Racial Disparities in Developmental Delay Diagnosis and Services

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UCLA Previously Published Works

Title

Racial Disparities in Developmental Delay Diagnosis and Services Received in Early

Childhood

Permalink

https://escholarship.org/uc/item/7g60302v

Journal

Academic Pediatrics, 21(7)

ISSN

1876-2859

Authors

Gallegos, Abraham

Dudovitz, Rebecca

Biely, Christopher

et al.

Publication Date

2021-09-01

DOI

10.1016/j.acap.2021.05.008

Peer reviewed

eScholarship.org Powered by the California Digital Library

University of California

Racial Disparities in Developmental Delay Diagnosis and

Services Received in Early Childhood

Abraham Gallegos, MD, MSHS

a,b

, Rebecca Dudovitz, MD, MSHS

, Christopher Biely, MS

Paul J. Chung, MD, MSHS

a,c,d

, Tumaini R. Coker, MD, MBA

, Elizabeth Barnert, MD, MPH,

, Alma D. Guerrero, MD, MPH

, Peter G. Szilagyi, MD, MPH

a,b

, Bergen B. Nelson, MD,

Department of Pediatrics, UCLA Mattel Children’s Hospital and Children’s Discovery &

Innovation Institute, David Geffen School of Medicine at University of California, Los Angeles,

Los Angeles, California

UCLA NRSA T32 Primary Care Research Fellowship, University of California, Los Angeles, Los

Angeles, California

Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA, USA

Department of Health Policy and Management, Fielding School of Public Health, University of

California, Los Angeles, Los Angeles, California

Department of Pediatrics, University of Washington and Seattle Children’s Research Institute,

Seattle, Washington

Children’s Hospital of Richmond at Virginia Commonwealth University, Richmond, Virginia

Abstract

Background and objectives: Racial disparities in diagnosis and receipt of services for

early childhood developmental delay (DD) are well known but studies have had difficulties

distinguishing contributing patient, healthcare system and physician factors from underlying

prevalence. We examine rates of physician diagnoses of DD by preschool and kindergarten entry

controlling for a child’s objective development via scoring on validated developmental assessment

along with other child characteristics.

Methods: We used data from the preschool and kindergarten entry waves of the Early Childhood

Longitudinal Study, Birth Cohort. Dependent variables included being diagnosed with DD by

a medical provider and receipt of developmental services. Logistic regression models tested

whether a child’s race was associated with both outcomes during preschool and kindergarten while

controlling for the developmental assessments, as well as other contextual factors.

Results: Among 7,950 children, 6.6% of preschoolers and 7.5% of kindergarteners were

diagnosed with DD. Of preschool children with DD, 66.5% were receiving developmental

Corresponding author: Abraham Gallegos; Department of Pediatrics, Mattel Children’s Hospital and Children’s Discovery &

Innovation Institute, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, California;

[email protected].

Conflict of interest statement: The authors have no financial relationships relevant to this article to disclose. It should be noted Dr.

Peter Szilagyi, Editor-in-Chief of Academic Pediatrics, is part of the authorship group.

HHS Public Access

Author manuscript

Acad Pediatr

. Author manuscript; available in PMC 2022 June 06.

Published in final edited form as:

Acad Pediatr

. 2021 ; 21(7): 1230–1238. doi:10.1016/j.acap.2021.05.008.

Author Manuscript Author Manuscript Author Manuscript Author Manuscript

services, while 69.1% of kindergarten children with DD were receiving services. Children who

were Black, Asian, spoke a primary language other than English and had no health insurance were

less likely to be diagnosed with DD despite accounting for cognitive ability. Black and Latinx

children were less likely to receive services.

Conclusion: Racial minority children are less likely to be diagnosed by their pediatric

provider with DD and less likely to receive services despite accounting for a child’s objective

developmental assessment. The pediatric primary care system is an important target for

interventions to reduce these disparities.

Keywords

developmental delay disparities; Early Childhood Longitudinal Study Birth cohort; Early

intervention

Background

Developmental disabilities affect approximately 16% of children and early identification

of delay and participation in developmental services is associated with individual and

societal benefits.

