CoChat
Sign Up
Cited by 111Autism Spectrum Disorder ResearchChild Nutrition and Feeding IssuesGenetics and Neurodevelopmental Disorders

The DOI matches its Crossref record; 104 of the 104 references it cites were found in a registry or an index.

A comparison of temporal trends in United States autism prevalence to trends in suspected environmental factors

Open access
Nevison, Cynthia D·2014·Environmental Health
DOI 10.1186/1476-069x-13-73PMC PMC4177682
Open this paper in CoChat — free accountOpen PDF

Abstract

BACKGROUND: The prevalence of diagnosed autism has increased rapidly over the last several decades among U.S. children. Environmental factors are thought to be driving this increase and a list of the top ten suspected environmental toxins was published recently. METHODS: Temporal trends in autism for birth years 1970-2005 were derived from a combination of data from the California Department of Developmental Services (CDDS) and the United States Individuals with Disabilities Education Act (IDEA). Temporal trends in suspected toxins were derived from data compiled during an extensive literature survey. Toxin and autism trends were compared by visual inspection and computed correlation coefficients. Using IDEA data, autism prevalence vs. birth year trends were calculated independently from snapshots of data from the most recent annual report, and by tracking prevalence at a constant age over many years of reports. The ratio of the snapshot:tracking trend slopes was used to estimate the "real" fraction of the increase in autism. RESULTS: The CDDS and IDEA data sets are qualitatively consistent in suggesting a strong increase in autism prevalence over recent decades. The quantitative comparison of IDEA snapshot and constant-age tracking trend slopes suggests that ~75-80% of the tracked increase in autism since 1988 is due to an actual increase in the disorder rather than to changing diagnostic criteria. Most of the suspected environmental toxins examined have flat or decreasing temporal trends that correlate poorly to the rise in autism. Some, including lead, organochlorine pesticides and vehicular emissions, have strongly decreasing trends. Among the suspected toxins surveyed, polybrominated diphenyl ethers, aluminum adjuvants, and the herbicide glyphosate have increasing trends that correlate positively to the rise in autism. CONCLUSIONS: Diagnosed autism prevalence has risen dramatically in the U.S over the last several decades and continued to trend upward as of birth year 2005. The increase is mainly real and has occurred mostly since the late 1980s. In contrast, children's exposure to most of the top ten toxic compounds has remained flat or decreased over this same time frame. Environmental factors with increasing temporal trends can help suggest hypotheses for drivers of autism that merit further investigation.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/1476-069x-13-73

Cites

104 of 104 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 Autism prevalence vs. birth year for California IDEA data, derived using two independent methods: 1) Constant-age tracking of 9 year-olds over 20 years of annual reports from 1991–2010 (red) and 2) Age-resolved snapshot from the most recent report in 2010 (blue). The slope of each curve over the same birth year interval, 1993–2001, is estimated with a least squares linear fit. The snapshot fit (grey) spans ages 9–17 in the 2010 report. The constant-age tracking fit spans report years 2002–2010. The snapshot:tracking slope ratio over the 1993–2001 birth year interval is 0.80.
Figure 1 Autism prevalence vs. birth year for California IDEA data, derived using two independent methods: 1) Constant-age tracking of 9 year-olds over 20 years of annual reports from 1991–2010 (red) and 2) Age-resolved snapshot from the most recent report in 2010 (blue). The slope of each curve over the same birth year interval, 1993–2001, is estimated with a least squares linear fit. The snapshot fit (grey) spans ages 9–17 in the 2010 report. The constant-age tracking fit spans report years 2002–2010. The snapshot:tracking slope ratio over the 1993–2001 birth year interval is 0.80.CC BY · PubMed Central
Figure 2 Temporal trends in CDDS autistic disorder (blue) and California IDEA autism data (red). For both CDDS and IDEA, age-resolved snapshots for 2002 (squares) and constant-age tracking data for 5 year-olds (triangles) are shown. Trends slopes (symbol b, in units of autism count per 104 per year) are approximated using least squares linear regression over birth year intervals 1988–1995 (for 2002 snapshots) and 1995–2001 (for 5 year-old tracking).
Figure 2 Temporal trends in CDDS autistic disorder (blue) and California IDEA autism data (red). For both CDDS and IDEA, age-resolved snapshots for 2002 (squares) and constant-age tracking data for 5 year-olds (triangles) are shown. Trends slopes (symbol b, in units of autism count per 104 per year) are approximated using least squares linear regression over birth year intervals 1988–1995 (for 2002 snapshots) and 1995–2001 (for 5 year-old tracking).CC BY · PubMed Central
Figure 3 Temporal trend in blood lead (Pb) concentration in U.S. children compared to the temporal trend in autism, constructed from a composite of CDDS 2002 snapshot data (covering birth years 1970–1997) and California IDEA 5 year-old tracking data for birth years 1995–2005 (see Section Method s for details).
Figure 3 Temporal trend in blood lead (Pb) concentration in U.S. children compared to the temporal trend in autism, constructed from a composite of CDDS 2002 snapshot data (covering birth years 1970–1997) and California IDEA 5 year-old tracking data for birth years 1995–2005 (see Section Method s for details).CC BY · PubMed Central
Figure 4 Temporal trend in autism compared to trends in highway sector emissions of direct PM2.5 and indirect PM2.5 and ozone precursor species. Emissions are normalized to the 1970 values for CO (=163 Mtons), NOx (=13 Mtons), and VOCs (=17 Mtons) and to the 1990 values for SO2 (=0.5 Mtons), and direct PM2.5 (=0.3 Mtons).
Figure 4 Temporal trend in autism compared to trends in highway sector emissions of direct PM2.5 and indirect PM2.5 and ozone precursor species. Emissions are normalized to the 1970 values for CO (=163 Mtons), NOx (=13 Mtons), and VOCs (=17 Mtons) and to the 1990 values for SO2 (=0.5 Mtons), and direct PM2.5 (=0.3 Mtons).CC BY · PubMed Central
Figure 5 Temporal trend in autism compared to temporal trend in cumulative amount of postnatal aluminum adjuvant administered to U.S. children by 18 months of age. Red circles are years with published immunization schedules. Red triangles reflect educated guesses (see Additional file 1 ) for details) in gap years without published schedules. The red curve is lagged 1 year because 18 month-olds born, e.g., in 1994 will likely follow the 1995 schedule.
Figure 5 Temporal trend in autism compared to temporal trend in cumulative amount of postnatal aluminum adjuvant administered to U.S. children by 18 months of age. Red circles are years with published immunization schedules. Red triangles reflect educated guesses (see Additional file 1 ) for details) in gap years without published schedules. The red curve is lagged 1 year because 18 month-olds born, e.g., in 1994 will likely follow the 1995 schedule.CC BY · PubMed Central
Figure 6 Temporal trend in autism compared to temporal trend in U.S. application of glyphosate to genetically-modified corn and soy crops, as estimated from US Department of Agriculture data (see Additional file 1 ).
Figure 6 Temporal trend in autism compared to temporal trend in U.S. application of glyphosate to genetically-modified corn and soy crops, as estimated from US Department of Agriculture data (see Additional file 1 ).CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

