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. Author manuscript; available in PMC: 2019 Jul 1.
Published in final edited form as: Autism. 2017 Jun 21;22(5):625–635. doi: 10.1177/1362361316689330

Self-injurious behaviors in children with autism spectrum disorder enrolled in the Study to Explore Early Development

Gnakub Norbert Soke 1,2, Steven A Rosenberg 1, Cordelia Robinson Rosenberg 1, Roma A Vasa 3, Li-Ching Lee 4, Carolyn DiGuiseppi 1
PMCID: PMC5912993  NIHMSID: NIHMS927667  PMID: 28635306

Abstract

We assessed potential factors associated with “current” or “ever” self-injurious behaviors, reported in the Autism Diagnostic Interview–Revised, among children with autism spectrum disorder (n = 692) from the Study to Explore Early Development. Data on factors examined were obtained from questionnaires, standardized clinical instruments, and birth certificates. We employed a log-binomial regression to assess these associations. Although most associations were quite similar for currently and ever exhibiting self-injurious behaviors, a few differences were noted. We documented previously unreported associations of current self-injurious behaviors with maternal age and cesarean delivery, and ever self-injurious behaviors with maternal age, child sex, gestational age, and maternal race. We also confirmed previously reported associations with adaptive skills, somatic conditions (sleep, gastrointestinal, and sensory abnormalities), and other behavioral problems. These findings are informative for clinical practice and future research.

Keywords: autism, autism spectrum disorder, challenging behaviors, developmental disabilities, self-injurious behaviors

Autism spectrum disorder (ASD) is a pervasive neurodevelopmental condition characterized by impairments in social communication and interaction, and the presence of restricted and repetitive patterns of behaviors, interests, or activities (American Psychiatric Association (APA), 2013). Self-injurious behaviors (SIB) are reported in ASD (Baghdadli et al., 2003; Duerden et al., 2012; Minshawi et al., 2014a; Rattaz et al., 2015; Soke et al., 2016; Weiss, 2002). SIB include various repetitive and rhythmic behaviors, such as arm biting, head banging, and hair pulling, that occur without an apparent intent of willful self-harm but may pose significant risk of harm to self (Dempsey et al., 2016; Fee and Matson, 1992). Individual consequences of SIB may include injuries (e.g. lacerations, contusions, concussions, bleeding) and infections that can result in emergency room visits and hospitalizations (Devine, 2014; Ianuzzi et al., 2015; Minshawi et al., 2014b). Those with SIB are more likely to be excluded from educational and vocational activities and placed in residential facilities (Devine, 2014; Ianuzzi et al., 2015; Minshawi et al., 2014b). SIB can affect the entire family (e.g. high medical expenditures and stress) (Ianuzzi et al., 2015), and increase the societal costs of care in those with ASD (Minshawi et al., 2014b). The etiology of SIB is not completely understood, and most likely results from interactions between biological (e.g. genetic and somatic conditions) and environmental factors (e.g. inability to communicate and interact with others). Furthermore, in those with developmental disabilities, SIB may serve different functions, such as communication, social interaction, and self-regulation (Carr, 1977; Devine, 2014; Guess and Carr, 1991; Kurtz et al., 2012; Soke et al., 2017).

There are few large epidemiological studies that examine SIB in ASD (Matson and Goldin, 2013). This limits the ability to fully delineate risk factors for SIB and to develop targeted interventions (Soke et al., 2017). Risk factors for SIB examined in past studies varied depending on the study. In general, no significant associations were reported between SIB and race/ethnicity or sex (Baghdadli et al., 2003; Horovitz et al., 2011; Kozlowski et al., 2012; Sell et al., 2012). In contrast, low cognitive and adaptive skills, presence of other challenging behaviors, and somatic conditions, including sleep and sensory problems, were associated with SIB (Baghdadli et al., 2003; Carroll et al., 2014; Duerden et al., 2012; Goldman et al., 2011; Kanne and Mazurek, 2011; Schroeder et al., 2014). Inconsistent results were reported concerning associations of SIB with child chronological age (Baghdadli et al., 2003; Duerden et al., 2012; Esbensen et al., 2009; Murphy et al., 2009), autism severity (Baghdadli et al., 2003; Duerden et al., 2012; Rattaz et al., 2015), gastrointestinal problems (Buie et al., 2010; Christensen et al., 2009; Kang et al., 2014; Kennedy and Thompson, 2000, as cited by Thompson and Caruso, 2002; Maenner et al., 2012), and developmental regression (Lance et al., 2014; Soke et al., 2017; Wiggins et al., 2009).

