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Pediatrics. 2011 November; 128(5): 883–891.
PMCID: PMC3208957

Prevalence of Autism Spectrum Disorder in Adolescents Born Weighing <2000 Grams



To estimate the diagnostic prevalence of autism spectrum disorders (ASDs) in a low birth weight (LBW) cohort.


Participants belonged to a regional birth cohort of infants (N = 1105) born weighing <2000 g between October 1, 1984, and July 3, 1989, and followed up by periodic assessments to 21 years of age. At 16 years (n = 623), adolescents were screened for ASD using a wide net (previous professional diagnosis of an ASD or a score above a liberal cutoff on the Social Communication Questionnaire or the Autism Spectrum Symptoms Questionnaire). At 21 years (n = 189), 60% of screen positives and 24% of screen negatives were assessed for diagnoses of ASD by the Autism Diagnostic Observation Schedule or the Autism Diagnostic Interview–Revised.


Samples retained at ages 16 and 21 years were representative of samples assessed at earlier ages except for lower levels of social risk. Of positive screens, 11 of 70 had ASD; of negative screens, 3 of 119 had ASD. The fractions of the 2 screening groups with ASD (14.3% in screen-positives and 2.5% in screen negatives) were weighted by fractions of screen-positives and screen-negatives among the adolescents (18.8% and 81.2%, respectively). This calculation produced an estimated prevalence rate of ASD in the entire cohort of 5% (31 of 623).


The diagnostic prevalence of ASD in this LBW preterm cohort was higher than that reported by the Centers for Disease Control and Prevention for 8-year-olds in the general US population in 2006.

Keywords: low birth weight, preterm, autism spectrum, screening, diagnosis, outcome


Low birth weight and/or prematurity are considered to be risk factors for autism spectrum disorders, largely on the basis of retrospective studies or prospective studies that have used screening rather than diagnostic instruments.


This is the first study of the prevalence of autism spectrum disorders in a prospectively followed low birth weight population using validated diagnostic instruments. The 5% estimated prevalence rate found was ~5 times the rate reported in the general population.

Low birth weight (LBW) and prematurity are established risk factors for cognitive and motor disability.1,2 The prevalence of neurodevelopmental impairment increases with diminishing birth weight and gestational age.3 As survival of the smallest and most immature infants improves, impaired survivors represent an increasing public health challenge.

Emerging evidence suggests that LBW may also be a risk factor for autism spectrum disorders (ASDs). Retrospective studies have suggested an association between LBW and/or preterm birth and risk for ASD.410 Prospective studies in children1113 and adolescents3,1416 have supported this suggestion. Most prospective studies, however, have determined risk for ASD on the basis of screening instruments rather than a definitive diagnosis. Only 1 prospective study to date has assessed the actual diagnostic prevalence of ASD in children born prematurely.17,18 In that study, 219 parents of 11-year-olds born at the extremely low gestational age of <26 weeks in the United Kingdom and Ireland were interviewed by telephone or responded to an online survey of a multipurpose structured psychiatric interview, the Development and Well-being Assessment (DAWBA).19 Using this instrument, the prevalence of ASD in births <26 weeks was reported to be 8%. Such extreme prematurity, however, affects <0.25% of all US births.20

This report presents the screening and diagnostic prevalence of ASD in a large population-representative cohort of adolescents born weighing between 500 and 2000 g, a weight interval that represents ~3% of US births.21


Neonatal Brain Hemorrhage Study Cohort

The study sample was drawn from the Neonatal Brain Hemorrhage Study (NBHS) cohort, consisting of all infants admitted to 3 hospitals that together cared for 85% of births <2000 g in 3 central New Jersey counties from October 1, 1984, to July 30, 1987.22 At that time, these 3 counties were demographically comparable to the nation as a whole, except for having a slightly higher per capita income and slightly lower proportion of minorities.22 This cohort was prospectively enrolled at birth and reassessed at ages 2,23,24 6,25,26 9,27,28 16,29,30 and 21 years. All enrolled families spoke English.