1 retracted

Show all 103 references

Research works printed but not linked: 7

  1. California Health and Human Services Agency, Dept. of Developmental Services: Autistic Spectrum Disorders. Changes in California Caseload. An Update: 1999 Through 2002. 2003, Sacramento, CA: California Health and Human Services Agency, Dept. of Developmental Services
  2. USEPA (United States Environmental Protection Agency): America’s Children and the Environment, Volume 13. 2013, 504-3
  3. Davis SC, Diegel SW, Boundy RG: Transportation Energy Data Book. 2010, Oak Ridge, TN: Center for Transportation Analysis, Oak Ridge National Laboratory, 29
  4. USEPA (United States Environmental Protection Agency): National Emissions Inventory (NEI) Air Pollutant Emissions Trends Data. 2012
  5. Institute of Medicine (IOM): Immunization Safety Review: Vaccines and Autism. 2004, Washington, D.C, 214-
  6. Osteen C, Livingston M: Pest Management Practices. In: Agricultural Resources and Environmental Indicators 2006 Edition, Chapter 4.3: In (Wiebe K, Gollehon N, Eds) EIB-16. 2006, Washington, DC: USDA
  7. Grube Donaldson D, Kiely T, Wu LA: Pesticides Industry Sales and Usage, 2006 and 2007 Market Estimates, US EPA. 2011

Cited by

Sorted by citations

Items 101–109 of 109

Related

See all

Metadata

Authors
Nevison, C. D.
Affiliations
Institute of Arctic and Alpine Research (US)
Corresponding author
Nevison, Cynthia D
ORCID
Nevison, Cynthia D
Venue
Environmental Health
Publisher
Springer Science and Business Media LLC
Published
2014-09-05
Volume
13
Issue
1
Pages
73-73
ISSN
1476-069X (ISSN-L)
DOI
10.1186/1476-069x-13-73
PMC
PMC4177682
OpenAlex
W2105742120
Cited by
111
References
103
Citations by year
2026: 7 · 2025: 3 · 2024: 5 · 2023: 5 · 2022: 10 · 2021: 12 · 2020: 11 · 2019: 5 · 2018: 9 · 2017: 21 · 2016: 9 · 2015: 14
FWCI
8.11
Type
journal article
Language
en
Open access
Licence
Locations
  • Environmental Health (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
  • Health Sciences › Medicine › Psychiatry and Mental health › Child Nutrition and Feeding Issues
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
Keywords
autism prevalence, temporal trends, environmental toxins, autism risk factors, lead exposure, organochlorine pesticides, vehicle emissions, polybrominated diphenyl ethers, alum adjuvant, glyphosate, diagnostic criteria revision, Individuals with Disabilities Education Act, children's environmental exposure
MeSH terms
Adolescent, Autistic Disorder, Child, Child, Preschool, Environmental Pollutants, Female, Humans, Male, United States, Prevalence

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review