Key Points
Question
What is the prevalence of adverse childhood experiences across 23 states stratified by demographic characteristics?
Findings
In this cross-sectional survey of 214 157 respondents, participants who identified as black, Hispanic, or multiracial, those with less than a high school education, those with annual income less than $15 000, those who were unemployed or unable to work, and those identifying as gay/lesbian or bisexual reported significantly higher exposure to adverse childhood experiences than comparison groups.
Meanings
These findings highlight the importance of understanding why some individuals are at higher risk of experiencing adverse childhood experiences than others, including how this increased risk may exacerbate health inequities across the lifespan and future generations.
This cross-sectional survey updates the prevalence estimate of adverse childhood experiences among a representative sample of US adults in 23 states.
Abstract
Importance
Early adversity is associated with leading causes of adult morbidity and mortality and effects on life opportunities.
Objective
To provide an updated prevalence estimate of adverse childhood experiences (ACEs) in the United States using a large, diverse, and representative sample of adults in 23 states.
Design, Setting, and Participants
Data were collected through the Behavioral Risk Factor Surveillance System (BRFSS), an annual, nationally representative telephone survey on health-related behaviors, health conditions, and use of preventive services, from January 1, 2011, through December 31, 2014. Twenty-three states included the ACE assessment in their BRFSS. Respondents included 248 934 noninstitutionalized adults older than 18 years. Data were analyzed from March 15 to April 25, 2017.
Main Outcomes and Measures
The ACE module consists of 11 questions collapsed into the following 8 categories: physical abuse, emotional abuse, sexual abuse, household mental illness, household substance use, household domestic violence, incarcerated household member, and parental separation or divorce. Lifetime ACE prevalence estimates within each subdomain were calculated (range, 1.00-8.00, with higher scores indicating greater exposure) and stratified by sex, age group, race/ethnicity, annual household income, educational attainment, employment status, sexual orientation, and geographic region.
Results
Of the 214 157 respondents included in the sample (51.51% female), 61.55% had at least 1 and 24.64% reported 3 or more ACEs. Significantly higher ACE exposures were reported by participants who identified as black (mean score, 1.69; 95% CI, 1.62-1.76), Hispanic (mean score, 1.80; 95% CI, 1.70-1.91), or multiracial (mean score, 2.52; 95% CI, 2.36-2.67), those with less than a high school education (mean score, 1.97; 95% CI, 1.88-2.05), those with income of less than $15 000 per year (mean score, 2.16; 95% CI, 2.09-2.23), those who were unemployed (mean score, 2.30; 95% CI, 2.21-2.38) or unable to work (mean score, 2.33; 95% CI, 2.25-2.42), and those identifying as gay/lesbian (mean score 2.19; 95% CI, 1.95-2.43) or bisexual (mean score, 3.14; 95% CI, 2.82-3.46) compared with those identifying as white, those completing high school or more education, those in all other income brackets, those who were employed, and those identifying as straight, respectively. Emotional abuse was the most prevalent ACE (34.42%; 95% CI, 33.81%-35.03%), followed by parental separation or divorce (27.63%; 95% CI, 27.02%-28.24%) and household substance abuse (27.56%; 95% CI, 27.00%-28.14%).
Conclusions and Relevance
This report demonstrates the burden of ACEs among the US adult population using the largest and most diverse sample to date. These findings highlight that childhood adversity is common across sociodemographic characteristics, but some individuals are at higher risk of experiencing ACEs than others. Although identifying and treating ACE exposure is important, prioritizing primary prevention of ACEs is critical to improve health and life outcomes throughout the lifespan and across generations.
Introduction
The foundation for lifelong health, well-being, and even prosperity is built in childhood. Positive experiences strengthen developing biological systems, whereas childhood adversity can increase morbidity and mortality and have an effect on access to life opportunities.1,2,3,4 From 1995 through 1997, Kaiser Permanente and the Centers for Disease Control and Prevention conducted an investigation of the prevalence and effect of childhood abuse and neglect and household challenges among more than 17 000 health maintenance organization members. Results revealed that almost two-thirds of study participants reported at least 1 adverse childhood experience (ACE) before the age of 18 years.1 Replications of the ACE Study have found similar prevalence rates across settings and populations.2,5 However, demographic diversity within these investigations has been limited. The present study provides updated prevalence estimates of ACEs in what is to our knowledge the largest (N = 248 934), most diverse sample of US adults to date. This investigation highlights the burden of early adversity that interferes with achieving our country’s goals for optimal health, well-being, and equity.
