ACEs in older adults? 2) Are socio-demographic characteristics, and medical and behavioral co-morbidities differed by ACEs exposure among older adults? 3) Do ACEs represent factors associated with diagnosing past-year psychiatric and substance use disorders in older adults? And finally, 4) Which socio-demographic factors and medical and behavioral co-morbidities are independently associated with a higher likelihood of diagnosing past-year psychiatric or substance use disorders, net of ACEs, in older adults? Based on prior literature, we hypothesized that older adults with ACEs are more likely to have past-year psychiatric or substance use disorders than those without ACEs. Understanding patterns of ACEs and the relationship of ACEs with past-year psychiatric and substance use disorders may help guide both healthcare providers and policymakers to address critical roles of ACEs in treating older adults with psychiatric or substance use disorders.

METHODS

Data source and study sample

We used restricted data from the National Epidemiologic Survey on Alcohol and Related Conditions Wave III (NESARC-III), which has been sponsored by the National Institute on Alcohol Abuse and Alcoholism (NIAAA).25 NESARC-III, a nationally representative cross-sectional survey, was conducted from April 2012 to June 2013, and collected comprehensive information about physical and mental health diagnoses and drug-related services use among non-institutionalized civilian adults aged 18 or older, with a focus on alcohol and other substance use disorders.26 We limited our sample to adults aged 65 or older (n=5,806 unweighted). The overall survey response rate of NESARC-III was 60.1%.26 Our study was exempted from review by the Institutional Review Board (#2000022543) at Yale School of Medicine as we used de-identified secondary data. Further details of the survey, including study descriptions, questionnaires, sampling methodology, and other technical reports are available on the NESARC-III website.25

Measures

Adverse childhood experiences (ACEs).

NESARC-III assessed survey respondents’ ACEs that they experienced before the age of 18 years, using validated questionnaire forms from the Childhood Trauma Questionnaire (CTQ),27,28 the Conflict Tactics (CT) Scale,29 childhood sexual abuse questionnaire,30 and CDC-Kaiser ACE study.31,32 NESARC-III adopted these questionnaire items for the assessment of ACEs, and the validated measures are summarized in Supplementary Table S1.17,33–35 We included six major categories of ACEs: 1) neglect; 2) physical/psychological abuse; 3) sexual abuse; 4) witnessing domestic violence; 5) parental psychopathology, and 6) other traumatic events. In the first four categories, survey participants were asked to rate the frequency of such events on a 5-point scale (never, almost never, sometimes, fairly often, and very often). We constructed binary variables for each of these categories where ‘yes’ (or 1) = fairly often or very often and ‘no’ (or 0) = otherwise for neglect and physical/psychological abuse, and ‘yes’=sometimes, fairly often, or very often, and ‘no’=otherwise for sexual abuse and domestic violence. Participants were also asked (yes or no) if they had experienced parental psychopathology (e.g., parental illicit drug problem) and other traumatic events (e.g., parent’s suicide). Thus, we created binary variables for these categories by coding 1=yes to any and 0=otherwise. Finally, based on these six category variables, we constructed a binary variable for having any ACEs exposure, where 1=yes to any and 0=no to all. We created these measures based on previous studies.27–32

Psychiatric and substance use disorders.

The Alcohol Use Disorder and Associated Disabilities Interview Schedule-5 (AUDADIS-5)36 was used to capture past-year mental disorders, using criteria based on the Diagnostic and Statistical Manual of Mental Disorder, fifth edition (DSM-5). Past-year psychiatric disorders (yes or no)37,38 included: major depressive disorder, dysthymia, generalized anxiety disorder, post-traumatic stress disorder, panic disorder, and bipolar 1 disorder. Past-year substance use disorders (yes or no)37,38 included: alcohol use disorder, tobacco use disorder, and any illicit drug use disorder (i.e., sedative use disorder, cannabis use disorder, opioid use disorder, cocaine use disorder, stimulant use disorder, hallucinogen use disorder, heroin use disorder, inhalant/solvent use disorder, or club drug use disorder).