Two-Stage Design and Sampling Methods

The prevalence of ASD in the NBHS cohort was estimated by using a 2-stage design. In the first stage, a screening for ASD using parent questionnaires was conducted at the 16-year follow-up. In the second stage, at the 21-year follow-up, a diagnostic assessment for ASD was conducted with young adults recruited from all those who screened positive in the first stage and from a systematically obtained sample of those who screened negative in the first stage. Lists of screened negative potential recruits were initially selected at random in batches on the basis of year of birth (to ensure minimum appropriate age of participants), stratified according to gender to match the male:female ratio of screen-positives for that birth year. When numbers of screen-negative recruits fell short for a given birth year, additional recruits were drawn from all remaining screen-negatives of the appropriate gender without respect to birth year.

First Stage: Screening Procedure for ASD (at 16 Years of Age)

As part of a larger psychiatric follow-up,29 adolescents were assessed for symptoms of ASD by using the Social Communication Questionnaire (SCQ), previously known as the Autism Screening Questionnaire,31 and the Autism Spectrum Screening Questionnaire (ASSQ).32 Adolescents' parents were also asked whether a professional had ever diagnosed their child with an ASD (autism, Asperger syndrome, or pervasive developmental disorder [not otherwise specified]). Screening data were obtained primarily by questionnaires collected at a home visit (499 [80%]) and the remainder by mail and/or telephone (127 [20%]).

A participant in the 16-year follow-up was considered “screen-positive” if he or she met any of the following criteria: (1) a score of ≥9 on the SCQ; (2) a score of ≥12 on the ASSQ; or (3) a history of professional diagnosis of ASD. The screen was designed to cast as wide a net as possible, so the cutoff points used were lower than the customary cutoff points of 15 for the SCQ31 and 22 for the ASSQ.32

Second Stage: Recruitment and Diagnostic Procedure

Young adults were located by using tracking information available from earlier follow-ups; when necessary, Accurint, a national tracking system, was used. In some cases, parents facilitated contact.

The diagnostic instruments used were: (1) the Autism Diagnostic Interview–Revised (ADI-R)33 (administered to parents); and (2) the Autism Diagnostic Observation Schedule (ADOS, module 4) (administered to the young adults).34 Both the ADIR and the ADOS are well-validated instruments widely used in research. The validity of these tools may be compromised in the circumstance of severe to profound disability (eg, mental age < 2 years).35,36 In this circumstance, additional information obtained from clinical history can be combined with information from the ADI-R and/or ADOS to inform a best-estimate diagnosis using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria.37 Two research associates, who were blind to screening status and research reliable in the administration and scoring of the diagnostic instruments, completed the assessments under the supervision of the director of the Regional Autism Center (Dr Levy). In-person assessments took place at the Children's Hospital of Philadelphia or at the Children's Hospital of Philadelphia Specialty Care Center in Princeton, New Jersey. For the ADIR, scores needed to be above published threshold scores on each of 4 domains: (1) reciprocal social interaction; (2) communication; (3) restricted, repetitive, stereotyped patterns of behavior; and (4) abnormality of development evident at or before 36 months.38 For the ADOS, the total score on the communication and social domains needed to be above the published threshold for an ASD.39

Of the total 189 patients evaluated at 21 years of age, data were available from both the ADOS and the ADI-R on 144 (76%). An additional 75 had data from either the ADOS alone (n = 10) or the ADI-R alone (n = 65). Most of those evaluated with the ADIR alone (n = 62) had distance or scheduling issues that precluded an in-person ADOS evaluation; the remaining 3 patients were evaluated only by parental interview using the ADI-R because they were severely disabled.

Human Subjects Consideration

This study was approved by the institutional review board of the Children's Hospital of Philadelphia and the New York State Psychiatric Institute. Consent was obtained from the participating young adults (or their legal guardians, as applicable) and their families.