Methods
Data Collection
The Behavioral Risk Factor Surveillance System (BRFSS) is an annual, nationally representative telephone survey that collects data from noninstitutionalized adults regarding their health-related risk behaviors, chronic health conditions, and use of preventive services. The BRFSS has 3 overall components: core modules (sets of questions consistently administered to all states and territories to establish national estimates), optional modules (Centers for Disease Control and Prevention–developed questions that states can include in their BRFSS survey depending on their priorities), and state-added questions (state-customized items). ACE questions were included as an optional module in the BRFSS from 2009 through 2012 and as state-added questions thereafter. States that used ACE items in their surveys were contacted to establish data use agreements to share ACE data. Individual state BRFSS data sets and publicly available ACE modules were merged, resulting in a combined data set from 23 states from January 1, 2011, through December 31, 2014 (Box). A few states included the ACE items on their BRFSS during multiple years. The survey weights were adjusted to reflect the mean population totals during the period for which these data were collected. All data used in this study are deidentified public health surveillance data and, therefore, not subject to institutional review board approval. The ACE module consists of 11 questions adapted from the Centers for Disease Control and Prevention–Kaiser ACE Study3 on exposure to adversity experienced before 18 years of age. Each question is collapsed into 1 of 8 ACE categories: physical abuse, emotional abuse, sexual abuse, household mental illness, household substance use, incarcerated household member, parental separation or divorce, and household domestic violence. The responses were dichotomized to indicate exposure and summed to create an ACE score (range, 1.00-8.00, with higher scores indicating greater exposure). Ford et al6 provide a full description of the BRFSS ACE module and calculated ACE score.
Box. States With Behavioral Risk Factor Surveillance System ACE Items Included in the Analyses by Year.
2011 (n = 10)
California
Maine
Minnesota
Montana
Nebraska
Nevada
Oregon
Vermont
Washington
Wisconsin
2012 (n = 6)
Connecticut
Iowa
North Carolina
Oklahoma
Tennessee
Wisconsin
2013 (n = 7)
Alaska
Iowa
Maine
Michigan
Oregon
Utah
Wisconsin
2014 (n = 13)
Alaska
Arizona
Colorado
Florida
Iowa
Kansas
Nevada
North Carolina
Oklahoma
Oregon
Pennsylvania
South Carolina
Wisconsin
ACE prevalence estimates within each ACE type were calculated and stratified by demographic variables that included sex, age group, race/ethnicity, annual household income, educational attainment, employment status, sexual orientation, and geographic region. Employment status responses were categorized into the 4 categories of employed (employed for wages, self-employed), unemployed (out of work for any period), not in the workforce (homemakers, students, and retirees), and unable to work. States with ACE data during the 2011-2014 data collection period were categorized using the following census geographic delineations: Midwest (Iowa, Kansas, Michigan, Minnesota, Nebraska, and Wisconsin), Northeast (Connecticut, Maine, Pennsylvania, and Vermont), South (Florida, North Carolina, Oklahoma, South Carolina, and Tennessee), and West (Alaska, Arizona, California, Montana, Nevada, Oregon, Utah, and Washington).
Statistical Analysis
Data were analyzed from March 15 through April 25, 2017. Descriptive statistics for the overall sample, stratified by sex, were estimated across several key sociodemographic variables, including age group, race/ethnicity, annual household income, educational attainment, employment status, sexual orientation, and geographical region. Next, a frequency analysis was conducted to obtain an overall distribution of the ACE exposure for each respondent in the sample using 0, 1, 2, 3, and 4 or more ACE exposure categories. Prevalence of each of the 8 ACE types assessed in the sample was subsequently computed along with their corresponding 95% CIs stratified by each of the aforementioned sociodemographic characteristics. Mean ACE scores and 95% CIs were also estimated within each of the sociodemographic groups. Survey weights were used throughout analysis to reduce bias due to nonresponse and noncoverage. Data analyses were conducted using R software (version 3.32; R Core Team).
Results
Table 1 provides a summary of weighted estimates on demographic and census region statistics for the 214 157 respondents included in the sample (51.51% female; 48.49% male). All age groups were generally represented. Respondents were predominately white (68.08%; 95% CI, 67.40%-68.76%), identified as straight (96.02%; 95% CI, 95.85%-96.33%), had at least a high school diploma (86.16%; 95% CI, 85.65-86.67), were employed (54.15%; 95% CI, 53.53%-54.78%), and earned more than $50 000 a year (43.54%; 95% CI, 42.89%-44.19%). In addition, 30.44% (95% CI, 29.89%-30.98%) of respondents resided in the South and 39.53% (95% CI, 39.08%-39.99%) resided in the West.
Table 1. Demographic Characteristics of the 2011-2014 BRFSS Samplea.
