Role of Primary Care Clinician Concern During Screening for Early Identification of Autism.

OBJECTIVE: The aim of this study was to evaluate the added value of primary care clinician (PCC)-indicated concern during primary care universal standardized screening in early identification of autism. METHODS: Toddlers were screened for autism during primary care checkups (n = 7,039, aged 14.24-22.43 months) in 2 studies. Parents completed the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up. For each participant, PCCs indicated whether they had autism concerns (optional in 1 study-before or after viewing screening results, required before viewing screen results in the other). Children at high likelihood for autism from screen result and/or PCC concern (n = 615) were invited for a diagnostic evaluation; 283 children attended the evaluation. RESULTS: Rates of PCC-indicated autism concerns were similar whether PCCs were required or encouraged to indicate concerns. High likelihood of autism indication on both screen and PCC concern resulted in the highest positive predictive value for autism and positive predictive value for any developmental disorder, as well as the highest evaluation attendance, with no significant difference between the positive screen-only and PCC concern-only groups. Although the frequency of PCC-indicated autism concern did not differ significantly based on the child's cognitive level, PCCs were more likely to identify children with more obvious autism characteristics compared with more subtle autism characteristics as having autism. CONCLUSION: The findings support the recommendation of the American Academy of Pediatrics that both screening and surveillance for autism be incorporated into well-child visits. High likelihood of autism on either screen or PCC concern should trigger a referral for an evaluation.

Age and sex differences in the association between neighborhood socioeconomic environment and incident diabetes: Results from the diabetes location, environmental attributes and disparities (LEAD) network.

Objective: Worse neighborhood socioeconomic environment (NSEE) may contribute to an increased risk of type 2 diabetes (T2D). We examined whether the relationship between NSEE and T2D differs by sex and age in three study populations. Research design and methods: We conducted a harmonized analysis using data from three independent longitudinal study samples in the US: 1) the Veteran Administration Diabetes Risk (VADR) cohort, 2) the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort, and 3) a case-control study of Geisinger electronic health records in Pennsylvania. We measured NSEE with a z-score sum of six census tract indicators within strata of community type (higher density urban, lower density urban, suburban/small town, and rural). Community type-stratified models evaluated the likelihood of new diagnoses of T2D in each study sample using restricted cubic splines and quartiles of NSEE. Results: Across study samples, worse NSEE was associated with higher risk of T2D. We observed significant effect modification by sex and age, though evidence of effect modification varied by site and community type. Largely, stronger associations between worse NSEE and diabetes risk were found among women relative to men and among those less than age 45 in the VADR cohort. Similar modification by age group results were observed in the Geisinger sample in small town/suburban communities only and similar modification by sex was observed in REGARDS in lower density urban communities. Conclusions: The impact of NSEE on T2D risk may differ for males and females and by age group within different community types.

Assessing the association between food environment and dietary inflammation by community type: a cross-sectional REGARDS study.

BACKGROUND: Communities in the United States (US) exist on a continuum of urbanicity, which may inform how individuals interact with their food environment, and thus modify the relationship between food access and dietary behaviors. OBJECTIVE: This cross-sectional study aims to examine the modifying effect of community type in the association between the relative availability of food outlets and dietary inflammation across the US. METHODS: Using baseline data from the REasons for Geographic and Racial Differences in Stroke study (2003-2007), we calculated participants' dietary inflammation score (DIS). Higher DIS indicates greater pro-inflammatory exposure. We defined our exposures as the relative availability of supermarkets and fast-food restaurants (percentage of food outlet type out of all food stores or restaurants, respectively) using street-network buffers around the population-weighted centroid of each participant's census tract. We used 1-, 2-, 6-, and 10-mile (~ 2-, 3-, 10-, and 16 km) buffer sizes for higher density urban, lower density urban, suburban/small town, and rural community types, respectively. Using generalized estimating equations, we estimated the association between relative food outlet availability and DIS, controlling for individual and neighborhood socio-demographics and total food outlets. The percentage of supermarkets and fast-food restaurants were modeled together. RESULTS: Participants (n = 20,322) were distributed across all community types: higher density urban (16.7%), lower density urban (39.8%), suburban/small town (19.3%), and rural (24.2%). Across all community types, mean DIS was - 0.004 (SD = 2.5; min = - 14.2, max = 9.9). DIS was associated with relative availability of fast-food restaurants, but not supermarkets. Association between fast-food restaurants and DIS varied by community type (P for interaction = 0.02). Increases in the relative availability of fast-food restaurants were associated with higher DIS in suburban/small towns and lower density urban areas (p-values < 0.01); no significant associations were present in higher density urban or rural areas. CONCLUSIONS: The relative availability of fast-food restaurants was associated with higher DIS among participants residing in suburban/small town and lower density urban community types, suggesting that these communities might benefit most from interventions and policies that either promote restaurant diversity or expand healthier food options.

Initial diagnostic impressions of trainees during autism evaluations: High specificity but low sensitivity.

