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A Positive Association found between AutismPrevalence and Childhood Vaccination uptake acrossthe U.S. PopulationGayle DeLong

a

aDepartm ent of Economics and Finance, Baruch Col lege/ Cit y Universi t y of New York, New

York , New York , USAVersion of record first published: 26 May 2011.

To cite this art icle: Gayle DeLong (2011): A Posit ive Associat ion f ound bet ween Auti sm Prevalence and Childhood Vaccinat iuptake across the U.S. Population, Journal of Toxicology and Environmental Health, Part A: Current Issues, 74:14, 903-916

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Journal of Toxicology a nd Environmental Health, Part A, 74:903916, 2011

Copyright Taylor & Francis Group, LLC

ISSN: 1528-7394 print / 1087-2620 online

DOI: 10.1080/15287394.2011.573736

A POSITIVE ASSOCIATION FOUND BETWEEN AUTISM PREVALENCEAND CHILDHOOD VACCINATION UPTAKE ACROSS THE U.S. POPULATION

Gayle DeLong

Department of Economics and Finance, Baruch College/City University of New York, New York,New York, USA

The reason for the rapid rise of autism in the United States that began in the 1990s isa mystery. Although individuals probably have a genetic predisposition to develop autism,researchers suspect that one or more environmental triggers are also needed. One of thosetriggers might be the battery of vaccinations that young children receive. Using regressionanalysis and controlling for family income and ethnicity, the relationship between the propor-tion of children who received the recommended vaccines by age 2 years and the prevalence of

autism (AUT) or speech or language impairment (SLI) in each U.S. state from 2001 and 2007was determined. A positive and statistically significant relationship was found: The higher theproportion of children receiving recommended vaccinations, the higher was the prevalenceof AUT or SLI. A 1% increase in vaccination was associated with an additional 680 childrenhaving AUT or SLI. Neither parental behavior nor access to care affected the results, sincevaccination proportions were not significantly related (statistically) to any other disability orto the number of pediatricians in a U.S. state. The results suggest that although mercury hasbeen removed from many vaccines, other culprits may link vaccines to autism. Further studyinto the relationship between vaccines and autism is warranted.

Autism is an urgent and growing public

health problem in the United States. The ill-ness impairs speech, language, social abilities,and behavior. In 1990, autism was considereda rare disease (Tebben 1990), but less than 2decades later autism affected an estimated 1 in91 U.S. children (Kogan et al. 2009). Althoughscientists generally agree that a genetic predis-position for autism exists (Rutter 2000), genesalone do not change quickly enough to createthe current epidemic. The recent explosion inthe prevalence of autism suggests the existenceof one or more environmental triggers (Blaxill

Received 29 October 2010; accepted 1 March 2011.This study includes data from the U.S. National Centers for Health Statistics (NCHS). Any analyses, interpretations, or conclusions

reached are the authors own and not those of the NCHS, which is responsible only for the initial data. The author is grateful to JosGarrofe Dorea, Anthony Mawson, Jonathan Rose, Paul Turner, and David Yermack as well as seminar participants at Baruch Collegeand two anonymous reviewers for thoughtful comments. Francis Donnelly provided invaluable assistance in creating the geographicinformation system graphic. The author has two children with pervasive development disorder, not otherwise specified. She has filed apetition in the U.S. Court of Federal Claims under the National Vaccine Injury Compensation Program for one of her children. The authoris on the board of directors and research committee of Sensible Action for Ending Mercury-Induced Neurological Disorders (SafeMinds).

Address correspondence to Gayle DeLong, PhD, Associate Professor, Department of Economics and Finance, Baruch College/CityUniversity of New York, One Bernard Baruch Way, Box B10-225, New York, NY 10010, USA. E-mail: [email protected]

2004). Could one of those triggers be the

battery of vaccinations given to young children?Chronic, negative reactions to vaccinationshave been recognized in both humans andanimals. In the late 19th Century, Burnett(1884/1960) described long-term negativeeffects such as eczema, diarrhea, and fatiguein some individuals who received a series ofsmallpox vaccinations. By the 1990s, veterinar-ians began to notice that some animals devel-oped chronic ailments such as autoimmunedisorders and seizures after being vaccinated(Smith 1995; Dodds 2001). In the early

903


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904 G. DELONG

2000s, vaccines were shown to be linked toautoimmune disorders and, possibly, autism inhumans (Shoenfeld and Aron-Maor 2000).