Characteristic | Male Respondents | Female Respondents | All | |||
---|---|---|---|---|---|---|
No. | Weighted % (95% CI) | No. | Weighted % (95% CI) | No. | Weighted % (95% CI) | |
Age group, y | ||||||
18-24 | 4894 | 13.04 (12.19-13.89) | 4703 | 11.60 (10.87-12.32) | 9597 | 12.30 (11.74-12.85) |
25-34 | 8192 | 17.98 (16.96-19.00) | 10 635 | 16.61 (15.82-17.39) | 18 827 | 17.27 (16.63-17.91) |
35-44 | 10 717 | 16.89 (16.17-17.60) | 14 930 | 16.15 (15.58-16.72) | 25 647 | 16.51 (16.05-16.96) |
45-54 | 15 544 | 18.44 (17.77-19.11) | 21 532 | 18.19 (17.63-18.74) | 37 076 | 18.31 (17.88-18.74) |
55-64 | 20 688 | 16.19 (15.64-16.74) | 28 403 | 16.03 (15.88-16.76) | 49 091 | 16.26 (15.91-16.60) |
≥65 | 26 996 | 17.47 (16.95-17.99) | 45 280 | 21.14 (20.69-21.60) | 72 276 | 19.37 (19.01-19.70) |
Race/ethnicity | ||||||
White | 73 343 | 67.48 (66.40-68.55) | 106 062 | 68.64 (67.77-69.52) | 179 405 | 68.08 (67.40-68.76) |
Black | 3939 | 7.71 (7.12-8.30) | 7163 | 8.97 (8.43-9.51) | 11 102 | 8.36 (7.96-8.75) |
Other | 3357 | 7.07 (6.41-7.72) | 4411 | 5.60 (5.14-6.06) | 7768 | 6.31 (5.91-6.71) |
Multiracial | 1757 | 1.75 (1.56-1.95) | 2316 | 1.56 (1.41-1.71) | 4073 | 1.65 (1.53-1.78) |
Hispanic | 3972 | 16.00 (15.02-16.97) | 5522 | 15.22 (14.42-16.03) | 9494 | 15.60 (14.98-16.22) |
Household income, $ | ||||||
<15 000 | 6430 | 10.97 (10.23-11.70) | 12 886 | 14.58 (13.95-15.20) | 19 316 | 12.79 (12.31-13.27) |
15 000-24 999 | 11 669 | 15.76 (14.98-16.54) | 20 822 | 19.21 (18.47-19.95) | 32 491 | 17.50 (16.96-18.04) |
25 000-34 999 | 9176 | 11.44 (10.79-12.09) | 13 794 | 12.12 (11.54-12.69) | 22 970 | 11.78 (11.35-12.21) |
35 000-49 999 | 12 757 | 14.70 (13.95-15.46) | 16 736 | 14.09 (13.49-14.68) | 29 493 | 14.39 (13.91-14.87) |
≥50 000 | 39 272 | 47.13 (46.11-48.16) | 43 951 | 40.01 (39.21-40.81) | 83 223 | 43.54 (42.89-44.19) |
Educational attainment | ||||||
Less than high school | 6396 | 13.93 (13.17-14.70) | 8678 | 13.75 (13.07-14.44) | 15 074 | 13.84 (13.33-14.35) |
High school diploma/GED | 25 093 | 28.61 (27.72-29.50) | 36 196 | 27.58 (26.84-28.33) | 61 289 | 28.08 (27.50-28.66) |
Some college | 23 003 | 31.14 (30.17-32.10) | 37 576 | 33.91 (33.17-34.65) | 60 579 | 32.56 (31.96-33.17) |
College degree | 31 569 | 26.32 (25.52-27.13) | 41 998 | 24.76 (24.16-25.36) | 73 567 | 25.52 (25.02-26.01) |
Employment status | ||||||
Employed | 49 406 | 60.99 (60.03-61.95) | 57 141 | 47.73 (46.94-48.53) | 106 547 | 54.15 (53.53-54.78) |
Unemployed | 4837 | 8.50 (7.86-9.13) | 5812 | 7.06 (6.60-7.51) | 10 649 | 7.75 (7.37-8.14) |
Unable to work | 5170 | 6.91 (6.38-7.44) | 8996 | 7.33 (6.89-7.77) | 14 166 | 7.13 (6.78-7.47) |
Other | 27 830 | 23.61 (22.83-24.39) | 54 219 | 37.88 (37.12-38.64) | 82 049 | 30.97 (30.41-31.52) |
Sexual orientation | ||||||
Straight | 36 577 | 96.30 (95.96-96.64) | 50 216 | 95.90 (95.56-96.24) | 86 793 | 96.02 (95.85-96.33) |
Gay/lesbian | 610 | 1.89 (1.63-2.16) | 548 | 1.14 (0.96-1.32) | 1158 | 1.50 (1.35-1.66) |
Bisexual | 363 | 0.95 (0.77-1.13) | 691 | 1.84 (1.59-2.08) | 1054 | 1.41 (1.25-1.56) |
Other | 527 | 0.86 (0.74-0.98) | 909 | 1.12 (0.95-1.30) | 1436 | 1.00 (0.96-1.10) |
Census region | ||||||
Midwest | 33 607 | 19.62 (19.15-20.08) | 47 093 | 19.55 (19.16-19.94) | 80 700 | 19.58 (19.34-19.82) |
Northeast | 9151 | 10.22 (9.89-10.55) | 13 689 | 10.66 (10.38-10.94) | 22 840 | 10.45 (10.28-10.61) |
South | 15 827 | 29.72 (28.71-30.73) | 24 563 | 31.12 (30.37-31.87) | 40 390 | 30.44 (29.89-30.98) |
West | 28 955 | 40.44 (39.58-41.31) | 41 272 | 38.68 (38.03-39.33) | 70 227 | 39.53 (39.08-39.99) |
Abbreviations: ACE, adverse childhood experiences; BRFSS, Behavioral Risk Factor Surveillance System; GED, General Education Development.