Lack of power due to small sample sizes, selection bias that may have resulted from inclusion of children from clinical samples, and limited external validity of the findings are some of the limitations of past studies (Duerden et al., 2012). In addition, the diversity of instruments used to assess SIB, including both non-standardized and standardized questionnaires, such as the Autism Diagnostic Interview–Revised (ADI-R) (Lord et al., 1994) and the Childhood Autism Rating Scale (CARS; Schopler et al., 1986), impedes the ability to combine findings meta-analytically to increase power. Large studies that examine SIB in children with ASD recruited from educational as well as clinical settings are needed. Furthermore, to our knowledge, no study has compared the factors associated with currently observed SIB (“current SIB”) versus ever having exhibited SIB (“ever SIB”). The purpose of this study is to enhance our knowledge of factors influencing SIB by assessing potential associations with current and ever SIB, reported in the ADI-R, in a community-based sample of children with ASD. In addition, this study evaluates the concordance between parental report of SIB on the ADI-R and clinician’s observations of SIB during the Autism Diagnostic Observation Schedule (ADOS) (Lord et al., 2000).

Methods

Study design

We employed a cross-sectional design using data from the Study to Explore Early Development (SEED), a multi-site case–control study that enrolled children aged 30–68 months from six sites in the United States: California, Colorado, Georgia, Maryland, North Carolina, and Pennsylvania (Schendel et al., 2012). These analyses were authorized by the SEED Data Sharing Committee and all data were collected under the original SEED protocol, approved by the institutional review boards of the Centers for Disease Control and Prevention and each participating site.

Participants

SEED participants were recruited from multiple sources, including specialized ASD diagnostic and treatment centers, early intervention providers, and vital records. After clinical evaluation by trained clinicians using standardized instruments, enrolled children were classified into the ASD case group or one of two control groups (Schendel et al., 2012). For the current study, we included only children who met study criteria for ASD case classification. Details on the methodology used to classify children as “ASD” in SEED have been provided by others (Schendel et al., 2012; Wiggins et al., 2015a, 2015b). In brief, eligible children aged 30–68 months (born between 1 September 2003 and 31 August 2006), with a knowledgeable caregiver who was fluent in English or, at two sites, English or Spanish, were enrolled and underwent a comprehensive assessment by clinicians with expertise in assessment and diagnosis of children with ASD, using standardized instruments, including ADOS, ADI-R, Mullen Scales of Early Learning (MSEL; Mullen, 1995), and Vineland Adaptive Behavior Skills (VABS-2; Sparrow et al., 2005). ASD cases included in this study met the Diagnostic and Statistical Manual for Mental Disorders (4th ed., text rev., DSM-IV-TR; APA, 2000) criteria for ASD and the cut-offs for ASD classification on the ADOS and the ADI-R, based on an algorithm developed by SEED clinicians (Wiggins et al., 2015a).

Measures

We assessed two primary outcomes: current SIB and ever SIB, categorized as “yes” or “no.” Data for both outcomes were obtained from question 83 on the ADI-R. Parents are asked about the presence of current or ever SIB (e.g. biting the wrist, banging the head that resulted in tissue damage), with a duration of at least 3 months. If the parents’ answer was coded as “2” (self-injury definitely present) or “3” (definite self-injury with serious damage), the child was considered as having current SIB. When the answer was coded as “0 (none) or 1 (slight self-injury e.g. occasionally bites own had/arm when annoyed … no substantial tissue damage),” the child was classified as not having current SIB. To assess ever SIB, parents were asked whether SIB occurred in the past, and we categorized their answers in the same way as for current SIB.

A secondary outcome, observed SIB from the ADOS, categorized as “yes” or “no,” was also evaluated. ADOS question D3 assesses whether the clinician notices SIB during the assessment (“observed SIB”). If the clinician assessment of SIB was coded as “1” (dubious or possible self-injury, and/or rare but clear self-injury) or “2” (more than one clear example of self-injury), the child was classified as having observed SIB. If the observation of SIB was coded as “0,” the child was categorized as not having observed SIB.

Factors examined for potential relation to SIB included sociodemographic characteristics, development, autism severity, somatic conditions, behavioral issues, child comorbid diagnoses, maternal medical and psychiatric conditions during pregnancy, labor complications, and child perinatal conditions (see Table 1 for complete listing). Data on these factors were collected from standardized instruments (MSEL, VABS-2, ADI-R, Child Sleep Habit Questionnaire (CSHQ), Gastrointestinal Symptom Inventory (GSI)); SEED-specific instruments (caregiver interview, maternal medical history); and birth certificates. We used ADOS calibrated scores, derived from ADOS raw scores, to assess autism severity (Gotham et al., 2009). The presence of gastrointestinal problems was derived by combining parent’s responses to GSI question 14, 15, 16, 17, and 18. Sleep scores represented the total scores from the five individual sleep domain scores in the CSHQ. We analyzed adaptive behaviors skills scores, intelligence quotient (IQ), and sleep scores as continuous variables, since the plots of these variables versus SIB did not show specific cut-points. Other child comorbid diagnoses were grouped as follows: child neurologic conditions (cerebral palsy, seizure disorder); child developmental conditions (attention-deficit/hyperactivity disorder, learning disability, vision and hearing impairments); and child genetic conditions (Down syndrome, fragile X syndrome, tuberous sclerosis). Neonatal complications included major (any condition leading to admission into the intensive care unit) and minor (jaundice, fetal distress). Labor complications were categorized as major (uterus rupture, general anesthesia) and minor (fever, bleeding). The following maternal medical conditions during pregnancy were examined: eclampsia, diabetes, anemia, and high blood pressure.

