ImportanceThe Modified Checklist for Autism in Toddlers (M-CHAT) and the M-CHAT, Revised With Follow-up (M-CHAT-R/F)—henceforth referred to as M-CHAT(-R/F)—are the most commonly used toddler screeners for autism spectrum disorder (ASD). Their use often differs from that in the original validation studies, resulting in a range of estimates of sensitivity and specificity. Also, given the variability in reports of the clinical utility of the M-CHAT(-R/F), researchers and practitioners lack guidance to inform autism screening protocols.ObjectiveTo synthesize variability in sensitivity and specificity of M-CHAT(-R/F) across multiple factors, including procedures for identifying missed cases, likelihood level, screening age, and single compared with repeated screenings.Data SourcesA literature search was conducted with PubMed, Web of Science, and Scopus to identify studies published between January 1, 2001, and August 31, 2022.Study SelectionArticles were included if the studies used the M-CHAT(-R/F) (ie, original or revised version) to identify new ASD cases, were published in English-language peer-reviewed journals, included at least 10 ASD cases, reported procedures for false-negative case identification, screened children by 48 months, and included information (or had information provided by authors when contacted) needed to conduct the meta-analysis.Data Extraction and SynthesisThe systematic review and meta-analysis was conducted within the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. The Quality Assessment of Diagnostic Accuracy Studies–2 tool evaluated bias in sample selection. Data extraction and quality assessment were performed by 2 authors independently. The overall diagnostic accuracy of the M-CHAT(-R/F) was assessed with the hierarchic summary receiver operating characteristic (HSROC) model.Main Outcomes and MeasuresSensitivity, specificity, diagnostic odds ratios, and HSROC curves of M-CHAT(-R/F).ResultsThe review included 50 studies with 51 samples. The pooled sensitivity of M-CHAT(-R/F) was 0.83 (95% CI, 0.77-0.88), and the pooled specificity was 0.94 (95% CI, 0.89-0.97). Heterogeneity analyses revealed greater diagnostic accuracy for low- vs high-likelihood samples, a concurrent vs prospective case confirmation strategy, a large vs small sample size, use of M-CHAT(-R/F) Follow-up, and non-English vs English only.Conclusions and RelevanceOverall, results of this study suggest the utility of the M-CHAT(-R/F) as an ASD screener. The wide variability in psychometric properties of M-CHAT(-R/F) highlights differences in screener use that should be considered in research and practice.

We examined the relationship between maternal intake of established dietary patterns and child autism-related outcomes in two prospective cohorts in the United States. Participants were drawn from the Early Autism Risk Longitudinal Investigation (EARLI, n = 154) and the Nurses’ Health Study II (NHSII, n = 727). Dietary information was collected via food frequency questionnaires (FFQs) and used to calculate the empirical dietary inflammatory pattern (EDIP), Alternative Healthy Eating Index (AHEI), Western and Prudent dietary patterns, and the alternative Mediterranean Diet (aMED) score. Primary analyses examined associations with continuous autism-related traits as measured by the Social Responsiveness Scale (SRS), and secondary analyses with autism spectrum disorder (ASD) diagnosis. We used crude and multivariable quantile regression fixed at the 50th percentile to examine associations between quartiles of dietary patterns and SRS scores, and logistic regression to examine associations with ASD diagnosis. There was suggestion of a positive association with the Western diet (Q4 vs. Q1, ß = 11.19, 95% CI: 3.30, 19.90) in EARLI, though the association was attenuated with adjustment for total energy intake, and no clear associations were observed with other dietary patterns and ASD diagnosis or SRS scores. Further work is needed to better understand the role of maternal dietary patterns in ASD and related outcomes.

Prior work has suggested associations between prenatal exposure to several classes of pesticides and child autism spectrum disorder (ASD). We examined a previously developed pesticide residue burden score (PRBS) and intake of high pesticide residue foods in association with ASD‐related traits. Participants were drawn from the Early Autism Risk Longitudinal Investigation (EARLI) (n = 256), a cohort following mothers who previously had a child with ASD through a subsequent pregnancy and that child's development. ASD‐related traits were captured according to total Social Responsiveness Scale (SRS) scores at age 3 (mean raw total SRS score = 35.8). Dietary intake was assessed through a food frequency questionnaire collected during pregnancy. We also incorporated organic intake and fatty foods in modified versions of the PRBS. Associations between high‐residue fruit and vegetable intake, the overall PRBS and modified versions of it, and SRS scores were assessed using multivariable linear regression. Overall, we did not observe associations between pesticide residues in foods and ASD‐related outcomes, and modified versions of the PRBS yielded similar findings. However, reductions in ASD‐related traits were observed with higher overall fruit and vegetable intake (adjusted estimates for Q4 vs. Q1: β −12.76, 95%CI −27.8, 2.3). Thus, findings from this high familial probability cohort did not suggest relationships between pesticide residues in the diet according to the PRBS and ASD‐related traits. Beneficial effects of fruit and vegetable intake may influence these relationships. Future work should consider fruit and vegetable intake in association with ASD‐related outcomes. Lay Summary Diet is the main source of exposure to most pesticides in use today. In this study, we examined the relationship between pesticide exposure from residues in the diet during pregnancy and child autism‐related traits. We found that these pesticide residues from the diet were not related to child autism‐related outcomes at age three. However, higher prenatal fruit and vegetable intake was associated with reductions in child autism‐related traits.

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Background The Social Responsiveness Scale (SRS) is a 65‐item measure yielding a continuous score capturing autism‐related traits. Scores based on SRS item subsets have been analytically examined but administration of shortened versions has not been evaluated prospectively. Objective The goal of this study was to compare psychometric properties of two shortened versions of the SRS to the full 65‐item SRS, in young children from both a clinical and general population setting. Methods Study participants (aged 3–5 years) were drawn from the AJ Drexel Autism Institute clinic (n = 154) and Kaiser Permanente Northern California (n = 201) and block randomized to receive either the 16‐item short SRS, a newly developed computer adaptive testing‐SRS, or the published full‐length SRS. Total scores across the three SRS administration methods were scaled to facilitate comparisons. Scores were plotted to assess distributional properties, while Receiver Operating Characteristic analysis was used to estimate Area Under the Curve (AUC) and address predictive ability. Results Overall, distributional properties of the three administration methods were highly comparable, with shortened measures demonstrating similar ability to capture the range of the distribution and case non‐case separation as the full SRS. In addition, AUC values were high (0.91–0.97) and comparable across the administration methods, though there was evidence of difference in predictive ability across measures for females (AUC for full SRS = 0.99 vs. 0.84 for short). Within individual comparisons of short versus full scores (available only for participants at the general population site) suggested underestimation of actual full SRS scores with the CAT‐SRS. Conclusions Our findings broadly support the construct validity and performance of shortened SRS versions examined here, though the full measure may be needed to more accurately assess traits consistent with ASD diagnosis in females. This work suggests opportunities for collection of ASD‐related phenotype in settings where participant burden or feasibility considerations may have otherwise prohibited such measurement.