Neighborhood Disadvantage and Autism Spectrum Disorder in a Population With Health Insurance.

Importance: Family socioeconomic status has been associated with autism spectrum disorder (ASD) diagnoses. Less is known regarding the role of neighborhood disadvantage in the United States, particularly when children have similar access to health insurance. Objective: To evaluate the association between neighborhood disadvantage and the diagnosis of ASD and potential effect modification by maternal and child demographic characteristics. Design, Setting, and Participants: This cohort study examined a retrospective birth cohort from Kaiser Permanente Southern California (KPSC), an integrated health care system. Children born in 2001 to 2014 at KPSC were followed up through KPSC membership records. Electronic medical records were used to obtain an ASD diagnosis up to December 31, 2019, or the last follow-up. Data were analyzed from February 2022 to September 2023. Exposure: Socioeconomic disadvantage at the neighborhood level, an index derived from 7 US census tract characteristics using principal component analysis. Main Outcomes and Measures: Clinical ASD diagnosis based on electronic medical records. Associations between neighborhood disadvantage and ASD diagnosis were determined by hazard ratios (HRs) from Cox regression models adjusted for birth year, child sex, maternal age at delivery, parity, severe prepregnancy health conditions, maternal race and ethnicity, and maternal education. Effect modification by maternal race and ethnicity, maternal education, and child sex was assessed. Results: Among 318 372 mothers with singleton deliveries during the study period, 6357 children had ASD diagnoses during follow-up; their median age at diagnosis was 3.53 years (IQR, 2.57-5.34 years). Neighborhood disadvantage was associated with a higher likelihood of ASD diagnosis (HR, 1.07; 95% CI, 1.02-1.11, per IQR = 2.70 increase). Children of mothers from minoritized racial and ethnic groups (African American or Black, Asian or Pacific Islander, Hispanic or Latinx groups) had increased likelihood of ASD diagnosis compared with children of White mothers. There was an interaction between maternal race and ethnicity and neighborhood disadvantage (difference in log-likelihood = 21.88; P < .001 for interaction under χ24); neighborhood disadvantage was only associated with ASD among children of White mothers (HR, 1.17; 95% CI, 1.09-1.26, per IQR = 2.00 increase). Maternal education and child sex did not significantly modify the neighborhood-ASD association. Conclusions and Relevance: In this study, children residing in more disadvantaged neighborhoods at birth had higher likelihood of ASD diagnosis among a population with health insurance. Future research is warranted to investigate the mechanisms behind the neighborhood-related disparities in ASD diagnosis, alongside efforts to provide resources for early intervention and family support in communities with a higher likelihood of ASD.

Costs of coronary heart disease and mortality associated with near-roadway air pollution.

BACKGROUND: Emerging evidence indicates that the near-roadway air pollution (NRAP) mixture contributes to CHD, yet few studies have evaluated the associated costs. OBJECTIVE: We integrated an assessment of NRAP-attributable CHD in Southern California with new methods to value the associated mortality and hospitalizations. METHODS: Based on population-weighted residential exposure to NRAP (traffic density, proximity to a major roadway and elemental carbon), we estimated the inflation-adjusted value of NRAP-attributable mortality and costs of hospitalizations that occurred in 2008. We also estimated anticipated costs in 2035 based on projected changes in population and in NRAP exposure associated with California's plans to reduce greenhouse gas emissions. For comparison, we estimated the value of CHD mortality attributable to PM less than 2.5µm in diameter (PM2.5) in both 2008 and 2035. RESULTS: The value of CHD mortality attributable to NRAP in 2008 was between $3.8 and $11.5 billion, 23% (major roadway proximity) to 68% (traffic density) of the $16.8 billion attributable to regulated regional PM2.5. NRAP-attributable costs were projected to increase to $10.6 to $22 billion in 2035, depending on the NRAP metric. Cost of NRAP-attributable hospitalizations for CHD in 2008 was $48.6 million and was projected to increase to $51.4 million in 2035. CONCLUSIONS: We developed an economic framework that can be used to estimate the benefits of regulations to improve air quality. CHD attributable to NRAP has a large economic impact that is expected to increase by 2035, largely due to an aging population. PM2.5-attributable costs may underestimate total value of air pollution-attributable CHD.