Table 1.

Characteristics of children with autism spectrum disorder in the Study to Explore Early Development (SEED) based on current and ever had self-injurious behaviors.

Variable Current self-injurious behavior (n = 692)
Ever self-injurious behaviors (n = 692)
Yes (n = 194) No (n = 498) Yes (n = 330) No (n = 362)
Child sex
 Male   158 (81.44)   408 (81.93)   279 (84.55)   287 (79.28)
 Female     36 (18.56)     90 (18.07)     51 (15.45)     75 (20.72)
Child enrollment age (months)
 Mean (SD) 55.50 (6.98) 56.15 (6.58) 55.32 (7.44) 56.08 (6.18)
Child gestational age (weeks)
 Mean (SD) 37.84 (3.19) 38.19 (2.96) 37.98 (3.18) 38.20 (2.88)
Child birth weight (g)
 Mean (SD) 3391.58 (1482.18) 3365.15 (1195.96) 3343.18 (1289.31) 3399.33 (1275.73)
Maternal race
 White   126 (64.95)   299 (60.04)   222 (67.27)   203 (56.08)
 Non-White     64 (32.99)   191 (38.35)   103 (31.21)   152 (41.99)
 Missing       4 (2.06)       8 (1.61)       5 (1.52)       7 (1.93)
Maternal ethnicity
 Hispanic     24 (12.37)     60 (12.05)     41 (12.42)     43 (11.88)
 Non-Hispanic   167 (86.08)   431 (86.55)   284 (86.06)   314 (86.74)
 Missing       3 (1.55)       7 (1.40)       5 (1.52)       5 (1.38)
Language spoken at home
 English   172 (88.66)   431 (86.55)   294 (89.09)   309 (85.36)
 Other     19 (9.79)     61 (12.25)     32 (9.70)     48 (13.26)
 Missing       3 (1.55)       6 (1.20)       4 (1.21)       5 (1.38)
Maternal education
 College degree or higher     79 (40.72)   278 (55.82)   144 (43.64)   213 (58.84)
 No college   112 (57.73)   212 (42.57)   181 (54.85)   143 (39.50)
 Missing       3 (1.55)       8 (1.61)       5 (1.51)       6 (1.66)
Maternal smoking status
 Yes     30 (15.46)     66 (13.25)     54 (16.36)     42 (11.60)
 No   164 (84.54)   432 (86.75)   276 (83.64)   320 (88.40)
Maternal age (years)
 Mean (SD) 30.19 (5.69) 32.21 (5.39) 30.74 (5.65) 32.46 (5.32)
Family income (quartiles)
 First (lowest)     71 (36.60)     92 (18.48)   101 (30.61)     62 (17.13)
 Second     45 (23.20)   130 (26.10)     81 (24.54)     94 (25.97)
 Third     35 (18.04)   128 (25.70)     68 (20.60)     95 (26.24)
 Fourth (highest)     34 (17.52)   130 (26.10)     65 (19.70)     99 (27.35)
 Missing       9 (4.64)     18 (3.62)     15 (4.55)     12 (3.31)
Developmental regression
 Yes     51 (26.29)   116 (23.29)     83 (25.15)     84 (23.20)
 No   143 (73.71)   382 (76.71)   247 (74.85)   278 (76.80)
 Missing       0       0       0       0
IQ score
 Mean (SD) 63.18 (19.34) 68.31 (20.04) 65.61 (20.01) 68.03 (19.89)
Adaptive score
 Mean (SD) 67.96 (13.90) 76.12 (18.5) 71.09 (14.52) 76.35 (19.89)
Sleep score
 Mean (SD) 51.51 (11.27) 46.66 (9.18) 50.04 (10.55) 46.16 (9.17)
ADOS-severity score
 Mean (SD)   7.21 (1.62)   7.16 (1.57)   7.20 (1.59)   7.14 (1.58)
Sensory problems
 Yes   162 (83.51)   346 (69.48)   263 (79.70)   245 (67.68)
 No     32 (16.49)   152 (30.52)     67 (20.30)   117 (32.32)
Gastrointestinal problems
 Yes     83 (42.78)   139 (27.91)   176 (53.33)   245 (67.68)
 No     94 (48.46)   327 (65.66)   124 (37.58)     98 (27.07)
 Missing     17 (8.76)     32 (6.43)     30 (9.09)     19 (5.25)
Child behavioral issues
 Yes     99 (51.03)   130 (26.10)   152 (46.06)     77 (21.27)
 No     95 (48.97)   368 (73.90)   178 (53.94)   285 (78.73)
Child neurologic conditions
 Yes     21 (10.82)     17 (3.41)     24 (7.27)     14 (3.87)
 No   173 (89.18)   481 (96.59)   306 (92.73)   348 (96.13)
Child developmental conditions
 Yes   132 (68.04)   281 (56.43)   215 (65.15)   198 (54.70)
 No     62 (31.96)   217 (43.57)   115 (34.85)   164 (45.30)
Child genetic conditions
 Yes       5 (2.58)       7 (1.41)       6 (1.82)       6 (1.66)
 No   189 (97.42)   491 (98.59)   324 (98.18)   356 (98.34)
Child other conditions
 Yes     19 (9.79)     45 (9.04)     33 (10.00)     31 (8.56)
 No   175 (90.21)   453 (90.96)   297 (90.00)   331 (91.44)
Neonatal complications
 Major     51 (26.29)     94 (18.87)     75 (27.73)     70 (19.34)
 Minor     64 (32.99)   182 (36.55)   107 (32.42)   139 (38.40)
 None     79 (40.72)   222 (44.58)   148 (44.85)   153 (42.26)
Plurality
 Yes     28 (14.43)     77 (15.56)     51 (15.45)     54 (14.92)
 No   166 (85.57)   421 (84.46)   279 (84.54)   308 (85.08)
Mode of delivery
 Vaginal   103 (53.10)   312 (62.65)   117 (35.45)   142 (39.23)
 Cesarean     85 (43.81)   174 (34.94)   201(60.91)   214 (59.12)
 Missing       6 (3.09)     12 (2.41)     12 (3.64)       6 (1.66)
Labor complications
 Major       9 (4.64)     23 (4.62)     16 (4.85)     16 (4.42)
 Minor     31 (15.98)     55 (11.04)     41 (12.42)     45 (12.43)
 None   154 (79.38)   420 (84.34)   273 (82.73)   301 (83.15)
Maternal medical conditions during pregnancy
 Yes     74 (38.14)   161 (32.33)   119 (36.06)   116 (32.04)
 No   120 (61.86)   337 (67.67)   211 (63.94)   246 (67.96)
Maternal depression
 Yes     58 (29.90)   121 (24.30)   102 (30.91)     77 (21.27)
 No   136 (70.10)   377 (75.70)   228 (69.09)   285 (78.73)
Maternal mental retardation
 Yes     12 (6.19)     18 (3.61)     31 (9.39)     12 (3.31)
 No   181 (93.30)   476 (95.58)   299 (90.61)   350 (96.69)
 Missing       1 (0.52)       4 (0.80)       0       0
Maternal anxiety
 Yes     26 (13.40)     40 (8.03)     36 (10.91)     30 (18.29)
 No   168 (86.60)   458 (91.97)   294 (89.09)   332 (91.71)
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SD: standard deviation; IQ: intelligence quotient; ADOS: Autism Diagnostic Observation Schedule.