There are several reasons why vaccinesmay trigger autism. Certain vaccines containthimerosal, a preservative that is almost halfmercury (Hg) by weight, which was shown tobe associated with adverse effects includingautism. Nataf et al. (2006) found that childrenwith autism have higher levels of precopro-porphyrin, a biomarker for Hg toxicity, thanneurotypical children. This finding was con-firmed by Geier and Geier (2007) and Geieret al. (2009) in the United States, Austin andShandley (2008) in Australia, and Youn et al.(2010) in Korea. Thimerosal-containing hep-

atitis B shots were associated with delayedacquisitions of vital reflexes in baby macaques(Hewitson et al. 2010). Although thimerosalwas removed from many vaccines from 2000,it is still present in almost all influenza shotsas well as eight other U.S. vaccines givento children (Centers for Disease Control andPrevention 2010). In addition, the CDC beganin the early 2000s to encourage the inoculationof pregnant women and children aged 6 to 23months against influenza (Centers for DiseaseControl and Prevention 2001; 2002). Given

the increased use of influenza shots contain-ing thimerosal, childrens exposure to Hg viavaccines was likely increased in utero but notdecreased after fetuses were born, even thoughthimerosal was removed from other vaccines.

There are other possible links between vac-cines and autism besides Hg. Vaccines alsocontain the neurotoxin aluminum (Al) as wellas live viruses. The Al in vaccines has beenassociated with disorders in the central ner-vous system (Authier et al. 2001) as well aswith autism (Blaylock 2008). Combining Hg

and Al magnifies the toxicity of each (Haley2005). Both metals also are known to suppressthe immune system (Havarinasab et al. 2005);thus, a susceptible person may not be able tomount an effective immunological response tothe live viruses found in certain vaccines suchas the measlesmumpsrubella shot. Measles-containing vaccines stimulate the production ofcytokines that inflame and damage the brain,

possibly contributing to autism (Ashwood et al.2004; Vargas et al. 2005; Singh 2009).

Children with autism appear to have vul-nerabilities that their neurotypical peers do notpossess. Autistic children tend to exhibit higherlevels of oxidative stress and poorer methyla-tion, the process by which the body detoxifiesitself (James et al. 2004). This difficulty in detox-ifying could be associated with metals fromvaccines being sequestered in the brain andcausing neurological damage (Kern et al. 2007).Vaccines may also increase the oxidative stressof children with preexisting mitochondrial dys-functions to such an extent that the childrendevelop autism (Poling et al. 2006). In gen-eral, susceptibility to developing a neurological

disability after exposure to an environmentalinsult such as a vaccine depends on factors suchas a childs age at time of exposure, amountof exposure, genetic predisposition, and stress(Kern and Jones 2006).

Compounding these biological issues is thefact that the number of vaccinations recom-mended for U.S. children by age 2 years hasmore than tripled, from 8 vaccinations in 1983to 27 in 2010 (Centers for Disease Control andPrevention 1983; 2010). Although individualvaccines are tested for safety and efficacy, no

study has ever examined the safety of the entirevaccination schedule recommended for U.S.children by the CDC. Neither the short-termnor chronic interactions among all the vaccinesin a childs recommended schedule have everbeen tested.

Examining the relationship between theproportion of children who receive vaccina-tions and the prevalence of autism may provideinsights into whether autism is an adverse reac-tion to vaccinations. If an association betweenreceiving vaccinations and developing autism is

found to exist across geography and throughtime, further investigation into the hypothesisis warranted.

