epidemiology and the changing paradigm of autism ... and the changing paradigm of autism spectrum...

Epidemiology and the Changing

Paradigm of Autism Spectrum

Disorders

9th Annual Developmental Disabilities Conference

UCSF

March 11, 2010

Marshalyn Yeargin-Allsopp, MD

Medical Epidemiologist

Chief, Developmental Disabilities Branch

National Center on Birth Defects and

Developmental Disabilities

Centers for Disease Control and Prevention

Overview

What is Public Health Surveillance?

What is Prevalence?

Changes in ASD diagnostic classification systemsover time

Changes in ASD prevalence estimates over time

Use of different surveillance methods

ADDM Network

Overview

New prevalence estimates

Future directions

Bottom Line: Why is the current prevalence of ASDhigher than previously reported?

Public health surveillance is the

systematic, ongoing assessment

of the health of a community,

based on the collection,

interpretation, and use of health

data and information.

Surveillance provides information

necessary for public health

decision making. *

* Teutsch SM, Churchill RE. Principles and practice of

public health surveillance: 2nd ed. Oxford University

Press. 2000.

Public Health Surveillance

What is Prevalence?

Prevalence= Number of instances of a

condition in a given population at a designated

time.

Calculated as: number of instances of condition

Total number of people in the given

population

Changes in ASD Diagnostic

Classification Systems Over Time

Kanner criteria (1956)

Lack of affective contact; desire forsameness; fascination with objects;mutism or non-communicativelanguage before 30 months of age

Autism Prevalence & Epidemiologic

Studies: Kanner Criteria

Author Rate/1,000

(95% CI)

No. Children with

Autistic Disorder

# children in

population

M/F

Ratio

IQ < 70

%

Lotter, 1966

(England)

0.45

(0.31-0.62)

35 78,000 2.6 84

Brask, 1972

(Denmark)

0.43

(0.26-0.66)

20 46,500 1.5 NR

Treffert, 1970

(USA)

0.07-0.31

(0.0-1.0)

69 899,750 3.0 NR

Wing & Gould, 1979

(England)

0.49

(0.29-0.78)

17 34,700 16.0 70

Hoshino et al.,1982

(Japan)

0.23

(0.19-0.27)

142 609,848 9.9 NR

McCarthy et al., 1984

(Ireland)

0.43

(0.29-0.59)

28 65,000 1.3 NR



Rutter criteria (1978)

Emphasized delayed and unusualsocial and language development andearly onset and unusual behaviors

Author Rate/1,000

(95% CI)

No. Children

with Autistic

Disorder

# children in

population

M/F

Ratio

IQ < 70

%

Ishii & Takahashi, 1983

(Japan)

1.6

(1.2-2.8)

56 35,000 6.0 NR

Bohman et al.

1983 (Sweden)

0.3

(0.2-0.5)

39 69,000 1.6 NR

Steinhausen et al.,

1986 (Germany)

0.19

(0.14-0.24)

52 279,616 2.3 44%

Autism Prevalence and Epidemiologic

Studies: Rutter criteria



DSM-III (1980)

Differentiated autism fromschizophrenia (not apsychiatric disorder, butdevelopmental)

Concept of “PDD” introduced:infantile autism; childhoodonset PDD; atypical PDD


Studies: DSM III CriteriaAuthor Rate/1,000

(95% CI)

No. Children

with Autistic

Disorder

# children in

population

M/F

Ratio

IQ <

70

%

Gillberg, 1984

(Sweden)

0.20

(0.13-.30)

26 128,584 1.8 80

Steffenberg & Gillberg,

1986 (Sweden)

0.45

(0.31-0.62)

35 78,413 5.7 NR

Matsuishi et al., 1987

(Japan)

1.55

(1.16-1.64)

51 32,834 4.0 NR

Burd et al., 1987

(USA)

0.12

(0.00-0.20)

21 180,986 2.7 NR

Bryson et al., 1988

(Canada)

1.01

(0.62-1.54)

21 20,800 2.5 76

Tanoue et al., 1988

(Japan)

1.38

(1.16-1.64)

132 95,394 4.1 NR


Studies: DSM III Criteria, continued

Author Rate/1,000

(95% CI)

No. Children

with Autistic

Disorder

# children in

population

M/F

Ratio

IQ < 70

%

Ciadella & Mamelle,

1989 (France)

0.51

(0.39-0.63)

67 135,180 2.0 NR

Sugiyama & Abe, 1989

(Japan)

1.30

(0.7-2.1)