Analytical strategy

We used a two-step approach to assess the factors associated with current and ever SIB. First, bivariate associations were evaluated between each factor and parent-reported current and ever SIB, respectively, using a log-binomial regression. Variables associated with current or ever SIB at p ≤ 0.20 were included in the second step (multivariable analyses). Sex, IQ scores, and enrollment site were selected a priori for inclusion in all models. We tested separate models for current and ever SIB using PROC GENMOD (SAS© version 9.3, Cary, NC, USA) and reported unadjusted and adjusted estimates at the significance level of 0.05. We examined possible effect modification by IQ through inclusion of interaction terms in the models. As a secondary analysis, we explored whether associations identified with current or ever SIB were also present with observed SIB.

We examined concordance between parent-reported current and ever SIB with observed SIB using McNemar’s test and reported the level of agreement (Kappa statistic) with 95% confidence intervals.

Results

This study involved 692 children with ASD. In Table 1, we presented the attributes of children with current and ever SIB. The prevalence of parent-reported current SIB was 28% and ever SIB was 47% on the ADI-R.

Among the 31 variables tested in bivariate analyses, 21 variables for current SIB and 20 variables for ever SIB were examined in multivariable analyses. Five variables (lower child adaptive skills, child sleep, gastrointestinal and behavioral problems/issues, and younger maternal age) were significantly associated with both current and ever SIB in multivariable models (Tables 2 and 3). Significant independent associations were also found between current SIB alone and higher cognitive skills, child genetic conditions, sensory problems, cesarean birth, and major neonatal complications (Table 2). Additional variables significantly associated only with ever SIB included lower gestational age, male sex, and non-Hispanic white race; sensory problems approached statistical significance for ever SIB (Table 3). None of these relationships were modified by IQ. Although none of the identified associations with current or ever SIB were found with observed SIB, the directionality of their relationships was similar in current or ever SIB compared to observed SIB for most variables analyzed (Supplemental Tables).

Table 2.

Associations between report of current self-injurious behaviors (SIB) and risk and protective factors in the Study to Explore Early Development (SEED).