[1 2]

The pediatric primary care system plays an important role in caring for

children with developmental delay (DD), including providing developmental screening and

surveillance, facilitating a timely diagnoses, addressing any associated medical conditions

and linking families to services

[3]

. This is particularly true prior to school entry, as

pediatricians are often the only trained provider routinely assessing young children’s

development.

There exist multiple racial and ethnic disparities along the continuum of DD diagnosis

and management. These disparities likely represent the culmination of interconnecting

variables, including patient factors, health care system factors, and clinical encounter factors.

[4]

Minority children are less likely to be diagnosed with any form of DD as well as a

number of specific DD conditions.

[1 5]

For example, Latinx, Black and Asian children with

autism spectrum disorder and attention deficit hyperactivity disorder are diagnosed at a later

age and with more severe symptoms than white children.

[6–8]

Additionally, racial/ethnic

minority children are more likely to face disparities in the processes leading to a potential

diagnosis, as they are less likely to access high quality primary care services and their

parents are less likely to be asked about developmental concerns.

[9 10]

Finally, these children

are less likely to receive developmental services and less likely to be placed into special

education.

[11 12]

Many of the studies that have described disparities in DD diagnosis and

use of services have difficulty distinguishing whether these differences are driven by true

epidemiologic differences in prevalence of developmental delay versus health care system

or clinical encounter factors leading to under-recognition or poor management of existing

delays.

[13–15]

We take a unique analytic approach that allows us to more closely examine this distinction.

By accounting for objective measures of a child’s development (via score on validated

developmental assessment tool), access to well child care, and other contextual factors,

we test whether differences in parental report of receiving a DD diagnosis by a doctor

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across racial and ethnic groups, are largely driven by differences in the prevalence DD

versus patient, health care system, clinical encounter factors. Identifying the factors driving

these racial and ethnic disparities is critical to developing interventions to eliminate those

disparities moving forward.

METHODS

Data Source and Analytic Sample

We utilized the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B) database, a

nationally representative sample of children born in the United States in 2001 followed

longitudinally through kindergarten entry in 2006–2008. The analytic sample included

7,950 children with complete data on the primary outcome (diagnosis by preschool),

developmental trajectory (preschool models), and preschool sampling weight. Data were

collected from birth certificates, parent and guardian interviews, direct child assessments,

and reports from childcare providers and teachers when children were approximately 9

months, 2 years, 4 years (preschool wave), and 5–6 years old (kindergarten entry waves).

Approximately 14,000 births were sampled for the study and yielded 10,688 cases in the

first wave, for a response rate of 76%. Response rates in subsequent waves were 91%−93%.

There was a planned 15% reduction in the sample prior to the kindergarten entry waves;

6,900 children in the kindergarten entry waves completed direct assessments.

Measures

Outcomes—Diagnosis of DD by preschool and diagnosis of DD by kindergarten entry

were assessed with items from the 2-year, preschool, and kindergarten entry parent

interviews. During each interview, parents were asked “Has a doctor ever told you that

(child) has the following conditions?” Delay in learning to talk, another DD, and mental

retardation were listed among the possible conditions in the 2-year interview. In addition,

another DD, mental retardation, and autism or pervasive developmental disorders (PDD)

were listed among the possible conditions in the preschool interview and kindergarten entry

interviews. Children were considered to have a diagnosis by preschool if parents answered

yes to at least one of the above conditions from the 2-year interview or preschool interview.

Children were considered to have a diagnosis by kindergarten entry if parents answered

yes to at least one of the conditions from the 2-year interview, preschool interview, or

kindergarten entry interviews.

Services by preschool and services by kindergarten entry were assessed with items from the

2-year, preschool, and kindergarten entry parent interviews. During each interview, parents

were asked “For each service, please tell me if (child) or your family received this service

to help with (child’s) special needs. Has anyone in your household ever received…” Speech

or language therapy and special classes with other children were listed among the possible

services in the interviews. In addition, parents were asked, “Is (child) currently participating

in an early intervention program or regularly receiving any services for (his/her) conditions

from…” The local school district, a state or local health or social service agency, a doctor,

clinic, or other health care provider, and other sources were listed as the possible services in

the interviews. Children were considered to have services by preschool if parents answered

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yes to at least one of these services from the 2-year interview or preschool interview.