16 12,263 NR 38

Ritvo, et al., 1989

(USA)

0.40

(0.31-0.50)

241 769,620 3.7 66


Studies: DSM III-R Criteria

DSM-III-R (1987)

Concept of PDD continued; autismand PDD-NOS

Autism Prevalence &

Epidemiologic Studies: DSM III-R

CriteriaAuthor Rate/1,000

(95% CI)

No. Children

with Autistic

Disorder

# children in

population

M/F

Ratio

IQ < 70

%

Gillberg et al., 1991

(Sweden)

0.95

(0.74-1.95)

74 78,100 2.9 82

Webb et al., 1997

(Wales)

0.72

(0.54-0.95)

53 73,300 6.6 NR

Powell et al., 2000

(England)

0.96

(0.64-1.39)

28 29,200 5.7 NR

Croen et al., 2001

(USA)

1.1

(1.06-1.14)

5038 4.6 million 4.0 NR



ICD-10 (1992)

Greatly expanded PDD concept –autism; atypical autism; Rettsyndrome; other childhooddisintegrative disorder; overactivedisorder associated with MR/ID andstereotyped movements; Aspergersyndrome; other PDDs; PDD,unspecified


Studies: ICD-10Author Rate/1,000

(95% CI)

No. Children

with Autistic

Disorder

# children in

population

M/F

Ratio

IQ <

70

%

Fombonne &

Mazaubrun, 1992

(France)

0.49

(0.47-0.65)

154 274,816 2.1 87

Honda et al., 1996

(Japan)

2.11

(1.25-3.33)

18 8,537 2.6 50

Fombonne et al., 1997

(France)

0.54

(0.46-0.62)

174 325,347 1.8 88

Arvidsson et al., 1997

(Sweden)

3.10

(1.14-6.72)

6 1941 4.5 100


Studies: ICD-10, cont.

Author Rate/1,000

(95% CI)

No. Children

with Autistic

Disorder

# children in

population

M/F

Ratio

IQ <

70

%

Sponheim & Skjedae,

1998

(Norway)

0.38

(0.25-0.56)

25 65,688 2.0 64

Kadesjo et al., 1999

(Sweden)

6.0

(1.97-14.1)

5 826 9.0 60

Baird et al., 2000

(England)

3.1

(2.29-4.06)

50 16,235 15.7 40

Magnusson &

Saemundsen, 2000

(Iceland)

0.86

(0.60-1.18)

37 43,153 3.6 49

Lingam et al, 2003

(England)

1.5

(1.3-1.7)

278 186,206 ~4.8 NR


Studies: ICD-10, cont.

Author Rate/1,000

(95% CI)

No. Children

with Autistic

Disorder

# children in

population

M/F

Ratio

IQ <

70

%

Lauritsen et al., 2004

(Denmark)

1.2

(1.1-1.3)

805 682,397 ~3.5 NR

Baird, et al., 2006

(United Kingdom)

3.89

(3.39-4.43)

255 56,946 ~6.9 56

Williams et al., 2008

(United Kingdom)

6.19

(4.9-7.5)

86 14, 062 6.8 14.7



DSM-IV (1994) and DSM-IV TR (2000)

Also expanded PDD concept – autisticdisorder; Asperger syndrome; Rettsyndrome; CDD; PDD-NOS

Autism Prevalence &

Epidemiologic Studies: DSM-IV

Author Rate/1,000

(95% CI)

No. Children

with Autistic

Disorder

# children in

population

M/F

Ratio

IQ <

70

%

Kielinen et al., 2000

(Finland)

1.22

(1.06-1.41)

187 152,732 2.0 50

Chakrabarti &

Fombonne, 2001

(England)

1.68

(1.1-2.46)

26 15,500 4.3 24

Fombonne, et al. 2001

(United Kingdom)

2.61

(1.81-3.70)

27 12, 529 8.0 44.4

Bertrand et al., 2001

(USA)

4.0

(2.8-5.5)

36 8,996 2.2 49


Studies: DSM-IV, continuedAuthor Rate/1,000

(95% CI)

No. Children

with Autistic

Disorder

# children in

population

M/F

Ratio

IQ <

70

%

Yeargin-Allsopp et al.,

2003 (USA)

3.4

(3.2-3.6)

987 289,456 4.0 62

Gurney et al., 2003

(USA)

4.4

(4.3-4.5)

4094 930,454 NR NR

Icasiano et al., 2004

(Australia)

3.9

(3.3-4.5)

177 45,384 8.3 47

Fombonne et al., 2006

(Canada)