METHODS

In this study, the relationship betweenthe proportion of U.S. children who receiveda series of vaccinations recommended by


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ASSOCIATION BETWEEN AUTISM AND VACCINATION 905

the U.S. Centers for Disease Control andPrevention (CDC) by age 2 years and the preva-lence of autism in each U.S. state over time wasexamined.

Measures

Prevalence of autism To determine autismprevalence by U.S. state, the number of 8-year-old students classified with either (1) autismor (2) speech or language impairments (speechdisorders) was divided by the total numberof 8-year-olds in the state. The number ofchildren with disabilities came from the U.S.Department of Education, Office of SpecialEducation Programs (2007) and the total num-

ber of students came from the U.S. Departmentof Education, National Center for EducationStatistics. Although the diagnosis of autism isusually made when a child is 3 or 4 yearsold, some children are not diagnosed until theyare older. Children who receive a diagnosisof autism usually do so by the time they are8 years old. The category of speech or lan-guage impairments was included with autism,because these impairments are closely linkedto autism (Conti-Ramsden et al. 2006; De Fosseet al. 2004; Herbert et al. 2007).

Exposure to a recommended vaccinationseries Since 1994, the CDC has commis-sioned an annual survey to estimate vaccina-tion coverage in the United States for preschoolchildren. Surveyors at the National OpinionResearch Center (NORC) at the University ofChicago randomly call homes to find house-holds with children aged 19 to 35 months.When such a household is found, the inter-viewer asks which vaccinations the child hasreceived. If the parent or guardian agrees,NORC follows up the telephone interview

with a written survey to the vaccinationprovider. The survey reaches approximately30,000 households with children of the appro-priate age. The proportion of children in eachstate that receives the various vaccines recom-mended by the CDC is reported. Starting in1995, the CDC reports the percentage of youngchildren who have received the 4:3:1:3:3series of shots, which consists of at least four

doses of the diphtheria, tetanus, and pertussis(or diphtheria, tetanus, and acellular pertussis)vaccine, three doses of poliovirus vaccine, onedose of any measles-containing vaccine, threedoses of the Hib vaccine, and three doses ofhepatitis B vaccine. The results of this surveyas well as the follow-up verification from thevaccination provider are available to the pub-lic (Centers for Disease Control and Prevention,National Center for Health Statistics 2007).Since the possible magnification effect of thetoxins in vaccines is of interest as well asthe possible interactions between toxins andlive viruses, the proportion of children whoreceived the entire 4:3:1:3:3 series of vaccina-tions by the time they were 19 to 35 months

old was examined in this study.Children who are vaccinated at age 2 yearsmay not develop autism until they are older.To determine the prevalence of autism for aspecific cohort of children, the vaccinationdata from when the children were 2 years oldis compared with autism prevalence when theyare 8 years old. The relevant vaccination datafor children who were 8 years old in 2001 arethose from 1995, when the children were 2years old. For children who turned 8 years oldin 2002, the relevant vaccination data are from

1996, and so on. The earliest available datavaccination data from 1995were matchedwith autism prevalence up to 2007. Table 1shows the vaccination and autism/speechdisorder data by state for the various years inthis study.

Figure 1 shows the relationship betweenthe prevalence of 8-year-old children withautism or speech disorders by state in 2005and vaccination proportions 6 years earlier. Thedarker the shading of the state, the higher isthe proportion of children who received the

4:3:1:3:3 series of vaccinations by the timethey were 2 years old; the larger the cir-cle, the greater is the prevalence of autismor speech disorders. Groupings of data weredetermined using the Natural Breaks (Jenks)method in the Arc geographic information sys-tem (ArcGIS) software package (EnvironmentalSystem Research Institute Inc. 2009). The mappresents an ambiguous picture: Some states,