Socio-demographic covariates.

We included the following socio-demographic variables:37,38 age (65-74, 75-84, or ≥85), sex, race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, or other); marital status (married, never married, or other); family income (< $20,000, $20,000-$39,999, or ≥ $40,000); employment (%); education (< high school, high school or equivalent, some college, or ≥ bachelor’s degree); insurance coverage (Medicare, Medicaid, or uninsured); disability income support (%); geographic region (Northeast, Midwest, South, or West); and urbanity (urban or rural).

Medical co-morbidities.

We also considered medical co-morbidities in the past 12 months as covariates, since they may be related to psychiatric or substance use disorders. Respondents were asked whether or not they had medical conditions (e.g., arthritis, diabetes, and insomnia) (yes or no) in the past 12 months. Among those who responded positively, they were further asked, “Did a doctor or health professional tell you had you had [a medical condition]?” Using these two questionnaire items for each medical condition, we created a series of chronic conditions in the past 12 months (see Table 2 for a comprehensive list).39 For obesity, we calculated a body mass index (BMI), with BMI ≥30.0 considered obese.39 Using these variables, we further constructed a count variable representing the number of multiple chronic conditions (0, 1, 2, 3, or ≥4). In addition, survey participants were asked if they had ever (in their lifetime) attempted suicide (yes or no).

Table 2.

Clinical and behavioral health characteristics (column %) of older adults by adverse childhood experiences (ACEs), NESARC-III

With ACEs Without ACEs Total Bivariate odds ratio
Sample size
 Unweighted sample 2,114 3,692 5,806
 Weighted population 14,824,690 26,527,881 41,352,571
 (row %) (35.9%) (64.2%) 100.0%)
Past-year psychiatric disorder
 Major depressive disorder 8.5 3.7 5.4 2.37 (1.83, 3.09)***
 Dysthymia 2.6 1.3 1.8 2.00 (1.30, 3.09)**
 Generalized anxiety disorder 4.8 3.1 3.7 1.58 (1.13, 2.22)**
 Post-traumatic stress disorder 4.3 1.0 2.2 4.47 (2.88, 6.95)***
 Panic disorder 1.5 0.5 0.9 2.94 (1.45, 5.98)**
 Bipolar I disorder 0.8 0.2 0.4 3.53 (1.13, 10.96)*
Past-year substance use disorder
 Tobacco use disorder 11.4 6.8 8.5 1.76 (1.42, 2.19)***
 Alcohol use disorder 3.4 1.8 2.4 1.93 (1.26, 2.95)**
 Any illicit drug use disordera) 1.2 0.5 0.8 2.32 (1.23, 4.40)*
Chronic medical condition
 Hypertension 26.3 54.6 55.2 1.07 (0.95, 1.21)
 Arthritis 50.8 45.0 47.1 1.26 (1.09, 1.45)**
 Dyslipidemiab) 45.2 40.9 42.4 1.19 (1.05, 1.35)**
 Obesityc) 30.1 28.0 28.8 1.11 (0.94, 1.27)
 Diabetes 22.4 20.3 21.0 1.14 (1.00, 1.29)
 Cancerd) 10.7 12.9 12.1 0.81 (0.68, 0.98)*
 Insomnia 13.4 9.1 10.7 1.55 (1.28, 1.87)***
 Pulmonary diseasese) 12.6 8.5 10.0 1.55 (1.26, 1.91)***
 Tachycardia 10.4 7.9 8.8 1.35 (1.11, 1.64)**
 Other cardiac diseasesf) 13.6 14.8 14.4 0.91 (0.73, 1.13)
 Angina 7.2 5.9 6.3 1.24 (0.96, 1.61)
 Fibromyalgia 3.6 2.1 2.6 1.76 (1.22, 2.56)**
 Peptic ulcer disease 3.5 2.7 3.0 1.31 (0.95, 1.79)
 Liver diseasesg) 1.8 1.0 1.3 1.86 (1.10, 3.13)*
 Sexually transmitted diseasesh) 0.8 0.3 0.5 3.04 (1.25, 7.44)*
Lifetime suicide attempt 4.4 0.8 2.1 5.86 (3.50, 9.83)***
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Note:

*

<0.05;

**

<0.01;

***

<0.001.

a)

includes sedative use disorder, cannabis use disorder, opioid use disorder, cocaine use disorder, stimulant use disorder, hallucinogen use disorder, heroin use disorder, inhalant/solvent use disorder, or club drug use disorder;

b)

includes high cholesterol or high triglycerides;

c)

indicates ≥30.0 of body-mass index;

d)

includes liver cancer, breast cancer, cancer of the mouth, tongue, throat or esophagus, or any other cancer;

e)

includes lung problems like chronic bronchitis, emphysema, pneumonia or influenza;

f)

includes heart attack or myocardial infarction, or other form of heart disease;

g)

includes cirrhosis of the liver or any other form of liver disease; and

h)

includes sexually transmitted/venereal disease or ever tested positive for HIV or AIDS.

Data analysis

We estimated the prevalence of ACEs and their sub-types in US older adults, and then used a weight-corrected Pearson’s chi-squared statistic to compare the socio-demographic characteristics between older adults with and without ACEs. We also compared differences in medical, and psychiatric or behavioral co-morbidities by ACEs status using bivariate logistic regression. A series of multivariable-adjusted logistic regression analyses were conducted to determine if having experienced the ACEs was associated with the outcomes of interest (i.e., psychiatric disorders and substance use disorders), as well as socio-demographic and clinical factors independently associated with these outcomes. We further conducted stratified analyses by major depressive disorder, dysthymia, generalized anxiety disorder, and post-traumatic disorder. We did not conduct multivariable-adjusted stratified analyses for panic disorder, bipolar 1 disorder, and any illicit drug use disorder because sample sizes for these conditions were insufficient. A p-value <0.05 was used to indicate statistical significance for all comparisons, and Stata MP/6-Core 15.1 was used for all analyses.40 The svy and related commands in Stata were used to account for the complex survey sampling design of the NESARC-III (e.g., unequal probability of selection, clustering and stratification).26

RESULTS

Prevalence of ACEs

A total of 35.9% of older adults, representative of 14.8 million older adults nationwide, reported that they had some form of ACEs (See Figure 1). The three most common types of ACEs were parental psychopathology (20.3%), other traumatic events (14.0%), and physical or psychological abuse (8.4%). There was no gender difference in reporting ACEs, except for sexual abuse; 4.9% of females reported that they experienced sexual abuse as compared with 1.6% of males (p<0.001). Among older adults who reported having experienced ACEs, 57.5% had one form of ACEs, 24.6% had two forms of ACEs, and 18.0% experienced three or more types of ACEs.

Figure 1.

Figure 1.

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Prevalence of adverse childhood experiences (ACEs) in older adults by ACE type, NESARC-III.

Note: Bars represent 95% confidence intervals.

Socio-demographic characteristics by ACEs

Table 1 presents socio-demographic characteristics of the sample by ACEs status. The majority of our sample were aged 65-74 (59.4%), female (55.8%), non-Hispanic white (80.1%), currently married (57.6%), and covered by Medicare (91.0%). We found significant different distributions in terms of age, race/ethnicity, education, and insurance coverage. Older adults with ACEs were more likely to be age 65-74 (66.8% versus 55.3%) (p<0.001), non-Hispanic black racial group (8.7% vs. 7.6%) (p=0.040), to report receiving disability income support (14.9% versus 11.5%) (p=0.001), and were less likely to be uninsured (1.1% versus 2.0%) (p=0.015).

Table 1.

Selected socio-demographic characteristics (column %) of older adults by adverse childhood experiences (ACEs), NESARC-III.