Statistical Analysis

Two sets of analyses addressed attrition issues. The first set compared those who were screened as adolescents to the remaining eligible adolescents on basic sample characteristics shown in Table 1 using t tests for continuous measures and χ2 tests for categorical ones. The second set determined whether sample loss between adolescence and young adulthood was conditional on ASD screening status. These analyses were conducted using 2 (positive versus negative screen status) by 2 (retained in sample versus not retained) analysis of variances (for continuous dependent measures), logistic regressions (for dichotomies), and multinomial regressions (for categorical variables having >2 categories). Significant interactions and main effects are reported; consistent with general statistical practice, follow-up comparisons between retention groups within screen status strata were only undertaken where there were significant interactions.

Sample Characteristics: LBW Adolescents Screened for ASD at 16 Years of Age and Others Eligible but Not Screened for ASD at 16 Years of Age

Prevalence in the entire cohort was calculated by weighting the proportions of screen-positives and screen-negatives found to have ASD as young adults by the proportion of screen-positives and screen-negatives in the adolescent sample.

The relation of the ASD diagnosis to basic sample characteristics was examined by using χ2 statistics. SPSS software40 was used for all analyses; the criterion for statistical significance was set at a 2-tailed α value of 0.05.


Sample Attrition

Figure 1 shows the attrition of the sample from birth to young adulthood. By 16 years of age, 862 adolescents were considered eligible for follow-up; of these, 628 participated. All but 5 participating families completed the autism screening instruments at that time, leaving a final sample of 623 (72%; Fig 1). Of these, 80.7% completed all 3 parts of the screen and very few (8.0%) completed only 1 part. At 21 years of age, 60% of the screen-positive group (n = 70) was evaluated for an ASD diagnosis at 21 years of age (Fig 1), whereas 40% (n = 47) were lost to follow-up because of inability to contact (n = 11), inability to schedule because of time/distance constraints (n = 27), or refusal (n = 9).

Sample attrition.

Table 1 shows the characteristics of adolescents screened for ASD and those eligible but not screened at 16 years of age. The 2 groups differed significantly only with respect to lower maternal social risk at birth in those screened.

Table 2 shows the characteristics of those who were and were not retained in the sample from 16 to 21 years of age according to screen status. These data address the possibility that characteristics of those retained (versus not retained) were dependent on screen status. With the exception of 1 component of maternal birth social risk (ie, receipt of public assistance), this was not the case. For this 1 variable, there was a significant interaction between screen status and sample retention (Wald χ21 = 4.92, P = .027) such that there was a greater discrepancy between retained and not-retained among the screen-positives, although those retained had lower percentages of those receiving public assistance in both groups (Table 2 legend).

Birth Risk Factors and 16-Year Neurodevelopmental Status in Screen-Positives and Screen-Negatives According to Sample Retention From 16 to 21 Years

Significant main effects of retention, irrespective of screen status, were all in the expected direction, namely that those not retained in the sample at 21 years of age (n = 434) were more likely than those retained in the sample (n = 189) to be at greater risk for suboptimal neurodevelopmental outcomes (Table 2 legend).

Significant main effects of screen status, irrespective of sample retention, were similarly all in the same direction. Those who screened positive at 16 years of age (n = 117) compared with those who screened negative (n = 506) were more likely to be at greater risk for suboptimal neurodevelopmental outcomes (Table 2 legend). Notably, however, boys were only marginally more common among the screen-positives (56.4%) than among the screen-negatives (47.6%; P < .10), indicating that the gender matching of screen-negatives to screen-positives was fairly successful. Another important characteristic of the screen positive and screen-negative samples (data not shown in Table 2)—namely, the percentage of families in each group who were interviewed by telephone because of scheduling and distance issues—also did not differ across the groups (32.9% and 34.5%, respectively).

Screening Prevalence at 16 Years of Age

Of the 623 adolescents screened for ASD, 117 (18.8%) were screen-positive by 1 or more of the 3 screening criteria. Of the 117 screen-positives, 62 were positive on the SCQ alone, 26 were positive on the ASSQ alone, and 6 were positive solely by parent report of a professional diagnosis. Sixteen were positive on 2 parts, and 7 were positive on all 3 parts of the screen.

Diagnostic Prevalence of ASD

Of the 70 young adults examined who were screen-positive as adolescents, 11 were found to have ASD (Table 3). Of the 119 screen-negatives, 3 were found to have ASD.