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TABLE

1.VaccinationRate(19

952001)andAUT/SLIPrevalence(20012007)byU.S.State

Vaxrate

AUT/SLI

Vaxrate

AUT/SLI

Vaxra

te

AUT/SLI

Vaxrate

AUT/SLI

Vaxrate

AUT/SLI

Vaxrate

AUT/SLI

Vax

rate

AUT/SLI

U.S.state

1995

2001

1996

2002

1997

2003

1998

2004

1999

2005

2000

2006

2001

2007

Alabama

45.8

4.6

65.2

4.4

76.5

4.4

74.2

4.5

74.1

4.7

76.1

4.6

79.1

4.5

Alaska

54.3

5.8

67.2

5.1

68.8

5.5

74.1

6.0

74.5

4.8

70.6

5.0

71.2

4.8

Arizona

51.2

3.8

61.8

4.1

62.0

4.1

69.0

4.8

67.3

5.2

67.2

5.4

68.1

6.2

Arkansas

53.6

4.8

61.4

4.8

74.8

5.0

65.9

5.3

70.4

5.8

67.1

6.3

69.1

5.9

California

57.7

4.5

65.8

4.6

67.1

4.6

69.8

4.6

70.5

4.6

72.3

4.7

72.6

4.6

Colorado

51.4

3.1

66.3

3.5

64.4

3.6

67.9

3.6

69.6

3.9

71.6

4.0

71.5

4.1

Connecticut

63.9

3.6

80.6

3.9

76.0

3.7

81.5

3.9

82.3

3.9

81.6

4.2

78.4

4.1

Delaware

54.7

3.3

73.5

3.2

68.3

3.3

68.0

3.6

69.0

3.1

66.2

2.1

68.9

N/A

DistrictofCoumbia

49.8

3.2

66.8

2.3

62.4

2.7

63.5

2.6

70.9

2.7

70.0

3.7

74.9

3.3

Florida

53.4

6.0

72.1

6.0

67.3

5.6

75.4

5.6

77.9

5.7

71.7

6.4

73.0

6.4

Georgia

61.7

5.2

76.9

5.5

72.9

5.7

75.7

5.9

77.9

5.9

77.7

5.9

78.5

5.7

Hawaii

66.2

2.0

74.4

1.8

73.2

1.7

73.0

1.4

79.2

1.3

72.8

1.4

70.8

1.0

Idaho

40.7

4.0

51.9

3.9

63.9

3.8

66.2

4.2

65.0

4.2

70.7

4.6

70.2

4.4

Illinois

57.2

5.6

64.9

5.6

67.4

5.6

73.7

5.5

72.0

5.5

71.2

5.7

72.7

5.6

Indiana

41.8

8.8

56.7

8.9

62.7

9.1

68.8

9.1

65.3

9.2

72.0

9.8

71.1

10.0

Iowa

47.7

1.6

70.3

2.5

71.0

2.1

78.1

2.2

78.9

2.2

82.5

2.1

78.6

2.0

Kansas

35.7

5.1

58.2

5.1

72.1

5.2

72.1

5.0

70.7

5.1

71.3

4.9

72.8

4.9

Kentucky

59.6

6.0

70.4

6.0

70.2

5.8

75.5

6.3

84.4

6.6

77.0

7.1

75.9

7.1

Louisiana

61.8

5.1

73.0

5.1

70.6

5.2

72.4

5.4

72.3

5.1

71.8

5.4

64.1

5.6

Maine

46.6

6.6

68.4

6.9

78.4

6.8

78.3

7.2

76.8

7.7

76.0

7.5

75.1

7.2

Maryland

59.2

4.5

64.9

4.7

73.7

4.8

72.3

4.6

72.7

4.5

75.4

4.7

73.4

4.6

Massachusetts

70.7

2.2

79.9

2.6

81.1

3.0

79.6

3.3

81.4

3.6

81.4

3.8

76.6

4.1

Michigan

46.7

5.1

66.2

5.5

69.3

5.5

73.9

5.7

70.9

5.9

73.7

6.2

70.0

6.2

Minnesota

41.2

4.0

63.2

4.3

63.7

4.4

73.1

4.5

78.5

4.8

82.4

4.8

76.3

5.1

Mississippi

38.1

6.2

68.1

6.4

70.8

6.6

79.5

6.2

79.0

6.2

