Evidence map›Paper›PMID 39994155›Full record

ArticleJournal of racial and ethnic health disparities2026

Associations Between Sociodemographic Predictors and Age of Referral for Autism Spectrum Disorder (ASD) Diagnosis Since the Beginning of the COVID-19 pandemic.

Mallika Mathur, Ruosha Li, Sandra McKay, Christine Markham, Deepali K Ernest, Shreela Sharma

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Article in Journal of racial and ethnic health disparities, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Mallika MathurDepartment of Epidemiology, Center for Health Equity, School of Public Health, The University of Texas Health Science Center at Houston, 1200 Pressler Street, Houston, TX, 77030, USA. mallika.mathur@uth.tmc.edu.
Ruosha LiDepartment of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Sandra McKayDepartment of Pediatrics, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Christine MarkhamDepartment of Health Promotion and Behavioral Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Deepali K ErnestDepartment of Epidemiology, Center for Health Equity, School of Public Health, The University of Texas Health Science Center at Houston, 1200 Pressler Street, Houston, TX, 77030, USA.
Shreela SharmaDepartment of Epidemiology, Center for Health Equity, School of Public Health, The University of Texas Health Science Center at Houston, 1200 Pressler Street, Houston, TX, 77030, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeSociodemographic characteristics, such as race and ethnicity, are associated with delays in ASD diagnosis. However, limited literature has examined the characteristics associated with delayed diagnosis since the start of the COVID-19 pandemic. This study aimed to identify the individual and aggregate sociodemographic characteristics associated with the age at which a child receives a referral for a diagnosis (from March 2020 to May 2023) and evaluate the impacts of the pandemic on this association.

methodsUsing cross-sectional data obtained from patients' electronic health records and the U.S. Census Bureau, we examined associations using linear regressions (N = 507). A subgroup analysis was conducted comparing two pandemic-related time frame phases: acute (March 2020-December 2021) and endemic (January 2022-May 2023).

resultsThe mean age of referral was 37.3 months; 83.2% were Medicaid recipients, 42.6% were Latino/Hispanic, and 29.8% were Black non-Hispanic. Children were referred for an evaluation at an older age during the acute phase compared to the endemic phase (40.4 vs. 35.4 months). There were no significant associations between race and ethnicity and age of referral. Population educational attainment was negatively associated with the age of referral (p < 0.05). The subgroup analysis showed a positive association between median population income and age of referral during the endemic phase (p < 0.05).

conclusionReferrals to receive a diagnosis occur later than the screening recommendations. Future work should focus on developing health system-wide practices, particularly among health systems serving large proportions of underserved populations, targeting early referrals for an evaluation to receive an ASD diagnosis.

Indexed as

Autism Spectrum DisorderCOVID-19Delayed DiagnosisReferral and ConsultationAge FactorsChildChild, PreschoolCross-Sectional StudiesEthnicityFemaleHumansInfantMalePandemicsSARS-CoV-2Sociodemographic FactorsAge of referralAutism spectrum disorderChildrenCOVID-19Sociodemographic

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.