Children were considered to have services by kindergarten entry if parents answered yes to

at least one of these services from the 2-year interview, preschool interview, or kindergarten

entry interviews.

Child Characteristics—We identified child characteristics likely associated with the

diagnosis of a DD and receipt of services. Measures included child’s race/ethnicity

(non-Hispanic White, African American, Hispanic or Latino, Asian, other, multiracial),

highest level of parental education (less than high school diploma, high school diploma

or vocational degree, some college, bachelor’s degree or higher), child’s sex, household

income and poverty status, urbanicity (rural, urban), primary home language (English,

non-English), health insurance (yes, no), number of well-child visits between interviews,

center-based child care attendance (yes, no) and developmental trajectory. Health insurance

at the 9-month interview, 2-year interview, and preschool interview were included in the

preschool models and the kindergarten entry models. The kindergarten entry models also

included health insurance at the kindergarten 2006–2007 interview. The number of well-

child visits between the 9-month interview and 2-year interview (less than two, at least two)

and the number of well-child visits between the 2-year interview and preschool interview

(zero, at least one) were included in the preschool models and kindergarten entry models.

The kindergarten entry models also included the number of well-child visits between the

preschool interview and kindergarten entry interview (one, at least one). Center-based child

care attendance at the 9-month interview, 2-year interview, and preschool interview were

included in the preschool models and the kindergarten entry models.

We created a 4-category variable capturing if children scored in the lowest decile on

developmental assessments over time, allowing us to account for both their developmental

status at the time of each assessment, as well as their developmental trajectory over time.

For the preschool models, developmental trajectory was based on the Bayley Short Form-

Research Edition (BSF-R) mental scale score at the 9-month and 2-year interviews with

scoring as follows: 0 = both scores > 10th percentile, 1 = 9-month score ≤10th percentile and

2-year score > 10th percentile, 2 = 9-month score > 10th percentile and 2-year score≤10th

percentile, and 3 = both scores ≤10th percentile. For the kindergarten models, developmental

trajectory was based on the BSF-R mental scale score at the 2-year interview and early

reading and math item response theory (IRT) scale scores at the preschool interview. We

created a 4-category variable to assess whether a child had DD between preschool and

kindergarten as follows: 0 = 2-year BSF-R mental scale score > 10th percentile and 4-year

old preschool early reading and math scale scores > 10th percentile, 1 = 2-year BSF-R

mental scale score ≤10th percentile and 4-year-old preschool early reading and math scale

scores > 10th percentile, 2 = 2-year BSF-R mental scale score > 10th percentile and

4-year-old preschool early reading or math scale score ≤10th percentile, and 3 = 2-year

BSF-R mental scale score ≤10th percentile and preschool early reading or math scale score

≤10th percentile. This variable distinguished children consistently scoring above the bottom

decile from children scoring in the bottom decile.

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Analytic Approach—To identify child characteristics associated with the likelihood of

receiving a DD diagnosis at both the Preschool wave and Kindergarten wave, we conducted

a weighted multivariable logistic regression model of diagnosis by preschool and diagnosis

by kindergarten on child characteristics, respectively. To identify child characteristics

associated with receipt of developmental support services after a diagnosis has been made,

we conducted weighted multivariate logistic regression models of receipt of services by

preschool and receipt of services by kindergarten on the sample of children who had a

diagnosis of DD by preschool and by kindergarten, respectively. Both models included all

of the child characteristics described above, and controlled for the child’s developmental

status. Unweighted sample sizes were rounded to the nearest 50, as required by the National

Center for Education Statistics. Analyses were conducted using the “svy” suite of commands

in Stata 14.0 (StataCorp LP, College Station, TX) to account for the ECLS-B survey design

elements of stratification, clustering, and weighting.

Results

Table 1 displays the characteristics of our analytic sample. Among the 7,950 preschool and

kindergarten children in the analytic sample, 750 (6.6%) preschool children and 600 (7.5%)

kindergarten children were told by their physicians of a DD diagnosis. Of those preschool

children with a DD diagnosis, 500 (66.5%) were receiving developmental services, while

450 (69.1%) kindergarten children with a diagnosis of DD were receiving developmental

services.