75.9

6.7

80.2

6.8

Missouri

50.5

6.2

68.3

7.1

67.6

7.5

74.8

8.1

68.9

8.5

76.8

9.0

75.5

8.7

Montana

44.7

5.7

59.2

5.1

64.3

5.7

75.2

6.0

76.4

6.2

71.1

N/A

77.9

5.9

Nebraska

49.2

7.3

65.3

7.0

66.4

7.2

71.1

7.7

79.8

7.7

75.5

7.6

78.9

7.9

Nevade

55.9

4.0

61.9

4.0

65.5

4.2

70.4

3.9

68.5

4.3

69.1

5.0

68.1

5.1

NewHampshire

72.7

3.5

77.3

3.2

76.8

3.3

75.8

3.4

78.4

3.7

78.9

3.6

77.6

3.9

NewJersey

60.5

7.1

68.5

7.3

70.5

7.1

76.7

7.2

75.3

7.2

71.2

7.6

73.1

7.7

NewMexico

43.8

5.1

66.2

5.1

66.1

5.0

66.0

4.8

66.6

4.9

64.5

5.3

63.2

5.5

906


6/15

NewYork

62.6

3.6

72.6

3.8

68.1

4.1

79.9

4.2

78.2

4.4

72.3

4.6

77.1

5.0

NorthCarolina

62.5

5.1

69.8

5.0

76.5

5.1

76.7

5.5

77.1

5.5

82.8

5.8

80.4

5.9

NorthDakota

65.7

6.5

71.9

6.8

73.2

6.8

73.0

7.3

76.3

6.5

80.3

6.9

78.7

6.7

Ohio

47.7

4.3

69.5

4.4

63.9

4.3

71.0

4.4

73.0

4.5

68.9

4.7

71.2

4.6

Oklahoma

42.3

5.6

59.0

6.1

65.0

5.9

70.3

5.9

70.4

6.5

68.3

7.0

70.0

6.7

Oregon

56.6

6.1

62.4

6.1

62.0

6.1

67.4

6.4

63.8

6.6

74.7

6.8

68.5

6.9

Pennsylvania

62.2

4.4

70.1

4.7

70.9

4.7

75.7

4.9

80.8

5.0

77.8

5.3

78.8

5.4

RhodeIsland

58.5

6.1

77.0

6.3

72.0

6.6

76.9

6.5

83.2

6.2

80.5

6.8

81.7

6.9

SouthCarolina

72.2

7.1

83.0

7.4

74.4

7.3

83.8

7.2

78.0

7.3

78.5

7.0

78.7

7.3

SouthDakota

27.5

6.5

62.0

7.1

67.0

7.5

66.1

7.7

76.9

7.6

73.6

7.9

76.5

8.7

Tennessee

57.8

5.3

72.3

5.4

71.3

5.4

73.5

5.3

70.0

5.5

76.8

5.9

79.7

6.0

Texas

52.4

4.0

62.5

4.1

65.3

4.2

63.7

4.2

64.8

4.2

63.5

4.3

69.7

4.3

Utah

43.7

4.7

53.4

4.8

53.7

4.9

64.8

5.4

65.8

5.2

68.2

5.7

66.1

6.6

Vermont

55.8

3.4

76.8

3.0

78.0

2.3

80.7

2.9

85.2

2.5

77.0

2.8

80.3

N/A

Virginia

52.8

4.2

68.3

4.5

66.6

4.6

75.1

4.6

74.9

4.7

70.7

4.9

74.9

4.7

Washington

57.0

4.1

68.5

4.0

66.6

4.0

68.8

4.1

67.1

4.2

72.5

4.3

71.2

4.4

W

Virginia

28.9

9.9

50.5

9.7

73.4

10.1

75.6

10.2

77.8

10.7

71.9

11.0

78.1

11.3

Wisconsin

53.1

4.2

67.1

4.4

70.9

4.7

70.6

4.9

78.6

5.1

74.2

5.7

79.5

6.0

Wyoming

18.9

6.9

48.0

6.8

69.2

7.6

75.4

8.1

81.5

8.2

78.2

8.7

74.3

10.0

Note.Vaxrate=

proportion

of2-year-olds(%)receiving4:3:1:3:3series

ofvaccinations6yearsearlier.AUT/SLI=prevalenceofautismorspeech/languageimpairment(%)inyear

indicated.N/A=

notavailable.