With ACEs Without ACEs Total P-value
Sample size
 Unweighted sample 2,114 3,692 5,806
 Weighted population 14,824,690 26,527,881 41,352,571
 (row %) (35.9%) (64.2%) (100.0%)
Age
 65-74 66.8 55.3 59.4 <0.001
 75-84 26.7 33.7 31.2
 85+ 6.6 11.0 9.4
Gender
 Male 43.6 44.5 44.2 0.547
 Female 56.4 55.5 55.8
Race/ethnicity
 Non-Hispanic white 80.8 79.8 80.1 0.006
 Non-Hispanic black 8.7 7.6 8.0
 Hispanic 7.0 7.1 7.1
 Othera) 3.5 5.6 4.8
Marital status
 Married 57.2 57.8 57.6 0.879
 Never married 3.3 3.4 3.4
 Otherb) 39.5 38.8 39.0
Family income
 <$20,000 27.0 25.9 26.3 0.643
 $20,000 - $39,999 29.6 29.6 29.6
 ≥$40,000 43.3 44.5 44.1
Employment
 No 74.2 75.1 74.8 0.508
 Yes 25.8 24.9 25.3
Education
 <High school 20.2 17.5 18.5 0.011
 High school or equivalent 27.6 29.6 28.9
 Some college 27.7 24.8 25.9
 ≥Bachelor’s degree 24.5 28.0 26.8
Insurance coveragec)
 Medicare (%) 91.6 90.6 91.0 0.313
 Medicaid (%) 9.9 9.3 9.5 0.451
 Uninsured (%) 1.1 2.0 1.7 0.015
Disability income support (%) 14.9 11.5 12.7 0.001
Region
 Northeast 17.9 19.7 19.1 0.197
 Midwest 21.4 22.1 21.9
 South 37.2 37.7 37.5
 West 23.5 20.5 21.6
Urbanity
 Rural 25.4 28.1 27.1 0.072
 Urban 74.7 71.9 72.9
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Note:

a)

includes two or more racial/ethnic groups;

b)

includes divorced, separated, widowed, partnered, or other; and

c)

each insurance type has a response of yes or no.

Medical and psychiatric/behavioral co-morbidities by ACEs

Table 2 presents bivariate analyses of medical and behavioral co-morbidities by ACEs status in US older adults. Those who experienced ACEs were more than twice as likely to have past-year psychiatric disorder diagnoses, with the exception of generalized anxiety disorder (bivariate odds ratio=1.58; 95% confidence intervals [CI]=1.13, 2.22). Having experienced any ACEs was also positively associated with past-year substance use disorders. Having experienced any ACEs was associated with greater odds of several chronic medical conditions, including: pulmonary diseases (p<0.001), insomnia (p<0.001), arthritis (p<0.01), dyslipidemia (p<0.01), fibromyalgia (p<0.01), cancer (p<0.05), liver diseases (p<0.05), and sexually transmitted diseases (p<0.05), respectively. Finally, having experienced ACEs was positively associated with lifetime suicide attempt (bivariate odds ratio=5.86; 95% CI=3.50, 9.83).

Associations of ACEs with psychiatric and substance use disorders

Table 3 presents the results from the multivariable-adjusted analyses for the associations between ACEs and each outcome. Having experienced ACEs was associated with a higher likelihood of a past-year psychiatric disorder diagnosis (adjusted odds ratio [aOR]=2.11; 95% CI=1.74, 2.56), a past-year alcohol use disorder diagnosis (aOR=1.76; 95% CI=1.18, 2.63), and a past-year tobacco use disorder diagnosis (aOR=1.45; 95% CI=1.17, 1.81). Factors that independently increased the likelihood of a past-year psychiatric disorder diagnosis included: being female (p<0.001), marital status of other than married or never married (e.g., divorced, separated, or widowed) (p<0.001), having three or more chronic medical conditions (p<0.01), and history of life-time suicide attempt (p<0.001). Increasing age was associated with a lower likelihood of past-year psychiatric disorder diagnoses. Socio-demographic factors associated with a higher likelihood of past-year alcohol use disorder diagnosis were an educational level of bachelor’s degree or higher (p<0.05) and those living in urban areas (p<0.05). On the other hand, being older (p<0.01) and being female (p<0.01) were associated with a lower likelihood of having a past-year alcohol use disorder. Similar patterns were found in tobacco use disorder.