Multiple child characteristics were associated with receiving a DD diagnosis by preschool

(Table 2). Children scoring in the bottom decile on standardized developmental assessment

at any time prior to preschool were more likely to be diagnosed. A child who scored below

the bottom decile on both the 9-month and 2-year assessments had the highest odds of being

diagnosed, with an aOR of 9.53 (95% CI 6.46–14.06). Male children were also more likely

to be diagnosed with DD (aOR 2.27, 95% CI 1.83– 2.81). Black children had the lowest

regression coefficient of other racial/ethnic groups to be diagnosed with DD (aOR 0.42,

95% CI 0.29–0.61). Asian children were also less likely to be diagnosed (aOR 0.56, 95%

CI 0.33–0.97), as were those whose primary language was not English (aOR 0.54, 95%

CI 0.32–0.93) and those who lacked health insurance at 2-years old (aOR 0.43, 95% CI

0.22–0.83). Conversely, children attending center-based child care during preschool were

more likely to obtain a diagnosis than those who did not attend (aOR 1.52, 95% CI 1.17 –

1.97).

Analyses examining child characteristics associated with receipt of developmental services

by preschool amongst those with a diagnosis of DD revealed that race/ethnicity,

developmental status, participation in center-based child care were significantly associated

with receiving services. Black and Latinx children had decreased odds of receiving services

by preschool (Table 2) (aOR 0.31, 95% CI 0.13 – 0.71 and aOR 0.35, 95% CI 0.15 – 0.

86, respectively). Children scoring in the bottom decile on both the 9-month and 2-year

assessments or those with downward trending developmental trajectory (scoring in the

lowest decile at 24-months) and children attending center-based child care during preschool

were more likely to receive developmental services (aOR 2.26, 95% CI 1.19 – 4.30).

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Similar characteristics were associated with the likelihood of receiving a diagnosis by

kindergarten to those associated with receiving a diagnosis in preschool (Table 3). Black

and Asian children had decreased odds of being diagnosed (aOR 0.49, 95% CI 0.28 –

0.87 and aOR 0.53, 95% CI 0.28 – 0.98, respectively). Once again scoring in the lowest

decile on either/both the 2-year and preschool developmental assessment was associated

with increased odds of receiving a diagnosis. Scoring in the lowest decile on both the 2-year

and the preschool assessments was associated with the highest odds of receiving a diagnosis,

with an aOR 13.05 (95% CI 8.18 – 20.82). Children with a non-English primary language

also had lower odds of receiving a diagnosis (aOR 0.47, 95% CI 0.27 – 0.84). Lastly,

children without insurance during the kindergarten wave were less likely to be diagnosed

(aOR 0.35, 95% CI 0.13 – 0.95). Characteristics associated with receiving developmental

support services by kindergarten included race, economic status and parental education.

Black children with a diagnosis had lower odds of receiving services (aOR 0.29, 95% CI

0.11–0.78), as were children living in homes with income 100% - below 130% of the federal

poverty limit (aOR 0.27, 95% CI 0.09 - .85) when compared to children living in homes

with income at or above 185% of the federal poverty limit (Table 3).

Discussion

In this nationally representative cohort of children, we found that a child’s race/ethnicity,

sex, primary-language spoken at home, insurance status, child care attendance and

objectively measured developmental trajectory were all associated with parents reporting

having being told by a doctor that their child have a DD diagnosis. Children scoring in

the bottom decile of a validated developmental assessment (BSF-R) at either the preschool

and/or kindergarten wave were more likely to have parents who reported their child had a

DD diagnosis and more likely to receive EI services. Notably, parents of children who were

racial/ethnic minorities and those who lived in non-English primary language households

were less likely to report being told by a doctor of a DD diagnosis despite taking into

account multiple patient and healthcare system factors on multivariable logistic regression.

The persistence of decreased odds of receiving a DD diagnosis even after controlling

for access to well child care visits, socioeconomic status, child’s sex, geographical

residential area, insurance status, child care attendance, and scores on formal developmental

assessments over time, suggest that lower likelihood of receiving a DD diagnosis among

racial/ethnic and non-English speaking children are not explained by differences in the

underlying prevalence of DD nor are they explained by the multiple patient and health care

system variables we accounted for.