2.16

(1.65-2.78)

61 27,749 8.3 NR

Wong & Hui, 2007

(China)

1.61

NR

682 4,247,206 6.58 NR

Rice et al., 2007

(USA)

6.7

(6.3-7.0)

1252 187,761 2.8-5.5 36-61


Studies: DSM-IV, continued

Author Rate/1,000

(95% CI)

No. Children

with Autistic

Disorder

# children in

population

M/F

Ratio

IQ <

70

%

Rice et al., 2007

(USA)

6.6

(6.3-6.8)

2685 444,050 3.4-6.5 45

Rice et al., 2009

(USA)

8.0

(7.6-8.4)

1,376 172,335 4.5 44

Rice et al., 2009

(USA)

9.0

(8.6-9.3)

2,757 308, 038 4.5 41

Brugha et al., 2009

(England)

10.0

(5-20)

19 (Adults) 2854 (Adults) 1.8 NR

Historical perspective on Autism

prevalence before 2009

Prior to1990s 1990-2006 2007

1 in 2,000 1 in 500 1 in 150

Four times more common in boys

Intellectual impairment is important co-morbidity (approximately 50-

70% in earlier studies; less in recent studies)

Trend studies:

Attributed increases (mostly ASD) to increased awareness and

service availability, improved recognition and methodological

changes.

Use of Different Surveillance Methods

Administrative datasets (single administrativesource, e.g., service provider databases andstate-wide agencies that coordinate servicesfor children with DD)

Community surveys

National surveys

Multiple source record review

Multiple Source Record Review

CDC’s Approach to ASD Prevalence

Population-based screening

Abstraction of evaluation records

Reliable application of coding schemeto determine case status

Metropolitan Atlanta Developmental Disabilities

Surveillance Program (MADDSP)

Ongoing, active monitoring program since 1991

5 counties of metro Atlanta

Multiple sources (educational, clinical, service sources)

5 Disabilities:

Mental Retardation/

Intellectual Disability

Cerebral Palsy

Hearing Loss

Vision Impairment

Autism Spectrum Disorders (since 1996)

How do the rates of ASDs compare with

other disabilities?

Rates of Developmental Disabilities in Metropolitan

Atlanta (8-year-olds, 2000)

Intellectual Disability 12.0 per 1,000

Autism* 6.5 per 1,000

Cerebral Palsy 3.1 per 1,000

Hearing Loss 1.2 per 1,000

Vision Impairment 1.2 per 1,000

Karapurkar-Bhasin, Brocksen, Avchen, Van Naarden Braun. Prevalence of four developmental disabilities among children

aged 8 years - the Metropolitan Atlanta Developmental Disabilities Surveillance Program, 1996 and 2000. MMWR SS

2005;55;1–9.

* Centers for Disease Control and Prevention . Prevalence of Autism Spectrum Disorders --- Autism and

Developmental Disabilities Monitoring Network, Six Sites, United States, 2000. MMWR SS 2007; 56;1-11.

Goals:

Accurate and comparable population-based

estimates of the prevalence of Autism

Spectrum Disorder (ASD) in selected regions

of U.S.

Describe the characteristics of children with

Autism

Examine trends in prevalence

ADDM Network Methods

Active case-finding with broad retrospectiverecords-based screening for ASD classificationsor behaviors.

Focus on children at age 8 to identify peakprevalence.

Multiple health and education sources ofinformation.

Detailed behavioral, developmental, and testinginformation collected.

Ongoing quality control within and across sites.

Independent review and clinician confirmation ofASD case status based on the DSM-IV criteria.

Standard for setting ASD prevalence estimates inthe U.S.

ADDM 2002 ASD Prevalence Results

(Published in MMWR, 2007)

• Findings across 14 sites:

• Approximately 10% of US 8-year-old children

• 2,685 children were identified with an ASD.

• The average prevalence was 6.6 per 1,000.

• Range of 3.3 (AL) to 10.6 (NJ) per 1,000 children; however,for 12 of the 14 sites ASD prevalence was in a tighter rangefrom 5.2 to 7.6 per 1,000.

Baseline:Baseline:An average of 1:150 Children in the US has an ASD

Estimated: 560,000 children between 0-21 years

Centers for Disease Control and Prevention (CDC). Prevalence of —Autism Spectrum Disorders --- Autism and DevelopmentalDisabilities Monitoring Network, 14 Sites, United States, 2002. MMWR SS 2007;56(No.SS-1).