Table 3.

Multivariable-adjusted analysis for associations of adverse childhood experiences (ACEs) with past-year DSM-5 psychiatric disorder and substance use disorder in older adults, NESARC-III.

Psychiatric disorder Substance use disorder
Alcohol use disorder Tobacco use disorder
Reference group in a parenthesis. aOR (95% CI) aOR (95% CI) aOR (95% CI)
ACEs (No)
 Yes 2.11 (1.74, 2.56)*** 1.76 (1.18, 2.63)** 1.45 (1.17, 1.81)**
Age (65-74)
 75-84 0.66 (0.52, 0.83)** 0.40 (0.23, 0.69)** 0.47 (0.35, 0.62)***
 85+ 0.56 (0.38, 0.85)** 0.12 (0.03, 0.51)** 0.15 (0.08, 0.28)***
Gender (Male)
 Female 1.35 (1.07, 1.71)* 0.26 (0.15, 0.45)*** 0.55 (0.44, 0.68)***
Race/ethnicity (non-Hispanic white)
 Non-Hispanic black 0.71 (0.52, 0.95)* 1.03 (0.51, 2.07) 0.93 (0.64, 1.35)
 Hispanic 0.86 (0.62, 1.18) 1.00 (0.49, 2.05) 0.42 (0.26, 0.68)***
 Othera) 1.11 (0.71, 1.74) 0.38 (0.09, 1.64) 0.77 (0.44, 1.35)
Marital status (Married)
 Never married 1.39 (0.89, 2.18) 0.60 (0.23, 1.59) 1.34 (0.81, 2.21)
 Otherb) 1.72 (1.35, 2.18)*** 1.66 (0.96, 2.88) 1.71 (1.29, 2.28)***
Family income (<$20,000)
 $20,000 - $39,999 1.22 (0.94, 1.57) 1.02 (0.54, 1.92) 1.00 (0.71, 1.41)
 ≥$40,000 0.88 (0.65, 1.20) 0.82 (0.39, 1.72) 0.59 (0.42, 0.82)**
Employment (No)
 Yes 0.91 (0.73, 1.13) 0.99 (0.59, 1.64) 1.23 (0.95, 1.60)
Education (<High school)
 High school or equivalent 0.89 (0.66, 1.19) 1.48 (0.80, 2.74) 0.64 (0.49, 0.83)**
 Some college 0.99 (0.72, 1.35) 1.48 (0.75, 2.94) 0.72 (0.50, 1.01)
 ≥Bachelor’s degree 0.98 (0.68, 1.40) 2.35 (1.15, 4.80)* 0.23 (0.15, 0.36)***
Insurance coverage (No)
 Yes 0.82 (0.29, 2.36) 2.61 (0.56, 12.12) 2.51 (1.00, 6.27)*
Disability income support (No)
 Yes 1.43 (1.11, 1.83)** 1.01 (0.57, 1.78) 1.43 (1.08, 1.90)*
Region (Northeast)
 Midwest 0.99 (0.74, 1.32) 1.57 (0.81, 3.04) 1.39 (0.98, 1.98)
 South 0.89 (0.70, 1.12) 1.35 (0.70, 2.62) 1.39 (1.02, 1.90)*
 West 1.28 (0.96, 1.70) 0.99 (0.49, 1.98) 0.91 (0.66, 1.25)
Urbanity (Rural)
 Urban 1.13 (0.94, 1.36) 2.08 (1.08, 3.98)* 1.10 (0.85, 1.43)
Multiple chronic conditions (None)
 1 0.87 (0.52, 1.46) 2.07 (0.82, 5.25) 0.95 (0.63, 1.42)
 2 1.55 (1.01, 2.36)* 1.64 (0.67, 4.00) 0.72 (0.47, 1.10)
 3 1.84 (1.24, 2.73)** 1.38 (0.54, 3.54) 0.83 (0.55, 1.23)
 ≥4 2.64 (1.77, 3.93)*** 1.53 (0.64, 3.68) 0.90 (0.61, 1.33)
Lifetime suicide attempt (No)
 Yes 4.00 (2.54, 6.31)*** 1.32 (0.56, 3.08) 2.16 (1.26, 3.70)**
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Note:

*

<0.05;

**

<0.01;

***

<0.001.

a)

includes two or more racial/ethnic groups; and

b)

includes divorced, separated, widowed, partnered, or other.

Table 4 presents results of the multivariable-adjusted analyses for associations between ACEs and specific past-year psychiatric disorders. Having experienced ACEs was no longer significantly associated with dysthymia or generalized anxiety disorder, although the relationships remain positive. Across all psychiatric disorder types, lifetime suicide attempt was consistently associated with an increased likelihood of psychiatric disorder diagnoses (p<0.001). Having four or more chronic conditions was also associated with an increased likelihood of psychiatric disorder diagnoses (p<0.05), with the exception of dysthymia.

Table 4.

Multivariable-adjusted analysis for associations of adverse childhood experiences (ACEs) with past-year DSM-5 psychiatric disorder by sub-type in older adults, NESARC-III.

Major depressive disorder Dysthymia Generalized anxiety disorder Post-traumatic stress disorder
Reference group in a parenthesis. aOR (95% CI) aOR (95% CI) aOR (95% CI) aOR (95% CI)
ACEs (No)
 Yes 1.87 (1.44, 2.44)*** 1.57 (0.94, 2.60) 1.21 (0.85, 1.71) 3.59 (2.27, 5.66)***
Age (65-74)
 75-84 0.72 (0.53, 0.98)* 0.97 (0.55, 1.69) 0.56 (0.38, 0.84)** 0.50 (0.28, 0.90)*
 85+ 0.46 (0.29, 0.75)** 0.44 (0.18, 1.08) 0.67 (0.33, 1.36) 0.50 (0.24, 1.04)
Gender (Male)
 Female 1.56 (1.17, 2.09)** 0.93 (0.53, 1.63) 1.60 (1.10, 2.32)* 0.85 (0.56, 1.31)
Race/ethnicity (non-Hispanic white)
 Non-Hispanic black 0.89 (0.59, 1.37) 0.72 (0.36, 1.46) 0.43 (0.24, 0.80)** 0.80 (0.43, 1.47)
 Hispanic 1.03 (0.65, 1.66) 0.72 (0.28, 1.85) 0.71 (0.40, 1.28) 0.96 (0.46, 2.00)
 Othera) 0.83 (0.45, 1.56) 2.17 (0.87, 5.38) 0.44 (0.20, 0.97)* 3.06 (1.42, 6.60)**
Marital status (Married)
 Never married 1.77 (0.90, 3.48) 2.62 (1.16, 5.93)* 0.78 (0.35, 1.72) 1.35 (0.54, 3.39)
 Otherb) 2.39 (1.69, 3.38)*** 2.06 (1.15, 3.70)* 1.30 (0.85, 1.97) 1.74 (1.08, 2.81)*
Family income (<$20,000)
 $20,000 - $39,999 1.02 (0.71, 1.47) 2.03 (1.18, 3.49)* 1.24 (0.82, 1.88) 1.19 (0.76, 1.85)
 ≥$40,000 0.80 (0.54, 1.19) 1.25 (0.64, 2.41) 0.75 (0.46, 1.21) 0.99 (0.52, 1.87)
Employment (No)
 Yes 1.16 (0.87, 1.55) 0.93 (0.50, 1.72) 0.81 (0.55, 1.19) 0.86 (0.52, 1.41)
Education (<High school)
 High school or equivalent 1.06 (0.73, 1.54) 0.80 (0.41, 1.54) 1.06 (0.63, 1.80) 0.50 (0.27, 0.90)*
 Some college 1.03 (0.71, 1.47) 0.97 (0.48, 1.95) 1.44 (0.83, 2.49) 0.80 (0.40, 1.60)
 ≥Bachelor’s degree 0.94 (0.58, 1.51) 0.78 (0.33, 1.81) 1.42 (0.79, 2.58) 0.62 (0.28, 1.37)
Insurance coverage (No)
 Yes 0.75 (0.22, 2.55) 0.37 (0.07, 1.91) 0.46 (0.11, 1.89) -c)
Disability income support (No)
 Yes 1.27 (0.94, 1.72) 1.43 (0.82, 2.50) 1.52 (0.93, 2.49) 1.57 (0.97, 2.52)
Region (Northeast)
 Midwest 0.99 (0.61, 1.62) 0.61 (0.27, 1.34) 1.23 (0.79, 1.92) 0.75 (0.36, 1.53)
 South 1.03 (0.68, 1.55) 0.73 (0.37, 1.45) 0.88 (0.55, 1.41) 1.07 (0.56, 2.03)
 West 1.65 (1.03, 2.63)* 1.33 (0.58, 3.01) 1.54 (0.98, 2.41) 0.79 (0.41, 1.51)
Urbanity (Rural)
 Urban 1.21 (0.83, 1.75) 1.22 (0.61, 2.43) 1.40 (0.95, 2.06) 0.86 (0.52, 1.41)
Multiple chronic conditions (None)
 1 0.84 (0.48, 1.46) 0.83 (0.26, 2.66) 0.77 (0.28, 2.14) 0.99 (0.35, 2.82)
 2 1.47 (0.85, 2.51) 0.69 (0.22, 2.17) 1.60 (0.70, 3.70) 1.90 (0.76, 4.76)
 3 1.75 (1.04, 2.95)* 1.41 (0.53, 3.72) 2.13 (0.90, 5.07) 2.21 (0.81, 6.00)
 ≥4 2.43 (1.47, 4.01)** 1.95 (0.86, 4.43) 2.65 (1.12, 6.23)* 3.77 (1.56, 9.09)**
Lifetime suicide attempt (No)
 Yes 4.06 (2.46, 6.72)*** 5.69 (2.40, 13.51)*** 3.78 (2.25, 6.34)*** 3.74 (1.77, 7.91)**
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Note:

*

<0.05;

**

<0.01;

***

<0.001.

a)

includes two or more racial/ethnic groups; and

b)

includes divorced, separated, widowed, partnered, or other; and

c)

was dropped due to a limited sample size.

DISCUSSION

This is the first study to investigate the associations of ACEs with past-year psychiatric and substance use disorders in older adults using a nationally representative sample. We found that more than one third of older adults reported having experienced some form of ACEs, although prevalence rates of ACE sub-types vary from 3.4% for sexual abuse to 20.3% for parental psychopathology. The overall rate (35.9%) reported in our study is lower than previous studies, which ranged from 46.5%19 to 51.7%17 among younger population groups. We, however, could not compare our findings to these studies directly given other differences between the study samples. For example, one study was conducted in 2013 with a national sample of adults aged 18-69 in England.19 Another study, although conducted in the U.S., used a broader definition of older adults (i.e., ages 50 or older).17

Among older adults, parental psychopathology (e.g., a parent being hospitalized for a mental illness or a parent who had problems with alcohol or substance use) was the most common type of ACEs, and the exposure of ACEs was positively associated with most past-year psychiatric and substance use disorders. Such findings may suggest the evidence of cumulative effects of adverse events in childhood within individuals with any mental disorder; however, these findings may also be explained by the heritability of these disorders. Thus, further longitudinal studies are needed to adequately examine the causative roles of biological heritability versus environmental stress (e.g., ACEs) in the pathophysiology of these disorders. Similar to a previous study,17 we did not find gender differences in ACEs, except in sexual abuse.