There are multiple potential sources of this disparity. There are patient factors we were

unable to account for including parental understanding of normal development. Parents

of minority, non-English primary language children may have a different understanding

of normal pediatric development and developmental disorders that may lead to different

help-seeking behavior.

[16 17]

There are healthcare system factors we were unable to account

for, notably access to validated developmental screening, provider availability or quality

of care. Ethnic minority children and children in a non-English primary language home

have been shown to have poorer primary care quality, less access to family-centered care

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and receive poorer anticipatory guidance.

[18–20]

These children also have decreased access

to formal developmental assessment by being less able to see developmental behavioral

specialists and less likely to receive a formal developmental assessment by EI, though some

of these differences may be driven, in part, by decreased EI referral rates by primary care

providers.

[21–24]

Physician and clinical encounter factors were also largely unexplored. Ethnic minority

children and children in a non-English primary language home are more likely to have

ineffective physician interactions due to difficulties in communication.

[25]

Physicians may

also be under the influence of implicit bias which may impact the encounter by contributing

to difficulties in communication and by impacting the medical decision making process.

[26 27]

In our specific study, our outcome variable was defined as “being told by a doctor”

of a DD diagnosis. It is possible some of our disparities described are a result of physicians

inadequately explaining a diagnosis. Both families and physicians may also lack knowledge

of the EI referral process, which has been recognized to be a barrier to EI referrals

and follow-up.

[28 29]

Decreased use of developmental screening and overreliance on the

generally less sensitive practice of developmental surveillance may also contribute.

Whether the factors contributing to the observed disparities are occurring inside or

outside of the pediatric primary care clinic, pediatric primary care providers manage the

culmination of potentially inadequate care and bear a large responsibility for identifying DD,

communicating that diagnosis, and connecting a child with developmental services. Hence,

it is critical to that pediatricians have the resources necessary to delivery care in a way that

advances health equity.

Potential interventions to reduce the disparities observed in this study include integrating

developmental and primary care services with the use of developmental specialist,

parent coaches or developmental programs focused around strengthening the parent-child

relationship via videotaping parental-patient interactions.

[30–32]

These programs work to

both educate parents and facilitate communication between parents and the pediatric team.

Improving reimbursement rates for developmental screening can serve to increase their

use. Building an infrastructure within the pediatric clinic, with case managers and social

workers to improve screening completion and follow up of DD referrals. Physicians need

training in cross-cultural communication and strategies to mitigate implicit bias. Finally,

we must recognize the role of systemic racism in contributing to and perpetuating these

disparities.

[33]

As child health providers, we should advocate for policy changes that can

improve child health equity, including, advocating for improved quality of pediatric primary

care, combatting childhood poverty, increased rates of reimbursement for developmental

screening, improved quality and access to public preschool and child care, increased

administrative workers dedicated to assuring equal utilization of EI services and improving

cultural competency and cross cultural communication training.

This present study has several limitations. We used the ECLS-B, and while it is a nationally

representative cohort, we were limited by the available variables. Diagnosis was determined

by parental report, which may under-estimate the true rate of diagnosis for DD. We also

recognize that our outcome variable is dependent entirely on parental report and it is largely

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reliant on parental recall and it is possible differences in recall may be contributing to

disparities described; however, studies demonstrate parental recall of medical diagnosis

correlate well with pediatricians’ records, even for specific DD diagnoses and even while

accounting for parental education.

[34 35]

Additionally, data collection concluded in 2007, and

the prevalence of DD has increased in recent years, which may impact the generalizability

of our findings to the current era. However, we believe that many of the barriers and

facilitators to diagnosis and management of DD are unlikely to have significantly. Despite

these limitations we feel this study has important implications for pediatricians and child

health advocates.

Conclusion

The study is the first to demonstrate racial and ethnic disparities in parental reports’ of DD

diagnoses, accounting for children’s developmental status. Specifically, Black and Asian

children, as well as children from non-English speaking households were less likely to

receive a DD diagnosis and/or receive services for DD. This finding points to a critical

need to develop and test interventions to reduce these disparities, including those delivered

in clinical settings. Primary care providers have the potential to play a critical role in

developing and implementing interventions to reduce disparities in access to developmental

support services, as they are often the only professional with developmental training who

regularly see children and families prior to starting school. As both direct providers and

child health advocates, pediatricians are well poised to ensure that all children receive

regular developmental screening, which supports timely diagnosis of delays, and the

necessary care coordination to access services to ultimately maximize their developmental

potential and reduce health disparities starting from a young age.