Prevalence of Autism Spectrum Disorders

(ASDs) –Autism and Developmental

Disabilities Monitoring (ADDM) Network, 2006*

Updated ASD prevalence

estimates:

– 2006 Surveillance Year for

11 sites

– Prevalence changes from

2002 to 2006

– 2004 Surveillance Year

(optional year in appendix)

for 8 sites

*December, 2009

ADDM 2006 ASD Prevalence Results

• Average prevalence of ASD about 1% of 8-year-oldchildren

• Average = about 1 in 110 children (range 1 in 80to 1 in 240)

• Approximately 1 in 70 boys and 1 in 315 girls

• Similar to other recent studies in Europe, Asia,and North America.

• Prevalence increased 57% between 2002 and 2006

• No single factor explains changes in ASDprevalence

• Some increases due to better documentation inrecords

• Despite slight improvements in age of diagnosis,significant delays persist

ADDM 2006 Surveillance Year:Health Source Access Only (5/11 sites)

Site Area 8-year-olds in Population

in 2006

1. Alabama 32 counties 35,126

2. Florida 1 county 27,615

3. Missouri 5 counties 26,533

4. Pennsylvania 1 county 17,886

5. Wisconsin 10 counties 34,058

2006 sites continued…

ADDM 2006 Surveillance Year:Health and Education Source Access

(6/11 sites)

Site Area 8-year-olds in Population

in 2006

6. Arizona 1 county 41,650

7. Colorado 1 county 7,184

8. Georgia 5 counties 46,621

9. Maryland 6 counties 26,489

10. North Carolina 10 counties 22,195

11. South Carolina 23 counties 22,681

11 site total 308,038;

~8% of US 8-year-olds

Surv Year Birth

Year

# sites 8-year-old

Population

8-year-old

children with

an ASD

Average Prev

/ 1,000

Range

2000 1992 6 187,761 1,252 6.7

4.5-9.9

2002 1994 14 407,578 2,685 6.6

3.3-10.6

2004 1996 8 172,335 1,376 8.0

4.6-9.8

2006 1998 11 308,038 2,759 9.0

4.2-12.1

2008 2000 11(14) In process

ADDM Network Overall Identified ADDM Network Overall Identified

ASD Prevalence, 2000-2006ASD Prevalence, 2000-2006

• From 4.2 per 1,000 (FL) to 12.1 per 1,000 8-year-old

children (AZ and MO)

• Average across all 11 sites of 9.0 per 1,000, about 1%

of 8–year-old children

About 1 in 110 children

ADDM 2006 Surveillance YearOverall Prevalence

ADDM 2006 ASD Prevalence Overall and Based on Previously Documented ASDClassification

Embargoed confidential data – for MADDSP stakeholders Presentation Only

Males and Females

• Average ASD prevalence for

• Males = 14.5 per 1,000

• Females = 3.2 per 1,000

About 1 in 70 males and 1 in 315 females

• Average 4.5 males to every female with ASD

ADDM 2006 Surveillance YearPrevalence by Sex

ADDM 2006 Surveillance Year

Prevalence by Race or Ethnicity

Race/ethnicity

• White, non-Hispanic children with highest ASD prevalence, but

variability

• White, non-Hispanic: average 9.9 per 1,000 (1 in 100

children),

• Ranging from 3.4 to 14.8 per 1,000 children.

• Black, non-Hispanic: average 7.2 per 1,000 (1 in 140

children),


• Hispanic: average 5.9 per 1,000 (1 in 170 children)


• 70-95% with a documented developmentalconcern before the age of 3 years

• 13–30% of children had a reporteddevelopmental regression by 24 months ofage

• Average age of earliest ASD diagnosis was 4years, 6 months; ranging from 3 years, 6months to 5 years

ADDM 2006 Surveillance YearDevelopmental Concerns and Age of Earliest

Documented ASD Diagnosis

ADDM 2006: Special Education Services

9

Change in ASD Prevalence from 2002 to 2006

by Total, Gender, & Race or Ethnicity

(10 Sites)

• Overall, data reflect increases in identified ASD

prevalence and among subgroups – site variation exists.