In addition, there is another mechanism to explain the positive associations of ACEs with psychiatric and substance use disorders.19 Individuals with any ACEs may be more likely to have lasting effects on emotional and other behavioral functioning, leading to poor emotional regulation, lower self-esteem, negative self-images, and/or poor psycho-social skills throughout the life course. These individuals were thus more likely to have past-year psychiatric or substance use disorders. Further, these factors are often risk-factors for suicide attempts,41 which were also identified as a key independent factor associated with past-year psychiatric or substance use disorder diagnoses.

There are several implications from this study. First, because the rate of ACEs is common and can be a risk factor for any mental illness in older adults, actively querying about ACEs by healthcare providers may be a useful initial step to detect psychiatric or substance use disorders, which may be unidentified otherwise. Identifying ACEs can also be beneficial in the treatment plan for older adults with any mental disorder. For instance, psycho-therapeutic approaches (e.g., cognitive-behavioral therapy) can potentially address such ACEs and promote mental well-being in older adults.

Second, developing and implementing interventions to address ACEs can also be beneficial to prevent mental disorders as well as other health conditions in older adults, especially when assuming that ACEs have cumulative, life-long negative effects on mental health among older adults.10 At the policy-level, individual states and communities have taken legislative actions to pursue primary prevention of ACE in children. While there are only four states (i.e., Alaska, Oklahoma, Washington, and Wisconsin) that have taken legislative priorities to reduce and prevent ACEs in children,42,43 a long-term policy analysis is needed to assess such interventions on mental health among older adults, so that these interventions can be implemented more widely if they are successful.

Several limitations deserve comment from this study. First, measurement or recall bias may present in assessing the ACEs in a cross-sectional survey, such as the NESARC-III, leading to misclassification of older adults with or without ACEs. One study reported that retrospective measures of ACEs in adulthood often involve a substantial rate of false-negatives, leading to measurement errors.44 In addition, a more recent systematic review and meta-analysis45 suggested that retrospective measurement based on interviews is more reliable than questionnaires. Thus, it is possible that measurement errors may be inevitable in this study. Second, the research design employed in this study was cross-sectional, and thus, the associations we found in this study cannot establish causation. Third, the NESARC-III excluded certain vulnerable populations (e.g., institutionalized or homeless), which may limit the generalizability of the findings.

Despite the limitations, several strengths of our study included the use of: 1) standardized measures of ACEs, 2) past-year psychiatric and substance use disorder diagnoses based on the DSM-5 criteria, and 3) nationally representative sample. Our findings highlight that ACEs are common and are associated with past-year psychiatric or substance use disorders in older adults, even after controlling for other important covariates. Because ACEs may have long-term effects on older adults’ mental well-being, ACEs should be considered when treating older adults with any potential mental illness. While further research is needed, preventing ACEs may lead to large improvements in public mental health that persist well into older age.

Supplementary Material

Supinfo

Supplementary Table S1. Validated measures of adverse childhood experiences (ACEs)

Obtained funding:

In the past three years, Rhee was supported in part by the National Institute on Aging (#T32AG019134). STW was supported in part by Agency for Healthcare Research and Quality (AHRQ) (#K12HS023000), American Foundation for Suicide Prevention, Brain and Behavior Research Foundation (formerly NARSAD), the Patient-Centered Outcomes Research Institute, and the Robert E. Leet and Clara Guthrie Patterson Foundation.

Role of the funder/sponsor:

The funding agency had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript, and decision to submit the manuscript for publication.

Conflict of interest disclosures:

Each author completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. DCS has received consulting fees from Janssen Research & Development, LLC. STW has received funding administered through Yale University from Janssen Research & Development, LLC and Sage Therapeutics.

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Supplementary Materials

Supinfo

Supplementary Table S1. Validated measures of adverse childhood experiences (ACEs)

NIHMS1943253-supplement-Supinfo.docx (21.7KB, docx)

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