Funding source:

UCLA NRSA T32 Primary Care Research Fellowship, UL1TR000124 and KL2TR000122 from the National

Institutes of Health/National Center for Advancing Translational Science, through the UCLA Clinical and

Translational Sciences Institute

Role of Funder/Sponsor:

The funder/sponsor did not participate in the work.

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Table 1:

Characteristics of sample population (weighted sample)

N = 7,950 Percentage (N)

Race

White 53.8 (3,500)

Black 13.8 (1,250)

Hispanic 25.2 (1,550)

Asian 2.6 (750)

Other 0.7 (250)

Multiracial 3.9 (650)

Annual Household Income

≥ 185% of FPL 53.7 (4,300)

130% - below 185% of FPL 12.6 (1,000)

100% - below 130% of FPL 9.9 (750)

< 100% of FPL 23.8 (1,900)

Highest Parental Education

≥ Bachelor’s 31.5 (2,850)

Some college 25.9 (2,000)

High school diploma/vocational 29.7 (2,150)

< High school diploma 12.9 (950)

Child Sex

Female 48.8 (3,900)

Male 51.2 (4,050)

Urbanicity

Rural 15.2 (1,300)

Urban 84.9 (6,700)

Primary Language Spoken at Home

English 81.0 (6,400)

Non-English 19.0 (1,550)

Health Insurance

9-months 2-years Preschool Kinder

Yes 95.9 (7,700) 95.7 (7,650) 95.2 (7,600) 95.6 (5,900)

No 4.1 (250) 4.3 (300) 4.8 (350) 4.4 (250)

Well-child Visit in the past year (2 years old)

≥2 88.9 (7,050)

<2 11.1 (850)

Well-child Visit in the past year (Preschool)

≥1 96.3 (7,650)

0 3.7 (250)

Well-child Visit in the past year (Kindergarten)

≥1 95.8 (5,850)

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N = 7,950 Percentage (N)

0 4.2 (250)

Center-based Child Care Attendance 9-months 2-years Preschool

Yes 9.1 (700) 17.1 (1,350) 54.6 (4,500)

No 90.9 (7,250) 82.9 (6,650) 45.4 (3,450)

Developmental Trajectory (Preschool models)

>10

percentile 9-month BSF-R mental score and >10

percentile 2-year

BSF-R mental score

81.8 (6,000)

<=10

percentile 9-month BSF-R mental score and >10

percentile 2-

year BSF-R mental score

8.3 (900)

>10

percentile 9-month BSF-R mental score and <=10

percentile 2-

year BSF-R mental score

8.2 (750)

<=10

percentile 9-month BSF-R mental score and <=10

percentile

2-year BSF-R mental score

1.8 (300)

Developmental Trajectory (Kindergarten models)

>10

percentile 2-year BSF-R mental score and >10

percentile for both

preschool academic scores

78.1 (5,750)

<=10

percentile 2-year BSF-R mental score and >10

percentile for

both preschool academic scores

5.5 (600)

>10

percentile 2-year BSF-R mental score and <=10

percentile at least

one preschool academic score

13.0 (900)

<=10

percentile 2-year BSF-R mental score and <=10

percentile at

least one preschool academic score

3.4 (350)

Diagnosis (by Preschool)

No 93.4 (7,250)

Yes 6.6 (750)

Diagnosis (by Kindergarten entry)

No 92.5 (5,500)

Yes 7.5 (600)

Services (by Preschool)

No 33.5 (250)

Yes 66.5 (500)

Services (by Kindergarten entry)

No 30.9 (200)

Yes 69.1 (450)

Unweighted sample sizes are rounded to the nearest 50, as required by the National Center for Education Statistics. We used a kindergarten entry

wave sampling weight for the kindergarten entry variables. For the other variables, we used a preschool wave sampling weight. Receipt of services

by preschool and receipt of services by kindergarten entry were restricted to children who had a diagnosis of developmental delay by preschool and

kindergarten entry, respectively.