Variable Univariable analyses*
Multivariable analyses**
PR and 95% CI p value aPR and 95% CI p value
Child sex (female vs male) 1.02 (0.67, 1.40)   0.88 0.89 (0.65, 1.22)   0.49
Child age (1 month) 1.01 (0.75, 1.03)   0.38             –     –
Gestational age (1 week) 1.07 (0.98, 1.16)   0.11 1.01 (0.97, 1.05)   0.63
Birth weight (1 g) 1.01 (1.00, 1.00)   0.81             –     –
Non-White vs White maternal race 0.85 (0.64, 1.11)   0.23             –     –
Hispanic vs non-Hispanic maternal ethnicity 1.02 (0.75, 1.39)   0.88             –     –
Language spoken at home (other vs English) 0.83 (0.55, 1.26)   0.38             –     –
Maternal level of education (no college degree vs college) 1.56 (1.44, 1.69) <0.0001 0.95 (0.84, 1.07)   0.38
Maternal smoking (yes vs no) 1.13 (0.90, 1.43)   0.28             –     –
Maternal age at birth (1 year) 0.95 (0.94, 0.96) <0.0001 0.97 (0.95, 0.98) <0.0001
Family income (quartiles)
 First (lowest) 2.10 (1.59, 2.77) <0.0001 1.13 (0.64, 2.01)   0.67
 Second 1.24 (0.94, 1.64)   0.13 1.05 (0.76, 1.46)   0.77
 Third 1.04 (0.80, 1.35)   0.79 0.98 (0.67, 1.44)   0.93
Fourth (highest) 1.00   1.00 1.00   1.00
Regression (yes vs no) 1.12 (0.98, 1.28)   0.10 0.85 (0.66, 1.11)   0.23
IQ score (1 unit) 0.99 (0.98, 0.99) <0.0001 1.01 (1.00, 1.02)   0.008
Adaptive score (1 unit) 0.97 (0.96, 0.98) <0.0001 0.98 (0.97, 0.99) <0.0001
Sleep score (1 unit) 1.03 (1.02, 1.04) <0.0001 1.02 (1.01, 1.03)   0.007
Autism severity scores (1 unit) 1.01 (0.95, 1.08)   0.67             –     –
Sensory problems (yes vs no) 1.83 (1.60, 2.09) <0.0001 1.41 (1.16, 1.71)   0.0004
Gastrointestinal problems (yes vs no) 1.67 (1.49, 1.88) <0.0001 1.39 (1.15, 1.67)   0.0006
Child behavioral issues (yes vs no) 1.69 (1.33, 2.16) <0.0001 1.83 (1.56, 2.14) <0.0001
Child neurologic conditions (yes vs no) 2.09 (1.33, 3.27)   0.001 1.31 (0.91, 1.87)   0.14
Child developmental conditions (yes vs no) 1.44 (1.11, 1.86)   0.001 1.05 (0.72, 1.55)   0.78
Child genetic conditions (yes vs no) 1.50 (1.16, 1.93)   0.002 1.33 (1.06, 1.67)   0.02
Child other conditions (yes vs no) 1.06 (0.96, 1.18)   0.23             –     –
Neonatal complications
 Major 1.34 (1.04, 1.73)   0.02 1.13 (1.03, 1.25)   0.008
 Minor 0.99 (0.82, 1.20)   0.93 1.03 (0.83, 1.29)   0.75
 None 1.00 1.00
Labor complications
 Major 1.05 (0.67, 1.65)   0.84 0.89 (0.53, 1.48)   0.64
 Minor 1.34 (0.98, 1.84)   0.07 1.22 (0.89, 1.67)   0.21
 None 1.00 1.00
Plurality (yes vs no) 0.94 (0.74, 1.20)   0.64             –     –
Mode of delivery (C-section vs vaginal) 1.32 (1.12, 1.56)   0.0003 1.52 (1.24, 1.86) <0.0001
Maternal medical conditions during pregnancy (yes vs no) 1.20 (1.01, 1.42)   0.03 1.03 (0.85, 1.11)   0.63
Maternal depression during pregnancy (yes vs no) 1.22 (0.90, 1.66)   0.20 0.93 (0.64, 1.34)   0.68
Maternal mental retardation during pregnancy (yes vs no) 1.54 (1.10, 2.16)   0.01 0.91 (0.62, 1.31)   0.60
Maternal anxiety during pregnancy (yes vs no) 1.47 (1.22, 1.76) <0.0001 1.34 (0.86, 2.09)   0.19
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PR: prevalence ratio; aPR: adjusted prevalence ratio; CI: confidence interval; IQ: intelligence quotient.

*

All variables with p values from univariable analysis that are shown in bold were included in the multivariable model.

**

All variables with p values from multivariable analysis that are shown in bold were significantly associated with SIB.

Table 3.

Associations between report of ever exhibiting self-injurious behaviors (SIB) and risk and protective factors in the Study to Explore Early Development (SEED).