This sample consists of the 23 states that included the ACE module at least once from 2011 to 2014 in the BRFSS. Sample sizes are unweighted; percentages are weighted to the state population totals.
Overall, 38.45% (95% CI, 38.00%-38.89%) of the respondents reported experiencing 0 ACEs; 23.53% (95% CI, 23.12%-23.94%), 1 ACE; 13.38% (95% CI, 13.05%-13.71%), 2 ACEs; 8.83% (95% CI, 8.56%-9.10%), 3 ACEs; and 15.81% (95% CI, 15.45%-16.18%), 4 or more ACEs. Mean ACE scores were higher among women and younger adults. Respondents identifying as multiracial reported the highest level of overall ACE exposure (mean score, 2.52; 95% CI, 2.36-2.67) compared with the other race/ethnicity categories. Significantly higher mean ACE exposures were reported by participants with less than a high school education (mean score, 1.97; 95% CI, 1.88-2.05), those with income less than $15 000 per year (mean score, 2.16; 95% CI, 2.09-2.23), and those identifying as gay/lesbian (mean score, 2.19; 95% CI, 1.95-2.43) and bisexual (mean score, 3.14; 95% CI, 2.82-3.46) compared with those completing high school or more education, those in all other income brackets, and those identifying as straight, respectively. Respondents with lower ACE scores were more likely to be employed (mean score, 1.58; 95% CI, 1.56-1.61) than those with higher ACE scores, who were more likely to report being unemployed (mean score, 2.30; 95% CI, 2.21-2.38) or unable to work (mean score, 2.33; 95% CI, 2.25-2.42). Among the individual ACE types, emotional abuse was the most commonly reported (34.42%; 95% CI, 33.81%-35.03%), followed by parental separation or divorce (27.63%; 95% CI, 27.02%-28.24%) and household substance abuse (27.56%; 95% CI, 27.00%-28.14%) (Table 2). The percentage experiencing specific ACE types varied across each demographic subgroup. For example, compared with male respondents, female respondents reported a greater prevalence of child sexual abuse (16.33% [95% CI, 15.82%-16.85%] vs 6.70% [95% CI, 6.27%-7.13%]), household substance abuse (28.72% [95% CI, 27.99%-29.46%] vs 26.33% [95% CI, 25.45%-27.21%]), and household mental illness (19.19% [95% CI, 18.52%-19.85%] vs 13.71% [95% CI, 12.96%-14.47%]).
Table 2. Prevalence of Measured ACE Types and Mean ACE Score by Sociodemographic Characteristicsa.