907


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908 G. DELONG

FIGURE 1. Vaccination (1999) and Autism or Speech Disorder (2005) by U.S. State (color figure available online).

such as Texas, have low vaccination rates andlow prevalence of autism, while other states,such as Indiana, have low vaccination rates

and a high prevalence of autism. Conversely,Wyoming has a high vaccination rate and highprevalence of autism, while Vermont has ahigh vaccination rate and low prevalence ofautism. Additionally, Figure 1 merely presentsa snapshot, based on prevalence data in 2005.More rigorous analysis is needed that includesseveral years of data, as well as variables tocontrol for influences other than the vaccineseries.

Controlling for family environment Familyincome and ethnicity may influence whether a

child receives a diagnosis of autism. More afflu-ent parents may be more prone to seek a diag-nosis (McAdoo and DeMyer 1977). Ethnicitymay be a factor in terms of the postula-tion that a deficiency in vitamin D is asso-ciated with autism: Dark-skinned people areknown to require more vitamin D and there-fore might be more prone to develop autism(Cannell 2008). For these reasons, variables

that measure household income and ethnicityare included.

To measure income, the median income

for a four-person family reported by the U.S.Census Bureau (2008) was used. The inflation-adjusted median income (using the year 2000as the base) for the year the child was born wasused. For example, the prevalence of autismor speech disorder for 8-year-olds in a par-ticular U.S. state in 2001 was matched withthe median income in that state from 1993.Ethnicity figures were derived directly from theCDCs National Immunization Survey. The sur-vey reported whether the child was Hispanic,

African American, white non-Hispanic, or

other. For each state and year, the percent-age of each ethnic group in the survey wasdetermined.

Statistical Analysis

To understand whether vaccination mightbe linked to autism, data on the prevalenceof autism or speech disorders between 2001


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ASSOCIATION BETWEEN AUTISM AND VACCINATION 909

and 2007 were matched with vaccinationrates between 1995 and 2001 for each U.S.state. Regression analysis determines how a 1%change in the vaccination rate influences thepercent change in the prevalence of autismor speech disorders (Lewis-Beck 1990). Thestatistical model used took into considerationthe unique characteristics of each state. Forexample, each state had a unique mixture ofpollution, which may have affected the preva-lence of autism (Palmer et al. 2006; 2009), yetsuch an effect was not included in this study.

A fixed-effects, within-group panel regression(Hall and Cummins 2005) controlled for theseunique yet undefined characteristics by deriv-ing a different starting point (intercept) for each

U.S. state. The 51 different interceptsone foreach U.S. state and the District of Columbiareflected the base level of autism or speechdisorders occurring in that state that werenot explained by the other independent vari-ables (vaccination rates, income, or ethnicity).The model then produced a single relation-ship between the independent variables andthe prevalence of autism or speech disorders.

Although each state started from a differentprevalence rate of autism or speech disorder,the relationships between the dependent vari-

able and independent variables was consideredthe same across state; a 1% change in vacci-nation rates was associated with the same per-cent change in prevalence of autism or speechdisorder across states. Similarly, the model con-trolled for the year in which an observationtook place. If autism awareness increased in aparticular year, the prevalence might also rise(Liu et al. 2010). To control for reasons thatoccur in a particular year, time dummy vari-ables for the year of observation were included:If an observation of prevalence occurred in

the year 2002, then the variable 2002 took avalue of 1 and the other year variables tooka value of 0. Heteroskedastic-robust standarderrors were calculated and used in determin-ing p values (Hall and Cummins 2005). Thestatistical package TSP 4.5 was used for theanalysis.