Reducing the age of first autism diagnosis facilitates access to critical early intervention services. A current "waitlist crisis" for autism diagnostic evaluation thus demands that we consider novel use of available clinical resources. Previous work has found that expert autism clinicians can identify autism in young children with high specificity after only a brief observation; rapid identification by non-experts remains untested. In the current study, 252 children ages 12-53 months presented for a comprehensive autism diagnostic evaluation. We found that junior clinicians in training to become autism specialists (n = 29) accurately determined whether or not a young child would be diagnosed with autism in the first five minutes of the clinic visit in 75% of cases. Specificity of brief observations was high (0.92), suggesting that brief observations may be an effective tool for triaging young children toward autism-specific interventions. In contrast, the lower negative predictive value (0.71) of brief observations, suggest that they should not be used to rule out autism. When trainees expressed more confidence in their initial impression, their impression was more likely to match the final diagnosis. These findings add to a body of literature showing that clinical observations of suspected autism should be taken seriously, but lack of clinician concern should not be used to rule out autism or overrule other indicators of likely autism, such as parent concern or a positive screening result.

Sex differences in early autism screening using the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up (M-CHAT-R/F).

LAY ABSTRACT: This study examined a widely used autism screening tool, the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up to identify differences in screening for autism between toddler males and females. Examining sex differences in screening for autism in toddlerhood is important as it determines who will be referred for evaluations and receive diagnoses, which is critical for access to autism-specific early intervention. This study found that females were less likely to screen positive and be invited for evaluations compared with males. Females at high likelihood for autism were less likely to be diagnosed with autism, which decreases confidence in the screener's results. Importantly, the Modified Checklist for Autism in Toddlers, Revised, with Follow-Up accurately identified both males and females with autism. Future research should examine ways to improve accuracy in screening results for females.

Categorizing community type for epidemiologic evaluation of community factors and chronic disease across the United States.

Existing classifications of community type do not differentiate urban cores from surrounding non-rural areas, an important distinction for analyses of community features and their impact on health. Inappropriately classified community types can introduce serious methodologic flaws in epidemiologic studies and invalid inferences from findings. To address this, we evaluate a modification of the United States Department of Agriculture's Rural Urban Commuting Area codes at the census tract, propose a four-level categorization of community type, and compare this with existing classifications for epidemiologic analyses. Compared to existing classifications, our method resulted in clearer geographic delineations of community types within urban areas.

Comparing Global and Spatial Composite Measures of Neighborhood Socioeconomic Status Across US Counties.

Area-level neighborhood socioeconomic status (NSES) is often measured without consideration of spatial autocorrelation and variation. In this paper, we compared a non-spatial NSES measure to a spatial NSES measure for counties in the USA using principal component analysis and geographically weighted principal component analysis (GWPCA), respectively. We assessed spatial variation in the loadings using a Monte Carlo randomization test. The results indicated that there was statistically significant variation (p = 0.004) in the loadings of the spatial index. The variability of the census variables explained by the spatial index ranged from 60 to 90%. We found that the first geographically weighted principal component explained the most variability in the census variables in counties in the Northeast and the West, and the least variability in counties in the Midwest. We also tested the two measures by assessing the associations with county-level diabetes prevalence using data from the CDC's US Diabetes Surveillance System. While associations of the two NSES measures with diabetes did not differ for this application, the descriptive results suggest that it might be important to consider a spatial index over a global index when constructing national county measures of NSES. The spatial approach may be useful in identifying what factors drive the socioeconomic status of a county and how they vary across counties. Furthermore, we offer suggestions on how a GWPCA-based NSES index may be replicated for smaller geographic scopes.

Neighborhood Socioeconomic Environment and Risk of Type 2 Diabetes: Associations and Mediation Through Food Environment Pathways in Three Independent Study Samples.

OBJECTIVE: We examined whether relative availability of fast-food restaurants and supermarkets mediates the association between worse neighborhood socioeconomic conditions and risk of developing type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: As part of the Diabetes Location, Environmental Attributes, and Disparities Network, three academic institutions used harmonized environmental data sources and analytic methods in three distinct study samples: 1) the Veterans Administration Diabetes Risk (VADR) cohort, a national administrative cohort of 4.1 million diabetes-free veterans developed using electronic health records (EHRs); 2) Reasons for Geographic and Racial Differences in Stroke (REGARDS), a longitudinal, epidemiologic cohort with Stroke Belt region oversampling (N = 11,208); and 3) Geisinger/Johns Hopkins University (G/JHU), an EHR-based, nested case-control study of 15,888 patients with new-onset T2D and of matched control participants in Pennsylvania. A census tract-level measure of neighborhood socioeconomic environment (NSEE) was developed as a community type-specific z-score sum. Baseline food-environment mediators included percentages of 1) fast-food restaurants and 2) food retail establishments that are supermarkets. Natural direct and indirect mediating effects were modeled; results were stratified across four community types: higher-density urban, lower-density urban, suburban/small town, and rural. RESULTS: Across studies, worse NSEE was associated with higher T2D risk. In VADR, relative availability of fast-food restaurants and supermarkets was positively and negatively associated with T2D, respectively, whereas associations in REGARDS and G/JHU geographies were mixed. Mediation results suggested that little to none of the NSEE-diabetes associations were mediated through food-environment pathways. CONCLUSIONS: Worse neighborhood socioeconomic conditions were associated with higher T2D risk, yet associations are likely not mediated through food-environment pathways.