Characteristics | ACE Category, Weighted % (95% CI) | ACE Score, Mean (95% CI)b | |||||||
---|---|---|---|---|---|---|---|---|---|
Abuse | Intimate Partner Violence | Household Substance Abuse | Household Mental Illness | Parental Separation or Divorce | Incarcerated Household Member | ||||
Emotional | Physical | Sexual | |||||||
Total | 34.42 (33.81-35.03) |
17.94 (17.42-18.47) |
11.60 (11.26-11.94) |
17.51 (17.02-18.02) |
27.56 (27.00-28.14) |
16.53 (16.04-17.04) |
27.63 (27.02-28.24) |
7.90 (7.44-8.38) |
1.57 (1.55-1.59) |
Sex | |||||||||
Male | 34.92 (33.95-35.89) |
18.38 (17.52-19.24) |
6.70 (6.27-7.13) |
16.79 (16.00-17.58) |
26.33 (25.45-27.21) |
13.71 (12.96-14.47) |
27.45 (26.50-28.40) |
8.58 (7.78-9.38) |
1.46 (1.44-1.49) |
Female | 33.94 (33.19-34.70) |
17.53 (16.92-18.14) |
16.33 (15.82-16.85) |
18.19 (17.57-18.81) |
28.72 (27.99-29.46) |
19.19 (18.52-19.85) |
27.80 (27.02-28.57) |
7.26 (6.75-7.78) |
1.68 (1.65-1.70) |
Age group, y | |||||||||
18-24 | 40.53 (38.07-43.00) |
18.61 (16.46-20.77) |
9.02 (7.81-10.22) |
17.06 (15.13-18.99) |
29.12 (26.86-31.38) |
25.01 (22.80-27.22) |
35.74 (33.42-38.07) |
16.65 (14.40-18.89) |
1.87 (1.80-1.95) |
25-34 | 39.12 (37.03-41.21) |
21.36 (19.49-23.24) |
11.23 (10.20-12.26) |
20.46 (18.72-22.20) |
32.15 (30.16-34.15) |
23.35 (21.49-25.21) |
39.46 (37.30-41.61) |
13.58 (11.72-15.44) |
1.95 (1.89-2.00) |
35-44 | 38.49 (37.05-39.94) |
20.59 (19.35-21.83) |
13.87 (12.97-14.76) |
20.69 (19.43-21.95) |
29.04 (27.73-30.35) |
18.10 (17.04-19.16) |
33.61 (32.17-35.05) |
7.97 (7.19-8.76) |
1.84 (1.79-1.90) |
45-54 | 37.84 36.63-39.05) |
19.61 (18.65-20.57) |
13.76 (13.01-14.52) |
20.02 (19.03-21.02) |
30.95 (29.78-32.12) |
15.56 (14.75-16.37) |
27.30 (26.12-28.47) |
6.46 (5.76-7.16) |
1.68 (1.64-1.72) |
55-64 | 33.61 (32.64-34.57) |
17.47 (16.69-18.24) |
13.21 (12.54-13.89) |
17.16 (16.39-17.93) |
27.84 (26.90-28.79) |
13.82 (13.18-14.45) |
19.59 (18.69-20.48) |
4.69 (4.13-5.25) |
1.43 (1.40-1.46) |
≥ 65 | 20.57 (19.92-21.21) |
11.22 (10.68-11.76) |
8.19 (7.76-8.61) |
10.64 (10.08-11.19) |
18.19 (17.57-18.82) |
7.19 (6.82-7.55) |
14.21 (13.61-14.81) |
2.24 (1.98-2.51) |
0.87 (0.85-0.88) |
Race/ethnicity | |||||||||
White | 34.95 (34.33-35.56) |
16.67 (16.16-17.18) |
11.43 (11.08-11.77) |
15.73 (15.23-16.23) |
28.21 (27.62-28.81) |
18.38 (17.83-18.92) |
25.77 (25.17-26.37) |
6.59 (6.13-7.06) |
1.52 (1.50-1.54) |
Black | 28.22 (26.17-30.28) |
13.93 (12.09-15.77) |
13.28 (11.89-14.67) |
19.71 (17.97-21.46) |
25.82 (23.75-27.89) |
11.14 (9.36-12.92) |
42.50 (39.96-45.04) |
13.25 (11.64-14.86) |
1.69 (1.62-1.76) |
Other | 29.97 (26.93- 33.02) |
14.94 (12.65-17.24) |
7.97 (6.54-9.40) |
17.52 (15.01-20.02) |
17.46 (15.15-19.78) |
11.37 (9.09-13.66) |
19.14 (16.48-21.80) |
8.89 (7.37-10.41) |
1.51 (1.42-1.59) |
Multiracial | 49.11 (45.33-52.89) |
26.52 (23.30-29.74) |
19.09 (16.55-21.64) |
25.63 (22.56-28.70) |
40.54 (36.83-44.25) |
26.87 (23.41-30.33) |
38.72 (35.16-42.29) |
16.11 (13.25-18.97) |
2.52 (2.36-2.67) |
Hispanic | 35.83 (33.59-38.07) |
26.18 (24.10-28.27) |
12.43 (11.17-13.69) |
23.48 (21.57-25.40) |
28.16 (26.11-30.21) |
12.53 (10.83-14.22) |
30.03 (27.79-32.27) |
10.29 (7.70-12.88) |
1.80 (1.70-1.91) |
Household income, $ | |||||||||
<15 000 | 38.38 (36.44-40.32) |
26.25 (24.44-28.05) |
17.35 (15.97-18.73) |
25.45 (23.68-27.23) |
33.31 (31.43-35.2) |
17.77 (16.44-19.10) |
35.40 (33.41-37.39) |
12.72 (11.47-13.98) |
2.16 (2.09-2.23) |
15 000-24 999 | 36.76 (35.08-38.44) |