Variable Univariable analyses*
Multivariable analyses**
PR and 95% CI p value aPR and 95% CI p value
Child sex (female vs male) 0.82 (0.64, 1.05)   0.12 0.77 (0.59, 1.00)   0.05
Child age (1 month) 1.01 (0.99, 1.02)   0.20 1.01 (0.99, 1.02)   0.12
Gestational age (1 week) 0.99 (0.97, 1.01)   0.12 0.98 (0.97, 0.99)   0.003
Birth weight (1 gram) 0.98 (0.94, 1.03)   0.41             –     –
Non-White vs White maternal race 0.77 (0.63, 0.94)   0.01 0.71 (0.57, 0.88)   0.002
Hispanic vs non-Hispanic Maternal ethnicity 1.03 (0.82, 1.29)   0.81             –     –
Language spoken at home (other vs English) 0.82 (0.66, 1.02)   0.07 0.91 (0.72, 1.15)   0.41
Maternal level of education (no college degree vs college) 1.38 (1.24, 1.55) <0.0001 1.05 (0.93, 1.18)   0.40
Maternal smoking (yes vs no) 1.21 (1.08, 1.36)   0.001 0.96 (0.85, 1.09)   0.53
Maternal age at birth (years) 0.94 (0.92, 0.97) <0.0001 0.98 (0.97, 0.99)   0.0004
Family income (quartiles)
 Lowest 1.56 (1.23, 1.99)   0.0003 1.19 (0.91, 1.56)   0.20
 Second lowest 1.17 (1.06, 1.29)   0.002 1.02 (0.95, 1.09)   0.56
 Middle 1.05 (0.97, 1.14)   0.22 1.00 (0.88, 1.14)   0.95
 Highest 1.00   1.00 1.00   1.00
Regression (yes vs no) 1.06 (0.96, 1.17)   0.28             –     –
IQ score (1 unit) 0.99 (0.97, 0.99)   0.0006 1.00 (0.99, 1.01)   0.11
Adaptive score (1 unit) 0.97 (0.96, 0.99) <0.0001 0.99 (0.98, 0.99) <0.0001
Sleep score (1 unit) 1.02 (1.01, 1.03) <0.0001 1.01 (1.00, 1.02)   0.02
Autism severity score (1 unit) 0.99 (0.95, 1.04)   0.80             –     –
Sensory problems (yes vs no) 1.42 (1.12, 1.81)   0.0004 1.24 (0.97, 1.59)   0.08
Gastrointestinal problems (yes vs no) 1.34 (1.21, 1.47) <0.0001 1.21 (1.07, 1.36)   0.003
Child behavioral issues (yes vs no) 1.73 (1.50, 1.99) <0.0001 1.57 (1.35, 1.83) <0.0001
Child neurologic conditions (yes vs no) 1.35 (1.11, 1.65)   0.003 1.09 (0.89, 1.35)   0.40
Child developmental conditions (yes vs no) 1.26 (1.11, 1.43)   0.005 1.01 (0.79, 1.28)   0.97
Child genetic conditions (yes vs no) 1.05 (0.66, 1.66)   0.50             –     –
Child other conditions (yes vs no) 1.09 (0.83, 1.43)   0.53             –     –
Neonatal complications
 Major 1.05 (0.88, 1.25)   0.44             –
 Minor 0.88 (0.70, 1.12)   0.30             –
 None 1.00
Labor complications
 Major 1.05 (0.88, 1.25)   0.57
 Minor 1.00 (0.82, 1.22)   0.98             –
 None 1.00
Plurality (yes vs no) 1.02 (0.88, 1.18)   0.78             –     –
Mode of delivery (C-section vs vaginal) 0.93 (0.79, 1.10)   0.41             –
Maternal medical conditions during pregnancy (yes vs no) 1.10 (1.05, 1.27)   0.21
Maternal depression during pregnancy (yes vs no) 1.28 (1.14, 1.45) <0.0001 1.08 (0.90, 1.30)   0.40
Maternal mental retardation during pregnancy (yes vs no) 1.56 (1.36, 1.80) <0.0001 1.13 (0.85, 1.50)   0.41
Maternal anxiety during pregnancy (yes vs no) 1.16 (1.07, 1.26)   0.0006 0.98 (0.84, 1.13)   0.74
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PR: prevalence ratio; aPR: adjusted prevalence ratio; CI: confidence interval; IQ: intelligence quotient.

*

All variables with p values from univariable analysis that are shown in bold were included in the multivariable model.

**

All variables with p values from multivariable analysis that are shown in bold were significantly associated with SIB.

The comparisons of the proportions of children with parent-reported current SIB and ever SIB, respectively, to the proportions with observed SIB and the corresponding Kappa statistics are presented in Tables 4 and 5. Parents were more likely to report current SIB (28%) and ever SIB (47%) compared to clinician observation of SIB (6%). The concordance of responses from parents (SIB; yes/no) and clinician observation (yes/no) was 72. 25% for current SIB (i.e. 3.32% for yes and 68.93% for no) and 55.49% for ever SIB (i.e. 4.77% for yes and 50.72% for no).

Table 4.

Agreement between clinician’s documentation of self-injurious behaviors (SIB) and parental report of current SIB in children included in the Study to Explore Early Development (SEED).