Comparing competing geospatial measures to capture the relationship between the neighborhood food environment and diet.

PURPOSE: To examine how the choice of neighborhood food environment definition impacts the association with diet. METHODS: Using food frequency questionnaire data from the Reasons for Geographic and Racial Differences in Stroke study at baseline (2003-2007), we calculated participants' dietary inflammation score (DIS) (n = 20,331); higher scores indicate greater pro-inflammatory exposure. We characterized availability of supermarkets and fast food restaurants using several geospatial measures, including density (i.e., counts/km2) and relative measures (i.e., percentage of all food stores or restaurants); and various buffer distances, including administrative units (census tract) and empirically derived buffers ("classic" network, "sausage" network) tailored to community type (higher density urban, lower density urban, suburban/small town, rural). Using generalized estimating equations, we estimated the association between each geospatial measure and DIS, controlling for individual- and neighborhood-level sociodemographics. RESULTS: The choice of buffer-based measure did not change the direction or magnitude of associations with DIS. Effect estimates derived from administrative units were smaller than those derived from tailored empirically derived buffer measures. Substantively, a 10% increase in the percentage of fast food restaurants using a "classic" network buffer was associated with a 6.3 (SE = 1.17) point higher DIS (P< .001). The relationship between the percentage of supermarkets and DIS, however, was null. We observed high correlation coefficients between buffer-based density measures of supermarkets and fast food restaurants (r = 0.73-0.83), which made it difficult to estimate independent associations by food outlet type. CONCLUSIONS: Researchers should tailor buffer-based measures to community type in future studies, and carefully consider the theoretical and statistical implications for choosing relative (vs. absolute) measures.

The first five minutes: Initial impressions during autism spectrum disorder diagnostic evaluations in young children.

Diagnosticians report that autism spectrum disorder (ASD) is immediately apparent in some, but not all, children ultimately diagnosed. Clinicians' initial diagnostic impressions have implications for ASD early detection, yet the literature raises questions about their accuracy. This study explores diagnostic impressions of ASD specialists made within the first 5 minutes of meeting a young child and investigates factors associated with the match between initial impressions and final diagnoses. Participants were children (n = 294, aged 12-53 months) referred for an ASD evaluation as part of multi-site ASD screening studies. After 5 minutes observing each child, clinicians with expertise diagnosing ASD recorded if they thought the child would meet criteria for ASD following a complete evaluation, and recorded their confidence in this impression. Clinicians' initial impressions matched the final diagnosis in 81% of cases. Ninety-two percent of cases initially thought to have ASD met criteria following a full evaluation; however, 24% of cases initially thought not to have ASD also met criteria, suggesting a high miss rate. Clinicians were generally confident in their initial impressions, reporting highest confidence for children initially thought correctly not to have ASD. ASD behavioral presentation, but not demographic characteristics or developmental level, were associated with matching initial impression and final diagnosis, and confidence. Brief observations indicating ASD should trigger referral to intervention services, but are likely to under-detect positive cases and should not be used to rule out ASD, highlighting the need to incorporate information beyond initial clinical impression. LAY SUMMARY: When children come in for an autism evaluation, clinicians often form early impressions-before doing any formal testing-about whether the child has autism. We studied how often these early impressions match the final diagnosis, and found that clinicians could not easily rule out autism (many children who initially appeared not to have autism were ultimately diagnosed), but were generally accurate ruling in autism (when a child appeared to have autism within 5 minutes, they were almost always so diagnosed).

A Cross-Sectional Study of Depressive Symptoms and Risky Alcohol Use Behaviors Among HIV Primary Care Patients in New York City.

An association between problem drinking and depression among HIV-infected individuals has been previously demonstrated; however, which specific risky drinking behaviors are associated with higher levels of depression has not yet been investigated. Using an adult sample of HIV-infected primary care patients (78% male, 94% Black or Hispanic), we investigated whether depressive symptoms are associated with various risky drinking behaviors. Participants were administered the Beck Depression Inventory-II to assess depressive symptoms, and the Alcohol Use Disorders and Associated Disabilities Interview Schedule-IV to evaluate alcohol involvement. Participants with depressive symptoms (26%) were at higher risk for alcohol dependence [adjusted odds ratio (AOR) 3.8; 95% CI 2.0-7.2], regular binge drinking (AOR 2.0; 95% CI 1.1-3.8), and regular daytime drinking (AOR 2.1; 95% CI 1.2-3.8), in comparison with their non-depressed counterparts. Because both depression and unhealthy drinking negatively affect medication adherence and clinical outcomes, a better understanding of the association between depression and certain risky drinking behaviors among HIV-infected individuals is vital to improving their care and prognoses.