21.60 (20.15-23.05) |
13.24 (12.32-14.16) |
22.50 (21.02-23.99) |
31.51 (29.89-33.12) |
16.70 (15.40-18.00) |
32.36 (30.64-34.08) |
10.97 (9.69-12.25) |
1.89 (1.83-1.95) |
25 000-34 999 | 35.54 (33.57-37.51) |
19.17 (17.49-20.85) |
12.51 (11.38-13.64) |
18.68 (17.01-20.36) |
29.53 (27.64-31.41) |
16.98 (15.39-18.57) |
29.82 (27.82-31.81) |
9.14 (7.38-10.90) |
1.66 (1.60-1.72) |
35 000-49 999 | 34.52 (32.79-36.26) |
18.59 (16.86-20.31) |
11.56 (10.61-12.51) |
17.51 (16.20-18.82) |
27.99 (26.35-29.64) |
16.88 (15.36-18.41) |
29.10 (27.26-30.94) |
7.92 (6.41-9.42) |
1.52 (1.48-1.57) |
≥50 000 | 33.67 (32.79-34.55) |
14.55 (13.87-15.23) |
9.86 (9.38-10.35) |
14.38 (13.69-15.07) |
24.67 (23.88-25.45) |
16.47 (15.70-17.25) |
22.83 (22.02-23.65) |
4.83 (4.25-5.42) |
1.39 (1.36-1.41) |
Educational attainment | |||||||||
Less than high school | 34.64 (32.65-36.63) |
25.92 (24.02-27.82) |
13.07 (11.91-14.24) |
25.99 (24.13-27.85) |
35.22 (33.18-37.25) |
14.55 (13.01-16.09) |
32.37 (30.33-34.42) |
14.60 (12.70-16.50) |
1.97 (1.88-2.05) |
High school graduate/GED | 33.88 (32.69-35.08) |
17.88 (16.86-18.89) |
11.03 (10.37-11.70) |
18.54 (17.53-19.56) |
28.67 (27.55-29.79) |
14.63 (13.70-15.56) |
31.25 (30.04-32.47) |
8.85 (7.94-9.75) |
1.59 (1.56-1.62) |
Some college | 36.90 (35.80-37.99) |
18.39 (17.50-19.28) |
13.23 (12.58-13.89) |
17.35 (16.52-18.18) |
29.27 (28.26-30.28) |
19.26 (18.31-20.22) |
29.15 (28.11-30.19) |
7.81 (7.03-8.59) |
1.67 (1.64-1.70) |
College graduate | 31.67 (30.69-32.64) |
13.07 (12.27-13.88) |
9.17 (8.74-9.61) |
12.12 (11.44-12.80) |
20.01 (19.26-20.77) |
16.09 (15.24-16.94) |
19.07 (18.09-20.06) |
3.50 (2.86-4.15) |
1.23 (1.21-1.25) |
Employment status | |||||||||
Employed | 35.74 (34.90-36.58) |
17.41 (16.69-18.14) |
10.64 (10.20-11.09) |
17.43 (16.74-18.13) |
27.56 (26.78-28.33) |
16.69 (16.00-17.37) |
28.33 (27.50-29.16) |
7.91 (7.27-8.55) |
1.58 (1.56-1.61) |
Unemployed | 44.49 (41.83-47.16) |
26.52 (24.08-28.96) |
15.46 (13.77-17.14) |
24.98 (22.74-27.22) |
36.22 (33.64-38.79) |
23.37 (20.99-25.75) |
41.37 (38.63-44.12) |
17.20 (14.29-20.11) |
2.30 (2.21-2.38) |
Unable to work | 44.60 (42.06-47.14) |
29.50 (27.15-31.84) |
23.25 (21.61-24.90) |
28.72 (26.37-31.07) |
40.12 (37.69-42.55) |
23.89 (21.83-25.95) |
37.20 (34.69-39.72) |
11.84 (9.98-13.70) |
2.33 (2.25-2.42) |
Other | 27.26 (26.33-28.20) |
14.10 (13.35-14.85) |
9.78 (9.26-10.31) |
13.25 (12.56-13.94) |
22.45 (21.57-23.33) |
12.85 (12.07-13.63) |
20.76 (19.84-21.68) |
4.84 (4.27-5.41) |
1.22 (1.19-1.25) |
Sexual orientation | |||||||||
Bisexual | 59.16 (53.81-64.51) |
34.93 (29.58-40.28) |
34.54 (28.91-40.16) |
29.55 (24.31-34.79) |
46.28 (40.75-51.80) |
16.96 (16.46-17.46) |
45.97 (40.43-51.50) |
18.65 (13.97-23.33) |
3.14 (2.82-3.46) |
Gay/Lesbian | 47.15 (41.89-52.40) |
30.76 (25.65-35.87) |
23.22 (18.93-27.52) |
26.89 (22.03-31.75) |
37.14 (31.85-42.43) |
33.03 (27.83-38.24) |
36.28 (30.90-41.66) |
12.56 (8.66-16.46) |
2.19 (1.95-2.43) |
Other | 35.49 (30.16-40.81) |
24.11 (19.41-28.80) |
10.85 (7.82-13.89) |
20.59 (16.21-24.97) |
23.18 (18.65-27.71) |
39.78 (34.34-45.22) |
21.98 (17.69-26.26) |
7.45 (4.65-10.25) |
1.55 (1.35-1.76) |
Straight | 34.48 (33.87-35.10) |
16.60 (16.12-17.07) |
12.09 (11.63-12.54) |
16.17 (15.68-16.67) |
26.38 (25.81-26.96) |
19.05 (14.10-23.99) |
26.58 (25.97-27.18) |
7.10 (6.73-7.46) |
1.60 (1.57-1.63) |
Census region | |||||||||
Midwest | 35.27 (34.46-36.09) |
16.36 (15.71-17.01) |