Estimated Prevalence of ASD in Total Cohort (N = 623) Based on Findings in 198 Participants With Diagnostic Assessment at 21 Years of Age

To estimate the prevalence of ASD cases in the original sample of 623 adolescents, the numbers of young adults found to have ASD in the 2 screening groups (14.3% among the screen-positives and 2.5% among the screen-negatives) were weighted by the fractions of screen-positives and negatives among the adolescents (18.8% and 81.2%, respectively) as shown in Table 3. Thus, the best estimate of the prevalence of ASD in the entire adolescent LBW cohort is 5.0% (31 of 623).

Characteristics of the Cases

Of the 14 cases, 3 were screen-negative as adolescents and 11 were screen-positive (Table 4). All 14 cases had an ADI-R completed by a parent. Six did not have ADOS scores; 5 of these could only be interviewed by telephone, precluding an ADOS assessment, and 1 was assessed using the ADOS, but the results were considered invalid because of physical disability. Of the 8 cases with a completed ADOS, 2 met the threshold on both the ADI-R and ADOS, 1 on only the ADI-R, and the rest on only the ADOS.

Characteristics of the ASD Cases

The overall male to female gender ratio was 3.7:1 (11 boys, 3 girls). Sixty-four percent (9 of 14) were relatively high functioning and verbal (ie, phrase speech and IQ ≥70). Of the 11 cases who were screen-positive in adolescence, 6 were reported to have been diagnosed with ASD by a professional and 5 had not. For these 11 subjects, scores on the Weschler Abbreviated Scale of Intelligence at 16 years of age ranged widely, from 50 (the default score for those too cognitively impaired to be tested) to 112; their Vineland scores also varied widely, ranging from 32 to 81. By contrast, of the 3 cases who screened negative in adolescence, all IQ scores were at least 1 SD above the mean (≥115), whereas Vineland composite scores ranged from 85 to 95. None of these 3 cases met threshold on the ADI-R. Six of the 14 cases (42.9%) met criteria for at least 1 other psychiatric disorder at 16 years of age on the basis of a validated psychiatric interview.30

None of the basic sample characteristics in Table 1 were significantly related to a diagnosis of ASD, although there were marginal relations for gender and birth weight (P < .10). The percentage of boys having a diagnosis of ASD (9.9%) was larger than that of girls having a diagnosis (3.3%; χ21 = 3.32, P = .07). In addition,10.6% of those born weighing <1500 g had an ASD diagnosis compared with only 3.7% of those born weighing between 1500 and 2000 g (χ21 = 3.68, P = .055).


This is the first study to have estimated the prevalence of ASD in a prospectively followed LBW population using research-validated diagnostic instruments. ASD prevalence in this US population-representative cohort of LBW (<2000 g) adolescents was estimated to be 5%, a fivefold increase over that reported by the Centers for Disease Control and Prevention for 8-year-olds in the US general population in 2006 (0.9%).41 In addition, we found that 18.8% of the adolescents screened positive for ASD. Screening criteria were designed to maximize sensitivity, contributing to the high false-positive rate encountered. Nonetheless, 2.5% of those with ASD, notably high-functioning boys, were not picked up on screening.

As a group, the 14 subjects with ASD diagnosed in young adulthood seemed to be relatively high functioning in terms of IQ and spoken language. The proportion (63%) with an IQ of ≥70 (at least borderline intelligence) was higher than that of a recent population estimate of 45% for school-aged cases of ASD.42 All of the cases here had developed phrase speech, which has recently been reported as absent in 10% to 20% of persons with ASD.43 One possible reason for these apparent differences is that ASD associated with prematurity has a distinctive neurodevelopmental profile. Alternatively, a number of additional low-functioning ASD cases might have been diagnosed had the retention rate in the screen-positive group been greater. The greater retention of those with less overall social risk is consistent with this possibility. Addressing these alternative possibilities is beyond the scope of this report.