Total Males Females White

non-

Hispanic

Black

non-

Hispani

c

Hispanic

% Change

Average57% 60% 48% 55% 41% 91%

Change in ASD Prevalence from 2002 to

2006 by Cognitive Functioning Level

Cognitive

Impairment

(IQ 70)

Borderline

(IQ=71-85)

Average to Above

Average (IQ>85)

% Change, Average 35% 90% 72%

• There were increases across all levels of cognitive

functioning

• In 2006SY, between 29-51% of children with cognitive

impairment (average 41%)

Conclusions: ADDM 2006SY

Average prevalence of ASD about 1% of 8-year-oldchildren

Average = about 1 in 110 children (range 1 in 80to 1 in 240)

Approximately 1 in 70 boys and 1 in 315 girls

Prevalence estimates increased 57% between 2002and 2006

No single factor explains changes in ASDprevalence

Some increases due to better documentation inrecords

Despite slight improvements in age ofdiagnosis, significant delays persist

Why has the prevalence of ASD reported from

ADDM increased from 2002 to 2006?

No single explanation –likely multiple factors at play

Need to continue monitoring over time to follow trends

Identification issues which contributed to small

increases across sites:

more evaluation records (4 vs. 5)

better quality of documentation

some sites, able to locate more records

some sites, more stable population

some sites, better identification of Hispanic children (AZ)

some sites, more identification of children without

cognitive impairment

Implications

ASDs are an urgent public health issue

Prevalence estimates can be used to planpolicy, educational, and intervention services.

Coordinated and collaborative response isneeded to:

Intensify search for risk factors;

Improve early identification/access to EIservices;

Better understand how to intervene to helpreduce the debilitating symptoms of ASDs;

Address needs of persons with ASD andprovide coordinated support services

Where do we go from here?

Expand surveillance to include additionalpopulations

Older/Younger Cohorts

Other conditions (i.e. ADHD, Fragile X, FAS, LD,Epilepsy)

Special investigations

Continue working with government/non-government partners to take a comprehensiveapproach to ASD surveillance/research (IACC)

Bottom Line

Changes in diagnoses?

Awareness?

Availability of services?

Real increase in symptoms?

Regardless – more children with ASD identified

and the impact on the families and service

systems is real!

For more information

ADDM Reports in CDC’s MMWR SurveillanceSummaries

www.cdc.gov/mmwr

ADDM Video

http://www.cdc.gov/ncbddd/autism/videos/ADDM/index.html

Updated autism website

www.cdc.gov/autism

Learn the Signs. Act Early.

www.cdc.gov/actearly

MADDSP Staff

Marshalyn Yeargin-

Allsopp

Alana Aisthorpe

Andrew Autry

Jon Baio

Claudia Bryant

Owen Devine

Nancy Doernberg

Santrell Green

Susie Graham

Christine Hill

Nancy Hobson

Diana Schendel

Laura Schieve

Darlene

Sowemimo

Melody Stevens

Melissa Talley

Ignae Thomas

Kim Van Naarden

Braun

Lisa Wiggins

Susan Williams

Joanne Wojcik

Lekeisha Jones

Rita Lance

Katrina Langston

Charmaine

McKenzie

Michael Morrier

Amy Pakula

Mary Philips

Lori Plummer

Catherine Rice

Julia Richardson

Matthew Rudy

Principal investigators and Project Coordinators:

CDC: Catherine Rice, Jon Baio, Kim Van Naarden Braun, Marshalyn

Yeargin-Allsopp, Susan Graham, and Anita Washington;

Alabama: Beverly Mulvihill, Martha Wingate, Russell S. Kirby, Meredith Hepburn,

Neva Garner;

Arizona: Sydney Pettygrove, Chris Cunniff, F. John Meaney, Kristen Clancy

Mancilla;

Colorado: Lisa Miller, Cordelia Robinson, Gina Quintana, Yolanda Castillo, and

Andria Ratchford;

Florida: Marygrace Yale Kaiser and Claudia Rojas;

Maryland: Li-Ching Lee, Rebecca Landa, Craig Newschaffer, and Maria Kolotos;

Missouri: John Constantino and Robert Fitzgerald;

North Carolina: Julie Daniels and Paula Bell;

Pennsylvania: Ellen Giarelli, Jennifer Pinto-Martin, Susan E. Levy, and Rachel

Meade Reiss;

South Carolina: Jane Charles, Joyce Nicholas, and Lydia King;

Wisconsin: Maureen Durkin, and Carrie Arneson.

Additional assistance was provided by project staff including data abstractors, clinician

reviewers, epidemiologists, and data management/programming staff. Ongoing ADDM

Network support was provided by: Nancy Doernberg, Joanne Wojcik, Rita Lance, Lori

Plummer, and Lekeisha Jones.

Thank You!

The findings and conclusions in this presentation are those of the authors and do not

necessarily represent the views of the Centers for Disease Control and Prevention

epidemiology and the changing paradigm of autism ... and the changing paradigm of autism spectrum...

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