The model that results from the 7 yearsof prevalence data (years 2001 to 2007)

with control variables as well as time dummyvariables is:

Autism = a+ b1Vaccination+ b2Log(Income) + b3Hispanic+ b4African

American+ b5Other+ b62002+b72003+ b82004 + b92005+b102006 + b112007

If a combination of independent variablesperfectly predicts another independent vari-able, the model is said to suffer from per-fect multicollinearity and some coefficientswill be undefined (Lewis-Beck 1990). In thismodel, if the percentage of the populationin a U.S. state that was Hispanic, African

American, and other is known, then the per-centage of the population that was white,non-Hispanic might be determined with cer-tainty. Similarly, if the year of the prevalenceobservation was not between 2002 and 2007,then the year of the observation was 2001with certainty. Therefore, to obtain meaning-ful coefficients, the dummy variable for theyear 2001 as well as the percentage of white,non-Hispanic children were removed from themodel.

RESULTS

The results are reported in the first columnof Table 2. The association between receivingthe 4:3:1:3:3 series of vaccinations and theprevalence of autism or speech disorders is apositive and statistically significant 1.7%. Thiscoefficient represents the average change inthe prevalence of autism or speech disordersfor a 1% change in vaccination rates, hold-ing the other independent variables constant.This result holds both across geography and

over time. The results suggest that if a givenU.S. state has a 1% higher vaccination ratethan another U.S. state, then the state with thehigher vaccination rate might have, on average,a 1.7% higher prevalence of autism or speechdisorders. Further, if a given U.S. state decreasesits vaccination coverage by 1% from one yearto the next, prevalence of autism or speechdisorders may, on average, fall by 1.7%. If 100%


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TABLE

2.AnalysisofLearningDisabilities,UnitedStates,20012007,FixedEffe

ctsModel

Autismorspeech

orlanguage

impairment

Emotional

disturbance

Hearing

impairment

Me

ntal

retardation

Orthopedic

impairment

Otherhea

lth

impairment

Specificlearning

disability

Traumaticbrain

injury

Visual

impairment

Proportionof

children

receiving

4:3:1:3:3

vaccination

series

0.0166

(0.00)0.0010(0.31)

0.0026(0.70)

0.0

008(0.69)

0.0008(0.42)

0.0018(0.32)

0.0064

(0.09)

0.0006(0.17)

0.0003

(0.10)

Log(household

Income)

0.0029(0.70)

0.0006(0.72)

0.0081(0.31)

0.0

008(0.34)

0.0014(0.46)

0.0011(0.73)

0.0004(0.95)

0.0014

(0.01)

0.0001(0.71)

Hispanic(%)

0.0213(0.13)

0.0006(0.83)

0.0269

(0.06)

0.0

117

(0.00)

0.0042(0.20)

0.0029(0.56)

0.0061(0.72)

0.0008(0.41)

0.0005(0.29)

African

American,not

Hispanic(%)

0.0216(0.13)

0.0108(0.15)

0.0443(0.12)

0.0

053(0.97)

0.0073(0.19)

0.0055(0.29)

0.0231(0.23)

0.0001(0.90)

0.0001(0.79)

Other,not

Hispanic(%)

0.0208(0.41)

0.0124

(0.03)0.0074(0.64)

0.0

024(0.69)

0.0025(0.60)

0.0078(0.26)

0.0479

(0.01)

0.0009(0.77)

0.0013

(0.04)

AdjustedR2

.9636

.9358

.1803

.95

36

.7935

.9090

.9006

.9280

.5312

n

354

354

348

354

327

352

356

231

302

Note.Standarderrorsarehetero

skedastic-robustusingWhitesmethod.Timedummyvariablesincluded;pvaluesareinparentheses.Themaximumnumberofobservationsis357.Notevery

statereportseachdisabilityforeveryyearsothenumberofobservationscouldbelessthan357.Significanceindicatedas

()()p

autismo y vacunacion.pdf

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