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Table 2:

Diagnosis and service for preschool

Preschool Diagnosis Preschool Services

Odds ratio p-value 95% CI Odds ratio p-value 95% CI

Race

White Reference Reference

Black 0.42 <0.001 0.29–0.61 0.31 0.01 0.13 – 0.71

Hispanic 0.84 0.47 0.53– 1.34 0.35 0.02 0.15 – 0.86

Asian 0.56 0.04 0.33– 0.97 0.37 0.11 0.11 – 1.26

Other 0.99 0.98 0.50– 1.97 0.61 0.46 0.16 – 2.29

Multiracial 0.52 0.03 0.30– 0.92 0.79 0.69 0.25 – 2.49

Annual household income

At or above 185% of the poverty level Reference Reference

below 100% poverty 1.41 0.07 0.97– 2.07 0.65 0.23 0.33 – 1.31

100% - below 130% poverty 0.96 0.86 0.59 – 1.54 0.43 0.17 0.13 – 1.43

130% - below 185% poverty 1.08 0.72 0.69– 1.70 0.56 0.22 0.22 – 1.42

Highest parental education

≥ Bachelor’s Reference Reference

Some college 0.95 0.79 0.63– 1.43 1.06 0.87 0.56 – 2.00

HS diploma 0.79 0.28 0.51– 1.22 1.87 0.09 0.91 – 3.82

< HS diploma 0.79 0.40 0.46– 1.36 1.79 0.25 0.66 – 4.88

Child Sex

Female Reference Reference

Male 2.27 <0.001 1.83– 2.81 1.39 0.29 0.75 – 2.59

Urbanicity

Rural Reference Reference

Urban 0.89 0.55 0.62– 1.30 1.39 0.42 0.62 – 3.12

Primary Language spoken at home

English Reference Reference

Non-English language 0.54 0.03 0.32– 0.93 0.77 0.55 0.33 – 1.81

Insurance status: 9 months, 2 years, preschool

Yes Reference Reference

9 months: No insurance 1.16 0.75 0.47– 2.87 0.34 0.18 0.07– 1.64

24 months: No insurance 0.43 0.01 0.22– 0.83 0.47 0.38 0.09 – 2.55

Preschool: No insurance 0.90 0.77 0.45– 1.81 0.90 0.89 0.20 – 4.10

Well child visits: 9 months – 2 years

≥ 2 Well child visits from 9 months to 2 years Reference Reference

< 2 Well child visits from 9 months to 2 years 1.19 0.38 0.81– 1.74 0.93 0.87 0.38 – 2.27

Well child visits: 2 years to preschool

≥ 1 Well child visits 2 years to preschool Reference Reference

0 Well child visits 2 years to preschool 0.67 0.31 0.31– 1.47 0.36 0.30 0.05 – 2.54

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Preschool Diagnosis Preschool Services

Odds ratio p-value 95% CI Odds ratio p-value 95% CI

Child is in center-based child care

No Reference Reference

9 months: yes 0.97 0.88 0.61 – 1.54 1.12 0.83 0.39 – 3.24

2 year: yes 1.33 0.09 0.95 – 1.86 1.17 0.61 0.64 – 2.12

Preschool: yes 1.52 0.002 1.17 – 1.97 2.26 0.01 1.19 – 4.30

Developmental trajectory:

9-month BSF-R mental score, 2-year BSF-R mental score

>10

% 9-month BSF-R score, >10

% 2-year BSF-R score

Reference Reference

<=10

% 9-month BSF-R score, >10

% 2-year BSF-R score

2.39 <0.001 1.61– 3.54 0.94 0.85 0.50 – 1.77

>10

% 9-month BSF-R score, <=10

% 2-year BSF-R score

7.16 <0.001 5.13– 10.01 2.84 <0.001 1.63 – 4.94

<=10

% 9-month BSF-R score, <=10

% 2-year BSF-R

score

9.53 <0.001 6.46– 14.06 3.25 0.04 1.08 – 9.71

We used a preschool wave sampling weight for the preschool models.