High-resolution MODIS aerosol retrieval during wildfire events in California for use in exposure assessment.

Retrieval of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) using the Collection 5 (C005) algorithm provides large-scale (10 × 10 km) estimates that can be used to predict surface layer concentrations of particulate matter with aerodynamic diameter smaller than 2.5 µm (PM2.5). However, these large-scale estimates are not suitable for identifying intraurban variability of surface PM2.5 concentrations during wildfire events when individual plumes impact populated areas. We demonstrate a method for providing high-resolution (2.5 km) kernel-smoothed estimates of AOD over California during the 2008 northern California fires. The method uses high-resolution surface reflectance ratios of the 0.66 and 2.12 µm channels, a locally derived aerosol optical model characteristic of fresh wildfire plumes, and a relaxed cloud filter. Results show that the AOD derived for the 2008 northern California fires outperformed the standard product in matching observed aerosol optical thickness at three coastal Aerosol Robotic Network sites and routinely explained more than 50% of the variance in hourly surface PM2.5 concentrations observed during the wildfires.

Automobile traffic around the home and attained body mass index: a longitudinal cohort study of children aged 10-18 years.

OBJECTIVES: The objective of this study is to examine the relationship between measured traffic density near the homes of children and attained body mass index (BMI) over an eight-year follow up. METHODS: Children aged 9-10 years were enrolled across multiple communities in Southern California in 1993 and 1996 (n=3318). Children were followed until age 18 or high school graduation to collect longitudinal information, including annual height and weight measurements. Multilevel growth curve models were used to assess the association between BMI levels at age 18 and traffic around the home. RESULTS: For traffic within 150 m around the child's home, there were significant positive associations with attained BMI for both sexes at age 18. With the 300 m traffic buffer, associations for both male and female growth in BMI were positive, but significantly elevated only in females. These associations persisted even after controlling for numerous potential confounding variables. CONCLUSIONS: This analysis yields the first evidence of significant effects from traffic density on BMI levels at age 18 in a large cohort of children. Traffic is a pervasive exposure in most cities, and our results identify traffic as a major risk factor for the development of obesity in children.

Air pollution exposure assessment for epidemiologic studies of pregnant women and children: lessons learned from the Centers for Children's Environmental Health and Disease Prevention Research.

The National Children's Study is considering a wide spectrum of airborne pollutants that are hypothesized to potentially influence pregnancy outcomes, neurodevelopment, asthma, atopy, immune development, obesity, and pubertal development. In this article we summarize six applicable exposure assessment lessons learned from the Centers for Children's Environmental Health and Disease Prevention Research that may enhance the National Children's Study: a) Selecting individual study subjects with a wide range of pollution exposure profiles maximizes spatial-scale exposure contrasts for key pollutants of study interest. b) In studies with large sample sizes, long duration, and diverse outcomes and exposures, exposure assessment efforts should rely on modeling to provide estimates for the entire cohort, supported by subject-derived questionnaire data. c) Assessment of some exposures of interest requires individual measurements of exposures using snapshots of personal and microenvironmental exposures over short periods and/or in selected microenvironments. d) Understanding issues of spatial-temporal correlations of air pollutants, the surrogacy of specific pollutants for components of the complex mixture, and the exposure misclassification inherent in exposure estimates is critical in analysis and interpretation. e) "Usual" temporal, spatial, and physical patterns of activity can be used as modifiers of the exposure/outcome relationships. f) Biomarkers of exposure are useful for evaluation of specific exposures that have multiple routes of exposure. If these lessons are applied, the National Children's Study offers a unique opportunity to assess the adverse effects of air pollution on interrelated health outcomes during the critical early life period.