9.86 (9.36-10.36) |
15.54 (14.92-16.17) |
26.61 (25.85-27.36) |
16.08 (15.44-16.72) |
23.99 (23.21-24.77) |
7.16 (6.65-7.67) |
1.47 (1.44-1.50) |
Northeast | 32.22 (31.09-33.36) |
15.10 (14.24-15.97) |
10.84 (10.02-11.67) |
15.02 (14.12-15.91) |
24.49 (23.46-25.52) |
15.34 (14.44-16.23) |
24.50 (23.43-25.56) |
6.35 (5.69-7.02) |
1.56 (1.5-1.61) |
South | 29.83 (28.40-31.26) |
15.51 (14.26-16.77) |
11.48 (10.94-12.02) |
17.19 (16.00-18.37) |
27.75 (26.38-29.12) |
16.20 (14.94-17.46) |
31.13 (29.61-32.65) |
8.60 (7.53-9.66) |
1.55 (1.51-1.58) |
West | 38.08 (37.14-39.03) |
21.33 (20.51-22.15) |
12.54 (11.96-13.12) |
19.39 (18.61-20.17) |
28.71 (27.84-29.57) |
17.33 (16.61-18.05) |
27.58 (26.72-28.43) |
8.46 (7.94-8.98) |
1.73 (1.69-1.76) |
Abbreviations: ACE, adverse childhood experiences; GED, General Education Development.
Data are obtained from the Behavioral Risk Factor Surveillance System, 2011-2014.
Scores range from 0 to 8, with higher scores indicating higher exposure.
Discussion
This study is, to our knowledge, the largest and most diverse collection of ACE data from the BRFSS to date and provides an expanded investigation of ACE exposure across 23 states. Findings reveal that ACEs are prevalent across all demographic characteristics, yet some populations experience a greater, unequal burden of such exposure. Identifying such inequities provides important information about the conditions in which children of adults with high ACEs are growing up and the subsequent effects of ACE exposure, including opioid use and misuse, on future generations. The variation of ACEs across demographic groups supports literature showing that social and structural conditions contribute to the risk of exposure to childhood adversity7 and that exposure to ACEs may exacerbate inequities in health, social, and economic outcomes across generations.4,8
Limitations
This study has several limitations. The BRFSS data are cross-sectional and therefore cannot establish causality. The BRFSS relies on self-reported health information and retrospective reporting of ACEs, which may be susceptible to memory and response biases.9 However, previous studies establish the general validity of self-reported childhood adversity.10 In addition, ACEs measured on the BRFSS do not represent the entire spectrum of early adversities that exist, nor do they measure critical dimensions of exposure, such as severity or the age at onset, which can also significantly affect health and well-being.11,12 In addition, not all gender identifications, races, and sexual orientations are assessed on the BRFSS, which limits our understanding of the prevalence of ACEs in some populations, including those with multiple minority identities.
Conclusions
Despite these limitations, this study has potentially significant implications for population health. Notably, these findings highlight the importance of understanding why some groups are at greater risk than others of experiencing ACEs, including how this risk may exacerbate health inequities across the lifespan and across generations. Although identifying and treating ACE exposure is important, the primary prevention of ACEs is critical if we are to prevent the associated negative health and life outcomes. By ensuring that all children have access to safe, stable, nurturing relationships and environments,13,14,15 we can prevent or alleviate the effects of ACEs, thereby achieving multiple public health goals.