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Table 3

Diagnosis and service for kindergarten entry

Kindergarten Diagnosis Kindergarten Services

Odds ratio p-value 95% CI Odds ratio p-value 95% CI

Race

White Reference Reference

Black 0.49 0.02 0.28 – 0.87 0.29 0.02 0.11 – 0.78

Hispanic 0.80 0.40 0.47 – 1.35 0.45 0.12 0.16 – 1.23

Asian 0.53 0.04 0.28 – 0.98 0.39 0.19 0.09 – 1.61

Other 0.94 0.89 0.43 – 2.09 1.19 0.81 0.29 – 4.85

Multiracial 0.58 0.18 0.26 – 1.28 0.58 0.51 0.11 – 3.01

Annual household income

At or above 185% of the poverty level Reference Reference

below 100% poverty 1.29 0.33 0.77 – 2.18 0.81 0.62 0.35 – 1.87

100% - below 130% poverty 1.01 0.98 0.53 – 1.91 0.27 0.03 0.09 – 0.85

130% - below 185% poverty 1.20 0.43 0.79 – 1.91 0.73 0.58 0.24 – 2.23

Highest parental education

≥ Bachelor’s Reference Reference

Some college 0.67 0.11 0.40 – 1.10 1.06 0.88 0.51 – 2.19

HS diploma 0.79 0.40 0.46 – 1.36 3.18 0.02 1.23 – 8.27

< HS diploma 0.64 0.20 0.32 – 1.28 1.43 0.56 0.41 – 4.96

Child sex

Female Reference Reference

Male 2.28 <0.001 1.57 – 3.31 1.12 0.76 0.55 – 2.29

Urbanicity

Rural Reference Reference

Urban 1.06 0.81 0.66 – 1.71 1.23 0.60 0.56 – 2.71

Primary Language spoken at home

English Reference Reference

Non-english language 0.47 0.01 0.27 – 0.84 1.23 0.72 0.39 – 3.81

Insurance status: 9 months, 2 years, preschool,

kindergarten

Yes Reference Reference

9 months: No insurance 0.92 0.89 0.29 – 2.91 2.69 0.27 0.46 – 15.78

24 months: No insurance 0.61 0.33 0.22 – 1.68 0.13 0.14 0.01 – 1.90

Preschool: No insurance 0.63 0.42 0.20 – 1.95 0.67 0.70 0.08 – 5.47

Kindergarten: No insurance 0.35 0.04 0.13 – 0.95 0.70 0.74 0.08 – 5.92

Well child visits: Number of visits, 9 months – 2 years

≥ 2 Well child visits Reference Reference

< 2 Well child visits 0.96 0.86 0.59 – 1.56 0.52 0.28 0.16 – 1.73

Well child visits: Number of visits, 2 years to preschool

≥ 1 Well child visits Reference Reference

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Kindergarten Diagnosis Kindergarten Services

Odds ratio p-value 95% CI Odds ratio p-value 95% CI

0 Well child visits 0.91 0.84 0.34 – 2.43 0.68 0.77 0.05 – 9.22

Well child visits: Number of visits, preschool to kinder

≥ 1 Well child visits Reference Reference

< 0 Well child visits 0.44 0.11 0.16 – 1.21 0.11 0.11 0.01 – 1.71

Child is in center-based child care

No Reference Reference

9 months: yes 0.61 0.10 0.34 – 1.11 1.13 0.85 0.30 – 4.20

2 year: yes 1.37 0.17 0.88 – 2.13 1.95 0.07 0.94 – 4.02

Preschool: yes 1.71 0.002 1.22 – 2.40 2.12 0.06 0.98 – 4.62

Developmental trajectory: 2-year BSF-R mental scale

score, Preschool early reading and math IRT scale scores

>10

% 2-year BSF-R score, >10

% Preschool score

Reference Reference

<=10

% 2-year BSF-R score, >10

% Preschool score

6.52 <0.001 4.32 – 9.84 2.37 0.12 0.79 – 7.07

>10

% 2-year BSF-R score, <=10

% Preschool score

2.83 <0.001 1.86 – 4.32 0.74 0.51 0.30 – 1. 84

<=10

% 2-year BSF-R score, <=10

% Preschool score

13.05 <0.001 8.18 – 20.82 2.47 0.06 0.95 – 6.42

We used a kindergarten entry wave sampling weight for the kindergarten entry models.

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