Prospective studies have reported high screening prevalence in LBW and/or premature toddlers ranging from 21%13,44 to 37%12 using the Modified Checklist for Autism in Toddlers. In prospective cohorts of older children (11 and 14–15 years), the screening prevalence was not quite so high (<1% to 3.7%), but some studies did not use autism-specific screens.16,45,46 Johnson et al17 recently reported screening and diagnostic prevalence of ASD of their prospective cohort of all births <26 weeks in 1995 in the United Kingdom and Ireland. Of the survivors, 71% were assessed at 11 years using the SCQ screening instrument and a clinical best estimate diagnostic package, the DAWBA. Screening prevalence was 15.8%, comparable to that found in our study. Diagnostic prevalence was 8%. It is not clear whether restriction of the Johnson et al sample to extremely low gestational age survivors and/or features of the DAWBA account for the higher diagnostic prevalence rate in their study.

To date, the only epidemiologic study to estimate prevalence rates of ASD in adults born prematurely is that of Moster et al.2 Using linked compulsory national registries in Norway, they found that the rates of disability payments for ASD among adults 20 to 36 years old in 2003 (born between 1967 and 1983) rose significantly as gestational ages declined. Rates in that study rose from 0.05% among those born at term (gestational age ≥ 37 weeks) to 0.6% among those born at gestational ages of 23 to 27 weeks. Although these rates were considerably lower than the 5% found here, the inverse relation of gestational age to ASD of sufficient severity to warrant disability payments in adulthood highlights the long-term public health impact of prematurity on ASD-associated disability.


In this study, rigorous diagnostic procedures were used to estimate the diagnostic prevalence of ASD in AN LBW population. Given that the present cohort was not restricted to those at the lower extremes of birth weight and gestational age, generalizability of our findings is broader than is often the case in LBW/preterm follow-up studies. Moreover, because this cohort is population based, findings are likely to have greater generalizability than those from hospital-based cohorts.


The proportion lost to follow-up over the 5-year period between the adolescent and young-adult follow-up was relatively high. However, the differences in characteristics between those retained in the young adult sample versus those not retained were, for the most part, the same among those who screened positively and negatively in adolescence. Some adolescents did not receive all parts of the 3-part screen. In addition, not all young adults were assessed using both the ADIR and ADOS. ASD diagnosis at an earlier follow-up age might have increased participant availability for the in-person ADOS evaluations. Finally, the lack of a normal birth weight control group allowed comparison only with general population estimates of ASD prevalence.


The estimated prevalence of ASD diagnoses in this LBW cohort was 5 times the prevalence reported by the Centers for Disease Control and Prevention for 8-year-olds in the general US population in 2006. This prospective study, using rigorous diagnostic procedures, confirms that the rate of ASD is elevated among LBW/preterm survivors.


Funding for this study was provided by National Institutes of Health grant R01MH073807 (to Dr Pinto-Martin, primary investigator) (March 1, 2009, to February 28, 2010, to Drs Pinto-Martin and Levy; subcontract to Dr Whitaker, primary investigator, at Columbia University; to Drs Lorenz and Feldman; and to Dr Paneth, primary investigator, at Michigan State).

Administrative, technical, and material support was provided by Catherine Christman. Research clinical evaluations of the young adult participants were conducted by Michelle Petrongolo, MS, and Megan Carolan Tomkinson, MEd, from the Children's Hospital of Philadelphia. They received no compensation other than salary support through the grant.

Dr Pinto-Martin (the principal investigator) had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Pinto-Martin, Paneth, Levy, Whitaker, and Feldman were responsible for study concept and design; Drs Pinto-Martin, Paneth, Levy, and Whitaker performed the acquisition of data; Drs Feldman and Paneth conducted the statistical analysis; Drs Pinto-Martin, Paneth, and Whitaker obtained funding; and all authors were responsible for analysis and interpretation of data, drafting of the manuscript, and critical revision of manuscript for important intellectual content.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

Funded by the National Institutes of Health (NIH).

low birth weight
autism spectrum disorder
Development and Well-being Assessment
Neonatal Brain Hemorrhage Study
Social Communication Questionnaire
Autism Spectrum Screening Questionnaire
Autism Diagnostic Interview–Revised
Autism Diagnostic Observation Schedule


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