Photo of an ethnically diverse group of 4-year-old girls and boys holding hands and smiling.

How many 4-year-old children were identified with ASD in Minnesota?

2.5% is hte average percentage identified with autism

1 in 40 4-year-old children were identified with autism in the ADDM Network

Using data from 2022, MN-ADDM researchers found 1 in 40 (2.5%) 4-year-old children were identified with autism. This is similar to the overall ADDM Network prevalence of 4-year-old children identified with autism (1 in 34 or 2.9%) in the United States where the CDC tracked ASD in 2022. This rate is higher than the rate of 1 in 53 (1.9%) that was found in 2020 in Minnesota.

Which children were more likely to be identified with ASD in Minnesota?

Males were 2.8 times more likely to be identified with autism than females.

Prevalence of autism in 4-year-old children in Minnesota by U.S. Census race and ethnicity

Race and Ethnicity

Prevalence Estiamte

Prevalence per 1,000 children

95% Confidence Interval

Prevalence Ratio Compared to White

Overall

1 in 40

25

(27.7-27.1)

Asian/Pacific Islander

1 in 39

25.6

(19.9-33.0)

1.7*

Black

1 in 26

38

(32.5-44.4)

2.5*

Hispanic

1 in 30

33

(25.8-42.0)

21.*

Multiracial

1 in 35

28.4

(20.2-39.8)

1.8*

White

1 in 65

15.5

(12.9-18.5)

--

American Indian or Alaska Native children were included in the denominator but were not included in prevalence estimations due to low numbers of children with ASD

*Significant prevalence ratio (95% CI excludes 1.0).

Asian/Pacific Islander, Black, Hispanic, and Multiracial children had higher autism prevalence than White children.

When were 4-year-old children first diagnosed with ASD in Minnesota?

Cumulative incidence refers to the rate of identification over time. Compared with children aged 8 years, Minnesota 4-year-olds had a higher cumulative incidence than 8-year-olds, meaning ASD identification is happening at a faster pace in the younger age group than the older age group. Minnesota 4-year-olds were identified at 1.5 times the rate of 8-year-olds.

MN 4-year-olds were identified at the same rate (1.1) as 8-year-olds
US 4-year-olds were identified at 1.7 times the rate of 8-year-olds

Tracking Area

The tracking area included parts of three counties (Anoka, Hennepin, Ramsey) including the large metropolitan cities of Minneapolis and Saint Paul.

4-year-old children in the tracking area included 17,069 children of the following race and ethnicity

  • American Indian or Alaska Native - 1%
  • Asian or Pacific Islander (including Hmong) – 13%
  • Black, non-Hispanic (including Somali) – 23%
  • Hispanic –11%
  • White, non-Hispanic – 45%
  • Two or more races – 7%

Implications

This is the fifth time Minnesota data has been included in findings from the ADDM Network and the third time we have included 4-year-old prevalence. Overall prevalence of autism among 4-year-olds in 2022 (1 in 40) was higher than prevalence among 4-year-olds in 2020 (1 in 53), but similar to prevalence among 4-year-olds in 2018 (1 in 44). Autism prevalence increased between 2020 and 2022 for both males and females and across all race/ethnicity categories. The portions of Ramsey and Hennepin counties included in prevalence estimates differed in 2018, 2020, and 2022 which may have impacted prevalence estimates.

In Minnesota, and across the ADDM network, we saw a decrease in the male-to-female ratio of autism prevalence. In the past, males typically had an autism rate 4 times higher than females. In 2022, the male: female ratio was 2.8 in Minnesota and 2.8 across ADDM sites combined. (Note: the ADDM project only collects data on male and female sex as indicated in records and does not include gender identification information.) In terms of race/ethnicity, as in 2020, we saw higher rates of autism for Asian/Pacific Islander, Black, and Hispanic children compared to White. We also saw a higher autism rate for Multiracial children compared to White in 2022; these two groups had similar autism rates in 2020.

In Minnesota, we identify autism much later than when first concerns are reported. We found that 4-year-old children are being identified with autism at about the same rate as 8-year-olds, which indicates that identification is not happening more frequently at earlier ages. Minnesota’s cumulative incidence rate for 4-year-olds lags behind that of the ADDM network overall. The slow rate of early identification in Minnesota is concerning due to the critical importance of early identification and intervention. Many states, including MN, have invested in early intervention to help children and families gain access to early intervention services. For example, Minnesota’s Early Intensive Developmental and Behavioral Intervention (EIDBI) Benefit provides early intensive intervention for people with autism and related conditions. To learn more about the EIDBI benefit follow this link:

https://mn.gov/dhs/partners-and-providers/news-initiatives-reports-workgroups/long-term-services-and-supports/eidbi/eidbi.jsp

Limitations

The findings in this report reflect a small number of children concentrated in a large metropolitan area and may not reflect prevalence across the entire state.

The numbers of 4-year-old children with autism from some racial/ethnic groups are small, and their prevalence estimates will be less precise than estimates for larger-sized populations. Confidence intervals show the range in which we are 95% confident that true prevalence lies, and a larger confidence interval means less precision (e.g., 19.9–33.0 for Asian/Pacific Islander children). This tells us we should use caution before drawing conclusions about differences between some groups.

MN-ADDM reviewed records from participating public school special education programs but did not review private school education records or all charter school education records in our geographic area. Similarly, if a child was identified with autism in a clinic outside of those included in MN-ADDM’s geographic area, their health records may not have been captured. Incomplete information could lead to misclassifying children’s cognitive ability, overestimating the age when they were first evaluated or when autism was identified, or failing to capture that the children were identified as having autism.