SIB in ADI-R: yes SIB in ADI-R: no Total p value Kappa and 95% CI
SIB in ADOS: yes   23 (3.32)   21 (3.03)   44 (6.36)
SIB in ADOS: no 171 (24.71) 477 (68.93) 648 (93.64) <0.0001 0.10 (0.04, 0.16)
Total 194 (28.03) 498 (71.97) 692
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ADI-R: Autism Diagnostic Interview–Revised; ADOS: Autism Diagnostic Observation Schedule; CI: confidence interval.

Table 5.

Agreement between clinician’s documentation of self-injurious behaviors (SIB) and parental report of ever had SIB in children included in the Study to Explore Early Development (SEED).

SIB in ADI-R: yes SIB in ADI-R: no Total p value Kappa and 95% CI
SIB in ADOS: yes   33 (4.77)   11 (1.59)   44 (6.36)
SIB in ADOS: no 297 (42.92) 351 (50.72) 648 (93.64) <0.0001 0.07 (0.03, 0.11)
Total 330 (47.69) 362 (52.31) 692
Open in a new tab

ADI-R: Autism Diagnostic Interview–Revised; ADOS: Autism Diagnostic Observation Schedule; CI: confidence interval.

Discussion

We found five factors—adaptive behaviors scores, gastrointestinal, sleep and behavioral problems, and younger maternal age—to be associated with both current and ever SIB. We also documented that parents reported SIB far more often than clinicians observed SIB.

Our findings were similar to those reported by Soke et al. (2017) concerning the association between SIB and low adaptive scores, sleep and behavioral problems, and abnormalities in sensory processing. These authors examined the potential factors associated with SIB in a study that included large samples of children with ASD from two national databases in the United States and discussed possible mechanisms explaining the associations between SIB and the above factors (see Soke et al., 2017 for details). In line with reports from past studies (Devine, 2014; Duerden et al., 2012; Kurtz et al., 2003; Soke et al., 2017), the associations between SIB and the above factors may indicate that, in some children with ASD, SIB may have specific functions, including communication (e.g. expression of pain or discomfort), social interaction (e.g. attention), and self-regulation.

Like others (Buie et al., 2010; Christensen et al., 2009; Kennedy and Thompson, 2000, as cited by Thompson and Caruso, 2002), we documented an association between gastrointestinal problems and SIB although this was not found in several other studies (Kang et al., 2014; Maenner et al., 2012; Soke et al., 2017). It is possible that variability in the definition of “gastrointestinal problems” may explain this difference. Nevertheless, this association is consistent with the hypothesis that in children with limited verbal abilities, SIB may be a way to express pain associated with gastrointestinal conditions (e.g. constipation, acid reflux; Kennedy and Thompson, 2000, as cited by Thompson and Caruso, 2002).

The presence of known genetic conditions, higher IQ scores, younger maternal age, and cesarean delivery were significantly related to current SIB; male child sex, non-Hispanic White race and younger age of the mother, and lower gestational age were associated with ever SIB. The association between genetic conditions with current SIB has been reported by others (Moss et al., 2012; Symons et al., 2003) and may be due to biological perturbations (e.g. neurotransmitter activity) found in these genetic conditions. Unlike most studies (e.g. Duerden et al., 2012; Minshawi et al., 2014a), we found a positive relationship between IQ scores and current SIB. Most studies have categorized IQ and did not adjust for numerous child and familial factors, as we did, which may explain the discrepancy. It is also possible that children with low cognitive skills have substantial delays resulting in decreased ability to engage in SIB. The associations of current SIB with lower maternal age and cesarean delivery, and of ever exhibiting SIB with younger maternal age, male child sex, lower gestational age, and non-Hispanic white maternal race, have not been previously identified and require replications in future studies. While these associations may have resulted from chance alone, different hypotheses may also explain these findings. For example, the association between younger maternal age and increased prevalence of both current and ever SIB may be due to the association between maternal younger age and perinatal or post-natal complications, such as preterm birth, low birth weight, and growth retardation (Fall et al., 2015). It is also possible that other factors, such as poverty, high levels of stress, low educational attainment, barriers in access to specialty services, and limited coping skills and knowledge of typical child development, may negatively affect the quality of mother–child interactions and result in the occurrence of SIB, or may instead influence the accuracy of reporting of SIB on the ADI-R. We found a higher prevalence of SIB among children born from cesarean delivery than those born vaginally. It is possible that cesarean mode of delivery is a marker for suboptimal perinatal environment (e.g. placental insufficiency, congenital malformations) that may result in brain insults leading to SIB. Like us, Walker et al. (2015) reported similar associations between developmental delays and perinatal complications.