Footnotes
Abbreviation: ACE, adverse childhood experience.
Data are obtained from the Behavioral Risk Factor Surveillance System, 2011-2014.
References
- 1.Felitti VJ, Anda RF, Nordenberg D, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the Adverse Childhood Experiences (ACE) Study. Am J Prev Med. 1998;14(4):245-258. doi: 10.1016/S0749-3797(98)00017-8 [DOI] [PubMed] [Google Scholar]
- 2.Gilbert LK, Breiding MJ, Merrick MT, et al. Childhood adversity and adult chronic disease: an update from ten states and the District of Columbia, 2010. Am J Prev Med. 2015;48(3):345-349. doi: 10.1016/j.amepre.2014.09.006 [DOI] [PubMed] [Google Scholar]
- 3.Shonkoff JP. Capitalizing on advances in science to reduce the health consequences of early childhood adversity. JAMA Pediatr. 2016;170(10):1003-1007. doi: 10.1001/jamapediatrics.2016.1559 [DOI] [PubMed] [Google Scholar]
- 4.Metzler M, Merrick MT, Klevens J, Ports KA, Ford DC. Adverse childhood experiences and life opportunities: shifting the narrative. Child Youth Serv Rev. 2017;72:141-149. doi: 10.1016/j.childyouth.2016.10.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Finkelhor D, Turner HA, Shattuck A, Hamby SL. Prevalence of childhood exposure to violence, crime, and abuse: results from the National Survey of Children’s Exposure to Violence. JAMA Pediatr. 2015;169(8):746-754. doi: 10.1001/jamapediatrics.2015.0676 [DOI] [PubMed] [Google Scholar]
- 6.Ford DC, Merrick MT, Parks SE, et al. Examination of the factorial structure of adverse childhood experiences and recommendations for three subscale scores. Psychol Violence. 2014;4(4):432-444. doi: 10.1037/a0037723 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Sedlak AJ, Mettenburg J, Basena M, et al. Fourth National Incidence Study of Child Abuse and Neglect (NIS–4): Report to Congress, executive summary. US Dept of Health and Human Services; January 2010. https://www.acf.hhs.gov/sites/default/files/opre/nis4_report_exec_summ_pdf_jan2010.pdf. Accessed October 20, 2017. [Google Scholar]
- 8.Font SA, Maguire-Jack K. Pathways from childhood abuse and other adversities to adult health risks: the role of adult socioeconomic conditions. Child Abuse Negl. 2016;51:390-399. doi: 10.1016/j.chiabu.2015.05.013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Tourangeau R, Yan T. Sensitive questions in surveys. Psychol Bull. 2007;133(5):859-883. doi: 10.1037/0033-2909.133.5.859 [DOI] [PubMed] [Google Scholar]
- 10.Hardt J, Rutter M. Validity of adult retrospective reports of adverse childhood experiences: review of the evidence. J Child Psychol Psychiatry. 2004;45(2):260-273. doi: 10.1111/j.1469-7610.2004.00218.x [DOI] [PubMed] [Google Scholar]
- 11.Finkelhor D, Shattuck A, Turner H, Hamby S. Improving the Adverse Childhood Experiences Study scale. JAMA Pediatr. 2013;167(1):70-75. doi: 10.1001/jamapediatrics.2013.420 [DOI] [PubMed] [Google Scholar]
- 12.Cronholm PF, Forke CM, Wade R, et al. Adverse childhood experiences: expanding the concept of adversity. Am J Prev Med. 2015;49(3):354-361. doi: 10.1016/j.amepre.2015.02.001 [DOI] [PubMed] [Google Scholar]
- 13.Fortson BL, Klevens J, Merrick MT, Gilbert LK, Alexander SP. Preventing Child Abuse and Neglect: A Technical Package for Policy, Norm, and Programmatic Activities. Atlanta, GA: National Center for Injury Prevention and Control; 2016. [Google Scholar]
- 14.Centers for Disease Control and Prevention . Essentials for Childhood: Steps to Create Safe, Stable, Nurturing Relationships and Environments. Atlanta, GA: National Center for Injury Prevention and Control; 2014. [Google Scholar]
- 15.Garner AS, Shonkoff JP; Committee on Psychosocial Aspects of Child and Family Health; Committee on Early Childhood, Adoption, and Dependent Care; Section on Developmental and Behavioral Pediatrics . Early childhood adversity, toxic stress, and the role of the pediatrician: translating developmental science into lifelong health. Pediatrics. 2012;129(1):e224-e231. doi: 10.1542/peds.2011-2662 [DOI] [PubMed] [Google Scholar]