In contrast to results from most past studies (Horovitz et al., 2011; Jang et al., 2013; Sell et al., 2012), we found that children with parent-reported ever SIB were less likely to have a mother who was of minority race. This discrepancy may be due to differences in the definition of race used between studies, as we examined maternal rather than child race. It is also possible that these findings reveal true racial differences in SIB prevalence, since other studies have documented similar racial differences in the occurrence of attention, anxiety, and lack of or excessive fearfulness (Hartley et al., 2008; Sell et al., 2012). Furthermore, unlike most studies (Baghdadli et al., 2003; Rubenstein et al., 2015), we found a higher prevalence of ever SIB in males compared to females. Past studies may have had insufficient power to find differences by sex, or our findings may indicate true differences similar to those reported for other challenging behaviors, such as aggression (Giarelli et al., 2010). The prevalence of ever SIB decreased with an increased gestational age. Since prematurity can be associated with developmental delays (Kerstjens et al., 2012), it is possible that brain immaturity may play an important role in the occurrence of SIB.

We found a higher prevalence of SIB reported by parents than was observed by clinicians. The concordance of the presence of SIB between parents and clinicians was low for both current and ever SIB. In most cases, parents reported SIB that were not identified by the clinician. However, in a few instances, clinician observed SIB while parents had not reported it. The discrepancy between parents and clinicians may be due to a number of reasons. Clinicians documented SIB during a 30- to 40-min assessment with the child interacting with an unfamiliar adult in an unfamiliar place. This may not allow sufficient time for the child to display SIB; conversely, this novel environment might elicit SIB as a way for the child to avoid the interaction with the clinician. In contrast, parents’ answers on the ADI-R are based on a much longer period of observing the child in a typical environment. It is also possible that parents reported even minor forms of SIB, which may not be considered as SIB by clinicians. On the other hand, some parents may also fail to report SIB during the interview, due to a number of reasons, including lack of awareness or understanding of SIB, embarrassment, or some other factors. The lower proportion of children identified by clinicians as having SIB can also explain why the factors related to SIB reported in the ADI-R were not significantly related to SIB recorded in the ADOS.

There are a number of strengths to the study: (1) the use of a large sample of children with ASD identified through both clinical and educational sources, some of whom were not previously identified, and diagnosed using the current standards; (2) testing of a wide range of predictors, including prenatal and perinatal factors; and (3) use of standardized instruments to assess SIB and other factors. Nevertheless, some limitations are noted. The SEED network included only six sites in the United States and these sites are not representative of all US children with ASD. Thus, these findings may not be generalizable to communities that were not included in this study. We could not infer a temporal relationship between SIB and the factors evaluated, since we used a cross-sectional design. Among children whose SIB were only reported by clinicians and not by parents, it was not possible to assess if these behaviors were only seen during the ADOS, or if they persisted thereafter. The differences in the proportion of children with current versus ever SIB may have resulted from over-reporting of ever SIB, since parents may have reported transient SIB, which has been documented in both children with developmental disabilities and typically developing children at a very young age (Berkson and Tupa, 2000; Symons et al., 2005). It is also important to point out that SIB and associated factors such as sleep, gastrointestinal, behavior issues were all based from parent reports, raising the possibility of method variance. High levels of parental stress may have resulted in over-reporting of both SIB and other factors. As documented above, the observation of the child during the ADOS is of short duration and may limit the possibility for clinicians to detect SIB that may regularly occur in the house and reported by parents. This may explain the large discrepancy between parent-reported SIB and clinician observation.

Findings from this study support the need for a comprehensive and multidisciplinary approach for assessing and managing SIB in ASD, as has been suggested by our research group and others (Isaksen et al., 2013; Minshawi et al., 2014b; Soke et al., 2017). In the presence of SIB, comprehensive assessment rather than a priori consideration of SIB as behaviorally induced can detect any potential condition that may explain the occurrence of SIB. The co-occurrence of other behavioral problems (e.g. aggression) with SIB may provide an opportunity for clinicians to ask questions about the presence of SIB. Furthermore, as discussed by Soke et al. (2017), our findings suggest that providing interventions that target communication skills, behavioral issues, or sleep or gastrointestinal problems may help prevent SIB in some children and also improve their overall level of function and quality of life. We also identified a number of new associations that merit further evaluation in future studies. Longitudinal etiologic studies, which may collect data on some of the factors identified here and include direct observation of the child for a longer duration and in a number of different settings (e.g. clinic, house, school), are needed in order to establish the temporality of the associations identified and the validity of parent-reported SIB. In summary, SIB is an important public health problem in individuals with ASD, and these findings can be used to inform future research and potentially improve the management of SIB in children with ASD, which will positively affect the quality of life of children with SIB and their families.

Supplementary Material

Supplemental Tables

Acknowledgments

We would like to thank SEED principal investigators, co-principal investigators, scientists, and project staff at each participating site. We also thank all children and families who participated in this study.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This publication was supported by six cooperative agreements from the Centers for Disease Control and prevention: Cooperative Agreement Number U10DD000180, Colorado Department of Public Health; Cooperative Agreement Number U10DD000181, Kaiser Foundation Institute (CA); Cooperative Agreement Number U10DD000182, University of Pennsylvania; Cooperative Agreement Number U10DD000183, Johns Hopkins University; Cooperative Agreement Number U10DD000184, University of North Carolina at Chapel Hill; and Cooperative Agreement Number U10DD000498, Michigan State University. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

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